Ecosystem services of mixed stands of scots pine and maritime pine: biodiversity conservation and carbon sequestration

Daphne López Marcos Ph.D. Thesis Ecosystem services of mixed stands of Scots pine and Marime pine: biodiversity conservaon and carbon sequestraon PROGRAMA DE DOCTORADO EN CONSERVACIÓN Y USO SOSTENIBLE DE SISTEMAS FORESTALES TESIS DOCTORAL: Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration SERVICIOS ECOSISTÉMICOS DE MASAS MIXTAS DE PINO ALBAR Y PINO RESINERO: CONSERVACIÓN DE LA BIODIVERSIDAD Y SECUESTRO DE CARBONO Presentada por Daphne López Marcos para optar al grado de Doctora por la Universidad de Valladolid Dirigida por: Dra. Carolina Martínez Ruiz Dra. Mª Belén Turrión Nieves Daphne López-Marcos PhD. Thesis 2 This research was funded by the Ministry of Economy and Competitiveness of the Spanish Government project conceded to Felipe Bravo (FORMIXING. AGL2014-51964-C2-1-R) and a predoctoral grant to Daphne López-Marcos (BES-2015-072852). Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 3 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration Servicios ecosistémicos de masas mixtas de pino albar y pino resinero: conservación de la biodiversidad y secuestro de carbono PhD Student: Daphne López Marcos Supervisors: Dr. Carolina Martínez Ruiz Area of Ecology Department of Agroforestry Sciences University of Valladolid Dr. Mª Belén Turrión Nieves Area of Edaphology and Agricultural Chemistry Department of Agroforestry Sciences University of Valladolid Supervisor of the International Stay: Prof. Quentin Ponette Earth Life Insitute Univesité Catholique de Louvain, Belgium. External Reviewers: Dr. Jaime Madrigal-González Institute for Environmental Sciences University of Geneva Geneva, Switzerland Dr. Adele Muscolo Department of Agraria Università degli Studi Mediterranea Reggio Calabria, Italy Doctorate program: Doctorado en Conservación y Uso Sostenible de Sistemas Forestales Sustainable Forest Management Research Institute UVa-INIA (iuFOR) Escuela Técnica Superior de Ingenierías Agrarias (E.T.S.II.AA.) de Palencia University of Valladolid (UVa), Palencia, Spain Place of Publication: Palencia, Spain. Year of Publication: 2020 Online Publication: http://biblioteca.uva.es/export/sites/biblioteca/ Printed by: LLAR digital Design: Carmen Calvo Mañero (cover picture), Elena López Laureiro (Cover desing) and Daphne López Marcos (main text and graphical material) Daphne López-Marcos PhD. Thesis 4 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 5 Un immense incendie ravage la jungle. Affolés, les animaux fuient en tous sens. Seul un colibri, sans relâche, fait l’aller-retour de la rivière au brasier, une minuscule goutte d’eau dans son bec, pour l’y déposer sur le feu. Un toucan à l’énorme bec l’interpelle “tu es fou, colibri, tu vois bien que cela ne sert à rien”. “Oui, je sais” réponds le colibri, “mais je fais ma part”… Daphne López-Marcos PhD. Thesis 6 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 7 Agradecimientos Sin duda este es uno de los apartados más complicados de escribir de la tesis, pues no hay estadística que ayude a expresar lo que un@ siente. Miro hacia atrás, y durante estos años han sido muchas las personas con las que he compartido buenos y malos momentos. Este ejercicio de retrospección no sólo se remonta al inicio del contrato que me ha permitido hacer esta tesis (2016), sino también a los años previos en los que conseguir financiación sólo traía una ilusión seguida de un gran disgusto (2012). Por ello, de antemano mis disculpas si a alguien he olvidado. Quería expresar mi más sincero agradecimiento a todas aquellas personas que durante estos años han estado a mi lado: Gracias al Ministerio de Ciencia Innovación y Universidades (antiguo MINECO) en colaboración con el Fondo Social Europeo (UE) por haberme otorgado esta gran oportunidad de formación mediante un contrato predoctoral (BES-2015-072852) a través de la convocatoria 2015 de contratos predoctorales en el marco del Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016. Así como a la Escuela de Doctorado de la Universidad de Valladolid (EsDUVa) y el Instituto Universitario de Investigación en Gestión Forestal Sostenible (iuFOR) por facilitar actividades formativas. Gracias a Felipe Bravo, por confiar en mi para desarrollar este trabajo y permitirme colaborar en el sub-proyecto 2 del Proyecto FORMIXING “Complejidad y sostenibilidad en bosques mixtos: dinámica, selvicultura y herramientas de gestión adaptativa” (AGL2014-51964-C2-1-R). Gracias por enseñarme a comprender un poquito mejor la ciencia forestal. Gracias a mis directoras, Carolina Martínez Ruiz y María Belén Turrión, por guiarme y dirigir esta tesis. Gracias por vuestra dedicación y entrega a este trabajo y por darme la oportunidad de trabajar y aprender a vuestro lado. En especial quiero agradecer a Carolina (tu eres quien más me ha sufrido) por todo el esfuerzo y desvelos puestos en esta tesis. Trabajar contigo es un privilegio y una lección de vida. En estos años juntas he comprendido lo que es tener un MAESTRO (con mayúsculas). Eres capaz de conseguir lo máximo de las personas con quienes trabajas, pero siempre con mimo, cariño y respeto. Tu profesionalidad y tesón me han enseñado a ser más paciente (reto complicado), perder el miedo a la estadística y a amar la ecología. Por todo, en lo profesional y en lo personal, de verdad, GRACIAS. Thanks to Quentin Ponette, Mathieu Jonard and Hugues Titeux for your advice and help with the statistical analysis of the first paper of this thesis and for welcoming me in the Earth and Life Institute of the Université catholique de Louvain la Neuve (Belgium) during my international stay. Gracias a María Belén Turrión, Francisco Lafuente, Carmen Blanco y Juan Carlos Arranz por sus consejos en la fase de análisis de laboratorio. En especial a Carmen y Juan Carlos por su ayuda en la etapa de laboratorio y poner así de manifiesto la importante labor de los técnicos de laboratorio en el desarrollo de cualquier investigación, ya que sin su trabajo previo el nuestro sería imposible Gracias Josu González-Aday por tu consejo en la estadística del cuarto artículo de esta tesis. Gracias a Cristóbal Ordoñez por su ayuda para localizar las parcelas. Gracias a José Riofrío y Nico Cattaneo por las horas de debate sobre los tripletes y por vuestros valiosos comentarios. Gracias a Juan Manuel Diez Clivillé (DEP) y a María de la Fuente, quienes, sin conocerme, pusieron su esfuerzo en la revisión del inglés. Daphne López-Marcos PhD. Thesis 14 mantenían el mismo nivel de riqueza en el sotobosque. Además, se identificó un gradiente de fertilidad edáfico definido por el carbono orgánico y reservas de magnesio intercambiable. Los hemicroptófitos, cuya abundancia fue mayor en los rodales mixtos, fue la única forma de vida del sotobosque que se correlacionó positivamente con la fertilidad del suelo. Además, cuando se analizó la regeneración de las principales especies arbóreas y la composición de las especies del sotobosque (III), el porcentaje de área basal de ambas especies de Pinus fue la única característica del rodal que influyó significativamente en la composición del sotobosque y en la regeneración de los árboles. Especies características de zonas húmedas y templadas, incluido el regenerado de P. sylvestris, dominaban en los rodales monoespecíficos de P. sylvestris, y especies típicas de áreas mediterráneas bien drenadas, incluido el regenerado de P. pinaster, dominaban en los rodales monoespecíficos de P. pinaster. En los rodales mixtos, la regeneración del roble melojo nativo fue mayor y estuvo acompañada por especies típicas del sotobosque que comparten su mismo nicho de regeneración. Finalmente, cuando se estudió la productividad del arbolado a dos escalas espaciales, se relacionó con el suelo y se analizó su repercusión en el sotobosque (IV), se encontró en los rodales mixtos un sobre-rendimiento del arbolado a pequeña escala espacial, que se relacionó con la mayor eficiencia en el uso del espacio por ambas especies de pinos, gracias a la complementariedad de nicho edáfico (uso del agua y fertilidad). Además, no se encontró un efecto negativo del sobre-rendimiento del arbolado sobre la riqueza del sotobosque que se mantiene en los rodales mixtos gracias a la contribución de los hemicriptófitos. Se destaca la importancia de la escala para determinar la relación diversidad-productividad en bosques. Estos resultados contribuyen a comprender mejor algunos de los mecanismos subyacentes a la relación arbolado-sotobosque-suelo en bosques mixtos. Parece que la mezcla de P. sylvestris y P. pinaster supone una ventaja competitiva sobre las masas monoespecíficas en cuanto a la conservación de la biodiversidad, secuestro de carbono, fertilidad y productividad. Teniendo en cuenta, además, que estas mezclas están ampliamente distribuidas en España, parece adecuado proponer que se sigan potenciando en el área de estudio porque contribuyen a incrementar la acumulación de carbono en el subsuelo, proporcionar un sobre-rendimiento del arbolado, conservar el regenerado de especies endémicas como el roble melojo y mantener la riqueza del sotobosque en suelos con menor contenido hídrico. Palabras clave: Pinus sylvestris, Pinus pinaster, Quercus pyrenaica, bosque mixto, servicios ecosistémicos, conservación de la biodiversidad, secuestro de carbono, fertilidad, productividad, carbono del subsuelo, cationes intercambiables del suelo, formas de vida de Raunkiær, gradiente hídrico, mantenimiento de la riqueza, melojar endémico, complementariedad de nicho, sobrerendimiento, relación arbolado-sotobosque-suelo. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 15 Outline of the thesis This thesis comprises four studies focused on increasing the knowledge of the dynamics and the functioning of mixed vs. monospecific stands of Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.) in relation to the provision of ecosystem services such as biodiversity conservation and carbon sequestration. For that, the relationships between different components of forest ecosystem (i.e. overstory, understory and soil) are addressed in the different chapters (see Figure 1). Chapter (I), the first article of the compendium, addresses the study of soil profile by depths, including organic and mineral horizons, and its relationship with the overstory composition at the stand level (see Figure 19). The aim of this study is to quantify the differences among stand types in carbon storage along the soil profile and its relationship with exchangeable cations in mixed vs. monospecific stands of Scots pine and Maritime pine. Chapter (II), the second article of the compendium, addresses the characterization of the understory (Raunkiær´s life-forms richness and composition) and its relationship with the overstory composition and soil properties (of the whole soil profile) at the stand level (see Figure 25). The aim of this study is to assess the effect of the overstory on the understory richness and life-forms composition and its relation to soil status. Chapter (III), the third article of the compendium, also addresses the characterization of the understory, but now at the species level (species richness and composition) and including main tree species regeneration, and its relationship with overstory composition and stand characteristics (see Figure 30). The aim of this study is to relate the understory richness and tree regeneration to significant stand characteristics, responsible for the niche segregation of the main understory species. Chapter (IV), the fourth article of the compendium, addresses the fundamental role of scale in determining the relationship between species richness and ecosystem functioning in forests (Figure 37). The aim of this study is to assess the effect of the mixture of Pinus sylvestris and P. pinaster on productivity at two spatial scales, the relation of overyielding found in mixed stands with soil moisture and fertility, and its effect on the understory richness. Daphne López-Marcos PhD. Thesis 16 Figure 1. Thesis synthesis. Ilustration of a triplet with the three stand types (monospecifics stands of Pinus sylvestris or P. pinaster, and mixed stand) and their ecosystem components, overstory, understory, and soil. Also, the relationships between different ecosystem components assesed in each original article are indicated. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 17 List of Original Articles This thesis has generated four original articles published or under consideration for publication in SCI journals. The firt two have already been published, and the third one has been accepted for publication. The fourth paper is under revision. Each article gives rise to a chapter of this thesis. Chapter I López-Marcos D, Martínez-Ruiz C,Turrión MB, Jonard M, Titeux H, Ponette Q, Bravo F (2018). Soil carbon stocks and exchangeable cations in monospecific and mixed pine forests. European Journal of Forest Research 137: 31–84. doi:10.1007/s10342-018-1143-y Q1 Journal of "Forestry" category with an impact factor of 2.629 in the last 5 years. Chapter II López-Marcos D, Turrión MB, Bravo F, Martínez-Ruiz C (2019). Understory response to overstory and soil gradients in mixed vs. monospecific Mediterranean pine forests. European Journal of Forest Research 138: 939–955. doi:10.1007/s10342-019-01215-0 Q1 Journal of "Forestry" category with an impact factor of 2.629 in the last 5 years. Chapter III López-Marcos D, Turrión MB, Bravo, F, Martínez-Ruiz C (2020a). Can mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? Annals of Forest Science doi: 10.1007/s13595-020-0919-7 Q1 Journal of "Forestry" category with an impact factor of 2.555 in the last 5 years. Chapter IV López-Marcos D, Turrión MB, Bravo F, Martínez-Ruiz C (2020b). Overyielding at a small spatial scale in mixed pine forests as result of belowground resources complementarity: implications for understory richness conservation. Ambio (under revision) Q1 Journal of "Enviromental Sciences" category with an impact factor of 4.674 in the last 5 years. Note: Citation styles in each original article are standardised through the Thesis. Numeration of tables and figures is correlative throughout the thesis. Daphne López-Marcos PhD. Thesis 18 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 19 General introduction Ecosystem services Westman (1977) wondered for the first time how much nature's services cost and coined the term “nature’s services”, and years after Ehrlich and Mooney (1983) mention for the first time the term “ecosystem services”. However, related ideas had been brewing in the academic literature for decades (Costanza et al. 2017). What changed in the second half of the 20th century was that the loss of these ecosystem services became much more apparent, as natural capital was quickly being depleted (Beddoe et al. 2009). A key event in the history of ecosystem services was a meeting in October 1995 of Pew Scholars in Conservation and the Environment in New Hampshire (Costanza et al. 2017). During the meeting, the idea to synthesize all the information being assembled into a quantitative global assessment of the value of ecosystem services was proposed and it was concluded that quantity was significantly larger than the global gross domestic product at the time (Costanza et al. 2017). Thus was demonstrated that ecosystem services were much more important to human wellbeing than conventional economic thinking had given them credit for (Costanza et al. 2017). An important milestone of ecosystem services research was the Millennium Ecosystem Assessment (MEA; La Notte et al. 2017), a monumental work involving over 1300 scientists (Fisher et al. 2009). MEA classified the ecosystem services in four categories: supporting, regulating, provisioning and cultural services (Table 1; MEA 2005), and defined the “ecosystem services” as the ecological characteristics, functions, or processes that directly or indirectly contribute to human wellbeing: that is, the benefits that people derive from functioning ecosystems (MEA 2005). MEA (2005), in their reports, evaluates the ecosystem services of different systems as Marine Fisheries Systems, Coastal Systems, Inland Water Systems, Forest and Woodland Systems, Dryland Systems, Island Systems, Mountain Systems, Polar Systems, Cultivated Systems, and Urban Systems. Daphne López-Marcos PhD. Thesis 20 Table 1. Ecosystem services categories (MEA 2005; Wallace 2007). Ecosystem services Definition Examples Provisioning services The products obtained from ecosystems Food, fiber, genetic resources, biochemicals, natural medicines, ornamental resources, and freshwater Regulating services The benefits obtained from the regulation of ecosystem processes Air quality regulation, climate regulation, water regulation, erosion regulation, disease regulation, pest regulation and pollination Cultural services The non-material benefits people obtain from ecosystems through spiritual enrichment, cognitive development, reflection, recreation, and aesthetic experience Cultural diversity, spiritual and religious values, recreation and ecotourism, aesthetic values, knowledge systems, and educational values Supporting services The ecosystem services that are necessary for the production of all other ecosystem services Soil formation, photosynthesis, primary production, nutrient cycling, and water cycling Since the world’s forests cover thirty percent of the earth’s surface and provide critical and diverse services and values to human society the formally measuring and accounting for forest ecosystem services is a necessary first step toward properly valuing them (Jenkins and Schaap 2018). MEA (2005) examined the state of forest ecosystem services worldwide and concluded that the combined economic value of ‘nonmarket’ (social and ecological) forest services may exceed the recorded market value of timber, although these values are rarely taken into account in forest management decisions. Figure 2. Forest ecosystem services (Illustration by Daphne López-Marcos based on Lambini et al. 2018) MEA (2005) mentions as Major Classes of Forest Services the biodiversity conservation and the carbon sequestration (Figure 2). On the one hand, the forest functions as a primary habitat for a wide range of species supporting biodiversity maintenance and conservation (Jenkins and Schaap 2018). But also, the forest growth sequesters and stores carbon from the atmosphere, contributing to the regulation of the global carbon cycle and climate change mitigation (Jenkins and Schaap 2018). Thus, the analysis of biodiversity conservation and carbon sequestration in a forest type (i.e. mixed stands of Scots pine and Maritime pine) will be the target of this thesis. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 21 Biodiversity conservation The biodiversity concept is in constant evolution because it continues to be a topic of great interest since the end of the 19th century when Ecology emerges as a science (Martínez-Ruiz 2009). Magurran (1988, 2004) dedicates several chapters to its importance and measurement. At the Rio Earth Summit in 1992, one of the most widely accepted definitions of biodiversity emerged: "the variability among living organisms, including terrestrial, marine and other aquatic ecosystems, and the ecological complexes of which they are part: this includes diversity within species, between species, and of ecosystems” (UNEP 1992). Unfortunately, such important processes as interspecific interactions, natural disturbances, and nutrient cycles are left to mention. Biodiversity is not simply the number of genes, species, ecosystems in a defined area (Noos 1990). To complete this definition is necessary to recognize the three primaries attributes of ecosystems that constitute the biodiversity of an area, i.e. composition, structure, and function. The composition is the total number of species (Noos 1990; MEA 2005); the structure is a measure of their heterogeneity and complexity through the study of their patterns (Noos 1990; MEA 2005); and the function tries to understand the impact of processes in the ecosystem (Noos 1990; MEA 2005). The importance of forest biodiversity for both its existence value as a major component of global biodiversity and its utilitarian value as the source of innumerable biological resources used by people has been recognized by the Convention on Biological Diversity and numerous other agreements and studies. Understory vegetation represents the largest component of plant biodiversity in most forest ecosystems (Mestre et al. 2017) and is a key element in the forest ecosystem because of its high compositional, structural and functional diversity, its numerous interactions with different trophic levels, and its important role in ecosystem functioning (Aubin et al. 2008; Liu et al. 2017). Thus, the understory biodiversity should be also considered to know the potential of mixed vs. monospecific stand of Scots pine and Maritime pine in the provision of ecosystem services. Accordingly, this thesis addresses the analysis of first, diversity composition through the study of the richness (II) (III) (IV), composition and niche amplitude (III) of the plant species of the understory; second, biodiversity structure through the study of the understory Raunkiær’s lifeforms composition (II) and the tree species mixture proportion (II) (III) and third, diversity function through the study of the overstory and understory relationships with soil carbon sequestration (I) (II) and soil water and fertility (II) (IV). Daphne López-Marcos PhD. Thesis 22 Carbon sequestration Warming in the climate system is unequivocal and the human influence on the climate system is clear (IPCC 2014). Global warming has its origin in increasing the atmospheric concentration of greenhouse gases (Herrero de Aza 2010), such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). The term “carbon sequestration” is defined as the transfer and secure storage of atmospheric CO2 into other long-lived pools that would otherwise be emitted or remain in the atmosphere (Lal 2008). These pools are located in the ocean, biosphere, pedosphere, and geosphere (Lorenz and Lal 2010). Forest ecosystems can sequestrate the atmospheric CO2 during photosynthesis and stored the fixed carbon in the vegetation biomass (Ruiz-Peinado 2013). Also, forest ecosystems can sequester carbon in the soil for secure carbon storage (Lorenz and Lal 2010). Thus, forests play an important role in the global carbon cycle as an Earth’s terrestrial carbon sink (Andivia et al. 2016). Carbon sequestration is necessary to reduce CO2 concentrations and promote the mitigation of the effects of warming on the planet (Herrero de Aza 2010) and is considered one of the most cost-effective climate change mitigation strategies in the sustainable forest management (Figure 3; IPCC 2014), being also a forest ecosystem service. Figure 3. Carbon and oxigen fluxes associated with the photosynthesis in mixed forests of Scots pine and Maritime pine. CO2 = carbon dioxide, O2 = oxigen; C = carbon. Illustration by Carmen Calvo-Mañero. