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      Predicting bee community responses to land-use changes: Effects of geographic and taxonomic biases

      a , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 24 , 26 , 27 , 28 , 26 , 29 , 30 , 31 , 32 , 27 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 4 , 42 , 40 , 43 , 44 , 45 , 46 , 47 , 48 , 43 , 49 , 50 , 51 , 52 , 4 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 25 , 62 , 63 , 30 , 51 , 64 , 65 , 66 , 26 , 1 , 67 , 68 , 69 , 70 , 26 , 71 , 1 , 2

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          Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises.

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          Most cited references 29

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          Primary forests are irreplaceable for sustaining tropical biodiversity.

          Human-driven land-use changes increasingly threaten biodiversity, particularly in tropical forests where both species diversity and human pressures on natural environments are high. The rapid conversion of tropical forests for agriculture, timber production and other uses has generated vast, human-dominated landscapes with potentially dire consequences for tropical biodiversity. Today, few truly undisturbed tropical forests exist, whereas those degraded by repeated logging and fires, as well as secondary and plantation forests, are rapidly expanding. Here we provide a global assessment of the impact of disturbance and land conversion on biodiversity in tropical forests using a meta-analysis of 138 studies. We analysed 2,220 pairwise comparisons of biodiversity values in primary forests (with little or no human disturbance) and disturbed forests. We found that biodiversity values were substantially lower in degraded forests, but that this varied considerably by geographic region, taxonomic group, ecological metric and disturbance type. Even after partly accounting for confounding colonization and succession effects due to the composition of surrounding habitats, isolation and time since disturbance, we find that most forms of forest degradation have an overwhelmingly detrimental effect on tropical biodiversity. Our results clearly indicate that when it comes to maintaining tropical biodiversity, there is no substitute for primary forests.
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            A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems.

            Bees provide essential pollination services that are potentially affected both by local farm management and the surrounding landscape. To better understand these different factors, we modelled the relative effects of landscape composition (nesting and floral resources within foraging distances), landscape configuration (patch shape, interpatch connectivity and habitat aggregation) and farm management (organic vs. conventional and local-scale field diversity), and their interactions, on wild bee abundance and richness for 39 crop systems globally. Bee abundance and richness were higher in diversified and organic fields and in landscapes comprising more high-quality habitats; bee richness on conventional fields with low diversity benefited most from high-quality surrounding land cover. Landscape configuration effects were weak. Bee responses varied slightly by biome. Our synthesis reveals that pollinator persistence will depend on both the maintenance of high-quality habitats around farms and on local management practices that may offset impacts of intensive monoculture agriculture. © 2013 Blackwell Publishing Ltd/CNRS.
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              Using observation-level random effects to model overdispersion in count data in ecology and evolution

              Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated) data, or an excess frequency of zeroes (zero-inflation). Accounting for overdispersion in such models is vital, as failing to do so can lead to biased parameter estimates, and false conclusions regarding hypotheses of interest. Observation-level random effects (OLRE), where each data point receives a unique level of a random effect that models the extra-Poisson variation present in the data, are commonly employed to cope with overdispersion in count data. However studies investigating the efficacy of observation-level random effects as a means to deal with overdispersion are scarce. Here I use simulations to show that in cases where overdispersion is caused by random extra-Poisson noise, or aggregation in the count data, observation-level random effects yield more accurate parameter estimates compared to when overdispersion is simply ignored. Conversely, OLRE fail to reduce bias in zero-inflated data, and in some cases increase bias at high levels of overdispersion. There was a positive relationship between the magnitude of overdispersion and the degree of bias in parameter estimates. Critically, the simulations reveal that failing to account for overdispersion in mixed models can erroneously inflate measures of explained variance (r 2), which may lead to researchers overestimating the predictive power of variables of interest. This work suggests use of observation-level random effects provides a simple and robust means to account for overdispersion in count data, but also that their ability to minimise bias is not uniform across all types of overdispersion and must be applied judiciously.

