@misc{ReegHeineMihanetal.2019, author = {Reeg, Jette and Heine, Simon and Mihan, Christine and McGee, Sean and Preuss, Thomas G. and Jeltsch, Florian}, title = {Simulation of herbicide impacts on a plant community}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {528}, issn = {1866-8372}, doi = {10.25932/publishup-42303}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423039}, pages = {16}, year = {2019}, abstract = {Background Semi-natural plant communities such as field boundaries play an important ecological role in agricultural landscapes, e.g., provision of refuge for plant and other species, food web support or habitat connectivity. To prevent undesired effects of herbicide applications on these communities and their structure, the registration and application are regulated by risk assessment schemes in many industrialized countries. Standardized individual-level greenhouse experiments are conducted on a selection of crop and wild plant species to characterize the effects of herbicide loads potentially reaching off-field areas on non-target plants. Uncertainties regarding the protectiveness of such approaches to risk assessment might be addressed by assessment factors that are often under discussion. As an alternative approach, plant community models can be used to predict potential effects on plant communities of interest based on extrapolation of the individual-level effects measured in the standardized greenhouse experiments. In this study, we analyzed the reliability and adequacy of the plant community model IBC-grass (individual-based plant community model for grasslands) by comparing model predictions with empirically measured effects at the plant community level. Results We showed that the effects predicted by the model IBC-grass were in accordance with the empirical data. Based on the species-specific dose responses (calculated from empirical effects in monocultures measured 4 weeks after application), the model was able to realistically predict short-term herbicide impacts on communities when compared to empirical data. Conclusion The results presented in this study demonstrate an approach how the current standard greenhouse experiments—measuring herbicide impacts on individual-level—can be coupled with the model IBC-grass to estimate effects on plant community level. In this way, it can be used as a tool in ecological risk assessment.}, language = {en} } @phdthesis{Reeg2019, author = {Reeg, Jette}, title = {Simulating the impact of herbicide drift exposure on non-target terrestrial plant communities}, doi = {10.25932/publishup-42907}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429073}, school = {Universit{\"a}t Potsdam}, pages = {178}, year = {2019}, abstract = {In Europe, almost half of the terrestrial landscape is used for agriculture. Thus, semi-natural habitats such as field margins are substantial for maintaining diversity in intensively managed farmlands. However, plants located at field margins are threatened by agricultural practices such as the application of pesticides within the fields. Pesticides are chemicals developed to control for undesired species within agricultural fields to enhance yields. The use of pesticides implies, however, effects on non-target organisms within and outside of the agricultural fields. Non-target organisms are organisms not intended to be sprayed or controlled for. For example, plants occurring in field margins are not intended to be sprayed, however, can be impaired due to herbicide drift exposure. The authorization of plant protection products such as herbicides requires risk assessments to ensure that the application of the product has no unacceptable effects on the environment. For non-target terrestrial plants (NTTPs), the risk assessment is based on standardized greenhouse studies on plant individual level. To account for the protection of plant populations and communities under realistic field conditions, i.e. extrapolating from greenhouse studies to field conditions and from individual-level to community-level, assessment factors are applied. However, recent studies question the current risk assessment scheme to meet the specific protection goals for non-target terrestrial plants as suggested by the European Food Safety Authority (EFSA). There is a need to clarify the gaps of the current risk assessment and to include suitable higher tier options in the upcoming guidance document for non-target terrestrial plants. In my thesis, I studied the impact of herbicide drift exposure on NTTP communities using a mechanistic modelling approach. I addressed main gaps and uncertainties of the current risk assessment and finally suggested this modelling approach as a novel higher tier option in future risk assessments. Specifically, I extended the plant community model IBC-grass (Individual-based community model for grasslands) to reflect herbicide impacts on plant individuals. In the first study, I compared model predictions of short-term herbicide impacts on artificial plant communities with empirical data. I demonstrated the capability of the model to realistically reflect herbicide impacts. In the second study, I addressed the research question whether or not reproductive endpoints need to be included in future risk assessments to protect plant populations and communities. I compared the consequences of theoretical herbicide impacts on different plant attributes for long-term plant population dynamics in the community context. I concluded that reproductive endpoints only need to be considered if the herbicide effect is assumed to be very high. The endpoints measured in the current vegetative vigour and seedling emergence studies had high impacts for the dynamic of plant populations and communities already at lower effect intensities. Finally, the third study analysed long-term impacts of herbicide application for three different plant communities. This study highlighted the suitability of the modelling approach to simulate different communities and thus detecting sensitive environmental conditions. Overall, my thesis demonstrates the suitability of mechanistic modelling approaches to be used as higher tier options for risk assessments. Specifically, IBC-grass can incorporate available individual-level effect data of standardized greenhouse experiments to extrapolate to community-level under various environmental conditions. Thus, future risk assessments can be improved by detecting sensitive scenarios and including worst-case impacts on non-target plant communities.}, language = {en} } @misc{JeltschGrimmReegetal.2019, author = {Jeltsch, Florian and Grimm, Volker and Reeg, Jette and Schl{\"a}gel, Ulrike E.}, title = {Give chance a chance}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {742}, issn = {1866-8372}, doi = {10.25932/publishup-43532}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-435320}, pages = {19}, year = {2019}, abstract = {A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.}, language = {en} } @article{JeltschGrimmReegetal.2019, author = {Jeltsch, Florian and Grimm, Volker and Reeg, Jette and Schl{\"a}gel, Ulrike E.}, title = {Give chance a chance}, series = {Ecosphere}, volume = {10}, journal = {Ecosphere}, number = {5}, publisher = {ESA}, address = {Ithaca, NY}, issn = {2150-8925}, doi = {10.1002/ecs2.2700}, pages = {19}, year = {2019}, abstract = {A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.}, language = {en} }