@article{MillesDammhahnJeltschetal.2022, author = {Milles, Alexander Benedikt and Dammhahn, Melanie and Jeltsch, Florian and Schl{\"a}gel, Ulrike and Grimm, Volker}, title = {Fluctuations in density-dependent selection drive the evolution of a pace-of-life syndrome within and between populations}, series = {The American naturalist : a bi-monthly journal devoted to the advancement and correlation of the biological sciences}, volume = {199}, journal = {The American naturalist : a bi-monthly journal devoted to the advancement and correlation of the biological sciences}, number = {4}, publisher = {Univ. of Chicago Press}, address = {Chicago}, issn = {0003-0147}, doi = {10.1086/718473}, pages = {E124 -- E139}, year = {2022}, abstract = {The pace-of-life syndrome (POLS) hypothesis posits that suites of traits are correlated along a slow-fast continuum owing to life history trade-offs. Despite widespread adoption, environmental conditions driving the emergence of POLS remain unclear. A recently proposed conceptual framework of POLS suggests that a slow-fast continuum should align to fluctuations in density-dependent selection. We tested three key predictions made by this framework with an ecoevolutionary agent-based population model. Selection acted on responsiveness (behavioral trait) to interpatch resource differences and the reproductive investment threshold (life history trait). Across environments with density fluctuations of different magnitudes, we observed the emergence of a common axis of trait covariation between and within populations (i.e., the evolution of a POLS). Slow-type (fast-type) populations with high (low) responsiveness and low (high) reproductive investment threshold were selected at high (low) population densities and less (more) intense and frequent density fluctuations. In support of the predictions, fast-type populations contained a higher degree of variation in traits and were associated with higher intrinsic reproductive rate (r(0)) and higher sensitivity to intraspecific competition (gamma), pointing to a universal trade-off. While our findings support that POLS aligns with density-dependent selection, we discuss possible mechanisms that may lead to alternative evolutionary pathways.}, language = {en} } @article{LeinsGrimmDrechsler2022, author = {Leins, Johannes A. and Grimm, Volker and Drechsler, Martin}, title = {Large-scale PVA modeling of insects in cultivated grasslands}, series = {Ecology and evolution}, volume = {12}, journal = {Ecology and evolution}, number = {7}, publisher = {Wiley}, address = {Hoboken}, issn = {2045-7758}, doi = {10.1002/ece3.9063}, pages = {17}, year = {2022}, abstract = {In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60-year periods (2020-2079) on a fine temporal (daily) and high spatial (250 x 250 m(2)) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.}, language = {en} } @article{LiAbdulkadirSchattenbergetal.2022, author = {Li, Shuang and Abdulkadir, Nafi'u and Schattenberg, Florian and da Rocha, Ulisses Nunes and Grimm, Volker and M{\"u}ller, Susann and Liu, Zishu}, title = {Stabilizing microbial communities by looped mass transfer}, series = {Proceedings of the National Academy of Sciences of the United States of America : PNAS}, volume = {119}, journal = {Proceedings of the National Academy of Sciences of the United States of America : PNAS}, number = {17}, publisher = {National Acad. of Sciences}, address = {Washington}, issn = {0027-8424}, doi = {10.1073/pnas.2117814119}, pages = {11}, year = {2022}, abstract = {Building and changing a microbiome at will and maintaining it over hundreds of generations has so far proven challenging. Despite best efforts, complex microbiomes appear to be susceptible to large stochastic fluctuations. Current capabilities to assemble and control stable complex microbiomes are limited. Here, we propose a looped mass transfer design that stabilizes microbiomes over long periods of time. Five local microbiomes were continuously grown in parallel for over 114 generations and connected by a loop to a regional pool. Mass transfer rates were altered and microbiome dynamics were monitored using quantitative high-throughput flow cytometry and taxonomic sequencing of whole communities and sorted subcommunities. Increased mass transfer rates reduced local and temporal variation in microbiome assembly, did not affect functions, and overcame stochasticity, with all microbiomes exhibiting high constancy and increasing resistance. Mass transfer synchronized the structures of the five local microbiomes and nestedness of certain cell types was eminent. Mass transfer increased cell number and thus decreased net growth rates mu'. Subsets of cells that did not show net growth mu'SCx were rescued by the regional pool R and thus remained part of the microbiome. The loop in mass transfer ensured the survival of cells that would otherwise go extinct, even if they did not grow in all local microbiomes or grew more slowly than the actual dilution rate D would allow. The rescue effect, known from metacommunity theory, was the main stabilizing mechanism leading to synchrony and survival of subcommunities, despite differences in cell physiological properties, including growth rates.}, language = {en} } @article{DrechslerWaetzoldGrimm2022, author = {Drechsler, Martin and W{\"a}tzold, Frank and Grimm, Volker}, title = {The hitchhiker's guide to generic ecological-economic modelling of land-use-based biodiversity conservation policies}, series = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog}, volume = {465}, journal = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0304-3800}, doi = {10.1016/j.ecolmodel.2021.109861}, pages = {22}, year = {2022}, abstract = {Biodiversity loss is a result of interacting ecological and economic factors, and it must be addressed through an analysis of biodiversity conservation policies. Ecological-economic modelling is a helpful approach to this analysis, but it is also challenging since modellers often have a specific disciplinary background and tend to misrepresent either the ecological or economic aspects. Here, we introduce some of the most important concepts from both disciplines, and since the two modelling cultures also differ between the two disciplines, we present an integrated, consistent guide through all the steps of generic ecological-economic modelling, such as formulation of the research question, development of the conceptual model, model parametrisation and analysis, and interpretation of model results. Although we focus on generic models aimed at a general understanding of causes and remedies for biodiversity loss, the concepts and guidance provided here may also help in the modelling of more specific conservation problems. This guide is aimed at the intersection of three disciplines: ecology, economics and mathematical modelling, and addresses readers who have some knowledge in at least one of these disciplines and want to learn about the others to build and analyse generic ecological-economic models. Compared to textbooks, the guide focuses on the practice of modelling rather than lengthy explanations of theoretical concepts. We attempt to demonstrate that generic ecological-economic modelling does not require magical powers and instead is a manageable exercise.}, language = {en} }