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 23 Although the carbon input inthe vegetation (overstory and understory) is considerable, the more important carbon inputs are below ground. About two-thirds of the carbon stored by forest ecosystems are contained in the forest soil (Table 2; Pan et al. 2011). Table 2. Stored carbon in vegetation and soil in diferent biomes (Pardos 2010). Bioma Distribution Stored carbon (Gt) Vegetation Soil Total Temperate forests USA, Europe, China, Australia 59 100 159 Boreal forests Rusia, Canada, Alaska 88 471 559 Tropical forests Asia, Africa, South America 66 264 330 The mechanisms of carbon storage vary depending on climate, vegetation, soil texture and mineralogical composition (Almendros 2004). Therefore, the species composition (Augusto et al. 2015) and the identity of the dominant species (Ruiz-Peinado et al. 2017) besides the climate, type of soil, and geomorphology affect both the accumulation and the distribution of the carbon along the soil profile (Chapin 2003) including the forest floor (Ruiz-Peinado et al. 2017). Consequently, the carbon stock of the upper mineral horizon is not a useful estimator of the total carbon set of the soil, since a substantial fraction of this carbon can be stored in the subsoil (Jandl et al. 2014). Although the carbon stock in the subsoil is less dynamic, it can contribute to changes in the total soil carbon set (Jandl et al. 2014). Thus, the study of the soil profile (I) (II) and the forest floor (I) is of great relevance. On the other hand, the soil nutrient status could be an indirect consequence of the organic matter contribution to the soil (Cremer and Prietzel 2017), since the decomposition of plant tissues in terrestrial ecosystems regulates the transfer of carbon and nutrients to the soil (Wang et al. 2014a,b). But also the soil nutrient status could be an indirect consequence of the forest management through the tree species selection (Jandl et al. 2014; Cremer and Prietzel 2017). Thus, it is necessary to clarify the relationships of soil nutrients, as soil exchangeable cations, with soil organic matter (I) and vegetation (II) (IV). The indirect benefits of soil carbon sequestration are reflected in the improvement of other soil features, such as water retention capacity or nutrient availability (Almendros 2004). All these characteristics are associated with the potential of organic matter to regulate soil composition (Almendros 2004). Thus, it is relevant to study not only the soil organic matter but also other soil features, as water or fertility, to better understand this process. Daphne López-Marcos PhD. Thesis 30 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 31 Objectives and hypothesis General objective The purpose of this thesis is to increase the knowledge on the dynamics and the functioning of mixed vs. monospecific stands of Scots pine and Maritime pine concerning the provision of ecosystem services such as the conservation of biodiversity and carbon sequestration. For that, we relate the different components of the forest ecosystem such as overstory, understory, and soil (see Figure1). Our general hypothesis is that mixed stands of Scots pine and Maritime pine can supply ecosystem services more efficiently than the respective monospecific forests. Specific objectives The specific objectives and the hypotheses are structured by chapters: I. To quantify the differences among stand types in carbon storage along the soil profile (every 10 cm depth) and its relationship with the exchangeable cations, and to investigate the possible causes of these observed differences. We hypothesize that the stand type influences the C storage and, indirectly, the exchangeable base cations of the mineral soil by the organic matter decomposition effect. Thus, differences in the topsoil among stand types are expected to be found, as well as a positive interactive effect of the admixture of both pine species on the accumulation of carbon in the soil profile in comparison with monospecific stands. II. To assess the effect of the overstory on the understory richness and Raunkiær’s life-forms composition and its relationship with soil properties. We hypothesize that the admixture of both pine species has a positive interactive effect on the understory richness in comparison with monospecific stands and that the understory composition and richness are positively correlated with (and can be derived from) the availability of nutrients and water. Daphne López-Marcos PhD. Thesis 32 III. To relate the understory richness and tree regeneration to significant stand characteristics, responsible for the niche segregation of the main understory species. We hypothesize that the proportion of both Pinus species in the overstory is the most influential characteristic of the stands on the understory composition and tree regeneration and that the mixture of both pine species favors the native tree regeneration and associated understory species that contribute to conserving a high understory species richness in mixed stands. IV. To assess the effect of the spatial scale on overstory yield in mixed forests, to understand the mechanisms involved, and to analyze the overstory yield effect on the understory richness. We hypothesize that there is an overstory overyielding in the mixed stand, only detected at a small spatial scale, caused by soil niche complementarity. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 33 Material and methods Study area The experimental device is located in the "Sierra de la Demanda" between the Burgos and Soria regions, in North-Central Spain (41° 47' 35'' N and 41° 53' 41'' N latitude, and 2° 56' 12'' W and 3° 20' 46" W longitude). It consists of eighteen forest plots distributed in six triplets located on an east-west axis of about 33 km and on a north-south axis of about 11 km (Figure 7). For further details about the location of the triplets, see Figure 45, 47, 48, 49, 50 and 51 in Suplementary material ‘Location’). Figure 7. (a) Location the study area in Europe. (b) Location of the triplets in the ‘Sierra de la Demanda’ in the North-Central Spain and location of the plots in each triplet. Pinus sylvestris monospecific stands: red circles; Pinus pinaster monospecific stand: yellow circles; Mixed stand of P. sylvestris and P. pinaster: blue circles. The climate of the study area is Temperate (mainly temperate with dry summer, Csb, and in a minor extent temperate without a dry season and warm summer, Cfb) according to the Köppen classification (1936) for the Iberian Peninsula. The mean annual temperature ranges from 8.7 to 9.8 °C and the annual rainfall ranges from 684 to 833 mm. The altitude varies from 1093 to 1277 m a.s.l and the slope from 0.9 to 20%. The geological parent materials are sandstones and marls from the Mesozoic era (IGME 2015). The soils are Inceptisols with a xeric soil moisture regime and a mesic temperature regime and they are classified as Dystroxerept Typic or Typic Humixerept (sensu Soil-Survey-Staff 2014). The sandy soil texture was dominant and the pH varies from extremely acidic to very acidic (López-Marcos et al. 2018). The natural vegetation surrounding the study area, highly degraded by anthropogenic action, is characterized by Pyrenean oak (Quercus pyrenaica Willd.) forests or communities dominated by junipers. Daphne López-Marcos PhD. Thesis 34 In ‘Supplementary material’, a description of the climate (Figure 52), including the mean annual temperature (Figure 53) and the annual rainfall (Figure 54) is shown, as well as information on the geological materials (Figure 55), the soils (Figure 56), and the potential (Figure 57) and current (Table 34) vegetation of the study area. A detail description of the pit soil profile of each plot is also provided (Tables 35-88). Experimental design The experimental device has 18 plots distributed in six triplets (Figure 8). Each triplet consists of three circular plots of 15 m radius, including two plots dominated either by P. sylvestris (PS) or P. pinaster (PP) and one mixed plot that contained both species (MM). Plots within triplet are located less than 1 km from each other (Figure 9) so that the environmental conditions are homogeneous within the triplet, although they can differ among distinct triplets (see in Suplementary material ‘Climate’, ‘Soils’ and ‘Vegetation’). Figure 8. Ilustration of a triplet. Modified of Cattaneo (2018). The sampling design in triplets is well balanced for stand composition (six repetitions per stand type) but not necessarily balanced for other stand characteristics (i.e. density, total basal area, dominant height, mean quadratic diameter, age). Stand characteristics are intended to be similar within the triplet (avoiding biases in the sampling design) but differed between triplets (see Table 34 in ‘Suplementary material’) facilitating a pair-wise plausible comparison of mixed versus monospecific stands (Riofrío 2018). Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 35 Figure 9. Map of triplet 5 as an example. Traditionally, forest management has consisted of strip clear-cutting with soil movement and planting or sowing when necessary, and moderate thinning from below (Riofrío et al. 2019) benefiting P. sylvestris (López-Marcos et al. 2019c). The stands have had no silvicultural intervention or damage in the last ten years in an attempt to minimize the effect of the thinning or another type of intervention in what is intended to study, either growth, floristic richness or soil nutrients. Triplets belong to the network of permanent plots of the Sustainable Forest Management Research Institute UVa-INIA (iuFOR) and they have been previously used in a series of recent studies (Riofrío et al. 2017a, b, 2019; Cattaneo 2018; López-Marcos et al. 2018, 2019, 2020a). The plots were selected to rely on species composition. In monospecific plots of Scots pine and Maritime pine, the target species constitutes at least 80% of the total basal area. Plots are defined as mixed when the combined basal area of both species represents at least the 90%, and the basal area of each target species is higher than 15%. Thus, the proportion of other species remained lower than 10% (Riofrío 2018). The plots have approximately a full-cover, with densities above 60% (Cattaneo 2018). Therefore, the percentage of the basal area of the dominant species in the monospecific plots of P. sylvestris was greater than 83%, the percentage of the basal area Daphne López-Marcos PhD. Thesis 36 of the dominant species in the monospecific plots of P. pinaster was greater than 95%, and the basal area percentage of both species in the mixed plots ranged from 33 to 67%. The age of the selected plots ranged between 44 and 151 years, the stand density between 509 and 1429 trees ha-1, the basal area between 33.3 and 70.30 and m2 ha-1 and the dominant height between 15.60 and 25.04 m (see Table 34 in ‘Supplementary material’). Soil sampling and laboratory analyses One soil pit of at least 50 cm depth was dug at each plot (eighteen in total) for organic (Forest floor, FF) and mineral soil horizons characterization. Forest floor A 25x25 cm quadrant (Figure 10) placed at the top of the pit was used to collect the forest floor or organic horizon. Coarse woody materials, such as large branches, were carefully removed from the forest floor before sampling (Andivia et al. 2016). The forest floor was separated into three fractions according to van Delft et al. (2006): almost undecomposed litter or fresh fraction (FsL), partially decomposed litter or fragmented fraction (FgL) and mostly decomposed organic matter or humified fraction (HmL). Figure 10. Forest floor sampling and handling procedure. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 37 The three fractions of leaf litter were dried separately at 60 °C during 48 h and weighed (±0.01 g) to determine the amount of biomass of each litter fraction per hectare (BFsL, BFgL, BHmL). A representative portion of each sample was ground up and analyzed with a LECO-CHN 2000 elemental analyzer to determine total organic carbon (TOC) and total nitrogen (TN) concentrations. The total forest floor biomass (BFF) was calculated as the sum of BFsL, BFgL and BHmL. The total organic carbon stock (Cstocks) of FsL, FgL and HmL litter fractions were calculated by multiplying TOC concentration by the biomass of each fraction (Andivia et al. 2016) to obtain C stockFsL, C stockFgL, CstockHmL, respectively. Cstock of the FF (CstockFF) was the sum of CstockFsL, CstockFgL and CstockHmL. The C/N ratio was calculated for the fresh (CNFgL), fragmented (CNFgL), and humified litter (CNHmL). C/N of the FF was calculated as the weighted average of C/N of three decomposition fractions (Equation 1). CNFF = ⌈(BFsL BFF )CNFsL⌉+ ⌈(BFgL BFF )CNFgL⌉+⌈(BHmL BFF )CNHmL⌉ Mineral soil Two undisturbed soil samples were collected from each mineral horizon of each pit with steel cylinders (98.18 cm3) keeping their original structure in order to determine the bulk density of each horizon. One disturbed sample was also taken from each mineral horizon of each pit (ca. 2.5 kg; see Figure 11). Figure 11. Mineral soil sampling procedure. The percentages of fine (%FR) and coarse (%CR) roots were estimated visually in each horizon at the time of digging the soil pit, i.e. many, normal, few, very few or no roots cover in the cross-section of the soil profile classified as 80%, 50%, 30%, 10% and 0% respectively. The roots with a diameter below 5 mm were considered fine roots and those with a diameter above 5 mm as coarse roots. Daphne López-Marcos PhD. Thesis 38 Both undisturbed and disturbed mineral soil samples were dried at 105 °C during 24 h before analyses. Undisturbed mineral soil samples were weighed (± 0.001 g) and used to calculate the soil bulk density (bD). Disturbed mineral soil samples were sieved (2 mm) before physical and chemical analyses. Physical analyses included percentage by weight of coarse fraction (> 2 mm; stones) and earth fraction (< 2 mm; EF), particle distribution determined by the pipette method (MAPA 1994) and subsequent determination of clay (%clay), sand (%sand) and silt (%silt) contents, and classification according to USDA criteria. Available water (AW) was determined by the MAPA (1994) method as the difference between water content at field capacity (water remaining in a soil after it has been thoroughly saturated for 2 days and allowed to drain freely) and the permanent wilting point (soil water content retained at 1500 kPa using Eijkelkamp pF Equipment). Chemical parameters analyzed for each mineral horizon included: exchangeable cations (Ca+2, Mg+2, K+, Na+) extracted with 1 M ammonium acetate at pH = 7 (Schollenberger and Simon 1945) and determined using an atomic absorption/emission spectrometer; total organic carbon (TOC) and total nitrogen (TN) quantified by dry combustion using a Leco CHN 2000 elemental analyzer; easily oxidizable carbon (oxC) analyzed using the K-dichromate oxidation method (Walkley 1947); and available phosphorus using the Olsen method (Olsen and Sommers 1982). Then the information from chemical and physical analyses of soil from mineral horizons was converted by depths (every 10 cm) and estimated for the whole profile as follows (Figure 12): o By depths. The mineral soil horizon data were converted into five different depths (every 10 cm) calculating weighted averages between the horizons (Figure 12b; see also Appendix Ic). Figure 12. Mineral soil profile by horizons (a), by depths (b) and as a whole (c) in the Maritime pine monospecific stand of triplet 5, as an example. o For the whole profile. The mineral soil horizon data were used to calculate the stocks of different soil properties and the soil water content in the whole profile (Figure 12c). First, in each horizon, the water holding capacity (WHC) and the stock of different soil properties were Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 39 calculated as indicated in Appendix IIb. After, the water holding capacity and the stocks of different soil properties in the soil profile (0–50 cm) were calculated as the sum of the values of each horizon (see Appendix IIb). In addition, the sum of bases (SB) was the sum of the Ca+2, Mg+2, K+ and Na+ concentrations (cmol+ kg−1). Overstory sampling and data analyses In order to assess the role of scale in determining the relationship between species richness and productivity, the overstory composition and structure were characterized at two different spatial scales: 1) at the stand level (Figure13), i.e. within each circular plot of 15 m radius; and 2) at a smaller scale (Figure 14), i.e. within each circular 4 m radius subplot centered in each quadrat of understory sampling according to Rodríguez-Calcerrada et al. (2011). Figure 13. Ilustration of overstory study at stand level of triplet 5 as an example. Red circles: Scots pine stems; Yellow circles: Maritime pine stems. The diameter of each circle represents the basal area. Figure 14. Ilustration of overstory study at the smaller spatial scale in the sub-plot number 5 of each stand type in triplet 5. Red circles: Scots pine stems; Yellow circles: Maritime pine stems. The diameter of each circle represents the basal area. The number and diameter of all stems > 7.5 cm DBH (diameter at the breist height) for every Pinus species in each plot were computed at both spatial scales. Tree density (N), total basal area (GT), and the basal area of each Pinus species (GPS: P. sylvestris basal area; GPP: P. pinaster basal area) were calculated at both spatial scales; GT, GPS and GPP as indicated in Appendix IVa. Daphne López-Marcos PhD. Thesis 46 Introduction Over the last decades, the management of mixed-species forests has taken on greater relevance as a result of the growing evidence that they can supply numerous ecological, economic and socio-cultural goods and services more efficiently than monospecific forests (Gamfeldt et al. 2013a). Taking into account that 23% of the land is covered by mixed forests in the pan-European region (FAO 2011), mixed forests management is becoming a new paradigm (Bravo-Oviedo et al. 2014) in order to increase the provision of many high-value goods and ecosystem services (Stenger et al. 2009), including biodiversity conservation or carbon sequestration (European Commission 2010). Forests play an important role in the global carbon cycle and in the Earth’s terrestrial carbon sink (Andivia et al. 2016). Forest ecosystems contain approximately 1725 Pg of carbon and about two-thirds are contained in the forest soil (Pan et al. 2011). However, there is still great uncertainty regarding best management strategies to promote soil organic carbon sequestration (Andivia et al. 2016), including the mixture of different species of trees (Jandl et al. 2007). Carbon accumulation mechanisms may vary depending on the dominant species (Augusto et al. 2015) and the different layers of the soil (Vesterdal et al. 2013) since the aboveground litter and the root litter are the responsible for soil C input (Rasse et al. 2005). Therefore, the mixture of tree species can affect both the accumulation and the distribution of the carbon along the soil profile (Chapin 2003). Although a general understanding of the effect of tree species across site types have not yet been reached (Jandl et al. 2007), many authors suggest that the impact on the forest floor or mineral soil depends on the identity of the species, species richness, and kind of mixture (Ruiz-Peinado et al. 2017). In fact, Dawud et al. (2016) revealed that forests with greater diversity had higher soil carbon stocks in deeper layers. However, most reports of positive mixture effects on C storage focus on mixtures that combine species with contrasting traits, such as the mixing of European beech and Norway spruce (Andivia et al. 2016), the mixing of European beech, Douglas fir and Norway spruce (Cremer et al. 2016), or even in plantations of mixed stand vs monocultures in a chronosequence of Pinus massoniana-Cinnamomum camphora (Liu et al. 2017). The effect of mixing for species that are expected to behave quite similarly as they belong to the same genus is still unknown, despite being frequent in many environments, such as the admixtures of Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.) in Spain. Both Pinus species show similar crown architecture and slight differences in shade tolerance (Riofrío et al. 2017a), but clearly differ in leaf traits (e.g. more recalcitrant leaf litter for P. pinaster; Herrero et al. 2016; longer P. pinaster needles; Amaral Franco 1986), whereas the information on Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 47 root distribution is not clear, since rooting depth may vary depending on the moisture conditions (Bakker et al. 2006). Maritime pine is an important species of Mediterranean forests and Scots pine is the most widely distributed species of pine in the world (Bogino and Bravo 2014). They are two of the main forest species in Spain (Scots pine: 1.20 million ha; Maritime pine: 0.68 million ha) and grow in monospecific and mixed stands, either naturally or as a result of species selection for afforestation (Serrada et al. 2008). In addition to their wide distribution and forest area, they hold great ecological and socio-economic value (Riofrío et al. 2017b). Mixed stands where these two species coexist are particularly interesting because of their location at the rear-edges for P. sylvestris forests, where ecological conditions (high temperatures, frequent droughts) approach the species tolerance limit and the most drastic effects of climate change are predicted (Matías and Jump 2012). Forest management in general and tree species selection, in particular, have various impacts on soil biological, physical and chemical processes and characteristics (Jandl et al. 2007; Cremer and Prietzel 2017). With regard to the soil chemical properties, soil exchangeable cation concentrations may be affected by tree species composition (Cremer and Prietzel 2017). Different tree species growing under similar conditions, such as climate, soil type, and land use history differ substantially from each other with respect to foliage nutrient content, root and litter chemistry, all of them having a large impact on soil nutrient input, output, and cycling (Augusto et al. 2015; Cremer and Prietzel 2017). Also, the soil nutrient input could be an indirect consequence of the organic matter contributions to soil (Cremer and Prietzel 2017), since the decomposition of plant tissues in terrestrial ecosystems regulates the transfer of carbon and nutrients to the soil (Wang et al. 2014). Differences in the concentration of cations in the soil may depend on differences between tree species in biomass