Beyond productivity- Effects of extreme weather events on ecosystem processes and biotic interactions

Beyond productivity: Effects of extreme weather events on ecosystem processes and biotic interactions Dissertation zur Erlangung des akademischen Grades Dr. rer. nat. vorgelegt der Fakultät für Biologie, Chemie und Geowissenschaften der Universität Bayreuth von Frau Julia Walter (M.A.) geboren am 01.09.1981 in Memmingen Die vorliegende Arbeit wurde unter der Betreuung von Prof. Anke Jentsch in der Zeit von Mai 2008 bis Februar 2011 am Helmholtz Zentrum für Umweltforschung-UFZ in Leipzig, und von Januar 2012 bis April 2012 am Lehrstuhl für Störungsökologie an der Universität Bayreuth angefertigt. Vollständiger Abdruck der von der Fakultät für Biologie, Chemie und Geowissenschaften der Universität Bayreuth genehmigten Dissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.). Dissertation eingereicht am: 11.04. 2012 Zulassung durch die Prüfungskommission: 11.09.2012 Wissenschaftliches Kolloquium: 25.10.2012 Amtierende Dekanin: Prof. Dr. Beate Lohnert Prüfungsausschuss: Prof. Anke Jentsch (Erstgutachterin) Prof. Christiane Werner Pinto (Zweitgutachterin) Prof. Michael Hauhs (Vorsitzender) Prof. Thomas Foken Prof. John Tenhunen Table of Contents 1. Short summary of the thesis/ Kurze Zusammenfassung der Doktorarbeit.......................................... 1 2. Background of the thesis..................................................................................................................... 6 2.1. Climate change and extreme weather events ............................................................................... 6 2.1.1. Temperature extremes .......................................................................................................... 8 2.1.2. Precipitation extremes .......................................................................................................... 8 2.2. Plant and ecosystem response towards extreme weather events................................................ 10 2.2.1. Morphological and physiological response of single plants to various climatic stress types . 11 Plant response to heat............................................................................................................... 11 Plant response to frost .............................................................................................................. 11 Plant response to drought......................................................................................................... 12 Plant response to heavy rainfall................................................................................................ 12 2.2.2. Impact of extreme weather events on plant communities and ecosystems......................... 13 Observational studies ............................................................................................................... 13 Experimental evidence on extreme weather events and plant communities ............................ 14 3. On this thesis..................................................................................................................................... 18 3.1. Objectives of this thesis ............................................................................................................. 18 3.2. Outline of manuscripts............................................................................................................... 19 3.3. Emerging research questions ..................................................................................................... 21 3.3.1. Resilience and stress memory............................................................................................. 21 3.3.2. Extreme weather events and ecosystem processes at multiple levels................................. 22 3.3.3. Climate change and land use .............................................................................................. 23 List of manuscripts and declaration of own contribution...................................................................... 24 Presentations of my work at conferences.............................................................................................. 28 Curriculum for the postgraduate school HIGRADE ............................................................................. 29 Acknowledgements............................................................................................................................... 30 References of the Introduction .............................................................................................................. 31 Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining .................. productivity.................................................................................................................... 37 Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance?....................................................................... 71 Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes......................................................................................................................... 90 Manuscript 4: Do plants remember drought? Hints towards a drought-memory in grasses............... 105 Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought ...................................................................................... 121 Manuscript 6: Increased rainfall variability reduces biomass and forage quality of temperate grassland largely independent of mowing frequency .................................................................. 145 Manuscript 7: Combined effects of multifactor climate change and land-use on decomposition in temperate grassland ..................................................................................................... 167 Synopsis .............................................................................................................................................. 191 Short summary of the thesis 1 1. Short summary of the thesis/ Kurze Zusammenfassung der Doktorarbeit Under global climate change, extreme weather events, such as heat waves, drought or heavy rain spells, are projected to increase in magnitude and frequency. As these may affect vegetation and ecosystems more than gradual shifts in mean climatic parameters, investigating the consequences of extreme weather events recently became an important issue in climate change research. The main focus of most experiments investigating effects of extreme weather events on vegetation is on primary productivity. In our experiment in artificially planted communities, even an extreme drought of 1000-year recurrence did not have effects on aboveor below-ground biomass production from 2005-2010 (manuscript 1). Thus, the main objectives of this thesis were (1) to investigate if extreme weather events have an effect on ecosystem functions1 beyond productivity, (2) to test if such a high resistance or resilience2 in response to drought regarding productivity also exists in more naturally grown plant communities and (3) to further elucidate possible mechanisms of the surprisingly large stability of the plant communities. To investigate these objectives, several experimental studies were conducted in artificially planted, as well as in naturally grown grassland communities and consequences of extreme weather events for ecosystem processes, such as decomposition and herbivory were investigated. In a pot experiment, it was studied, if grass plants react improved towards repeated drought when compared to a first drought and thus reveal a kind of drought memory. Such a memory might be one possible, but up until now widely neglected mechanism of resilience. Even though biomass production remained stable in our experiment in artificially planted communities (manuscript 1), biomass quality was severely affected by extreme drought, thereby strongly affecting the development of a herbivore caterpillar feeding on drought-exposed leaves (manuscript 2). Further, plant compounds of the host plant depended on the composition of the plant community it was grown in. This in turn resulted in strong effects on the larval mortality of herbivores feeding on such plants. In contrast to the study in artificially planted communities (manuscript 1), aboveground net primary productivity (ANPP) was reduced in naturally composed grassland in response to extreme rainfall variability, including an extreme drought followed by heavy 1 Ecosystem functions: Processes that involve more than one ecosystem or trophic level and are important for the maintenance of the whole ecosystem (e.g. decomposition, which is important for nutrient turnover, or providing food of good quality to sustain food webs) 2 Resilience is understood here as the time required to return to a steady-state following disturbance (Holling (1973); Gunderson (2000)) Short summary of the thesis 2 rainfall (manuscript 6). Forage quality was altered by drought. Furthermore, mowing frequency strongly altered forage quality and biomass production, but did not interact with rainfall variability and thus did neither buffer, nor amplify effects of extreme rainfall variability. Despite effects of rainfall variability on ANPP, grassland showed high resilience after drought followed by heavy rain, as effects were large shortly after the extreme event, but did not persist until a second harvest later in the year. In natural grassland, rainfall variability and drought also affected ecosystem processes, here litter decomposition, beyond productivity (manuscript 7). Drought followed by heavy rain pulses decreased decomposition rates. Decomposition in more frequently mown meadows was more vulnerable towards drought exposure. Winter warming and additional winter rain had no long-term effect on decomposition. To conclude, projected increases in drought frequency under climate change may inhibit decomposition and alter nutrient and carbon cycling along with soil quality in temperate grassland, whereas a reduction of snow cover leading to more variable soil surface temperatures may counteract increased decomposition under winter warming. In this thesis, an ecological stress memory as one possible mechanism of resilience is defined as any response of a single plant after a stress experience that improves the reaction of the plant towards future stress experience and which is assessed on a whole plant level (manuscript 3). This thesis further provides evidence of a drought memory in grass plants (manuscript 4): Plants repeatedly subjected to drought showed improved photo-protection and a higher rate of living biomass when compared to plants faced with their first drought. Similarly, tree seedlings exposed to drought in summer revealed higher frost resistance during winter, providing evidence of a long-lasting “cross-stress-memory” (manuscript 5). To sum up, the thesis shows that extreme weather events, even though neither severely affecting biomass production in artificially composed, nor in naturally growing communities in the long-term, exert strong influence on physiological or biogeochemical parameters, such as plant compounds or soil biotic activity. These changes in turn modify ecosystem functions beyond productivity, for example herbivory or decomposition, possibly altering biotic interations and nutrient cycling. Furthermore, the findings imply that plants exhibit a stress memory after stress exposure, which may be one mechanisms leading to a high stability and resilience upon frequent stress. Kurze Zusammenfassung der Doktorarbeit 3 Kurze Zusammenfassung der Doktorarbeit Im Zuge des globalen Klimawandels werden extreme Wetterereignisse, wie Hitzewellen, Dürren oder Starkregenereignisse sehr wahrscheinlich häufiger und auch intensiver werden. Da diese Vegetation und Ökosysteme stärker beeinflussen können als graduelle Änderungen in klimatischen Durchschnittsparametern, ist die Untersuchung der Konsequenzen extremer Wetterereignisse in letzter Zeit verstärkt in den Fokus der Klimawandelforschung getreten. Das Hauptaugenmerk der meisten Experimente, die Folgen extremer Wetterereignisse für die Vegetation untersuchen, liegt auf der Primärproduktivität. Innerhalb unseres Experiments in künstlich zusammengesetzten Gemeinschaften wurde die oberund unterirdische Biomasseproduktion durch eine extreme Dürre nicht beeinflusst (Manuskript 1). Daher sind die Ziele dieser Arbeit, zu untersuchen, (1) ob extreme Wetterereignisse einen Effekt auf Ökosystemfunktionen1, außer der reinen quantitativen Produktion von Biomasse haben, (2) ob die Ergebnisse der hohen Stabilität in den künstlich zusammengesetzten Artengemeinschaften auch für die natürlich gewachsenen Gründlandbeständen gelten und (3) mögliche Mechanismen der erstaunlichen Stabilität der Pflanzengemeinschaften näher zu beleuchten. Dafür wurden mehrere Experimente in künstlichen und natürlichen Pflanzengemeinschaften durchgeführt, in denen Folgen extremer Wetterereignisse für Ökosystemprozesse, wie z. B. Streuabbau oder Herbivorie, untersucht wurden. In einem Topfexperiment wurde außerdem untersucht, ob Graspflanzen besser mit einer wiederholten Dürre im Vergleich zu einer ersten Dürre umgehen können, und damit eine Art Dürregedächtnis aufweisen. Ein solches Gedächtnis könnte ein möglicher, aber bisher wenig erforschter Mechanismus von Resilienz2 sein. Obwohl die Biomasseproduktion künstlich zusammengesetzter Gemeinschaften stabil blieb (Manuskript 1), änderte sich die Biomassequalität stark durch extreme Dürre. Dadurch veränderte sich die Entwicklung einer phytophagen Raupe, wenn sie Blätter fraß, die einer Dürre ausgesetzt worden waren (Manuskript 2). Außerdem beeinflusste die Artenzusammensetzung der Gemeinschaft, in der die Futterpflanze wuchs, die Pflanzeninhaltsstoffe, was die Sterberate der Larven veränderte. 1 Prozesse, die mehr als eine Ökosystemebene betreffen und die für die Aufrechterhaltung des gesamten Systems notwendig sind 2 Benötigte Zeit, um nach einer Störung wieder einen stabilen Zustand zu erreichen (Holling (1973); Gunderson (2000)) Kurze Zusammenfassung der Doktorarbeit 4 Im Gegensatz zur Studie in künstlich zusammengesetzten Gemeinschaften (Manuskript 1) wurde die oberirdische Nettoprimärproduktion (NPP) durch den Einfluss von extremer Niederschlagsvariabilität, also extremer Dürre gefolgt von starkem Regen, reduziert (Manuskript 6). Auch die Futterqualität wurde durch die Dürre modifiziert. Des Weiteren beeinflusste die Mahdfrequenz Futterqualität und Biomasseproduktion. Allerdings konnte die Mahdfrequenz die Effekte der extremen Niederschlagsvariabilität weder abpuffern, noch verstärken; es gab keine Interaktion zwischen den beiden Faktoren. Trotz der Effekte der Niederschlagsvariabilität auf die NPP zeigte sich wieder eine hohe Resilienz von Grünland nach Dürre und Starkregen, da die negativen Effekte direkt nach dem extremen Wetterereignis sehr stark waren, aber nicht bis zur zweiten Ernte Ende des Jahres anhielten. Auch im natürlichen Grünland wurden Ökosystemprozesse, hier Streuabbau, neben der Produktivität beeinflusst: Dürre, gefolgt von Starkregen, verringerte Streuabbauraten. Streuabbau in öfter gemähten Wiesen wurde durch die Dürre stärker beeinträchtigt. Wintererwärmung und zusätzlich applizierter Winterniederschlag hatten keine langfristigen Effekte auf den Abbau. Zusammenfassend lässt sich sagen, dass die vorhergesagte Zunahme von Dürren den Streuabbau behindern und dadurch in Nährstoffund Kohlenstoffkreislauf eingreifen könnte. Das Tauen der Schneedecke bei Wintererwärmung führte zu einer erhöhten Variabilität der Bodenoberflächentemperatur und könnte damit erhöhten Abbauraten durch Wintererwärmung entgegen wirken. Die vorliegende Arbeit definiert ökologisches Stressgedächtnis als die Stressantwort einer Einzelpflanze, die die Reaktion dieser gegenüber wiederholtem Stress verbessert. Ein solches Stressgedächtnis könnte ein möglicher Mechanismus von Resilienz sein (Manuskript 3). Die Arbeit zeigt erste Hinweise auf ein Dürregedächtnis bei Grasspflanzen. Pflanzen, die wiederholter Dürre ausgesetzt waren wiesen einen besseren Schutz vor oxidativem Stress und dadurch mehr lebende Biomasse auf als Pflanzen, die das erste Mal einer Dürre ausgesetzt wurden. Auch waren Baumkeimlinge, die im Sommer eine Dürre erfuhren, im Winter frostresistenter, was auf ein „Cross-Stressgedächtnis“ hinweist (Manuskript 5). So zeigt diese Arbeit, dass extreme Wetterereignisse, selbst wenn sie die Biomasseproduktion nicht stark oder langfristig beeinflussen, physiologische oder biogeochemische Parameter, wie z. B. Pflanzeninhaltsstoffe oder die Aktivität der Bodenfauna, verändern. Diese Änderungen modifizieren wiederum Ökosystemfunktionen, wie Herbivorie oder Streuabbau, wodurch möglicherweise langfristig in biotische Interaktionen oder Stoffkreisläufe eingegriffen wird. Weiterhin legt diese Arbeit nahe, dass Kurze Zusammenfassung der Doktorarbeit 5 Pflanzen, nachdem sie Stress ausgesetzt waren, ein Stressgedächtnis entwickeln können, das zu erhöhter Stabilität und Resilienz unter häufigen Stressereignissen führt. Background of the thesis 6 2. Background of the thesis 2.1. Climate change and extreme weather events Instrumental temperature records show that a warming of the climate system over the last century is unequivocal (Hulme, 2005; Blenkinsop and Fowler, 2007; Trenberth et al., 2007). The global mean surface temperatures have risen by 0.74 ° C (±0.18 ° C) on average from 1905-2006 (Hulme, 2005; Blenkinsop and Fowler, 2007; Trenberth et al., 2007). Warming was most pronounced over land regions, especially over the northern hemisphere during winter and spring (Trenberth et al., 2007). In Germany temperatures have risen by 1° C from 1901-2000, with a more pronounced warming during winter (Schönwiese et al., 2005; Zebisch et al., 2012). Other temperature indices, such as the global sea level rise of around 17 cm in the last century, the reduction of snow cover in the northern hemisphere or the widespread glacier retreat are consistent with the record showing rising temperatures (Trenberth et al., 2007). Furthermore, global warming is accelerating quickly: the warming rate of 0.13° C per decade from 1955-2005 is almost double the warming rate of 0.07 ° C per decade for 1906-2005 (Beierkuhnlein and Foken, 2008; Trenberth et al., 2007). It is now widely acknowledged, that anthropogenic green house gas emissions account for the largest part of observed warming since preindustrial times and that the observed warming can not be explained by internal forcing or natural external radiative forcing only (Hegerl et al., 2007; Trenberth et al., 2007). Future projections indicate a further warming of between 1.1° C and 6.4 ° C until 2100, depending on the emission scenario used in the model. Even if CO2 emissions were held constant on the level of the year 2000 (which is already not fulfilled), temperatures continued to rise for at least the first third of the 21st century (Meehl et al., 2007). Along with rising temperatures, other components of the climate system, for example precipitation, are observed and projected to change. Modifications in the magnitude, as well as in the frequency and duration of extreme weather events are of increasing concern: Such changes may occur both through changes in the mean or in the variability of the distribution of a climate variable, causing disproportionally large changes in the frequency or intensity of weather extremes, compared with the changes in the mean (Meehl et al., 2000b; Nicholls and Alexander, 2007) (Fig. 1). Extreme weather events are more and more responsible for a large part of climate related damage to society and ecosystems (Field et al., 2012). Background of the thesis 13 oxygen, for example by developing air roots. Plants not adapted to flooding can sometimes acclimate by histological modifications, like aerenchymes. Otherwise, they experience hypoxia or even anoxia. This causes fermentation instead of respiration in the root cells, which restricts growth by a fast depletion of stored carbohydrates. Lactate and ethanol accumulate and might cause cell damage by increasing acidity. After re-aeration plants might suffer oxidative damage by formation of ROS (Schulze et al., 2005; Lambers et al., 2008). Often mykorrhiza are damaged in hypoxic soils, which impairs the plants nutrient supply. 2.2.2. Impact of extreme weather events on plant communities and ecosystems Observational studies Besides physiological and morphological alterations in single plants, climatic variables affect species distribution and ranges, phenological life cycle events, community composition and species interactions (Hughes, 2000; Visser and Holleman, 2001; Walther et al., 2002). Many observational studies document the effect of the gradual warming on vegetation: Polewards or upwards range shifts in response to warming have been observed for various species, e.g. an upward shift of the treeline and of alpine plants in Europe in the last decades (Hughes, 2000; Walther et al., 2002; Parmesan and Yohe, 2003; Thuiller, 2007). The rising temperatures also led to phenological shifts in many plant species, for instance to an earlier onset of bud burst or flowering (Walther et al., 2002). Warmer conditions often match the needs of invasive plants, that can possibly establish more rapidly and more widespread under new conditions. An increase of thermophilic invasive species has been documented in several ecosystems (Walther et al., 2002). Climate change may also lead to species extinctions, with species in mountain habitats or the Mediterranean especially endangered (McCarty, 2001; Thomas et al., 2004; Thuiller et al., 2005; Schröter et al., 2005). Compared to observations of the effects of gradual warming for plant communities, populations and species distribution, observational studies investigating the consequences of extreme weather events are rare, as the occurrence of extreme climatic events is also rare (Meehl et al., 2000a; Gutschick and BassiriRad, 2003; Jentsch et al., 2007). Rapid catastrophic shifts in community composition often follow disturbances caused by extreme climatic events (e.g. storms)(Scheffer et al., 2001). Even less dramatic events may cause changes in species competitive and facilitative interactions (Bertness and Callaway, 1994; Jentsch et al., 2007). For instance, competition intensifies in plant-plant interactions under extreme drought (Tielborger and Kadmon, 2000; Ludwig et al., 2004; Maestre and Cortina, 2004). Thus, naturally occurring droughts cause long-lasting shifts in plant community Background of the thesis 14 composition (Allen and Breshears, 1998; Breshears et al., 2005; Mueller et al., 2005). Drought further reduces forest resilience and productivity and is projected to increase tree mortality (Thompson et al., 2009; Lloret et al., 2004; Noormets et al., 2008; Allen et al., 2010). Many tree-species in the Mediterranean are projected to decrease their distribution due to more severe droughts (Schröter et al., 2005). In mesic grassland, however, increased precipitation variability, leading to longer dry periods followed by more extreme rainfall events, promoted plant coexistence and thus stabilized diversity (Adler et al., 2006). The extreme summer heat waves in Centraland Western Europe in 2003 and in Eastern Europe in 2010, accompanied by severe drought, caused crop failure and Europewide reductions in primary productivity (Ciais et al., 2005; Barriopedro et al., 2011). Warm spells during winter have also been observed to cause damage, as they may lead to a loss of frost acclimation and thus increased damage upon recurring frost. A winter “heat wave” in 2007 in northern Scandinavia, accompanied by thawing, led to extensive damage of the dominant dwarf-shrubs (Bokhorst et al., 2009). Strimbeck et al. (1995) found that a natural thaw during midwinter caused dehardening of montane red spruce. As global warming advances the beginning of the growing season, increasing damage caused by late frost events has been observed (Gu et al., 2008). Experimental evidence on extreme weather events and plant communities As observational evidence on the impacts of extreme weather events is limited, several controlled field-experiments assessed effects of extreme climatic events on natural or artificially composed vegetation. The advantages of well-conducted experiments5 are the possibility to incorporate control treatments and to minimize the influence of confounding factors. However, as such a reductionist approach implies rather artificial conditions rarely found in reality, the transfer of experimental evidence on complex, natural systems might be limited. In the beginning of experimental climate change research (1990s), studies testing effects of extreme weather events on plant communities were scarce (Jentsch et al., 2007; manuscript 1) and the majority of the experiments implemented changes in weather trends, such as warming or increased CO2. Until 2006, research investigating the effects of extreme events accounted for only one fifth of the experimental climate change studies published 