TY - JOUR A1 - Sarmento, Juliano Sarmento A1 - Jeltsch, Florian A1 - Thuiller, Wilfried A1 - Higgins, Steven A1 - Midgley, Guy F. A1 - Rebelo, Anthony G. A1 - Rouget, Mathieu A1 - Schurr, Frank Martin T1 - Impacts of past habitat loss and future climate change on the range dynamics of South African Proteaceae JF - Diversity & distributions : a journal of biological invasions and biodiversity N2 - Aim To assess how habitat loss and climate change interact in affecting the range dynamics of species and to quantify how predicted range dynamics depend on demographic properties of species and the severity of environmental change. Location South African Cape Floristic Region. Methods We use data-driven demographic models to assess the impacts of past habitat loss and future climate change on range size, range filing and abundances of eight species of woody plants (Proteaceae). The species-specific models employ a hybrid approach that simulates population dynamics and long-distance dispersal on top of expected spatio-temporal dynamics of suitable habitat. Results Climate change was mainly predicted to reduce range size and range filling (because of a combination of strong habitat shifts with low migration ability). In contrast, habitat loss mostly decreased mean local abundance. For most species and response measures, the combination of habitat loss and climate change had the most severe effect. Yet, this combined effect was mostly smaller than expected from adding or multiplying effects of the individual environmental drivers. This seems to be because climate change shifts suitable habitats to regions less affected by habitat loss. Interspecific variation in range size responses depended mostly on the severity of environmental change, whereas responses in range filling and local abundance depended mostly on demographic properties of species. While most surviving populations concentrated in areas that remain climatically suitable, refugia for multiple species were overestimated by simply overlying habitat models and ignoring demography. Main conclusions Demographic models of range dynamics can simultaneously predict the response of range size, abundance and range filling to multiple drivers of environmental change. Demographic knowledge is particularly needed to predict abundance responses and to identify areas that can serve as biodiversity refugia under climate change. These findings highlight the need for data-driven, demographic assessments in conservation biogeography. KW - biodiversity refugia KW - CFR Proteaceae KW - climate change KW - demographic properties KW - habitat loss KW - local abundances KW - process-based range models KW - range filling KW - range size KW - species distribution models Y1 - 2013 U6 - https://doi.org/10.1111/ddi.12011 SN - 1366-9516 VL - 19 IS - 4 SP - 363 EP - 376 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Schurr, Frank Martin A1 - Pagel, Jörn A1 - Sarmento, Juliano Sarmento A1 - Groeneveld, Juergen A1 - Bykova, Olga A1 - O'Hara, Robert B. A1 - Hartig, Florian A1 - Kissling, W. Daniel A1 - Linder, H. Peter A1 - Midgley, Guy F. A1 - Schröder-Esselbach, Boris A1 - Singer, Alexander A1 - Zimmermann, Niklaus E. T1 - How to understand species' niches and range dynamics: a demographic research agenda for biogeography JF - Journal of biogeography N2 - Range dynamics causes mismatches between a species geographical distribution and the set of suitable environments in which population growth is positive (the Hutchinsonian niche). This is because sourcesink population dynamics cause species to occupy unsuitable environments, and because environmental change creates non-equilibrium situations in which species may be absent from suitable environments (due to migration limitation) or present in unsuitable environments that were previously suitable (due to time-delayed extinction). Because correlative species distribution models do not account for these processes, they are likely to produce biased niche estimates and biased forecasts of future range dynamics. Recently developed dynamic range models (DRMs) overcome this problem: they statistically estimate both range dynamics and the underlying environmental response of demographic rates from species distribution data. This process-based statistical approach qualitatively advances biogeographical analyses. Yet, the application of DRMs to a broad range of species and study systems requires substantial research efforts in statistical modelling, empirical data collection and ecological