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      Impact of human disturbance on bee pollinator communities in savanna and agricultural sites in Burkina Faso, West Africa

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          Abstract

          All over the world, pollinators are threatened by land‐use change involving degradation of seminatural habitats or conversion into agricultural land. Such disturbance often leads to lowered pollinator abundance and/or diversity, which might reduce crop yield in adjacent agricultural areas. For West Africa, changes in bee communities across disturbance gradients from savanna to agricultural land are mainly unknown. In this study, we monitored for the impact of human disturbance on bee communities in savanna and crop fields. We chose three savanna areas of varying disturbance intensity (low, medium, and high) in the South Sudanian zone of Burkina Faso, based on land‐use/land cover data via Landsat images, and selected nearby cotton and sesame fields. During 21 months covering two rainy and two dry seasons in 2014 and 2015, we captured bees using pan traps. Spatial and temporal patterns of bee species abundance, richness, evenness and community structure were assessed. In total, 35,469 bee specimens were caught on 12 savanna sites and 22 fields, comprising 97 species of 32 genera. Bee abundance was highest at intermediate disturbance in the rainy season. Species richness and evenness did not differ significantly. Bee communities at medium and highly disturbed savanna sites comprised only subsets of those at low disturbed sites. An across‐habitat spillover of bees (mostly abundant social bee species) from savanna into crop fields was observed during the rainy season when crops are mass‐flowering, whereas most savanna plants are not in bloom. Despite disturbance intensification, our findings suggest that wild bee communities can persist in anthropogenic landscapes and that some species even benefitted disproportionally. West African areas of crop production such as for cotton and sesame may serve as important food resources for bee species in times when resources in the savanna are scarce and receive at the same time considerable pollination service.

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            Simultaneous inference in general parametric models.

            Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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              Global biodiversity scenarios for the year 2100.

              Scenarios of changes in biodiversity for the year 2100 can now be developed based on scenarios of changes in atmospheric carbon dioxide, climate, vegetation, and land use and the known sensitivity of biodiversity to these changes. This study identified a ranking of the importance of drivers of change, a ranking of the biomes with respect to expected changes, and the major sources of uncertainties. For terrestrial ecosystems, land-use change probably will have the largest effect, followed by climate change, nitrogen deposition, biotic exchange, and elevated carbon dioxide concentration. For freshwater ecosystems, biotic exchange is much more important. Mediterranean climate and grassland ecosystems likely will experience the greatest proportional change in biodiversity because of the substantial influence of all drivers of biodiversity change. Northern temperate ecosystems are estimated to experience the least biodiversity change because major land-use change has already occurred. Plausible changes in biodiversity in other biomes depend on interactions among the causes of biodiversity change. These interactions represent one of the largest uncertainties in projections of future biodiversity change.
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                Author and article information

                Contributors
                katharina.stein@uni-rostock.de
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                17 June 2018
                July 2018
                : 8
                : 13 ( doiID: 10.1002/ece3.2018.8.issue-13 )
                : 6827-6838
                Affiliations
                [ 1 ] Department of Animal Ecology and Tropical Biology Biocenter University of Wuerzburg Wuerzburg Germany
                [ 2 ] Department of Botany and Botanical Garden Institute of Biological Sciences University of Rostock Rostock Germany
                [ 3 ] Faculty of Organic Agricultural Sciences Universität Kassel Kassel Germany
                [ 4 ] Unité de Formation et de Recherche des Sciences de la Nature Unité de Recherche en Ecologie et Biodiversité Université Nangui Abrogoua Abidjan Côte d'Ivoire
                [ 5 ] Department of Entomology Royal Belgian Institute of Natural Sciences Brussels Belgium
                [ 6 ] Laboratoire de Biologie et Ecologie Végétales UFR/SVT Université Ouaga1 Pr Joseph Ki‐Zerbo Ouagadougou Burkina Faso
                Author notes
                [*] [* ] Correspondence

                Katharina Stein, Department of Botany and Botanical Garden, Institute of Biological Sciences, University of Rostock, Wismarsche Strasse 44, 18051 Rostock, Germany.

                Email: katharina.stein@ 123456uni-rostock.de

                Author information
                http://orcid.org/0000-0003-3111-6172
                http://orcid.org/0000-0001-5536-9700
                Article
                ECE34197
                10.1002/ece3.4197
                6053565
                f67d43bd-3cf9-4133-915d-9d06530734d6
                © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 January 2018
                : 05 April 2018
                : 19 April 2018
                Page count
                Figures: 5, Tables: 0, Pages: 12, Words: 8482
                Funding
                Funded by: German Federal Ministry of Education and Research (BMBF)
                Funded by: BMBF
                Funded by: Deutsche Forschungsgemeinschaft
                Funded by: Universität Rostock
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                ece34197
                July 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.3 mode:remove_FC converted:20.07.2018

                Evolutionary Biology
                bee communities,cotton,sesame,species spillover,sub‐saharan africa
                Evolutionary Biology
                bee communities, cotton, sesame, species spillover, sub‐saharan africa

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