Plant canopies mitigate the decline of soil microbial functions under climatic disequilibrium

Plant canopies mitigate the decline of soil microbial functions under climatic disequilibrium | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 6 May 2025 V1 Latest version Share on Plant canopies mitigate the decline of soil microbial functions under climatic disequilibrium Authors : Jorge Prieto-Rubio 0000-0002-5600-5113 [email protected] , Jordi Margalef-Marrasé , Francisco Lloret , Marta Goberna , Ana Rincón , and Miguel Verdu 0000-0002-9778-7692 Authors Info & Affiliations https://doi.org/10.22541/au.174655095.52300335/v1 353 views 179 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Plant responses to climate are shaped by their climatic niche, defined by the range of climatic conditions under which they can persist. A mismatch between this niche and current climate can lead to climatic disequilibrium, impacting plant performance and plant--soil interactions. We investigated how such disequilibrium influences soil microbial functioning by quantifying eight enzyme activities involved in carbon, nitrogen, and phosphorus cycling. We sampled 300 soils beneath plant canopies and adjacent open areas along a gradient of climatic disequilibrium in ten Mediterranean shrublands in the Iberian Peninsula. Plant communities near their climatic optimum exhibited similar enzymatic activity under canopies and in open ground. However, as plant communities deviated from their optimum, soils beneath canopies hosted higher enzyme activity compared to open grounds. These results suggest that plant canopies buffer microbial functioning under climatic stress, shedding light on how climate-driven disequilibria alter plant--soil interactions and ecosystem resilience. Introduction The assembly of plant communities results from the combined action of biotic and abiotic drivers that altogether delimitate the realised ecological niches of coexisting species 1 . Among these components, climate plays a fundamental role as it constrains the adaptive responses of plant species across spatial and temporal scales 2 . The performance of plant species under macro-climatic conditions defines their climatic niche (CN), i.e., the multi-dimensional space that represents the optimum-to-critical climatic ranges for the plant species’ performance and, thus, their distribution 3,4 . The CNs can be extended beyond the species level to include the plant community and site levels 5,6 , hence offering the opportunity to track scale-dependent ecological processes. Plant community and species responses to environmental conditions will depend on their CN, necessarily influencing the biotic interactions such as competition, facilitation, pollination or predation 7,8 . Therefore, the position of a plant within its climatic niche is also expected to determine its interactions with the associated soil microbiota, potentially altering key microbial-mediated ecosystem processes, such as soil carbon and nutrient cycling, and ultimately shaping the functioning of plant communities. Climate change can move plant species and communities out of their optimal climatic niche conditions and, as a consequence, generate climatic disequilibrium (CD) scenarios 4,9 . CD is defined as the mismatch between the observed climate, under which a plant species occurs, and the climatic optimal requirements of the same species in a given location 4 . Several studies on the response of plant communities with different CD to climate change have shown that high levels of climatic disequilibrium lead to a great impact on plant performance at physiological and population levels 4,8,10,11 . In contrast, plant communities closer to their climatic optimum have shown great vigor in facing the negative consequences arising from climate change 12 , which may help to buffer the loss of ecological functions 13 , including those mediated by soil microbiota. Soil microbial communities are main biotic engines responsible for key soil functions 14 . Distinct microbial guilds (e.g., saprotrophic bacteria and fungi, or mycorrhizal fungi, among others) can differentially contribute to carbon and nutrient mobilization in soil, for instance by directly promoting nutrient acquisition from host roots or through soil organic matter decomposition 15,16 . The majority of soil microorganisms are heterotrophs capable of releasing extracellular enzymes that cleave complex