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      A quantitative review of abundance‐based species distribution models

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          Greedy function approximation: A gradient boosting machine.

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            The global diversity of birds in space and time.

            Current global patterns of biodiversity result from processes that operate over both space and time and thus require an integrated macroecological and macroevolutionary perspective. Molecular time trees have advanced our understanding of the tempo and mode of diversification and have identified remarkable adaptive radiations across the tree of life. However, incomplete joint phylogenetic and geographic sampling has limited broad-scale inference. Thus, the relative prevalence of rapid radiations and the importance of their geographic settings in shaping global biodiversity patterns remain unclear. Here we present, analyse and map the first complete dated phylogeny of all 9,993 extant species of birds, a widely studied group showing many unique adaptations. We find that birds have undergone a strong increase in diversification rate from about 50 million years ago to the near present. This acceleration is due to a number of significant rate increases, both within songbirds and within other young and mostly temperate radiations including the waterfowl, gulls and woodpeckers. Importantly, species characterized with very high past diversification rates are interspersed throughout the avian tree and across geographic space. Geographically, the major differences in diversification rates are hemispheric rather than latitudinal, with bird assemblages in Asia, North America and southern South America containing a disproportionate number of species from recent rapid radiations. The contribution of rapidly radiating lineages to both temporal diversification dynamics and spatial distributions of species diversity illustrates the benefits of an inclusive geographical and taxonomical perspective. Overall, whereas constituent clades may exhibit slowdowns, the adaptive zone into which modern birds have diversified since the Cretaceous may still offer opportunities for diversification.
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              Predicting species distribution: offering more than simple habitat models

              In the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Ecography
                Ecography
                Wiley
                0906-7590
                1600-0587
                January 2022
                December 15 2021
                January 2022
                : 2022
                : 1
                Affiliations
                [1 ]Landscape Ecology, Inst. of Terrestrial Ecosystems, ETH Zürich Zürich Switzerland
                [2 ]Swiss Federal Research Inst. WSL Birmensdorf Switzerland
                [3 ]Inst. for Marine and Antarctic Studies, Univ. of Tasmania Hobart TAS Australia
                [4 ]IFREMER, Unité Écologie et Modèles pour l'Halieutique Nantes France
                [5 ]Inst. for the Oceans and Fisheries, Univ. of British Columbia Vancouver BC Canada
                [6 ]MARBEC, Univ. de Montpellier, CNRS, Ifremer, IRD Montpellier France
                [7 ]NORCE Climate, Bjerknes Centre for Climate Research Bergen Norway
                Article
                10.1111/ecog.05694
                cb18999f-6d57-49aa-8141-b5b910609c17
                © 2022

                http://creativecommons.org/licenses/by/3.0/

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

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