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      A comparison of different Malaise trap types

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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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            The value of the world's ecosystem services and natural capital

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              More than 75 percent decline over 27 years in total flying insect biomass in protected areas

              Global declines in insects have sparked wide interest among scientists, politicians, and the general public. Loss of insect diversity and abundance is expected to provoke cascading effects on food webs and to jeopardize ecosystem services. Our understanding of the extent and underlying causes of this decline is based on the abundance of single species or taxonomic groups only, rather than changes in insect biomass which is more relevant for ecological functioning. Here, we used a standardized protocol to measure total insect biomass using Malaise traps, deployed over 27 years in 63 nature protection areas in Germany (96 unique location-year combinations) to infer on the status and trend of local entomofauna. Our analysis estimates a seasonal decline of 76%, and mid-summer decline of 82% in flying insect biomass over the 27 years of study. We show that this decline is apparent regardless of habitat type, while changes in weather, land use, and habitat characteristics cannot explain this overall decline. This yet unrecognized loss of insect biomass must be taken into account in evaluating declines in abundance of species depending on insects as a food source, and ecosystem functioning in the European landscape.
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                Author and article information

                Journal
                Insect Conservation and Diversity
                Insect Conserv Diversity
                Wiley
                1752-458X
                1752-4598
                November 2022
                August 17 2022
                November 2022
                : 15
                : 6
                : 666-672
                Affiliations
                [1 ]Field Station Fabrikschleichach, Department of Animal Ecology and Tropical Biology Julius‐Maximilians‐University Würzburg Würzburg Germany
                [2 ]Department of River Ecology and Conservation Senckenberg Research Institute and Natural History Museum Frankfurt Gelnhausen Germany
                [3 ]Faculty of Biology University of Duisburg‐Essen Essen Germany
                [4 ]University of Applied Sciences Trier, Environmental Campus Birkenfeld Hoppstädten‐Weiersbach Germany
                [5 ]Epidemiology Biostatistics and Prevention Institute, University Zürich Zürich Switzerland
                [6 ]Department of Developmental Biology/Institute of Biology Friedrich‐Alexander‐University Erlangen‐Nuremberg Erlangen Germany
                [7 ]Conservation Ecology Center Smithsonian's National Zoo and Conservation Biology Institute Front Royal Virginia USA
                [8 ]Seebach Germany
                [9 ]Bavarian Forest National Park Grafenau Germany
                Article
                10.1111/icad.12604
                2e388a1d-bfea-4d74-b1ad-0917df011418
                © 2022

                http://creativecommons.org/licenses/by-nc/4.0/

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

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