Dataset Information

Testing the environmental filtering concept in global drylands.

ABSTRACT: 1. The environmental filtering hypothesis predicts that the abiotic environment selects species with similar trait values within communities. Testing this hypothesis along multiple - and interacting - gradients of climate and soil variables constitutes a great opportunity to better understand and predict the responses of plant communities to ongoing environmental changes. 2. Based on two key plant traits, maximum plant height and specific leaf area (SLA), we assessed the filtering effects of climate (mean annual temperature and precipitation, precipitation seasonality), soil characteristics (soil pH, sand content and total phosphorus) and all potential interactions on the functional structure and diversity of 124 dryland communities spread over the globe. The functional structure and diversity of dryland communities were quantified using the mean, variance, skewness and kurtosis of plant trait distributions. 3. The models accurately explained the observed variations in functional trait diversity across the 124 communities studied. All models included interactions among factors, i.e. climate - climate (9% of explanatory power), climate - soil (24% of explanatory power) and soil - soil interactions (5% of explanatory power). Precipitation seasonality was the main driver of maximum plant height, and interacted with mean annual temperature and precipitation. Soil pH mediated the filtering effects of climate and sand content on SLA. Our results also revealed that communities characterized by a low variance can also exhibit low kurtosis values, indicating that functionally contrasting species can co-occur even in communities with narrow ranges of trait values. 4. Synthesis We identified the particular set of conditions under which the environmental filtering hypothesis operates in drylands worldwide. Our findings also indicate that species with functionally contrasting strategies can still co-occur locally, even under prevailing environmental filtering. Interactions between sources of environmental stress should be therefore included in global trait-based studies, as this will help to further anticipate where the effects of environmental filtering will impact plant trait diversity under climate change.

SUBMITTER: Le Bagousse-Pinguet Y

PROVIDER: S-EPMC5476209 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Testing the environmental filtering concept in global drylands.

Le Bagousse-Pinguet Yoann Y Gross Nicolas N Maestre Fernando T FT Maire Vincent V de Bello Francesco F Fonseca Carlos Roberto CR Kattge Jens J Valencia Enrique E Leps Jan J Liancourt Pierre P

The Journal of ecology 20170206 4

1. The environmental filtering hypothesis predicts that the abiotic environment selects species with similar trait values within communities. Testing this hypothesis along multiple - and interacting - gradients of climate and soil variables constitutes a great opportunity to better understand and predict the responses of plant communities to ongoing environmental changes. 2. Based on two key plant traits, maximum plant height and specific leaf area (SLA), we assessed the filtering effects of cli ...[more]

PMID: 28642625

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Project description:AIM:Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. LOCATION:224 sites in diverse dryland plant communities from 22 geographical regions in six continents. METHODS:Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (?(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (?(R2)), and a multivariate abundance-based metric (?(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. RESULTS:Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and ?(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((?(R2)) and ?(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). MAIN CONCLUSIONS:Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

Dataset Information

Testing the environmental filtering concept in global drylands.

Publications

Testing the environmental filtering concept in global drylands.

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