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      Late Quaternary climate legacies in contemporary plant functional composition

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          Abstract

          The functional composition of plant communities is commonly thought to be determined by contemporary climate. However, if rates of climate-driven immigration and/or exclusion of species are slow, then contemporary functional composition may be explained by paleoclimate as well as by contemporary climate. We tested this idea by coupling contemporary maps of plant functional trait composition across North and South America to paleoclimate means and temporal variation in temperature and precipitation from the Last Interglacial (120 ka) to the present. Paleoclimate predictors strongly improved prediction of contemporary functional composition compared to contemporary climate predictors, with a stronger influence of temperature in North America (especially during periods of ice melting) and of precipitation in South America (across all times). Thus, climate from tens of thousands of years ago influences contemporary functional composition via slow assemblage dynamics.

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          New multidimensional functional diversity indices for a multifaceted framework in functional ecology.

          Sébastien Villéger, Norman W H Mason, David Mouillot (2008)
          Functional diversity is increasingly identified as an important driver of ecosystem functioning. Various indices have been proposed to measure the functional diversity of a community, but there is still no consensus on which are most suitable. Indeed, none of the existing indices meets all the criteria required for general use. The main criteria are that they must be designed to deal with several traits, take into account abundances, and measure all the facets of functional diversity. Here we propose three indices to quantify each facet of functional diversity for a community with species distributed in a multidimensional functional space: functional richness (volume of the functional space occupied by the community), functional evenness (regularity of the distribution of abundance in this volume), and functional divergence (divergence in the distribution of abundance in this volume). Functional richness is estimated using the existing convex hull volume index. The new functional evenness index is based on the minimum spanning tree which links all the species in the multidimensional functional space. Then this new index quantifies the regularity with which species abundances are distributed along the spanning tree. Functional divergence is measured using a novel index which quantifies how species diverge in their distances (weighted by their abundance) from the center of gravity in the functional space. We show that none of the indices meets all the criteria required for a functional diversity index, but instead we show that the set of three complementary indices meets these criteria. Through simulations of artificial data sets, we demonstrate that functional divergence and functional evenness are independent of species richness and that the three functional diversity indices are independent of each other. Overall, our study suggests that decomposition of functional diversity into its three primary components provides a meaningful framework for its quantification and for the classification of existing functional diversity indices. This decomposition has the potential to shed light on the role of biodiversity on ecosystem functioning and on the influence of biotic and abiotic filters on the structure of species communities. Finally, we propose a general framework for applying these three functional diversity indices.
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            Vive la différence: plant functional diversity matters to ecosystem processes

            Sandra Dı́az, Marcelo Cabido (2001)
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              Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales.

              Anke Stein, Katharina Gerstner, Holger Kreft (2014)
              Environmental heterogeneity is regarded as one of the most important factors governing species richness gradients. An increase in available niche space, provision of refuges and opportunities for isolation and divergent adaptation are thought to enhance species coexistence, persistence and diversification. However, the extent and generality of positive heterogeneity-richness relationships are still debated. Apart from widespread evidence supporting positive relationships, negative and hump-shaped relationships have also been reported. In a meta-analysis of 1148 data points from 192 studies worldwide, we examine the strength and direction of the relationship between spatial environmental heterogeneity and species richness of terrestrial plants and animals. We find that separate effects of heterogeneity in land cover, vegetation, climate, soil and topography are significantly positive, with vegetation and topographic heterogeneity showing particularly strong associations with species richness. The use of equal-area study units, spatial grain and spatial extent emerge as key factors influencing the strength of heterogeneity-richness relationships, highlighting the pervasive influence of spatial scale in heterogeneity-richness studies. We provide the first quantitative support for the generality of positive heterogeneity-richness relationships across heterogeneity components, habitat types, taxa and spatial scales from landscape to global extents, and identify specific needs for future comparative heterogeneity-richness research. © 2014 John Wiley & Sons Ltd/CNRS.
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                Author and article information

                Journal
                Title: Global Change Biology
                Abbreviated Title: Glob Change Biol
                Publisher: Wiley
                ISSN: 13541013
                Publication date Created: October 2018
                Publication date (Print): October 2018
                Publication date (Electronic): July 29 2018
                Volume: 24
                Issue: 10
                Pages: 4827-4840
                Affiliations
                [1 ]Environmental Change Institute, School of Geography and the Environment; University of Oxford; Oxford UK
                [2 ]Department of Biology; Norwegian University of Science and Technology; Trondheim Norway
                [3 ]School of Life Sciences; Arizona State University; Tempe Arizona
                [4 ]Department of Ecology and Evolutionary Biology; University of Arizona; Tucson Arizona
                [5 ]Santa Fe Institute; Santa Fe New Mexico
                [6 ]Max Planck Institute for Biogeochemistry; Jena Germany
                [7 ]German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; Leipzig Germany
                [8 ]Center for Macroecology, Evolution and Climate; Natural History Museum of Denmark, University of Copenhagen; Copenhagen Denmark
                [9 ]Section for Ecoinformatics & Biodiversity, Department of Bioscience; Aarhus University; Aarhus C Denmark
                [10 ]School of Biological Sciences; Queens University; Belfast Northern Ireland
                [11 ]Center for Theoretical Study; Charles University; Prague Czech Republic
                [12 ]Department of Ecology, Faculty of Science; Charles University; Prague Czech Republic
                [13 ]Department of Meteorology; University of Reading; Reading UK
                [14 ]Center for Biodiversity Dynamics in a Changing World (BIOCHANGE); Aarhus University; Aarhus Denmark
                [15 ]School of Geographical Sciences; University of Bristol; Bristol UK
                [16 ]CNRS, CEFE; Université de Montpellier - Université Paul Valéry - EPHE; Montpellier France
                Article
                DOI: 10.1111/gcb.14375
                PubMed ID: 30058198
                SO-VID: ca101c73-ce01-430d-82ef-9dc17f7d0bb1
                Copyright © © 2018
                License:

                http://doi.wiley.com/10.1002/tdm_license_1.1

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