theory. Here we review current and potential contributions of these fields to a demographic understanding of niches and range dynamics. Our review serves to formulate a demographic research agenda that entails: (1) advances in incorporating process-based models of demographic responses and range dynamics into a statistical framework, (2) systematic collection of data on temporal changes in distribution and abundance and on the response of demographic rates to environmental variation, and (3) improved theoretical understanding of the scaling of demographic rates and the dynamics of spatially coupled populations. This demographic research agenda is challenging but necessary for improved comprehension and quantification of niches and range dynamics. It also forms the basis for understanding how niches and range dynamics are shaped by evolutionary dynamics and biotic interactions. Ultimately, the demographic research agenda should lead to deeper integration of biogeography with empirical and theoretical ecology. KW - Biodiversity monitoring KW - climate change KW - ecological forecasts KW - ecological niche modelling KW - ecological theory KW - geographical range shifts KW - global environmental change KW - mechanistic models KW - migration KW - process-based statistics Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2012.02737.x SN - 0305-0270 VL - 39 IS - 12 SP - 2146 EP - 2162 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Sarmento, Juliano Sarmento A1 - Bond, William J. A1 - Midgley, Guy F. A1 - Rebelo, Anthony G. A1 - Thuiller, Wilfried A1 - Schurr, Frank Martin T1 - Effects of harvesting flowers from shrubs on the persistence and abundance of wild shrub populations at multiple spatial extents JF - Conservation biology : the journal of the Society for Conservation Biology N2 - Wildflower harvesting is an economically important activity of which the ecological effects are poorly understood. We assessed how harvesting of flowers affects shrub persistence and abundance at multiple spatial extents. To this end, we built a process-based model to examine the mean persistence and abundance of wild shrubs whose flowers are subject to harvest (serotinous Proteaceae in the South African Cape Floristic Region). First, we conducted a general sensitivity analysis of how harvesting affects persistence and abundance at nested spatial extents. For most spatial extents and combinations of demographic parameters, persistence and abundance of flowering shrubs decreased abruptly once harvesting rate exceeded a certain threshold. At larger extents, metapopulations supported higher harvesting rates before their persistence and abundance decreased, but persistence and abundance also decreased more abruptly due to harvesting than at smaller extents. This threshold rate of harvest varied with species' dispersal ability, maximum reproductive rate, adult mortality, probability of extirpation or local extinction, strength of Allee effects, and carrying capacity. Moreover, spatial extent interacted with Allee effects and probability of extirpation because both these demographic properties affected the response of local populations to harvesting more strongly than they affected the response of metapopulations. Subsequently, we simulated the effects of harvesting on three Cape Floristic Region Proteaceae species and found that these species reacted differently to harvesting, but their persistence and abundance decreased at low rates of harvest. Our estimates of harvesting rates at maximum sustainable yield differed from those of previous investigations, perhaps because researchers used different estimates of demographic parameters, models of population dynamics, and spatial extent than we did. Good demographic knowledge and careful identification of the spatial extent of interest increases confidence in assessments and monitoring of the effects of harvesting. Our general sensitivity analysis improved understanding of harvesting effects on metapopulation dynamics and allowed qualitative assessment of the probability of extirpation of poorly studied species. KW - Allee effects KW - metapopulation dynamics KW - process-based models KW - serotinous Proteaceae KW - South African Cape Floristic Region KW - spatial scales KW - threshold behavior Y1 - 2011 U6 - https://doi.org/10.1111/j.1523-1739.2010.01628.x SN - 0888-8892 VL - 25 IS - 1 SP - 73 EP - 84 PB - Wiley-Blackwell CY - Malden ER - TY - THES A1 - Cabral, Juliano Sarmento T1 - Demographic processes determining the range dynamics