@misc{SchurrPagelSarmentoetal.2012,
  author    = {Schurr, Frank Martin and Pagel, J{\"o}rn and Sarmento, Juliano Sarmento and Groeneveld, Juergen and Bykova, Olga and O'Hara, Robert B. and Hartig, Florian and Kissling, W. Daniel and Linder, H. Peter and Midgley, Guy F. and Schr{\"o}der-Esselbach, Boris and Singer, Alexander and Zimmermann, Niklaus E.},
  title     = {How to understand species' niches and range dynamics: a demographic research agenda for biogeography},
  series = {Journal of biogeography},
  volume    = {39},
  journal   = {Journal of biogeography},
  number    = {12},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0305-0270},
  doi       = {10.1111/j.1365-2699.2012.02737.x},
  pages     = {2146 -- 2162},
  year      = {2012},
  abstract  = {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.},
  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}
}