organic molecules into simpler ones, allowing soil nutrient mineralization and fertility 17 . The extracellular enzymatic activity in soils is sensitive to shifts in various environmental factors, both biotic and abiotic, particularly those that represent or model the dynamics of the plant-soil interaction 18,19 . In this sense, soil organic matter acts as a key intermediary in the plant-soil system, with its availability primarily determined by the plant inputs 20 . Thus, it functions as the primary precursor of soil enzymatic activities, either enhancing or suppressing them based on its content and/or quality 21,22 . The role of soil organic matter on soil enzymatic activity is primarily promoted beneath the plant canopies 23 , and this is sustained even in harsh environments where plant communities inherently adapt to climatic stress. The buffering effects of plants on soil enzymatic activity loss can be tested in habitats where plant communities are typically structured into vegetation patches surrounded by open areas 24 , where species functionality may be hindered by environmental constraints, especially related to climate 9 . These patchy systems are frequent in drylands, and are typically constituted by several plant species interacting within a given patch 25–27 . The plant patches can modify the microclimatic conditions underneath their canopy (e.g., by reducing high temperature and radiation, and retaining soil moisture) 13,28 , leading to a preferential accumulation of water, organic matter, nutrients and biological activity in soils 23,24 . Therefore, plant patches are generally thought of as fertility islands and hotspots of soil microbial activity with enhanced decomposition and nutrient cycling 23,25 . However, the magnitude of this plant canopy effect on soil microbial activity under contrasting climate stress scenarios remains poorly understood. Here, we hypothesize that plant communities in drylands under increasing CD (i.e., composed by species further away from their optimum climatic conditions) will have lower plant canopy effects on soil microbial functions, particularly in the rates of enzymatic activities related to carbon (C), nitrogen (N) and phosphorus (P) cycling (Hypothesis 1) (Fig. 1). In addition, we expect that the negative effects of CD on these enzymatic activities will be more pronounced in adjacent open grounds than in soils under plant canopies (Hypothesis 2) (Fig. 1). To test these predictions, we first calculated the climatic disequilibrium (CD) of ten plant communities across Mediterranean ecosystems in the Iberian Peninsula (Fig. 2). The community CD was estimated by averaging the CDs of the most abundant canopy species (Table S1). The CD of each species is calculated as the Euclidean distance between its position in the climatic space (i.e., species’ climatic optimum) and the observed climatic conditions within the same climatic space. We also determined, through fluorogenic and spectrophotometric assays, eight potential enzymatic activities related to C, N and P mobilization in soils collected underneath patches of the canopy plants and in the open grounds in their vicinity (hereafter referred to as ‘microsites’). Then, we analyzed the relationship between the plant community CD and soil enzymatic activities in each microsite to determine the role of vegetation in preserving soil microbial functions under increasing levels of CD. The balance between the enzymatic activity underneath the plant patches versus the adjacent open ground was calculated, and also modelled as a function of soil organic matter content as a microsite-level property and main source for enzyme activity. Results Climatic space, climatic niches (CN) and climatic disequilibrium (CD) of plants The climatic space defined by 13 climatic biovariables (see the analytical procedure in Material and Methods) was reduced to two Principal Components (PC), which explained 48% and 27.6% of the total variance, respectively (Fig. S1). The first component (PC1) was positively correlated with temperature variables (annual mean temperature, maximum temperature of the warmest month), and negatively with precipitation variables (mean precipitation of the driest month and the mean precipitation of the wettest month) (Table S2). The second component (PC2) was positively correlated with temperature seasonality and negatively with precipitation variables (Table S2). The climatic