TY - JOUR A1 - Noonan, Michael J. A1 - Tucker, Marlee A. A1 - Fleming, Christen H. A1 - Akre, Thomas S. A1 - Alberts, Susan C. A1 - Ali, Abdullahi H. A1 - Altmann, Jeanne A1 - Antunes, Pamela Castro A1 - Belant, Jerrold L. A1 - Beyer, Dean A1 - Blaum, Niels A1 - Boehning-Gaese, Katrin A1 - Cullen Jr, Laury A1 - de Paula, Rogerio Cunha A1 - Dekker, Jasja A1 - Drescher-Lehman, Jonathan A1 - Farwig, Nina A1 - Fichtel, Claudia A1 - Fischer, Christina A1 - Ford, Adam T. A1 - Goheen, Jacob R. A1 - Janssen, Rene A1 - Jeltsch, Florian A1 - Kauffman, Matthew A1 - Kappeler, Peter M. A1 - Koch, Flavia A1 - LaPoint, Scott A1 - Markham, A. Catherine A1 - Medici, Emilia Patricia A1 - Morato, Ronaldo G. A1 - Nathan, Ran A1 - Oliveira-Santos, Luiz Gustavo R. A1 - Olson, Kirk A. A1 - Patterson, Bruce D. A1 - Paviolo, Agustin A1 - Ramalho, Emiliano Estero A1 - Rosner, Sascha A1 - Schabo, Dana G. A1 - Selva, Nuria A1 - Sergiel, Agnieszka A1 - da Silva, Marina Xavier A1 - Spiegel, Orr A1 - Thompson, Peter A1 - Ullmann, Wiebke A1 - Zieba, Filip A1 - Zwijacz-Kozica, Tomasz A1 - Fagan, William F. A1 - Mueller, Thomas A1 - Calabrese, Justin M. T1 - A comprehensive analysis of autocorrelation and bias in home range estimation JF - Ecological monographs : a publication of the Ecological Society of America. N2 - Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area ) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data. KW - animal movement KW - kernel density estimation KW - local convex hull KW - minimum convex polygon KW - range distribution KW - space use KW - telemetry KW - tracking data Y1 - 2018 U6 - https://doi.org/10.1002/ecm.1344 SN - 0012-9615 SN - 1557-7015 VL - 89 IS - 2 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Teckentrup, Lisa A1 - Grimm, Volker A1 - Kramer-Schadt, Stephanie A1 - Jeltsch, Florian T1 - Community consequences of foraging under fear JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - Non-consumptive effects of predators within ecosystems can alter the behavior of individual prey species, and have cascading effects on other trophic levels. In this context, an understanding of non-consumptive predator effects on the whole prey community is crucial for predicting community structure and composition, hence biodiversity patterns. We used an individual-based, spatially-explicit modelling approach to investigate the consequences of landscapes of fear on prey community metrics. The model spans multiple hierarchical levels from individual home range formation based on food availability and perceived predation risk to consequences on prey community structure and composition. This mechanistic approach allowed us to explore how important factors such as refuge availability and foraging strategy under fear affect prey community metrics. Fear of predators affected prey space use, such as home range formation. These adaptations had broader consequences for the community leading to changes in community structure and composition. The strength of community responses to perceived predation risk was driven by refuge availability in the landscape and the foraging strategy of prey animals. Low refuge availability in the landscape strongly decreased diversity and total biomass of prey communities. Additionally, body mass distributions in prey communities facing high predation risk were shifted towards small prey animals. With increasing refuge availability the consequences of non-consumptive predator effects were reduced, diversity and total biomass of the prey community increased. Prey foraging strategies affected community composition. Under medium refuge availability, risk-averse prey communities consisted of many small animals while risk-taking prey communities showed a more even body mass distribution. Our findings reveal that non-consumptive predator effects can have important implications for prey community diversity and should therefore be considered in the context of conservation and nature management. KW - Predator-prey interactions KW - Individual-based model KW - Landscape