TY - JOUR A1 - Pagel, Jörn A1 - Schurr, Frank Martin T1 - Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics JF - Global ecology and biogeography : a journal of macroecology N2 - 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. KW - Biogeography KW - ecological forecasts KW - global change KW - hierarchical Bayesian statistics KW - long-distance dispersal KW - niche theory KW - process-based model KW - range shifts KW - spatial demography KW - species distribution modelling Y1 - 2012 U6 - https://doi.org/10.1111/j.1466-8238.2011.00663.x SN - 1466-822X VL - 21 IS - 2 SP - 293 EP - 304 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Wacker, Alexander A1 - Martin-Creuzburg, Dominik T1 - Biochemical nutrient requirements of the rotifer Brachionus calyciflorus co-limitation by sterols and amino acids JF - Functional ecology : an official journal of the British Ecological Society N2 - 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. KW - consumer KW - consumer-diet imbalance KW - dietary mismatch KW - fatty acid KW - global change KW - lipid KW - nutrition KW - phytoplankton KW - tetrahymanol KW - zooplankton Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2435.2012.02047.x SN - 0269-8463 VL - 26 IS - 5 SP - 1135 EP - 1143 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Marion, Glenn A1 - McInerny, Greg J. A1 - Pagel, Jörn A1 - Catterall, Stephen A1 - Cook, Alex R. A1 - Hartig, Florian A1 - O&rsquo, A1 - Hara, Robert B. T1 - Parameter and uncertainty estimation for process-oriented population and distribution models: data, statistics and the niche JF - JOURNAL OF BIOGEOGRAPHY N2 - 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. KW - Bayesian inference KW - demography KW - dispersal KW - dynamic models KW - dynamic range models KW - establishment KW - global change KW - niche models KW - species distribution models Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2012.02772.x SN - 0305-0270 SN - 1365-2699 VL - 39 IS - 12 SP - 2225 EP - 2239 PB - WILEY-BLACKWELL CY - HOBOKEN ER - TY - JOUR A1 - Kissling, W. D. A1 - Dormann, Carsten F. A1 - Groeneveld, Juergen A1 - Hickler, Thomas A1 - Kühn, Ingolf A1 - McInerny, Greg J. A1 - Montoya, Jose M. A1 - Römermann, Christine A1 - Schiffers, Katja A1 - Schurr, Frank Martin A1 - Singer, Alexander A1 - Svenning, Jens-Christian A1 - Zimmermann, Niklaus E. A1 - O'Hara, Robert B. T1 - Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents JF - Journal of biogeography N2 - 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. KW - Community ecology KW - ecological networks KW - global change KW - guild assembly KW - multidimensional complexity KW - niche theory KW - prediction KW - species distribution model KW - species interactions KW - trait-based community modules Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2011.02663.x SN - 0305-0270 VL - 39 IS - 12 SP - 2163 EP - 2178 PB - Wiley-Blackwell CY - Hoboken ER -