niches (CN) for the plant species were defined across the climatic space (and synthesized by the centroid) (Fig. 3). The observed climate (OC) of each site was also projected into the climatic space, and its distance from the species’ CN resulted in the climatic distance (CD) of the plant species (Fig. 3; Table S3). The larger the distance between the species’ CN and OC, the higher the CD for the given species (Fig. 3; Table S3). Community CD was defined as the mean of the species CD per study site and the overall mean of CD scores across the ten study sites was 1.56. The lowest mean CD was recorded in HC (CD = 0.52), while plant communities with the most disequilibrated canopy species were CB, TA, and GA (with mean CD > 2, Fig. S2). Plant communities away from their climatic equilibrium showed lower rates of soil enzymatic activities Soil enzymatic activities showed contrasting rates across sites and microsites (i.e., patches and open ground) (Fig. S3; Table S4). Across sites, major enzymatic rates were detected for those activities targeting labile C, i.e., β-glucosidase and β-cellobiohydrolase, N cycling, i.e., chitinase and leucine amino-peptidase, and P cycling, i.e., acid phosphatase (Fig. S3; Table S4). A general trend to lower soil enzymatic activity rates with increasing plant community CD was detected (Fig. 4). Also, soil enzymatic activity tended to be higher in patches compared to open grounds, and this difference tended to increase in sites with plant communities showing higher CD (Fig. 4). In sites with plant communities showing higher CD, greater differences between soil enzymatic activity rates were detected underneath patches compared to open ground (Fig. 4). These differences were driven by the decline in soil enzymatic activity in the open ground (Fig. 4; Table 1). By contrast, the sites with low CD generally showed similar enzymatic activity rates between patches and adjacent open grounds, or even greater in the latter (Fig. 4; Table 1). Plant patches mitigated soil enzymatic activity losses under climatic disequilibrium The relative intensity of enzymatic activities in patches vs. open ground (RII EA ) as a function of the relative soil organic matter content (measured as RII SOM ) and the CD revealed positive relationships between RII EA and RII SOM (Table 2), particularly for enzymes decomposing labile-to-recalcitrant organic matter (i.e., β-glucosidase, β-cellobiohydrolase, β-xylosidase, chitinase and acid phosphatase). Meanwhile, enzymes strictly related to recalcitrant substrates (i.e., β-glucuronidase, laccase and leucine aminopeptidase) showed marginal or non-significant relationships with RII SOM or CD. In addition, the whole response of enzymatic activities (calculated by PCA) significantly positively correlated with responses of soil respiration (RII Resp , R 2 = 0.07, p = 0.003), but at lower extent than the significant predictors of enzymatic activity in Table 2 (CD, R 2 = 0.23, p < 0.001; RII SOM , R 2 = 0.18, p < 0.001) (Fig. S5). Discussion Climate change is altering global biodiversity and ecosystem functions 29 , by shifting species away from their climatic optimal requirements and reducing their performance 4,30 . In line with these observations, our study has revealed that climatic disequilibrium (CD) in plant communities reduces soil functioning, specifically microbial-mediated soil enzymatic activities related to C, N and P cycling. Previous studies have shown that CD alters the composition of plant communities 31,32 , affects the outcomes of plant-plant interactions 9,33 , and ultimately influences the dynamics of plant communities 34,35 . Here, we show that the effects of CD extend to other trophic levels, including soil decomposers, which perform essential ecosystem functions in terrestrial ecosystems. Across the studied habitats, soils exhibit higher enzyme activity rates associated with the decomposition of labile substrates, while those linked to recalcitrant compounds are either weakly expressed or absent. These patterns are likely driven by the biogeographical limitation of these nutrients in soils, as biological activity in drylands is globally constrained by the availability of mineral inputs, especially those linked to N and P cycling 36,37 , which in turn increases the demand by soil microorganisms through N- and P-enzymatic activities 38,39 . Furthermore, plant communities in these habitats are composed predominantly