5 Well-conducted experiments should include proper control treatments varying only the factor studied, should work with enough replicates to ensure statistical power and should randomly assign treatments and replicates. Further, treatment artifacts and biases caused by the experiment conductors have to be avoided (Hurlbert, 1984) Background of the thesis 15 (Jentsch et al., 2007). Most experiments assessed aboveground productivity as main response parameter and investigated effects of drought (manuscript 1). Precipitation manipulations: Experimentally applied drought decreased grassland productivity in some studies (Morecroft et al., 2004; van Ruijven and Berendse, 2010; de Boeck et al., 2011). However, productivity was often only affected in response to drought in arid habitats (Gilgen and Buchmann, 2009; Miranda et al., 2009) or in generally dry years (Bloor et al., 2010). The VULCAN experiments assessing data at shrubland sites across Europe, also found a trend to reduced biomass production after drought only at the drier sites (Penuelas et al., 2004; Penuelas et al., 2007). In mesic grassland, drought often had no long-term effects on productivity (Naudtsa et al., 2011), which was also found for the EVENT I experiment (manuscript 1). Despite often not having large effects on productivity, drought alters belowground processes, e.g. by reducing soil respiration (EVENT I and CLIMOOR experiment: Emmett et al., 2004; Kreyling et al., 2008; Sowerby et al., 2008; Toberman et al., 2008; manuscript 1). Several studies did not test the direct effects of drought, but the effects of increased rainfall variability (fewer, but larger events, including long dry intervals and heavy rain spells) on grassland parameters. Some studies showed a larger effect of mean annual precipitation on productivity (Barrett et al., 2002; Chou et al., 2008), while others found rainfall variability to be a more important driver for ANPP (Knapp et al., 2002; Fay et al., 2003). In the Rain Manipulation Plots (RaMPs) experiment at Konza Prairie Biological Station in Kansas, USA, a reduction in soil respiration, plant CO2 uptake (Harper et al., 2005) soil water content (Fay et al., 2003) and productivity (Fay et al., 2003; Knapp et al., 2002) and an increase in soil nitrogen availability and in plant diversity (Knapp et al., 2002) was found in temperate continental grassland under increased rainfall variability (larger but fewer rainfall events with a constant overall rainfall amount (Heisler and Weltzin, 2006). HeislerWhite et al. (2008, 2009) found a decrease in productivity at the temperate part of a transect and an increase in the semi-arid end under fewer, but larger rainfall events. In a Californian grassland, changes in precipitation patterns caused changes in trophic interactions, e.g. a reduction in consumer abundance on a longer time scale that overrode direct, autecological short-term effects (Suttle et al., 2007). The drought studies not applying compensating rain pulses show that arid systems or mesic systems in dry years are more vulnerable towards drought. Thus, a sufficient overall rainfall amount seems to be important for grassland recovery, which was also found in our Background of the thesis 16 study within the EVENT II experiment (manuscript 6). The impact of drought in arid ecosystems seems to depend largely on overall rainfall amount or the occurrence of several larger rain pulses. Experiments testing effects of heavy rainfall events on vegetation are rare. In the EVENT I experiment heavy rainfall events had only minor effects on productivity (Kreyling et al., 2008). Temperature manipulations: Experiments applying not only gradual warming, but extreme heat pulses, are scarce. Arnone et al. (2011) found only short-termed effects of an experimental heat wave on the productivity of the dominant grass species in tallgrass-prairie of Oklahoma, but no changes in most of the studied species. In cold biomes plants performed better during a warming pulse, but worse afterwards, possibly due to a loss of cold resistance and subsequent higher stress levels under the recurring cold (Marchand et al., 2005; Marchand et al., 2006; Bokhorst et al., 2009), whereas fresh litter decomposition was unaffected by warming pulses (Bokhorst et al., 2010). In the EVENT I experiment, repeated soil freeze-thaw cycles caused an increase in productivity of temperate grassland (Kreyling et al., 2010). However, lagged stress effects in heath communities diminished biomass two vegetation periods after applying warming pulses (Kreyling et al., 2010). Combined manipulations of multiple climatic variables: Few experiments apply multiple, combined climatic stressors on vegetation: The CLIMAITE project (Mikkelsen et al., 2008) applying elevated CO2, drought and warming as single factors and in combination on shrubland systems in Denmark found mostly smaller responses of nutrient cycling to the combined treatments than to the single treatments. Nevertheless, the future climate scenario combining all factors led to reduced N turnover (Larsen et al., 2011). Grime et al. (2008) found a large long-term resistance of infertile, established grassland in response to warming, droughts and water additions over 13 years. A mesocosm experiment including herbaceous species in Belgium also applied heat waves and drought as single and combined factors (de Boeck et al., 2011; van Peer et al., 2004). They found that negative effects of drought on CO2 exchange, growth, survival and biomass production were exacerbated by heat waves, whereas heat waves alone had no effect, due to transpirative cooling. The summarized results demonstrate that intensifying droughts might reduce productivity and also agricultural yield, especially under already dry conditions, with smaller Background of the thesis 17 to no effects in mesic grassland. Furthermore, some studies show that extreme events alter net carbon balance and soil processes, thereby altering nutritional pathways and soil quality. There is an urgent need to further combine multiple climatic stressors, as effects of such multifactor experiments might point in totally different directions as expected out of the response towards single factors (Mikkelsen et al., 2008). Studies investigating parameters other than productivity and soil respiration are needed to elucidate effects on biotic interactions and ecosystem processes on multiple levels. On this thesis 18 3. On this thesis 3.1. Objectives of this thesis The prevailing response parameter of most experiments investigating effects of extreme weather events on vegetation is primary productivity. In the EVENT I experiment, in which statistically extreme weather events were applied on artificially planted communities of varying speciesand functional diversity, the extreme weather events did surprisingly not cause large and detrimental changes in grassland productivity (Kreyling et al., 2010). The applied treatments could consequently not be called “extreme climatic events” sensu Smith (Smith, 2011a), as, although being extreme in their magnitude and length relative to the reference period, they did not cause an extreme response of plant communities, such as widespread species mortality or community breakdown. However, although not severely affecting productivity, the weather treatments caused more subtle changes on a physiological and biogeochemical level that are summarized in manuscript 1. Slight changes, for example in plant metabolic compounds can affect multiple ecosystem processes and levels, for instance by decreasing palatability for herbivores or by changing decomposition rates, which in turn alters trophic interactions and nutrient cycling. Thus, one objective of this thesis was to elucidate how extreme weather events affect ecosystem functions beyond productivity, such as plant-herbivore interactions or decomposition. Especially mesic grassland communities are often very stable when faced with extreme drought (see section 2.2.2.), which was also shown in the EVENT I experiment. Yet, the underlying mechanisms of such a high stability are not well understood. Another objective of this thesis is to further elucidate possible mechanisms of the surprisingly large resistance or resilience of plants and plant communities when faced with extreme weather events. Here, the focus is on a possible stress memory, as up until now it is unclear, how plants and plant communities react when stress is applied repeatedly over a relatively short time span. On the one hand, this might lead to a step-wise reduction in the ability to recover, until a total breakdown of the system (Scheffer et al., 2001). On the other hand, stress acclimation may lead to a persisting increase in stress resistance, a mechanisms that could be regarded as kind of stress memory. The consideration of not only an increased event magnitude, but also of an increased frequency of events is urgently needed in studying climatic extremes (Smith, 2011b). On this thesis 19 The EVENT I experiment is highly controlled in terms of species composition, as the planted community compositions were kept constant over the years by periodically weeding. To investigate if the findings of high stability in the artificially composed plant communities can be conferred to more natural systems, the EVENT II experiment was established on a semi-natural meadow in 2008. Here, not only rainfall was manipulated, but also different land-use scenarios were implemented. This experiment was also designed to answer the question whether the effects of drought or heavy rain are caused by an overall alteration in mean annual rainfall amount, or by increased rainfall variability (larger, but fewer rainfall events) under constant annual rainfall amount. For this reason, in EVENT II rainfall amount was kept constant from 2009 onwards and only the size of and the intervals between the rainfall events were varied. To sum up, the main objectives of this thesis were (1) to investigate if extreme weather events have an effect on ecosystem functions beyond productivity, (2) to test if the high stability or resilience in response to drought regarding productivity also exists in more naturally grown plant communities and (3) to further elucidate possible mechanisms of the surprisingly large resistance or resilience of the plant communities. 3.2. Outline of manuscripts The first manuscript summarizes 5 years of drought research in the artificially planted grassland communities of EVENT I. Extreme drought had no effect on abovegroundor belowground productivity. Nevertheless, several other physiological and biogeochemical parameters were affected. If physiological changes on a leaf level influence other ecosystem levels and processes in the long-term had thus to be investigated. The second manuscript therefore deals with changes in leaf compounds caused by extreme drought and resulting effects on herbivores feeding on such leaves. A second focus of this study was to elucidate effects of plant community composition on leaf compounds and, as a consequence, herbivore development. The study showed that changes in grass compounds caused by severe drought affected herbivores feeding on such grass: Caterpillars fed with drought-subjected leaves showed significantly higher survival, a longer duration of larval development and higher pupal weight. Further, plant compounds of our target grass depended on the composition of the plant community it was grown in, which in turn affected herbivore development: Larvae feeding on species-richest communities without legumes showed the highest mortality, which was closely linked to low protein content in these leaves. This study provides evidence that even quite subtle changes in plants caused by drought or community composition are able to influence biotic interactions and may even lead to desynchronisation On this thesis 20 of trophic and phenological adjustments under climate change. Furthermore, as climate change is likely to affect plant community composition, this will further affect leaf quality and thus plant-herbivore interactions. The second objective of this thesis was to elucidate possible mechanisms of the high stability of grassland productivity under climatic extremes. In the first three years of the EVENT I experiment, a drought of 100-year recurrence was applied (leading to 32 days of consecutive drought), and in the next years, a drought of 1000 year recurrence was applied. In every year, the same plots were subjected to drought. One possible mechanisms of resilience might be that the communities built up an ecological memory that helped them to cope with drought in the following years. As ecological memory on a community level is difficult to assess, we focused on an ecological stress memory on a single plant level. Surprisingly few studies investigated if whole plants are able to remember stress and to react improved towards a recurrent stress event. This issue is especially important as frequency of extreme weather events is projected to increase under climate change (Smith, 2011b). Further, a common definition of stress memory for ecologists is missing. The third manuscript thus first defines the concept of an ecological stress memory on a whole plant level, reviews the few existing studies indicating stress memory after climatic stress (drought, frost, heat) and discusses possible mechanisms of an ecological stress memory, including epigenetic ones. A drought memory in grass plants was investigated within a pot-experiment in which one group of plants was subjected to a single drought and the other to recurrent drought (manuscript 4). This study provided evidence that grass plants are able to remember drought even after a harvest and resprouting and to show a higher percentage of living biomass, due to improved photoprotection, when compared to plants subjected to their first drought. Similarly, the experiment pertaining to manuscript 5 tested frost hardiness of Pinus nigra juveniles and showed that plants exposed to drought during summer revealed higher frost hardiness in winter (manuscript 5). As both, frost and drought stress, involve dehydration stress, it might well be that an ecological cross-stress memory was involved here. Plant frost hardiness in this study was related to a higher concentration of carbohydrates. Content of carbohydrates is also often increased under drought (e.g. manuscript 2). Thus, the cross-stress memory indicated in manuscript 5 might be related to the faster synthesis of soluble carbohydrates. To test if the findings of the artificially composed plant communities also hold under more realistic conditions, an extreme drought was also applied on naturally grown grassland communities in the EVENT II experiment. Here, effects of increased rainfall variability (changes in timing and distribution of rainfall, but not in overall rainfall sum) on the On this thesis 21 productivity and some aspects of forage quality of established grassland were investigated. In contrast to the findings in artificially planted communities (manuscript 1), ANPP and forage quality were reduced in naturally composed grassland in response to extreme drought followed by heavy rainfall events (manuscript 6). Mowing frequency strongly altered forage quality and biomass production, but did did neither buffer, nor amplify effects of extreme rainfall variability on productiviy, as it did not interact with rainfall variability manipulations. Despite effects of rainfall variability on ANPP, grassland showed high resilience after extreme spring drought followed by heavy irrigation, as effects were large shortly after the extreme event, but did not persist until a second harvest later in the year, when no differences between the rainfall variability manipulations appeared. In the preceding year, when the extreme spring drought was not followed by irrigations and thus also received the smallest overall amount of water, negative effects on productivity were larger and remained until the second harvest in late summer. Then, formerly drought exposed communities still showed reduced biomass production. This highlights the important role of a sufficient overall amount of rainfall for recovery processes in temperate grassland and is in accordance with the drought studies mentioned in section 2.2.2., showing severely adverse effects of drought primarily in dry years or in arid biomes. As this thesis investigates effects of extreme weather events on ecosystems beyond productivity, manuscript 7 reports findings of a long-term decomposition experiment conducted within EVENT II. Extreme drought reduced litter decomposition when litter bags were exposed to drought for six weeks within an 11 month period. Surprisingly, low rainfall variability with regular irrigation decreased decomposition. Additional winter rain accelerated decomposition, whereas winter warming had no effect on decomposition, but reduced snow cover and increased variability of surface temperatures. More frequent mowing strongly stimulated decomposition, which could be attributed to changes in litter quality. However, the stimulating effect of frequent mowing was absent under extreme rainfall variability including drought. Projected increases in drought frequency under climate change may inhibit decomposition and alter nutrient and carbon cycling along with soil quality. Especially decomposition in intensively managed grassland appears vulnerable towards drought. 3.3. Emerging research questions 3.3.1. Resilience and stress memory Often, and also in our study (manuscript 1) grassland shows a surprisingly large resistance or resilience towards drought. Mechanisms of resilience remain to be elucidated. On this thesis 22 One likely mechanism is a stress memory of plants that renders them less vulnerable to repeated stress events (manuscripts 3, 4, 5). However, if such a mechanisms exists also under natural conditions and also on larger scales, e.g. on a community level, is yet to be investigated, especially as findings of manuscript 6 imply that grassland resilience under more natural conditions might be diminished under generally dry conditions. Possible mechanisms of a stress memory are largely unknown. Joint research of ecologists and molecular biologist is needed to elucidate possible epigenetic mechanisms. First studies already showed the heritability of acquired stress tolerance (see manuscript 3). Besides ecological stress memory, other underlying physiological and biogeochemical processes that serve to maintain productivity and might thus be mechanisms of community stability and recovery have to be identified and addressed in future research. Maintaining ecosystem resilience is of major importance to mitigate and prevent catastrophic consequences of global climate change. 3.3.2. Extreme weather events and ecosystem processes at multiple levels Up until now, the main response parameter studied in research on extreme climatic events is primary production (manuscript 1). However, even if primary production remains stable, other physiological and biogeochemical parameters are changed under extreme weather events (manuscripts 1, 2, 7). Such changes, e.g. food plant quality might seriously interfere in ecosystem synchronisation and ecosystem functioning. Further work to study long-term effects of extreme weather events on, e.g. biotic interactions or biodiversity is needed to estimate consequences of weather extremes and to enable policy makers to prevent destabilization of established food-webs and to seize measures for adaptation. How herbivores might react to changes in their host plant in more natural conditions than the ones described in manuscript 2 and whether specialists might react differently compared to generalist herbivores also needs further research. We showed that winter warming did not increase decomposition, due to loss of snow insulation and increased surface temperature variability. How decomposition might be affected by summer warming, also in combination with drought conditions, needs further study. Long-term changes in soil biotic activity under more frequent mowing needs to be addressed, to find explanations for the higher vulnerability of decomposition towards drought in more frequently mown communities. Preliminary results of the EVENT experiments also indicate strong effects of heavy rainfall on biotic interactions, such as mycorrhiza or decomposer fauna. As heavy rain events are expected to increase in the future, but are rarely studies yet, more investigations are needed to look at effects of heavy rain on ecosystem functions. Curriculum for postgraduate school 29 Curriculum and credit points for the postgraduate school HIGRADE and award course name duration own contribution credit points Introduction to water resources and aquatic ecosystem management 3 days active participation and homework 1 Introduction into biodiversity sciences 2 days active participation 1 Advanced course terrestrial ecosystem functions and biodiversity 3 days active participation 2 Advanced course proteomics 5 days lab work and analysis 2 Seminar on land-use conflicts and conservation of natural resources 1 day presentation and active participation 1 Application course “Land-use conflicts and conservation of natural resources in the Banaue region of Nothern-Luzon/ Philippines 12 days conduction of field experiment and writing of final report 3 Soft Skills: Presentations in Englisch 2 days active participation including short presentations 1 Soft Skills: Scientific Writing 3 days active participiation including writing of short sections 1 Soft Skills: Grant Aquisition 1 day participation 0.25 Four talks at international conferences preparation and presentation of talks 2 Four presentations in the UFZ reparatio seminar and one poster presentation at the UFZ Topic I conference preparation and presentation of talks 1.5 Organisation of UFZ doc days 2009 several days planning of location, activities, talks, schedule 0.75 Statistics: Data Analysis and Modelling using R 6 days active participation 1.25 Publication of articles in ISI-listed journals preparation of manuscripts, first and corresponding author 2 Participation at the competition “Wissenschaft Verstehen” and AWARD for the 3rd place Finals were held one day reparation of article and 15 minute presentation 1 20.75 Acknowledgements 30 Acknowledgements: I thank - Prof. Anke Jentsch for giving me the opportunity to do my phD within her group, for giving me space to develop own interests and ideas, for providing a working atmosphere that makes hard work easier, for giving me the chance to present my work at conferences and for being the family-friendliest supervisor - my second supervisor, Dr. Harald Auge, for many fruitful discussions and ideas for my research - the department of Conservation Biology at the Helmholtz-Centre for Environmental Research for my nice “winter-home”, Dr. Klaus Henle for giving me the opportunity to work in Bayreuth during summer and the graduate school HIGRADE for a lot of interesting courses and trainings and for funding some research stays - Prof. Carl Beierkuhnlein for giving me the possibility to use (wo)man-power and technical resources of his group and for fast and helpful editing of my manuscripts - Dr. Gregor Aas and the staff of the Ecological Botanical Garden of the University of Bayreuth for their support of the whole experiment - Prof. Wolfram Beyschlag (University of Bielefeld), Jun.Prof. Christiane Werner-Pinto (University of Bielefeld), Prof. John Tenhunen (University of Bayreuth), Dr. Uwe Rascher (FZ Jülich) and Harald Auge (UFZ Halle) for providing us their technical equipment and Dr. Sonja Löffler (LFE Eberswalde) for her help and support with the leaf chemical analysis - numerous student workers and interns within the EVENTexperiments for their help in maintenance, treatment execution and for doing measurements with me, even “pre-dawn”, especially to Roman Hein, Laura Nagy, Inés Pastor, Julia Gommola, Jan Taucha, Julia Smith, David Eichenberg and Clesio Gomes da Silva - all the technicians for their general help in the experiment, and especially Christian Schemm and Christine Pilsl for their help in the lab and Reinhold Stahlmann for his help with “computer-stuff” - all my co-phDs (Kerstin, Laura, David, Roman, Daniel, Jan) and our post-doc, Jürgen Kreyling, for making field work fun, for physical and psychological support and for many useful discussions - my parents, sisters friends and Roman and Smilla (I hope they all know what for) References 31 References of the Introduction: Adler, P.B., HilleRisLambers, J., Kyriakidis, P.C., Guan, Q., Levine, J.M., 2006. 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Vulnerabilität und Anpassungsstrategienklimasensitiver Systeme-UBA Forschungsbericht, www.umweltdaten.de/publikationen/fpdf-l/2947.pdf. Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 37 Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity Journal of Ecology, 2011, 99: 689–702. Anke Jentsch1*, Juergen Kreyling2, Michael Elmer3, Ellen Gellesch2, Bruno Glaser4, Kerstin Grant2, Roman Hein2, Marco Lara4, Heydar Mirzae6, Stefanie E. Nadler2, Laura Nagy1, Denis Otieno6, Karin Pritsch7, Uwe Rascher8, Martin Schädler9, Michael Schloter7, Brajesh K. Singh10, Jutta Stadler9, Julia Walter11, Camilla Wellstein2, Jens Wöllecke3 and Carl Beierkuhnlein2 1 Disturbance Ecology, University of Bayreuth, D-95440 Bayreuth, Germany. E-mail: [email protected] 2 Biogeography, University of Bayreuth, 95440 Bayreuth, Germany. 3 Soil Protection and Recultivation, BTU Cottbus, Konrad-Wachsmann-Allee 6, 03046 Cottbus, Germany. 4 Soilphysics, University of Bayreuth, 95449 Bayreuth, Germany 5 Soil Biogeochemistry, Martin-Luther University of Halle-Wittenberg, von Seckendorfplatz 3, 06120 Halle, Germany. 6 Plant Ecology, University of Bayreuth, 95440 Bayreuth, Germany. 7 Terrestrial Ecogenetics, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Ingolstaedter Landstraβe 1, 85764 Neuherberg, Germany. 8 Institute of Chemistry and Dynamics of the Geosphere, ICG-3, Phytosphere, Research Centre Jülich, LeoBrandt-Str., D-52425 Jülich, Germany. 9 Community Ecology, Helmholtz-Centre for Environmental Research – UFZ, Theodor-Lieser-Str. 4, 06110 Halle, Germany. 10 Centre for Plants and Environment, University of Western Sydney, Penrith South DC, NSW, Australia. 11 Conservation Biology, UFZ-Helmholtz, Centre für Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany. Corresponding author: Prof. Dr. Anke Jentsch, E-mail: [email protected]e Running title: Drought effect on multiple ecosystem services Summary 1. Studying the effects of extreme climatic or weather events such as drought and heat waves on biodiversity and ecosystem functions is one of the most important facets of climate change research. In particular, primary production is amounting to the common currency in field experiments worldwide. Rarely, however, are multiple ecosystem functions measured in a single study in order to address general patterns across different categories of responses and to analyse effects of climate extremes on various ecosystem functions. 2. We set up a long-term field experiment, where we applied recurrent severe drought events annually for five consecutive years to constructed grassland communities in central Europe. Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 38 The 32 response parameters studied were closely related to ecosystem functions such as primary production, nutrient cycling, carbon fixation, water regulation and community stability. 3. Surprisingly, in the face of severe drought, aboveand below-ground primary production of plants remained stable across all years of the drought manipulation. 4. Yet, severe drought significantly reduced below-ground performance of microbes in soil indicated by reduced soil respiration, microbial biomass and cellulose decomposition rates as well as mycorrhization rates. Furthermore, drought reduced leaf water potential, leaf gas exchange and leaf protein content, while increasing maximum uptake capacity, leaf carbon isotope signature and leaf carbohydrate content. With regard to community stability, drought induced complementary plant–plant interactions and shifts in flower phenology, and decreased invasibility of plant communities and primary consumer abundance. 5. Synthesis. Our results provide the first field-based experimental evidence that climate extremes initiate plant physiological processes, which may serve to regulate ecosystem productivity. A potential reason for different dynamics in various ecosystem services facing extreme climatic events may lie in the temporal hierarchy of patterns of fast versus slow response Such data on multiple response parameters within climate change experiments foster the understanding of mechanisms of resilience, of synergisms or decoupling of biogeochemical processes, and of fundamental response dynamics to drought at the ecosystem level including potential tipping points and thresholds of regime shift. Future work is needed to elucidate the role of biodiversity and of biotic interactions in modulating ecosystem response to extreme climatic events. Keywords: below-ground, competition, decomposition, invasion, leaf chemistry, microbial, phenology, plant–climate interactions, precipitation change, productivity Introduction Currently, knowledge about ecological responses to climate change is based largely on effects of climatic trends such as gradual warming, precipitation change and CO2 enrichment. However, the magnitude and frequency of extreme climatic or weather events such as severe drought, heat waves, heavy rain and late frost events are expected to increase in the near future (IPCC 2007; O’Gorman & Schneider 2009). Thus, predictions of effects of climate Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 45 drought. The maximum quantum efficiency of photosystem II was calculated as Fv/Fm. Variable fluorescence (Fv) and maximum fluorescence (Fm) were measured before dawn. Variable fluorescence was calculated as Fm-F0, Fm being the maximum fluorescence of the dark-adapted leaf after applying a saturating light pulse and F0 being the steady-state fluorescence yield of the dark-adapted leaf (Maxwell & Johnson 2000). To enable a comparison between absolute fluorescence values, a fluorescence standard material was measured before dawn and calculated as Fv/Fm (Fv = Fm – F0) (Maxwell & Johnson 2000). Absolute F0 and Fm values were taken to separate the effects of photodamage, becoming apparent with an increase of F0, from the effects of photoprotection related to enhanced nonphotochemical quenching, becoming apparent with a decrease in Fm (Walter et al., 2011). Leaf gas exchange Carbon dioxide assimilation (A) at the leaf was monitored in A. elatius in all the grassland communities. (No data could be obtained from H. lanatus in the particular year of data mining due to its leave status.) A series of weekly measurements were carried out using a portable gas exchange system (LI-6400, LI-Cor, Lincoln, NE, USA). A set of 3 grass tufts on each plot were identified and marked for measurements. On any measurement day, 2-3 suitable leaf blades selected from each of the tufts per plot were set parallel in the cuvette, with their upper surfaces well exposed so that they were fully illuminated during measurements. Every turn of measurements lasted one to two minutes, when a steady state was attained and a set of 10 readings per measurement logged at 10-s intervals. The selected leaves were marked and similar leaves were monitored either during midday (12:00 to 14:00 h) or throughout the day (from sunrise to sunset), when diurnal course measurements were conducted. The measured leaves were then excised at the end of the measurement period and the leaf area (LA) of the section of leaf enclosed in the cuvette determined using leaf area meter CI-202 CID, Camas, WA, USA. Leaf area information was then used to standardize the leaf gas exchange data. Soil respiration In situ rates of soil respiration were measured using a portable CO2 infrared gas analyser (EGM-4, PP Systems, Amesbury, USA) linked to a soil respiration chamber (SRC-1, PP System, Amesbury, USA). At the beginning of the vegetation period, permanent PVC collars (10 cm diameter, 5 cm height, light grey colour) were installed in every plot with a 1cm edge above soil surface to realize a closed system when the soil respiration chamber was placed on the collar during measurement. The day before each measurement, all aboveground vegetation was removed from the collar using scissors. During the timeframe of 8:00 Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 46 to 12:00, the soil respiration chamber was placed for 240 seconds on the collar of every plot. An internal fan realized the even distribution of air and the infrared gas analyser monitored the build-up of CO2 within the system. The rates of soil respiration were determined from this by fitting a quadratic equation to the change in CO2 concentration with time. For this study, we analysed the soil respiration rates at second 240 of each high-diversity grassland plot including A. elatius, H. lanatus, P. lanceolata and G. pratense on the last day of drought manipulation. Maximum leaf and canopy uptake rates Net ecosystem CO2 exchange was measured with chambers on 40 × 40 cm frames established on each of the treatment plots. Daily course of net ecosystem CO2 exchange (NEE) was measured using manually operated, closed gas exchange canopy chambers. Lightresponse curves depicting the net photosynthetic CO2 uptake rate (A) of plants at any measuring time were obtained from leaf-level gas-exchange measurements by fitting an empirical rectangular hyperbola model (Gilmanov et al. 2005): NEE = (α+Q / αQ-β) - γ, where α is the initial slope of the light-response curve and an approximation of the canopy light utilization efficiency (mol CO2/ mol PAR), β is the maximum CO2 uptake capacity (µmol m–2 s–1), Q is the photosynthetically active radiation (PAR, in µmol m–2 s–1), and γ is an approximation of the average daytime ecosystem respiration (lmol m–2 s –1). An approximation of maximum canopy uptake capacity was extrapolated from leaf-level measurements. Canopy net ecosystem exchange rate (NEE) was estimated from leaf photosynthetic rate at saturating light intensities (it was shown that A at PAR = 2000 µmol m– 2 s–1 correlates well with canopy NEE). Maximum gross primary productivity (GPPmax) was calculated as: GPPmax = NEE2000 – Reco, where A2000 is the maximum leaf photosynthetic rate at a saturating level of light intensity andReco is the corrected respiration term (γ) obtained from the model. Nutrient cycling In situ decomposition rate of cellulose Biological activity of soil fauna and microorganisms was determined indirectly from the decay of cellulose using mini-container tubes (Kreyling et al. 2008a). In total, 864 minicontainers were filled with 0.2 g of cellulose (poor in phosphorus, Schleicher & Schüll, Dassel, Germany) each, closed with a 2-mm mesh, and put into container tubes, consisting of 12 mini-containers each. Two tubes were buried horizontally 1 cm below soil surface in each grassland plot. After 94 days, one tube per plot was harvested, whereas the others were Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 47 harvested after 186 days. After careful cleaning and drying, the decay of cellulose was determined by subtracting final ashes-free dry mass from initial dry mass (105 °C). Mycorrhizal colonization One complete plant individual of P.lanceolata was taken from each plot on the last day of drought using a soil core sampler with 5 cm diameter (Eijkelkamp; Netherlands). This particular species was chosen, because pre-analysis revealed higher effects of drought on mycorrhizaal colonization of P. lanceolata than on that of other species tested. Roots were cut off and fixed in formalin-alcoholic-acid (50 % Ethanol, 40 % H2O, 7.5 % formalin, 2.5 % acidic acid), and stained with 5 % blue ink vinegar solution after boiling in 10 % KOH. Afterwards, mycorrhization ratios were determined by scanning 15 cm fine roots of each sample for arbuscules and vesicules under a microscope (400×) using the “magnified intersection method” (McGonigle et al. 1990). Soil microbial nitrogen pool Soil microbial nitrogen was extracted from fresh soil according to a modified chloroform fumigation–extraction method (Brookes et al. 1985). After chloroform fumigation (24 h at room temperature), dissolved organic and microbial N was extracted with 50 mL 0.5 M K2SO4 and quantified (DIMA TOC-100, Dimatec, Essen, Germany). Microbial biomass and relative abundance of microbial groups were measured using phospholipid fatty acid (PLFA) analysis as described (Singh et al. 2006). Potential soil enzyme activities For soil enzyme activity measurements, enzymes involved in carbon, nitrogen and phosphorus cycling were selected, thus addressing important microbial soil functions (Waldrop & Firestone 2006). The enzyme activities tested were acid phosphatase cleaving organically bound phosphate, cellobiohydrolase, β-xylosidase and β-glucosidase related to the degradation of plant cell wall components and N-acetylglucosaminidase representing chitinases that degrade chitin from fungal or arthropod origin. Soil samples for determining soil enzyme activities were collected immediately after finishing the drought manipulations (Kreyling et al. 2008a). Four samples per plot (depth 0 – 5 cm) were combined, mixed and kept at 4 °C until further processing within 4 weeks after sampling. Soil suspensions (0.4 g fresh soil in 40 mL H2O) were prepared from each sample. The assay is based on the enzymatic cleavage of the below-detailed methylumbelliferone (MU) coupled substrates and the subsequent detection of MU released during incubation. In brief, 50 μL per well of soil suspensions (three replicates each sample) were dispersed in microplates and 100 μL of substrate solutions were added to start the reactions. After stopping the reaction with 100 μL Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 48 of 2.5 M Tris buffer and centrifugation, MU concentrations were determined on a fluorescence spectrometer at excitation/emission wavelengths of 365/450 nm, respectively. The following enzyme substrates were used with the incubation times given: MUF-phosphate, 20 min; MUF-xyloside, 1 h; MUF-cellobiohydrofurane, 1 h; MUF-N-acetyl-β-glucosaminide, 40 min; MUF-β-glucoside, 1 h. Substrate concentrations in the incubation mix were 500 μM except for MUF-cellobiohydrofurane with 400 μM. To account for quenching and to calculate the amount of MUF released, calibration curves were included with 50 μL of soil samples as in the incubation wells and MUF-solutions to give a final amount of 0 - 500 pmol per well. Negative controls for autofluorescence of substrates were also included. Enzyme activities are expressed as MUF-release per gram soil dry weight per hour. Plant-available soil nitrate and ammonium Plant-available nitrogen was extracted from four homogenized, sieved (< 2 mm), mixed samples of the upper soil layer (0-10 cm) of each plot sampled in July using a 1 M KCl solution after filtration (Roth, Karlsruhe Germany, Typ 15 A Blauband) (Kreyling et al. 2010). Nitrate and ammonium were quantified using flow injection analysis (FIA, MLE Dresden FIA-LAB). Leaf carbon to nitrogen ratio Leaf carbon (C), leaf nitrogen (N) and C:N ratios were measured from mixed samples of two sun-exposed leaves of five individual plants per species and plot, sampled in July (Kreyling, Beierkuhnlein & Jentsch 2010). The samples were oven-dried for 48 h at 75 °C. The dry leaves were ball-milled and subsamples of 1 mg analysed with an elemental analyser in a mass spectrometer using ConFlo III interface. Plant-available nitrogen was extracted from four homogenized, sieved (2 mm) and filtered (Roth, Germany, Typ 15A Blauband) mixed samples of the upper soil layer (0–10 cm) of each plot using a 1 M KCl solution. Leaf protein content Total protein content in µg per mg fresh weight was determined as a proxy for nutritive value of the legume key species H. lanatus, which was growing in all plots. One leaf sample per plot was taken on the last day of drought treatment, frozen in liquid nitrogen and freeze-dried to determine protein-bound amino acids. Amino acids of the protein fraction were extracted. Amino acid concentrations were measured with an ion exchange chromatograph (Biotronik, amino acid analyser LC 3000) and protein content was calculated by pooling the content of each amino acid in the protein fraction. Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 49 Leaf nitrogen isotope signal Equally aged, south-facing leaves of A. elatius were collected and oven-dried at 60 °C for 48 h, and then fine-milled. Natural abundance of δ15N and total nitrogen concentration were analysed using an elemental analyser (EA 3000, EuroVector, Italy) coupled online to a ConFlo III interface (Thermo Electron, Bremen, Germany) connected to an isotope-ratio mass spectrometer (MAT 253, Thermo Electron, Bremen, Germany) . The δ15N values were calculated as: δ15N [‰] = ( Rsample/Rstandard ) -1)*1000, where R represents the ratio of 15N:14N isotopes. As standard, (nitrogen in) air was used. Community responses Invasibility Invasibility of the experimental communities was recorded three times per year: before and after the drought manipulations in early summer, and in fall (Kreyling et al. 2008c). Invading plant individuals were collected from the inner square metre of each plot and subsequently separated by species. Removal took place only after the first true leaves (after the cotyledons) emerged, but most specimens were considerably older than this and clearly established in the stand. At this point in development, we expected that number of individuals give a measure of established invaders rather than chance germinations. For each plot, the number of individuals was determined. The planted target species of the experiment were removed from the subsequent analysis. Tests confirmed that germination from the soil seed bank was negligible after one year. Thus, invasibility was only based on species invading from the matrix vegetation. Plant compositional change The measurements of above-ground species-specific cover (s. above) were used to evaluate shifts in the species abundance distributions of the artificial plant assemblages. Compositional change of each individual plot was evaluated by comparing the species abundance distribution at each time step to the initial species abundance distribution (five weeks after planting) by the Bray–Curtis index. Competitive effect / facilitative effect The Relative Neighbour Effect calculates the effect of neighbours relative to the plant with the greatest performance: RNE = Pcontr-Pmix/x with x = Pcontr if Pcontr > Pmix and x = Pmix if Pmix> Pcontr , where RNE = Relative neighbour effect (-1 ≤ RNE ≤ +1), Pcontr = performance Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 50 per plant for a plant growing alone ,Pmix = performance per plant for a plant growing in mixture. Negative values indicate facilitation, and positive values indicate competition (Markham & Chanway 1996). Senescence Tissue die-back was quantified by cover measurements of standing-dead plant organs (Kreyling et al. 2008d). A pin-point method was applied, recording the presence of plant organs in general and the presence for each species separately at 100 vertically inserted steel needles. These values were treated as percentage cover. The measurement was repeated four times over the course of the vegetation period. Variability in length of flowering For each species, weekly observations of the flowering status of four individuals per plot and species were carried out (Jentsch et al. 2009). Individuals were counted as ‘flowering’ when the anthers were visible in at least one flower. Flowering length was calculated as the difference between the dates of the 25 and 75 percentile of the flowering curve over time. Variability in length of flowering was obtained as the standard deviation between all species for each treatment (drought and control) separately. Statistical significance of difference in variability was evaluated by the Levene test. Variability in flower phenology Flower phenology was obtained from the same data as length of flowering (see above). As a surrogate, the mid-flowering date was calculated for each species and plot, i.e. the date of the 50 percentile of the flowering curve over time. Variability in flower phenology was expressed as the standard deviation between all species for each treatment (drought and control) separately. Statistical significance of difference in variability was evaluated by the Levene test. Resistance to herbivory (phenol content) For analysis of total soluble carbohydrates and total phenolics, three mixed samples of at least two plants per plot were taken at the end of the drought period, immediately frozen in liquid nitrogen and lyophilized (n=15). Thirty miligrams were extracted in 50 % methanol. Total soluble carbohydrates were analysed using the anthrone method with glucose as a standard. Extinction was measured at 620 nm. Total phenols were analysed using FolinCiocalteu’s reagent and catechin as a standard and measuring extinction at 750 nm. Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 51 Primary consumer abundance Richness was sampled in June in one circular area (40 cm diameter) in each grassland plot using a D-Vac suction sampler (ecotech GmbH, Bonn, Germany). For each plot, the sampling bag was removed and all sampled material was stored in ethanol. Arthropod samples were quantified as the total number of individuals and identified at least to order level. However, some taxa were identified to the family level (families within the Coleoptera, Hemiptera, most Hymenoptera) and in one case to genus level (Psylliodes [Chrysomelidae]. The use of higher taxonomic levels has been shown to produce a good approximation of total species richness (Biaggini et al. 2007). Statistical Analyses Linear Models combined with analysis of variance (ANOVA) were applied to test for significant differences between groups at single points of time, while taking the split-plot design into account. Homogeneous groups of factor combinations (drought manipulation, vegetation type, diversity level) were identified by Tukey HSD post hoc comparisons. Level of significance was set to p<0.05. Statistical significance of difference in variability of length in flowering was evaluated by the Levene test. For time series, Linear Mixed-Effects Models were employed to test for effects of drought manipulation and diversity and their respective interactions while taking the split-plot design and the repeated measures into account (time used as random factor). When no significant interaction was found, the model was simplified by using only the drought manipulations as fixed effects and time as random effect. Significance of differences (p < 0.05) was evaluated by Markov Chain Monte Carlo sampling of 1000 permutations. Linear Mixed-Effects Models were conducted with the function ‘lmer’ (Bates & Sarkar 2007). Prior to statistical analysis, data was logor square-root-transformed, if conditions of normality were not met, or to improve homogeneity of variances. Both characteristics were tested by examining the residuals versus fitted plots and the normal qq-plots of the linear models. All statistical analyses were performed using R. Results The effects of drought on all measured ecosystem properties are summarized in Fig. 1 using response ratios to standardize the effect size of the severe drought treatment. Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 52 Figure 1: Effects of recurrent severe drought events on 32 response parameters organized into ecosystem functions. All data were collected at the EVENT I experimental site (Jentsch, Kreyling & Beierkuhnlein 2007) in Central Europe during the years 2005 - 2009. A parameter is marked as significant (filled black bar), if data of at least one year showed significant differences between drought and ambient conditions (ANOVA). Data shown represent maximum effects from years with highest drought effects, averaged over all three experimental grassland communities. For references of published details please refer to Materials and methods section Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 53 Water regulation Severe drought significantly reduced soil moisture during the manipulation periods in all years (Figs 1, 2). Figure 2 Soil moisture in the EVENT experiment at -2 to -7 cm during manipulation (light grey boxes) and recovery after extreme drought for control (black line) and drought (grey line). MJJA = May, June, July, August. Plant available water is shown between the dashed lines: permanent wilting point (pF = 4.2) and field capacity (pF = 1.8). See Materials and methods for technical details. A high variability both within years and between years is evident due to inter-annual variability of precipitation (Table 2). Even though absolute minima in soil moisture were similar for drought and control in most years, soil moisture of the drought plots remained considerably longer below the approximate permanent wilting point (pF = 4.2) for the soil substrate. The manipulation effect vanished within days for all years except 2009, where a lag phase of about two months until August occurred. Table 2 Temperature and precipitation sums (added daily amount) for each year until the start of the drought manipulation and the respective alteration from the long-term mean (1971-2000, data: German Weather Service station Bayreuth) year temperature sum (1 January to start of manipulation) relative change of temperature sum compared to longterm mean (%) precipitation sum (1 January to start of manipulation) relative change of precipitation sum compared to longterm mean (%) 2005 824.7 -3 259.7 -9 2006 394.7 -38 208.3 +10 2007 978.7 +77 258.6 +9 2008 757.6 +40 282.2 +19 2009 574.9 +4 246.4 +4 Further, drought decreased leaf water potential, while increasing leaf carbon isotope signal in some species (Figure 1). Primary production At the level of the grassland community or ecosystem, respectively, local, annually recurrent 100-year and 1000-year extreme drought events had no significant effect on various Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 54 processes that contribute to primary production in any of the five years from 2005 to 2009 (Figs 1, 3). Surprisingly, neither above-ground primary production (ANPP), nor green cover of vegetation or below-ground production recorded as root length in the main rooting horizon were affected by drought (Figs 1, 3). Figure 3: (a) Above-ground Net Primary Production (ANPP) , (b) cover of green biomass, and (c) root length over five growing seasons (mean ± SE over all species compositions in grassland, n = 15 per data point). An asterisk marks significant treatment effects (ANOVA, Tukey HSD post hoc comparison: p < 0.05) Further, there was no significant drought effect on biomass production of the nitrogen-fixing plant L. corniculatus (Figure 1). Carbon fixation Drought increased the maximum uptake capacity (GPPmax) in grassland by 36 % (Figure 1). The soil respiration rate (Reco calculated by the model was lower under drought than under ambient conditions. Soil respiration was slightly but not significantly decreased at the end of the drought. 