of fear KW - Home range KW - Biodiversity KW - Foraging Y1 - 2018 U6 - https://doi.org/10.1016/j.ecolmodel.2018.05.015 SN - 0304-3800 SN - 1872-7026 VL - 383 SP - 80 EP - 90 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Romero-Mujalli, Daniel A1 - Jeltsch, Florian A1 - Tiedemann, Ralph T1 - Individual-based modeling of eco-evolutionary dynamics BT - state of the art and future directions JF - Regional environmental change N2 - A challenge for eco-evolutionary research is to better understand the effect of climate and landscape changes on species and their distribution. Populations of species can respond to changes in their environment through local genetic adaptation or plasticity, dispersal, or local extinction. The individual-based modeling (IBM) approach has been repeatedly applied to assess organismic responses to environmental changes. IBMs simulate emerging adaptive behaviors from the basic entities upon which both ecological and evolutionary mechanisms act. The objective of this review is to summarize the state of the art of eco-evolutionary IBMs and to explore to what degree they already address the key responses of organisms to environmental change. In this, we identify promising approaches and potential knowledge gaps in the implementation of eco-evolutionary mechanisms to motivate future research. Using mainly the ISI Web of Science, we reveal that most of the progress in eco-evolutionary IBMs in the last decades was achieved for genetic adaptation to novel local environmental conditions. There is, however, not a single eco-evolutionary IBM addressing the three potential adaptive responses simultaneously. Additionally, IBMs implementing adaptive phenotypic plasticity are rare. Most commonly, plasticity was implemented as random noise or reaction norms. Our review further identifies a current lack of models where plasticity is an evolving trait. Future eco-evolutionary models should consider dispersal and plasticity as evolving traits with their associated costs and benefits. Such an integrated approach could help to identify conditions promoting population persistence depending on the life history strategy of organisms and the environment they experience. KW - Modeling KW - Individual-based models KW - Ecology KW - Evolution KW - Eco-evolutionary dynamics Y1 - 2018 U6 - https://doi.org/10.1007/s10113-018-1406-7 SN - 1436-3798 SN - 1436-378X VL - 19 IS - 1 SP - 1 EP - 12 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Crawford, Michael A1 - Jeltsch, Florian A1 - May, Felix A1 - Grimm, Volker A1 - Schlägel, Ulrike E. T1 - Intraspecific trait variation increases species diversity in a trait-based grassland model JF - Oikos N2 - Intraspecific trait variation (ITV) is thought to play a significant role in community assembly, but the magnitude and direction of its influence are not well understood. Although it may be critical to better explain population persistence, species interactions, and therefore biodiversity patterns, manipulating ITV in experiments is challenging. We therefore incorporated ITV into a trait‐ and individual‐based model of grassland community assembly by adding variation to the plants’ functional traits, which then drive life‐history tradeoffs. Varying the amount of ITV in the simulation, we examine its influence on pairwise‐coexistence and then on the species diversity in communities of different initial sizes. We find that ITV increases the ability of the weakest species to invade most, but that this effect does not scale to the community level, where the primary effect of ITV is to increase the persistence and abundance of the competitively‐average species. Diversity of the initial community is also of critical importance in determining ITV's efficacy; above a threshold of interspecific diversity, ITV does not increase diversity further. For communities below this threshold, ITV mainly helps to increase diversity in those communities that would otherwise be low‐diversity. These findings suggest that ITV actively maintains diversity by