accumulation rates and/or biomass cation concentrations (Brandtberg et al. 2000). The amount and composition of litter produced also vary between species, and these two factors can, in turn, influence the rate of accumulation of organic matter and properties of the forest floor (Brandtberg et al. 2000). Whether species differ in the depth at which nutrient uptake is concentrated and/or in the rate of biocycling, the result may appear in subsoil mineral horizons (Brandtberg et al. 2000). The forest management practices must be used as a mitigation tool as regards the carbon sequestration because the type of tree species affects forest growth, carbon and nutrient cycling (Augusto et al. 2015). That is why we investigated the impact of the mixture of tree species of the same genus with a wide distribution in Spain (Pinus sylvestris and P. pinaster) on C storage along the soil profile in comparison with monospecific stands. We hypothesize that: (1) the stand type influences the C storage and, indirectly, the exchangeable base cations of the mineral soil by the Daphne López-Marcos PhD. Thesis 48 organic matter decomposition effect; (2) differences in the topsoil among stand types are expected to be found; and (3) the admixture of both pine species might have a positive interactive effect on the accumulation of carbon in the soil profile in comparison with monospecific stands. Therefore, the aims of this study were: (i) to quantify the differences among stand types in C storage, including both total accumulation in soil and distribution in the soil profile; (ii) to investigate the possible causes of the observed differences; and (iii) to explore how the difference in C accumulation might affect the exchangeable cation concentrations. Material and methods Study sites The research was carried out in eighteen forest plots (6 triplets) located in the ‘Sierra de la Demanda’ between the Burgos and Soria regions, in North-Central Spain (41°47'35'' N and 41°53'41''N latitude and 2°56'12''W and 3°20'46''W longitude; Figure 20). The climate is Temperate Type Cfb and Csb, i.e. temperate with dry or temperate summer and atlantic respectively, according to the Köppen classification (1936) for the Iberian Peninsula. The mean annual temperature ranges between 8.7 and 9.8 °C and the annual precipitation ranges between 684 and 833 mm (Nafría-García et al. 2013). Altitude varies from 1093 to 1277 m a.s.l., and the slope from 0.9 to 20%. The geological parent materials are sandstones and marl of Mesozoic age (IGME 2015). The soils are Inceptisols with a xeric soil moisture regime and mesic soil temperature regime and they are classified as Typic Dystroxerept or Typic Humixerept (sensu Soil-Survey-Staff 2014). The sandy soil texture was dominant and the pH varies from extremely acid to strongly acid (Appendix Ia). The natural dominant vegetation in the study area, highly degraded by anthropogenic action, is characterised by Pyrenean oak forests or communities dominated by junipers. Each triplet consisted of two plots dominated either by Pinus sylvestris (PS) or Pinus pinaster (PP) and one plot with a mixture of both species (MM) located less than 1 km from each other. Plots were circular of radius 15 m and the tree species composition was the main varying factor. The percentage of the basal area of the dominant species in the monospecific plots was greater than 83% or 95% for P. sylvestris or P. pinaster respectively, whereas the basal area percentage of both species in the mixed plots ranged from 33 to 67%. Historically, the area has been occupied by forests and it has been traditionally managed for decades through selective thinning, being P. sylvestris benefited. The stands had no silvicultural intervention or damage in the last ten years. The age of the selected plots ranged between 44 and 151 years, the stand Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 49 density between 509 and 1429 trees ha-1, the basal area between 33.3 and 70.30 and m2 ha-1 and the dominant height between 15.60 and 25.04 m (Appendix Ib). These plots belong to the network of permanent plots of iuFOR-UVa. Figure 20. Location of the triplets in the ‘Sierra de la Demanda’ in the North-Central Spain and location of the plots in each triplet. Pinus sylvestris monospecific stands (PS): red circles; Pinus pinaster monospecific stand (PP): yellow circles; Mixed stand of P. sylvestris and P. pinaster (MM): blue circles. Soil sampling One soil pit of at least 40 cm depth was dug at each plot (eighteen in total) for organic and mineral soil horizons characterization and sampling (Appendix Ic). A 25x25 cm quadrant placed at the top of the pit was used to collect the forest floor or organic horizon. Coarse woody materials, such as large branches, were carefully removed from the forest floor before sampling (Andivia et al. 2016). The forest floor (FF) was separated into three fractions according to Van Delft et al. (2006): almost undecomposed litter or fresh fraction (FsL), partially decomposed litter or fragmented fraction (FgL) and mostly decomposed organic matter or humified fraction (HmL). Two undisturbed soil samples were collected from each mineral horizon of each pit with steel cylinders (98.18 cm3) to keep their original structure (Appendix Ic). One disturbed sample was also taken from each mineral horizon of each pit (ca. 2.5 kg). The percentages of fine (%FR) and coarse (%CR) roots were estimated visually in each horizon at the time of digging the soil pit, Daphne López-Marcos PhD. Thesis 50 i.e. many, normal, few, very few or no roots coverage in the cross-section of the soil profile classified as 80%, 50%, 30%, 10% and 0% respectively. The roots with a diameter below 5 mm were considered fine roots and those with a diameter above 5 mm as coarse roots. Laboratory analyses The three fractions of leaf litter were dried separately at 60°C during 48 h and weighed (±0.01 g) to determine the amount of biomass of each litter fraction per hectare (BFsL, BFgL, BHmL). A representative portion of each sample was ground up and analyzed with a LECO-CHN 2000 elemental analyzer to determine total organic carbon and total nitrogen concentrations (TOC and N, respectively). Both undisturbed and disturbed mineral soil samples were dried at 105°C during 24 h before analyses. Undisturbed mineral soil samples were weighed (±0.001 g) and used to calculate the soil bulk density (bD). Disturbed mineral soil samples were sieved (2 mm) before physical and chemical analyses. Physical analyses included percentage by weight of coarse fraction (>2 mm; stones) and earth fraction (<2 mm; EF), particle distribution determined by the pipette method (MAPA 1994) and subsequent determination of clay (%clay), sand (%sand) and silt (%silt) contents, and classification according to USDA criteria. Chemical parameters analyzed for each mineral horizon included: exchangeable cations (Ca+2, Mg+2, K+, Na+) were extracted with 1N ammonium acetate at pH=7 (Schollenberger and Simon 1945) and determined using an atomic absorption/emission spectrometer; TOC was quantified by dry combustion using a Leco CHN 2000 elemental analyzer. Data analyses The percentage of Pinus pinaster basal area (% PP) was calculated as the ratio between the basal area of P. pinaster and the total basal area of each plot. Total FF biomass (BFF) was calculated as the sum of BFsL, BFgL and BHmL. C stocks of FsL, FgL and HmL litter fractions were calculated by multiplying TOC concentration by the biomass of each fraction (Andivia et al. 2016) to obtain C stockFsL, C stockFgL, C stockHmL respectively. C stock of the FF (C stockFF) was the sum of C stockFsL, C stockFgL and C stockHmL. The C:N ratio was calculated for the fresh (CNFgL), fragmented (CNFgL), and humified litter (CNHmL). C:N of the FF was calculated as the weighted average of C:N of three decomposition fractions. CNFF = ⌈(BFsL BFF )CNFsL⌉+ ⌈(BFgL BFF )CNFgL⌉+⌈(BHmL BFF )CNHmL⌉ Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 51 C stock in the mineral soil (C stockSOIL) was calculated as: C stockSOIL = TOCi⋅bDi⋅%EFi Ti, being TOCi the total organic carbon concentration, bDi the measured bulk density, %EFi the percentage of earth fraction and Ti the thickness of the soil horizon. The C stock in the whole mineral soil profile (C stock0-40cm) was calculated as the sum of the C stock of all soil horizons. The sum of bases (SB) was the sum of the Ca+2, Mg+2, K+ and Na+ concentrations (cmol+ kg-1). The mineral soil horizon data were converted into four different depths (every 10 cm) calculating weighted averages between the horizons. Some variables were transformed (lnx or 1/x) before statistical analysis to achieve residual normality and homoscedasticity. While soil texture is not expected to be affected by stand species composition, it may have a large impact on C sequestration in the mineral soil (Jandl et al. 2007). In order to remove the effect of the soil texture variability within a triplet, texture variables (sand, silt, clay) were therefore tested as additional fixed effects in the alternative models; based on AIC values, only the sand content was included in the final model. The possible effects of the type of stand on the C stockFF (C stockFF, C stockFsL, C stockFgL and C stockHmL) as well as on TOC, C stockSOIL, exchangeable cations (Na+, K+, Ca+2, Mg+2), and SB in different mineral soil layers were analyzed using Linear Mixed Models (LMM) with the Restricted Maximum Likelihood method (REML; Richards 2005). The type of stand was considered as a categorical variable with three levels: PS, PP and MM. In all cases, a null model considering the random effect of triplet was tested with the alternative model that included the fixed effects of the type of stand plus the soil sand content (%sand). The Akaike Information Criterion (AIC; Akaike 1973) was used to verify whether the alternative model was more parsimonious, i.e. smaller values of AIC, and the ANOVA was applied to test the significant differences between the null and the alternative models (see Appendix Id). One monodominant plot of P. sylvestris was considered an outlier and excluded from all analyses because it was the only one that presented aquic conditions (Soil-Survey-Staff 2014; see Appendix Ia). Finally, linear correlations between some variables of interest were investigated, using the Pearson's coefficient (p<0.05). In order to test the influence of the type of stand on the nature of the leaf litter and to verify whether the TOC comes from the leaf litter and/or the roots decomposition at different mineral soil layers. Also the relationships between TOC and either the exchangeable cations or SB were tested. All statistical analyses were implemented in the R environment (version 3.3.3, R-Core-Team 2015) using LME4 package for LMM (Bates et al. 2015). Daphne López-Marcos PhD. Thesis 52 Results Forest floor quantity and quality The biomass of the fresh (BFsL) and fragmented (BFgL) leaf litter showed the same trend (p<0.05 for BFgL; p<0.10 for BFsL) when comparing among stand types (Figure 21A), being higher in PS, lower in PP and intermediate in MM; no significant trend was found for BHmL. An opposite significant trend (p<0.05) was found for the C:N ratio of the fresh litter (CNFsL), being higher in PP, lower in PS and intermediate in MM; no clear trend was observed for CNFgL and CNHmL (Figure 21B). In addition, %PP was positively correlated with CNFsL (r = 0.64, p<0.005) and negatively with BFsL (r = -0.45; p<0.05), BFgL (r = -0.54; p<0.025) and BFF (r = -0.46; p<0.05). Figure 21. (A) Biomass (B, mean value, Mg ha-1) and (B) C:N ratio (CN, mean±SE) of the different fractions of leaf litter (FsL, FgL, HmL: fresh, fragmented and humidified, respectively) according to the type of stand. PS (n=5): Pinus sylvestris monodominant stands; PP (n=6): P. pinaster monodominant stand. MM (n=6): mixed stands of both species. Signification level: * p<0.05; (•) p<0.1. TOC in the mineral soil The total organic carbon concentration (TOC) decreased according to the depth in the three types of stand, as expected (Figure 22). It differed significantly (p<0.05) among stands in the topsoil (010 cm), and almost significantly at the third depth (20-30 cm, p<0.10). In the same way as for the C stockSOIL, two different trends were found for TOC: TOC0-10cm was higher in PS, lower in PP and intermediate in MM, while TOC20-30cm was higher in MM. This latter tendency, yet not significant, was also found at the second depth (10-20 cm). In addition, TOC0-10cm was negatively correlated with CNFF (r = -0.46; p<0.05), and TOC at intermediate depths (10-20 cm and 20-30 cm) was positively correlated with %FR (TOC10-20cm: r = 0.66, p<0.005; TOC20-30cm: 20-30 cm: r = 0.76, p<0.005). Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 53 Figure 22. Mean±SE of total organic carbon (TOC mg g-1) at four different depths of the mineral soil profile according to the type of stand. Other abbreviations as in Figure 21. Signification level: * p<0.05; (•) p<0.1. C stock in the soil profile The carbon stock in the forest floor (C stockFF) differed almost significantly among stands (p<0.1), being higher in PS (8.41±1.43 Mg TOC ha-1), lower in PP (4.87±0.89 Mg TOC ha-1) and intermediate in MM (6.67±1.09 Mg TOC ha-1). The same pattern was observed for the three fractions of the litter (Figure 23), being statistically significant only for the fragmented litter (C stockFgL, p<0.05) and almost significant for the fresh one (C stockFsL, p<0.10). The carbon stock in the mineral soil (C stockSOIL) decreased with depth in the three types of stand, as expected (Figure 23), but the differences among stands were only almost significant (p<0.10) at 0-10 cm, 20-30 cm, and 30-40 cm. Two different trends were found: C stock0-10cm and C stock30-40cm were higher in PS, lower in PP and intermediate in MM; by contrast, C stock10-30cm was the highest in MM. Cstock0-40cm was also higher in MM (93.70±13.63 Mg TOC ha-1), lower in PP (70.94±10.20 Mg TOC ha-1) and intermediate in PS (81.62±11.37 Mg TOC ha-1), but these differences were not statistically significant (p=0.18). Daphne López-Marcos PhD. Thesis 54 Figure 23. Carbon stock (C stock, mean value, Mg ha-1) in the forest floor (green tones) for the organic layers (FsL, FgL, HmL: fresh, fragmented and humidified litter, respectively), and in the mineral soil profile (brown tones) at four different depths according to the type of stand. Signification level: * p<0.05; (•) p<0.1. Sum of bases and exchangeable cations in the mineral soil The same two trends found for TOC and C stock in the mineral soil were observed for the exchangeable cations and the sum of bases (Table 3). In the topsoil (0-10 cm), exchangeable cations (K+, Ca+2, Mg+2) and the sum of bases (SB) differ significantly (p<0.05) among stands, being higher in PS, lower in PP and intermediate in MM (Table 3). In addition, K+ (r = 0.61, p<0.005), Ca+2 (r = 0.74, p<0.005), Mg+2 (r = 0.57, p<0.01) and SB (r = 0.71, p<0.005) correlated positively with TOC at this depth. However, in the 10-20 cm soil layer, K+ and Mg+2 reached significantly higher values in MM (p<0.05), and a similar trend but not significant (p>0.10) was found for Ca+2 and SB. Again, K+ (r = 0.53, p<0.025), Ca+2 (r = 0.73, p<0.005), Mg+2 (r = 0.56, p<0.01) and SB (r = 0.70, p<0.005) correlated positively with TOC at this depth. The same pattern was observed at the third soil depth (20-30 cm), where MM showed significantly higher values for Mg+2 (p<0.05) and almost significantly (p<0.1) for Ca+2 and SB. At this depth, only Ca+2 (r = 0.91, p<0.005), Mg+2 (r = 0.81, p<0.005) and SB (r = 0.90, p<0.005) correlated positively with TOC. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 55 Table 3. Mean±SE of exchangeable cations concentration and sum of bases (cmol+ kg−1) at four different depths of the mineral soil profile according to the type of stand. Other abbreviations as in Figure 21. Signification level: * p<0.05; (•) p<0.1. Depth (cm) PS MM PP p Na+ 0-10 0.86 ± 0.04 0.87 ± 0.03 0.80 ± 0.03 * 10-20 0.84 ± 0.03 0.87 ± 0.02 0.80 ± 0.02 * 20-30 0.82 ± 0.04 0.85 ± 0.03 0.81 ± 0.04 30-40 0.80 ± 0.05 0.87 ± 0.04 0.85 ± 0.06 * K+ 0-10 0.24 ± 0.05 0.21 ± 0.02 0.16 ± 0.03 * 10-20 0.18 ± 0.06 0.20 ± 0.02 0.14 ± 0.02 * 20-30 0.19 ± 0.07 0.15 ± 0.04 0.13 ± 0.04 () 30-40 0.19 ± 0.07 0.12 ± 0.03 0.14 ± 0.04 * Ca+2 0-10 4.03 ± 0.63 3.35 ± 0.48 3.06 ± 0.49 * 10-20 2.29 ± 0.12 2.95 ± 0.51 2.62 ± 0.53 20-30 1.70 ± 0.28 2.25 ± 0.65 1.45 ± 0.46 () 30-40 1.47 ± 0.22 1.50 ± 0.38 1.65 ± 0.68 * Mg+2 0-10 0.83 ± 0.16 0.80 ± 0.12 0.79 ± 0.13 * 10-20 0.56 ± 0.04 0.74 ± 0.13 0.70 ± 0.13 * 20-30 0.49 ± 0.07 0.62 ± 0.15 0.47 ± 0.12 * 30-40 0.53 ± 0.10 0.52 ± 0.13 0.55 ± 0.21 * SB 0-10 6.00 ± 0.84 5.22 ± 0.62 4.81 ± 0.66 * 10-20 3.87 ± 0.17 4.76 ± 0.66 4.29 ± 0.69 20-30 3.20 ± 0.34 3.87 ± 0.84 2.86 ± 0.59 () 30-40 2.99 ± 0.30 3.00 ± 0.56 3.18 ± 0.96 * In the deepest soil layer (30-40 cm), a different pattern was observed: Ca+2, Mg+2 and SB were significantly (p<0.05) higher in PP, whereas K+ was significantly higher (p<0.10) in PS. Only K+ correlated positively with TOC at this depth (r = 0.53; p<0.025). Na+ showed significantly higher values in MM (p<0.05) at 0-10 cm, 10-20 cm and 30-40 cm, and did not correlate with TOC at any depth. Discussion Our results show, that when comparing monospecific and mixed pine forests in central Spain, the carbon stocks and exchangeable cations in the first 30 cm of the mineral soil profile respond in a similar way to the influence of the type of stand within the same soil layer, although patterns differ considerably when comparing between layers. At the topsoil (0-10cm), C stock and cations reach higher values in PS, lower in PP and intermediate in MM, whereas at the subsoil layers (1030 cm) it reaches higher values in MM than in monospecific stands. Daphne López-Marcos PhD. Thesis 62 pine (Pinus sylvestris L.). 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Thesis 64 Vilà M, Vayreda J, Comas L, et al (2007) Species richness and wood production: A positive association in Mediterranean forests. Ecol Lett 10:241–250. doi: 10.1111/j.14610248.2007.01016.x Wang F, Zou B, Li H, Li Z (2014) The effect of understory removal on microclimate and soil properties in two subtropical lumber plantations. J For Res 19:238–243. doi: 10.1007/s10310-013-0395-0 Wang J, You Y, Tang Z, et al (2016) A comparison of decomposition dynamics among green tree leaves, partially decomposed tree leaf litter and their mixture in a warm temperate forest ecosystem. J For Res 27:1037–1045. doi: 10.1007/s11676-016-0248-8 Wang R, Dungait JAJ, Buss HL, et al (2017) Base cations and micronutrients in soil aggregates as affected by enhanced nitrogen and water inputs in a semi-arid steppe grassland. Sci Total Environ 575:564–572. doi: 10.1016/j.scitotenv.2016.09.018 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 65 Appendix Ia Table4. General soil properties of the soil profiles excavated under the monospecific stands of Scots pine (Pinus sylvestris). Soil: soil classification according to Soil-Survey-Staff (2014); Colour: dry and wet matrix colour (Hue Value/Chroma); Thickness: thickness of each horizon; Soil texture: textural class according to Soil-Survey-Staff (2014); Sand/Silt/Clay: % of sand, silt and clay determined by the pipette method (MAPA 1994); Stones: coarse soil material (>2mm); pH (H2O): pH according to MAPA (1994). Stand type Pinus sylvestris monospecific stands Triplet 01 02 03 04 05 06 Soil type Typic Dystroxerept Typic Dystroxerept Aquic Humixerept Typic Dystroxerept Typic Humixerept Typic Dystroxerept Horizon Ah Ah Ah Ah Ah Ah Colour Dry 10YR 4/2 10YR 4/2 10YR 4/1 10YR 5/2 10YR 4/2 10YR 7/2 Wet 10YR 2/2 10YR 3/2 10YR 2/1 10YR 3/1 10YR 2/1 10YR 6/3 Thickness (cm) 0-10 0-15 0-12 0-8 0-15 0-28 Soil texture Sandy Loam Loamy Fine Sand Loam Sandy Loam Sandy Loam Sandy Loam Sand/Silt/Clay 51/36/10 75/15/6 44/30/18 56/21/14 55/21/13 81/9/8 Stones (%) 2.25 7.90 6.11 9.04 2.68 13.03 pH (H2O) 4.22 3.95 4.35 4.63 4.05 4.45 Horizon AB AC AC AB AB C Colour Dry 10YR 6/4 10YR 7/3 10YR 6/1 10YR 6/6 10YR 6/3 10YR 4/1 Wet 7.5YR 4/6 10 YR 5/4 10YR 4/1 10YR 3/2 10YR 5/3 10YR 5/6 Thickness (cm) 10-40 15-35 12-30 08-30 15-40 28-65+ Soil texture Loam Loamy Fine Sand Sandy Loam Loam Sandy Loam Loamy Fine Sand Sand/Silt/Clay 35/39/17 79/10/8 58/26//12 48/41/12 53/23/12 74/12/11 Stones(%) 24.61 11.83 20.24 25.68 11.68 5.53 pH (H2O) 4.79 4.22 4.77 5.37 4.75 4.60 Horizon Bw C Cg C C - Colour Dry 7.5 YR 5/6 10 YR 6/6 10YR 8/1 10 YR 7/4 10 YR 7/4 - Wet 5 YR 4/6 10 YR 4/6 10YR 6/1 10YR 5/8 10YR 5/8 - Thickness (cm) 40-60+ 35-65+ 30-60+ 30-60+ 40-60+ - Soil texture Loam Sandy Loam Sandy Loam Loam Sandy Loam - Sand/Silt/Clay 34/31/23 77/10/10 60/21/11 35/35/22 49/26/16 Stones (%) 33.20 8.39 22.27 25.56 16.09 - pH (H2O) 4.82 4.76 4.69 4.98 5.31 - Daphne López-Marcos PhD. Thesis 66 Table 5. General soil properties of the soil profiles excavated under the monospecific stands of Maritime pine (Pinus pinaster). Soil: soil classification according to Soil-Survey-Staff (2014); Colour: dry and wet matrix colour (Value/Chroma); Thickness: thickness of each horizon; Soil texture: textural class according to Soil-Survey-Staff (2014); Sand/Silt/Clay: % of sand, silt and clay determined by the pipette method (MAPA 1994); stones: coarse soil material (>2mm); pH (H2O): pH according to MAPA (1994). Stand type Pinus pinaster monospecific stands Triplet 01 02 03 04 05 06 Soil type Typic Dystroxerept Typic Humixerept Typic Humixerept Typic Dystroxerept Typic Humixerept Typic Dystroxerept Horizon Ah Ah Ah Ah Ah Ah Colour Dry 10YR 5/3 10YR 4/1 10YR 5/2 10YR 6/2 10YR 5/1 10YR 6/2 Wet 10YR 3/2 10YR 2/1 10YR 3/1 10YR 3/1 10YR 2/1 10YR 4/1 Thickness (cm) 0-15 0-20 0-17 0-8 0-20 0-12 Soil texture Loam Sandy Loam Sandy Loam Sandy Loam Sandy Loam Loamy Fine Sand Sand/Silt/Clay 52/34/13 64/16/11 66/18/8 80/12/5 65/16/11 85/9/5 Stones (%) 3.14 31.84 59.50 5.62 12.01 6.44 pH (H2O) 4.67 3.98 5.04 4.75 4.45 4.90 Horizon AB C C AC AC C Colour Dry 10YR 6/4 10YR 7/4 10YR 6/6 10YR 6/6 10YR 6/2 10YR 7/3 Wet 10YR 4/4 10YR 5/6 10YR 4/6 10YR 3/2 10YR 4/2 10YR 6/4 Thickness (cm) 15-30 20-60+ 17-57+ 08-34 20-30 12-50+ Soil texture Loam Sandy Loam Sandy Loam Sandy Loam Sandy Loam Loamy Fine Sand Sand/Silt/Clay 48/37/14 72/10/13/ 68/15/10 74/13/8 59/24/11 84/8/6 Stones (%) 34.12 21.66 58.56 9.29 52.86 9.07 pH (H2O) 5.23 4.72 4.80 5.15 4.91 5.16 Horizon Bw - - C C - Colour Dry 5YR 5/6 - - 10YR 7/4 10YR 6/4 - Wet 5YR 4/6 - - 10YR 5/8 10YR 4/4 - Thickness (cm) 30-60+ - - 34-60+ 30-52+ - Soil texture Clay - - Loam Sandy Loam - Sand/Silt/Clay 15/31/52 64/16/14 61/23/8 Stones (%) 38.09 - - 12.75 65.63 - pH (H2O) 4.78 - - 5.01 4.41 - Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 67 Table 6. General soil properties of the soil profiles excavated under the mixed stands of Scots (Pinus sylvestris) and Maritime (Pinus pinaster) pines. Soil: soil classification according to Soil-Survey-Staff (2014); Colour: wet matrix colour (Value/Chroma); Thickness: thickness of each horizon; Soil texture: textural class according to Soil-Survey-Staff (2014); Sand/Silt/Clay: % of sand, silt and clay determined by the pipette method (MAPA 1994); Stones: coarse soil material (>2mm); pH (H2O): pH according to MAPA (1994). Stand type Mixed Stands Triplet 01 02 03 04 05 06 Soil type Typic Humixerept Typic Humixerept Typic Humixerept Typic Dystroxerept Typic Dystroxerept Typic Dystroxerept Horizon Ah Ah Ah Ah Ah Ah Colour Dry 10YR 5/3 10 YR 5/2 10 YR 4/1 10 YR 6/2 10 YR 4/1 10 YR 6/1 Wet 10 YR 3/2 10 YR 3/1 10 YR 2/2 10 YR 4/1 10 YR 2/1 10 YR 3/1 Thickness (cm) 0-35 0-23 0-17 0-20 0-12 0-30 Soil texture Loam Sandy loam Sandy loam Loamy Fine Sand Sandy loam Sandy loam Sand/Silt/Clay 43/46/11 66/11/13 53/23/15 77/14/5 51/24/18 72/14/9 Stones (%) 15.79 5.21 15.02 15.12 11.70 47.93 pH (H2O) 5.30 3.97 4.42 5.16 4.38 4.56 Horizon Bw C C C AC C Colour Dry 7.5 YR 6/6 10 YR 7/4 10 YR 6/3 10 YR 6/6 10 YR 6/3 10 YR 8/3 Wet 5 YR 5/8 10 YR 6/6 10 YR 5/3 10YR 5/8 10 YR 4/4 10 YR 5/6 Thickness (cm) 35-75+ 32-60+ 17-54+ 20-50 12-24 30-70+ Soil texture Clay loam Sandy loam Sandy loam Sandy loam Sandy loam Loamy Fine Sand Sand/Silt/Clay 24/33/31 69/14/15 72/12/11 71/14/11 47/22/17 78/14/5 Stones (%) 34.80 8.33 60.57 35.15 15.27 11.88 pH (H2O) 4.77 5.16 4.72 5.20 4.47 5.02 Horizon - - - - C - Colour Dry - - - - 10 YR 6/6 - Wet - - - - 10 YR 4/6 - Thickness (cm) - - - - 24-50+ - Soil texture - - - - Sandy loam - Sand/Silt/Clay 45/22/18 Stones (%) - - - - 17.88 - pH (H2O) - - - - 4.55 - Daphne López-Marcos PhD. Thesis 68 Appendix Ib Table 7. General stand variables for monospecific stands of Pinus sylvestris. N: stems per hectare; G: basal area per hectare; Ho: dominant height; dq: quadratic mean diameter. Age: normal age. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 69 Table 8. General stand variables for monospecific stands of Pinus pinaster. N: stems per hectare; G: basal area per hectare; Ho: dominant height; dq: quadratic mean diameter. Age: normal age. Daphne López-Marcos PhD. Thesis 70 Table 9. General stand variables for mixed stands of Scots pine and Maritime pine. N: stems per hectare; G: basal area per hectare; Ho: dominant height; dq: quadratic mean diameter. Age: normal age. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 71 Appendix Ic Figure 24. Soil sampling design. Daphne López-Marcos PhD. Thesis 78 Introduction Mixed forests’ potential to provide multiple goods and services to a wide variety of end users more efficiently than monospecific forests (Gamfeldt et al. 2013) has led to an increasing interest in mixed forests management (Bravo-Oviedo et al. 2014). Some potential benefits of the admixture of tree species include biodiversity conservation (Felton et al. 2010), soil conditions amelioration (Brandtberg et al. 2000) or carbon sequestration increase (European Commission 2010); additionally, under certain conditions mixed forests can produce higher yield than monocultures (Saetre et al. 1997). The mixture of tree species also performs as a measurement of adaptive management to climate change, increasing the resilience of forest ecosystems and improving their adaptability (Temperli et al. 2012). Taking into consideration that mixed forests account for around 40% of forests in Europe (MCPFE 2003) and 19% in Spain (MAGRAMA 2012), the development of appropriate management techniques to maintain and improve mixed forests is considered to be paramount to achieve forest management sustainability in the framework of global change and biodiversity conservation. To assess the potential advantages of mixed vs monospecific stands, field plots should have similar characteristics, i.e. ceteris paribus conditions, as in studies based on triplets (Del Río et al. 2015). One triplet consists of three plots (one mixed plot and their corresponding monospecific plots) located less than 1 km from each other in order to share climatic and soil conditions. Plots within triplets have similar site conditions, age, and density and they belong to the same management compartments where the same silviculture regime has been applied, thus, facilitating a pair-wise plausible comparison of mixed vs monospecific stands(Riofrío et al. 2017b). In the last decade in Europe, several studies based on triplets have been carried out and most of them analyze the tree component of ecosystems focusing on productivity (Thurm and Pretzsch 2016; Riofrío et al. 2017b; Condés et al. 2018), structural heterogeneity (Pretzsch et al. 2016; Riofrío et al. 2017b), growth efficiency (Pretzsch et al. 2015; Riofrío et al. 2017a) or modified tree morphology (Thurm and Pretzsch 2016; Dirnberger et al. 2017; Zeller et al. 2017; Cattaneo et al. 2018; Forrester et al. 2018). Others associate the tree and soil ecosystem components analyzing carbon stocks (Cremer et al. 2016; López-Marcos et al. 2018) and nutrients in the soil profile (Cremer and Prietzel 2017; López-Marcos et al. 2018) and in the forest floor (Cremer et al. 2016; López-Marcos et al. 2018; Sramek and Fadrhonsova 2018). Nevertheless, the relationship between three ecosystem components such as overstory, understory, and soil in ceteris paribus conditions has not yet been addressed. Since the overstory tree species differ in their effects on microclimatic and edaphic conditions, it has been suggested that environmental gradients (i.e. changes in soil fertility and Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 79 water availability) may be broader in mixed than in monospecific stands (Barkman 1992a; Saetre et al. 1997). Thus, mixed stands have the potential to host a more heterogeneous and speciesrich flora than monospecific stands (Hill 1992; Saetre et al. 1997). However, the effects of the overstory composition of mixed vs monospecific forests on the understory composition (Brown 1982; Enoksson et al. 1995; Saetre et al. 1997) and dynamics (Cavard et al. 2011) need to be studied more in depth: especially the effects of the overstory on the understory functional groups and their relationship with soil status. The understory is known to be strongly influenced by the composition and structure of the overstory through its influence on temperature, light, water, soil nutrients, and litter accumulation (Saetre et al. 1999; Felton et al. 2010; Rodríguez-Calcerrada et al. 2011). However, managers and ecologists have traditionally paid less attention to the understory component of forests (Nilsson and Wardle 2005; Antos 2009), despite the fact that the understory participates in a great variety of aboveground processes (e.g. tree seedling regeneration, forest succession, species diversity and stand productivity) and also in belowground processes, such as litter decomposition, soil nutrient cycling and soil water conservation (Liu et al. 2017). Understory plants represent the largest component of plant biodiversity in most forest ecosystems (Mestre et al. 2017). Although understory vegetation accounts for only a small portion of forest biomass (Pan et al. 2018), it is an important component of forest ecosystems driving ecosystem processes such as carbon cycling (Chen et al. 2017), nutrient recycling (Yarie 1978) and, thus, influencing the soil nutrient status (Cavard et al. 2011). The lower contribution of the understory to the forest biomass carbon pool is offset by its higher turnover rate, which allows a high annual carbon input into the understory relative to its total biomass (Cavard et al. 2011). In addition, it has been found that the understory removal has an important impact on biological and/or environmental parameters such as soil water content, soil temperature, and thus, on evapotranspiration, tree growth and soil properties (Wang et al. 2011). Therefore, the understory deserves more direct attention, especially in mixtures that combine coniferous tree species. Most reports of the overstory-understory relationship in mixed forests focus on mixtures that combine deciduous and coniferous tree species (Saetre et al. 1997, 1999; Barbier et al. 2008; Cavard et al. 2011; Inoue et al. 2017), not only in natural forests but also in plantations (Ou et al. 2015). They test the overstory effect on the understory biomass (Cavard et al. 2011), cover and structural heterogeneity (Saetre et al. 1997), biodiversity and the mechanisms involved (Barbier et al. 2008), the spatial relationship between the overstory and understory species distribution and soil nitrogen availability (Inoue et al. 2017), or soil microbial biomass and activity (Saetre et al. 1999). However, the effect of the overstory on the understory in Daphne López-Marcos PhD. Thesis 80 mixtures that combine coniferous tree species or even tree species of the same genus remains virtually unknown, at least in Europe (but see Mestre et al. 2017). This is so despite these mixtures are frequent in many environments, such as the admixtures of Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Aiton) in Spain. Both Pinus species show similar crown architecture and slight differences in shade tolerance (Riofrío et al. 2017b). Maritime pine is an important species of Mediterranean forests and Scots pine is the most widely distributed species of pine in the world (Bogino and Bravo 2014). They are two of the main forest species in Spain (Scots pine: 1.20 million ha; Maritime pine: 0.68 million ha) and they grow in monospecific and mixed stands, either naturally or as a result of species selection for afforestation (Serrada et al. 2008). Plant species characteristics, such as life-form, provide information on how plants have adapted to the environment, particularly to climate (Smith and Smith 2003). The classification of species within a community into life-forms provides a way of describing the structure of a community for comparison purposes. Raunkiær´s classification of life-forms (1934), which establishes a relationship between the embryonic or meristematic tissues that remain inactive over the winter or prolonged dry periods and their height above ground, allows us to compare communities according to their adaptability to the critical season (Smith 1913), that is to say, the summer drought under Mediterranean conditions but also frost in winter. On the other hand, soil properties can also play an important role in changes in the understory richness and composition (Cavard et al. 2011). Likewise, the understory can directly influence soil properties, such as temperature and moisture (Rodríguez et al. 2007a). Understanding the ecology of the understory vegetation has important implications for both biodiversity conservation and production-oriented forest management (Nilsson and Wardle 2005). Here, we investigated the influence of the mixture of two widely distributed pine species (Pinus sylvestris and P. pinaster) on the understory plant community compared to monospecific stands, as well as the role played by relevant soil properties. Raunkiær´s life-forms classification of the understory vegetation was used. The aims of this study were: (i) to assess the effect of the overstory on the understory life-forms composition; (ii) to link differences in the life-forms composition of the understory to soil properties; and (iii) to model the response of the understory richness and cover of different life-forms along the main gradients identified. We hypothesize that: (1) the admixture of both pine species has a positive interactive effect on the understory richness compared to monospecific stands; and (2) the understory composition and Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 81 richness are positively correlated with (and can be derived from) the availability of nutrients and water. Material and methods Study sites The research was carried out in eighteen forest plots (6 triplets) located in the ‘Sierra de la Demanda’ between the Burgos and Soria regions, in North-Central Spain (41°47'35''N and 41°53'41''N latitude and 2°56'12''W and 3°20'46''W longitude; Figure 26). The climate is Temperate with dry or temperate summer (Cfb, Csb), according to the Köppen (1936) classification for the Iberian Peninsula. The mean annual temperature ranges from 8.7 to 9.8 °C and the annual precipitation ranges from 684 to 833 mm (Nafría-García et al. 2013). Altitude varies from 1093 to 1277 m a.s.l., and the slope from 0.9 to 20%. The geological parent materials are sandstones and marl from the Mesozoic era (IGME 2015). The soils are Inceptisols with a xeric soil moisture regime and mesic soil temperature regime and they are classified as Typic Dystroxerept or Typic Humixerept (sensu Soil-Survey-Staff 2014). The sandy soil texture was dominant and the pH varies from extremely acid to strongly acid (see López-Marcos et al. 2018). The natural dominant vegetation in the study area, highly degraded by anthropogenic action, is characterised by Pyrenean oak (Quercus pyrenaica Willd.) forests or communities dominated by junipers (López-Marcos et al. 2018). Each triplet consisted of two plots dominated either by Pinus sylvestris (PS) or Pinus pinaster (PP) and one plot with a mixture of both species (MM) located less than 1 km from each other so that the environmental conditions were homogeneous within the triplet (Figure 26). Plots were circular of radius 15 m and the tree species composition was the main varying factor (López-Marcos et al. 2018). The percentage of the basal area of the dominant species in the monospecific plots was greater than 83% or 95% for P. sylvestris or P. pinaster respectively, whereas the basal area percentage of both species in the mixed plots ranged from 33 to 67%. Historically, this area has been occupied by forests and, for decades, it has been traditionally managed through selective thinning, benefiting P. sylvestris. The stands have had no silvicultural intervention or damage in the last ten years in an attempt to minimize the effect of the thinning or another type of intervention in what is intended to study, either growth, floristic richness or soil nutrients. The age of trees in the plots ranged from 44 to 151 years, the stand density from 509 to 1429 trees ha-1, the basal area from 33.3 to 70.3 m2 ha-1 and the dominant height between from 15.6 to 25.0 m (see López-Marcos et al. 2018). These plots belong to the network Daphne López-Marcos PhD. Thesis 82 of permanent plots of iuFOR-UVa and they have been previously used in a series of studies recently (Riofrío et al. 2017a; Cattaneo 2018; López-Marcos et al. 2018). Figure 26. Location of the triplets in the ‘Sierra de la Demanda’ in North-Central Spain and location of the plots in each triplet. Pinus sylvestris monospecific plots (PS): red circles; Pinus pinaster monospecific plots (PP): yellow circles; Mixed plots of both Pinus species (MM): blue circles. Understory and soil sampling Within each plot, 10 quadrats (1m×1m) were randomly located and the cover (%) of every understory vascular plant species present in each quadrat, including tree regeneration, was estimated visually by the same observer in June 2016 to encompass and better identify the maximum number of vascular plant species (Martínez-Ruiz and Fernández-Santos 2005). Vascular plant species were classified according to the Raunkiær´s classification of life-forms (1934) following (Aizpiru et al. 2007); see Appendix IIb. Therophytes are annuals plants whose shoot and root systems die after seed production and which complete their whole life cycle within one year; hemicryptophytes are perennial herbaceous plants with periodic shoot reduction to a remnant shoot system that lies relatively flat on the ground surface; geophytes have subterranean resting buds (i.e. bulbs, rhizomes…); chamaephytes (dwarf shrubs) are woody plants whose natural branch or shoot system remains perennially between 25 and 50 cm above ground surface; and phanerophytes (tree regeneration and shrubs) are woody plants that grow taller than 25-50 cm. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 83 Tree regeneration included the main tree species found as seedlings/saplings (i.e. Pinus sylvestris, P. pinaster, Quercus pyrenaica, and Q. faginea Lam.). In these stands, there are not subordinate tree species. Only two layers of vegetation can be distinguished (overstory and understory): the overstory measuring c.a. 20 m in height, and the understory with only 20 cm in height c.a., and never higher than 1 m. At the same time as the vegetation sampling, one soil pit of at least 50 cm depth was dug in each plot for soil profile characterization (López-Marcos et al. 2018). Two undisturbed soil samples were collected from each pit’s soil horizon with steel cylinders (98.2 cm3) to keep their original structure. Likewise, one disturbed sample was also taken from each pit’s soil horizon (ca. 2.5 kg). Laboratory analyses Both undisturbed and disturbed soil samples were dried at 105°C for 24 h before analyses. Undisturbed soil samples were weighed (±0.001 g) and used to calculate the soil bulk density. Disturbed soil samples were sieved (2 mm) before physical and chemical analyses. Physical analyses included percentage by weight of coarse fraction (>2 mm; %stones) and earth fraction (<2 mm; %EF). Available water was determined by the MAPA (1994) method as the difference between water content at field capacity (water remaining in a soil after it has been thoroughly saturated for two days and allowed to drain freely) and the permanent wilting point (soil water content retained at 1500 kPa using Eijkelkamp pF Equipment). Chemical parameters analyzed for each soil horizon included: easily oxidizable carbon using the K-dichromate oxidation method (Walkley 1947); total organic carbon and total nitrogen by dry combustion using a LECO CHN-2000 elemental analyzer; available phosphorus using the Olsen method (Olsen and Sommers 1982) and exchangeable cations (Ca+2, Mg+2, K+, Na+) were extracted with 1M ammonium acetate at pH=7 (Schollenberger and Simon 1945) and determined using an atomic absorption/emission spectrometer. Data analyses In each horizon, the water holding capacity (WHC) and the stock of different soil properties were calculated as indicated in Appendix IIb). The water holding capacity and the stocks of different soil properties in the soil profile (0-50 cm) were then calculated as the sum of the values of each horizon (see Appendix IIb). Richness was calculated as the total number of vascular plant species present in each plot (Colwell 2009), including understory vegetation and tree regeneration. Although several indices of diversity were tested, only the number of species showed to differ among stand types and Daphne López-Marcos PhD. Thesis 84 thus is shown in results. The cover (%) of each Raunkiær’s life-form in each plot was calculated as the average of the 10 vegetation sampling quadrats per plot. 2 tests of independence were carried out to compare the relative contribution of Raunkiær’s life-forms to the total cover and richness within each stand type. A redundancy analysis (RDA), as a linear-constrained ordination method with data scale standardization for units homogenization, was performed to describe the plant community using as vegetation variables the absolute cover data of Raunkiær’s life-forms, and the basal area (G) of all stems > 7.5 cm in diameter for every Pinus species in each plot. The vegan ‘envfit’ function fitted onto the RDA ordination plot with 9999 permutations (Oksanen 2016) was used to show that the type of stand but not the triplet determined differences in floristic composition between plots. Additionally, sample ordination scores were tested for a significant correlation with the vegetation variables by means of the Pearson's coefficient. To assist in the interpretation of the ordination axes according to the soil properties (Appendix IIc), these were fitted as vectors onto the RDA ordination plot using the vegan ‘envfit’ function. The advantage of the method is that it allows to test the significance of each vector adjusted by 9999 permutations, being able to calculate the R2 of each variable. The explanatory variables considered in the analysis were the water holding capacity and the stocks of different soil properties in the whole soil profile (0-50 cm). Moreover, sample ordination scores along RDA1 and RDA2 were tested for a significant correlation with the significant soil properties by means of Pearson's coefficient. The responses of each functional group (Raunkiær’s life-forms) and understory richness along RDA1 and the values of the significant soil properties (WHC, total organic carbon stock (Cstock), and exchangeable magnesium stock (Mg+2stock) were modeled by Huisman-OlffFresco (HOF) models (Huisman et al. 1993). These are a hierarchical set of five response models, ranked according to their increasing complexity (Model I, no species trend; Model II, increasing or decreasing trend where the maximum is equal to the upper bound; Model III, increasing or decreasing trend where the maximum is below the upper bound; Model IV, symmetrical response curve; Model V, skewed response curve. The AIC statistic (Akaike Information Criterion; Akaike 1973) was used to select the most appropriate response model for each life form (Johnson and Omland 2004); smaller values of AIC indicate better models. All statistical analyses were implemented in the R software environment (version 3.3.3; R Development Core Team 2016), using the vegan package for multivariate analyses (version 2.3-5; Oksanen 2016), and the eHOF package for HOF modeling (version 3.2.2; Jansen and Oksanen 2013). One monospecific plot of P. sylvestris was considered an outlier and excluded Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 85 from all analyses because it was the only one that presented aquic conditions (see LópezMarcos et al. 2018). Soils which have an aquic moisture regime are saturated long enough to cause anaerobic conditions (Soil-Survey-Staff 2014). Results Raunkiær’s life-forms in the understory The relative contribution of Raunkiær’s life-forms to the total cover and richness of the understory within each stand type differed significantly (cover: 2=43.7, df = 8, p<0.001, Figure 27a; richness: 2=16.4, df=8, p<0.04, Figure 27b). In both monospecific stands, phanerophytes (mostly in PS) and chamaephytes (mostly in PP) reached the highest relative cover and also contributed to high relative percentages of species richness; hemicryptophytes presented lower relative cover but higher or similar relative species richness than phanerophytes and chamaephytes; and geophytes and therophytes showed the lowest relative cover and scarce relative contribution to the total species richness, especially in PP. Figure 27. Relative cover (a) and species richness (b) of different Raunkiær’s life-forms in the understory of the three stand types. Abbreviations as in Figure 26. Nevertheless, in mixed stands (MM), chamaephytes and hemicryptophytes were the lifeforms with the highest relative cover (45.6±14.7 and 22.8±6.8%, respectively) and contributed also to high relative percentages of species richness (21.1±6.7 and 33.0±6.2%, respectively); phanerophytes reached lower relative cover (14.5±5.8%) but higher or lower relative species richness (25.7±8.2%) than chamaephytes and hemicryptophytes, respectively; and geophytes Daphne López-Marcos PhD. Thesis 86 and therophytes continue to be the life-forms that less contribute to the total cover and richness. Relationship between the overstory and the understory vegetation The RDA ordination of the plots produced eigenvalues () of 2.52 and 1.14 for the first two axes, and accounted for 36 and 23 % of the overall species variance, respectively (Figure 28). The plots dominated by P. sylvestris cluster together on the right of the diagram, those dominated by P. pinaster cluster on the left, whereas the mixed plots occupy an intermediate position (Figure 28). Thus, RDA1 showed an overstory composition gradient to which the understory responds. In fact, highly significant correlation between plot scores along RDA1 and basal area (G) of P. sylvestris (r = 0.89, p<0.005) and of P. pinaster (r = -0.93, p<0.005) were found, showing both an opposite tendency; the basal area of P. pinaster increases towards the negative end of the RDA1 while the basal area of P. sylvestris increases towards the positive end. Also the cover of therophytes (r = 0.59, p<0.01) and chamaephytes (r = -0.46, p<0.05) were correlated to RDA1 with an opposite trend, suggesting greater cover of therophytes in PS and greater cover of chamaephytes in PP, in accordance with what is shown in Figure 27a. On the other hand, hemicryptophytes (r = 0.68, p<0.005), phanerophytes (r = -0.64, p<0.005) and geophytes (r = 0.71, p<0.005) were significantly correlated to RDA2, suggesting greater cover of hemicryptophytes and geophytes in some P. sylvestris monospecific plots and mixed plots, and greater cover of phanerophytes in some P. sylvestris monospecific plots. Figure 28. RDA biplot of plots (dots) and vegetation variables (green lines), i.e. the Raunkiær’s life-forms cover, and the basal area (G) of Pinus sylvestris and P. pinaster; and the significant explanatory soil properties fitted onto the RDA as vectors using the envfit function (brown solid line: p<0.05; brown dashed lines: p<0.10; explained variation > 50%). WHC (water holding capacity), Cstock (total organic carbon stock), Mg+2stock (exchangeable magnesium stock). Other abbreviations as in Figure 26. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 87 Understory compositional change along the main gradients identified Understory richness showed an increasing trend bounded below the maximum attainable response along RDA1 (HOF model III; Figure 29a), i.e. as the basal area (G) of P. sylvestris increases. Understory richness also showed an increasing trend but where the maximum is equal to the upper bound (HOF model II) as WHC (Figure 29c) and Mg+2stock (Figure 29d) increase, whereas richness showed no response (HOF model I) to Cstock and, thus, it was not shown in Figure 29. Figure 29. HOF-derived response curves for the Raunkiær’s life-forms cover and total species richness of the understory, relative to RDA1 (a), and to significant soil properties, i.e. Cstock (b), WHC (c) and Mg+2stock (d). Abbreviations as in Figure 28. 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For Ecol Manage 174:167–176. doi: 10.1016/S0378-1127(02)00027-0 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 99 Zeller L, Ammer C, Annighöfer P, et al (2017) Forest ecology and management tree ring wood density of Scots pine and European beech lower in mixed-species stands compared with monocultures. For Ecol Manage 400:363–374. doi: 10.1016/j.foreco.2017.06.018 Daphne López-Marcos PhD. Thesis 100 Appendix IIa Table 12. Species classification according to the Raunkiær’s life-forms (Raunkiær 1934), following Aizpiru et al. (2007), their protection status in Spain according to Anthos (2017) project [(http://www.anthos.es/): CR: critically endangered; EN: endangered; VU: vulnerable (UICN 2012) and SpI: speciel interest], and Raunkiær’s life-forms cover (%) of each stand type. Lifeforms Species Protection status Raunkiær’s life-forms cover (%) Status Law Red book Region PS MM (mean±SE) PP Therophytes Aira caryophyllea L. 1.37±1.02 1.37±0.81 0.17±0.11 Geranium robertianum L. Melampyrum pratense L. Geophytes Pteridium aquilinum (L.) Kuhn VU 7 b Murcia 5.75±2.37 2.08±1.04 0.08±0.08 Asphodelus albus Mill. Simethis mattiazzii (Vand.) Sacc. EN 14 e Cataluña Hemicryptophytes Viola montcaunica Pau SI 5 Castilla la Mancha 8.87±2.66 7.32±2.69 4.92±3.24 Polygala vulgaris L. VU a Baleares Potentilla montana Brot. Agrostis castellana Boiss. & Reut. Galium saxatile L. Juncus conglomeratus L. Hypochaeris radicata L. Lotus corniculatus L. SpI 6 Extremadura Sanguisorba minor Scop. Deschampsia flexuosa (L.) Trin. Chamaephytes Erica australis L. 21.13±8.21 26.08±9.21 29.00±7.3 2 Erica arborea L. EN b Murcia Arenaria montana L. Calluna vulgaris (L.) Hull Arctostaphylos uva-ursi (L.) Spreng. SI 7 b Murcia Vaccinium myrtillus L. Phanerophytes Quercus pyrenaica Willd. CR 5,8,10, 11 d Spain 11.53±3.10 5.83±2.5 7.50±2.22 Ilex aquifolium L. VU 1,2,3,5, 6,9,11, 13 d Spain Pinus sylvestris L. Pinus pinaster Aiton SpI 5,10 a,b Baleares, Castilla la Mancha, Murcia Quercus faginea Lam. EN 4,7,13 b,c,d Spain Cistus laurifolius L. Juniperus oxycedrus L. EN 7 a Murcia 0F i Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 101 1Orden de 5 de noviembre de 1984 sobre protección de plantas de la flora autóctona amenazada de Cataluña. D.O.G.C. núm. 493, 12 de diciembre de 1984, págs. 3505-3506 2Orden de 10 de diciembre de 1984, sobre protección del acebo (Ilex aquifolium L.) en el territorio de la Comunidad Autónoma de Galicia. D.O.G. núm. 240, 15 de diciembre de 1984, págs. 4240-4241 3Decreto 18/1992, de 26 de marzo por el que se aprueba el Catálogo Regional de Especies Amenazadas de Fauna y Flora Silvestres y se crea la categoría de árboles singulares. B.O.C.M. núm. 85, 9 de abril de 1992, págs. 5-11 4Decreto 65/1995, de 27 de abril por el que se crea el Catálogo Regional de Especies Amenazadas de la Flora del Principado de Asturias y se dictan normas para su protección. B.O.P.A. núm. 128, 28 de junio de 1995, págs. 6118-6120 5Decreto 33/1998, de 5 de mayo de 1998 por el que se crea el Catálogo Regional de Especies Amenazadas de Castilla-La Mancha. D.O.C.M. núm. 22, 15 de mayo de 1998, págs. 3391-3398 6Decreto 37/2001, de 6 de marzo por el que se regula el Catálogo Regional de Especies Amenazadas de Extremadura. D.O.E. núm. 30, 13 de marzo de 2001, págs. 2349-2364 7Decreto 50/2003, de 30 de mayo por el que se crea el Catálogo Regional de Flora Silvestre Protegida de la Región de Murcia y se dictan normas para el aprovechamiento de diversas especies forestales. B.O.R.M. núm. 131, 10 de junio de 2003, págs. 11615-11624 8Ley 8/2003, de 28 de octubre de la flora y la fauna silvestres. B.O.J.A. núm. 218, 12 de noviembre de 2003, págs. 2379023810 9Decreto 181/2005, de 6 de septiembre del Gobierno de Aragón, por el que se modifica parcialmente el Decreto 49/1995, de 28 de marzo, de la Diputación General de Aragón, por el que se regula el Catálogo de Especies Amenazadas de Aragón. B.O.A. núm. 114, 23 de septiembre de 2005, págs. 11527-11532 10Decreto 63/2007, de 14 de junio por el que se crean el Catálogo de Flora Protegida de Castilla y León y la figura de protección denominada Microrreserva de Flora. B.O.C.yL. núm. 119, 20 de junio de 2007, págs. 13197-13204 11Decreto 70/2009, de 22 de mayo del Consell, por el que se crea y regula el Catálogo Valenciano de Especies de Flora Amenazadas y se regulan medidas adicionales de conservación. D.O.C.V. núm. 6021, 26 de mayo de 2009, págs. 2014320162 11Decreto 70/2009, de 22 de mayo del Consell, por el que se crea y regula el Catálogo Valenciano de Especies de Flora Amenazadas y se regulan medidas adicionales de conservación. D.O.C.V. núm. 6021, 26 de mayo de 2009, págs. 2014320162 12Orden de 10 de enero de 2011, de la Consejera de Medio Ambiente, Planificación Territorial, Agricultura y Pesca, por la que se modifica el Catálogo Vasco de Especies Amenazadas de la Fauna y Flora Silvestre y Marina, y se aprueba el texto único. B.O.P.V. núm. 37, 23 de febrero de 2011, págs. 1-12 13Decreto 23/2012, de 14 de febrero por el que se regula la conservación y el uso sostenible de la flora y la fauna silvestres y sus hábitats. B.O.J.A. núm. 60, 27 de marzo de 2012, págs. 114-163 14Resolución AAM/732/2015, de 9 de abril, por la que se aprueba la catalogación, descatalogación y cambio de categoría de especies y subespecies del Catálogo de flora amenazada de Cataluña. D.O.G.C. núm. 6854, 20 de abril de 2015, págs. 1-21 aSáez, Ll. & Rosselló, J.A. 2001. Llibre vermell de la flora vascular de les Isles Balears. Consejería de Medio Ambiente, Gobierno de las Islas Baleares, Palma de Mallorca, 232 p bSánchez Gómez, P., Carrión Vilches, M.A., Hernández González, A. & Guerra Montes, J. 2002. Libro rojo de la flora silvestre protegida de la Región de Murcia. Consejería de Agricultura, Agua y Medio Ambiente, D.G. del Medio Natural, Murcia, 685 p. cCabezudo, B., Talavera, S., Blanca, G., Salazar, C. Cueto, M.J., Valdés, B., Hernández Bermejo, J.E., Herrera, C., Rodríguez Hiraldo, C. & Navas, D. 2005. Lista roja de la flora vascular de Andalucía. Consejería de Medio Ambiente, Junta de Andalucía, Sevilla, 126 p dBañares, A., Blanca, G., Güemes, J., Moreno, J.C. & Ortiz, S., eds. 2008. Lista roja 2008 de la flora vascular española. Dir. Gen. de Medio Natural y Política Forestal (Min. de Medio Ambiente, y Medio Rural y Marino) - SEBICOP, Madrid eSáez, Ll., Aymerich, P. & Blanché, C. 2010. Llibre vermell de les plantes vasculars endèmiques i amenaçades de Catalunya. Argania Ed., Barcelona, 811 p. Daphne López-Marcos PhD. Thesis 102 Appendix IIb Table 13. Data analyses of soil properties: Water holding capacity. Water holding capacity of each horizon (WHCHi) WHCHi = UWHi⋅bDHi⋅%EFHi THi UWHi: Useful water of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Water holding capacity in the whole mineral soil profile (0-50cm; WHC): WHC = ∑ WHCHi Table 14. Data analyses of soil properties: Easily oxidizable carbon stock. Easily oxidizable carbon stock of each horizon (oxCstockHi) oxCstockHi = oxCHi⋅bDHi⋅%EFHi THi oxCHi: Easily oxidizable carbon of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Easily oxidizable carbon stock in the whole mineral soil profile (0-50cm; oxCstock) oxCstock = ∑ oxCstockHi Table 15. Data analyses of soil properties: Total organic carbon stock. Total organic carbon stock of each horizon (CstockHi) CstockHi = TOCHi⋅bDHi⋅%EFHi THi TOCHi: Total organic carbon of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Total organic carbon stock in the whole mineral soil profile (0-50cm; Cstock) Cstock = ∑ CstockHi Table 16. Data analyses of soil properties: Total nitrogen stock. Total nitrogen stock of each horizon (NstockHi) NstockHi = TNHi⋅bDHi⋅%EFHi TH i TNHi: total nitrogen of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Total nitrogen stock in the whole mineral soil profile (0-50cm; Nstock) Nstock = ∑ NstockHi Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 103 Table 17. Data analyses of soil properties: Available phosphorus stock. Available phosphorus stock of each horizon (PavstockHi) PavstockHi = TNHi⋅bDHi⋅%EFHi THi PavHi: total nitrogen of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Available phosphorus stock in the whole mineral soil profile (0-50cm; Pavstock) Pavstock = ∑ PavstockHi Table 18. Data analyses of soil properties: Exchangeable sodium stock. Exchangeable sodium stock of each horizon (Na+stockHi) Na+stockHi = TNHi⋅bDHi⋅%EFHi THi Na+Hi: Exchangeable sodium of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Exchangeable sodium stock in the whole mineral soil profile (0-50cm; Na+stock) Na+stock = ∑ Na+stockHi Table 19. Data analyses of soil properties: Exchangeable potassium stock. Exchangeable potassium stock of each horizon (K+stockHi) K+stockHi = TNHi⋅bDHi⋅%EFHi THi K+Hi: Exchangeable potassium of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Exchangeable potassium stock in the whole mineral soil profile (0-50cm; K+stock) K+stock = ∑ K+stockHi Table 20. Data analyses of soil properties: Exchangeable calcium stock. Exchangeable calcium stock of each horizon (Ca+2stockHi) Ca+2stockHi = TNHi⋅bDHi⋅%EFHi THi Ca+2Hi: Exchangeable calcium of each horizon bDHi: bulk density of each horizon %EFHi: % of earth fraction of each horizon THi: thickness of each horizon Exchangeable calcium stock in the whole mineral soil profile (0-50cm; Ca+2stock) Ca+2stock = ∑ Ca+2stockHi Daphne López-Marcos PhD. Thesis 110 Introduction The management of mixed forests is becoming a new paradigm (Bravo-Oviedo et al. 2014) in order to improve natural tree regeneration (Carnevale and Montagnini 2002; Löf et al. 2018), soil conditions (Brandtberg et al. 2000), and the provision of many high-value ecosystem services, including carbon sequestration (Gamfeldt et al. 2013; López-Marcos et al. 2018) or biodiversity conservation (Barbier et al. 2008; Gomez-Aparicio et al. 2009; Felton et al. 2010; Cavard et al. 2011; Korboulewsky et al. 2016); additionally, under certain conditions mixed forests can produce higher yields than monocultures (Saetre et al. 1997; Pretzsch et al. 2010; Gamfeldt et al. 2013; Toïgo et al. 2015; Jactel et al. 2018). Since the overstory tree species differ in their effects on microclimatic and edaphic conditions, it has been suggested that the environment in mixed stands is more heterogeneous compared with monocultures (Barkman 1992; Saetre et al. 1997). Thus, mixed stands have the potential to host a more heterogeneous and species-rich flora (Hill 1992; Saetre et al. 1997). Additionally, the greater variability of habitat conditions in mixed stands than in monospecific stands may be a favorable condition for seed dispersers, and germination and growth of native tree species (Carnevale and Montagnini 2002). The structure of the stands can also influence the establishment of native species through biotic interactions such as competition (Grace and Tilman 2003) and facilitation (Bruno et al. 2003; Callaway 2007; Brooker et al. 2008). Therefore, regeneration of mixed forests has become an important topic of practical concern throughout the world (Löf et al. 2018). The mass ratio hypothesis predicts that the ecosystem function is driven by the (traits of the) most abundant species in plant communities (Grime 1998; Ali and Yan 2017), such as specific leaf area or leaf nitrogen and phosphorus concentrations (Ali and Yan 2017). This hypothesis uses the relative abundance of each plant species to predict the effect of the most abundant species of plant communities on the ecosystem functions and services, like biodiversity (Grime 1998; Ali and Yan 2017). The application of this hypothesis is restricted to the role of autotrophs in ecosystem processes, and it postulates that the relationships between plant diversity and ecosystem properties can be explored by classifying species into categories, as dominants and subordinates (Grime 1998). Dominants are relatively large and make a substantial contribution to the plant community biomass, whereas subordinates show high fidelity of association with particular vegetation types but they are smaller and tend to occupy microhabitats delimited by the architecture and phenology of their associated dominants (Grime 1998). Most reports of the overstory-understory relationship in mixed forests focus on mixtures that combine deciduous-coniferous tree species (Saetre et al. 1997, 1999; Barbier et al. 2008; Cavard Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 111 et al. 2011; Inoue et al. 2017). They test the overstory effect on the understory biomass, songbirds, soil fauna, and ectomycorrhizae (Cavard et al. 2011), cover and structural heterogeneity (Saetre et al. 1997), plant biodiversity and the associated mechanisms (Barbier et al. 2008; Rodríguez-Calcerrada et al. 2011), the spatial relationship between the overstory and understory species distribution and soil nitrogen availability (Inoue et al. 2017), soil fauna diversity (Korboulewsky et al. 2016), or soil microbial biomass and activity (Saetre et al. 1999). However, the effect of the stand characteristics on the understory in mixtures that combine coniferous tree species or even tree species of the same genus remains virtually unknown (but see Mestre et al. 2017; López-Marcos et al. 2019). This is so despite these mixtures being frequent in many environments, such as the admixtures of Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.) in Spain. Both Pinus species show similar crown architecture and slight differences in shade tolerance (Riofrío et al. 2017a), but differ in water-stress tolerance (LópezMarcos et al. 2019). They are two of the main forest species in Spain and grow in pure and mixed stands either naturally or as a result of species selection for afforestation (Serrada et al. 2008). On the other hand, the facilitating effect of Pinus species in succession processes has already been well explored among restoration strategies such as the reintroduction of endangered tree species through the use of assisted regeneration; thus, the ecological and functional role of certain pioneer species may be of vital importance for the reestablishment of native ecosystems (Aguirre et al. 2006; Arrieta and Suárez 2006; Avendaño-Yáñez et al. 2016). Nevertheless, the use of evergreen conifers as nurse plants to establish Quercus spp. could reduced the cover of the understory and its species content (Pigott 1990). Additionally, the identification of realized niches of understory plant species and knowledge of their composition and dynamics can be important information to consider in the prediction models of potential responses to climate change (Olthoff et al. 2016). Based on the same experiment, we found that the composition of the overstory (i.e., the proportion of Pinus species) influenced the Raunkiær’s life-forms composition of the understory, with the abundance of hemicryptophytes being greater in mixed stands (López-Marcos et al. 2019). The effects of mixed versus monospecific stands on the understory were also related to soil water and fertility status (see also López-Marcos et al. 2019). In particular, mixed stands occupied areas with intermediate soil moisture whereas P. pinaster tolerated lower soil water content than P. sylvestris. The organic carbon and exchangeable magnesium stocks were also higher in mixed stands (see also López-Marcos et al. 2018). In the present paper, we addressed the influence of a mixture of these two widely distributed pine species (P. sylvestris and P. pinaster) on the understory plant community composition (at the species level) and the regeneration of main tree species, including native Quercus species, compared with monospecific Daphne López-Marcos PhD. Thesis 112 stands. For that, we used the same sampling design in triplets (monospecific P. sylvestris, monospecific P. pinaster and mixed P. sylvestris˗P. pinaster plots), well balanced for stand composition but not necessarily for other stand characteristics. The aims of this study were: (i) to test the effect of stand characteristics on species composition in the understory and tree regeneration; (ii) to model the response of distinct understory species and tree species regeneration to stand characteristics; and (iii) to estimate the niche amplitude of the main understory species, including tree regeneration, with respect to the stand characteristics. We hypothesized that (1) the proportion of Pinus species in the overstory is the most influential stand characteristic on the understory composition and tree regeneration according to previous studies; (2) the mixture of pine species favors the regeneration of native tree species like Pyrenean oak; and (3) the regeneration of native Pyrenean oak is accompanied by a group of associated understory species that contribute to maintain a high understory species richness in mixed stands as in monospecific P. sylvestris stands. Material and methods Study sites The research was carried out in eighteen forest plots (6 triplets) located in the Northern Iberian Range, in North-Central Spain (41º47'35''N and 41º53'41''N latitude, and 2º56'12''W and 3º20'46''W longitude; Figure 31). The climate is temperate with dry or temperate summer (Cfb, Csb) according to the Köppen (1936) classification for the Iberian Peninsula. The mean annual temperature is 9.0ºC and the annual precipitation around 800mm. Plots are located at an elevation ranging from 1093m to 1277m a.s.l. Soils are acidic with mostly sandy texture and medium to low water-retention capacity (see López-Marcos et al. 2018, 2019). Nearby climax vegetation (Rivas-Martínez 1987), highly degraded by anthropogenic action, is characterized by Pyrenean oak forests (Luzulo forsteri-Quercetum pyrenaicae S. and Festuco heterophyllaeQuercetum pyrenaicae S.) or juniper forests (Juniperetum hemisphaerico-thuriferae S.). Each triplet consisted of three circular plots of 15m radius, including two plots dominated either by Scots pine or Maritime pine and one mixed plot that contained both species, located less than 1km from each other so that the environmental conditions were homogeneous within triplets although they could differ among distinct triplets (see López-Marcos et al. 2018 for differences in soil properties). The sampling design in triplets was well balanced for stand composition (six repetitions per stand type) but not necessarily balanced for other stand characteristics (i.e., density, total basal area, dominant height, mean quadratic diameter, age) that were intended to be similar within the triplet (avoiding biases in the sampling design) but Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 113 differed between triplets to be able to be contrasted (see Table 25 in Appendix IIIb). The percentage of the basal area (%G) of the dominant species in the monospecific plots was greater than 83% or 95% for P. sylvestris or P. pinaster respectively, whereas the basal area percentage of both species in the mixed plots ranged from 33 to 67%. The age of the selected plots ranged between 44 and 151years, the stand density between 509 and 1429 trees ha-1, the basal area between 33.3 and 70.30m2ha-1, and the dominant height between 15.60 and 25.04m. Traditionally, forest management consists of strip clear-cutting with soil movement and planting or sowing when necessary, and moderate thinning from below (Riofrío et al. 2019). The stands have had no silvicultural intervention or damage in the last 10 years (López-Marcos et al. 2018). There were no statistical differences in the distance between the plots of the three stand types and forests of other tree species (Quercus