2005 2006 2007 2008 2009 0 100 200 300 400 Year ANPP [g m-² a-1] 0 20 40 60 80 100 Green cover [%] Ambient Drought Root length [cm 4 cm-2] n.s. n.s. (a) (b) 0 1 2 3 4 5 6(c) n.s. Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 61 Conclusion Our experimental data demonstrate that weather extremes initiate ecosystemregulating functions such as water and nutrient cycling, gas exchange and compositional dynamics while maintaining primary production. They indicate an important contribution of ecological complexity to the maintenance of productivity in the face of increased temporal climate variability and extraordinary weather events. However, single species reactions can not be translated directly to the community and ecosystem level. A potential reason for different drought impacts on various ecosystem properties may lie in the temporal hierarchy of fast versus slow response patterns. In our temperate grassland, we observed the following response dynamics within half a decade of recurrent drought events: very fast alteration of soil moisture status, subsequent fast change in nutrient cycling and gas exchange, slow species-specific response in primary production, inertia in community productivity. Such data on multiple response parameters within climate change experiments foster the understanding of mechanisms of resilience, of synergisms or decoupling in biogeochemical processes, and of fundamental response dynamics to drought at the ecosystem level. As it was the case with the open questions on the consequences of the crisis of biodiversity, we see this complexity in studying impacts of climate extremes as a new chance for a boost in ecological theory. Additionally, comprehensive studies on the complex responses will help developing coping strategies for the adapted management of these ecosystems. Future challenges consist of analysing responses for multiple ecosystem functions and at multiple levels of organization with the goal of assessing how they interact to influence emergent ecosystem properties, such as ecosystem function and stability. The observed stability in primary production in the face of recurrent severe drought does not mean that the responses at the ecosystem level are null. On the contrary, the observed changes in ecosystem regulating functions in terms of gas exchange, nutrient cycling, water regulation and community stability suggest a prominent role of extreme weather events in ecosystem response to climate change. However, modelling the behaviour of ecosystems during and after extreme climatic events at larger spatial scales and over longer periods of time requires more in-depth knowledge on possible response mechanisms at the level of plant communities. Potential epigenetic, physiological or trophic responses need to be rigorously further explored experimentally. Laboratory studies on molecular mechanisms have to be related to studies Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 62 with the same species in the field. Field studies must integrate various levels of functional diversity (Beierkuhnlein et al. in press). Phenotypical diversity of populations has to be considered. Life cycles of plant species and cohorts can be of crucial importance. Gradients in soil types have to be integrated. Then, we can reach a better understanding of the mechanisms that are initiated in plant communities by extreme events. Future work is needed to elucidate the role of biodiversity and of biotic interactions in modulating ecosystem response to extreme weather events. Further, we need more data on impacts of climate extremes on multiple ecosystem properties from various ecosystems and biomes, in order to foster the search for generality across different categories of response. Here, a major challenge is to assess the speed of response across various parameters, including long-term feedbacks, i.e. caused by a nitrogen-dependent feedback on productivity (Haddad et al. 2002). Generally, scientists are challenged by relating the ecosystem properties measured (here: net ecosystem exchange, biomass above and below ground, carbon fixation by photosynthesis, nutrient ratios) to ecosystem functions and services, such as productivity, carbon fixation, nutrient cycling, decomposition and water regulation. Measuring ecosystem services is a fast-developing research area with many debates on how to assess the services adequately. 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(2009) Greater impact of extreme drought on photosynthesis of grasslands exposed to warmer climate in spite of acclimation. Physiologia Plantarum, 136, 57-72. Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 66 Online Supporting Information Table S1: Search items for searching the ISI Web of Science® Database for publications on weather events and climate extremes. Asterisks are place holders within the search string Main category Search items in ISI Web of Knowledge Frost *frost event* OR severe night frost* OR *spring frost* OR freeze-thaw* OR thaw-freeze* OR late frost* OR severe frost* OR *ground frost* OR extreme frost* OR extreme cold* Heat & drought heat wave* OR heatwave* OR severe heat* OR *temperature event* OR dry spell* OR extreme heat* OR *winter warming* OR warm* winter OR summer drought* OR spring drought* OR autumn drought* OR severe drought* Storm extreme storm* OR *winter storm* OR hurricane* OR typhoon* OR cyclone* OR tornado* OR storm surge* OR *windstorm* OR *wind storm* OR *tropical storm* OR ice storm* Heavy rain extreme flood* OR summer flood* OR extreme rain* OR torrential rain* OR extreme precipitation OR *rainfall event* OR heavy rain* OR hail* OR wet spell* Extreme extreme event* OR extreme weather event* OR climat* extreme* OR extreme meteorological event* OR extreme weather* OR extreme climat* event* Table S2: Links for searching the ISI Web of Science® Database for publications on weather events and climate extremes Links Search items in ISI Web of Knowledge Main items in “Topic” Frost, Heat & drought, Storm, Heavy rain, Extreme AND in “Topic” wetland* OR floodplain* OR peat* OR bog* OR fen* OR swamp* OR mire OR grassland* OR meadow* OR pasture* OR heath* OR shrubland* OR forest* OR woodland* OR tundra OR taiga OR savanna* OR marsh* OR steppe OR desert* OR aquatic* OR limn* *bird* OR avian OR insect* OR butterfly* OR beetle* OR arthropod* OR moth* OR amphibian* OR reptile* OR mollusc* OR mollusk* OR vertebrate* OR *invertebrate* OR mammal* AND in “Topic” climat* change* OR global change* OR climat* warming NOT in “Topic” palaeo* OR paleo* OR pleistocene OR holocene Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 67 Table S3: Sampling years of all response parameters presented in Figure 1. Given are data from years with maximum drought effect Ecosystem property Year of sampling with maximum drought effect Ecosystem service Above-ground production (ANPP) 2005 Nitrogen fixing plants 2009 Plant cover 2009 Primary production Below-ground biomass 2007 shoot / root - ratio 2006 Gas exchange Maximum carbon uptake capacity 2005 Photosynthetic performance 2008 Leaf gas exchange 2007 Soil respiration 2010 Nutrient cycling Decomposition rate 2007 Mycorrhization rate 2008 Soil microbial biomass 2008 Soil enzyme activity 2006 Plant available NO32008 Plant available soil NH4 2008 soil microbial N 2009 Leaf C/N-ratio 2009 Leaf protein content 2009 Leaf carbohydrate content 2009 Leaf nitrogen isotope signal 2007 1° consumer abundance 2008 Soil moisture 2009 Water regulation Leaf water potential 2008 Leaf carbon isotope signal 2007 Community responses Invasibility 2006 Plant compositional change 2005 Senescence 2006 Variability in length of flowering 2006 Variability in flower phenology 2008 Resistance to herbivory 2009 Competitive effect 2007 Facilitative effect 2007 Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 68 (a) Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 69 (b) (c) Manuscript 1: Climate extremes initiate ecosystem regulating functions while maintaining productivity 70 (d) Figure S1: Research on ecological effects of climate extremes and weather events based on publications found in the ISI Web of Science (for search details see Table 2) (a) Temporal development of the number of publications on climate extremes (n=380) in the last two decade (shown is only the last decade); total yield 1134 peer-reviewed papers (b) Studied extreme weather events (n=464 inlcuding double or triple assignments) of the relevant peer-reviewed papers (n=380) yielded by the literature study. 24 publications did not specify the event. (c) Research activity in the three main biomes by proportion of publications based on 380 peer-reviewed papers particularly studying effects of climate extremes on ecosystem functions. Grassland includes deserts, peat and wetlands. Shrubland includes tundra. Any one paper may have been assigned to multiple subject areas. (d) Studied effects of extreme weather events on ecosystem properties arranged by ecosystem services and functions based on 380 peer-reviewed papers particularly studying effects of climate extremes on ecosystem functions Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 77 and the levels were shifted every second day, putting the lowest level to the highest place and all other levels one level lower. The plant leaves from one plot were fed to the larvae in four petri dishes (8 larvae in total). Caterpillars were able to eat ad libitum, as special care was taken that the grass inside one petri dish was never totally consumed. Leaves were replaced at least every second day. We recorded the mortality of the larvae, the development time until pupation, the weight of the pupae one day after pupation and pupal mortality. Through the isolation in climate chambers we were able to attribute the responses in herbivore performance to differences in plant compounds, as opposed to when feeding is conducted under field conditions and it is impossible to disentangle the effects of plant nutrients, compensatory feeding and direct weather effects on herbivores (Goverde et al. 2002). Statistical analysis Chemical leaf traits were analyzed using a two-way ANOVA with weather treatment and community composition as fixed factors. Additionally, we included the number of columns and rows as random factors. This automatically implements the nesting of composition within treatment-blocks in the mixed effect model (Faraway 2006; Dormann and Kühn 2008). If several samples per plot were taken, as was the case with phenolics, carbohydrates and condensed tannins, then the plot number was additionally included as a random factor in the mixed model, to avoid any pseudo-replication. Developmental time and pupal weight were analyzed using linear mixed effect models with the petri dish nested within the plot nested within the treatment block as a random factor, in addition to the row and the column of the treatment blocks as random factors. Larval and pupal mortality were analyzed using generalized mixed effect models with binomial distribution and otherwise the same model formula as for other developmental traits. The significance levels in the mixed effect models were evaluated by Markov Chain Monte Carlo sampling of 1000 permutations (Baayen 2009; package language R).The significance of the fixed factors for the generalized mixed effect models was determined by comparing the null model, without any factors, to the simplest factorial model, in which nonsignificant terms had been removed by backwards stepwise selection. Prior to all analyses, data were transformed accordingly, if the assumptions of ANOVA, homogeneity of variances and normality, were not met (C/N ratio and nitrogen content: log-transformed; RWC: arcsinsquareroot-transformed). To determine the relationship between chemical leaf traits and development traits, we applied hierarchical partitioning, as leaf chemical traits are often collinear (Schädler et al. Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 78 2003). In hierarchical partitioning, the independent influence and the joint influence (the influence from being correlated to another explanatory variable) of explanatory variables is calculated by comparing the model-fits of models with and without the particular variable (Mac Nally 2002; Dormann and Kühn 2008). To determine correlations between the different development traits, a correlation analysis was used to correlate pupal weight with developmental time, and logistic regression was used to investigate the relationship between pupal mortality and pupal weight. All statistical analyses were performed using R 2.11.0 (R Development Core Team 2010). For mixed effect models we used the software package lme4 (Bates & Mechler 2010), and for multiple post-hoc comparisons the package multcomp was used (Hothorn et al. 2008). Results Soil moisture The vegetation period for the year 2009 (April 1st – October 31st) with a total sum of 459 mm of precipitation was slightly wetter than the long-term average precipitation sum of 437 mm for the time period 1971-2000 (Data: German Weather Service). Soil moisture fell more quickly during the first half of the drought period compared to the second half, but rose quickly again after the drought period was over (Fig.1). Day of the year 140 150 160 170 180 0,00 0,05 0,10 0,15 0,20 0,25 0,30 Drought Control Soil moisture [vol % ] 0 5 10 15 20 25 Average Temperature [°C ] Day of the year 140 150 160 170 180 0,00 0,05 0,10 0,15 0,20 0,25 0,30 Drought Control Drought Control Soil moisture [vol % ] 0 5 10 15 20 25 Average Temperature [°C ] Fig. 1 Course of soil moisture in drought-exposed plots (black circles) and control plots (dark-grey squares), and average daily temperatures, assessed at a height of 1, 20 m (light grey bars). Data are shown from the first day of the drought manipulation (day of the year 140=May 20th, 2009) until two days after the extreme drought ended, indicated by the black vertical line (day of the year 182=July 1st, 2009). The average of hourly readings from five sensors per treatment were taken here (n=5) Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 79 The effect of drought and community composition on chemical leaf traits Drought significantly decreased RWC by 8 % (Fig. 2a), protein content by 23 % (Fig. 2b), nitrogen concentrations by 26 % (Table 3) and phenols by 7 %, when compared to the control treatment (Fig. 2c) (see Table 2 for statistical details). Furthermore, drought significantly increased the C/N ratio by 24 % and the soluble carbohydrates by 32 % (Fig. 2d, e). Condensed tannins however were not altered by drought manipulation (Table 2). CD RWC [%] 020 40 60 80 100 (a) CD Protein content [µg/mg FW] 012345 (b) CD Phenols [nmol/mg] 0 50 100 150 200 (c) CD C/N ratio [%] 0 10203040 (d) CD Carbohydrates [nmol/mg] 0 100 200 300 (e) Weather treatment CD RWC [%] 020 40 60 80 100 (a) CD Protein content [µg/mg FW] 012345 (b) CD Phenols [nmol/mg] 0 50 100 150 200 (c) CD C/N ratio [%] 0 10203040 (d) CD Carbohydrates [nmol/mg] 0 100 200 300 (e) Weather treatment CD RWC [%] 020 40 60 80 100 (a) CD Protein content [µg/mg FW] 012345 (b) CD Phenols [nmol/mg] 0 50 100 150 200 (c) CD C/N ratio [%] 0 10203040 (d) CD Carbohydrates [nmol/mg] 0 100 200 300 (e) CD RWC [%] 020 40 60 80 100 CD RWC [%] 020 40 60 80 100 (a) CD Protein content [µg/mg FW] 012345 CD Protein content [µg/mg FW] 012345 (b) CD Phenols [nmol/mg] 0 50 100 150 200 (c) CD C/N ratio [%] 0 10203040 CD C/N ratio [%] 0 10203040 (d) CD Carbohydrates [nmol/mg] 0 100 200 300 CD Carbohydrates [nmol/mg] 0 100 200 300 (e) Weather treatment Fig. 2 Differences in a) RWC (n=5), b) the protein content (n=5), c) the total soluble phenol content (n=15), d) the C/N ratio (n=5) and e) the total soluble carbohydrates (n=15) in leaves of Holcus lanatus under drought (light grey bars, D) compared to control (white bars, C). Asterisks indicate the level of significance: * p<0.05; **p<0.01; ***p<0.001. Means ± 1 SE are shown Community composition significantly affected the content of condensed tannins and phenols (Table 2) and marginally significantly affected the content of soluble carbohydrates (p=0.07) and proteins (p=0.01). Table 2 ANOVA results of the effects of drought treatment, community composition and, if significant, their interaction on RWC, total soluble protein content, nitrogen concentrations, C/N ratio (n=5, respectively), total soluble carbohydrates, total soluble phenols and condensed tannins (n=15, respectively). Values for interaction are only shown, when significant, as otherwise, the interaction term was excluded from the mixed model (df=degrees of freedom, MS=mean sum of squares). Asterisks indicate level of significance: `p<0.01; * p<0.05; **p<0.01; ***p<0.001 RWC protein nitrogen C/N carbohydrates phenols cond. tannins df MS F df MS F df MS F df MS F df MS F df MS F df MS F drought 1 0.18 28.4*** 1 7.51 7.4* 1 1.02 65.1*** 1 1.13 76.6*** 1 106533 68.3*** 1 5871 11.3** 1 76.4 0.6 composition 3 0.01 1.4 3 2.29 2.26` 3 0.01 0.7 3 0.01 0.8 3 3755 2.4` 3 2547 4.9** 3 516.6 4.2** interaction - - - - - - 3 0.06 4.1* 3 0.04 2.6` - - - - - - - - - residuals 30 0.01 32 1.01 32 0.02 32 0.01 97 1558 97 518 97 124.5 Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 80 The condensed tannins in H. lanatus from 4+ communities were significantly lower than the condensed tannins in leaves from 2and 4communities (Fig. 3a). Phenols were reduced in H. lanatus growing in legume communities (4+), when compared to H. lanatus from monocultures (1-) (Fig. 3b). Carbohydrates were marginally significantly increased in legume communities (4+) when compared to two-species communities without legume (2-) (Fig. 3c), while protein content was marginally significantly lower in four-species communities without legume (4-) when compared to legume communities (4+)(Fig. 3d). Fig. 3 Effects of plant community composition on a) the content of condensed tannins (n=15), b) the total soluble phenol content (n=15), c) the total soluble carbohydrates (n=15) and d) the total soluble proteins (n=5) in leaves of Holcus lanatus (1-: monoculture, 2-: two grasses, 4-: 2 grasses, 2 herbs; 4+:two grasses, 1 herb, 1 legume). Different letters indicate significant differences between the communities (p<0.05). Effects for carbohydrate and protein content were only marginally significant (p<0.1) As far as leaf nitrogen concentration was concerned, community composition significantly interacted with the drought treatment, as nitrogen concentration was reduced in all communities except for the 4+ communities in response to drought (Table 3). Table 3 Interactive effects of community composition and the drought treatment on the nitrogen concentration in leaves of H. lanatus (n=5). Means ± 1 standard deviation are given. Asterisks behind the community label indicate a significant drought effect in the respective community (p<0.05) composition 1- * 2- * 4- * 4+ control 1.99 ± 0.31 1.90 ± 0.31 1.88 ± 0.31 1.69 ± 0.30 drought 1.26 ± 0.32 1.45 ± 0.32 1.26 ± 0.32 1.51 ± 0.31 Cond. Tannins [nmol/mg] 010 20 30 40 1424+ Phenols [nmol/mg] 0 50 100 150 200 1424+ Carbohydrates [nmol/mg] 0100 200 300 Protein content [µg/mg FW] 012345 (a) (b) (d)(c) Community composition ab aa b aab b ab Cond. Tannins [nmol/mg] 010 20 30 40 1424+ Phenols [nmol/mg] 0 50 100 150 200 Phenols [nmol/mg] 0 50 100 150 200 1424+ Carbohydrates [nmol/mg] 0100 200 300 1424+ 1424+ Carbohydrates [nmol/mg] 0100 200 300 Protein content [µg/mg FW] 012345 (a) (b) (d)(c) Community composition ab aa b aab b ab Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 81 Development traits of S .littoralis and their relation to leaf chemical traits The community composition of the target grass was found to have a highly significant effect on larval mortality, with larvae feeding from 4plots showing a significantly higher mortality than in all other communities (Fig. 4). (P=0.007; Chisq= 12.2). The drought treatment did not affect larval mortality. Fig. 4 Effect of the plant community composition, in which H. lanatus grows, on the mortality of the 320 S. littoralis larvae. Different letters indicate significant differences between the communities (p<0.05) (n=20/treatment combination) The development time until pupation was highly significantly increased in those larvae that were reared on leaves subjected to drought (p=0.0003; F= 14.7; df=1). Furthermore, the drought treatment was found to significantly interact with community composition regarding development time until pupation (p=0.015; F= 3.8; df=3), as the larvae feeding on H. lanatus from the 2communities reacted with the greatest increase during the larval stage under drought (Table 4). Table 4 Differences in the duration of larval stage for 320 S. littoralis larvae feeding on H. lanatus leaves under the drought (light grey bars, D) and the control (white bars, C) treatments from four different community compositions. Drought significantly increased developmental time with strongest effects in 2communities (n=20/treatment combination). Means ± 1 standard deviation are given composition 1244+ control 25 ± 2.5 22 ± 2.4 25 ± 2.3 24 ± 2.3 drought 25 ± 2.3 27 ± 2.4 27 ± 2.5 26 ± 2.4 The larvae feeding on drought plants were also found to have significantly heavier pupae (p=0.033; F= 4.7; df=1) (Fig. 5a) and revealed a significantly lower pupal mortality (p=0.007; Chisq= 7.2) (Fig 5b), irrespective of community composition. Mortality [%] 02040 60 80 100 Community composition 1424+ aa b a Mortality [%] 02040 60 80 100 Mortality [%] 02040 60 80 100 Community composition 1424+ 1424+ aa b a Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 82 Fig. 5 Differences in (a) the pupal weight and (b) the pupal mortality for S. littoralis larvae fed with H. lanatus leaves out of the drought (light grey bars, D) and the control (white bars, C) treatments. Asterisks indicate the level of significance: *P\0.05; **P\0.01 (n = 20/treatment combination) Hierarchical partitioning showed that protein content had the greatest positive influence on the survival of larvae (Table 5). Table 5 Hierarchical partitions of the effects of leaf chemical traits on development duration, pupal weight, larval mortality and pupal mortality of 320 larvae. The total explained variance (R2), the individual effect on the explained variance, and the joint effect on explained variance are given. The latter quantifies the effect that can be explained by the correlation of a specific independent variable with other independent variables. + or – behind the most important partitions for one parameter indicate whether the parameters were negatively or positively correlated to the leaf chemical. RWC=Relative water content; C/N=C/N ratio; nitrogen=nitrogen concentration; carbon=carbon concentration; protein=total soluble proteins ; phenols= total soluble phenols ; tannins= condensed tannins ; carbos=total soluble carbohydrates RWC C/N nitrogen carbon protein phenols tannins carbos development total 0.143 0.259+ 0.2100.014 0.001 0.036 0.029 0.078 time independent 0.113 0.187 0.118 0.019 0.085 0.013 0.014 0.03 joint 0.03 0.071 0.091 -0.005 -0.084 0.024 0.015 0.048 pupal weight total 0.2290.024 0.04 0.031 0.079 0.094 0.077 0.04 independent 0.178 0.025 0.025 0.035 0.068 0.047 0.048 0.02 joint 0.051 -0.001 0.015 -0.003 0.012 0.047 0.029 0.021 larval mortality total 0.01 0.003 0.001 0.001 0.0470.006 0.005 0.009 independent 0.009 0.009 0.005 0.004 0.065 0.007 0.01 0.007 joint 0.001 -0.006 -0.004 -0.002 -0.018 -0.001 -0.005 0.002 pupal mortality total 0.031 0.0970.086 0.017 0 0.049 0.0960.042 independent 0.014 0.034 0.028 0.013 0.01 0.023 0.072 0.015 joint 0.017 0.063 0.058 0.004 -0.009 0.026 0.023 0.027 The development time was mainly positively influenced by the C/Nratio, and thus negatively by the nitrogen content, indicating that the development took longer, the less nitrogen was in the leaves (Table 5). Pupal weight was found to be negatively affected by RWC. Pupal survival, and thus adult eclosion was positively