helping the species on the margins of persistence, but mostly in habitats of relatively low alpha and beta diversity. KW - community assembly KW - individual-based model KW - intraspecific trait variation Y1 - 2018 U6 - https://doi.org/10.1111/oik.05567 SN - 0030-1299 SN - 1600-0706 VL - 128 IS - 3 SP - 441 EP - 455 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Tucker, Marlee A. A1 - Boehning-Gaese, Katrin A1 - Fagan, William F. A1 - Fryxell, John M. A1 - Van Moorter, Bram A1 - Alberts, Susan C. A1 - Ali, Abdullahi H. A1 - Allen, Andrew M. A1 - Attias, Nina A1 - Avgar, Tal A1 - Bartlam-Brooks, Hattie A1 - Bayarbaatar, Buuveibaatar A1 - Belant, Jerrold L. A1 - Bertassoni, Alessandra A1 - Beyer, Dean A1 - Bidner, Laura A1 - van Beest, Floris M. A1 - Blake, Stephen A1 - Blaum, Niels A1 - Bracis, Chloe A1 - Brown, Danielle A1 - de Bruyn, P. J. Nico A1 - Cagnacci, Francesca A1 - Calabrese, Justin M. A1 - Camilo-Alves, Constanca A1 - Chamaille-Jammes, Simon A1 - Chiaradia, Andre A1 - Davidson, Sarah C. A1 - Dennis, Todd A1 - DeStefano, Stephen A1 - Diefenbach, Duane A1 - Douglas-Hamilton, Iain A1 - Fennessy, Julian A1 - Fichtel, Claudia A1 - Fiedler, Wolfgang A1 - Fischer, Christina A1 - Fischhoff, Ilya A1 - Fleming, Christen H. A1 - Ford, Adam T. A1 - Fritz, Susanne A. A1 - Gehr, Benedikt A1 - Goheen, Jacob R. A1 - Gurarie, Eliezer A1 - Hebblewhite, Mark A1 - Heurich, Marco A1 - Hewison, A. J. Mark A1 - Hof, Christian A1 - Hurme, Edward A1 - Isbell, Lynne A. A1 - Janssen, Rene A1 - Jeltsch, Florian A1 - Kaczensky, Petra A1 - Kane, Adam A1 - Kappeler, Peter M. A1 - Kauffman, Matthew A1 - Kays, Roland A1 - Kimuyu, Duncan A1 - Koch, Flavia A1 - Kranstauber, Bart A1 - LaPoint, Scott A1 - Leimgruber, Peter A1 - Linnell, John D. C. A1 - Lopez-Lopez, Pascual A1 - Markham, A. Catherine A1 - Mattisson, Jenny A1 - Medici, Emilia Patricia A1 - Mellone, Ugo A1 - Merrill, Evelyn A1 - Mourao, Guilherme de Miranda A1 - Morato, Ronaldo G. A1 - Morellet, Nicolas A1 - Morrison, Thomas A. A1 - Diaz-Munoz, Samuel L. A1 - Mysterud, Atle A1 - Nandintsetseg, Dejid A1 - Nathan, Ran A1 - Niamir, Aidin A1 - Odden, John A1 - Oliveira-Santos, Luiz Gustavo R. A1 - Olson, Kirk A. A1 - Patterson, Bruce D. A1 - de Paula, Rogerio Cunha A1 - Pedrotti, Luca A1 - Reineking, Bjorn A1 - Rimmler, Martin A1 - Rogers, Tracey L. A1 - Rolandsen, Christer Moe A1 - Rosenberry, Christopher S. A1 - Rubenstein, Daniel I. A1 - Safi, Kamran A1 - Said, Sonia A1 - Sapir, Nir A1 - Sawyer, Hall A1 - Schmidt, Niels Martin A1 - Selva, Nuria A1 - Sergiel, Agnieszka A1 - Shiilegdamba, Enkhtuvshin A1 - Silva, Joao Paulo A1 - Singh, Navinder A1 - Solberg, Erling J. A1 - Spiegel, Orr A1 - Strand, Olav A1 - Sundaresan, Siva A1 - Ullmann, Wiebke A1 - Voigt, Ulrich A1 - Wall, Jake A1 - Wattles, David A1 - Wikelski, Martin A1 - Wilmers, Christopher C. A1 - Wilson, John W. A1 - Wittemyer, George A1 - Zieba, Filip A1 - Zwijacz-Kozica, Tomasz A1 - Mueller, Thomas T1 - Moving in the Anthropocene BT - global reductions in terrestrial mammalian movements JF - Science N2 - Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission. Y1 - 2018 U6 - https://doi.org/10.1126/science.aam9712 SN - 0036-8075 SN - 1095-9203 VL - 359 IS - 6374 SP - 466 EP - 469 PB - American Assoc. for the Advancement of Science CY - Washington ER - TY - JOUR A1 - Schibalski, Anett A1 - Körner, Katrin A1 - Maier, Martin A1 - Jeltsch, Florian A1 - Schröder, Boris T1 - Novel model coupling approach for resilience analysis of coastal plant communities JF - Ecological applications : a publication of the Ecological Society of America N2 - Resilience is a major research focus covering a wide range of topics from biodiversity conservation to ecosystem (service) management. Model simulations can assess the resilience of, for example, plant species, measured as the return time to conditions prior to a disturbance. This requires process-based models (PBM) that implement relevant processes such as regeneration and reproduction and thus successfully reproduce transient dynamics after disturbances. Such