of shrub species, and may influence soil enzyme activity through the soil organic matter content. Shrubs generally contribute more to absolute recalcitrant inputs to the soil than grasses 40 , but less than trees 41 . As a result, these shrub plant communities modulate the soil enzymatic activity by either favouring enzymes that primarily decompose labile substrates or by facilitating the synergistic degradation of recalcitrant compounds 38 . We observe these patterns mainly on β-glucosidase and β-cellobiohydrolase activities, which together break down cellulose, and on enzymes promoting N and P mobilization through chitine and phosphate-enriched compounds (Fig. 4, Table S4). Under climatic disequilibrium (CD) scenarios, we find that plant communities with low CD have high rates for all soil enzymes, while plant communities with high CD show significantly lower enzymatic activities. Furthermore, we detect that the negative effect of CD on soil microbial activity is particularly exacerbated in open grounds, while these functional losses are mitigated beneath vegetation patches. The potential vulnerability to soil microbial functional loss agrees with previous studies that evaluated the impact of macroclimatic variables on the biological activity in soils 42–44 . Indeed, the climate-based distribution modelling that we performed to infer CD helps to explain the microsite-based outcomes, as plant communities inhabiting sites with low CD would favour soil enzymatic activities beyond the vegetation patches, i.e., towards the open grounds. Meanwhile, plant communities under increasing CD would support the enzymatic activities beneath vegetation patches while declining in the open grounds 23,24,45 . In fact, plant communities with larger CD amplify the differences in soil enzymatic activities at the microsite level, confirming both the constraining effects of climatic stress on soil functions 44 , and the influence of canopy cover in alleviating the loss of soil microbial functions under such conditions 23 . This canopy effect is supported by the source content that promotes enzymatic activity, i.e., soil organic matter. In particular, β-glucosidase, β-cellobiohydrolase, β-xylosidase, chitinase and acid phosphatase activities mainly respond to the microsite-associated variations, as these enzymatic activities are maintained beneath the plant patches across CD scenarios. Beyond our expectations, soil enzymatic activities related to more recalcitrant organic sources, particularly β-glucuronidase and, to a lesser extent leucine amino-peptidase, reveal increasing rates underneath patches with high CD. This response partially matches with previous expectations for C cycling under warming 44 . However, we do not find laccase (i.e., oxidative activity) increasing with CD, possibly due to compositional shifts in the local exoenzyme-producing microbiota 16,46 . We have also found that the enzymatic activities measured in the laboratory are positively related with soil respiration rates in the field, supporting that microbial metabolism is maintained under patches when climatic disequilibrium increases. However, our models also reveal that there is additional unexplained variance, suggesting that other factors beyond those strictly related to climate disequilibrium or organic matter are contributing to soil microbial activity. Previous studies have shown the contribution of plant attributes, soil physicochemical properties, and the structure and dynamics of associated microbial communities 43,47 , on soil-microbial ecosystem functions. Hence, future multifaceted approaches with all these biotic and abiotic components of terrestrial ecosystems will help to understand the evolution of ecosystem functioning under climatic disequilibrium scenarios. In summary, our study reveals that climatic disequilibrium of plants -mostly derived from temperature and precipitation related variables- is an important driver of soil microbial functions in Mediterranean-type ecosystems, spatially structured in vegetation patches and open grounds, as moving into a loss of soil enzymatic activities when climatic disequilibrium increases. Despite the negative consequences of CD on the soil enzymatic activities, the contrasting climatic disequilibrium across plant communities evidenced the potential role of vegetation patches to conserve and buffer soil enzymatic activity when considering the whole ecosystem. Indeed, our