affected by content of condensed tannins and by C/N ratio. Pupal weight and development time were not correlated (Pearsons Pupal weight [g] 00.02 0.06 0.10 0.14 CD Weather treatment Pupal mortality [%} 020 40 60 80 CD (a) (b) Pupal weight [g] 00.02 0.06 0.10 0.14 CDCD Weather treatment Pupal mortality [%} 020 40 60 80 CDCD (a) (b) Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 83 correlation coefficient: -0.019; p=0.88). Pupal survival was positively related with pupal weight (p=0.023; logistic regression). Discussion The extreme 42-day drought did not only affect the water content of the target grass species, but also resulted in changes to almost all of the leaf chemical traits that we assessed. These changes to the leaf chemicals also clearly affected the development traits of the herbivore caterpillar. However, in contrast to our expectations, drought did not increase defensive compounds in the grass. Furthermore, the drought did not result in a worse overall herbivore performance, as adult eclosion and pupal weight were even higher for larvae fed from drought treated plants. The community composition of the target grass also affected some aspects of the leaf chemical composition, but changes cannot clearly be linked to increased competition or higher stability in more diverse communities. Differences mainly occurred in legume communities: H. lanatus growing in legume communities showed no effects of drought on the leaf nitrogen concentration and had the lowest content of condensed tannins and phenols. The community composition of the target grass affected the mortality of the herbivore, with highest mortality in larvae feeding on the grass growing in four-species communities without legume, in which also a trend towards lower protein content was apparent (4-). Soil moisture and plant stress The extreme drought conditions were accompanied by a marked decrease in soil moisture over the drought period, and this in turn clearly caused plant stress. In the year 2009 we did not directly quantify plant stress levels, e.g. by determining chlorophyll content or maximum quantum yield. However, a reduction in leaf relative water content in our target grass in all communities, along with marked changes in leaf chemicals, indicate acclimation processes and stress reactions, showing that the plants experienced stress (Sinclair and Ludlow 1985; Chaves et al. 2002). Effect of drought and community composition on chemical leaf traits A decrease in proteins and nitrogen, along with an increase in the C/N ratio under severe drought conditions has also been observed in other studies investigating drought effects on leaf chemicals (Shure et al. 1998; Liu et al. 2008). However, this is not in Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 84 accordance with the so-called “plant stress hypothesis”, which assumes available nitrogen to increase under plant stress (White 1984). Nevertheless, as nitrogen uptake is linked to water uptake, a decrease in nitrogen uptake, and therefore also protein content under drought, is not surprising. An increase in carbohydrates under drought could be attributed to osmotic adjustment in the course of drought acclimation. Soluble carbohydrates from starch degradation act as compatible solutes to prevent turgor loss in plant cells (Chaves et al. 2002; Regier et al. 2009). The decrease in total phenolics under drought does not support the idea that plants under stress use the surplus from carbohydrates (due to restricted growth while photosynthesis is still assimilating carbon) to accumulate more C-based defence compounds (Herms and Mattson 1992). However, a reduction of phenols in response to drought has also been reported by Shure et al. (1998). In our study, the need for osmotic adjustment under extreme drought might have been a reason not to accumulate phenols, but rather invest the surplus of carbon-based compounds in soluble carbohydrates. As community composition can alter resource partitioning between plants, it might also change the forage quality of leaf tissue. Both phenols and condensed tannins were found to be lowest in the communities that included one legume species. This kind of reduction in defence compounds can be explained by the potentially higher nitrogen availability in legume communities caused by N2-fixing in root-nodules, enabling higher growth rates at the expense of lower defence by C-based compounds (Herms and Mattson 1992). The trend towards higher protein content in leaves from legume communities compared to four-species communities without legumes support the idea of an increase in nitrogen availability in legume communities and increased competition for nitrogen in communities containing four species, but no legume. Moreover, labelling studies indicate a direct uptake of legume-derived nitrogen by grasses (Gubsch et al 2011). Overall, the nitrogen concentration of grasses growing in legume communities (4+) was not affected by drought, but showed changes in response to drought in the other communities. The higher stability in this communities and the possible fertilization effect of the legume support other studies which have shown an enhancement of the nitrogen availability for plants growing in legume communities (Spehn et al. 2002; Temperton et al. 2007; Dybzinski et al. 2008). Developmental traits of S. littoralis and their relation to leaf chemical traits The mortality of larvae was high, as the experiment was started immediately after hatching of the larvae, when they are quite vulnerable. Furthermore, H. lanatus seemed to be a sub-optimal food source for S. littoralis, as larvae the same age from the same egg strain Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 85 grew better when feeding on Plantago lanzeolata and Trifolium pratense, under otherwise similar conditions. Nevertheless, as we expected mortality to be high, due to the results from a prior trial experiment, we included enough replicates in order to obtain a substantial data set for statistical analysis. The reported changes in leaf metabolites, related to the drought treatment and differences in the community compositions, clearly had an effect on herbivore performance. Mortality of larvae was higher in four-species communities without a legume compared to the other communities. Hierarchical partitioning showed that the mortality rate depended mostly on the protein content. These data hint towards a central role of proteins for the survival of the early instars. Other studies, too, showed poor larval survival under low nitrogen concentrations (Myers and Post, 1981; Cates 1987; de Bruyn et al. 2002). Larval development up to pupation was significantly longer for larvae fed on droughtstressed plants, which might increase predation risk and thus mortality under natural conditions (Benrey and Denno 1997). In accordance with Fischer and Fiedler (2000) and with Morehouse and Rutowski (2010), the prolonged developmental time of the larvae was linked to a reduced N-availability in drought-stressed leaves. It might be that larvae fed longer on Nlimited grass to reach a certain “growth target” (Raubenheimer and Simpson 1997). Such compensatory feeding on low quality tissue may be a common phenomenon (Schädler et al. 2007b). Drought also had positive effects on herbivore performance, irrespective of community composition: The increased pupal weight might be explained by a higher uptake of energy, as carbohydrate contents in leaves increased under drought and as larvae fed longer on drought plants, possibly caused by lowered nitrogen contents. Thus, the “imbalanced diet” when feeding on drought stressed plants caused firstly compensatory longer feeding, to reach a certain nitrogen level necessary for development, and secondly led to a higher energy uptake and higher pupal weights (Raubenheimer and Simpson 1997). RWC was negatively related to pupal weight, as presumably water dilutes nutrients or carbohydrates in wellwatered plants. The increased pupal weight was correlated with a lower pupal mortality of the larvae that had been fed from drought-stressed plants, which is in accordance to other studies (Fischer and Fiedler 2000). It should be reiterated that the samples for the leaf chemical analysis were taken on the last two days of the drought treatment, whereas the larval development lasted from approximately ten days before to ten days after the drought. Thus, larvae fed on leaves that experienced milder stress levels in their late stages, which might have alleviated the effects of Manuscript 2: How do extreme drought and plant community composition affect host plant metabolites and herbivore performance 86 extreme drought on leaf chemical traits (Huberty and Denno 2004). Further studies with a higher temporal resolution would make it possible to investigate the course of changes in leaf traits over the whole range of plant stress responses. Nevertheless, the present study reveals that different development parameters can be differently influenced by extreme drought, even though these only lasted for around half of the duration of their larval development. Furthermore we show that plant community composition (and therefore also competition and the presence of specific plant functional traits) alters leaf metabolism and thereby affects herbivores. Concerning the debate on the hypotheses on plant-stress (White1984) versus plant-vigour (Price 1991) we confirm other studies which show the dependence of herbivore performance on plant-stress level (Scheirs and de Bruyn 2005), investigated traits (Cornelissen et al. 2008) and insect-feeding guild (Larsson 1989; Koricheva et al. 1998; Huberty and Denno 2004), as our results differ from other drought experiments using different feeding guilds (EnglishLoeb et al. 1997; de Bruyn et al. 2002). Differences to other studies may also be attributed to our specific experimental conditions: Plants were grown in experimental communities in the field, not in isolated pots in the greenhouse. This ensures more realistic plant growth conditions. In addition, the herbivores in our study have not been grown on the plants, but were fed in climate chambers, to more clearly relate the obtained results to changes in plant metabolites. Another reason for differences to other studies and prominent hypotheses might be that the plants were severly stressed, but also released from stress and recovered during the feeding experiment. According to Huberty and Denno (2004) this might have caused differences in herbivore performance when compared to feeding experiments under constant stress. Our study provides additional evidence that the nitrogen limitation hypothesis, stating that high nitrogen contents are beneficial for herbivore performance (White1984) does not seem to be widely applicable over all development traits and stages (Fischer and Fiedler 2000). Similar to Fischer & Fiedler (2000) our data provide hints that higher protein or nitrogen contents are beneficial for a faster rate of development and higher larval survival, although they might reduce adult eclosion. Conclusion Our findings suggest that extreme droughts, which are projected to increase in frequency with climate change, can also affect the development of herbivores. This is primarily caused by a Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 93 Important aspects are not only the persistence of species and substrate, but also the possibilities for species to recolonize (Nystrom and Folke, 2001). An overview on the various understandings of ecological memory is provided by Golinski et al. (2008). The complexity of the processes involved in the broad definition of ecological memory including temporal patterns up to evolutionary scales and spatial patterns up to landscape levels (Thompson et al., 2001), may limit its applicability in ecology as well as the possibility to assess and measure such a memory. It thus appears necessary to apply a reductionist framework to foster our understanding of the importance of ecological memory in times of global change (see Table 1 for examples and levels of ecological memory after disturbances). In the following, we focus on ecological stress memory of single individuals as a starting point. Ecological stress memory is defined here as any response of a single plant after a stress experience that improves the response of the plant towards future stress experience and which is assessed on a whole plant level (Fig. 1). negative response neutral response improved response no stress no stress stress stress acclimation recovery stress memory recovery acclimation stress memory Æimproved performance damage lagged stress effects collapse response to stress time negative response neutral response improved response no stress no stress stress stress acclimation recovery stress memory recovery acclimation stress memory Æimproved performance damage lagged stress effects collapse response to stress time Fig.1 Plant stress response under single and repeated stress without acclimation leads to stress damage (negative response), exhibiting acclimation (neutral response) and exhibiting an additional ecological stress memory (improved response). Acclimation helps to prevent stress damage and to promote recovery, despite often leading to reduced growth during stress. An ecological stress memory exists, when the plant keeps a sort of “stress imprint” after stress exposure that improves plant response to recurrent stress compared to plants without stress memory. Lagged stress effects are detrimental effects that occur some time after the stress occurred. Stress damage may lead to even greater damage or complete collapse when recurrent stress is applied Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 94 An ecological stress memory might involve the persistence of acclimation mechanisms and protective substances. However, it is not acclimation per se, as such a memory remains active long after the stress has been applied, and enables the plant to respond quicker and more adequate to a recurrent stress event. It thus requires a persisting “imprint” modifying future stress response. For acclimation, the plant does not need to experience real stress, as, e.g. for frost acclimation, certain environmental cues are sufficient to trigger acclimation within the seasonal life cycle performance. Ecological stress memory has a temporal dimension and, in this sense can only be studied after the stress stopped and the plant recovered, e.g. took up its pre-stress metabolism again and repaired or compensated damage. After applying recurrent stress, ecological stress memory should lead to an improved performance when compared to plants without a persisting stress memory. Contrastingly, lagged or delayed stress effects are detrimental effects of single stress events that become clearly apparent only after some time, e.g. when the plant dies or a community collapses (Fig. 1). The response of trees to drought, for instance, is often expressed in increased mortality but this may happen even several years after the drought event (Bigler et al., 2007). Likewise, alterations in soil frost events can lead to increased mortality of dwarf-shrubs after more than one year, but with no apparent effects in the first year after the stress event (Kreyling et al., 2010). Such lagged responses clearly indicate carry-over effects in fitness which are not easily detectable directly after the event and which may explain the findings of reduced resilience upon repeated stress events. For example, Lloret et al. (2004) investigated the impact of recurrent drought (1985 and 1995) on resprouting and die-back in Quercus ilex. They found a progressive loss of individual resilience upon recurrent drought, as the ability to survive and resprout was reduced compared to the first drought. Mueller et al. (2005) examined Pinus edulis and Juniperus monosperma mortality after extreme drought episodes and also found a reduction of resilience and a higher mortality rate for a recurrent drought in 2002 compared to the previous drought in 1996. It may have been that detrimental effects have persisted even after many years and plants may not have been recovered before the following stress exposure: Starch stocks in lignotubers of Q. ilex were found not to be restored to their pre-stress values even 10 years after an extreme drought (Lopez et al., 2009). Thus, to clearly distinguish such lagged stress effects from an ecological stress memory it may be necessary for experiments to apply a recurrent stress event and to compare the answer of recurrently stressed plants to single stressed plants. Only when the performance to recurrent stress is improved when compared to single stressed plants, the definition allows calling this an ecological stress memory. Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 95 In the following, we review mechanisms of drought tolerance and evidences for drought memory, of frost tolerance and frost memory as well as of heat stress tolerance and heat stress memory. 3. Drought tolerance and drought memory Plants are able to acclimate to drought stress, thereby increasing their drought tolerance. Mechanisms of acclimation include the accumulation of osmoprotective proteins, like dehydrins (Bohnert, 2000; Lambers et al., 2008), the accumulation of soluble sugars (Lambers et al., 2008; Walter et al., 2012), a reduction of the photosynthetic apparatus along with additional mechanisms to prevent damage by reactive oxygen species (Munne-Bosch and Alegre, 2000) and the accumulation of compatible solutes (proline, betaine) (Bohnert, 2000). Changes in gene expression that accompany drought acclimation are often ABAmediated, and upregulated genes include genes of the LEA family (late embryogenesis abundant) (Bohnert, 2000; Lambers et al., 2008). In addition to physiological changes, phenotypic and morphological responses can be initiated during drought stress, such as an increased root to shoot ratio or the development of roots in deeper soil layers (Newman et al., 2006). Some recent findings indicate the existence of an ecological drought memory: Walter et al. (2011) found an increase in photoprotection in single grass plants under repeated drought when compared to plants that were not subjected to drought previously, even several weeks after the first drought was applied and after the plants were completely cut and regrown (Fig. 2A). Similarly, Onate et al. (2011) showed that Urtica dioica subjected to combined drought and nutrient deficiency in their juvenile phase revealed improved drought stress tolerance in mature leaves, especially in reproductive shoots. Under laboratory conditions, Goh et al. (2003) found that Arabidopsis thaliana repeatedly subjected to high levels of abscisic acid (ABA), also involved in drought stress signaling and response, led to a formation of ecological stress memory, as gene expression was changed in response to following stress events compared to non-treated plants. Knight et al. (1998) observed changes in drought stress-induced calcium-signaling after plants had encountered either osmotic or oxidative stress previously. Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 96 Fig. 2 Examples for (A) ecological drought memory (adapted from Walter et al. 2011), (B) ecological heat memory (adapted from Whittle et al. 2009) and (C) for an ecological cross-stress memory (adapted from Kreyling et al. 2012b). Plants were either unstressed (light gray bars) or subjected to drought stress (A, C) or heat stress (B) (dark gray bars; pretreatment indicated on the y-axis) and performance was measured under subsequent drought (A), heat (B) or frost (C) stress (as indicated by inserts) in the same plants (A, C) or in the F 3 generation (B). Different letters indicate significant differences between plants with and without pre-stress according to the sources Cuk et al. (2010) showed that modified activity of antioxidative enzymes (catalase, ascorbate peroxidase), which are often also upregulated under drought, is inherited to the next generation of A. thaliana. It seems likely that maternal plants inheriting stress tolerance would reveal an ecological stress memory themselves. To sum up, there is evidence that certain physiological processes in plants are modified by former stress events. These modifications can be decisive in face of repeated events and may stimulate a faster start of protective mechanisms and increased stress tolerance and compensation. However, studies investigating this topic are rare and more studies investigating drought memory in different species and also under more natural conditions and studies comparing the response to recurrent drought manipulations to the response to single drought manipulations are needed in the future. 50 Seed number per plant P and F1 23°C P and F1 30°C F3: heat 500 1500 a b (B) Living biomass [%] 0 10 20 30 40 50 60 70 a b drought No previousdrought Previousdrought (A) a b No previousdrought Previousdrought frost Cold hardiness [LT50 °C] -40 0 -10 -20 -30 (C) 50 Seed number per plant P and F1 23°C P and F1 30°C F3: heat 500 1500 a b (B) 50 Seed number per plant P and F1 23°C P and F1 30°C F3: heat 500 1500 a b (B) Living biomass [%] 0 10 20 30 40 50 60 70 a b drought No previousdrought Previousdrought (A) Living biomass [%] 0 10 20 30 40 50 60 70 a b drought No previousdrought Previousdrought (A) a b No previousdrought Previousdrought frost Cold hardiness [LT50 °C] -40 0 -10 -20 -30 (C) a b No previousdrought Previousdrought frost Cold hardiness [LT50 °C] -40 0 -10 -20 -30 a b No previousdrought Previousdrought frost Cold hardiness [LT50 °C] -40 0 -10 -20 -30 (C) Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 97 4. Frost tolerance and frost memory In regions where subzero temperatures are reached, perennial plants show the potential to acclimate to frost to reduce frost damage, caused by intracellular ice crystals and dehydration. As apoplastic ice formation leads to cell dehydration, drought acclimation and frost acclimation often involve the same mechanisms, like accumulation of soluble sugars or transcription of dehydrins and LEA-genes (Lambers et al., 2008; Janska et al., 2010). Frost acclimation is triggered by low temperature and by changes in the photoperiod (Thomashow, 1999; Janska et al., 2010). Hardening usually takes several weeks, while dehardening, i.e. the loss of frost hardiness, can occur within hours after temperature increase (Rapacz et al., 2000), leaving the plants vulnerable to short-term late frost events during the growing season or after winter warming events. The frequency of frost days and nights is expected to decrease in various biomes under global climate warming (IPCC 2007), yet, an increase in minimum temperature over winter is unlikely (Kodra et al., 2011). Observed and projected reduction in snow cover, which acts as insulation for many plants, in combination with more variable air temperatures may further exacerbate the frequency of frost stress in many northern regions (Kreyling, 2010). As global warming may regionally lead to an earlier dehardening and onset of the growing season, the risk of late frost damage is likely to increase, when the timing of late frost events is not changing (Rigby and Porporato, 2008;Woldendorp et al., 2008). Furthermore, global warming might lead to more frequent freeze-thaw cycles during winter, possibly associated with (partial) dehardening after especially warm winter days, leading to frost damage at further sub-zero temperatures (Bokhorst et al., 2009). It is well established that plants are able to “remember“ low temperatures over a certain time span, as vernalization, the promotion of spring flowering favored by low temperatures requires some sort of winter-memory (Sung and Amasino, 2005). Here, we argue that cold tolerance acclimation is no ecological stress memory itself, as the plants harden under low temperatures but without experiencing frost stress. Cold acclimation rather is an evolutionary response to avoid frost stress. Experience of frost stress, for example during freeze-thaw cycles or under late frost events, could enable the plant to react differently to the next frost spell, even without prior acclimation. Tahkokorpi et al. (2007) found increased anthocyanin levels in spring in newly grown stems of Vaccinium myrtillus after plants had been subjected to frost stress in winter, Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 98 compared to plants not experiencing frost stress before. This strongly indicates an ecological frost stress memory on a whole plant level. Under laboratory conditions, Knight et al. (1996) found a modified calcium signature in A. thaliana after plants had experienced a cold shock before. Calcium acts as a second messenger in low temperature signaling and may therefore trigger altered response to repeated frost. However, Polle et al. (1996) showed that spruce needles surviving a spring frost event revealed less antioxidative enzymes and pigments in the following fall, thus probably showing reduced frost protection despite a transient increase in antioxidative enzymes after spring frost was applied. This shows that frost stress may lead to a loss of resilience rather than to the formation of a “positive” ecological frost memory. To sum up, few studies hint towards the existence of an ecological frost stress memory (Tahkokorpi et al. 2007; Knight et al. 1996), although the response to repeated frost stress has not yet been investigated. It remains to be elucidated if frost stress experience helps to survive subsequent frost stress, as one study also indicates a decrease in frost resistance after frost stress (Polle et al. 1996). 