@article{MarionMcInernyPageletal.2012,
  author    = {Marion, Glenn and McInerny, Greg J. and Pagel, J{\"o}rn and Catterall, Stephen and Cook, Alex R. and Hartig, Florian and O\&rsquo, and Hara, Robert B.},
  title     = {Parameter and uncertainty estimation for process-oriented population and distribution models: data, statistics and the niche},
  series = {JOURNAL OF BIOGEOGRAPHY},
  volume    = {39},
  journal   = {JOURNAL OF BIOGEOGRAPHY},
  number    = {12},
  publisher = {WILEY-BLACKWELL},
  address   = {HOBOKEN},
  issn      = {0305-0270},
  doi       = {10.1111/j.1365-2699.2012.02772.x},
  pages     = {2225 -- 2239},
  year      = {2012},
  abstract  = {The spatial distribution of a species is determined by dynamic processes such as reproduction, mortality and dispersal. Conventional static species distribution models (SDMs) do not incorporate these processes explicitly. This limits their applicability, particularly for non-equilibrium situations such as invasions or climate change. In this paper we show how dynamic SDMs can be formulated and fitted to data within a Bayesian framework. Our focus is on discrete state-space Markov process models which provide a flexible framework to account for stochasticity in key demographic processes, including dispersal, growth and competition. We show how to construct likelihood functions for such models (both discrete and continuous time versions) and how these can be combined with suitable observation models to conduct Bayesian parameter inference using computational techniques such as Markov chain Monte Carlo. We illustrate the current state-of-the-art with three contrasting examples using both simulated and empirical data. The use of simulated data allows the robustness of the methods to be tested with respect to deficiencies in both data and model. These examples show how mechanistic understanding of the processes that determine distribution and abundance can be combined with different sources of information at a range of spatial and temporal scales. Application of such techniques will enable more reliable inference and projections, e.g. under future climate change scenarios than is possible with purely correlative approaches. Conversely, confronting such process-oriented niche models with abundance and distribution data will test current understanding and may ultimately feedback to improve underlying ecological theory.},
  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}
}
@article{WackerMartinCreuzburg2012,
  author    = {Wacker, Alexander and Martin-Creuzburg, Dominik},
  title     = {Biochemical nutrient requirements of the rotifer Brachionus calyciflorus co-limitation by sterols and amino acids},
  series = {Functional ecology : an official journal of the British Ecological Society},
  volume    = {26},
  journal   = {Functional ecology : an official journal of the British Ecological Society},
  number    = {5},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0269-8463},
  doi       = {10.1111/j.1365-2435.2012.02047.x},
  pages     = {1135 -- 1143},
  year      = {2012},
  abstract  = {It has been proposed that growth and reproduction of animals is frequently limited by multiple nutrients simultaneously. To improve our understanding of the consequences of multiple nutrient limitations (i.e. co-limitation) for the performance of animals, we conducted standardized population growth experiments using an important aquatic consumer, the rotifer Brachionus calyciflorus. We compared nutrient profiles (sterols, fatty acids and amino acids) of rotifers and their diets to reveal consumerdiet imbalances and thus potentially limiting nutrients. In concomitant growth experiments, we directly supplemented potentially limiting substances (sterols, fatty acids, amino acids) to a nutrient-deficient diet, the cyanobacterium Synechococcus elongatus, and recorded population growth rates. The results from the supplementation experiments corroborated the nutrient limitations predicted by assessing consumerdiet imbalances, but provided more detailed information on co-limiting nutrients. While the fatty acid deficiency of the cyanobacterium appeared to be of minor importance, the addition of both cholesterol and certain amino acids (leucine and isoleucine) improved population growth rates of rotifers, indicating a simultaneous limitation by sterols and amino acids. Our results add to growing evidence that consumers frequently face multiple nutrient limitations and suggest that the concept of co-limitation has to be considered in studies assessing nutrient-limited growth responses of consumers.},
  language  = {en}
}