of plant species, and their consequences for biodiversity maintenance in the face of environmental change T1 - Einfluss demographischer Prozesse auf die Verbreitungsmuster von Pflanzenarten und ihre Konsequenzen für den Schutz der Biodiversität im Angesicht von Umweltwandel N2 - The present thesis aims to introduce process-based model for species range dynamics that can be fitted to abundance data. For this purpose, the well-studied Proteaceae species of the South African Cape Floristic Region (CFR) offer a great data set to fit process-based models. These species are subject to wildflower harvesting and environmental threats like habitat loss and climate change. The general introduction of this thesis presents shortly the available models for species distribution modelling. Subsequently, it presents the feasibility of process-based modelling. Finally, it introduces the study system as well as the objectives and layout. In Chapter 1, I present the process-based model for range dynamics and a statistical framework to fit it to abundance distribution data. The model has a spatially-explicit demographic submodel (describing dispersal, reproduction, mortality and local extinction) and an observation submodel (describing imperfect detection of individuals). The demographic submodel links species-specific habitat models describing the suitable habitat and process-based demographic models that consider local dynamics and anemochoric seed dispersal between populations. After testing the fitting framework with simulated data, I applied it to eight Proteaceae species with different demographic properties. Moreover, I assess the role of two other demographic mechanisms: positive (Allee effects) and negative density-dependence. Results indicate that Allee effects and overcompensatory local dynamics (including chaotic behaviour) seem to be important for several species. Most parameter estimates quantitatively agreed with independent data. Hence, the presented approach seemed to suit the demand of investigating non-equilibrium scenarios involving wildflower harvesting (Chapter 2) and environmental change (Chapter 3). The Chapter 2 addresses the impacts of wildflower harvesting. The chapter includes a sensitivity analysis over multiple spatial scales and demographic properties (dispersal ability, strength of Allee effects, maximum reproductive rate, adult mortality, local extinction probability and carrying capacity). Subsequently, harvesting effects are investigated on real case study species. Plant response to harvesting showed abrupt threshold behavior. Species with short-distance seed dispersal, strong Allee effects, low maximum reproductive rate, high mortality and high local extinction are most affected by harvesting. Larger spatial scales benefit species response, but the thresholds become sharper. The three case study species supported very low to moderate harvesting rates. Summarizing, demographic knowledge about the study system and careful identification of the spatial scale of interest should guide harvesting assessments and conservation of exploited species. The sensitivity analysis’ results can be used to qualitatively assess harvesting impacts for poorly studied species. I investigated in Chapter 3 the consequences of past habitat loss, future climate change and their interaction on plant response. I use the species-specific estimates of the best model describing local dynamics obtained in Chapter 1. Both habitat loss and climate change had strong negative impacts on species dynamics. Climate change affected mainly range size and range filling due to habitat reductions and shifts combined with low colonization. Habitat loss affected mostly local abundances. The scenario with both habitat loss and climate change was the worst for most species. However, this impact was better than expected by simple summing of separate effects of habitat loss and climate change. This is explained by shifting ranges to areas less affected by humans. Range size response was well predicted by the strength of environmental change, whereas range filling and local abundance responses were better explained by demographic properties. Hence, risk assessments under global change should consider demographic properties. Most surviving populations were restricted to refugia, serving as key conservation focus.The findings obtained for the study system as well as the advantages, limitations and potentials of the model presented here are further discussed in the General Discussion. In