Contrasting immediate impact of prescribed fires and experimental summer fires on soil organic matter quality and microbial properties in the forest floor and mineral soil in Mediterranean black pine forest

Science of the Total Environment 907 (2024) 167669 Available online 15 October 2023 0048-9697/© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). Contrasting immediate impact of prescribed fires and experimental summer fires on soil organic matter quality and microbial properties in the forest floor and mineral soil in Mediterranean black pine forest M. Teresa Fontúrbel a , Enrique Jim´ enez a , Agustín Merino b , * , Jos´ e A. Vega a a Centro de Investigaci´ on Forestal de Louriz´ an, Xunta de Galicia, PO Box 127, 36080 Pontevedra, Spain b University of Santiago de Compostela, Escuela Polit´ ecnica Superior, Soil Science and Agricultural Chemistry, Lugo, Spain HIGHLIGHTS GRAPHICAL ABSTRACT •Prescribed fire did not affect analysed properties in forest floor and mineral topsoil. •Summer fire greatly increased OM recalcitrance and reduced microbial properties in forest floor. •Summer fire reduced microbial biomass and enzyme activities in the mineral topsoil. •Microbial and OM quality parameters, indicators of summer fire impact on forest floor. •Useful information regarding burning prescriptions in these ecosystems was obtained. ARTICLE INFO Editor: Paulo Pereira Keywords: Prescribed fire Experimental fire Organic matter quality Microbial properties Black pine stands ABSTRACT Prescribed fire (PB) is used to achieve ecological objectives and to reduce fuel hazard thus limiting detrimental impacts of wildfire and appropriate selection of prescription window is critical for these goals. Operational use of PB in the Mediterranean forest is scarce and information about its effects on soil remains incomplete. This study for the first time i) compared the immediate impact of spring and autumn PB and experimental summer fire on key properties of forest floor and mineral topsoil in Mediterranean black pine forest, and ii) assessed the capacity of PB to reduce fuel, with limited immediate impacts on soil. PB significantly reduced the 32.5 % of pre-fire forest floor depth, while summer fire consumed 88.5 % and exposed about 30 % of the mineral soil surface. Mean maximum temperature during fire at the mineral soil surface was 23 ◦C in PB, in contrast to 128 ◦C in summer fire, while soil heating at 2 cm depth was negligible in both cases. PB did not cause immediate changes in OM quality parameters, and chemical (C and N concentrations, C/N and pH) and microbiological properties (Cmic, Cmic/C, and β-glucosidase, acid phosphatase and alkaline phosphatase activities) in forest floor or mineral topsoil (0–2 cm). By contrast, summer fire greatly increased OM recalcitrance and reduced Cmic, Cmic/C and enzyme activities in forest floor immediately after fire. In the mineral topsoil, only microbial properties were significantly reduced. The maximum temperature reached during fire in forest floor and topsoil was associated with most of the overall changes in properties in both layers. The findings suggest that prescribed fire can * Corresponding author. E-mail address: [email protected] (A. Merino). Contents lists available at ScienceDirect Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv https://doi.org/10.1016/j.scitotenv.2023.167669 Received 17 August 2023; Received in revised form 2 October 2023; Accepted 6 October 2023 Science of the Total Environment 907 (2024) 167669 2 significantly reduce fuel with limited initial impacts on soil. Although these findings are encouraging for operational use of prescribed burning in the ecosystem under study, long-term monitoring of repeated application of the technique on soil properties and other ecosystem components is necessary. 1. Introduction Wildfire is a recurrent ecological disturbance that affects many forest ecosystems worldwide and has the potential to cause substantial impacts on key processes and ecosystem services (Pausas and Keeley, 2019; Roces-Díaz et al., 2022). Southern European forests and shrublands are strongly affected by this phenomenon, reflecting a long history of occurrence and extension of both wildfires and human use of fire (Fernandes, 2018; San-Miguel-Ayanz et al., 2018). The projections made in climate change studies indicate that wildfire in the area will intensify in the coming years, due to increased numbers of drought events (Dupuy et al., 2020), among other factors. Prescribed fire is an important tool in forest management and may be effective for reducing fuel loads, thus decreasing the intensity of any wildfire that may affect the treated area, and minimizing its negative impacts while contributing to maintaining ecosystem resilience and sustainable forest management (Fernandes and Botelho, 2003; Ryan et al., 2013; Fernandes, 2015; Hiers et al., 2020). Despite its recognised performance, prescribed burning application is controversial (Harper et al., 2018; Pereira et al., 2021) and it is scarcely used at operational level in Mediterranean forests (Fernandes et al., 2013; Fernandes, 2018). The scientific information of prescribed burning on soil properties in Mediterranean forest is limited (Alca˜ niz et al., 2018) and particularly for black pine, although a number of recent studies have assessed the prescribed fire impact on selected soil properties (Kara and Bolat, 2009; Plaza-´ Alvarez et al., 2017, 2018, 2019). A number of studies have concluded that prescribed fire usually has less impact on soil than wildfire (Johnson and Curtis, 2001; Nave et al., 2011; Wang et al., 2012; Pereira et al., 2021; Agbeshie et al., 2022). Nonetheless, the available data indicate a high level of variability in the response to prescribed fire, in some cases with no differences relative to wildfire (Shakesby et al., 2015; James et al., 2018; Pressler et al., 2019; Roces-Díaz et al., 2022). This may be