work highlights the role of canopy plants in maintaining the ecosystem functioning in the face of climatic imbalances that are expected to increase with ongoing climate change. But, at the same time, it warns that this buffering role may be at risk if climatic disruptions impact engineering plant species constituting the vegetation cover. Materials and Methods Study sites and sampling The study was performed in ten plant communities distributed across the Iberian Peninsula (Fig. 2). These communities are shrublands and inhabit areas influenced by a Mediterranean-type climate, with high inter- and intra- annual variability in the temperature and precipitation regimes, and contrasting drought periods concentrated during summer 48 . Throughout the study sites, we studied 31 plant species distributed across 14 orders, 17 families and 22 genera (see Table S1). In each site, we sampled surface soils (0-10 cm depth) underneath the vertical projection of three plant individuals belonging to 5 representative canopy species and in adjacent open ground areas with the same surface dimensions. We collected a total of 300 soil samples (10 sites, 5 species, 3 individuals per species, plus paired open grounds), each one consisting of five (ca. 200 g) sub-samples that were pooled into a composite sample. During soil collections, we determined soil respirations (g CO 2 m -2 h -1 ), by using an EGM-5 Gas Analyzer (PP Systems). The analyzer also recorded soil moisture (M soil ) and soil temperature (T soil ) at the time of each respiration measurement. During the sampling campaign (~ 5 days per site), soils were preserved at 4°C until laboratory processing. After each sampling, all soil samples were sieved through a 2 mm mesh, and preserved at -20 °C until the enzymatic activity assays. The sampling campaign was carried out from March to July 2023, and enzymatic tests in soils were performed in July 2023. Measurement of soil enzymatic activities and organic matter We determined eight potential soil enzymatic activities related to carbon and nutrient mobilisation in soils 49–51 . Five of these enzymatic activities were associated to C cycling in soils, allowing to track from labile to recalcitrant organic components: β-glucosidase (EC 3.2.1.3) and β-cellobiohydrolase (EC 3.2.1.91) that breakdown cellulose into labile residues; β-xylosidase (EC 3.2.1.37) and β-glucuronidase (EC 3.2.1.31) that are hemicellulose-hydrolyzing enzymes and related to intermediate-recalcitrant organic residues; and laccase activity (EC 1.10.3.2), that facilitates lignin oxidation, i.e., a highly recalcitrant organic molecule. In addition, we determined acid phosphatase (EC 3.1.3.2) activity as proxy of P mineralization; and chitinase (EC 3.2.1.14) and leucine aminopeptidase (EC 3.4.11.1) activities that respectively cleave chitin and polypeptides, hence contributing to N mobilisation. The experimental procedure for soil multi-enzymatic activity determination consisted in incubating 1 g of soil at 100 rpm and 25 °C overnight in the corresponding buffer (Tris-maleate 40 Mm at pH 8 for leucine aminopeptidase; and Tris–acetate 10 Mm at pH 4.5 for the remaining enzymes) 52 . After ending soil incubations, all enzymes except laccase were determined by fluorogenic assays that were performed by using the substrates methylcoumarin (AMC) for leucine aminopeptidase, and methylumbelliferone (MU) for the rest of enzymes. For laccase activity, a photometric assay was carried out by using 2,2-Azino-bis 3-ethylbenzothiazoline-6-sulfonic acid (ABTS) as a substrate 52 . For each enzymatic activity, we performed two replicates and one negative control per soil sample, i.e., a total of 900 assays per enzymatic activity. The enzymatic activities were measured with a Victor microplate reader (Perkin-Elmer Life Sciences, Massachusetts, USA), at excitation/emission wavelengths of 355/460 nm for the fluorogenic assays, and 415 nm for the determination of laccase activity. In parallel, soil organic matter (SOM, in %) at each sample was determined by calcination at 360º for 4.5 h in the Laboratory of Plant Material and Chemical Analysis at the Pyrenean Institute of Ecology (IPE-CSIC, Jaca, Spain). Climatic and canopy species occurrence data To determine the climatic niche of plant canopy species occurring in the ten studied sites, the geographical occurrence and the associated climatic information of the 31 studied plant species was