TY - JOUR A1 - Allan, Eric A1 - Manning, Pete A1 - Alt, Fabian A1 - Binkenstein, Julia A1 - Blaser, Stefan A1 - Blüthgen, Nico A1 - Böhm, Stefan A1 - Grassein, Fabrice A1 - Hölzel, Norbert A1 - Klaus, Valentin H. A1 - Kleinebecker, Till A1 - Morris, E. Kathryn A1 - Oelmann, Yvonne A1 - Prati, Daniel A1 - Renner, Swen C. A1 - Rillig, Matthias C. A1 - Schaefer, Martin A1 - Schloter, Michael A1 - Schmitt, Barbara A1 - Schöning, Ingo A1 - Schrumpf, Marion A1 - Solly, Emily A1 - Sorkau, Elisabeth A1 - Steckel, Juliane A1 - Steffen-Dewenter, Ingolf A1 - Stempfhuber, Barbara A1 - Tschapka, Marco A1 - Weiner, Christiane N. A1 - Weisser, Wolfgang W. A1 - Werner, Michael A1 - Westphal, Catrin A1 - Wilcke, Wolfgang A1 - Fischer, Markus T1 - Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition JF - Ecology letters N2 - Global change, especially land-use intensification, affects human well-being by impacting the delivery of multiple ecosystem services (multifunctionality). However, whether biodiversity loss is a major component of global change effects on multifunctionality in real-world ecosystems, as in experimental ones, remains unclear. Therefore, we assessed biodiversity, functional composition and 14 ecosystem services on 150 agricultural grasslands differing in land-use intensity. We also introduce five multifunctionality measures in which ecosystem services were weighted according to realistic land-use objectives. We found that indirect land-use effects, i.e. those mediated by biodiversity loss and by changes to functional composition, were as strong as direct effects on average. Their strength varied with land-use objectives and regional context. Biodiversity loss explained indirect effects in a region of intermediate productivity and was most damaging when land-use objectives favoured supporting and cultural services. In contrast, functional composition shifts, towards fast-growing plant species, strongly increased provisioning services in more inherently unproductive grasslands. KW - Biodiversity-ecosystem functioning KW - ecosystem services KW - global change KW - land use KW - multifunctionality Y1 - 2015 U6 - https://doi.org/10.1111/ele.12469 SN - 1461-023X SN - 1461-0248 VL - 18 IS - 8 SP - 834 EP - 843 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Bailleul, Frederic A1 - Grimm, Volker A1 - Chion, Clement A1 - Hammill, Mike T1 - Modeling implications of food resource aggregation on animal migration phenology JF - Ecology and evolution N2 - The distribution of poikilotherms is determined by the thermal structure of the marine environment that they are exposed to. Recent research has indicated that changes in migration phenology of beluga whales in the Arctic are triggered by changes in the thermal structure of the marine environment in their summering area. If sea temperatures reflect the spatial distribution of food resources, then changes in the thermal regime will affect how homogeneous or clumped food is distributed. We explore, by individual-based modelling, the hypothesis that changes in migration phenology are not necessarily or exclusively triggered by changes in food abundance, but also by changes in the spatial aggregation of food. We found that the level of food aggregation can significantly affect the relationship between the timing of the start of migration to the winter grounds and the total prey capture of individuals. Our approach strongly indicates that changes in the spatial distribution of food resources should be considered for understanding and quantitatively predicting changes in the phenology of animal migration. KW - Animal migration KW - food structuring KW - global change KW - individual-based model KW - polar environment Y1 - 2013 U6 - https://doi.org/10.1002/ece3.656 SN - 2045-7758 VL - 3 IS - 8 SP - 2535 EP - 2546 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Binzer, Amrei A1 - Guill, Christian A1 - Rall, Björn C. A1 - Brose, Ulrich T1 - Interactive effects of warming, eutrophication and size structure: impacts on biodiversity and food-web structure JF - Global change biology N2 - Warming and eutrophication are two of the most important global change stressors for natural ecosystems, but their interaction is poorly understood. We used a dynamic model of complex, size-structured food webs to assess interactive effects on diversity and network structure. We found antagonistic impacts: Warming increases diversity in eutrophic systems and decreases it in oligotrophic systems. These effects interact with the community size structure: Communities of similarly sized species such as parasitoid-host systems are stabilized by warming and destabilized by eutrophication, whereas the diversity of size-structured predator-prey networks decreases strongly with warming, but decreases only weakly with eutrophication. Nonrandom extinction risks for generalists and specialists lead to higher connectance in networks without size structure and lower connectance in size-structured communities. Overall, our results unravel interactive impacts of warming and eutrophication and suggest that size structure may serve as an important proxy for predicting the community sensitivity to these global change stressors. KW - complex food webs KW - extinctions KW - generalists KW - global change KW - size structure KW - specialists Y1 - 2016 U6 - https://doi.org/10.1111/gcb.13086 SN - 1354-1013 SN - 1365-2486 VL - 22 SP - 220 EP - 227 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Heger, Tina A1 - Bernard-Verdier, Maud A1 - Gessler, Arthur A1 - Greenwood, Alex D. A1 - Grossart, Hans-Peter A1 - Hilker, Monika A1 - Keinath, Silvia A1 - Kowarik, Ingo A1 - Küffer, Christoph A1 - Marquard, Elisabeth A1 - Mueller, Johannes A1 - Niemeier, Stephanie A1 - Onandia, Gabriela A1 - Petermann, Jana S. A1 - Rillig, Matthias C. A1 - Rodel, Mark-Oliver A1 - Saul, Wolf-Christian A1 - Schittko, Conrad A1 - Tockner, Klement A1 - Joshi, Jasmin Radha A1 - Jeschke, Jonathan M. T1 - Towards an Integrative, Eco-Evolutionary Understanding of Ecological Novelty: Studying and Communicating Interlinked Effects of Global Change JF - Bioscience N2 - Global change has complex eco-evolutionary consequences for organisms and ecosystems, but related concepts (e.g., novel ecosystems) do not cover their full range. Here we propose an umbrella concept of "ecological novelty" comprising (1) a site-specific and (2) an organism-centered, eco-evolutionary perspective. Under this umbrella, complementary options for studying and communicating effects of global change on organisms, ecosystems, and landscapes can be included in a toolbox. This allows researchers to address ecological novelty from different perspectives, e.g., by defining it based on (a) categorical or continuous measures, (b) reference conditions related to sites or organisms, and (c) types of human activities. We suggest striving for a descriptive, non-normative usage of the term "ecological novelty" in science. Normative evaluations and decisions about conservation policies or management are important, but require additional societal processes and engagement with multiple stakeholders. KW - Anthropocene KW - eco-evolutionary experience KW - global change KW - novel ecosystems KW - shifting baselines Y1 - 2019 U6 - https://doi.org/10.1093/biosci/biz095 SN - 0006-3568 SN - 1525-3244 VL - 69 IS - 11 SP - 888 EP - 899 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Kissling, W. D. A1 - Dormann, Carsten F. A1 - Groeneveld, Juergen A1 - Hickler, Thomas A1 - Kühn, Ingolf A1 - McInerny, Greg J. A1 - Montoya, Jose M. A1 - Römermann, Christine A1 - Schiffers, Katja A1 - Schurr, Frank Martin A1 - Singer, Alexander A1 - Svenning, Jens-Christian A1 - Zimmermann, Niklaus E. A1 - O'Hara, Robert B. T1 - Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents JF - Journal of biogeography N2 - Aim Biotic interactions within guilds or across trophic levels have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of species interaction distribution models (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co-occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non-stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio-temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co-occurrence datasets across large-scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio-temporal data on biotic interactions in multispecies communities. KW - Community ecology KW - ecological networks KW - global change KW - guild assembly KW - multidimensional complexity KW - niche theory KW - prediction KW - species distribution model KW - species interactions KW - trait-based community modules Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2011.02663.x SN - 0305-0270 VL - 39 IS - 12 SP - 2163 EP - 2178 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Koussoroplis, Apostolos-Manuel A1 - Pincebourde, Sylvain A1 - Wacker, Alexander T1 - Understanding and predicting physiological performance of organisms in fluctuating and multifactorial environments JF - Ecological monographs : a publication of the Ecological Society of America. N2 - Understanding how variance in environmental factors affects physiological performance, population growth, and persistence is central in ecology. Despite recent interest in the effects of variance in single biological drivers, such as temperature, we have lacked a comprehensive framework for predicting how the variances and covariances between multiple environmental factors will affect physiological rates. Here, we integrate current theory on variance effects with co-limitation theory into a single unified conceptual framework that has general applicability. We show how the framework can be applied (1) to generate mathematically tractable predictions of the physiological effects of multiple fluctuating co-limiting factors, (2) to understand how each co-limiting factor contributes to these effects, and (3) to detect mechanisms such as acclimation or physiological stress when they are at play. We show that the statistical covariance of co-limiting factors, which has not been considered before, can be a strong driver of physiological performance in various ecological contexts. Our framework can provide powerful insights on how the global change-induced shifts in multiple environmental factors affect the physiological performance of organisms. KW - co-limitation KW - covariance KW - eco-physiology KW - feeding rate KW - global change KW - multiple stressors KW - nonlinear averaging KW - nutrients KW - scale transition KW - temperature KW - temporal ecology KW - variance Y1 - 2017 U6 - https://doi.org/10.1002/ecm.1247 SN - 0012-9615 SN - 1557-7015 VL - 87 SP - 178 EP - 197 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Kürschner, Tobias A1 - Scherer, Cédric A1 - Radchuk, Viktoriia A1 - Blaum, Niels A1 - Kramer-Schadt, Stephanie T1 - Movement can mediate temporal mismatches between resource availability and biological events in host-pathogen interactions JF - Ecology and evolution N2 - Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species' populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host-pathogen