summary, the results indicate that 1) process-based demographic models for range dynamics can be fitted to data; 2) demographic processes improve species distribution models; 3) different species are subject to different processes and respond differently to environmental change and exploitation; 4) density regulation type and Allee effects should be considered when investigating range dynamics of species; 5) the consequences of wildflower harvesting, habitat loss and climate change could be disastrous for some species, but impacts vary depending on demographic properties; 6) wildflower harvesting impacts varies over spatial scale; 7) The effects of habitat loss and climate change are not always additive. N2 - Das Ziel dieser Studie bestand daher darin, prozess-basierte Modelle zu entwickeln, die mit Daten zur Abundanz von Arten parametrisiert werden können. Die außergewöhnlich gut erforschten Proteaceen der südafrikanischen Kapregion (CFR), für die ein umfangreicher Datensatz zur Verfügung steht, stellen ein sehr geeignetes Untersuchungssystem zur Erstellung derartiger prozess-basierter Modelle dar. In Kapitel 1 beschreibe ich ein prozess-basiertes Modell für die Verbreitungsdynamik sowie die Methoden zur Parametrisierung des Modells mit Daten zu Abundanzverteilungen. Das Modell umfasst ein räumlich-explizites demographisches Modul und ein Beobachtungsmodul. Das demographische Modul verbindet artspezifische Habitatmodelle, die das geeignete Habitat beschreiben, und prozess-basierte demographische Modelle, die die lokale Dynamik und die Windausbreitung von Samen umfassen. Nach der Überprüfung der Parametrisierungs¬methoden mit simulierten Daten, wende ich die Modelle auf acht Proteaceenarten mit unterschiedlichen demographischen Eigenschaften an. Außerdem untersuche ich die Rolle von positiver (Allee-Effekte) und negativer Dichte-Abhängigkeit. Die Ergebnisse zeigen, dass Allee-Effekte und überkompensatorische Dynamik für viele Arten tatsächlich eine Rolle spielen. Der Großteil der geschätzten Parameter stimmt quantitativ mit unabhängigen Daten und beschreibt erfolgreich, wie die Abundanzverteilung aus der Bewegung und Interaktion der Individuen entsteht. Die vorgestellten Methoden scheinen daher zur Untersuchung von Ungleichgewichtsszenarien geeignet, die die Ernte von Infloreszenzen in Wildbeständen (Kapitel 2) und Umweltwandel (Kapitel 3) einschließen. In Kapitel 2 untersuche ich die Effekte der Ernte von Infloreszenzen in Wildbeständen. Das Kapitel beinhaltet eine Sensitivitätsanalyse über mehrere räumliche Skalen sowie demographische Eigenschaften. Darauf folgend wurden die Effekte der Ernte anhand von drei realen Arten untersucht. Die Reaktion der Pflanzen auf die Ernte zeigte ein Verhalten mit abrupten Schwellenwerten. Die durch die Ernte am stärksten gefährdeten Arten zeichneten sich durch kurze Samenausbreitungsdistanzen, starke Allee Effekte, geringe maximale Reproduktionsrate, hohe Mortalität und hohe lokale Aussterbewahrscheinlichkeit aus. Die Betrachtung größerer räumlicher Skalen wirkte sich trotz schärferer Grenzwerte positiv auf die Reaktion der Arten aus. Die drei untersuchten realen Arten konnten sehr geringe bis mittlere nachhaltige Ernteraten ertragen. Zusammenfassend lässt sich sagen, dass Kenntnisse über die Demographie des Untersuchungssystems und die umsichtige Identifizierung der zu betrachtenden räumlichen Skala zu einer besseren Einschätzung der Ernteintensität und der Naturschutzziele führen sollten. In Kapitel 3 wird die Reaktion der Arten auf vergangene Habitatverluste und zukünftigen Klimawandel sowie die Interaktion der beiden untersucht. Der Klimawandel wirkte sich dabei vornehmlich negativ auf die Größe des Verbreitungsgebiets und die Ausnutzung des potentiellen Habitats (‚Range Filling’) aus, wobei es zu einer Verschiebung des Habitats ohne erfolgreiche Kolonisierung kam. Der Habitatverlust reduzierte vor allem die lokalen Abundanzen. Die meisten Arten wurden vor allem durch das Szenario mit beiden Klimawandel und Habitatsverlust stark beeinträchtigt. Der negative Effekt war allerdings geringer als nach einer einfachen Aufsummierung der Einzeleffekte zu erwarten wäre. Dies erklärt sich aus einer Verschiebung des Verbreitungsgebiets der Arten in Regionen, in denen es in der Vergangenheit zu geringeren Habitatverlusten kam. Die Größe des Verbreitungsgebiets wurde am besten durch die Stärke des Umweltwandels vorhergesagt, wogegen das Range Filling und die lokalen Abundanzen hauptsächlich von den demographischen Eigenschaften