compiled. The occurrence data referring to each plant species were extracted from the Global Biodiversity Information Facility (GBIF) database (GBIF 2021, http://www.gbif.org). Raw GBIF-based datasets were filtered to avoid geographic and temporal inconsistencies. First, to avoid possible errors and historical distribution changes, we only used records from 1970 onwards from the species native range area, based on Plants of the World Online, (POWO 2024, www.plantsoftheworldonline.org) criteria. Then, we reduced the occurrence density of 1 per km 2 to avoid climatically duplicated records as the resolution of the climatic data was of 1 km 2 area 35 . The climatic information was extracted from CHELSA database (version 2.1, 1 km² resolution) 53 , for the period 1981-2010, and for all the occurrences of the studied species. To construct the climatic niche for each species, we selected 13 bioclimatic variables (bio) from CHELSA: annual mean temperature (bio 1), temperature seasonality (bio 4), maximum temperature of the warmest month (bio 5), minimum temperature of the coldest month (bio 6), annual range of temperature (bio 7), mean temperature of the warmest quarter (bio 10), and mean temperature of the coldest quarter (bio 11) all of which are related to temperature. Additionally, we selected other variables related to precipitation: annual precipitation (bio 12), precipitation of the wettest month (bio 13), precipitation of the driest month (bio 14), precipitation seasonality (bio 15), precipitation of the wettest quarter (bio 16), and precipitation of the driest quarter (bio 17). These bioclimatic variables were those that did not derive from the interaction of temperature and precipitation (e.g., temperature of the wettest month), hence avoiding subsequent orthogonality constraints when applying ordination analyses for dimensionality reduction 11,33 . Further, the possible sampling bias and the spatial autocorrelation 54 were prevented by reducing occurrence density to a non-significant autocorrelation distance based on our bioclimatic data ( ecodist R package) 55 . We finally obtained 31 occurrence datasets, ranging from 100 to 15,193 observations per species (See Supplementary Information 2). Climatic niche (CN) and climatic disequilibrium (CD) of plants We used climatic data from the distribution range area of all the studied plant species to construct a climatic common space and the species climatic niches (CN) 56 . First, we built a common climatic space for all the studied canopy species using the 13 bioclimatic variables extracted from all the filtered occurrences. To reduce the dimensionality within our set of variables and build the climatic common space, we performed a correlation-based principal components analysis (PCA) using the dudi.pca function of the ade4 R package 57 . From this calculation, we extracted all the predicted values (i.e., scores) belonging to the two first axes of all the occurrences. Each species CN was characterised based on the two main components of the PCA of the common climatic space. For each species, a 2-dimensional kernel density function was applied to smooth the density of its occurrence scores along the two main dimensions of the PCA 58 . We applied a Gaussian kernel function using the kde function of the ks R package 59 , which allowed us to determine the expected density of occurrences in each cell of the climatic space. The optimal bandwidth matrix for each density function was selected by cross-validation 60 . Subsequently, the niche optimum for each species was obtained by calculating the centre of gravity (centroid) of the 2-dimensional kernel distribution using the COGravity function from the SDMTools R package 61 . Simultaneously, the observed climate (OC) for each study site was extracted from the CHELSA climate database 53 . The OC of each study site was then translated into the common climatic space using suprow function ( Ade4 R package) 57 . Finally, the climatic disequilibrium (CD) for each species was calculated for each site by applying the two-dimensional Euclidean distance between the OC of the study site and the niche centroid of each studied species 62 . The larger the distance between the species’ CN and OC, the higher the CD for the given species (Fig. 3; Table S3). The CD scores calculated for the five predominant plant canopies per study site were averaged to determine CD at the plant community