@article{HothornMuellerSchroederetal.2011,
  author    = {Hothorn, Torsten and M{\"u}ller, J{\"o}rg and Schroeder, Boris and Kneib, Thomas and Brandl, Roland},
  title     = {Decomposing environmental, spatial, and spatiotemporal components of species distributions},
  series = {Ecological monographs : a publication of the Ecological Society of America.},
  volume    = {81},
  journal   = {Ecological monographs : a publication of the Ecological Society of America.},
  number    = {2},
  publisher = {Wiley},
  address   = {Washington},
  issn      = {0012-9615},
  doi       = {10.1890/10-0602.1},
  pages     = {329 -- 347},
  year      = {2011},
  abstract  = {Species distribution models are an important tool to predict the impact of global change on species distributional ranges and community assemblages. Although considerable progress has been made in the statistical modeling during the last decade, many approaches still ignore important features of species distributions, such as nonlinearity and interactions between predictors, spatial autocorrelation, and nonstationarity, or at most incorporate only some of these features. Ecologists, however, require a modeling framework that simultaneously addresses all these features flexibly and consistently. Here we describe such an approach that allows the estimation of the global effects of environmental variables in addition to local components dealing with spatiotemporal autocorrelation as well as nonstationary effects. The local components can be used to infer unknown spatiotemporal processes; the global component describes how the species is influenced by the environment and can be used for predictions, allowing the fitting of many well-known regression relationships, ranging from simple linear models to complex decision trees or from additive models to models inspired by machine learning procedures. The reliability of spatiotemporal predictions can be qualitatively predicted by separately evaluating the importance of local and global effects. We demonstrate the potential of the new approach by modeling the breeding distribution of the Red Kite (Milvus milvus), a bird of prey occurring predominantly in Western Europe, based on presence/absence data from two mapping campaigns using grids of 40 km 2 in Bavaria. The global component of the model selected seven environmental variables extracted from the CORINE and WorldClim databases to predict Red Kite breeding. The effect of altitude was found to be nonstationary in space, and in addition, the data were spatially autocorrelated, which suggests that a species distribution model that does not allow for spatially varying effects and spatial autocorrelation would have ignored important processes determining the distribution of Red Kite breeding across Bavaria. Thus, predictions from standard species distribution models that do not allow for real-world complexities may be considerably erroneous. Our analysis of Red Kite breeding exemplifies the potential of the innovative approach for species distribution models. The method is also applicable to modeling count data.},
  language  = {en}
}
@misc{DormannSchymanskiCabraletal.2012,
  author    = {Dormann, Carsten F. and Schymanski, Stanislaus J. and Cabral, Juliano Sarmento and Chuine, Isabelle and Graham, Catherine and Hartig, Florian and Kearney, Michael and Morin, Xavier and R{\"o}mermann, Christine and Schr{\"o}der-Esselbach, Boris and Singer, Alexander},
  title     = {Correlation and process in species distribution models: bridging a dichotomy},
  series = {Journal of biogeography},
  volume    = {39},
  journal   = {Journal of biogeography},
  number    = {12},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0305-0270},
  doi       = {10.1111/j.1365-2699.2011.02659.x},
  pages     = {2119 -- 2131},
  year      = {2012},
  abstract  = {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.},
  language  = {en}
}
@misc{KisslingDormannGroeneveldetal.2012,
  author    = {Kissling, W. D. and Dormann, Carsten F. and Groeneveld, Juergen and Hickler, Thomas and K{\"u}hn, Ingolf and McInerny, Greg J. and Montoya, Jose M. and R{\"o}mermann, Christine and Schiffers, Katja and Schurr, Frank Martin and Singer, Alexander and Svenning, Jens-Christian and Zimmermann, Niklaus E. and O'Hara, Robert B.},
  title     = {Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents},
  series = {Journal of biogeography},
  volume    = {39},
  journal   = {Journal of biogeography},
  number    = {12},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0305-0270},
  doi       = {10.1111/j.1365-2699.2011.02663.x},
  pages     = {2163 -- 2178},
  year      = {2012},
  abstract  = {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.},
  language  = {en}
}
@article{RadchukKramerSchadtFickeletal.2019,
  author    = {Radchuk, Viktoriia and Kramer-Schadt, Stephanie and Fickel, J{\"o}rns and Wilting, Andreas},
  title     = {Distributions of mammals in Southeast Asia: The role of the legacy of climate and species body mass},
  series = {Journal of biogeography},
  volume    = {46},
  journal   = {Journal of biogeography},
  number    = {10},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0305-0270},
  doi       = {10.1111/jbi.13675},
  pages     = {2350 -- 2362},
  year      = {2019},
  abstract  = {Aim Current species distributions are shaped by present and past biotic and abiotic factors. Here, we assessed whether abiotic factors (habitat availability) in combination with past connectivity and a biotic factor (body mass) can explain the unique distribution pattern of Southeast Asian mammals, which are separated by the enigmatic biogeographic transition zone, the Isthmus of Kra (IoK), for which no strong geophysical barrier exists. Location Southeast Asia. Taxon Mammals. Methods We projected habitat suitability for 125 mammal species using climate data for the present period and for two historic periods: mid-Holocene (6 ka) and last glacial maximum (LGM 21 ka). Next, we employed a phylogenetic linear model to assess how present species distributions were affected by the suitability of areas in these different periods, habitat connectivity during LGM and species body mass. Results Our results show that cooler climate during LGM provided suitable habitat south of IoK for species presently distributed north of IoK (in mainland Indochina). However, the potentially suitable habitat for these Indochinese species did not stretch very far southwards onto the exposed Sunda Shelf. Instead, we found that the emerged landmasses connecting Borneo and Sumatra provided suitable habitat for forest dependent Sundaic species. We show that for species whose current distribution ranges are mainly located in Indochina, the area of the distribution range that is located south of IoK is explained by the suitability of habitat in the past and present in combination with the species body mass. Main conclusions We demonstrate that a strong geophysical barrier may not be necessary for maintaining a biogeographic transition zone for mammals, but that instead a combination of abiotic and biotic factors may suffice.},
  language  = {en}
}