5. Heat stress tolerance and heat stress memory On a cell-level, heat stress acclimation is rather well understood: Upon exposure to extremely high temperatures, expression of normal housekeeping genes is stopped and heat shock proteins (HSP), which act to prevent protein damage or photo-oxidation and which repair already denaturated proteins (chaperones) are increasingly synthesized (Parcellier et al., 2003; Baniwal et al., 2004; Kotak et al., 2007). Furthermore, compatible solutes like prolin or betaine act to stabilize proteins (Schulze et al., 2005). Under global warming it is very likely that heat waves will increase in frequency and magnitude over most land areas, as indicated, e.g., by the European mega-heatwaves in 2003 and 2010 (Schär et al., 2004; Barriopedro et al., 2011; IPCC 2011). Yet, studies investigating an ecological heat stress memory are widely lacking in plant ecology. Interestingly, a transgenerational ecological stress memory was found for mild heat stress: Plants from the F3 generation showed a heat-specific fitness improvement when the parental and F1 generation had been treated with mild heat (30°C), even when the F2 generation was grown under normal conditions (Whittle et al., 2009) (Fig. 2B). As for all Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 99 transgenerational studies, the existence of ecological stress memory within one plant generation was not tested, but is implied by the inheritance of stress tolerance. To conclude, we found no study investigating an ecological heat stress memory in single plants. Nevertheless, the results by Whittle et al. (2009) indicate the existence of a heat stress memory improving heat tolerance after heat stress was already experienced in the past. 6. Cross-stress memory As frost, heat and drought stress all involve cell dehydration, acclimation mechanisms are partly the same (Beck et al., 2007). It is thus possible that acclimation and formation of a stress memory to one kind of stress also prevents damage by other stressors, providing crossstress memory and tolerance. For instance, frost tolerance of local populations or ecotypes, respectively, is related to drought tolerance (Blodner et al., 2005). More specifically, exposure to an extreme drought event in the preceding year was found to support late frost tolerance in grass species (Kreyling et al., 2012a) and maximum frost hardiness in juvenile Pinus nigra (Kreyling et al., 2012b) (Fig. 2C). Another form of cross-stress tolerance is increased herbivore resistance after the experience of abiotic stress like drought, caused by an increase in C-based secondary metabolites upon growth restriction due to abiotic stress (Herms and Mattson, 1992). It is unclear yet, how long such modifications of secondary compounds are maintained. However, Agrawal (2002) showed that the progeny of maternal plants attacked by herbivores also revealed higher induced resistance towards herbivores. This implies heritability and thus a form of stress memory of induced defense, although it is unclear if this could also act to prevent drought, heat or frost damage. 7. Possible mechanisms behind an ecological stress memory As possible mechanisms for an ecological stress memory, Bruce et al. (2007) suggest the accumulation of transcription factors or proteins to facilitate a fast response upon repeated stress exposure as well as epigenetic mechanisms, such as histone modifications or chemical changes at the DNA (methylation, acetylation) that are inherited through mitotic or even meiotic cell divisions (Bossdorf et al., 2008; Chinnusamy et al., 2008; Boyko and Kovalchuk, 2011). Another possibility is the accumulation of protective substances. However, this is not likely to be very important, as synthesis of protective substances is costly and often prevents Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 100 normal growth (Herms and Mattson, 1992). Today, it is well established that plant stress induces epigenetic changes (Goh et al., 2003; Chinnusamy et al., 2008). It was shown that epigenetic changes upon UV-C and flagellin exposure (Molinier et al., 2006), upon TMV (tobacco-mosaic-virus)-exposure (Boyko et al., 2007), upon pathogen or herbivore attack or low nutrients (Verhoeven et al., 2010) and upon nitrogen deficiency (Kou et al., 2011) are inherited. Furthermore, inherited DNA-hypomethylation in rice seedlings increased pathogen resistance (Akimoto et al., 2007) and inherited epigenetic changes upon TMV exposure increased pathogen resistance in progenies (Kathiria et al., 2010) However, no general heritability of epigenetic changes upon stress exposure was found in A. thaliana, implying that transgenerational epigenetic memory seems to be restricted to special conditions (Pecinka et al., 2009). The results of Tahkokorpi et al. (2007) hint towards epigenetic changes as underlying mechanisms of an ecological frost memory, as the new stems growing in spring never experienced frost stress themselves but revealed modifications (see Section 4). Thus, information had to be conveyed through mitotic divisions. A further possibility to retain an ecological stress memory are changes in phenology or morphology of the plant that remain stable over longer time scales than mere changes in the accumulation of protective substances. Shifts in root to shoot ratio in response to drought (Kalapos et al., 1996; Kahmen et al., 2005) or winter warming pulses (Kreyling et al., 2008) are one obvious morphological response with implications for future drought tolerance. Furthermore, specific leaf area can be adapted to drought conditions (Kalapos et al., 1996), thereby reducing water loss of this tissue also for future drought events (see Table 1 for examples of mechanisms of an ecological stress memory). 8. Research challenges Studies investigating ecological stress memory are rare. Most studies on the duration and heritability of plant stress are conducted on a cellular level and focus on genetic or epigenetic aspects. In such studies, time spans between the initial and the repeated stress is usually restricted to only several hours to days (Bruce et al., 2007). More ecologically relevant research and assessments of stress tolerance and ecological stress memory are needed. Furthermore, multigenerational epigenetic studies should consider consequences of extreme weather events more prominently. In order to evaluate the ecological relevance of ecological stress memory, assessing ecologically meaningful parameters at the plant level in controlled lab experiments needs to Manuscript 3: Ecological stress memory and cross stress tolerance in plants in the face of climate extremes 101 be accompanied by field experiments and observations after naturally occurring extremes. Here, long-term fieldand monitoring studies investigating the response to naturally occurring extremes in natural plant communities might be very valuable. To simultaneously elucidate underlying processes and mechanisms, cooperation between ecologists and molecular biologists are urgently needed. For instance, it is still unclear whether unseasonable frost damage in spring influences acclimation in the following fall and if this might be detrimental or beneficial. In particular the absolute degree and the temporal stability of ecological stress memory requires attention because ecological stress memory could play an important role in stabilizing ecological communities in the face of more frequent extreme climatic events. Here, we suggest that ecological stress memory can, at least partly, explain the surprisingly weak effects of repeated extreme drought events on the productivity of grassland communities (Jentsch et al. 2011). Heritability of beneficial stress memory to following generations, potentially by epigenetic processes, is another highly relevant aspect for our understanding of ecological response to more frequent extreme climatic events. To conclude, there are evidences for the existence of an ecological stress memory. However, mechanisms and consequences are not yet well investigated. A stress memory of single plants might act to stabilize plant communities under frequent climatic extremes and might increase resilience. It might be even possible to mitigate detrimental effects of extreme events by artificially applying milder stress on a small scale, e.g. for agriculture. However, it is not yet clear if, on a field and landscape scale, lagged detrimental effects might lead to a reduction of resilience under repeated extreme weather events that outweigh possible positive effects of an ecological stress memory. Furthermore, increased acclimation towards recurring stressors might reduce mortality of plants, but might as well reduce agricultural yield if plants reduce their photosynthetic activity to prevent damage. Hopefully, future research will contribute to elucidate mechanisms and consequences of an ecological stress memory. Acknowledgements: We thank two anonymous reviewers for valuable hints and comments to clarify our concepts and improve our manuscript. References: Agrawal, A.A., 2002. Herbivory and maternal effects: mechanisms and consequences of transgenerational induced plant resistance. 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Jentsch, A., Kreyling, J., Beierkuhnlein, C., 2007. A new generation of climate-change experiments: events, not trends. Frontiers in Ecology and the Environment 5, 365–374. Jentsch, A., Kreyling, J., Elmer, M., Gellesch, E., Glaser, B., Grant, K., Hein, R., Lara, M., Mirzae, H., Nadler, S., Nagy, L., Otieno, D., Pritsch, K., Rascher, U., Schädler, M., Schloter, M., Singh, B., Stadler, J., Walter, J., Wellstein, C., Wöllecke, J., Beierkuhnlein, C., 2011. Climate extremes initiate ecosystem-regulating functions while maintaining productivity. Journal of Ecology 99, 689–702. Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 109 Germany (49°55´19´´N,11°3455``E, 365 m asl). Tubes were embedded into the homogenized soil (loamy sand consisting of 82 % sand, 13 % silt, 5 % clay to a depth of 80cm). Plants were kept under natural ambient conditions for two years and harvested twice per year. Furthermore, tubes were periodically weeded. In April 2009, tubes, including the soil, were arranged under a rain-out-shelter for the experiment. To avoid the lateral flow of water into the pots, they were placed on plates on a plastic sheet. The transparent rain-out shelter was left open at the side up to 80 cm, allowing air exchange near to the surface and thus avoiding greenhouse-effects. Plants were subjected to two different treatments and arranged in a completely randomized design: 28 plants in the recurrent drought treatment (two plants died in the two years before the experiment started) were subjected to an early drought in June 2009 (D1), whereby water was completely withheld for 16 days from June 3rd until June 18th. The same plants were subjected to a later drought (D2), whereby water was withheld for 16 days from September 4th to September 19th. The recurrent drought treatment was compared to a single drought treatment: 27 replicates (three plants died prior to the experiment) were watered regularly every third day with 300ml rain water (C1) while the first drought period was applied to double-stressed plants. C1 plants were exposed to their first drought in September (C2), concomitant to the second drought of the recurrent drought treatment (See Fig. 1 for an overview). Fig. 1 Overview on the experimental time course and on applied treatments. In June, drought was applied for 16 days to D1 plants, while C1 plants were watered regularly. All plants were watered after the 16th day until the onset of the late drought in September. In September all plants (D2 and C2) were subjected to the drought for 16 days and were watered after that. Only in comparing plants subjected to a second, late drought (D2) to plants experiencing their first drought (C2) at the same point in time, we could prevent confounding of potential drought memory effects with seasonality or timing effects. A comparison between the response to the first drought in June and the response to the second drought in September is thus not valid to investigate potential drought memory effects. We also did not have a wellwatered control in September, as we were interested in a potential “drought-memory”, which can only be investigated by comparing single-stressed with double-stressed plants. To quantify effects of a single, early drought (D1), drought plants were compared to wellwatered plants during the first drought period (C1). All plants were watered with the same June 3rd-18th Sept. 4th-19th D1 C1 D2 C2 droughted watered June 3rd-18th Sept. 4th-19th D1 C1 D2 C2 droughted watered Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 110 amount of water (300 ml, every third day) until the onset of the experiment and in between the two drought treatments. 2.2. Aboveground biomass Aboveground biomass was harvested on July 5th, 17 days after the first drought (D1 and C1) ended, and on October 9th, 21 days after the second drought ended (D2 and C2). After this time, reversible drought damages should have been recovered. As we only compare D2 with C2 plants and D1 with C1 plants, the difference of four days in recovery time after drought does not have an effect on the results. Plants were cut 4 cm above the ground in order to simulate common management techniques in meadows, sorted into living (green) and dead biomass. Dead biomass was defined as wilted, brown plant parts that lost chlorophyll. Biomass was dried at 70° C for 72 hours and weighed. Percentage of dead biomass was calculated as percentage of oven-dried, dead biomass in relation to overall oven-dried biomass of individual plants. 2.3. Relative leaf water content (RWC) Relative leaf water content was determined in the afternoon of the 13th day of the first and second drought treatment (June 15th and September 16th), according to Barrs and Weatherley (1962).The second lowest leaf of each plant was cut, stored in a moistened plastic bag for transport, and immediately weighed to determine fresh weight (FW). Leaves were stored in distilled water at 4° C over night and weighed the next morning to determine turgid weight (TW). Afterwards leaves were dried at 70° C and the dry weight (DW) was determined. RWC was calculated as: 100* )( )( (%) DWTW DWFW RWC − − = 2.4. Chlorophyll a fluorescence Chlorophyll a fluorescence was recorded using a pulse-amplitude-modulated photosynthesis yield analyzer (PAM 2000 and Mini-PAM) (Waltz, Effeltrich, Germany) with a leaf clip holder as described by Bilger et al. (1995). The second or third fully-expanded leaves were measured on four different blades of one individual. Four measurements per plant were averaged for further analysis. We obtained predawn fluorescence values (between 2:00 and 4:00) at the end of the first drought treatment, throughout the second drought period and Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 111 throughout the early recovery phase after the second drought. The maximum quantum efficiency of photosystem II was calculated as Fv/Fm. Variable fluorescence (Fv) and maximum fluorescence (Fm) were measured before dawn. Fv was calculated as Fm-F0, Fm being the maximum fluorescence of the dark adapted leaf after applying a saturating light pulse and F0 being the steady state fluorescence yield of the dark adapted leaf (Maxwell and Johnson, 2000). To enable a comparison between absolute fluorescence values, a fluorescence standard material was measured before and after each measuring cycle. Standard measurements were used to normalize the fluorescence values obtained and to calibrate the two different PAMs in use. Predawn measurements of fluorescence at the dark adapted leaf allow drawing conclusions about underlying processes which alter plant photosynthetic performance and about photoinhibitory damage and non-photochemical quenching (Maxwell and Johnson, 2000). Absolute F0 and Fm values were taken to separate the effects of photodamage, becoming apparent with an increase of F0, from the effects of photoprotection related to enhanced non-photochemical quenching, becoming apparent with a decrease in Fm (Osmond et al., 1993; Araus et al., 1998; Maxwell and Johnson, 2000). 2.5. Leaf gas exchange The net CO2 assimilation rate (Pn) and transpiration were measured at midday (between 11:30 and 13:30), when drought stress should be at its maximum, due to high temperature and irradiance. It was measured on the second, fully developed leaf of each plant using a gas-exchange system (Li-6400, Li-Cor, Lincoln, NE, USA) equipped with a CO2 cartridge to adjust and maintain constant CO2 of 400 μmol mol–1 air within the leaf cuvette. Gas exchange measurements were conducted on clear days without clouds to maintain constant PPFD. After reaching steady-state photosynthesis, data were logged. The leaf area was estimated simultaneously by measuring the leaf width and later on used to correct values for net photosynthesis, as leaf blades did not fill the whole leaf cuvette. Gas exchange was measured under ambient light conditions at the end of the first drought period, in the early and late drought period and in the early recovery phase after the drought. 2.6. Statistical analysis To determine significant differences between single and recurrent drought treatments, analyses of variance were performed for all variables for each sampling date. We defined “treatment” as a fixed factor. “Provenance” was a random factor in this experiment, as Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 112 provenances were chosen randomly out of a larger population of provenances, and as we were not interested in the specific provenances, but in the whole population of our plants (Dormann and Kühn, 2009). We examined the residuals against fitted plots and normal qq-plots prior to each analysis to test whether the assumptions for ANOVA, homogeneity of variances and normality, could be met (Faraway, 2006). If this was not the case, data were powertransformed (fluorescence data), log-transformed (absolute biomass data) or arcsintransformed (relative water content) accordingly. All statistical analyses were performed using R 2.11.0 (R Development Core Team 2010). For mixed effect models we used the software package nlme (Pinheiro et al., 2008). 3. Results 3.1. Effects of the first drought (D1) Temperature [°C] 10 12 14 16 18 20 22 24 26 28 0 2 4 6 8 10 12 14 Precipitation [mm] 0 5 10 15 20 8 10 12 14 16 18 20 22 24 26 Average Temperature Maximum Temperature Day of experiment 0 5 10 15 Precipitation (a) (b) Temperature [°C] 10 12 14 16 18 20 22 24 26 28 0 2 4 6 8 10 12 14 Precipitation [mm] 0 5 10 15 20 8 10 12 14 16 18 20 22 24 26 Average Temperature Maximum Temperature Day of experiment 0 5 10 15 Precipitation (a) (b) Temperature [°C] 10 12 14 16 18 20 22 24 26 28 0 2 4 6 8 10 12 14 Precipitation [mm] 0 5 10 15 20 8 10 12 14 16 18 20 22 24 26 Average Temperature Maximum Temperature Average Temperature Maximum Temperature Day of experiment 0 5 10 15 Precipitation (a) (b) Fig. 2 Course of daily maximum temperature (grey squares), daily average temperature (black circles) and precipitation (dark grey bars) at the study site during the experimental periods in June (a) and September (b). Vertical black line indicates the start of the drought treatment, grey dashed line indicates when rewatering started. Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 113 Temperature and precipitation data during the experimental period in June are shown in Figure 2. Early drought treatment (D1) in June significantly reduced the relative leaf water content measured at the end of the drought treatment compared to the well-watered control (C1) by around 22% (P<0.001; Fig. 3a). C1 D1 Relative leaf water content [%] 020 40 60 80 100 (a) Pn [µmol CO 2 m -2 s -1 ] 02 4 6 8 10 12 (d) C1 D1 Fv/Fm 0.0 0.2 0.4 0.6 0.8 1.0 (c) C1 D1 C1 D1 Living biomass [%] 0204060 80 (b) C1 D1 Relative leaf water content [%] 020 40 60 80 100 (a) Pn [µmol CO 2 m -2 s -1 ] 02 4 6 8 10 12 (d) C1 D1 Fv/Fm 0.0 0.2 0.4 0.6 0.8 1.0 (c) C1 D1 C1 D1 Living biomass [%] 0204060 80 (b) Fig. 3 Effects of the first drought (D1) in June (dark grey) compared to well-watered control plants (C1) (light grey) on relative water content of leaves (a), percentage of living biomass (b), maximum quantum efficiency Fv/Fm, measured predawn (c), and net photosynthesis Pn, measured during midday (d). Relative leaf water content (a) was measured three days before the end of the drought treatment, maximum quantum efficiency Fv/Fm (c) and net photosynthesis Pn (d) were recorded on the last day of the drought treatment. Total aboveground harvest was conducted 17 days after the end of the first drought treatment and the percentage of dead biomass (dry weight) (b) was calculated. Means and SE are shown, asterisks indicate significance (*, P≤ 0.05; **, P≤ 0.01; ***, P≤ 0.001). Early drought treatment (D1) had no effect on the total aboveground biomass when compared with the well-watered control treatment (C1) (data not shown). However, drought Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 114 reduced the percentage of living biomass significantly by around 15% (P=0.03; Fig. 3b). On the last day of early drought treatment (D1) the photochemical efficiency (Fv/Fm) of plants under drought was significantly reduced compared to the well-watered control (P=0.004; Fig. 3c). Plants under early drought treatment (D1) exhibited reduced net photosynthesis by 58% on the last day of the early drought treatment (P<0.001; Fig. 3d). 3.2. Effects of recurrent drought events (D2) compared to a single drought event (C2) in September 3.2.1. Temperature, Relative leaf water content and productivity in the second drought period Average daily temperatures during the experimental period in September ranged between 10°C and 20°C (Fig. 2b). The maximum temperature was exceptionally high with 25.5° C on the 6th day of the experiment in September and lowest on the 11th day of the experiment with 12.3° C. The withholding of water was reflected in the relative water content of the leaves, which was reduced to around 65% but did not reveal any differences between single and recurrently dried plants (D2 vs. C2: P=0.38, Fig. 4a). C2 Relative leaf water content [%] 02040 60 80 D2 (a) Living biomass [%] 0 10203040506070 C2 D2 (b) C2 Relative leaf water content [%] 02040 60 80 D2 (a) Living biomass [%] 0 10203040506070 C2 D2 (b) Fig. 4 Leaf water status at the end of the second drought period 13 days after water had been withheld (a), and percentage of living biomass for the second harvest, three weeks after the end of the drought treatment (b). Means +/- 1 SE are shown, asterisk indicates significance of difference (*, P≤ 0.05). Plants in single and recurrent drought treatments produced an almost equal amount of overall (living and dead) aboveground biomass (1.47g in recurrent drought treatment (D2) and 1.49g in single drought treatment (C2)). However, the percentage of living biomass, was increased significantly by 7% in plants subjected to recurrent drought (D2) compared to plants experiencing their first drought (C2) (P=0.048) (Fig. 4b). Total living biomass was increased Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 115 by 10% in recurrent drought treatment, although this effect did not prove to be significant (0.91g in recurrent drought treatment and 0.82g in single drought treatment, P=0.18). 