@misc{NathanHorvitzHeetal.2011,
  author    = {Nathan, Ran and Horvitz, Nir and He, Yanping and Kuparinen, Anna and Schurr, Frank Martin and Katul, Gabriel G.},
  title     = {Spread of North American wind-dispersed trees in future environments},
  series = {Ecology letters},
  volume    = {14},
  journal   = {Ecology letters},
  number    = {3},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {1461-023X},
  doi       = {10.1111/j.1461-0248.2010.01573.x},
  pages     = {211 -- 219},
  year      = {2011},
  abstract  = {P>Despite ample research, understanding plant spread and predicting their ability to track projected climate changes remain a formidable challenge to be confronted. We modelled the spread of North American wind-dispersed trees in current and future (c. 2060) conditions, accounting for variation in 10 key dispersal, demographic and environmental factors affecting population spread. Predicted spread rates vary substantially among 12 study species, primarily due to inter-specific variation in maturation age, fecundity and seed terminal velocity. Future spread is predicted to be faster if atmospheric CO2 enrichment would increase fecundity and advance maturation, irrespective of the projected changes in mean surface windspeed. Yet, for only a few species, predicted wind-driven spread will match future climate changes, conditioned on seed abscission occurring only in strong winds and environmental conditions favouring high survival of the farthest-dispersed seeds. Because such conditions are unlikely, North American wind-dispersed trees are expected to lag behind the projected climate range shift.},
  language  = {en}
}
@article{PagelSchurr2012,
  author    = {Pagel, J{\"o}rn and Schurr, Frank Martin},
  title     = {Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics},
  series = {Global ecology and biogeography : a journal of macroecology},
  volume    = {21},
  journal   = {Global ecology and biogeography : a journal of macroecology},
  number    = {2},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {1466-822X},
  doi       = {10.1111/j.1466-8238.2011.00663.x},
  pages     = {293 -- 304},
  year      = {2012},
  abstract  = {Aim The study and prediction of speciesenvironment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties. Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation. Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology.},
  language  = {en}
}