partly because the term “prescribed fire” is used to denote different types of fire, ranging from low severity fires used in fuel reduction burning under forest canopy to fires used to burn heavy logging slash and that can have severe impacts on soil. It follows from the above that there is an urgent need to quantify prescribed fire characteristics and determine the appropriate conditions of use that reconcile the objectives of fuel hazard reduction with tolerable impacts on soil. On the other hand, quantitatively comparing the impacts of prescribed fires and wildfires on soil is challenging. Although the fire characteristics, fuel moisture and temperatures generated during fire can be measured in prescribed fire, this is not the case in wildfire. In the latter, post-fire surrogate indicators of temperatures or fire severity must be used (e.g. Lutes et al., 2006; Keeley, 2009; Parsons et al., 2010; Vega et al., 2013). Moreover, the pre-fire values of the variables analysed are not precisely known, given the unpredictability of wildfire (Forbes et al., 2006), and are substituted by data from unburned surroundings considered control areas. This type of data may not be fully representative of pre-fire conditions, thus potentially introducing a high degree of uncertainty in the fire impact assessment (Thompson et al., 2007; Bormann et al., 2008; Urbanski, 2014). In fact, the pre-fire values of the soil variables analysed were only able to be measured in some wildfire studies (Murphy et al., 2006; Homann et al., 2011; Miesel et al., 2018; Zhang et al., 2023). Experimental forest fires provide an opportunity to reliably know the pre-fire soil properties and to record the thermal regime during the fire (Stoof et al., 2012; Santín et al., 2016). The immediate effects of prescribed fire and wildfire on the forest floor and mineral topsoil are primarily caused by the heat released from the combustion of the forest floor material and less frequently by the combustion of organic matter in the mineral soil. The magnitude of the fire impact (soil burn severity) depends on the soil properties and on fire temperature and duration (Neary et al., 1999; Certini, 2005; Keeley, 2009). Understanding how the fire affects soil organic matter (SOM) is essential, not only for its crucial role in the global C cycle and climate impacts, but also because shifts in SOM critically affect most of soil properties and forest ecosystem services. Changes in mineral soil organic matter induced by fire are complex and involve alterations in its quantity and quality (Gonz´ alez-P´ erez et al., 2004; Santín et al., 2015a, 2015b; Jim´ enez-Morillo et al., 2018). Likewise, in the forest floor layer, changes in C concentration have been observed (Nave et al., 2011; Santín et al., 2016; Matosziuk et al., 2020) while fire-caused substantial reductions in the C stock have been frequently measured (Boerner et al., 2008; Nave et al., 2011; Krishnaraj et al., 2016; Santín et al., 2016; Volkova et al., 2021). Fire-induced changes in SOM quality may have a particular influence on soil biological properties (Gonz´ alez-P´ erez et al., 2004; Knicker, 2007) and have been associated with long lasting alterations in soil microbial biomass (Aaltonen et al., 2019), bacterial community structure (Ling et al., 2021) and the catabolic capacity and mineralising activity of soil microbiota (Gu´ enon et al., 2011, 2013). While the aforementioned studies refer to wildfire, equivalent information for prescribed fire is extremely scarce, and the relationships between changes in SOM quality and soil microbial parameters response remain largely unexplored. Early studies analysing the effects of prescribed burning have shown that changes in forest floor OM quality are strong predictors of microbial biomass and activity (Fritze et al., 1994; Pietik¨ ainen and Fritze, 1995), but more recent research is lacking. Furthermore, these prescribed fires conducted in boreal forests were actually logging slash burns, which generally have very severe effects on the soil. Extrapolation of the results of such studies to prescribed fire used to reduce fuel under tree canopies and to other ecosystems may not be valid. Both soil microbial biomass C (Cmic) and enzyme activities often undergo changes immediately after wildfire and prescribed fire. These changes have been found to increase gradually with soil burn severity, varying from scarce alterations in low severity fires to dramatic decreases in the properties in severe fires (Vega et al., 2013; Fern´ andez- García et al., 2019). Thus, the differences in burn severity could explain the apparent inconsistencies in the effects reported immediately after (or very shortly after) wildfire or experimental fire. For example, some studies have reported increased Cmic (i.e. Goberna et al., 2012; Rodríguez et al., 2018), decreased Cmic (i.e. Prieto-Fern´ andez et al., 1998; B´ arcenas-Moreno et al., 2011; Díaz-Ravi˜ na et al., 2012) or no change in Cmic (Borgogni et al., 2019), but in most cases soil burn severity was not assessed or different methods were used, making comparisons difficult. Discrepancies in the immediate effects of prescribed burning have also been observed in several studies in regard to soil Cmic (i.e. Armas- Herrera et al. (2016), Catalanotti et al., 2018; Plaza-´ Alvarez et al., 2021), β-glucosidase activity (Barreiro et al., 2010; Múgica et al., 2018; Rai et al., 2023) and phosphatase activity (Sa´ a et al., 1993; Fontúrbel et al., 2012; Plaza-´ Alvarez et al., 2021). Regarding the forest floor, very few studies have assessed the impact of prescribed or experimental fire on microbial parameters. Although the effects are generally more pronounced than in the mineral topsoil, they are also very variable (Cheng et al., 2023). Negative or neutral effects in the organic layer Cmic have been observed shortly after prescribed burning (Choromanska and DeLuca, 2001; Fontúrbel et al., 