systems. We adapted an established individual-based model of host-pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host's explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life-history events affect host-pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts' biological events. However, a temporal mismatch reduced host-pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat-dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host-pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change. KW - classical swine fever KW - dynamic landscapes KW - global change KW - host– pathogen dynamics KW - individual‐ based model KW - movement ecology Y1 - 2021 U6 - https://doi.org/10.1002/ece3.7478 SN - 2045-7758 VL - 11 IS - 10 SP - 5728 EP - 5741 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Marion, Glenn A1 - McInerny, Greg J. A1 - Pagel, Jörn A1 - Catterall, Stephen A1 - Cook, Alex R. A1 - Hartig, Florian A1 - O&rsquo, A1 - Hara, Robert B. T1 - Parameter and uncertainty estimation for process-oriented population and distribution models: data, statistics and the niche JF - JOURNAL OF BIOGEOGRAPHY N2 - The spatial distribution of a species is determined by dynamic processes such as reproduction, mortality and dispersal. Conventional static species distribution models (SDMs) do not incorporate these processes explicitly. This limits their applicability, particularly for non-equilibrium situations such as invasions or climate change. In this paper we show how dynamic SDMs can be formulated and fitted to data within a Bayesian framework. Our focus is on discrete state-space Markov process models which provide a flexible framework to account for stochasticity in key demographic processes, including dispersal, growth and competition. We show how to construct likelihood functions for such models (both discrete and continuous time versions) and how these can be combined with suitable observation models to conduct Bayesian parameter inference using computational techniques such as Markov chain Monte Carlo. We illustrate the current state-of-the-art with three contrasting examples using both simulated and empirical data. The use of simulated data allows the robustness of the methods to be tested with respect to deficiencies in both data and model. These examples show how mechanistic understanding of the processes that determine distribution and abundance can be combined with different sources of information at a range of spatial and temporal scales. Application of such techniques will enable more reliable inference and projections, e.g. under future climate change scenarios than is possible with purely correlative approaches. Conversely, confronting such process-oriented niche models with abundance and distribution data will test current understanding and may ultimately feedback to improve underlying ecological theory. KW - Bayesian inference KW - demography KW - dispersal KW - dynamic models KW - dynamic range models KW - establishment KW - global change KW - niche models KW - species distribution models Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2012.02772.x SN - 0305-0270 SN - 1365-2699 VL - 39 IS - 12 SP - 2225 EP - 2239 PB - WILEY-BLACKWELL CY - HOBOKEN ER - TY - JOUR A1 - Mooij, Wolf M. A1 - Trolle, Dennis A1 - Jeppesen, Erik A1 - Arhonditsis, George B. A1 - Belolipetsky, Pavel V. A1 - Chitamwebwa, Deonatus B. R. A1 - Degermendzhy, Andrey G. A1 - DeAngelis, Donald L. A1 - Domis, Lisette Nicole de Senerpont A1 - Downing, Andrea S. A1 - Elliott, J. Alex A1 - Fragoso Jr, Carlos Ruberto A1 - Gaedke, Ursula A1 - Genova, Svetlana N. A1 - Gulati, Ramesh D. A1 - Håkanson, Lars A1 - Hamilton, David P. A1 - Hipsey, Matthew R. A1 - ‘t Hoen, Jochem A1 - Hülsmann, Stephan A1 - Los, F. Hans A1 - Makler-Pick, Vardit A1 - Petzoldt, Thomas A1 - Prokopkin, Igor G. A1 - Rinke, Karsten A1 - Schep, Sebastiaan A. A1 - Tominaga, Koji A1 - Van Dam, Anne A. A1 - Van Nes, Egbert H. A1 - Wells, Scott A. A1 - Janse, Jan H. T1 - Challenges and opportunities for integrating lake ecosystem modelling approaches JF - Aquatic ecology N2 - A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models. KW - aquatic KW - food web dynamics KW - plankton KW - nutrients KW - spatial KW - lake KW - freshwater KW - marine KW - community KW - population KW - hydrology KW - eutrophication KW - global change KW - climate warming KW - fisheries KW - biodiversity KW - management KW - mitigation KW - adaptive processes KW - non-linear dynamics KW - analysis KW - bifurcation KW - understanding KW - prediction KW - model limitations KW - model integration Y1 - 2010 U6 - https://doi.org/10.1007/s10452-010-9339-3 SN - 1573-5125 SN - 1386-2588 VL - 44 SP - 633 EP - 667 PB - Springer Science + Business Media B.V. CY - Dordrecht ER - TY - JOUR A1 - Pagel, Jörn A1 - Schurr, Frank Martin T1 - Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics JF - Global ecology and biogeography : a journal of macroecology N2 - Aim The study and prediction of speciesenvironment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties. Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation. Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology. KW - Biogeography KW - ecological forecasts KW - global change KW - hierarchical Bayesian statistics KW - long-distance dispersal KW - niche theory KW - process-based model KW - range shifts KW - spatial demography KW - species distribution modelling Y1 - 2012 U6 - https://doi.org/10.1111/j.1466-8238.2011.00663.x SN - 1466-822X VL - 21 IS - 2 SP - 293 EP - 304 PB - Wiley-Blackwell CY - Malden ER -