3.2.2. Photosynthetic parameters With progressive drought stress, Fv/Fm in the single and recurrent drought treatment declined, reaching a minimum for the double-stressed plants (D2) on the 14th day of the experiment, two days before rewatering (Fig. 5a). Single-stressed plants (C2) already reached minimal quantum efficiency on the 11th day of the drought and Fv/Fm values rose again after that. The loss of leaf water and photochemical efficiency under extreme drought was reflected in a decline of net photosynthesis by more than 60% compared to net photosynthesis before the drought treatment started (D2 and C2) (Fig. 5b). Fig. 5 Course of maximum quantum efficiency Fv/Fm, measured predawn (a) and net photosynthesis, measured during midday (b) in A. elatius subjected to recurrent or single drought before and during the drought phase and rewatering in September. Dark grey dashed line indicates the start of the drought, black dashed line indicates the end of the drought and the start of rewatering in September. Means +/- 1 SE are shown, asterisk indicates significance of difference between single and recurrent drought treatments on single days (*, P≤ 0.05). Grasses under recurrent drought (D2) showed lower maximum quantum efficiency compared to plants exposed to a single drought (C2), from the eleventh day of the experiment until the end of measurements, 10 days after the onset of rewatering (Fig. 5a). This reduction was significant on the last day of measurements under the drought (14th day of the Rewatering 345678 Pn [µmolCO 2 m -2 s -1 ] Day of experiment 1 4 7 10 13 16 19 22 25 0.4 0.5 0.6 0.7 0.8 Fv/Fm C2single D2recurrent Drought (a) (b) Rewatering 345678 Pn [µmolCO 2 m -2 s -1 ] Day of experiment 1 4 7 10 13 16 19 22 25 0.4 0.5 0.6 0.7 0.8 Fv/Fm C2single D2recurrent Drought (a) (b) Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 116 experiment, P=0.05) and on the first day after rewetting (17th day of the experiment, P=0.02) (Fig. 5a). During drought and in the post-drought recovery phase, plants subjected to single (C2) and recurrent drought (D2) did neither differ significantly regarding net photosynthesis, nor transpiration (transpiration data not shown). However, on the 14th day of the experiment, net photosynthesis of grasses subjected to recurrent drought (D2) was 25% lower compared to grasses being subjected to their first drought (C2), but this effect was not significant (P=0.11). A closer look at fluorescence parameters on both of these days with significant reductions in Fv/Fm (14th and 17th day of experiment) revealed that the decrease of Fv/Fm in plants subjected to recurrent drought can be explained by a decrease in Fm rather than by an increase in F0 (Table 2). Two days before rewatering, Fm was reduced by around 20% (14th day of the experiment, P=0.07). F0 was non-significantly reduced by around 6% (P=0.57). Fm was reduced by around 10% on the first day of measurements after rewetting (17th day of the experiment, P=0.3) as opposed to F0, which was reduced by only 0.5% in plants subjected to recurrent drought (P=0.94) (Table 2). Table 2 Maximum fluorescence (Fm) and steady state fluorescence (F0) two days before rewatering (14) and one day after rewatering (17) in the recurrent and single drought treatment during the experimental period in September. Means +/- 1 SE are shown (n=5). day of experiment 14 17 Fm single 0.696 ± 0.0031 0.793 ± 0.0026 recurrent 0.553 ± 0.0030 0.718 ± 0.0025 F0 single 0.157 ± 0.0001 0.170 ± 0.0001 recurrent 0.148 ± 0.0001 0.169 ± 9.9e-5 Fv/Fm of both treatments recovered gradually after the drought treatment ended, reaching predrought values ten days after rewatering had started, on the 26th day of the experiment (Fig. 5a). One week after rewetting, net photosynthesis had been almost completely restored, showing reductions of only 9% compared to pre-drought values. 4. Discussion This study investigated, whether A. elatius plants of six midand eastern European provenances can remember drought stress over an entire vegetation period even after a harvest. We hypothesized that plants would not show different performance under recurrent drought. This hypothesis was not confirmed, as grasses responded consistently different in recurrent drought as compared to a single drought, indicating enhanced photoprotection. Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 117 Surprisingly, this effect persisted after total aboveground biomass harvest and regrowth. The observed changes in reaction to recurrent drought are not in accordance with findings indicating reduced resistance or resilience after having already been exposed to drought stress before (Lloret et al., 2004; Zavalloni et al., 2008 ). However, these were conducted under field conditions and Zavalloni et al. (2008) investigated community responses. Thus, different outcome of the experiments are not surprising. The findings are in accordance with reported stress imprint effects or stress memory (Bruce et al., 2007). However, to our knowledge, no study has already provided evidence that grasses do remember drought stress even after a harvest and can exhibit improved performance in the face of repeated abiotic stress over such a long duration. Stress imprint and acclimation were previously mostly reported to last for “several days” (Bruce et al., 2007). Under severe drought, grasses experiencing recurrent drought showed reduced maximum quantum efficiency Fv/Fm (Fig. 5a). This was mainly related to reductions in maximum fluorescence, indicating enhanced dissipation of light energy to prevent photodamage (Maxwell and Johnson, 2000). Osmond et al. (Osmond et al., 1993) and Araus et al. (Araus et al., 1998) suggest that a correlation of reduced Fv/Fm with an increase of F0 can be interpreted as chronic photoinhibitory damage due to the degradation of the D1 protein in the reaction centers. By contrast, a constant F0 and decreasing Fm values, as in our study, point towards photoinhibition related to enhanced non-photochemical quenching via the Xanthophyll cycle and thus indicate photoprotection (Araus et al., 1998). Another possible explanation of decreased Fv/Fm caused by reduced Fm values might be a reduction of chlorophyll. Unfortunately, we did not measure chlorophyll content in our study. However, a reduction of chlorophyll can be considered as a feature of acclimation, as it reduces the possibility of photodamage because of an excess of energy (Munne-Bosch and Alegre, 2000). Net photosynthesis did not reveal any differences between grasses under recurrent (D2) and single drought (C2), but showed a trend towards lower photosynthesis in plants receiving recurrent stress under extreme drought (Fig. 5b). This is in accordance with the reduced photochemical efficiency in plants recurrently experiencing drought (D2). The results of the aboveground biomass support the hypothesis of enhanced photoprotection of double-stressed plants, as the percentage of living biomass was significantly increased in plants experiencing their second drought, although total aboveground biomass or total living biomass were not significantly altered. Plants can adapt to drought by enhancing root growth. However, relative water content of the leaves was not significantly enhanced in plants experiencing recurrent drought, Manuscript 4: Do plants remember drought? Hints towards a drought memory in grasses 118 indicating that the observed results can not be explained by changes in root biomass or improved water uptake mechanisms. Ecophysiological measurements did not reveal any consistent differences between recurring (D2) and single drought (C2) in the post drought recovery phase. Maximum quantum efficiency two days after rewetting in grasses subjected to recurring drought was significantly lower compared to grasses subjected to their first drought. This was more likely related to increased stress levels under drought rather than a lower recovery rate. Some studies indicated that recovery rate depends on experienced stress level (Miyashita et al., 2005; Resco et al., 2009). The significantly lower percentage of dead biomass in plants subjected to recurring drought can be a sign of quicker recovery, but is more likely to be a sign of improved photoprotection, as discussed above. In accordance to other studies, the recovery of ecophysiological parameters was quite fast, almost reaching pre-stress levels after about one week (Galle et al., 2007; Galmes et al., 2007). We did not elucidate underlying molecular or biochemical mechanisms for acclimation in this study, as we were interested in the effects or recurrent drought on agricultural relevant performance parameters. Thus, we can only hypothesize about potential long-lasting acclimation processes in the grasses. The observed phenotypic plasticity could be either explained by belowground dynamics or by long-lasting changes in gene expression, rendering the plants more permissive to react quickly to recurrent stress, e.g. epigenetic processes (Aubin-Horth and Renn, 2009;Molinier et al., 2006; Bird, 2007; Bossdorf et al., 2008). Verhoeven et al. (Verhoeven et al., 2010) recently showed that stress induces changes in methylation patterns and that these patterns are heritable. An investigation of the changes in methylation patterns as a response to drought and a link of observed methylation patterns to stress response are very promising. Furthermore, we could only investigate six provenances of A. elatius plants, which originated mainly from areas in Europe with quite similar climatic conditions. Other, more different provenances were not surviving in sufficient replicates for our study. Nevertheless, an extension of our experiment to other provenances and plant groups seems promising, as they may reveal different acclimation patterns and therefore also different responses to recurrent drought. 5. Conclusion To conclude, our study indicates that grasses under drought retain a long-lasting stress imprint that facilitates a faster and more protective response towards a recurrent drought. Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 125 Here, eight provenances of P. nigra from autochthonous origins and from southern Germany were tested for their cold hardiness in a common garden experiment in southern Germany. We hypothesized that (1) cold hardiness differs between provenances, with provenances from colder origins displaying superior cold hardiness, and that (2) cold hardiness is affected by climatic experiences of the individuals with drought increasing cold hardiness and warming decreasing cold hardiness. We further expected that (3) differences in cold hardiness between provenances are physiologically-related to the content of soluble carbohydrates and lipid composition of the needles, and that (4) the (sub-) mediterranean species P. nigra is less frost-tolerant than tree species native to Central Europe, while (5) cold hardiness of the fine roots of P. nigra is high compared to cold hardiness of its foliage as it naturally occurs in regions without continuous snow cover. 2. Material and methods Juveniles of P. nigra from eight provenances throughout Europe were exposed to different climate change scenarios (warming and extreme drought) in a common garden experiment. Cold hardiness was determined by the Relative Electrolyte Leakage method (REL) in two consecutive winters. The experiment was established in Bayreuth, Germany (49°55’19” N, 11°34’55” E) in March 2009. The long-term mean annual temperature for the site is 8.2°C, whereas long-term mean annual precipitation is 724 mm. 2.1. Experimental design Eight provenances of P. nigra (Figure 1; Table 1) were obtained as seeds and cultivated at the Bavarian Institute for Forest Seeding and Planting (ASP) in Teisendorf, Germany from April 2008 to April 2009. Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 126 Figure 1: Origins of the target provenances (open circles) within the distribution of P. nigra (black lines and dots for fragmented populations Isajev et al., 2004). X indicates the experimental site. Abbreviations of provenances are specified in Table 1. Grey scales display the mean minimum temperature for the period 1950 to 2000 with a 5’ spatial resolution (Hijmans et al., 2005). These provenances are part of an international long-term provenance trial which started in 2009 (Huber, 2011). The provenances stem from autochthonous populations of P. nigra except for the provenance from Zellingen, Germany, which was introduced from Austrian sources in 1909. Subspecies identities of the provenances are assigned geographically and morphologically (Table 1), as genetic analyses are not yet available (Huber, 2011). Table 1 Origins of target provenances used in the experiment with corresponding climatic information. Skie: Identification number in an international provenance trial (Huber, 2011). MAT: Mean Annual Temperature; MinT: Mean Minimum Temperature; MAP: Mean Annual Precipitation; Precip. Seasonality: Coefficient of variation in mean monthly precipitation sum. All climate data for the period 1950 to 2000 from worldclim (Hijmans et al., 2005). Provenance Country Subspecies Skie North East Altitude (m) MAT (°C) MinT (°C) MAP (mm) Precip. Seasonality DE Germany nigra 01 49°53'17" 09°43'16" 290 9.2 -3.1 587 18 AU Austria nigra 07 47°46'00" 16°11'00" 369 8.4 -4.9 712 33 YU Serbia nigra 12 43°49'39" 19°35'22" 866 8.7 -5.6 964 17 HR Croatia nigra/ dalmatica 14 43°26'00" 17°13'00" 256 13.2 1.2 1108 33 IT.N Italy nigra 17 45°42'00" 13°49'00" 372 11.4 -1.2 1212 17 IT.S Italy laricio 19 39°18'08" 16°20'22" 1500 9.0 2.2 1300 48 FR1 France nigra 23 44°09'10" 05°52'30" 549 10.7 -2.9 789 16 FR2 France laricio 24 44°24'18" 03°58'39" 581 10.8 -0.9 745 19 Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 127 The Croatian provenance stems from a location very close to one of the few autochthonous stands of P. nigra subspecies dalmatica and its assignment to the subspecies nigra is somewhat questionable. The seedlings were transported to Bayreuth and individually planted into 4-litre plastic pots filled with sandy silt (pH 7.3, total C 1.9%, total N 0.15%, plant available NO3--N 22.5 mg l-1; plant available NH4+-N 1.8 mg l-1). Selection of the plants occurred randomly for each provenance from all those plants alive at the planting date. The mean plant size at the start of the experiment was 12.2 cm ± 2.5 cm SD. The potted individuals were exposed to the fully crossed threefold factorial combination of (1) a drought manipulation (drought and control) and (2) a continuous warming manipulation (warming and reference) and (3) the provenance treatment (eight provenances). The two climate treatments were crossed resulting in four climate manipulations (control, drought, warming, warming & drought), that were replicated three times, resulting in 12 experimental units in total. The provenance treatment was nested within each experimental unit. Each provenance was further replicated with seven plants per experimental unit (nested replicates), resulting in 21 plants per factorial combination of the three-factorial design and 672 plants overall. Each experimental unit was covered by a single rain-out shelter (11 m by 7 m, 3.8 m high) constructed of a steel frame (GlasMetall Riemer GmbH) and covered with a transparent polyethylene sheet (0.2 mm, SPR5, Hermann Meyer GmbH) enabling an almost 90% penetration of photosynthetically-active radiation. The edge of the rain-out shelters was at a height of 80 cm. The control irrigation regime simulated the local daily 30-year average precipitation. The application was carried out twice a week with collected rain water. The drought treatment consisted of 42 days without precipitation, which represents the local statistical 1000-year recurrence drought event. Drought duration was not a priori set before the manipulations. We monitored plant performance during the treatment and would have stopped the treatment when either 66% of the plants showed water stress symptoms (discoloration of foliage) or when 33% of the plants exhibited lethal stress, or when the local 1000-year extreme would be reached. The latter condition was set because we assume that events with more than 1000 year recurrence time are not too realistic even when changing frequencies of extremes due to climate change are acknowledged (Schär et al., 2004). The same protocol was applied in a parallel experiment with four grass species (Beierkuhnlein et al., 2011), which all showed severe drought symptoms after about 20 days, emphasizing the high drought tolerance of Pinus nigra. The drought treatment started on May 27th 2009 and resulted in the soil moisture Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 128 falling below the permanent wilting point (pF = 4.2) of the soil approximately three weeks after the start of the treatment (Figure 2). In the re-wetting phase each individual in the drought treatments received 240, 280 and 300 ml on three days within one week (in total 820 ml or 36 mm). Following that, the pots were irrigated according to the control precipitation treatment. Total amount of precipitation in the drought treatment was 13% lower than in the control over the year. The drought was simulated in the first year of the experiment only. Throughout the second year, all plants received control irrigation. Figure 2: Temperature at mean plant height, snow cover and soil moisture (-2.5 to -7.5 cm) over the course of the experiment. Sampling dates are indicated by arrows. The warming treatment was performed continuously until October in the first year of the experiment and from April to the end of the experiment in January of the second year. The warming manipulation took place both passively (wind-shelters which reduced the wind speed by 70 % and black floor-covers versus white floor covers) and actively (IR-radiation with approximately 30 W per m²), which increased the air temperature at plant height by 1.6°C on average when the warming treatment was affected (Figure 2). Maximum differences were 5.2°C (single measurements) or 3.6°C for daily mean temperature. The fourth treatment was a combination of drought and warming. The warming increased the drought effect, reducing the soil moisture by another 1.5% on average (Figure 2). Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 129 During the first winter of the experiment, plants were kept outside the shelters in a sand bed from October to April. Figure 2 illustrates that the plants were covered by snow during the coldest parts of the first winter. For the second winter, plants were kept inside the shelters with the warming treatment ongoing. 2.2. Response parameters Cold hardiness was quantified by a slightly modified version of the relative electrolyte leakage method (REL) of ex-situ samples according to Strimbeck et al. (2007): Pre-tests revealed no differences in absolute values when the samples were frozen with or without 1ml solution containing an ice nucleator, presumably because the surface of the samples was wet and froze at around 0°C anyhow. Furthermore, higher freezing rates were applied. At a rate of 0.6°C/h (Strimbeck et al. 2007) it would have taken 3.5 days to reach our minimum temperature, whereas commonly the rate of 6°C/h is applied (e.g. Sutinen 1992, Schaberg 2008). Two needles from the current year were sampled per individual in mid-winter of both years (January 20th in 2010 and January 31st in 2011), rinsed with de-ionized water, and cut to 0.5 cm. Samples from the seven nested replicates per provenance and experimental unit were combined to form one mixed sample, homogenized and subsequently divided into seven subsamples subjected to different temperature levels for one hour (+4.5°C, -7.5°C, -14.5°C, - 23°C, -33°C; -40°C, -196°C (liquid N)) using a controlled environment chamber (LichtThermostate Typ 1301, RUMED) and a manually controlled chain of freezers sequentially at the lowest temperatures. Initial electrolyte leakage was determined in 16 ml 0.1% v/v Triton X-100_Bidest after 24 h and the final electrolyte leakage was determined after autoclavation of the samples. Electrolyte leakage was quantified by the conductivity of the solution at 25°C measured with a WTW inolab pH/Cond 720. Cold hardiness is expressed as the LT50 for each mixed sample, estimated by non-linear regression of the REL versus the temperature levels using the formula by Anderson et al. (1988): (1) YT is the REL at temperature T, Ymin is the asymptotic value of the response variable in uninjured tissue, Ymax is the asymptotic value at maximum low-temperature stress, k represents the steepness of the response curve, and Tm is the midpoint of the symmetrical curve (an estimate of LT50). Curve fitting was carried out using a quantile regression and the function “nlrq()” from the software package “quantreg” (Koenker, 2006). Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 130 The multitude of different technical protocols for REL used in the literature (freezing with or without additional solution, various freezing rates and durations, etc.) limits the comparability between studies strongly. However, the relative differences within a protocol should be robust and more or less independent of e.g. freezing rates (Sutinen et al 1992). Therefore, we stick to the interpretation of relative differences within our study and minimize the discussion of absolute values. Cold hardiness of needles from the current year or terminal buds was additionally determined for juvenile and adult individuals of the most important local tree species (P. sylvestris, Picea abies, Fagus sylvatica and Quercus petraea). Samples were taken on 26th of January in the first winter. Three mixed samples of seven individuals each were obtained from a nearby forest (lowland site: 350 m asl) and, for the juvenile stage of the two conifers, from a highland site (Waldstein, Fichtelgebirge, 760 m asl) about 50 km northwest of the experimental site. In the second winter, carefully excavated fine roots of two provenances (FR1 and IT.S) exhibiting low and high cold hardiness in their foliage in the first year were analyzed for their cold hardiness by applying the same protocol as for the needles. Mean annual minimum temperatures for the period 1950 to 2000 (mean temperature of the coldest day for the years 1950-2000) for each geographic origin of the provenances were retrieved from worldclim (Hijmans et al., 2005) and used as indicators for minimum temperatures (Table 1). We assume that the relative differences between geographic origins have been suitably reflected, although these values exceed the absolute minimum temperatures due to daily averaging (for our experimental site the minimum temperature based on worldclim is -3.5°C while the absolute annual minimum temperatures between 1998 and 2011 at an hourly resolution ranged between -10.8 and -25.5°C). An ordinary least squares regression between this indicator and cold hardiness was applied for the control treatment in order to detect local adaptation to late frost events. Soluble carbohydrates were quantified in the first winter for two provenances exhibiting low and high cold hardiness, respectively (FR1 and IT.S). Mixed samples of one needle from the seven plants per experimental unit were taken, immediately frozen in liquid nitrogen and stored at -30°C. Frozen material was ground in a ball mill; soluble carbohydrates of 20 mg of plant material were extracted in 50 % methanol and analyzed using the anthrone method (Kleber et al., 1997). Extinction was measured at 620 nm. We used known concentrations of Glucose as a standard. Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 131 Lipid composition was obtained for the same two provenances (FR1 and IT.S). Epicuticular wax lipids including alkanes as the most abundant wax component were recovered by rinsing needles for 60 seconds in dichloromethane (DCM), which resembles standard techniques using chloroform (Radler and Horn, 1965). After removal of the epicuticular wax lipids, needles were ground to a fine powder using a ball mill (Retsch M200). Internal waxes were recovered by standard Soxhlet extraction using a mixture of DCM/Methanol (93:7) (Wiesenberg et al., 2010). Extracts of internal and epicuticular waxes were dried and sequentially separated using solid-phase extraction into lipid fractions including fatty acid and alkane fractions (Wiesenberg et al., 2010). The following section only discusses the results of the alkane fraction as a representative component of epicuticular wax lipids and the fatty acids of internal lipids as the dominant compound class of cell membranes. Other fractions were also analyzed, but no significant differences in their distribution patterns were obtained. Aliquots of deuteriated standards (D39C20 acids and D50C24 alkane, respectively) were added to the lipid fractions for compound identification and quantification. Fatty acid fractions were derivatized using BSTFA (N,OBis (trimethylsilyl) trifluoroacetamide) for 1h at 80°C, whereas alkanes did not require any further preparation. All fractions were measured using gas chromatography coupled with flame ionization detection (Agilent 7890). In addition to lipid distribution patterns, molecular proxies were also determined to evaluate the differences between provenances and climate manipulations. The average chain length (ACL) of lipids is influenced by lipid biosynthesis and regulates the water repellency of hydrophobic hydrocarbon chains of fatty acids in cell membranes as well as fatty acids and alkanes in epicuticular waxes (Kolattukudy et al., 1976). Initially, the ACL was used to differentiate plant and microbial sources of organic matter in terrestrial sediments (Bray and Evans, 1961): ACL = Σ (zn * n) / Σ (zn) (2) where n is the number of carbons and zn the amount of fatty acids or alkanes with n carbons. Another parameter to obtain the differences in the lipid biosynthesis as affected by environmental stress is the predominance of odd versus even alkanes, the so-called carbon preference index (CPI: Kolattukudy et al., 1976): CPI = [(Σ n-C25-33 odd / Σ n-C24-32 even) + (Σ n-C25-33 odd / Σ n-C26-34 even)]/2 (3) The degradation of alkanes and a less effective synthesis of the predominant odd alkanes in waxes lead to a reduction of the CPI under environmental stress (Wiesenberg et al., 2008). Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 132 An analysis of variance (ANOVA) combined with linear mixed effect models were applied to test for the main and interactive effects of the three factors: provenance, drought, and warming on cold hardiness (LT50), soluble carbohydrate content and lipid composition. Including the experimental unit as a random factor accounted for the split-plot design (Pinheiro and Bates, 2004). Data were log transformed to improve the homogeneity of variances and the normality of residuals if necessary. All statistical analyses were conducted with the software R 2.11.1 (R Development Core Team, 2010) and the additional packages “nlme” and “quantreg”. 3. Results 3.1. Local adaptation in cold hardiness Mean cold hardiness differed between the provenances by about 10°C in both winters (Figure 3). Figure 3: Cold hardiness (LT50) as affected by geographic origin (provenances; left) and preceding climatic conditions (drought and warming in interaction; right) in the first (upper panel) and second (lower panel) year of the experiment. ANOVA-results are provided per year with significant effects in bold. Mean values and standard errors are shown for 84 individuals per bar for the provenances and 168 individuals per bar for the climate treatments. Note that the drought manipulation only took place in the first summer of the experiment. The warming treatment stopped three months before sampling in the first year while running throughout sampling in the second year. Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 133 The LT50 values ranged between a minimum of -21.2°C for provenance FR2 and a maximum of -32.1°C for provenance FR1 in the first winter; and between a minimum of -23.2°C for provenance FR2 and a maximum of -33.1°C for the provenance from Serbia (YU) in the second winter. Provenances from colder origins generally displayed superior cold hardiness (Figure 4). Significant correlations (r² = 0.77 in the first winter and r² = 0.80 in the second winter) between cold hardiness and mean minimum winter temperature at the origins were found for the autochthonous provenances in both years if the provenance from Croatia was excluded from the analyses. When included, no significant correlation was found in the first winter, while the correlation was weaker (r² = 0.59) while still remaining significant in the second winter. Figure 4: Local adaptation in cold hardiness depending on the mean minimum temperature at the origin. Linear regressions are shown for all autochthonous provenances (DE, open triangle, not included) excluding the provenance from Croatia (HR, open circle), as its autochthonous status is questionable. Results of the regression including the provenance from Croatia are given in parentheses. Cold hardiness (LT50) displays the mean of the control treatment per provenance (n = 21). 3.2. Climatic experiences alter cold hardiness Cold hardiness was affected by the climatic experiences of the individuals. The extreme summer drought increased cold hardiness by 3.9°C on average in the first winter and there was a non-significant trend in the same direction in the second winter after the drought manipulation (Figure 3). Unexpectedly, the summer warming from the first year resulted in increased cold hardiness of 3.4°C on average while the year-round warming of the second year resulted in no significant effect, although the trend followed the same direction as in the first year. Interestingly, the drought and the warming effect in the first year were not additive (ANOVA, interaction between drought and warming: F = 16.0; p = 0.004), resulting in lower Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 134 cold hardiness in the untreated variant and comparable, high cold hardiness in the other three climate manipulations (Figure 3). 3.3. Physiological reasons for varying cold hardiness The amount of soluble carbohydrates in the needles increased by 25.9% in a provenance exhibiting high cold hardiness compared to a provenance showing low cold hardiness (Table 2; ANOVA: F = 15.3; p = 0.004). The drought manipulation had no significant effect on the carbohydrate concentration (F = 0.0; p = 0.889). Table 2: Comparison of carbohydrate content and average chain length (ACL) of fatty acids of current year needles between two provenances exhibiting low (IT.S) and high (FR1) cold hardiness. Samples taken in the first winter of the experiment, mean ± standard deviation provided, n = 3. Cold hardiness of source Control Drought Cold hardiness (LT50 in °C) high -25.8 ± 2.3 -36.7 ± 1.0 low -17.5 ± 1.6 -26.8 ± 4.5 Soluble carbohydrates (‰TM) high 118.4 ± 9.4 111.9 ± 9.5 low 89.0 ± 15.9 93.7 ± 3.0 ACL of epicuticular wax fatty acids high 18.8 ± 0.2 17.7 ± 0.2 low 18.1 ± 0.0 17.8 ± 0.1 ACL of internal fatty acids high 17.8 ± 0.5 17.6 ± 0.1 low 17.5 ± 0.1 17.1 ± 0.3 ACL of epicuticular wax alkanes high 27.5 ± 0.1 27.6 ± 0.0 low 27.5 ± 0.1 27.5 ± 0.1 CPI of epicuticular wax alkanes high 9.3 ± 0.2 10.4 ± 0.2 low 12.0 ± 0.6 11.9 ± 0.4 The composition of internal fatty acids (ACL) as main components of cell membranes did not differ significantly between a provenance exhibiting high cold hardiness and a provenance showing low cold hardiness (F = 3.7; p = 0.092). Likewise, no effect of the drought manipulation was found (F = 1.7; p = 0.222). For the epicuticular wax lipids, the provenance with the high cold hardiness was characterized by a slightly higher ACL (3.9 %; F = 5.2; p = 0.051) than that with the low cold hardiness. The drought treatment led to a general decrease in ACL (F = 22.0; p = 0.002), which was stronger for the plants with a high (5.5 %) rather than a low cold hardiness (1.5 %; interaction between provenance and drought manipulation: F = 7.7; p = 0.024). Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 141 selection of frost-tolerant provenances could be based on the current climatic conditions within the species ranges. However, our finding that climatic experiences within the life of single plants alter cold hardiness indicates that provenance trials under control conditions may be misleading under changing climatic mean and extreme conditions. The multitude of possible climatic variables to be selected for and uncertainties concerning future climates imply that the search for best-adapted provenances should not be the only strategy. In addition, management actions which promote genetic diversity (e.g. supporting natural regeneration and addition of genetically diverse material) are crucial as genetic diversity enables organisms to continue adapting and evolving to new conditions within one or several generation cycles (Hosius et al., 2006; Schaberg et al., 2008b). Furthermore, the role of herbivores and diseases under changing climate requires detailed investigations. For instance, a needle blight known as the “red band disease” (Dothistroma septospora) is reported to increase in importance over recent years in P. nigra (Isajev et al., 2004), a development that may be related to climate change (Watt et al., 2011). Ultimately, tree species responses should be regarded in the context of populations under competitive pressure. The advantage of common garden experiments is that they can detect the spectrum of possible species-specific responses. Nevertheless, there is a need to test the obtained results in communities where the competitive balance might amplify or buffer responses. 5. Conclusions Cold hardiness of Pinus nigra foliage is highly variable between provenances and shows signs of local adaptation to prevailing minimum temperatures at the origin. Both severe drought events and summer warming can increase cold hardiness, indicating that the interaction of different climate parameters leads to unexpected results and that winter survival can be altered by climatic events during the growing season. Physiologically, cold hardiness is related to soluble carbohydrate content and lipid composition. Interestingly, variation of cold hardiness of the needles within the (sub-) mediterranean species P. nigra was higher than between this species and other species common to the temperate zone of Central Europe. Taken together, our results imply that the cold hardiness of the foliage of P. nigra is adaptive to long-term growing conditions at the origin (genetic heritage) and to short-term alterations of these conditions (individual plasticity), while first hints suggest that cold hardiness of the Manuscript 5: Cold hardiness of Pinus nigra Arnold as influenced by geographic origin, warming, and extreme summer drought 142 roots is high and probably not under selective pressure currently. Our data from mid-winter suggests that belowand above-ground cold hardiness of selected provenances appear to be well adapted to cultivation in temperate regions as an adaptation strategy against the adverse effects of climate change in dry habitats. However, with respect to late spring and early autumn frost events, the temporal pattern of frost hardiness with potential intra-specific differences should be investigated in more detail. 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Julia Waltera*, Kerstin Grantb∗, Carl Beierkuhnleinc, Jürgen Kreylingc, Michael Weberd, Anke Jentschb aConservation Biology, Helmholtz Centre for Environmental ResearchUFZ, Permoserstraße 15, 04318 Leipzig, Germany, [email protected], phone:+49-341-2351654, fax: :+49-341-2351470, corresponding author bDisturbance Ecology, Bayreuth University, 95440 Bayreuth, Germany cDepartment of Biogeography, Bayreuth University, 95440 Bayreuth, Germany dDepartment of Plant Physiology, Bayreuth University, 95440 Bayreuth, Germany Highlights 1. Grassland was subjected to increased rainfall variability and mowing frequency. 2. Increased rainfall variability reduces grassland productivity and forage quality. 3. More frequent mowing initially increases and later on decreases productivity. 4. Mowing regime does mostly not interact with rainfall variability manipulations. 5. Sufficient overall rainfall amount is important for grassland resilience. Abstract Climate models indicate that global warming will stimulate atmospheric exchange processes and increase rainfall variability, leading to longer dry periods and more intense rainfall events. Recent studies suggest that both the magnitude of the rainfall events and their frequency may be as important for temperate grassland productivity as the annual sum. However, until now interactive effects between land management practice, such as mowing frequency, and rainfall variability on productivity and forage quality have not been studied in detail. Here, we present the data from a field experiment (EVENT II) in which a CentralEuropean grassland was subjected to increased spring rainfall variability (low, intermediate and extreme rainfall variability without any change to the rainfall amount) and increased mowing frequency (four times compared to twice a year). We assessed biomass production, ∗ authors contributed equally to the publication Manuscript 6: Increased rainfall variability reduces biomass and forage quality of temperate grassland largely independent of mowing frequency 146 forage quality parameters, root-length and shoot-root ratio. Enhanced spring rainfall variability reduced midsummer productivity and the leaf N and protein concentrations of a target species, but did not exert any long-term effects on biomass production and forage quality in late summer. However, the increased spring rainfall variability reduced aboveground net primary productivity by 15 %. More frequent mowing increased productivity in the first year of the study, but decreased productivity at the end of the second year, showing a decline in the potential for overcompensation after a history of more intense mowing. Generally, more frequent mowing decreased the shoot-root ratio and increased the concentration of leaf N. Increased mowing frequency neither buffered, nor amplified the adverse effects of rainfall variability on productivity, but made leaf N concentrations in early summer more responsive to altered rainfall patterns. These results highlight the fact that even relatively small and short-term alterations to rainfall distribution can reduce production and forage quality, with little buffering capacity of altered mowing frequency. Comparisons with productivity data from the first year of the study, in which both, rainfall distribution and rainfall amount were modified, demonstrate the crucial role of sufficient moisture (annual rainfall amount) for grassland resilience: In this first year, negative effects of extreme rainfall variability lasted until the end of the year. To conclude, increased rainfall variability under climate change will likely affect agricultural yield in temperate meadows. Management strategies to buffer these effects have yet to be developed. Keywords: EVENT II experiment, extreme weather event, rainout-shelter, forage quality, Alopecurus pratensis, Trifolium pratense 1. Introduction Climate change is projected to modify not only annual precipitation sum, but also to result in more extreme rainfall regimes in many parts of the world (IPCC 2007; Jentsch and Beierkuhnlein, 2008). This will cause more severe drought periods as well as an increase in the frequency and magnitude of extreme precipitation events (Trenberth et al., 2003, Min et al., 2011). Evidence is mounting that the frequency and severity of droughts and extreme precipitation events has already increased over recent decades in many regions (Blenkinsop and Fowler, 2007; Haylock and Goodess, 2004; IPCC 2007). Primary productivity and ecosystem functioning in terrestrial ecosystems are strongly influenced by the annual amount of precipitation (Sala et al., 1988). However, recent research suggests that rainfall variability may exert an even stronger influence on ecosystem Manuscript 6: Increased rainfall variability reduces biomass and forage quality of temperate grassland largely independent of mowing frequency 147 functioning, where especially temperate grassland systems seem to be responsive to changes in rainfall variability. In grassland, more extreme rainfall regimes (less, but more intense rainfall events) affect ANPP (aboveground net primary productivity) (Barrett et al., 2002; Fay, 2009; Heisler-White et al., 2009; Knapp et al., 2002), carbon cycling (Chou et al., 2008; Fay, 2009; Harper et al., 2005) and N mineralization (Barrett et al., 2002, Heisler-White et al., 2009). The latter may in turn affect leaf quality in terms of N or protein content. Large reductions in ANPP have been shown in mesic grassland in response to more extreme rainfall patterns (Fay et al., 2003; Heisler-White et al., 2009; Knapp et al., 2008). In addition to the rainfall amount and variability, land management strategies, such as mowing frequency, can affect productivity and leaf litter quality in managed grassland. More frequent cutting is known to increase leaf N content. However, whether or not mowing increases or decreases the productivity of grassland depends on the mowing intensity, e.g. mowing history, mowing frequency and cutting height (Green and Detling, 2000; McNaughton, 1979; Turner et al., 1993; Weigelt et al., 2009). Mowing or defoliation is likely to alter the response to rainfall variability by altering plant community composition (Swemmer and Knapp, 2008). Furthermore, a reduction of transpirative tissue alters water uptake and consumption and therefore reaction towards rainfall (Heitschmidt et al., 1999; McNaughton, 1979; Yang and Midmore, 2004). Currently, a knowledge gap exists on how land management practices, such as mowing frequency, are interacting with more extreme rainfall regimes: Increased mowing frequency might buffer the effects of rainfall variability on grassland, diminishing the amplitude of the response towards rainfall extremes (Swemmer and Knapp, 2008). A study by Bernhardt-Römermann et al. (2011) indicates that climate parameters get less important for biomass production under intermediate mowing frequencies. However, land management strategies might also amplify the effects of rainfall variability. To our knowledge, this is the first study to experimentally manipulate mowing and rainfall patterns in European managed grassland (meadows) in order to identify any potential interactions between rainfall variability and mowing frequency. The primary objectives of our study were (1) to investigate the factorially-combined effects of increased spring rainfall variability and increased mowing frequency on the productivity and the forage quality of semi-natural, Central-European temperate grassland and (2) to determine, whether mowing frequency amplifies or buffers the effects of rainfall variability on biomass production and leaf quality of a target species. We conducted a field experiment in which we altered the temporal distribution and the magnitude of the rainfall events, but not the overall rainfall sum. To assess potential interactions between rainfall Manuscript 6: Increased rainfall variability reduces biomass and forage quality of temperate grassland largely independent of mowing frequency 148 variability and mowing frequency, we crossed the factor rainfall variability with the factor mowing frequency (two or four times per year). In the previous year, we altered the total rainfall amounts along with the alterations in rainfall variability. This enables a comparison between the effects of the altered total rainfall amounts and distribution and the effects of altered rainfall variability under constant total rainfall amounts. We hypothesized that (i) increased rainfall variability negatively affects productivity and leaf quality, as has been shown for other mesic grasslands, (ii) increased rainfall variability alone can cause changes in productivity that are comparable to changes caused by alterations in both, variability and the annual sum of rainfall together, (iii) more frequent mowing increases productivity and forage quality, as has been shown for more frequent, but still moderate mowing frequencies, (iv) more frequent mowing buffers adverse effects of increased rainfall variability on productivity and leaf quality, as growth responses might be synchronized and less responsive to rainfall changes after mowing. 2. Material & Methods 2.1 Study site The study was conducted within the EVENT II experiment in a semi-natural grassland in the Ecological Botanical Garden of the University of Bayreuth, Germany, Central Europe (49°55´19´´N, 11°3455``E, 365 m asl) (Jentsch & Beierkuhnlein, 2010). Communities are dominated by tall grasses, especially Alopecurus pratensis L. (meadow foxtail). The regional climate is temperate and moderately continental, with a mean annual temperature of 8.2 °C (1971–2000), and daily means ranging between -19.6 and 27.6. The mean annual precipitation of 724 mm (1971–2000) has a bimodal distribution with a major peak in June/July and a second peak in December/January (data: GermanWeather Service). The experiment was installed on a semi-natural, established meadow. For more than 20 years prior to the experiment, the meadow was mown twice per year and not fertilized. The rectangularly shaped experimental area has a total height difference of 95 cm within the diagonal from southwest to north east, and about 7 cm from southeast to north west. The soil of the experiment is classified as Stagnosol with a sandy-loamy Ap-horizon of about 30 cm depth, a strongly loamy Sw-horizon (20 cm) and a sandy-clayey Sd-horizon (>40 cm). Plant roots mainly occur in the upper 15 cm, with almost no roots penetrating below the A-horizon, mean pH-value is 5.9. Manuscript 6: Increased rainfall variability reduces biomass and forage quality of temperate grassland largely independent of mowing frequency 149 2.2 Experimental Design The EVENT II experiment was established in 2008. The experimental design consists of two factorially-crossed factors: (1) manipulation of the temporal distribution and magnitude of rainfall events in the growing season and (2) manipulation of mowing frequency. We implemented three scenarios of rainfall variability treatments in 2008 and 2009, assigned to the same plots: (1) low rainfall variability with weekly irrigation, ensuring a continuous water supply, (2) intermediate rainfall variability, with natural ambient rainfall variability and (3) extreme rainfall variability, including an extreme spring drought. Table 1 Average soil moisture [vol %], variation coefficient (CV) of soil moisture [%], number of rainfall events exceeding 1 mm, the sum of the rainfall amount [mm] and the variation coefficient (CV) of daily rainfall amount [%] in 2008 and 2009. parameter year time span low mid extreme natural average soil moisture 2008 26/05-30/10 2008 (158 days) 29 21 19 2009 01/04-31/10 2009 (214 days) 30 29 25 2009 01/04-17/05 2009 (47 days) 42 40 36 2009 -29/06 2009 (43 days) 29 29 21 2009 -09/08 2009 (43 days) 32 31 27 2009 -28/10 2009 (80 days) 23 24 22 CV soil moisture 2008 26/05-30/10 2008 (158 days) 20 31 38 2009 01/04-31/10 2009 (214 days) 35 35 37 2009 01/04-17/05 2009 (47 days) 6 8 13 2009 -29/06 2009 (43 days) 21 24 30 2009 -09/08 2009 (43 days) 25 29 26 2009 -28/10 2009 (80 days) 35 36 35 no. of events 2008 26/05-30/10 2008 (158 days) 61 53 45 2009 01/04-31/10 2009 (214 days) 80 71 60 2009 01/04-17/05 2009 (47 days) 19 16 16 2009 -29/06 2009 (43 days) 17 13 1 2009 -09/08 2009 (43 days) 17 16 17 2009 -28/10 2009 (80 days) 27 25 25 precipitation sum 2008 26/05-30/10 2008 (158 days) 445.2 334.8 296.1 334.8 2009 01/04-31/10 2009 (214 days) 596.8 596.8 596.8 458.5 2009 01/04-17/05 2009 (47 days) 130.2 99.5 99.5 99.5 2009 -29/06 2009 (43 days) 102.5 108.1 36.6 77.4 2009 -09/08 2009 (43 days) 164.2 152.2 223.7 127.1 2009 -28/10 2009 (80 days) 199.9 205 205 154.5 CV precipitation 2008 26/05-30/10 2008 (158 days) 164 183 204 183 2009 01/04-31/10 2009 (214 days) 204 256 297 227 2009 01/04-17/05 2009 (47 days) 227 280 280 280 2009 -29/06 2009 (43 days) 156 248 656 183 2009 -09/08 2009 (43 days) 192 205 223 220 -28/10 2009 (80 days) 203 275 275 192 1 Highest values in each category are in bold. 2 Values for the vegetation period 2008 and 2009 and for the time spans between the compensation irrigation treatments in 2009 for the differing rainfall variability treatments are given. Values for 2009 shown over one time span begin with a compensation irrigation and exclude the following compensation irrigation, as the latter is only effective for soil moisture and biomass for the following period. Manuscript 6: Increased rainfall variability reduces biomass and forage quality of temperate grassland largely independent of mowing frequency 150 In 2008, the first year of the study, total growing season amount of rainfall and variability of rainfall were altered. This made it possible to assess direct drought effects, as the extreme rainfall variability treatment also received least total rainfall (see Table 1 for an overview over soil moisture and rainfall parameters in both years). In 2009, the main year of the study, we controlled the amount of rainfall over the growing season for all treatments and manipulated only the distribution of rainfall, in order to isolate the effect of rainfall variability. All rainfall variability treatments were adjusted to the total 597 mm of rainfall of the low variability treatment in four compensation irrigations (Table 2). Thus, not only the length of the dry intervals, but also the magnitude of rainfall per event was changed. The low rainfall variability treatment received at least the 30-year weekly average rainfall each week. The vegetation periods from 1971 to 2000 served as a reference (data: German Weather Service). Missing amounts on natural rainfall were added if the weekly rainfall was less than the long-term average for the same week. This treatment ensured continuous water availability. If weekly rainfall exceeded the long-term sum, it was not subtracted for the next irrigation. For 2008, the overall rainfall amount of 553 mm on the low rainfall variability treatment (natural plus irrigated rainfall) within the vegetation period (April 1st-October 30th) exceeded the 30-year-average by 94 mm. In 2009, the total amount of 597 mm, irrigated on all treatments by applying compensation irrigations (see below), exceeded the 30-year-average by 138 mm. Both years consequently resemble rather wet years. The intermediate rainfall variability treatment remained under ambient conditions without any treatment, except for the compensation irrigations applied in 2009 which adjusted rainfall sum to the low rainfall variability treatment at four points of time (Table 2). Thus, in 2009 the intermediate rainfall variability treatment received the ambient rainfall plus the compensation irrigations. Table 2 Amount and timing of compensation irrigation [mm] in 2009 on the extreme and intermediate rainfall variability treatments given to apply the same overall rainfall amount on all treatments over the vegetation period. Treatment date extreme mid May 18th 36.6 36.6 June 30th 96.5* 25.1 August 10th 60.3 60.3 October 28th 32 32 *applied on two consecutive days