2016; Catalanotti et al., 2018; Giuditta et al., 2020) and decreases following logging slash burn (Pietik¨ ainen and Fritze, 1993). Decreases in β-glucosidase and phosphatase activities in the organic layer have also been reported shortly after prescribed burning (Fontúrbel et al., 2016) and immediately after wildfire M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 3 (Borgogni et al., 2019). These changes in the organic layer are important, given the critical role it plays in C storage, nutrient dynamics, water retention and protection against erosion (Currie, 1999; Schaap et al., 1997; Ponge, 2003; Nave et al., 2011). Overall, the abovementioned inconsistencies reflect the knowledge gap regarding the immediate impact of prescribed burning and the need for further research. Meta-analysis approaches have substantially increased the insights into the fire effects on soil and the ability to discriminate the effects of prescribed fire and wildfire on some of the above-mentioned properties (Johnson and Curtis, 2001; Nave et al., 2011; Dooley and Treseder, 2012; Wang et al., 2012; Li et al., 2021; Zhou et al., 2022; Cheng et al., 2023; Pei et al., 2023). However, they have also limitations. Data usually come from a mix of ecosystems, climates, fire severities, fire frequencies and time after fire, making questionable the applicability of their results to a specific area of interest. Moreover, the paucity of data of forest floor and immediate fire impact is remarkable. A few studies have compared the effects of prescribed fire under tree canopy and wildfire in the same ecological scenario (Choromanska and DeLuca, 2001; Bormann et al., 2008; Homann et al., 2011; Miesel et al., 2018). However, data on thermal regime during wildfire could not be obtained in these studies. Consequently, conducting experimental fire that simulates wildfire is essential to improve our understanding of the variables driving the environmental impacts of fire. According to the above, the objectives of this study were as follows: i) to quantify the differences in the immediate impact caused by spring and autumn prescribed fires and also experimental summer fires on key properties of both forest floor and mineral topsoil in a Mediterranean black pine forest ecosystem, and ii) to assess the capacity of prescribed burning to achieve appreciable fuel reduction with limited immediate impacts on selected properties of the forest floor and soil in the ecosystem under study. 2. Material and methods 2.1. Study sites The study was conducted in the north of the Cuenca Mountains (Iberian Mountain range, Central-Eastern Spain) in a typical pure and a mixed Mediterranean black pine forest. These forests are considered priority habitats for conservation (European Union, 1992) and “habitats of European interest” (European Union, 1996) and they form typically uneven-aged stands, comprising a range of age classes from seedlings to pole size trees. These forest are threatened by recurrent large wildfires (Lucas-Borja et al., 2016), and it is therefore important to explore whether fuel treatments, such as prescribed burning, are useful for reducing fuel hazard. Two sites were selected for study (Fig. S1a). The first, Pozuelo (40◦33 ′ 36 ″ N / 2◦15 ′ 56 ″ W; 1000–1050 m a.s.l; slope range: 3–8 %), is a mixed stand with Pinus nigra as the dominant species (89 %) and the presence of P. pinaster (11 %). The mean tree density is 627 ±238 trees ha −1 , the mean tree height is 12.2 ±2.0 m and mean diameter at breast height (d.b.h), 19.8 ±2.6 cm. The understorey vegetation is sparse, occurring in patches dominated by Cistus laurifolius L., Genista scorpius Sibth. & Sm. ex Boiss, and Prunus spinosa L. as the most frequent woody species and with the presence of the herbaceous species Arrhenatherum bulbosum and Bupleurum rigidum L. The second site, Beteta (40◦33 ′ 06 ″ N / 2◦06 ′ 32 ″ W; 1250–1300 m a.s.l; slope range: 3–10 %), is a monospecific forest of P. nigra. The mean tree density is 1286 ±339 trees ha −1 , the mean tree height is 17.0 ±1.6 m, and the mean dbh, 18.8 ±4.1 cm. The understory vegetation is scarce, with low cover. The main species are Genista scorpius Sibth. & Sm. ex Boiss, and Rosa canina L. In both sites of study understorey vegetation cover is in the range 5–20 % (Espinosa et al., 2020). The climate in the area is humid Mediterranean (Allu´ e, 1990), with a marked diurnal seasonal thermal oscillation, with average annual temperatures of 10.2 ◦C and 9.8 ◦C and average annual precipitation levels of 710 mm and 854 mm in Pozuelo and Beteta, respectively. Most of the Cuenca Mountains soils are calcareous, with predominantly shallow rendzina soils in the steeper areas and calcimorphic brown soils in the flat areas and troughs (Lucas-Borja et al., 2017). In both study areas, the soil is classified as Inceptisol (according to the Soil Taxonomy classification: Soil Survey Staff., 2014), or Dystric Cambisol (IUSS Working Group WRB, 2015). 2.2. Experimental design, fire treatment and forest floor and topsoil sampling Nine 50 m ×50 m plots were established in each study site (Pozuelo and Beteta), and three plots were randomly assigned to the spring and autumn prescribed fires and the experimental summer fires, respectively (Fig. S1 b, c). For acquisition of most data, a subplot of 30 m ×30 m was established in the centre of each plot. Prescribed fires were conducted, in May (spring burns) and November (autumn burns) 2016, and experimental summer fires in late June 2019 (hereafter, summer fires). Strip head fire technique was used in all cases. Both fire types were carried out by the Cuenca province Forest Service and EPRIF staff. The simulated wildfires were intended to reflect the typical early summer conditions in the area, with a low moisture content in the forest floor and mineral topsoil, which could lead to undesired impacts on the soil. Prescribed burnings developed mean fire rates of spread