                Author and article information

                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                11 August 2016
                : 6
                [1 ]Department of Life Sciences, Imperial College London, Silwood Park Campus , Buckhurst Rd, Ascot, Berkshire SL5 7PY, UK
                [2 ]Department of Life Sciences, Natural History Museum , Cromwell Road, London SW7 5BD, UK
                [3 ]Nees Institute for Plant Biodiversity, University of Bonn , Meckenheimer Allee 170, 53115 Bonn, Germany
                [4 ]Laboratorio Ecotono, INIBIOMA (CONICET - Universidad Nacional del Comahue) , Quintral 1250, 8400 Bariloche, Río Negro, Argentina
                [5 ]Institute for Sustainability Sciences , Agroscope, Reckenholzstrasse 191, 8046 Zurich, Switzerland
                [6 ]Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon , Panama City, Republic of Panama
                [7 ]Biosciences, Nottingham Trent University , Nottingham, NG11 8NS, UK
                [8 ]Centre for Agri-Environmental Research, School of Agriculture, Policy and Development, University of Reading, Earley Gate, Reading , RG6 6AR, UK
                [9 ]Science & Technology Branch, Environment and Climate Change Canada, 1125 Colonel By Drive, Carleton University, Ottawa , Ontario K1A 0H3, Canada.
                [10 ]Alterra, Part of Wageningen University and Research , P.O. Box 47, 6700 AA WageningenI, Netherlands
                [11 ]Sustainability Research Institute, University of East London , 4-6 University Way, Docklands, London E16 2RD, UK
                [12 ]Grupo de Ecología y Manejo de Artrópodos, El Colegio de la Frontera Sur (ECOSUR), Carretera Antiguo Aeropuerto km 2.5 . Tapachula, 30700 Chiapas, Mexico
                [13 ]CSIRO Land and Water , Canberra, ACT 2601, Australia
                [14 ]British Trust for Ornithology (Scotland), Biological and Environmental Sciences, University of Stirling , FK9 4LA, UK
                [15 ]Department of Landscape Ecology, Institute for Natural Resource Conservation, Kiel University , Olshausenstrasse 75, 24118 Kiel, Germany
                [16 ]Department of Biology, Nature Conservation, University Marburg , Marburg, Germany
                [17 ]Institute of Integrative Biology, ETH Zurich , Switzerland
                [18 ]Applied Entomology, ETH Zurich , Schmelzbergstr. 7/LFO, 8092 Zurich, Switzerland
                [19 ]RSPB, Scottish Headquarters 2 Lochside View , Edinburgh Park, Edinburgh, EH12 9DH, UK
                [20 ]Institute for Environmental Sciences, University of Koblenz-Landau , Fortstr. 7, 76829 Landau, Germany
                [21 ]Conservation Ecology, Faculty of Biology, Philipps-Universität Marburg , Karl-von-Frisch-Str. 8, 35032 Marburg, Germany
                [22 ]Dipartimento di Scienze Veterinarie, Viale delle Piagge 2, 56100, Pisa, Universitá di Pisa , Italia
                [23 ]Department of Soil and Crop Sciences, Colorado State University , Fort Collins, CO 80523, USA
                [24 ]School of Life Sciences, University of Sussex , BN19QG, UK
                [25 ]Helmholtz Centre for Environmental Research - UFZ, Department of Community Ecology , Theodor-Lieser-Straβe 4, 06120 Halle, Germany
                [26 ]Agroecology, Department of Crop Sciences, Georg-August-University Göttingen , D-37077 Göttingen, Germany
                [27 ]School of Biological Sciences, Plymouth University , Plymouth PL4 8AA, UK
                [28 ]Department of Biology, University of Iowa , Iowa, USA
                [29 ]Agroscope, Institut for Sustainability Sciences , CH-8046 Zurich, Switzerland
                [30 ]Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Am Hubland , 97074 Würzburg, Germany
                [31 ]Justus-Liebig University, Department of Animal Ecology , Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany
                [32 ]Institut für Systematische und Evolutionäre Botanik , Switzerland
                [33 ]Dept. for Ecology and Conservation of Fauna and Flora, Federal Agency for Nature Conservation (Bundesamt für Naturschutz, BfN) , Konstantinstrasse 110, D-53179 Bonn, Germany
                [34 ]Institut de Recherche pour le Développement (IRD) , 93143 Bondy Cedex, France
                [35 ]Centro Internacional de Agricultura Tropical (CIAT), Tropical Soil Biology and Fertility Program, Latin American and Caribbean Region , Cali, Colombia
                [36 ]INRA, UR 406 Abeilles et Environnement, CS 40509 , F-84914 Avignon, France
