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 -