in the range 0.6–0.9 m min −1 , lower than the values measured in experimental summer fires (1.7–1.9 m min −1 ). Observed mean flame length was also lower in prescribed than summer fires (0.25–0.50 m versus 0.75–1.00 m, respectively). Fig. S2 illustrates the contrasted differences in fire behaviour observed in prescribed burning and experimental summer fires. Furthermore, a survey conducted several months after fires showed that while prescribed burnings did not cause apparent crown damage, crown scorch was observed on most trees in experimental fires. Before each fire, an automatic meteorological station (Onset, MA, USA) was placed close to the burning plot, within the forest (below canopy), to record the air temperature, relative humidity and 2-m wind speed at 1-min intervals during the prescribed and summer fires. Immediately prior to burning, samples of litter (Oi layer), upper duff (Oe layer), lower duff or humus (Oa layer) and mineral soil (0–2 cm) were collected at 20 regularly spaced points in each subplot. These samples were used to determine the respective moisture contents on dry basis by oven drying for 24 h (100 ◦C). Fire temperature was monitored at four different depths (Oi litter surface, Oa layer surface, soil surface and 2 cm depth) every second during each burn at 13 systematic points within the 30 m ×30 m subplots, with Inconel sheathed K-type thermocouples (1 mm diameter ground junction and 0.13 mm diameter wires) connected to buried data loggers. The mean depth of the forest floor before the fire and the reduction caused by the fire were determined in each plot. Three steel nails (length 30 cm) were driven into the ground until their heads were flush with the pre-fire forest floor surface close to each of 49 intersections of a grid (5 m ×5 m) within each 30 m ×30 m subplot. Immediately after the fire, the 147 nails in each plot were re-examined, and the exposed length of each nail and the depth of the remaining forest floor were measured. The mean value of these variables for the three nails assigned to each intersection was calculated in order to determine the respective mean pre-fire forest floor depth and reduction per plot. The percentage of area burned per plot in each fire was estimated as the percentage of intersections with the three nails affected by the fire and the percentage of mineral soil exposed per plot as the percentage of the total intersections (n =49) with complete forest floor combustion in the corresponding three nails. Forest floor and soil sampling dates were 1–3 days before and 2 days after the prescribed and experimental fires, to avoid any influence of post-fire soil conditions. Before the fire, 13 samples per plot of forest floor and mineral soil were collected at randomly selected points. To avoid trampling of the soil, samples were taken within the 1600 m 2 area formed by the 10 m wide strips surrounding the 30 m ×30 m subplot. A M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 4 25 cm ×25 cm metal square was used and all material inside the square was carefully cut with pruning shears down to the surface of the mineral soil and collected, discarding the woody material, and a homogeneous composite sample per plot was then obtained for forest floor and mineral soil, separately, by thoroughly mixing together the respective individual samples. The top 2 cm of mineral soil beneath the forest floor sample was then collected and a composite sample per plot was prepared, as for the forest floor. After fire, the remaining forest floor and topsoil samples (0–2 cm) were collected at 13 points in close proximity (<10 cm) to those where fire temperatures were measured. The remains of the forest floor were carefully removed with a sharp spatula and included the mineral ash produced during the partial combustion of this organic layer. The topsoil was then collected. When the combustion of the forest floor was complete, the soil samples included the mineral ash deposited on it. Composite samples per plot of forest floor and mineral soil were then obtained as before fire. 2.3. Laboratory analysis In the laboratory, the forest floor material was cut with scissors into small pieces to facilitate a more complete homogenisation and two types of subsamples were separated. Fresh subsamples were used for microbial analysis and air dried subsamples were used for chemical analysis. Mineral soil samples were sieved at 2 mm for chemical and microbial analysis. As before, fresh subsamples were used for microbial analysis and air-dried subsamples for chemical analysis. 2.3.1. SOM analysis Forest floor layer and mineral soils samples were analysed by thermal analysis (DSC-TG; Mettler Toledo Intl. Inc. TGA/DSC, Zurich, Switzerland). They were performed with 10 mg of sample under dry air (flow rate of 2.1 kg cm −2 and a scanning rate of 10 ◦C min −1 ). The heat of combustion (Q), in J g −1 , and weight loss (W), in mg g −1 , were determined by integrating the DSC or DTG curves over the exothermic region (150–600 ◦C). The areas under the DTG curves were divided into three groups, each representing a different degree of resistance to thermal oxidation (Merino et al., 2014, 2015): a) thermolabile (W1, 150–375 ◦C), b) recalcitrant (W2, 375–475 ◦C) and c) highly recalcitrant (W3, 475–550 ◦C). The resulting partial heats of combustion, denoted Q1, Q2 and Q3, were divided by the total Q and expressed as percentages. The T50w (the temperature at which 50 % of the weight of organic matter is lost) values were calculated. For mineral soil, the comparison between DSC and DTG allowed detection of possible endothermic reactions due to transformation of clay minerals. 