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      Herbicide risk assessments of non-target terrestrial plant communities: A graphical user interface for the plant community model IBC-grass

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          Abstract

          Plants located adjacent to agricultural fields are important for maintaining biodiversity in semi-natural landscapes. To avoid undesired impacts on these plants due to herbicide application on the arable fields, regulatory risk assessments are conducted prior to registration to ensure proposed uses of plant protection products do not present an unacceptable risk. The current risk assessment approach for these non-target terrestrial plants (NTTPs) examines impacts at the individual-level as a surrogate approach for protecting the plant community due to the inherent difficulties of directly assessing population or community level impacts. However, modelling approaches are suitable higher tier tools to upscale individual-level effects to community level. IBC-grass is a sophisticated plant community model, which has already been applied in several studies. However, as it is a console application software, it was not deemed sufficiently user-friendly for risk managers and assessors to be conveniently operated without prior expertise in ecological models. Here, we present a user-friendly and open source graphical user interface (GUI) for the application of IBC-grass in regulatory herbicide risk assessment. It facilitates the use of the plant community model for predicting long-term impacts of herbicide applications on NTTP communities. The GUI offers two options to integrate herbicide impacts: (1) dose responses based on current standard experiments (acc. to testing guidelines) and (2) based on specific effect intensities. Both options represent suitable higher tier options for future risk assessments of NTTPs as well as for research on the ecological relevance of effects.

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          Most cited references 16

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          CLO-PLA: the database of clonal and bud bank traits of Central European flora

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            Mechanisms of plant competition for nutrients, water and light

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              Functional trait diversity maximizes ecosystem multifunctionality

              Understanding the relationship between biodiversity and ecosystem functioning has been a core ecological research topic over the last decades. Although a key hypothesis is that the diversity of functional traits determines ecosystem functioning, we do not know how much trait diversity is needed to maintain multiple ecosystem functions simultaneously (multifunctionality). Here, we uncovered a scaling relationship between the abundance distribution of two key plant functional traits (specific leaf area, maximum plant height) and multifunctionality in 124 dryland plant communities spread over all continents except Antarctica. For each trait, we found a strong empirical relationship between the skewness and the kurtosis of the trait distributions that cannot be explained by chance. This relationship predicted a strikingly high trait diversity within dryland plant communities, which was associated with a local maximization of multifunctionality. Skewness and kurtosis had a much stronger impact on multifunctionality than other important multifunctionality drivers such as species richness and aridity. The scaling relationship identified here quantifies how much trait diversity is required to maximize multifunctionality locally. Trait distributions can be used to predict the functional consequences of biodiversity loss in terrestrial ecosystems.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: ResourcesRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                13 March 2020
                2020
                : 15
                : 3
                Affiliations
                [1 ] Plant Ecology and Nature Conservation, University of Potsdam, Potsdam, Germany
                [2 ] Bayer AG, Monheim am Rhein, Germany
                [3 ] Bayer CropScience, Research Triangle Park, North Carolina, United States of America
                [4 ] Berlin-Brandenburg Institute of Advances Biodiversity Research, Berlin, Germany
                National University of Kaohsiung, TAIWAN
                Author notes

                Competing Interests: The project was funded by Bayer AG. Authors employed by Bayer AG, namely SH, CM, TP, SM, worked on preparing this manuscript (see Author contributions). This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Article
                PONE-D-19-21544
                10.1371/journal.pone.0230012
                7069634
                32168318
                © 2020 Reeg et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 7, Tables: 6, Pages: 18
                Product
                Funding
                Funded by: Bayer AG
                The project was funded by Bayer AG. Authors employed by Bayer AG worked on preparing this manuscript (see Author contributions). We acknowledge the support of the Deutsche Forschungsgemeinschaft and Open Access Publishing Fund of University of Potsdam.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Agrochemicals
                Herbicides
                Biology and Life Sciences
                Ecology
                Plant Ecology
                Plant Communities
                Ecology and Environmental Sciences
                Ecology
                Plant Ecology
                Plant Communities
                Biology and Life Sciences
                Plant Science
                Plant Ecology
                Plant Communities
                Engineering and Technology
                Human Factors Engineering
                Man-Computer Interface
                Graphical User Interfaces
                Computer and Information Sciences
                Computer Architecture
                User Interfaces
                Graphical User Interfaces
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Seeds
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Biology and Life Sciences
                Psychology
                Behavior
                Animal Behavior
                Grazing
                Social Sciences
                Psychology
                Behavior
                Animal Behavior
                Grazing
                Biology and Life Sciences
                Zoology
                Animal Behavior
                Grazing
                Research and analysis methods
                Mathematical and statistical techniques
                Statistical methods
                Monte Carlo method
                Physical sciences
                Mathematics
                Statistics
                Statistical methods
                Monte Carlo method
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Stem Anatomy
                Internodes
                Custom metadata
                All software files and additional information are available at https://github.com/JetteReeg/IBCgrassGUI. Additional relevant data are within the paper and the Supporting Information file, except for the confidential dose-response data used in the supporting information file.

                Uncategorized

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