abhingen. Aus diesen Ergebnissen lässt sich schließen, dass Abschätzungen des Aussterbensrisikos unter Umweltwandel demographische Eigenschaften einbeziehen sollten. Die meisten überlebenden Populationen waren auf Refugien reduziert, die im Fokus der Naturschutzmaßnahmen stehen sollten. Zusammenfassend zeigen die Ergebnisse, dass 1) prozess-basierte demographische Modelle für die Verbreitungsdynamik von Arten mit Daten parametrisierbar sind; 2) die Einbeziehung demographischer Prozesse die Modelle für die Verbreitung von Arten verbessert; 3) verschiedene Arten von unterschiedlichen Prozessen beeinflusst werden und unterschiedlich auf Umweltwandel und Beerntung reagieren; 4) Dichteregulierung und Allee-Effekte bei der Untersuchung der Verbreitungsdynamik von Arten berücksichtigt werden sollten; 5) die Ernte von Infloreszenzen in Wildbeständen, sowie Habitatverlust und Klimawandel für manche Arten katastrophale Folgen haben können, deren Effekte aber von den demographischen Eigenschaften abhängen; 6) der Einfluss der Beerntung in Abhängigkeit von der betrachteten räumlichen Skala variiert; 7) die Effekte von Habitatverlust und Klimawandel nicht additiv sind. KW - Mechanistische Modelle KW - Verbreitungsdynamik von Arten KW - Proteaceen KW - Globalwandel KW - Ernte von Wildebeständen KW - Mechanistic models KW - species distribution models KW - Proteaceae KW - global change KW - harvesting Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-41188 ER - TY - JOUR A1 - Cabral, Juliano Sarmento A1 - Valente, Luis A1 - Hartig, Florian T1 - Mechanistic simulation models in macroecology and biogeography BT - state-of-art and prospects JF - Ecography : pattern and diversity in ecology N2 - Macroecology and biogeography are concerned with understanding biodiversity patterns across space and time. In the past, the two disciplines have addressed this question mainly with correlative approaches, despite frequent calls for more mechanistic explanations. Recent advances in computational power, theoretical understanding, and statistical tools are, however, currently facilitating the development of more system-oriented, mechanistic models. We review these models, identify different model types and theoretical frameworks, compare their processes and properties, and summarize emergent findings. We show that ecological (physiology, demographics, dispersal, biotic interactions) and evolutionary processes, as well as environmental and human-induced drivers, are increasingly modelled mechanistically; and that new insights into biodiversity dynamics emerge from these models. Yet, substantial challenges still lie ahead for this young research field. Among these, we identify scaling, calibration, validation, and balancing complexity as pressing issues. Moreover, particular process combinations are still understudied, and so far models tend to be developed for specific applications. Future work should aim at developing more flexible and modular models that not only allow different ecological theories to be expressed and contrasted, but which are also built for tight integration with all macroecological data sources. Moving the field towards such a ‘systems macroecology’ will test and improve our understanding of the causal pathways through which eco-evolutionary processes create diversity patterns across spatial and temporal scales. Y1 - 2016 U6 - https://doi.org/10.1111/ecog.02480 SN - 0906-7590 SN - 1600-0587 VL - 40 IS - 2 SP - 267 EP - 280 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Zurell, Damaris A1 - Berger, Uta A1 - Cabral, Juliano Sarmento A1 - Jeltsch, Florian A1 - Meynard, Christine N. A1 - Muenkemueller, Tamara A1 - Nehrbass, Nana A1 - Pagel, Jörn A1 - Reineking, Bjoern A1 - Schroeder, Boris A1 - Grimm, Volker T1 - The virtual ecologist approach : simulating data and observers N2 - Ecologists carry a well-stocked toolbox with a great variety of sampling methods, statistical analyses and modelling tools, and new methods are constantly appearing. Evaluation and optimisation of these methods is crucial to guide methodological choices. Simulating error-free data or taking high-quality data to qualify methods is common practice. Here, we emphasise the methodology of the 'virtual ecologist' (VE) approach where simulated data and observer models are used to mimic real species and how they are 'virtually' observed. This virtual data is then subjected to statistical analyses and modelling, and the results are evaluated against the 'true' simulated data. The VE approach is an