                [37 ]School of BioSciences, University of Melbourne , Parkville VIC 3010, Australia
                [38 ]New Zealand Institute for Plant and Food Research Ltd, Private Bag 92169, Auckland Mail Centre , Auckland 1142, New Zealand
                [39 ]Marshall Agroecology Ltd , 2 Nut Tree Cottages, Barton, Winscombe BS25 1DU, UK
                [40 ]Departamento de Biología, Facultad de Ciencias, Universidad Nacional de Colombia , Sede Bogotá, Colombia
                [41 ]University of California, Riverside Department of Entomology , 900 University Avenue, Riverside, CA 92521, USA
                [42 ]Department of Biology and Ecology, Faculty of Science, University of Novi Sad , 21000 Novi Sad, Serbia
                [43 ]Department of Biology, Lund University , SE-223 62 Lund, Sweden
                [44 ]Swedish University of Agricultural Sciences, Department of Ecology , Box 7044, SE-750 07 Uppsala, Sweden
                [45 ]RSPB, UK Headquarters The Lodge , Sandy, Bedfordshire, UK
                [46 ]Laboratorio de Investigaciones en Abejas, LABUN, Departamento de Biología, Facultad de Ciencias, Universidad Nacional de Colombia , Carrera 45 No. 26-85, Edif. Uriel Gutiérrez, Bogotá D.C., Colombia
                [47 ]Corporación para la Gestión de Servicios Ecosistémicos, Polinización y Abejas - SEPyA , Bogotá D.C., Colombia
                [48 ]School of Environmental Sciences, University of East Anglia , Norwich NR47TJ, UK
                [49 ]Laboratory of Biogeography & Ecology, Department of Geography, University of the Aegean , 81100 Mytilene, Greece
                [50 ]Entomology Department, Cornell University , Ithaca, NY 14850, USA
                [51 ]Botany, School of Natural Sciences, Trinity College Dublin , Dublin 2, Ireland
                [52 ]CREA-ABP, Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria, Centro di ricerca per l’agrobiologia e la pedologia , Via di Lanciola 12/A, I-50125 - Cascine del Riccio, Firenze, Italy
                [53 ]School of Environmental and Rural Science, University of New England , Armidale, New South Wales, Australia
                [54 ]Department of Biological Sciences, Brock University , St. Catharines, Ontario, L2S 3A1, Canada
                [55 ]Department of Environmental Sciences, University of Virginia , Charlottesville, Virginia 22904-4123, USA
                [56 ]Blandy Experimental Farm , 400 Blandy Farm Lane, Boyce, Virginia 22620, USA
                [57 ]Département des Sciences Biologiques, Université du Québec à Montreál, C.P. 8888, succursale Centre-ville , Montreál, Québec H3C 3P8, Canada
                [58 ]GEES (School of Geography, Earth and Environmental Sciences, University of Birmingham , Birmingham B15 2TT, UK
                [59 ]Department of Ecology, Environment and Plant Sciences, Stockholm University , SE-106 91 Stockholm, Sweden
                [60 ]CSIRO , Dutton Park, QLD 4102, Australia
                [61 ]University of Bern, Institute of Ecology and Evolution, Community Ecology , Baltzerstrasse 6, 3012 Bern, Switzerland
                [62 ]Animal and Plant Health Inspection Service, Plant Protection and Quarantine, United States Department of Agriculture (USDA) , South San Francisco, CA 94080, USA
                [63 ]Faculty of Sciences, National University of Colombia , Medellín (UNALMED), Columbia
                [64 ]Plant Biology and Conservation, Northwestern University , 2205 Tech Drive, O.T. Hogan Hall Rm 2-1444, Evanston, IL 60208, USA
                [65 ]Chicago Botanic Garden , 1000 Lake Cook Rd, Glencoe, IL 60011, USA
                [66 ]Department of Biology, Saint Louis University , 3507 Laclede Avenue, Macelwane Hall, St. Louis, MO 63103-2010, USA
                [67 ]Centre for Integrative Ecology, School of Biological Sciences, University of Canterbury , Private Bag 4800, Christchurch 8140, New Zealand
                [68 ]Division Forest, Nature, and Landscape, Department of Earth & Environmental Sciences, KU Leuven , Celestijnenlaan 200E, B-3001 Leuven, Belgium
                [69 ]Departamento de Ciencias Químico-Biológicas, Universidad de las Américas Puebla , Mexico
                [70 ]Spotvogellaan 68 , 2566 PN, Den Haag, The Netherlands
                [71 ]Department of Agricultural Biology, National Institute of Agricultural Science, RDA , Wanju-gun, Jellabuk-do, 55365, Korea
                Author notes
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/




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