level. Statistical analyses The absolute values of eight soil enzymatic activities were first evaluated at the plant community, plant species identity and microsite levels through post hoc analyses, by using functions in ggplot2 and multcompView R packages. To test whether plant communities away from their climatic equilibrium showed lower rates of enzymatic activity in patch and open-ground soils (Hypothesis 1), we performed Linear Mixed-Effect (LME) models by fitting the climatic disequilibrium (CD) averaged at plant community level and its interaction with microsite (i.e., patch vs open ground) as fixed factors, the study site as a random factor, and each soil enzymatic activity as the response variable. The modelling was performed with the lm function in the stats R package. The absolute values of enzymatic activities were log-transformed to fit them into a Gaussian distribution for a better model adjustment 63 . To evaluate canopy effects on the soil enzymatic activities across CD scenarios (Hypothesis 2), we calculated the relative interaction intensity index 64 for each enzymatic activity (RII EA ), which consisted of pairwise comparisons of enzymatic activities (EA) at the microsite level (i.e., patch with adjacent open ground) using the following equation: \begin{equation} \text{RII}_{\text{EA}}=\frac{\text{EA}_{\text{patc}h}\ -\ {EA}_{\text{open}}}{\text{EA}_{\text{patc}h}+\ {EA}_{\text{open}}}\ \nonumber \\ \end{equation} Using this index, positive values (RII EA > 0) indicate higher soil enzymatic activity beneath plant patches compared to adjacent open-ground soils, while negative values (RII EA < 0) indicate that open grounds have greater enzymatic activity than the plant patches. This RII-based approach was also applied to soil organic matter (RII SOM ). As for Hypothesis 1, we employed LME models, where each RII EA was treated as the response variable, CD of plant communities and RII SOM were included as fixed factors, and the study site was incorporated as a random factor. The whole response of enzymatic activities, measured through RII EA , were analyzed by Principal Component Analysis (PCA). The euclidean-distance matrix was calculated for the RII EA dataset by the vegdist function. The PC axes were used to determine the correlation with predictors of RII EA (i.e., CD and RII SOM ), and soil respiration (by calculating RII Soil_resp ) as partial outcome from enzyme activity, by using envfit function in vegan . All statistical analyses and figure plotting were developed in the RStudio environment 65 , and R v 4.4.1 66 . References 1. Chase, J. M., & Leibold, M. A. Ecological niches: linking classical and contemporary approaches. (2003).2. 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Available at: http://www.posit.co/. 66. Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria Available at: https://www.r-project.org/. Acknowledgments This research was supported by Generalitat Valenciana (CIPROM/2021/63, Prometeo program). We thank Daniel Rodríguez-Ginart, Alba Navarro-Montagud, Ricardo Sánchez-Martin, Patricio García-Fayos, Alicia Montesinos-Navarro and Santiago Donat for their support during field samplings, and Beatriz Pallol for her help in laboratory tasks. Competing interests The authors declare no competing interests. Fig. 1 | A conceptual framework illustrating how low (blue-coloured scenario) and increasing (yellow-coloured scenario) climatic disequilibrium in plant communities impacts on soil organic matter (SOM, purple asterisks) content and the balance of soil enzymatic activities (coloured balls) beneath a vegetation patch versus open ground. Fig. 2 | Location of the study sites with patchy vegetation in the Iberian Peninsula. The size of the circles is proportional to the magnitude of the climatic disequilibrium in each plant community. Circles are coloured to reflect their position on the gradient of climatic disequilibrium represented in the scale at the bottom of the graph. Fig. 3 | Degree of climatic disequilibrium (CD) in plant communities. Each plot shows the observed climate (OC, black triangles) for a given plant community and the climatic niche (CN) inferred for each plant species (coloured dots). The community CD was calculated as the averaged euclidean distance between each CN and OC. Plant communities are represented by sites across a CD gradient, from lower (left) to higher (right) values recorded on the plant canopy species (see Fig. 2 and Table S3). Fig. 4 | Relationship between plant community climatic disequilibrium (CD) and soil enzymatic activities. The response of each soil enzymatic activity was evaluated in open grounds (coloured in grey) and in patches (coloured in red, blue and yellow for enzymes related to C, N and P mobilisation, respectively). CD values within each community are the average disequilibria of their dominant canopy plants. Enzymatic activities (pmol mg soil −1 min −1 , and pmol g soil −1 day −1 for laccase activity) were log-transformed. Statistical relationships between variables are shown in Table 1. Enzymatic activity Est. t Est. t Est. t χ 2 Marginal Conditional β-Glucosidase -0.60 ± 0.41 4.48* -0.43 ± 0.13 2.35*** 0.49 ± 0.08 6.28*** 191.32*** 0.21 0.67 β-Cellobiohydrolase -0.10 ± 0.05 2.1ms 0.01 ± 0.04 0.26ns 0.07 ± 0.03 2.71*** 54.57*** 0.21 0.42 β-Xylosidase -0.09 ± 0.05 1.91ms -0.06 ± 0.03 1.89ms 0.06 ± 0.02 3.01** 88.72*** 0.09 0.42 β-Glucuronidase -0.01 ± 0.01 1.04ns -0.03 ± 0.01 2.56* 0.02 ± 0.01 3.31** 34.18*** 0.04 0.22 Laccase < -0.01 ± 0.01 0.93ns -0.01 ± 0.01 2.54* < -0.01 ± 0.01 1.62ns 147.45*** 0.04 0.52 Chitinase -0.16 ± 0.08 2.12ms 0.15 ± 0.07 2.31* 0.07 ± 0.04 1.81ms 67.86*** 0.32 0.53 Leucine aminopeptidase -0.19 ± 0.14 1.35ns -0.27 ± 0.09 3.18** 0.19 ± 0.05 3.72*** 130.75*** 0.05 0.49 Acid phosphatase -0.47 ± 0.16 3.06* -0.21 ± 0.13 1.56ns 0.30 ± 0.08 3.68*** 63.46*** 0.21 0.44 Table 1 | Relationships between soil enzymatic activities and plant community climatic disequilibrium and microsite (patch vs open ground). Linear mixed-effect models were performed to evaluate climatic disequilibrium (CD) interacting with the microsite (patch vs. open ground), and ‘Site’ as a random factor. Estimate coefficients and standard error are shown with the associated t-statistic (fixed factors), the χ2-statistic (random factor), and determination coefficient (R 2 ) for marginal (fixed) and conditional (fixed and random) factors. Significance is represented by ‘***’ p < 0.001; ‘**’ p < 0.01; ‘*’ p < 0.05; ‘ms’ p 0.10. Table 2 | Effects of climatic disequilibrium and organic matter content on enzymatic activity balance (patch vs. open open) in soils. Predictors Est. P-val Est. P-val Est. P-val Est. P-val Est. P-val Est. P-val Est. P-val Est. P-val Intercept -0.34 0.025 -0.22 0.200 -0.20 0.278 -0.30 0.118 -0.21 0.339 0.03 0.808 -0.32 0.088 -0.19 0.210 CD 0.32 0.002 0.35 0.007 0.20 0.094 0.24 0.052 0.02 0.875 0.18 0.035 0.23 0.052 0.17 0.078 RII SOM 0.50 <0.001 0.55 0.001 0.60 0.001 0.32 0.184 0.53 0.075 0.69 <0.001 0.06 0.702 0.63 <0.001 Random effects (Site) χ 2 6.54 0.011 7.21 0.007 7.37 0.007 0.79 0.371 0.76 0.384 3.63 0.057 10.41 0.001 6.47 0.011 Observations 150 150 148 150 124 150 150 150 Marginal R 2 / Conditional R 2 0.367 / 0.444 0.297 / 0.386 0.169 / 0.276 0.081 / 0.115 0.026 / 0.060 0.272 / 0.335 0.112 / 0.258 0.226 / 0.321 Linear mixed-effects models to evaluate the influence of climatic disequilibrium (CD) of plant communities and soil organic matter (measured by RII SOM ) on soil enzymatic activity balances (RII EA ), following the regression model fitting: lmer RII EA ~ CD + RII SOM + (1|Site). Values in bold show significant relationships between predictive and response variables measured by t-statistic (in red, P-value < 0.05; in black, P-value < 0.10). Information & Authors Information Version history V1 Version 1 06 May 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords canopy effects climatic disequilibrium climatic niche plant communities shrublands soil enzymatic activity soil functioning vegetation patch Authors Affiliations Jorge Prieto-Rubio 0000-0002-5600-5113 [email protected] Centro de Investigaciones sobre Desertificación View all articles by this author Jordi Margalef-Marrasé Centro de Investigaciones sobre Desertificación View all articles by this author Francisco Lloret CREAF View all articles by this author Marta Goberna Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria View all articles by this author Ana Rincón Instituto de Ciencias Agrarias View all articles by this author Miguel Verdu 0000-0002-9778-7692 Centro de Investigaciones sobre Desertificación View all articles by this author Metrics & Citations Metrics Article Usage 353 views 179 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Jorge Prieto-Rubio, Jordi Margalef-Marrasé, Francisco Lloret, et al. 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