intuitive and powerful evaluation framework that allows a quality assessment of sampling protocols, analyses and modelling tools. It works under controlled conditions as well as under consideration of confounding factors such as animal movement and biased observer behaviour. In this review, we promote the approach as a rigorous research tool, and demonstrate its capabilities and practical relevance. We explore past uses of VE in different ecological research fields, where it mainly has been used to test and improve sampling regimes as well as for testing and comparing models, for example species distribution models. We discuss its benefits as well as potential limitations, and provide some practical considerations for designing VE studies. Finally, research fields are identified for which the approach could be useful in the future. We conclude that VE could foster the integration of theoretical and empirical work and stimulate work that goes far beyond sampling methods, leading to new questions, theories, and better mechanistic understanding of ecological systems. Y1 - 2010 UR - http://www3.interscience.wiley.com/cgi-bin/issn?DESCRIPTOR=PRINTISSN&VALUE=0030-1299 U6 - https://doi.org/10.1111/j.1600-0706.2009.18284.x SN - 0030-1299 ER - TY - JOUR A1 - Dormann, Carsten F. A1 - Schymanski, Stanislaus J. A1 - Cabral, Juliano Sarmento A1 - Chuine, Isabelle A1 - Graham, Catherine A1 - Hartig, Florian A1 - Kearney, Michael A1 - Morin, Xavier A1 - Römermann, Christine A1 - Schröder-Esselbach, Boris A1 - Singer, Alexander T1 - Correlation and process in species distribution models: bridging a dichotomy JF - Journal of biogeography N2 - Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions. KW - Hypothesis generation KW - mechanistic model KW - parameterization KW - process-based model KW - species distribution model KW - SDM KW - uncertainty KW - validation Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2011.02659.x SN - 0305-0270 VL - 39 IS - 12 SP - 2119 EP - 2131 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Borregaard, Michael K. A1 - Amorim, Isabel R. A1 - Borges, Paulo A. V. A1 - Cabral, Juliano Sarmento A1 - Fernandez-Palacios, Jose M. A1 - Field, Richard A1 - Heaney, Lawrence R. A1 - Kreft, Holger A1 - Matthews, Thomas J. A1 - Olesen, Jens M. A1 - Price, Jonathan A1 - Rigal, Francois A1 - Steinbauer, Manuel J. A1 - Triantis, Konstantinos A. A1 - Valente, Luis A1 - Weigelt, Patrick A1 - Whittaker, Robert J. T1 - Oceanic island biogeography through the lens of the general dynamic model: assessment and prospect JF - Biological reviews KW - archipelago KW - diversity theory KW - general dynamic model KW - island biogeography KW - island evolution KW - trait evolution KW - volcanic islands Y1 - 2017 U6 - https://doi.org/10.1111/brv.12256 SN - 1464-7931 SN - 1469-185X VL - 92 SP - 830 EP - 853 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Radchuk, Viktoriia A1 - De Laender, Frederik A1 - Cabral, Juliano Sarmento A1 - Boulangeat, Isabelle A1 - Crawford, Michael Scott A1 - Bohn, Friedrich A1 - De Raedt, Jonathan A1 - Scherer, Cedric A1 - Svenning, Jens-Christian A1 - Thonicke, Kirsten A1 - Schurr, Frank M. A1 - Grimm, Volker A1 - Kramer-Schadt, Stephanie T1 - The dimensionality of stability depends on disturbance type JF - Ecology letters N2 - Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species-specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi-dimensional assessments are still to be recommended. KW - Community model KW - disturbance intensity KW - disturbance type KW - extinction KW - individual-based model KW - invariability KW - persistence KW - recovery KW - resistance Y1 - 2019 U6 - https://doi.org/10.1111/ele.13226 SN - 1461-023X SN - 1461-0248 VL - 22 IS - 4 SP - 674 EP - 684 PB - Wiley CY - Hoboken ER - TY - GEN A1 - Kalinkat, Gregor A1 - Cabral, Juliano Sarmento A1 - Darwall, William A1 - Ficetola, G. Francesco A1 - Fisher, Judith L. A1 - Giling, Darren P. A1 - Gosselin, Marie-Pierre A1 - Grossart, Hans-Peter A1 - Jaehnig, Sonja C. A1 - Jeschke, Jonathan M. A1 - Knopf, Klaus A1 - Larsen, Stefano A1 - Onandia, Gabriela A1 - Paetzig, Marlene A1 - Saul, Wolf-Christian A1 - Singer, Gabriel A1 - Sperfeld, Erik A1 - Jaric, Ivan T1 - Flagship umbrella species needed for the conservation of overlooked aquatic biodiversity T2 - Conservation biology : the journal of the Society for Conservation Biology Y1 - 2017 U6 - https://doi.org/10.1111/cobi.12813 SN - 0888-8892 SN - 1523-1739 VL - 31 SP - 481 EP - 485 PB - Wiley CY - Hoboken ER -