pyrenaica Willd., Q. faginea Lam., or Juniperus spp.; see Figure 36 in Appendix IIIa). Triplets belong to the network of permanent plots of the Sustainable Forest Management Research Institute UVa-INIA (iuFOR) and they have been previously used in a series of recent studies (Riofrío et al. 2017a, b, 2019; Cattaneo 2018; LópezMarcos et al. 2018, 2019). Figure 31. Location of the triplets in the ‘Sierra de la Demanda’ in North-Central Spain, the plots within each triplet, and the native forests (Pyrenean oak forest, Gall oak forest and Juniper forest). Pinus sylvestris monospecific plots (PS): red circles; Pinus pinaster monospecific plots (PP): yellow circles; Mixed plots of both Pinus species (MM): blue circles. Location of understory inventories: black squares. Daphne López-Marcos PhD. Thesis 114 Sampling of understory vegetation and tree regeneration Within each plot, 10 quadrats (1m×1m) were randomly selected and the vertical projection cover (%) of every understory vascular plant species, including tree regeneration, and bryophytes was estimated visually by the same observer in June 2016 (López-Marcos et al. 2019) to encompass and identify the maximum number of vascular plant species (Alday et al. 2010). Vascular plant species nomenclature follows Tutin et al. (1964-1980) and bryophytes nomenclature follows Crosby et al. (1992-1989). The number of individuals (stems) of the tree regeneration was also counted within each quadrat. Tree regeneration included the main tree species found at seedlings/saplings stages (i.e., P. sylvestris, P. pinaster, Q. pyrenaica and Q. faginea) because no old regeneration was found (it had probably been cleared by management for fire prevention); only seven old individuals of Juniperus oxycedrus L. were found that were considered to be part of the understory (height <1m) but not as regeneration, thus, estimating their cover but not counting them as individuals. In these stands, there were no subordinate tree species. Only two layers of vegetation could be distinguished (overstory and understory): the overstory measuring c.a. 20 m, and the understory never higher than 1 m. Data analyses The cover (%) of each species and density of main tree species regeneration (i.e. P. sylvestris, P. pinaster, Q. pyrenaica, and Q. faginea) in each plot were calculated as the average of the 10 quadrats. Richness was calculated as the total cumulative number of plant species in the 10 quadrats per plot (Colwell 2009), including understory vegetation and tree regeneration. Although several indices of diversity were tested, only the number of species showed any difference among stand types and thus is shown in results. To identify the characteristics of the stands that determine the understory plant species composition, a Detrended Correspondence Analysis (DCA) was applied on the matrix of cover of the understory plant species (30 species x 17 plots). To assist in the interpretation of the ordination axes, the stand characteristics and tree regeneration were fitted as vectors onto the DCA ordination plot using the vegan ‘envfit’ function (Oksanen 2016). The advantage of this method is that it allows for testing the significance of each vector adjusted by 9999 permutations, with the R2 of each variable able to be calculated. The explanatory variables considered in the analysis were (1) the stand characteristics: normal age (Age: years), density (N: trees ha−1), total basal area (G: m2ha−1), dominant height (Ho: m), quadratic mean diameter (dq: cm), and the percentage of basal area (%G) of P. sylvestris and P. pinaster; and (2) the tree regeneration Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 115 (individuals m-2) of P. sylvestris, P. pinaster, Q. pyrenaica and Q. faginea. Additionally, in order to relate overstory composition to tree regeneration, and tree regeneration to main understory species, Pearson’s correlation coefficients (p<0.05) between the regeneration density of the main tree species (P. sylvestris, P. pinaster and Q. pyrenaica) and the percentages of basal area of P. sylvestris and P. pinaster, as well as between the regeneration cover (%) of main tree species and the cover (%) of main species of the understory, were calculated. The response of understory plant species (total species richness and individual species cover) and tree regeneration (density: individuals m-2) with respect to the significant stand characteristics (i.e., the overstory composition by means of the percentage of basal area of P. pinaster) were modeled by Huisman-Olff-Fresco (HOF) models (Huisman et al. 1993). These are a hierarchical set of five response models, ranked by their increasing complexity (Model I, monotone trend, i.e. with constant abundance; Model II, increasing or decreasing trend where the maximum is equal to the upper bound; Model III, increasing or decreasing trend where the maximum is below the upper bound; Model IV, symmetrical response curve; Model V, skewed response curve). The Akaike Information Criterion (AIC; Akaike 1973) was used to select the most appropriate response model (Johnson and Omland 2004); smaller values of AIC indicate better models. HOF models were validated using "bootstrapping" because the frequency of appearance of 33% of species in the plots was low (< 10%; mostly for species following HOF model I). Finally, the location of species optima (μ) and niche widths (2t) for those species with unimodal responses were derived from the HOF models (Lawesson and Oksanen 2002). The 2t values were found by solving for the gradient points of the fitted HOF model relative to a strict Gaussian model at 2t (Lawesson and Oksanen 2002) . In the case of a symmetric unimodal response, the lower and upper t values are identical, while with a skewed model, the 2t intervals are not necessarily equal. All statistical analyses were implemented in the R software environment (version 3.3.3; R Development Core Team 2016) using the vegan package for multivariate analyses (version 2.3-5; Oksanen 2016), and the eHOF package for HOF models (version 3.2.2; Jansen and Oksanen 2013). One monospecific plot of P. sylvestris was considered an outlier and excluded from all analyses because it was the only one that presented aquic conditions (see López-Marcos et al. 2019). Soils that have an aquic moisture regime are saturated long enough to cause anaerobic conditions (Soil-Survey-Staff 2014). Daphne López-Marcos PhD. Thesis 116 Results Effects of stand characteristics on the understory vegetation The DCA ordination produced eigenvalues (λ) of 0.50 and 0.35 for the first two axes, with gradient lengths of 2.62 and 2.52 SD units, respectively (Figure 32). The adjustment of explanatory variables on the biplot ordination showed how the percentages of the basal area (%G) of P. sylvestris and P. pinaster were the stand characteristics that explained most variability (0.7 in both cases), with both showing an opposite tendency (Figure 32). This suggests a gradual change in the composition of the understory related to the overstory composition. The other characteristics of the stands were not significantly correlated with the DCA ordination, and thus they are not displayed in results (but see Table 23). Figure 32. DCA biplot of plots and species and projection of the significant two significant explanatory variables (p<0.05 and explained variation >50%). Stand characteristics other than %G of Pinus sylvestris and % G of Pinus pinaster were not significantly correlated with the DCA axes. PS Pinus sylvestris monospecific plots, PP Pinus pinaster mpnospecific plots, and MM mixed plots pf two Pinus species. Species codes: Agca (Agrostis castellana Boiss. & Reut), Aica (Aira caryophyllea L.), Armo (Arenaria montana L.,; Aruv (Arctostaphylos uva-ursi (L.) Spreng), Asal (Asphodelus albus Mill.), Cavu (Calluna vulgaris (L.) Hull), Cila (Cistus laurifolius L.), Defl (Deschampsia flexuosa (L.) Trin.), Erar (Erica arborea L.), Erau (Erica australis L.), Gasa (Galium saxatile L.), Gero (Geranium robertianum L.), Hysp (Hypnum spp.), Hyra (Hypochaeris radicata L.), Ilaq (Ilex aquifolium L.), Juco (Juncus conglomeratus L.), Juox (Juniperus oxycedrus L.), Loco (Lotus corniculatus L.), Mepa (Melampyrum pratense L.), Pipi (Pinus pinaster Aiton), Pisy (Pinus sylvestris L.), Povu (Polygala vulgaris L.), Pomo (Potentilla montana Brot.), Ptaq (Pteridium aquilinum (L.) Kuhn), Qufa (Quercus faginea Lam.), Qupy (Quercus pyrenaica Willd.), Sami (Sanguisorba minor Scop.), Sima (Simethis mattiazzii (Vand.) Sacc.) and Vimo (Viola montcaunica Pau). Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 117 Thirty understory species from twenty-one families were recorded, with Ericaceae being the most frequent (88%) and abundant (24%) taxonomical group, with greater cover in monospecific stands of P. pinaster (29%) and mixed stands (26%), followed by bryophytes (Hypnaceae; 94% frequency and 5% cover), most abundant in monospecific stands of P. sylvestris (15%). Rosaceae was more abundant in monospecific stands of P. sylvestris (2.4%) and mixed stands (1.8%), and Poaceae in mixed stands (6.3%). A wide group of families displayed residual cover (<1%; Aquifoliaceae, Asteraceae, Caryophyllaceae, Fabaceae, Geraniaceae, Juncaceae, Liliaceae, Poligalaceae, Rubiaceae, Scrophulariaceae, Violaceae, and Xanthorrhoeaceae). Table 23. Explanatory variables fitted as vectors onto the DCA ordination plot using the vegan ‘envfit’ function. Significance of each vector adjusted by 9999 permutations, and R2 of each variable. N: density (trees ha−1), G: total basal area (m2 ha−1), Ho: dominant height (m), dq: quadratic mean diameter (cm), Age: normal age (years); % G PS: the percentage of basal area of Pinus sylvestris, % G PP: the percentage of basal area of P. pinaster; and the tree regeneration density (individuals m-2) of P. sylvestris, P. pinaster, Q. pyrenaica and Q. faginea. DCA1 DCA2 R2 p Stand characteristics % G PS -0.544 0.839 0.484 0.019 * % G PP 0.544 -0.839 0.484 0.019 * N (trees ha−1) -0.114 -0.993 0.309 0.087 G (m2 ha−1) -0.751 -0.665 0.237 0.160 Ho (m) -0.829 0.559 0.305 0.081 dq (cm) -0.524 0.851 0.162 0.298 Age (years) -0.744 0.668 0.360 0.090 Tree regeneration density (ind/m2) P. sylvestris 0.284 0.959 0.365 0.015 * P. pinaster 0.977 -0.212 0.583 0.001 *** Q. pyrenaica -0.556 -0.831 0.413 0.011 * Q. faginea 0.985 0.171 0.602 0.004 ** Tree regeneration patterns along the overstory composition gradient The adjustment of tree regeneration, i.e. density (individuals m−2) of P. sylvestris, P. pinaster, Q. pyrenaica, and Q. faginea on the DCA ordination (Figure 33a) showed how tree regeneration was significantly correlated with the understory composition (r = 0.61, p = 0.015; r = 0.76, p = 0.001; r = 0.64, p = 0.011; and r = 0.78, p = 0.004, respectively), and is also related to the tree overstory composition. Indeed, P. sylvestris regeneration was positively correlated with the percentage of basal area of P. sylvestris (r = 0.48, p<0.05) and negatively correlated with the percentage of basal area of P. pinaster (r = -0.48, p=0.03). The P. pinaster regeneration was positively correlated with the percentage of basal area of P. pinaster (r = 0.46, p<0.05) and negatively correlated with the percentage of basal area of P. sylvestris (r = -0.46, p<0.05). On the other hand, the regeneration of distinct tree species with respect to overstory composition (Figure 33b) showed four different types of responses. Q. faginea (HOF model I) Daphne López-Marcos PhD. Thesis 118 showed monotone response and is not shown in Figure 33b; its presence was sporadic; only 12 individuals were found covering less than 1%. P. sylvestris showed a decreasing trend (HOF model II) as the percentage of basal area of P. pinaster increased. P. pinaster showed an increasing trend (HOF model II) as the percentage of basal area of P. pinaster increased. Lastly, the regeneration of Q. pyrenaica exhibited a symmetrical unimodal response curve (HOF Model IV), with higher density for intermediate percentages of P. pinaster basal area, i.e., in mixed stands. As a whole, 291 individuals of P. sylvestris, 215 individuals of P. pinaster and 129 individuals of Q. pyrenaica were recorded. Figure 33. (a) DCA of plots and projection of the significant explanatory variables (p<0.05 and explained variation >50%),. i.e. % G of Pinus sylvestris and % G of Pinus pinaster in brow, and the tree regeneration i.e. individuals m-2 of Pinus sylvestris, Pinus pinaster, Quercus pyrenaica and Quercus faginea in green. (b) HOF-derived response curves of the regeneration of tree species relative to the main gradient (% of G of Pinus pinaster). Abreviations as in figure 31. Relating the regeneration of main tree species to the species of the understory The regeneration cover of P. sylvestris was positively correlated with the cover of some hemicryptophytes (Hypochaeris radicata, Sanguisorba minor) and some therophytes (Geranium robertianum, Melampyrum pratense), and negatively correlated with the cover of the chamaephyte Erica australis (see Table 24). The regeneration cover of P. pinaster was positively correlated with the cover of Calluna vulgaris (chamaephyte) and negatively correlated with the cover of bryophytes (Hypnum spp.). The regeneration cover of Q. pyrenaica was positively correlated with the cover of some hemicryptophytes (Viola montcaunica, Polygala vulgaris, Agrostis castellana), and some shrub species: Erica arborea (chamaephyte) and Ilex aquifolium (phanerophyte). Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 119 Table 24. Pearson’s correlation coefficients between the regeneration cover (%) of main tree species, i.e. Pinus sylvestris (Pisy), Pinus pinaster (Pipi) and Quercus pyrenaica (Qupy), and the cover (%) of main understory species. Only significant correlations are shown (p<0.05). Species codes in Figure 32. Pisy Qupy Pipi Agca +0.54 Cavu +0.80 Erar +0.84 Erau -0.46 Gero +0.69 Hyra +0.46 Hysp -0.48 Ilaq +0.57 Mepa +0.68 Povu +0.55 Sami +0.69 Vimo +0.42 Understory species patterns along the overstory composition gradient The understory richness showed a decreasing trend bounded below the maximum attainable response where the percentage of basal area of P. pinaster was lower (HOF model III; Figure 34a). Responses of individual species with respect to the overstory composition separated the understory species into four groups. Group 1 (HOF model I) included 14 species that showed a monotone response and which are not shown in Figure 34; they mostly had cover ≤ 1%: Arenaria montana (0.09%), Asphodelus albus (0.24%), Galium saxatile (0.32%), Geranium robertianum (0.01%), Hypochaeris radicata (0.10%), Ilex aquifolium (0.06), Juncus conglomeratus (0.09%), Lotus corniculatus (0.03%), Melampyrum pratense (0.28%), Polygala vulgaris (0.18%), Quercus faginea (0.16%), Sanguisorba minor (0.01%), Simethis mattiazzii (0.12%) and Viola montcaunica (0.28%). Group 2 (Figure 34a) contained two species, P. sylvestris (Pisy; HOF model II) with a decreasing trend as the P. pinaster basal area increased and Hypnum spp. (Hysp; HOF model V) with asymmetrical response curve and with the maximum skewed at the minimum P. pinaster basal area. Group 3 (Figure 34b) included four woody species showing HOF model II with an increasing trend as the Pinus pinaster basal area increased, which were Arctostaphylos uva-ursi (Aruv), Pinus pinaster (Pipi), Calluna vulgaris (Cavu), and Cistus laurifolius (Cila), and two species with skewed response curve (HOF model V) with the maximum at the maximum values of Pinus pinaster basal area, which were Erica australis (Erau) and Deschampsia flexuosa (Defl). Lastly, seven species in Group 4 (Figure 34c) exhibited symmetrical unimodal response curves (HOF Model IV): Pteridium aquilinum (Ptaq), Erica arborea (Erar), Q. pyrenaica (Qupy), Juniperus oxycedrus (Juox), Aira caryophyllea (Aica), Agrostis castellana (Agca) and Potentilla montana Daphne López-Marcos PhD. Thesis 126 species richness (Brockerhoff et al. 2017), the encouraging of native tree regeneration in forest management plans is needed, not only in forest management plans whose objective is to include forest biodiversity as an ecosystem service but also when production is the main objective. Understanding the ecology of the understory vegetation has important implications for both biodiversity conservation and production-oriented forest management (Nilsson and Wardle 2005). Conclusion The composition of the understory and tree regeneration are influenced by the overstory composition but, according to previous studies, also by the soil conditions (soil water and fertility) that vary with the overstory composition. Species characteristic of humid and temperate zones, including P. sylvestris regeneration, dominate in P. sylvestris monospecific stands, and typical species of well-drained Mediterranean areas, including P. pinaster regeneration, dominates in P. pinaster monospecific stands. In mixed stands, where fertility is higher, the regeneration of the western European endemic species, Q. pyrenaica, is added to the regeneration of Pinus species. Also a positive effect of the studied mixture is observed on understory richness, similar to that of P. sylvestris monospecific stands but under lower soil water content. Understory species typical of the native Pyrenean oak forests in the Iberian Peninsula, which share with Q. pyrenaica the same regeneration niche, contribute to maintain high understory richness in such mixed pine forests. These results should make us reflect on the use of mixed stands (even when tree species are of the same genus) as a strategy for biodiversity conservation, through native tree regeneration and their accompanying understory species conservation. Acknowledgments We would like to thank Luis Alfonso Ramos Calvo for his invaluable help with soil sampling, Carmen Blanco and Juan Carlos Arranz from the University of Valladolid (UVa) for their advice in the laboratory analyses, José Riofrío and Cristóbal Ordoñez for their assistance in the characterization and location of plots in the field, the Regional Forest Service of Castilla and León for facilitatingthe triplet installation and monitoring, and Juan Manuel Díez Clivillé for language improvement. We also thank, Erwin Dreyer (Editor-in-Chief), Laurent Begès (Handling Editor), and two anonymous reviewers for their valuable comments to improve the manuscript. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 127 Contributions of the co-authors Conceptualization: DLM, CMR, MBT, FB. Methodology, Software: DLM, CMR; Validation: DLM, CMR. Formal analysis: DLM, CMR. Investigation: DLM, CMR, MBT, FB. Resources: CMR, MBT, FB. Data curation: DLM, CMR, MBT, FB. Writing: original draft: DLM, CMR, MBT, FB. Writing: review and editing: DLM, CMR, MBT, FB. Visualization: DLM, CMR, MBT, FB. Supervision: CMR, MBT, FB. Project administration: FB, funding acquisition: CMR, MBT, FB. Funding information This research was funded by a predoctoral grant to DLM (BES-2015-072852) and the Project FORMIXING (AGL2014-51964-C2-1-R) from the Ministry of Economy and Competitiveness of the Spanish Government. Data availability The data that support the findings of this study are available from Daphne LópezMarcos but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Felipe Bravo. Compliance with ethical standards The authors declare that they have no conflict of interest References Aguirre N, Sven G, Michael W, Bernd S (2006) Enrichment of Pinus patula plantations with native species in southern Ecuador. Lyonia 10 (1):17-29 Akaike H (1973) Information theory as an extension of the maximum likelihood principle. In: Brillinger D, Gani J, Hartigan J (eds) Second international symposium on information theory. Akademiai Kiado, Budapest (Hungary), pp 267–281 Alcántara JM, Garrido JL, Rey PJ (2019) Plant species abundance and phylogeny explain the structure of recruitment networks. 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PhD Dissertation, Universidad Complutense de Madrid (Spain) Wang J, You Y, Tang Z, et al (2016) A comparison of decomposition dynamics among green tree leaves, partially decomposed tree leaf litter and their mixture in a warm temperate forest ecosystem. J For Res 27:1037–1045. doi: 10.1007/s11676-016-0248-8 Yu F, Wang D, Yi X, et al (2014) Does animal-mediated seed dispersal facilitate the formation of pinus armandii-quercus aliena var. Acuteserrata forests? PLoS One 9:. doi: 10.1371/journal.pone.0089886 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 133 Appendix IIIa Figure 36. Distance from the center of the plots of different overstory composition (PS, MM, PP) to the nearest native forest of Pyrenean oak (Quercus pyrenaica Will.), Gall oak (Quercus faginea Lam.), or Juniper (Juniperus spp.), according to the cartographic server (WMS) of the Ministry for the Ecological Transition of the Government of Spain (http://wms.mapama.es/sig/Biodiversidad/). Daphne López-Marcos PhD. Thesis 134 Appendix IIIb Table 25. Descriptive statistics (Minimum (Min) ,Maximum (Max), and mean ± standard error (Mean±SE)) of stand characteristics (N: density (trees ha-1), G: basal area (m2ha-1), Ho: dominant height (m), dq: quadratic mean diameter (cm), and Age: normal age (years)) of three types of stands. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 135 Appendix IIIc Table 26. Location of optimum (μ), predicted maximum probability of occurrence (h) and niche amplitude based on 2t tolerances, for species with unimodal response along the main coecocline (%G of Pinus pinaster), as well as the frequency of species appearance in the plots (%). Specie Model h µ 2t % Agrostis castellana Boiss. and Reut IV 2.83 36.68 66.94 70.59 Aira caryophyllea L. IV 4.61 31.97 9.03 41.18 Deschampsia flexuosa (L.) Trin. V 3.76 72.89 58.75 41.18 Erica arborea L. IV 6.48 34.46 43.25 23.53 Erica australis L. V 24.10 78.97 43.50 82.35 Hypnum spp. V 18.58 19.47 42.55 94.12 Juniperus oxycedrus L. IV 10.74 6.37 3.21 11.76 Potentilla montana Brot. IV 4.79 29.86 36.93 52.94 Pteridium aquilinum (L.) Kuhn IV 9.28 18.02 13.95 29.41 Quercus pyrenaica Willd. IV 4.08 40.93 60.88 29.41 Daphne López-Marcos PhD. Thesis 142 determining the overstory yield differences by scale; and (3) to analyse the overstory yield effect on the understory richness in mixed vs. monospecific pine forests. We hypothesize that there is an overstory overyielding in mixed stand, only detected at small spatial scale, caused by soil niche complementarity. Material and methods Study sites The research was carried out in eighteen forest plots (6 triplets) located in the Northern Iberian Range, in North-Central Spain (41°47'35''N and 41°53'41''N latitude, and 2°56'12''W and 3°20'46''W longitude; Figure 38). The climate is Temperate with dry or temperate summer (Cfb, Csb) according to the Köppen (1936) classification for the Iberian Peninsula. The mean annual temperature ranges from 8.7 to 9.8 °C and the annual precipitation ranges from 684 to 833 mm (Nafría-García et al. 2013). Altitude varies from 1093 m to 1277 m a.s.l., and the slope from 0.9 to 20% (López-Marcos et al. 2018, 2019). The geological parent materials are sandstones and marl from the Mesozoic era (IGME 2015). The soils are Inceptisols with a xeric soil moisture regime and mesic soil temperature regime and they are classified as Typic Dystroxerept or Typic Humixerept (sensu Soil-Survey-Staff 2014). The sandy soil texture was dominant and the pH varies from extremely acid to strongly acid (see López-Marcos et al. 2018). Nearby climax vegetation, highly degraded by anthropogenic action, is characterized by Pyrenean oak (Quercus pyrenaica Willd.) forests or communities dominated by junipers (López-Marcos et al. 2018). Each triplet consisted of three circular plots of 15 m radius, including two plots dominated either by P. sylvestris (PS) or P. pinaster (PP) and one mixed plot that contained both species (MM), located less than 1 km from each other so that the environmental conditions were homogeneous within the triplet (Figure 38), although they could differ among distinct triplets (e.g. soil properties; see López-Marcos et al. 2018). In particular, a water-stress gradient associated with the overstory composition indicated that P. pinaster tolerated lower soil water content than P. sylvestris whereas mixed stands occupied areas with intermediate soil moisture. In addition, a soil fertility gradient defined by organic carbon and exchangeable magnesium stocks was identified, both being higher in mixed stands (López-Marcos et al. 2019). The percentage of the basal area of the dominant species in the monospecific plots was greater than 83% or 95% for P. sylvestris or P. pinaster respectively, whereas the basal area percentage of both species in the mixed plots ranged from 33 to 67%. The sampling design in triplets was well balanced for stand composition (six repetitions per stand type) but not Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 143 necessarily balanced for other stand characteristics (i.e. density, total basal area, dominant height, mean quadratic diameter, age) that were intended to be similar within the triplet (avoiding biases in the sampling design) but differed between triplets. However, a previous study showed how the percentage of the basal area of both Pinus species was the only characteristic of the stand that significantly influenced the understory composition and tree regeneration (LópezMarcos et al. 2020a). Other characteristics of the stand structure such as density, total basal area, dominant height, mean quadratic diameter or age did not have a significant influence on the understory because the tree species composition was the main varying factor (López-Marcos et al. 2020a). Figure 38. Location of the triplets in the ‘Sierra de la Demanda’ in North-Central Spain, the plots within each triplet (red circles: Pinus sylvestris monospecific plots, PS; yellow circles: Pinus pinaster monospecific plots, PP; blue circles: mixed plots of both Pinus species, MM), the understory inventories (small black squares), the overstory inventories at a smaller scale (black circumferences) and trees (P. sylvestris: small red triangles; P. pinaster: small yellow triangles) within each plot. Traditionally, forest management consists of strip clear-cutting with soil movement and planting or sowing when necessary, and moderate thinning from below (Riofrío et al. 2019) benefiting P. sylvestris (López-Marcos et al. 2019c). The stands have had no silvicultural intervention or damage in the last ten years in an attempt to minimize the effect of the thinning or another type of intervention in what is intended to study, either growth, floristic richness or soil nutrients. Triplets belong to the network of permanent plots of the Sustainable Forest Daphne López-Marcos PhD. Thesis 144 Management Research Institute UVa-INIA (iuFOR) and they have been previously used in a series of recent studies (Riofrío et al. 2017a, b, 2019; Cattaneo 2018; López-Marcos et al. 2018, 2019, 2020a). Understory sampling Within each plot, 10 inventories (1m×1m) were randomly located and the cover (%) of every understory vascular plant species, including tree regeneration, was estimated visually by the same observer in June 2016 (López-Marcos et al. 2019) to encompass and better identify the maximum number of vascular plant species (Alday et al. 2010). Vascular plant species were classified according to the Raunkiær’s life-forms (1934) following Aizpiru et al. (2007); see López-Marcos et al. (2019). Therophytes are annuals plants whose shoot and root systems die after seed production and which complete their whole life cycle within one year; hemicryptophytes are perennial herbaceous plants with periodic shoot reduction to a remnant shoot system that lies relatively flat on the ground surface; geophytes have subterranean resting buds (i.e. bulbs, rhizomes…); chamaephytes (dwarf shrubs) are woody plants whose natural branch or shoot system remains perennially between 25-50 cm above ground surface; and phanerophytes (tree regeneration and shrubs) are woody plants that grow taller than 25-50 cm. Tree regeneration included the main tree species found in seedling/sapling stages (i.e. P. sylvestris, P. pinaster, Q. pyrenaica, and Q. faginea Lam.). In these stands, there are no subordinate tree species. Only two layers of vegetation can be distinguished (overstory and understory): the overstory measuring c.a. 20 m in height, and the understory being only c.a. 20 cm in height, and never higher than 1 m (López-Marcos et al. 2019c). Soil sampling and laboratory analyses At the same time as the vegetation sampling, one soil pit of at least 50 cm depth was dug in each plot for soil profile characterization (López-Marcos et al. 2018). Two undisturbed soil samples were collected from each pit’s soil horizon with steel cylinders (98.2 cm3) to keep their original structure. Likewise, one disturbed sample was also taken from each pit’s soil horizon (ca. 2.5 kg). Both undisturbed and disturbed soil samples were dried at 105°C for 24 h before analyses. Undisturbed soil samples were weighed (±0.001 g) and used to calculate the soil bulk density. Disturbed soil samples were sieved (2 mm) before physical and chemical analyses. Physical analyses included percentage by weight of coarse fraction (>2 mm; %stones) and earth fraction (<2 mm; %EF). Available water was determined by the MAPA (1994) method as the difference between water content at field capacity (water remaining in a soil after it has been thoroughly Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 145 saturated for two days and allowed to drain freely) and the permanent wilting point (soil water content retained at 1500 kPa using Eijkelkamp pF Equipment). Chemical analyses included exchangeable cations (Ca+2, Mg+2, K+, Na+) that were extracted with 1N ammonium acetate at pH=7 (Schollenberger and Simon 1945) and determined using an atomic absorption/emission spectrometer. Overstory sampling The number and diameter of all stems > 7.5 cm in diameter for every Pinus species in each plot were computed at two spatial scales: 1) at the stand level, i.e. within each circular plot of 15 m radius; and 2) at a smaller scale, i.e. within each circular 4 m radius subplot centered in each quadrat of understory sampling according to Rodríguez-Calcerrada et al. (2011). In order to assess the 'randomness' of the spatial distribution pattern of trees (Byth and Ripley 1980), both without differentiating species (P. sylvestris + P. pinaster) and for each species separately (P. sylvestris or P. pinaster), two different distances were measured within each plot following Hopkins (1954): 1) the distance from a random point (the quadrat for understory sampling) to the nearest tree (piD), and 2) the distance from that tree to its nearest neighbor (iiD). Data analyses In each horizon, the water holding capacity (WHC) and the stock of the sum of bases (SBstock) were calculated as indicated in Appendix IV; the sum of bases (SB) was the sum of the Ca+2, Mg+2, K+ and Na+ concentrations (cmol+ kg−1). WHC and SBstock in the soil profile (0-50 cm) were then calculated as the sum of the values of each horizon (see Appendix IV). Richness was calculated as total cumulative number of plant species in the 10 quadrats per plot (Colwell 2009), including understory vegetation and tree regeneration (see López-Marcos et al. 2019). The cover (%) of each Raunkiær’s life-form in each plot was calculated as the average of the 10 vegetation sampling quadrats per plot (see López-Marcos et al. 2019). Tree density (N), total basal area (GT), and the basal area of each Pinus species (GPS: P. sylvestris basal area; GPP: P. pinaster basal area) were calculated at both spatial scales; GT, GPS and GPP as indicated in Appendix IV. At the smaller scale, the average of the ten circular 4 m radius subplots was made within each plot. The percentage of P. pinaster basal area was calculated as the ratio between the basal area of P. pinaster and the total basal area of each plot. Differences among stands in GT and N, at two spatial scales, were analysed using linear mixed models (LMM; Pinheiro and Bates 2000) with the restricted maximum likelihood method (REML; Richards 2005). The Hopkins' coefficient of aggregation (1954) was calculated for Daphne López-Marcos PhD. Thesis 146 determining the spatial distribution pattern of trees in each stand type. This test is based on the assumption that a population is randomly distributed whether the distance from a random point (the center of the quadrat for understory sampling) to the nearest tree (piD) is identical to the distance from that tree to its nearest neighbor (iiD). A t-Student test was used to check this assumption (p<0.05). Also differences among stands in piD and iiD were analysed using LMM with REML, both without differentiating species (P. sylvestris + P. pinaster) and for each species separately (P. sylvestris or P. pinaster). Structural Equation Models (SEMs) were used to explore to what extent the water (WHC) and fertility (SBstock) in the soil were related to the overyilding in GT (through its components i.e., GPS and GPP) and the understory richness mediated by hemicryptophytes. The SEM approach is based on a general linear model and enables the simultaneous assessment of multiple relationships (direct and indirect) between variables (Grace 2006). These relationships between variables can be represented in a “path” diagram where the variables are connected by arrows representing the theoretical structural model for the system under consideration (Rosseel 2012). SEMs model simplification method was based on Akaike Information Criterion (AIC) deleting all the non-significant model’s path coefficients (Alday et al. 2016). The goodness of fit of each model was evaluated with the chi-square statistic, the root mean square error of approximation (RMSEA), and the goodness-of-fit index (GFI). Chi-square values higher than 0.05, RMSEA below 0.08, and a GFI above 0.90 indicate an acceptable fit for the model (Grace 2006; Alday et al. 2016). For clarity, only the standardized path coefficients are reported in the figure. Finally, the response pattern of both Pinus species along the significant soil properties (i.e. WHC and SBstock), as well as of the understory richness (S) along the percentage of P. pinaster basal area were modeled by Huisman-Olff-Fresco (HOF) models (Huisman et al. 1993). These are a hierarchical set of five response models, ranked by their increasing complexity (Model I, monotone trend, i.e. with constant abundance; Model II, increasing or decreasing trend where the maximum is equal to the upper bound; Model III, increasing or decreasing trend where the maximum is below the upper bound; Model IV, symmetrical response curve; Model V, skewed response curve. The Akaike Information Criterion (AIC; Akaike 1973) was used to select the most appropriate response model (Johnson and Omland 2004); smaller values of AIC indicate better models. Finally, the location of species optima (μ) and niche widths (2t) for those species with unimodal responses were derived from the HOF models (Lawesson and Oksanen 2002). The 2t values were found by solving for the gradient points of the fitted HOF model relative to a strict Gaussian model at 2t (Lawesson and Oksanen 2002). In the case of a symmetric unimodal Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 147 response, the lower and upper t values are identical, while with a skewed model, the 2t intervals are not necessarily equal. All statistical analyses were implemented in the R software environment (version 3.3.3; R Development Core Team 2016) using the nlme package for Linear Mixed Models (LMM, version 3.1-137; Pinheiro et al. 2018), the eHOF package for HOF modeling (version 3.2.2; Jansen and Oksanen 2013) and the lavaan package for Structural Equation Models (SEMs, Rosseel 2012). Results Overstory density and basal area at two spatial scales No differences in total density among stands (PS, MM and PP) were found at neither of both spatial scales (Figure 39a,b). Nevertheless, at the stand level (Figure 39a) density seamed to increase from PS (683.99±48.91 ind. ha-1) to PP (775.93±137.12 ind. ha-1), whereas at the smaller scale (Figure 39b) density seamed to be higher in MM (868.72±128.49 ind. ha-1) with respect to the monospecific stands (PS: 566.99±96.48 ind. ha-1; PP: 727.46±107.41 ind. ha-1). In contrast, significant differences in the total basal area were found among stands at both spatial scales (Figure 39c,d). At the stand level (Figure 39c), the total basal area increased from PS (48.04±3.19 m2 ha-1) to PP (62.19±5.19 m2 ha-1), being intermediate in MM (55.24±4.94 m2 ha1). At a smaller spatial scale (Figure 39d), the total basal area increased from PS (39.15±4.93 m2 ha-1) to MM (66.21±8.00 m2 ha-1) and no differences between MM and PP (63.31±6.79 m2 ha-1) were found. Tree spatial distribution pattern The spatial distribution of trees regardless of species was random in the three stand types (Table 27). However, the spatial distribution of P. sylvestris and P. pinaster considered separately changed from random in monospecific stands to regular in mixed stands (Table 27). Without differentiating Pinus species, the distance from a random point to the nearest tree (piD) and the distance from that tree to the nearest neighbor (iiD) were lower in mixed stands than in monospecific stands, although, only the first was significantly different (Figure 40a,c). However, for each species separately (P. sylvestris or P. pinaster), piD was lower in mixed stands than in monospecific stands but iiD was higher in MM than in monospecific stands (Figure 40b,d). Daphne López-Marcos PhD. Thesis 148 Figure 39. (a) Density (ind. ha1; mean+SE), and (c) basal area (m2 ha-1; mean+SE) at stand level (i.e. within the circular plots of 15 m radius); and (b) density, and (d) basal area at a smaller scale (i.e. within the circular subplots of 4 m radius). PS: P. sylvestris monospecific stands (n=6), MM: mixed stands (n=6), and PP: P. pinaster monospecific stands (n=6). Diferent letters indicate differences among stand types (p<0.05) in total density and basal area. Table 27. Spatial distribution of trees regardeless of species (all tress: P. sylvestris + P. pinaster), and for each Pinus species separately, in each type of stand, calculed by Hopkins' coefficient of aggregation (1954) with p< 0.05; piD: distance from a random point (the center of the quadrat for understory sampling) to the nearest tree, and iiD: distance from that tree to its nearest neighbor. P. sylvestris monospecific stand Mixed stand P. pinaster monospecific stand All trees Random (piD = iiD) Random (piD = iiD) Random (piD= iiD) Pinus sylvestris Random (piD = iiD) Regular (piD < iiD) - Pinus pinaster - Regular (piD < iiD) Random (piD = iiD) Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 149 Figure 40. Comparing stands for each distance (piD: the distance from a random point to the nearest tree; iiD: the distance from that tree to its nearest neighbor), both without differentiating species (P. sylvestris + P. pinaster) and for each species separately (P. sylvestris or P. pinaster). Understory richness Thirty understory species from twenty-one families were recorded, with chamaephytes (mostly Ericaceae) being the most abundant (25% of absolute cover), following by phanerophytes (8%) and hemicryptophytes (7%). The understory richness showed an increasing trend bounded below the maximum attainable response as the percentage of basal area of P. sylvestris increased (HOF model III; Figure 41). Daphne López-Marcos PhD. Thesis 150 Figure 41. HOF-derived response curve of understory richness relative to the percentage (%) of basal area (G) of P. sylvestris. Understory richness maintenance and overyielding at small scale as a result of overstory-soilunderstory interactions The structural equation model (SEM) showed a reasonably good fit as GFI value was greater than 0.90 and RMSEA was near to 0.08 (Figure 42). The SEM clearly showed that soil fertility (SBstock) affected positively the basal area of P. sylvestris (GPS) and the cover of hemicryptophytes, whereas soil moisture (WHC) affected negatively the basal area of P. pinaster (GPP) and the cover of hemicryptophytes. There is also a negative relation between the basal area of both Pinus species. Finally, the standardized path coefficients indicated that soil moisture (WHC) and hemicryptophytes affected positively the understory richness (S). The overall goodness of the model fit increased when including hemicryptophytes. Figure 42. Conceptual model of the effects of soil moisture (WHC: water holding capacity) and fertility (SBstock: stock of sum of bases) on the basal area of the overstory species (GPS: basal area of P. sylvestris, GPP: basal area of P. pinaster) and the understory species richness (S) through the hemicryptophytes cover (Hemi). Continuous and dashed lines represent the signification level (p<0.1 or p>0.1, respectively). Red and green arrows represent negative and positive associations between variables, respectively. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 151 Niche complementarity of Pinus species: soil water and fertility Both Pinus species responded to soil moisture (WHC) and fertility (SBstock) with opposite trends (Figure 43a,b). P. sylvestris showed both asymmetrical response curves (HOF-model V) with the maximum skewed at the highest WHC and SBstock values. Conversely, P. pinaster showed both asymmetrical response curves (HOF-models V) with the maximum skewed at the lowest WHC and SBstock values. Figure 43. HOF-derived response curves of overstory species (Pisy: Pinus sylvestris and Pipi: Pinus pinaster) relative to (a) soil moisture (WHC: water holding capacity) and (b) fertility (SBstock: stock of sum of bases) gradients; and location of the optimum (µ) and niche withd (2t) for both Pinus species relative to (c) soil moisture (WHC) and (d) fertility (SBstock) gradients. In fact, the location of the optimum of overstory species along WHC and SBstock gradients (Figure 43c,d and Table 28) showed how P. pinaster had the greatest probability of occurrence (h > 50 and h>90 for WHC and SBstock respectively) in soils with low WHC (µ< 2 gwater cm-2) and Daphne López-Marcos PhD. Thesis 254 Table 56. Pit description of plot PP03 (monospecific stand of Pinus pinaster Ait. in triplet 03). Site, overstory and understory description, and pictures of the plot and the pit soil profile. * Plot PP03 Triplet 03 Monospecific stand of Pinus pinaster Aiton. Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 11/06/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Navaleno Place Fuente del Pardo Coordinates (UTM) X 30T 498471 Y 4636470 Altitude 1277 m Stepness 0.19% Orientation 200° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic humixerept Vegetation Potential Luzulo forsteri-Querceto pyrenaicae S. Current Pinus pinaster Ait. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp PP03 538 0 538 68.6 0 68.6 40.3 0 40.3 21.8 0 21.8 0 105 0 20 Understory vegetation Cover (%) More abundant understory vegetation Litter 86 Erica arborea, Erica australis, Pinus pinaster (seedlings/saplings), and Cistus laurifolius Vascular plants 15 Bryophytes 0 Pictures Plot Pit soil profile Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 255 Table 57. Pit description of plot PP03 (monospecific stand of Pinus pinaster Ait. in triplet 03): Climatic data, profile description including organic (leaf litter) and mineral horizons (Horizons). ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 79 64 60 84 86 53 31 30 44 97 89 90 801 Temperature (ºC) 1.7 2.5 5.1 7.6 11.5 14.8 17.7 17.4 13.9 9.4 5.0 2.6 9.1 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 20.00 3.00 34.00 19.00 47.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-17 10YR3/1 10YR5/2 Water status: moist. Mottle: non-existent. Rock Fragments: many, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: many fine roots and few coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 17-57+ 10YR4/6 10YR6/6 Water status: moist. Mottle: non-existent. Rock Fragments: many, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and few coarse roots. No soil crusts. Daphne López-Marcos PhD. Thesis 256 Table 58. Pit description of plot PP03 (monospecific stand of Pinus pinaster Ait. In triplet 03): analytic data of the mineral horizons. *** Analytic data Horizons Texture (%) Stones (%) Density (g cm-3) Porosity (%) Sand Silt Clay Bulk Real Ah 65.53 17.82 7.79 59.50 1.66 2.73 39.21 C 68.48 15.04 10.26 58.56 1.48 2.58 42.86 Horizons pH (H2O) EC (dS m-1) Pav (mg kg-1) TN (mg g-1) C properties (mg g-1) TOC oxC Cmic Cmin Ah 5.04 118.5 7.3 1.46 45.53 32.94 0.09 0.95 C 4.80 130.0 7.7 0.20 5.53 6.19 - - Horizons Exchangeable cations (cmol+ kg-1) CEC Na+ K+ Ca++ Mg++ SB Ah 19.93 0.85 0.17 3.41 0.83 5.26 C 10.83 0.82 0.06 0.95 0.35 2.18 Horizons Water properties FC (%) PWP (%) AW (%) WHC (g cm-2) Ah 39.38 29.02 10.36 1.19 C 11.43 2.61 8.82 1.78 Figure 65. Map of stems position in plot PP03 (monospecific stand of Pinus pinaster Ait. in triplet 03)****. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 257 Table 59. Pit description of plot MM03 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 03). Site, overstory and understory description, and pictures of the plot and the pit soil profile. * Plot MM03 Triplet 03 Mixed stand Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 11/06/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Navaleno Place Fuente del Pardo Coordinates (UTM) X 30T 498440 Y 4636436 Altitude 1241 m Stepness 18.70% Orientation 200° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic humixerept Vegetation Potential Luzulo forsteri-Querceto pyrenaicae S. Current Pinus sylvestris L. and Pinus pinaster Ait. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp MM03 693 495 198 63.5 33.0 30.5 34.1 29.1 44.3 25.0 22.6 24.8 100 95 23 23 Understory vegetation Cover (%) More abundant understory vegetation Litter 49 Erica australis, Deschampsia flexuosa, Hypnum spp. and Erica arborea Vascular plants 47 Bryophytes 5 Pictures Plot Pit soil profile Daphne López-Marcos PhD. Thesis 258 Table 60. Pit description of plot MM03 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 03): Climatic data, profile description including organic (leaf litter) and mineral horizons (Horizons). ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 79 64 60 84 86 53 31 30 44 97 89 90 801 Temperature (ºC) 1.7 2.5 5.1 7.6 11.5 14.8 17.7 17.4 13.9 9.4 5.0 2.6 9.1 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 18.80 2.00 31.00 34.00 35.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-17 10YR2/2 10YR4/1 Water status: moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: moderate, granular. Consistence: friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: many fine roots and few coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 17-54+ 10YR5/3 10YR6/3 Water status: moist. Mottle: non-existent. Rock Fragments: many, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: very friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and many coarse roots. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 259 Table 61. Pit description of plot MM03 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 03): analytic data of the mineral horizons. *** Analytic data Horizons Texture (%) Stones (%) Density (g cm-3) Porosity (%) Sand Silt Clay Bulk Real Ah 52.82 23.47 14.75 15.02 1.00 2.12 52.72 C 72.39 11.64 11.07 60.57 1.80 2.55 29.57 Horizons Ph (H2O) EC (dS m-1) Pav (mg kg-1) TN (mg g-1) C properties (mg g-1) TOC oxC Cmic Cmin Ah 4.42 153.0 5.1 0.33 73.67 56.12 0.08 0.70 C 4.72 130.5 1.6 0.20 6.36 4.65 - - Horizons Exchangeable cations (cmol+ kg-1) CEC Na+ K+ Ca++ Mg++ SB Ah 24.18 0.94 0.21 4.18 0.91 6.24 C 11.87 0.85 0.08 1.14 0.38 2.44 Horizons Water properties FC (%) PWP (%) AW (%) WHC (g cm-2) Ah 32.19 28.20 3.99 0.58 C 7.42 1.89 5.52 1.29 Figure 66. Map of stems position in plot MM03 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 03)**** Daphne López-Marcos PhD. Thesis 260 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 261 Triplet 4 Daphne López-Marcos PhD. Thesis 262 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 263 Table 62. Pit description of plot PS04 (monospecific stand of Pinus sylvestris L. in triplet 04). Site, overstory and understory description and pictures of the plot and the pit soil profile. * Plot PS04 Triplet 04 Monospecific stand of Pinus sylvestris L. Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 12/03/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Soria Place Pajar de la molinera Coordinates (UTM) X 30T 0504090 Y 4637606 Altitude 1169 m Stepness 14.00% Orientation 255° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic dystroxerept Vegetation Potential Festuco heterophyllae-Querceto pyrenaicae S. Current Pinus sylvestris L. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp PS04 634 580 57 48.9 40.7 8.2 31.3 29.9 43.0 22.9 22.6 21.2 78 0 26 0 Understory vegetation Cover (%) More abundant understory vegetation Litter 30 Hypnum spp., Erica arborea, Quercus pyrenaica (seedlings/saplings) and Erica australis Vascular plants 50 Bryophytes 20 Pictures Plot Pit soil profile Daphne López-Marcos PhD. Thesis 270 Table 69. Pit description of plot MM04 (Mixed stand of Pinus sylvestris L. and Pinus pinaster Aiton. of triplet 04): Climatic data, profile description including organic (leaf litter) and mineral (Horizons). ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 80 65 57 85 83 53 31 29 42 90 90 90 833 Temperature (ºC) 1.8 2.6 5.1 7.9 11.8 14.7 17.5 17.2 13.8 9.4 5.0 2.6 8.8 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 18.80 1.50 31.00 34.00 35.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-20 10YR4/1 10YR6/2 Water status: slightly moist. Mottle: non-existent. Rock Fragments: many, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: moderate, granular. Consistence: friable, sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: many fine roots and few coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 20-50 10YR5/8 10YR6/6 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: very friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and many coarse roots. No soil crusts. Horizon boundary: wavy and abrupt (lithic contact). Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 271 Table 70. Pit description of plot MM04 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 04): analytic data of the mineral horizons. *** Analytic data Horizons Texture (%) Stones (%) Density (g cm-3) Porosity (%) Sand Silt Clay Bulk Real Ah 76.96 14.32 5.35 15.12 0.88 2.25 60.92 C 71.44 13.95 10.64 35.15 1.33 2.54 47.70 Horizons pH (H2O) EC (dS m-1) Pav (mg kg-1) TN (mg g-1) C properties (mg g-1) TOC oxC Cmic Cmin Ah 5.16 38.6 3.9 1.39 23.41 15.12 0.08 0.70 C 5.20 24.7 3.3 0.74 5.63 4.46 - - Horizons Exchangeable cations (cmol+ kg-1) CEC Na+ K+ Ca++ Mg++ SB Ah 18.74 0.80 0.20 1.35 0.36 2.71 C 16.31 0.76 0.06 0.86 0.30 1.98 Horizons Water properties FC (%) PWP (%) AW (%) WHC (g cm-2) Ah 12.10 7.74 4.36 0.65 C 8.91 4.75 4.16 1.07 Figure 69 Map of stems position in plot MM04 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 04)****. Daphne López-Marcos PhD. Thesis 272 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 273 Triplet 5 Daphne López-Marcos PhD. Thesis 274 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 275 Table 71. Pit description of plot PS05 (monospecific stand of Pinus sylvestris L. in triplet 05). Site, overstory and understory description, and pictures of the plot and the pit soil profile. * Plot PS05 Triplet 05 Monospecific stand of Pinus sylvestris L. Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 12/03/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Soria Place Mojon Pardo Coordinates (UTM) X 30T 0503658 Y 4631296 Altitude 1145 m Stepness 0.01% Orientation 250° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic humixerept Vegetation Potential Festuco heterophyllae-Querceto pyrenaicae S. Current Pinus sylvestris L. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp PS05 651 651 0 54.9 54.9 0 32.8 32.8 0 23 23 0 121 0 23 0 Understory vegetation Cover (%) More abundant understory vegetation Litter 60 Hypnum spp., Erica australis and Pinus sylvestris (seedlings/saplings) Vascular plants 18 Bryophytes 24 Pictures Plot Pit soil profile Daphne López-Marcos PhD. Thesis 276 Table 72. Pit description of plot PS05 (Monospecific stand of Pinus sylvestris L. of triplet 05): Climatic data, profile description including organic (leaf litter) and mineral (Horizons) horizons. ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 78 64 56 84 84 53 31 31 42 92 89 89 810 Temperature (ºC) 1.5 2.5 4.8 7.7 11.5 14. 17.1 17.1 13.5 9.1 5.1 2.4 8.7 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 21.00 1.50 51.00 29.00 19.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-15 10YR2/1 10YR4/2 Water status: very wet. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Loam. Soil Structure: moderate, granular. Consistence: friable, sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: many fine roots and few coarse roots. No soil crusts. Horizon boundary: smooth and gradual. AB 15-40 10YR5/3 10YR6/3 Water status: very wet. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Loam. Soil Structure: weak, granular. Consistence: very friable, sticky and plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and common coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 40-60+ 10YR5/8 10YR7/4 Water status: very wet. Mottle: non-existent. Rock Fragments: many, gravely, Shape-spherical. Soil Texture: sandy. Soil Structure: weak, granular. Consistence: very friable, sticky and plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and many coarse roots. No soil crusts. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 277 Table 73. Pit description of plot PS05 (monospecific stand of Pinus sylvestris L. in triplet 05): analytic data of the mineral horizons. *** Analytic data Horizons Texture (%) Stones (%) Density (g cm-3) Porosity (%) Sand Silt Clay Bulk Real Ah 55.18 21.38 13.36 2.68 0.61 1.52 59.80 AB 53.21 23.32 11.99 11.68 1.11 2.40 53.61 C 49.16 26.32 16.34 16.09 1.29 2.54 49.23 Horizons pH (H2O) EC (dS m-1) Pav (mg kg-1) TN (mg g-1) C properties (mg g-1) TOC oxC Cmic Cmin Ah 4.05 102.1 7.4 3.23 84.60 72.00 0.39 0.79 AB 4.75 35.2 3.9 0.66 13.19 10.09 - - C 5.3 20.4 3.1 0.61 4.12 2.67 - - Horizons Exchangable cations (cmol+ kg-1) CEC Na+ K+ Ca++ Mg++ SB Ah 18.46 0.82 0.33 4.44 0.82 6.41 AB 12.93 0.69 0.48 1.01 0.32 2.49 C 10.06 0.77 0.14 1.31 0.42 2.64 Horizons Water properties FC (%) PWP (%) AW (%) WHC (g cm-2) Ah 46.57 26.86 19.71 1.76 AB 23.93 4.92 19.00 4.68 C 21.24 3.74 17.50 1.89 Figure 70. Map of stems position in plot PS05 (monospecific stand of Pinus sylvestris L. in triplet 05)****. Daphne López-Marcos PhD. Thesis 278 Table 74. Pit description of plot PP05 (monospecific stand of Pinus pinaster Ait. in triplet 05). Site, overstory and understory description, and pictures of the plot and the pit soil profile. * Plot PP05 Triplet 05 Monospecific stand of Pinus pinaster Aiton. Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 12/03/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Soria Place Mojon Pardo Coordinates (UTM) X 30T 0503674 Y 4631248 Altitude 1145 m Stepness 0.01% Orientation 250° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic humixerept Vegetation Potential Festuco heterophyllae-Querceto pyrenaicae S. Current Pinus pinaster Ait. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp PP05 722 0 722 70.3 0 70.3 35.2 0 35.2 21.4 0 21.4 0 115 0 20 Understory vegetation Cover (%) More abundant understory vegetation Litter 44 Erica australis, Arctostaphillos uva-ursi and Hypnum spp. Vascular plants 54 Bryophytes 3 Pictures Plot Pit soil profile Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 279 Table 75. Pit description of plot PP05 (monospecific stand of Pinus pinaster Ait. in triplet 05): Climatic data, profile description including organic (leaf litter) and mineral horizons (Horizons). ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 78 64 56 84 84 53 31 31 42 92 89 89 810 Temperature (ºC) 1.5 2.5 4.8 7.7 11.5 14.3 17.1 17.1 13.5 9.1 5.1 2.4 8.7 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 14.50 1.50 29.00 28.00 43.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-20 10YR2/1 10YR5/1 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, coarse gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: moderate, granular. Consistence: friable, sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: many fine roots and few coarse roots. No soil crusts. Horizon boundary: smooth and gradual. AC 20-30 10YR4/2 10YR6/2 Water status: slightly moist. Mottle: non-existent. Rock Fragments: many, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: moderate, granular. Consistence: friable, sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and common coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 30-52+ 10YR2/2 10YR6/4 Water status: slightly moist. Mottle: non-existent. Rock Fragments: many, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: friable, sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and few coarse roots. No soil crusts. Daphne López-Marcos PhD. Thesis 286 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 287 Table 80. Pit description of plot PS06 (monospecific stand of Pinus sylvestris L. in triplet 06). Site, overstory and understory description, and pictures of the plot and the pit soil profile. * Plot PS06 Triplet 06 Monospecific stand of Pinus sylvestris L. Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 12/03/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Cabrejas del Pinar Place Cueva de Matarubias Coordinates (UTM) X 30T 0504876 Y 4626851 Altitude 1093 m Stepness 2.00% Orientation 306° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic dystroxerept Vegetation Potential Junipereto hemisphaerico-thuriferae S. Current Pinus sylvestris L. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp PS06 821 778 42 33.3 30.8 2.6 22.7 22.4 27.7 18.5 17.8 19.5 44 0 26 0 Understory vegetation Cover (%) More abundant understory vegetation Litter 59 Pinus sylvestris (seedlings/saplings) and Cistus laurifolius. Vascular plants 31 Bryophytes 1 Pictures Plot Pit soil profile Daphne López-Marcos PhD. Thesis 288 Table 81. Pit description of plot PS06 (monospecific stand of Pinus sylvestris L. in triplet 06): Climatic data, profile description including organic (leaf litter) and mineral horizons (Horizons). ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 75 62 53 80 82 50 30 30 41 89 84 85 786 Temperature (ºC) 1.9 2.9 5.5 8.0 11.8 15.2 18.1 17.9 14.3 9.8 5.3 2.8 9.4 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 28.30 4.00 30.00 34.00 36.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-28 10YR6/3 10YR7/2 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: friable, sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: many fine roots and few coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 28-65+ 10YR5/6 10YR4/1 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: very friable, sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and many coarse roots. No soil crusts. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 289 Table 82. Pit description of plot PS06 (monospecific stand of Pinus sylvestris L. in triplet 06): analytic data of the mineral horizons. *** Analytic data Horizons Texture (%) Stones (%) Density (g cm-3) Porosity (%) Sand Silt Clay Bulk Real Ah 80.64 8.56 8.36 13.03 1.13 2.41 53.20 C 73.57 12.20 11.16 5.53 1.39 2.46 43.63 Horizons pH (H2O) EC (dS m-1) Pav (mg kg-1) TN (mg g-1) C properties (mg g-1) TOC oxC Cmic Cmin Ah 4.45 28.5 4.2 0.66 18.03 19.03 0.05 0.82 C 4.60 15.9 3.4 0.45 6.06 5.33 - - Horizons Exchangeable cations (cmol+ kg-1) CEC Na+ K+ Ca++ Mg++ SB Ah 22.6 0.9 0.1 2.4 0.5 3.8 C 16.3 0.8 0.1 1.5 0.4 2.8 Horizons Water properties FC (%) PWP (%) AW (%) WHC (g cm-2) Ah 15.01 6.45 8.56 2.35 C 9.16 3.06 6.11 1.76 Figure 73. Map of stems position of plot PS06 (monospecific stand of Pinus sylvestris L. in triplet 06)****. Daphne López-Marcos PhD. Thesis 290 Table 83. Pit description of plot PP06 (monospecific stand of Pinus pinaster Ait. in triplet 06). Site, overstory and understory description, and pictures of the plot and the pit soil profile. * Plot PP06 Triplet 06 Monospecific stand of Pinus pinaster Aiton. Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 12/03/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Cabrejas del Pinar Place Cueva de Matarubias Coordinates (UTM) X 30T 505260 Y 4627130 Altitude 1116 m Stepness 12.00% Orientation 222° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic dystroxerept Vegetation Potential Junipereto hemisphaerico-thuriferae S. Current Pinus pinaster Ait. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp PP06 594 0 594 37.5 0 37.5 28.4 0 28.4 16.9 0 16.9 0 49 0 23 Understory vegetation Cover (%) More abundant understory vegetation Litter 56 Calluna vulgaris, Pinus pinaster (seedlings/saplings), Arctostaphillos uva-ursi and Erica australis Vascular plants 42 Bryophytes 2 Pictures Plot Pit soil pofile Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 291 Table 84. Pit description of plot PP06 (monospecific stand of Pinus pinaster Ait. in triplet 06): Climatic data, profile description including organic (leaf litter) and mineral horizons (Horizons). ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 75 62 53 80 82 50 30 30 41 89 84 85 786 Temperature (ºC) 1.9 2.9 5.5 8.0 11.8 15.2 18.1 17.9 14.3 9.8 5.3 2.8 9.4 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 6.20 2.00 49.00 25.00 26.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-12 10YR4/1 10YR6/2 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and many coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 12-50+ 10YR6/4 10YR7/3 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: very friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and many coarse roots. No soil crusts. Daphne López-Marcos PhD. Thesis 292 Table 85. Pit description of plot PP06 (monospecific stand of Pinus pinaster Ait. in triplet 06): analytic data of the mineral horizons. *** Analytic data Horizons Texture (%) Stones (%) Density (g cm-3) Porosity (%) Sand Silt Clay Bulk Real Ah 85.29 8.91 4.98 6.44 1.21 2.63 53.89 C 84.45 8.28 6.13 9.07 1.41 2.65 46.78 Horizons pH EC (dS m-1) Pav (mg kg-1) TN (mg g-1) C properties (mg g-1) TOC oxC Cmic Cmin Ah 4.90 129.0 4.1 0.33 11.10 4.38 0.05 0.83 C 5.16 111.0 1.6 0.25 3.21 3.52 - - Horizons Exchangeable cations (cmol+ kg-1) CEC Na+ K+ Ca++ Mg++ SB Ah 13.4 0.9 0.1 1.8 0.5 3.2 C 16.0 0.8 0.1 1.1 0.4 2.4 Horizons Water properties FC (%) PWP (%) AW (%) WHC (g cm-2) Ah 24.71 1.18 23.53 3.20 C 18.69 1.03 17.66 8.60 Figure 74. Map of stems position in plot PP06 (monospecific stand of Pinus pinaster Ait. in triplet 06)****. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 293 Table 86. Pit description of plot MM06 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 06). Site, overstory and understory description, and pictures of the plot and the pit soil profile. * Plot MM06 Triplet 06 Mixed stand Site description Author Daphne López Marcos y Luis Alfonso Ramos Calvo Date 12/03/2016 Weather Sunny / Rain in the last 24 hours Soil climate Moisture regime Xeric Temperature regime Mesic Location Province Soria Town Cabrejas del Pinar Place Cueva de Matarubias Coordinates (UTM) X 30T 505084 Y 4627042 Altitude 1119 m Stepness 11.00% Orientation 184° Soil Parent material Sandstones and Marls Geologic age Mesozoic Soil type Typic dystroxerept (Soil Taxonomy, 2015) Vegetation Potential Junipereto hemisphaerico-thuriferae S Current Pinus sylvestris L. and Pinus pinaster Ait. Overstory description N (trees ha-1) G (m2 ha-1) DHB (cm) Ho (m) Age (years) SI plot Ps Pp plot Ps Pp plot Ps Pp plot Ps Pp Ps Pp Ps Pp MM06 679 396 283 33.3 13 20.2 25 20.5 30.2 16.1 15 16.1 44 49 23 23 Understory vegetation Cover (%) More abundant understory vegetation Litter 34 Arctostaphillos uva-ursi, Erica australis and Calluna vulgaris Vascular plants 59 Bryophytes 2 Pictures Plot Pit soil profile Daphne López-Marcos PhD. Thesis 294 Table 87. Pit description of plot MM06 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 06): Climatic data, profile description including organic (leaf litter) and mineral horizons (Horizons). ** Climatic description Month J F M A My Jn Jl Ag S O N D X Rainfall (mm) 75 62 53 80 82 50 30 30 41 89 84 85 786 Temperature (ºC) 1.9 2.9 5.5 8.0 11.8 15.2 18.1 17.9 14.3 9.8 5.3 2.8 9.4 Leaf litter description Biomass (Mg ha-1) Thickness (cm) Composition (%) Fresh Fragmented Humified 17.60 2.00 50.00 19.00 31.00 Horizon description Horizon Thickness (cm) Colour Description Wet Dry Ah 0-30 10YR3/1 10YR6/1 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: common fine roots and few coarse roots. No soil crusts. Horizon boundary: smooth and gradual. C 30-70+ 10YR5/6 10YR8/3 Water status: slightly moist. Mottle: non-existent. Rock Fragments: few, gravely, Shape-spherical. Soil Texture: Sand. Soil Structure: weak, granular. Consistence: very friable, slightly sticky and slightly plastic. Pores: common, fine and interstitial. No anthropic activity apparent. Roots: few fine roots and common coarse roots. No soil crusts. Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 295 Table 88. Pit description of plot MM06 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 06): analytic data of the mineral horizons. *** Analytic data Horizons Texture (%) Stones (%) Density (g cm-3) Porosity (%) Sand Silt Clay Bulk Real Ah 71.72 14.15 9.30 47.93 1.10 2.23 50.50 C 78.05 14.14 5.25 11.88 1.49 2.63 43.19 Horizons pH (H2O) EC (dS m-1) Pav (mg kg-1) TN (mg g-1) C properties (mg g-1) TOC oxC Cmic Cmin Ah 4.6 145.5 7.5 55.46 42.7 42.7 0.06 0.91 C 5.0 119.0 0.5 4.39 2.6 3.4 - - Horizons Exchangeable cations (cmol+ kg-1) CEC Na+ K+ Ca++ Mg++ SB Ah 17.4 0.9 0.2 3.9 0.8 5.8 C 10.5 0.9 0.1 1.1 0.4 2.5 Horizons Water properties FC (%) PWP (%) AW (%) WHC (g cm-2) Ah 41.92 5.20 36.72 6.33 C 14.06 0.95 13.11 5.17 Figure 75. Map of stems position in plot MM06 (mixed stand of Pinus sylvestris L. and Pinus pinaster Ait. in triplet 06)****. Daphne López-Marcos PhD. Thesis 302 oxCstock Easily oxidizable carbon stockin the whole mineral soil profile (0-50cm depth); Mg ha-1 avP Available phosphorus according to Olsen and Sommers (1982); ppm Pavstock Available phosphorus stock in the whole mineral soil profile (0-50 cm depth); Mg ha-1 PavstockHi Available phosphorus stock of each horizon (Mg ha-1) pH (H2O) pH according to MAPA (1994) PWP Permanenten wilting point (soil water content retained at 1500 kPa using Eijkelkamp pF Equipment); % SB Sum of bases (sum of the Ca+2, Mg+2, K+ and Na+ concentrations); cmolc kg−1 SB0-10cm Sum of bases in the topsoil (0-10 cm depth); cmolc kg−1 SB10-20cm Sum of bases in the 10-20 cm mineral soil layer (cmolc kg−1) SB20-30cm Sum of bases in the 20-30 cm mineral soil layer (cmolc kg−1) SB30-40cm Sum of bases in the 30-40 cm mineral soil layer (cmolc kg−1) SOC Soil organic carbon Stones Coarse soil material (>2mm); % Thi Thickness of each horizon (cm) TN Total nitrogen analyzed by dry combustion using a LECO CHN-2000 elemental analyzer( mg g-1) TOC Total organic carbon by dry combustion using a LECO CHN-2000 elemental analyzer (mg g-1) TOC0-10cm Total organic carbon in the topsoil (0-10 cm depth); mg g-1 TOC10-20cm Total organic carbon in the 10-20 cm mineral soil layer (mg g-1) TOC20-30cm Total organic carbon in the 20-30 cm mineral soil layer (mg g-1) TOC30-0cm Total organic carbon in the 30-40 cm mineral soil layer (mg g-1) WHC Water holding capacity in the whole mineral soil profile (0-50 cm); g water cm-2 WHCHi Water holding capacity of each horizon (g water cm-2) Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 303 Data analysis AIC Akaike Information Criterion (Akaike 1973) DCA Detrended Correspondence Analysis (Oksanen 2016) HOF models Huisman–Olff–Fresco models (Huisman et al. 1993) LMM Linear Mixed Models (Pinheiro and Bates 2000) RDA Redundancy analysis (Oksanen 2016) REML Restricted Maximum Likelihood method (Richards 2005) SEMs Structural Equation Models (Rosseel 2012) Others IGME Instituto Geológico y Minero de España Cfb Temperate without dry season and warm summer climate Csb Temperate with dry summer climate iuFOR Sustainable Forest Research Management Institute m a.s.l Metres abovethe sea level UVa University of Valladolid Daphne López-Marcos PhD. Thesis 304 Ecosystem services of mixed stands of Scots pine and Maritime pine: biodiversity conservation and carbon sequestration 305 “mais je fais ma part”