2.3.2. Forest floor and soil properties The following forest floor parameters were analysed: pH (in a 1:6 forest floor/water suspension), total C and N contents (by dry combustion with a LECO Elemental Analyzer), microbial biomass C, by the fumigation-extraction method (Vance et al., 1987) with colorimetric determination and the activities of β-glucosidase (Eivazi and Tabatabai, 1988) and acid and alkaline phosphomonoesterase (hereafter referred to as phosphatase) (Trasar-Cepeda et al., 2003). The following parameters were also determined: mean weight diameter (MWD) of soil aggregates, by dry sieving (Kemper and Rosenau, 1986), the percentage of soil water-stable aggregates (WSA), by rainfall simulation laboratory experiments (Rold´ an et al. (1994), and pH (in a 1:2.5 soil/water suspension). The organic C content was estimated by the difference between total C and inorganic C. The latter was determined by combustion of the soil samples in an elemental analyzer after ignition at 400 ◦C for 8 h to remove the organic C. 2.4. Statistical analyses To test the effects of site (Pozuelo and Beteta) and burn season (spring prescribed fire, autumn prescribed fire and summer fire) on the moisture content of the pre-burn forest floor layer, meteorological variables during the fires, maximum temperatures reached at different positions during the fires, forest floor depth reduction and percentage of burned area, the data were fitted to a general linear model (GLM) with two factors (site and burn season). The assumptions of normality and homoscedasticity were tested with the Shapiro-Wilk test and Levene test, respectively. When these assumptions were not met, as in the case of some temperatures, the data were analysed using non-parametric Mann-Whitney U and Kruskal-Wallis tests. A repeated measures general linear model was used to test the effects of site, burn season and sampling date and their interactions on forest floor and soil parameters, separately. The between-subject factors were site (with two levels: Pozuelo and Beteta), and season (with three levels: spring prescribed fire, autumn prescribed fire and summer fire). The within-subject factor was the sampling date, with two levels (immediately before fire and after fire). We also performed repeated measures analysis to test the effect of sampling date individually within each site and season. The assumptions of normality and homoscedasticity were tested with the Shapiro-Wilk test and Levene test, respectively. The test results showed that the assumptions were met in most cases. The same approach was used for the forest floor depth. The possible association between changes in OM quality parameters (T50w and Q3) of the forest floor and topsoil as independent variables and changes in microbial properties of forest floor and topsoil as dependent variables was evaluated separately for each combination of variables by ordinary least square linear regression. Changes were assessed through the corresponding post-fire/pre-fire ratios. Regression assumptions were met for all forest floor and soil variables. The data on OM quality and microbiological parameters of the forest floor and mineral soil jointly were also subjected to principal component analysis (PCA) in order to summarise the information contained in the original set of variables, thus enhancing the interpretability while minimizing loss of information. PCA allows identification of the most important or principal components (PCs), which explain most of the variation present in the original variables. The relationships between the aforementioned components and thermal and chemical properties and the main PCA factors were also explored by ordinary lineal regression. A significance level of p <0.05 was applied in all cases. All statistical analyses were conducted using the SPSS 25.0 statistical package. 3. Results 3.1. Conditions during fire, forest floor reduction and fire temperatures As expected, the moisture content of the Oi, Oe and Oa layers and of the topsoil layer (0–2 cm) immediately before the fire (Table 1) was significantly lower in the summer fires than in the spring and autumn prescribed fires at both sites. In addition, the moisture content of forest floor layers was slightly lower in spring than in autumn. At both study sites, the meteorological variables were also significantly more severe during summer fires than in spring and autumn fires (Table 2). Overall, the meteorological conditions were milder in autumn than in spring. The mean pre-fire forest floor depth ranged from 2.5 to 4.3 cm (Table 3), and the reduction in forest floor depth was significantly greater in summer fires than in prescribed fires, and in spring fires than in autumn fires. Most of plot area was affected by the fire, although with high variability (62.9–96.6 %) and with higher values in spring than in autumn. Only the summer fires exposed the mineral soil by complete combustion of the forest floor, in around one third of the plot area (31.5 %), although there was a high degree of variability between fires and within plots. The maximum temperatures reached during summer fires were significantly higher than those during the prescribed fires for all the measurement positions, except in the Oi layer surface in Beteta, where they did not differed (Table 4). The duration of temperature >60 ◦C on the humus surface (Oa layer) was generally <2 and 3 min in the spring M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 5 and autumn prescribed fires, and it was about 1 h in the summer fires. At the soil surface, the respective value was less than half a minute duration during prescribed fires, while in summer fires it was around 45 min. The average duration of temperatures of 200 ◦C or more on the humus surface was only about 13 s during the prescribed fires and between 8 and 11 min during the summer fires. At the soil surface, it was about 3 min during the summer fires at both study sites. 