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      Mapping functional diversity from remotely sensed morphological and physiological forest traits

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          Abstract

          Assessing functional diversity from space can help predict productivity and stability of forest ecosystems at global scale using biodiversity–ecosystem functioning relationships. We present a new spatially continuous method to map regional patterns of tree functional diversity using combined laser scanning and imaging spectroscopy. The method does not require prior taxonomic information and integrates variation in plant functional traits between and within plant species. We compare our method with leaf-level field measurements and species-level plot inventory data and find reasonable agreement. Morphological and physiological diversity show consistent change with topography and soil, with low functional richness at a mountain ridge under specific environmental conditions. Overall, functional richness follows a logarithmic increase with area, whereas divergence and evenness are scale invariant. By mapping diversity at scales of individual trees to whole communities we demonstrate the potential of assessing functional diversity from space, providing a pathway only limited by technological advances and not by methodology.

          Abstract

          As remote sensing technology improves, it is now possible to map fine-scale variation in plant functional traits. Schneider et al. remotely sense tree functional diversity, validate with field data, and reveal patterns of plant adaptation to the environment previously not retrievable from plot data

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          Rebuilding community ecology from functional traits.

          There is considerable debate about whether community ecology will ever produce general principles. We suggest here that this can be achieved but that community ecology has lost its way by focusing on pairwise species interactions independent of the environment. We assert that community ecology should return to an emphasis on four themes that are tied together by a two-step process: how the fundamental niche is governed by functional traits within the context of abiotic environmental gradients; and how the interaction between traits and fundamental niches maps onto the realized niche in the context of a biotic interaction milieu. We suggest this approach can create a more quantitative and predictive science that can more readily address issues of global change.
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            Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness

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

              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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                Author and article information

                Contributors
                fabian-daniel.schneider@geo.uzh.ch
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                13 November 2017
                13 November 2017
                2017
                : 8
                : 1441
                Affiliations
                [1 ]ISNI 0000 0004 1937 0650, GRID grid.7400.3, Remote Sensing Laboratories, Department of Geography, , University of Zurich, ; Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
                [2 ]ISNI 0000 0004 1937 0650, GRID grid.7400.3, Department of Evolutionary Biology and Environmental Studies, , University of Zurich, ; Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
                [3 ]ISNI 0000000107068890, GRID grid.20861.3d, Jet Propulsion Laboratory, , California Institute of Technology, ; 4800 Oak Grove Drive, Pasadena, CA 91011 USA
                Author information
                http://orcid.org/0000-0003-1791-2041
                http://orcid.org/0000-0001-6713-1599
                http://orcid.org/0000-0002-8430-3214
                http://orcid.org/0000-0002-7724-1633
                http://orcid.org/0000-0002-4283-2484
                http://orcid.org/0000-0003-3473-8065
                http://orcid.org/0000-0002-9627-9565
                Article
                1530
                10.1038/s41467-017-01530-3
                5682291
                29129931
                ed77607e-486c-4edf-b9c8-adb1b92854ee
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 September 2016
                : 25 September 2017
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