models are often complex and thus limited to either short-term or small-scale applications, whereas many research questions require species predictions across larger spatial and temporal scales. We suggest a framework to couple a PBM and a statistical species distribution model (SDM), which transfers the results of a resilience analysis by the PBM to SDM predictions. The resulting hybrid model combines the advantages of both approaches: the convenient applicability of SDMs and the relevant process detail of PBMs in abrupt environmental change situations. First, we simulate dynamic responses of species communities to a disturbance event with a PBM. We aggregate the response behavior in two resilience metrics: return time and amplitude of the response peak. These metrics are then used to complement long-term SDM projections with dynamic short-term responses to disturbance. To illustrate our framework, we investigate the effect of abrupt short-term groundwater level and salinity changes on coastal vegetation at the German Baltic Sea. We found two example species to be largely resilient, and, consequently, modifications of SDM predictions consisted mostly of smoothing out peaks in the occurrence probability that were not confirmed by the PBM. Discrepancies between SDM- and PBM-predicted species responses were caused by community dynamics simulated in the PBM and absent from the SDM. Although demonstrated with boosted regression trees (SDM) and an existing individual-based model, IBC-grass (PBM), our flexible framework can easily be applied to other PBM and SDM types, as well as other definitions of short-term disturbances or long-term trends of environmental change. Thus, our framework allows accounting for biological feedbacks in the response to short- and long-term environmental changes as a major advancement in predictive vegetation modeling. KW - Baltic Sea KW - hybrid model KW - Lolium perenne KW - model coupling KW - Scirpus maritimus KW - transient dynamics Y1 - 2018 U6 - https://doi.org/10.1002/eap.1758 SN - 1051-0761 SN - 1939-5582 VL - 28 IS - 6 SP - 1640 EP - 1654 PB - Wiley CY - Hoboken ER - TY - GEN A1 - Synodinos, Alexios D. A1 - Eldridge, David A1 - Geißler, Katja A1 - Jeltsch, Florian A1 - Lohmann, Dirk A1 - Midgley, Guy A1 - Blaum, Niels T1 - Remotely sensed canopy height reveals three pantropical ecosystem states BT - a comment T2 - Ecology : a publication of the Ecological Society of America Y1 - 2017 U6 - https://doi.org/10.1002/ecy.1997 SN - 0012-9658 SN - 1939-9170 VL - 99 IS - 1 SP - 231 EP - 234 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Reeg, Jette A1 - Heine, Simon A1 - Mihan, Christine A1 - McGee, Sean A1 - Preuss, Thomas G. A1 - Jeltsch, Florian T1 - Simulation of herbicide impacts on a plant community BT - comparing model predictions of the plant community model IBC-grass to empirical data JF - Environmental Sciences Europe N2 - 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. KW - Plant community model KW - Non-target terrestrial plants KW - Community-level effects KW - Herbicide risk assessment KW - Individual-based modeling Y1 - 2018 U6 - https://doi.org/10.1186/s12302-018-0174-9 SN - 2190-4715 SN - 2190-4707 VL - 30 IS - 44 PB - Springer CY - Berlin und Heidelberg ER - TY - JOUR A1 - Synodinos, Alexis D. A1 - Tietjen, Britta A1 - Lohmann, Dirk A1 - Jeltsch, Florian T1 - The impact of inter-annual rainfall variability on African savannas changes with mean rainfall JF - Journal of theoretical biology N2 - Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520–780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580–780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during ‘dry’ extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability. KW - Rainfall variability KW - Savanna-grassland bistability KW - Stochastic differential equations KW - Coexistence mechanisms KW - Fire Y1 - 2017 U6 - https://doi.org/10.1016/j.jtbi.2017.10.019 SN - 0022-5193 SN - 1095-8541 VL - 437 SP - 92 EP - 100 PB - Elsevier Ltd. CY - London ER -