3.2. Changes in forest floor properties The repeated measures analysis of variance revealed significant effects of season, burn (pre-burn, post-burn) and the interaction between both factors on most of the properties analysed (Supplementary Table S1). Significant differences were also observed for some of the properties analysed as a function of site (referred to here as location). The mean values of the variables analysed are summarised in Table 5 and Figs. 1, 2 and 3, including the results of the one-way repeated measures analyses carried out for each location and season. Table 1 Moisture content (%, relative to dry weight) of the different forest floor layers: litter (Oi), fermentation (Oe) and humus (Oa) and of the mineral topsoil (0–2 cm) immediately before spring and autumn prescribed fire and summer experimental fire in Pozuelo and Beteta (mean ±standard error). Site Pozuelo Beteta Fire type Prescribed Prescribed Experimental Prescribed Prescribed Experimental Season Spring Autumn Summer Spring Autumn Summer Oi layer 13.6 ±0.6 b 30.5 ±0.8 a 8.4 ±1.2 c 12.3 ±0.9 b 26.7 ±2.9 a 6.1 ±0.7 b Oe layer 33.6 ±1.6 b 56.7 ±5.2 a 8.9 ±2.3 c 31.2 ±0.8 b 40.3 ±0.8 a 6.7 ±0.6 c Oa layer 106.5 ±1.8 b 135.7 ±11.8 a 13.9 ±4.5 c 95.7 ±2.8 b 107.7 ±4.7 a 10.6 ±0.8 c Topsoil layer 27.8 ±1.0 a 25.7 ±1.0 a 7.5 ±3.8 b 24.5 ±2.5 a 28.8 ±3.2 a 14.3 ±1.6 b Mean values indicated by different letters for each site are different (according to post-hoc Newman-Keuls test). Table 2 Meteorological conditions during spring and autumn prescribed fire and summer experimental fire in Pozuelo and Beteta (mean ±standard error). T, ambient temperature, RH relative humidity, WS wind speed. Site Pozuelo Beteta Fire type Prescribed Prescribed Experimental Prescribed Prescribed Experimental Season Spring Autumn Summer Spring Autumn Summer T (◦C) 21.5 ±0.7 b 11.9 ±0.2 c 26.8 ±1.5 a 20.4 ±0.9 b 12.0 ±0.5 c 27.9 ±1.4 a RH (%) 47.7 ±3.0 b 67.0 ±0.8 a 31.1 ±8.9 c 32.7 ±1.4 b 43.5 ±0.5 a 24.4 ±8.1 c WS (m s −1 ) 0.8 ±0.3 b 0.3 ±0.2 c 1.5 ±0.3 a 0.8 ±0.0 b 0.1 ±0.0 c 1.7 ±0.3 a Mean values indicated by different letters for each site are different (according to the post-hoc Newman-Keuls test). Table 3 Pre-fire (BF) and post-fire (AF) forest floor depth, reduction of forest floor depth (percentage of the pre-fire value), percentage of the plot area burned by fire and percentage of plot area with mineral soil exposed after burning in spring and autumn prescribed fire and summer experimental fire in Pozuelo and Beteta (mean ± standard error). Site Pozuelo Beteta Fire type Prescribed Prescribed Experimental Prescribed Prescribed Experimental Season Spring Autumn Summer Spring Autumn Summer Forest floor depth, cm BF 2.8 ±0.2 a 3.4 ±0.2 a 3.0 ±0.4 a 4.3 ±0.4 a 3.5 ±0.1 a 3.8 ±0.3 a AF 1.8 ±0.2 b 2.6 ±0.2 b 0.3 ±0.1 b 2.5 ±0.4 b 2.7 ±0.2 b 0.5 ±0.2 b Forest floor depth reduction (%) 37.4 ±7.4 b 25.1 ±3.2 c 91.1 ±3.4 a 41.3 ±3.3 b 23.1 ±4.0 c 87.1 ±6.3 a Area burned (%) 81.3 ±9.7 a 62.9 ±9.5 b 96.6 ±1.8 a 95.1 ±1.4 a 63.4 ±8.6 b 90.5 ±7.6 a Mineral soil exposed (%) 0.0 ±0.0 0.0 ±0.0 25.2 ±10.6 0.0 ±0.0 0.0 ±0.0 36.3 ±12.7 Mean values indicated by different letters for forest floor depth variables indicate significant differences between the values before and after fire for each site and burn season. For the other variables, different letters indicate significant different differences for mean values between each burn season in each site (according to the posthoc Newman-Keuls test). Table 4 Maximum temperatures (◦C) reached at the litter surface (Oi layer), humus surface (Oa layer), mineral soil surface (Topsoil) and at 2 cm below the soil surface (2 cm depth) during the spring and autumn prescribed fire and summer experimental fire in Pozuelo and Beteta (mean ±standard error). Site Pozuelo Beteta Fire type Prescribed Prescribed Experimental Prescribed Prescribed Experimental Season Spring Autumn Summer Spring Autumn Summer Oi layer 321 ±115 b 134 ±61bc 564 ±7 a 359 ±32a 276 ±110 a 465 ±40 a Oa layer 125 ±40 b 47 ±27 bc 339 ±6 a 123 ±35 b 93 ±39 b 299 ±32 a Topsoil 33 ±2 b 13 ±0 c 148 ±21a 34 ±4 b 11 ±4 b 108 ±8 a 2 cm depth 19 ±0 b 11 ±0 c 37 ±2 a 16 ±1 b 8 ±1 c 37 ±1 a Mean values indicated by different letters for each site are different (according to the post-hoc Kruskal-Wallis and Mann-Whitney tests). M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 6 The C and N concentrations and values of the microbial variables were significantly higher in Beteta than in Pozuelo, while the opposite was observed for the C/N ratio. Overall, burning significantly increased pH, although the response was due to the more marked increase in the summer fires, not observed in the prescribed fires (Table 5). Regarding the effects on OM quality, the Differential Thermogravimetric (DTG) analysis curves of the two sites studied, showed two exothermic bands, with maxima at 330 and 410 ◦C, in the unburnt samples from both study sites (Fig. 1). After prescribed burning (spring or autumn), no changes in the OM quality were detected (Supplementary Table S1) and no significant differences were found in the distribution of the thermolabile fractions (Q1, Q2 and Q3; Table 5) or in T50w (Fig. 4). Unlike the prescribed fires, the summer fires led to significant changes in the DTG curves (Fig. 1) and in the distribution of thermolabile OM fractions (Fig. 2 and Table 5). Heating significantly reduced the area attributed to labile OM (Q1) in both Pozuelo and Beteta and increased the area of highly recalcitrant OM (Q3), although the difference in the latter was only significant in Pozuelo. In accordance, the Table 5 Values (mean ±standard error) of forest floor properties at the two study sites (Pozuelo and Beteta) before (BF) and after (AF) the spring and autumn prescribed fire and the summer experimental fire. Site Pozuelo Beteta Fire type Prescribed Prescribed Experimental Prescribed Prescribed Experimental Season Spring Autumn Summer Spring Autumn Summer C (%) BF 32.7 ±2.4 a 32.2 ±1.1 a 37.40 ±1.97 a 40.2 ±2.3 a 38.8 ±1.4 a 42.3 ±1.9 a AF 34.3 ±3.0 a 30.2 ±4.9 a 32.30 ±2.24 a 44.2 ±2.2 a 36.8 ±3.0 a 45.9 ±1.31 a N (%) BF 0.87 ±0.12 a 0.92 ±0.08 a 1.02 ±0.06 a 1.16 ±0.05 a 1.06 ±0.06 a 1.20 ±0.08 a AF 0.86 ±0.06 a 0.87 ±0.06 a 0.98 ±0.02 a 1.27 ±0.05 a 0.89 ±0.07 a 1.40 ±0.09 a C/N BF 38.3 ±2.2 a 35.5 ±1.9 a 36.9 ±0.9 a 34.6 ±0.4 a 36.6 ±1.5 a 35.4 ±1.1 a AF 39.9 ±1.2 a 34.3 ±4.1 a 32.8 ±1.8 a 34.8 ±0.5 a 41.6 ±3.4 a 33.0 ±2.4 a pH BF 5.64 ±0.12 a 5.94 ±0.17 a 5.13 ±0.16 a 6.02 ±0.15 a 5.98 ±0.33 a 5.55 ±0.23 a AF 6.24 ±0.28 a 6.28 ±0.11 a 8.33 ±0.34 b 6.53 ±0.23 a 6.50 ±0.58 a 7.07 ±0.70 a Q1 (%) BF 48.2 ±0.9 a 48.1 ±1 a 45.6 ±0.9 a 50.5 ±2.5 a 46.9 ±0.7 a 43.9 ±1.2 a AF 46.1 ±0.6 a 46.5 ±0.6 a 26.2 ±3.7 b 48.3 ±0.6 a 51.0±1.4 a 27.2 ±5.5 b Q2 (%) BF 46.0 ±0.5 a 46.2 ±0.9 a 48.5 ±0.8 a 42.8 ±2.1 a 46.3 ±0.9 a 48.2 ±0.8 a AF 46.7 ±1.1 a 46.3 ±0.8 a 56.2 ±4.1 a 44.7 ±0.5 a 43.6 ±0.9 a 55.9 ±2.8 a Q3 (%) BF 5.8 ±0.6 a 5.7 ±0.2 a 5.8 ±0.3 a 6.7 ±0.4 a 6.8 ±0.2 a 7.9 ±0.5 a AF 7.2 ±0.5 a 7.2 ±1.3 a 17.5 ±2.4 b 7.0 ±0.3 a 5.5 ±2.3 a 16.9 ±3.6 a Different letters (highlighted in bold) indicate significant differences between values before and after fire for each site and fire season. Statistically significant results are highlighted in bold. Means indicated by different letters (highlighted in bold) indicate significant differences between values before and after fire for each site and fire season. Fig. 1. Differential thermogravimetric curves (DTG) in the forest floor in the two study sites (Pozuelo and Beteta), before and after the spring and autumn prescribed fire and the summer experimental fire. M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 7 values of T50w increased dramatically (Fig. 2) after the summer fires. The microbial properties and enzyme activities of the forest floor were not significantly modified by prescribed fire, while summer fire caused a significant reduction in microbial biomass C (Cmic), Cmic/C and soil enzyme activities (β-glucosidase and acid phosphatase) at both study sites (Fig. 3). The relative reductions in these properties relative to pre-fire values, caused by summer fires, were greater in Pozuelo (85 %, 72 %, 97 % and 97 %, respectively) than in Beteta (47 %, 51 %, 77 % and 79 %, respectively). Alkaline phosphatase activity was only detected in Beteta, owing to the slightly higher pH values than in Pozuelo. The activity of this enzyme decreased also significant after the summer fires, with a relative reduction of 70 % (Fig. 3 i). The relative changes in the forest floor variables analysed (relative to the corresponding pre-fire value, expressed in %) for prescribed burning and summer fires are summarised in Table 6. The Q3, Cmic, Cmic/C and enzyme activities were the variables that showed the greatest changes in values between both fire types. Significant relationships between changes in forest floor microbial parameters and changes in organic matter quality were detected (Table 7). The relative increase in OM recalcitrance was associated with reductions in the values of the microbial parameters. 3.3. Changes in mineral topsoil (0–2 cm) properties The results of the repeated measures analysis showed that study site was the factor with the greatest influence on the soil properties analysed (Supplementary Table S2), with values generally being higher in Beteta than in Pozuelo, which is consistent with observations for the forest floor. Season, burn and the interaction of both factors significantly influenced some of these variables, with changes being more pronounced in relation to the summer fires than to the spring and autumn fires. The mean values of topsoil properties before and after prescribed and experimental fires are shown in Table 8 and Figs. 4, 5 and 6, indicating the significant changes obtained by one-way repeated measures analysis for each study site and season. The DTG curves for the mineral soil (Fig. 4) showed two exothermic bands with maxima at 330 and 410 ◦C in the unburnt samples from the two sites studied. The thermolabile fraction (Q1) of topsoil accounted for 50 % of the total heat (Jg −1 ) released in the laboratory-controlled combustion, and between 6 % and 12 % of the total heat was highly recalcitrant (Q3). The prescribed fires did not lead to changes in the SOM quality (Table 8), and no differences in the distribution of the thermolabile fractions nor in T50w were observed (Fig. 5). After the summer fires a significant increase in T50w were observed, in Pozuelo only. After the summer fires, Cmic and Cmic/OC were significantly reduced in both study sites, whereas the β-glucosidase only decreased significantly in Pozuelo and the alkaline phosphatase activity, in Beteta (Fig. 6). As in the forest floor, summer fires produced greater relative reductions in Cmic, Cmic/OC and β-glucosidase in Pozuelo (53 %, 50 % and 61 %, respectively) than in Beteta (45 %, 42 % and 42 %, respectively), although these differences were always smaller than in the forest floor. The Cmic, Cmic/OC and enzyme activities were the soil variables in which the greatest differences between the relative variations for prescribed burning and summer fires were observed (Table 6). No significant relationship between changes in microbial properties and changes in T50w and Q3 was detected. 3.4. Combined interpretation of changes in forest floor and soil parameters The results of the principal component analysis (PCA) revealed that factor 1 (PC1) and factor 2 (PC2), both with eigenvalues >1, accounted for 60 % and 26 % of the total variation, respectively (Fig. 7). PC1 clearly distinguished the samples collected after the summer fires and the other samples. Negative values on the PC1 axis were associated with high levels of T50w and Q3 in the forest floor, i.e. recalcitrant OM, and positive values, with high levels of Q1, Cmic, Cmic/OC, β-glucosidase and acid phosphatase activities in the forest floor layer, i.e. labile OM and high microbial biomass and activity (Fig. 8). The separation on the PC2 axis was not as clear, with Beteta samples being better represented in the positive part of the axis (associated with high values of T50w and Q3 in the mineral soil) and Pozuelo samples in the negative part of the axis (associated with high values of Q1 in the mineral soil). The distribution of the samples in the PCA clearly indicated that the main differences in soil and forest floor properties jointly were due to the summer fires and, to a lesser extent, to the study site. Significant negative relationships were observed between PC1 and the maximum temperatures reached at the surface of Oa layer, the mineral soil surface and 2 cm of mineral soil depth (R 2 =0.51, 0.84 and 0.88; respectively; p <0.05; n =18) and the duration of temperatures ≥200 ◦C on the Oa layer surface (R 2 =0.52). PC2 was mainly associated with soil chemical properties (not included in the PCA), positively with SOC, total N and pH and negatively with SOC/N (R 2 ranging from 0.52 to 0.84; p <0.05; n =36). 4. Discussion 4.1. Heating of forest floor and topsoil during prescribed and experimental fires The temperature profiles during fires, which showed a sharp decrease in the maximum values with depth in both forest floor and topsoil, support previous findings for fires in other Mediterranean pine forests (Cannac et al., 2009; Catalanotti et al., 2018; Merino et al., 2019; Giuditta et al., 2020; Moya et al., 2021; Plaza-´ Alvarez et al., 2021). Maximum temperatures in the forest floor layers varied widely, Fig. 2. Mean values of T50w (temperature at which 50 % of the weight of OM is lost) in the forest floor in the two study sites (Pozuelo and Beteta), before and after the spring and autumn prescribed fire and the summer experimental fire. M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 8 Fig. 3. Microbial variables in the forest floor in Pozuelo (at the left) and Beteta (at the right), before and after the spring and autumn prescribed fire and the summer experimental fire. (a) and (b): Microbial biomass C (Cmic); (c) and (d): Cmic/C ratio; (e) and (f): β-glucosidase activity; (g) and (h): Acid phosphatase activity; (i): Alkaline phosphatase activity. M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 9 especially in the autumn and spring fires, reflecting a patchy pattern of burning in some plots. The pronounced differences between the maximum temperatures observed in prescribed and experimental summer fires could be due to the different moisture contents of the humus and soil (Frandsen and Ryan, 1986; Hartford and Frandsen, 1992; Preisler et al., 2000). Nonetheless, the very low heat penetration detected in the mineral soil was remarkable, even in the summer fires conducted with fuel with a very low moisture content, and was probably favoured by a moderate forest floor fuel load (Busse et al., 2010). This could also explain the limited mineral soil exposure in these fires. 4.2. Forest floor properties The lack of significant differences in C and N concentrations and C/N Fig. 4. Differential thermogravimetric curves (DTG) in the mineral topsoil (0–2 cm) in the two study sites (Pozuelo and Beteta), before and after the spring and autumn prescribed fire and the summer experimental fire. Table 6 Mean values of the relative changes in forest floor and mineral soil variables analysed (relative to the corresponding pre-fire value, %) for prescribed fire and summer fire. Forest Floor Mineral soil (0–2 cm) Spring and autumn prescribed fire Summer experimental fire Spring and autumn prescribed fire Summer experimental fire MWD – – −2.1 a −5.1 a WSA – – 2.1 a 0.9 a pH 8.4 a 44.7 a 0.1 a 4.3 a C* 1.1 a −2.3 a −6.2 a −15.3 a N −2.5 a 7.7 a −8.6 a −4.4 b C/N 3.7 a −8.7 b 3.5 a −10.8 b T50w 0.2 a 18.2 b 0.9 a 4.3 a Q1 0.0 a −40.5 b −2.8 a −8.3 a Q2 −0.2 a 15.9 b 2.2 a 8.0 a Q3 6.8 a 154.2 b 13.5 a 13.3 a Cmic −4.7 a −65.6 b 31.6 a −49.0 b Cmic/C −3.6 a −61.2 b 42.7 a −39.9 b GLU −6.2 a −85.6 b 0.1 a −51.6 b acPHO −15.1 a −87.1 b 32.0 a −34.0 b alkPHO 32.6 a −63.4 b −3.4 a −72.5 b MWD, mean weight diameter of aggregates (mm). WSA, soil water stable aggregates (%). C*, total carbon in the forest floor, organic carbon in the mineral soil (%). N, total nitrogen (%). T50w, temperature at which 50 % of the weight of OM is lost (◦C). Q1, partial heat of combustion at temperatures of 200–375 ◦C (%). Q2, partial heat of combustion at temperatures of 375–475 ◦C (%). Q3, partial heat of combustion at temperatures of 475–550 ◦C (%). Cmic, microbial biomass C ( μ g g −1 ). GLU, β-glucosidase activity ( μ mol g −1 h −1 ). acPHO, acid phosphatase activity ( μ mol g −1 h −1 ). alkPHO, alkaline phosphatase activity ( μ mol g −1 h −1 ) only in Beteta site. Different letters (highlighted in bold) indicate significant differences between prescribed fire and summer fire. Table 7 Determination coefficient (R 2 ) of the linear regression between changes in forest floor microbial properties and changes in T50w and Q3 of the forest floor layer (n =18). The sign of the relationship is shown in brackets. Cmic post / Cmic pre (Cmic / C) post / (Cmic / C) pre GLU post/ GLU pre acPHO post / acPHO pre T50w post / T50w pre 0.759** (−) 0.734** (−) 0.751** (−) 0.794** (−) Q3 post / Q3 pre 0.701** (−) 0.531** (−) 0.745** (−) 0.698** (−) Cmic post and Cmic pre, forest floor microbial biomass C (mg/kg) after and before fire, respectively; (Cmic /C) post and (Cmic / C) pre, forest floor Cmic/C ratio after and before fire, respectively; GLU post and GLU pre, forest floor β-glucosi- dase activity ( μ mol g −1 h −1 ) after and before fire, respectively; acPHO post and acPHO pre, forest floor acid phosphatase activity ( μ mol g −1 h −1 ) after and before fire, respectively.* (p <0.05) or ** (p <0.01). M.T. Fontúrbel et al. Science of the Total Environment 907 (2024) 167669 16 Matosziuk, L.M., Gallo, A., Hatten, J., Bladon, K.D., Ruud, D., Bowman, M., et al., 2020. Short-term effects of recent fire on the production and translocation of pyrogenic carbon in Great Smoky Mountains National Park. Front. 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