TY - JOUR A1 - Travis, Justin M. J. A1 - Mustin, Karen A1 - Benton, Tim G. A1 - Dytham, Calvin T1 - Accelerating invasion rates result from the evolution of density-dependent dispersal N2 - Evolutionary processes play an important role in shaping the dynamics of range expansions, and selection on dispersal propensity has been demonstrated to accelerate rates of advance. Previous theory has considered only the evolution of unconditional dispersal rates, but dispersal is often more complex. For example, many species emigrate in response to crowding. Here, we use an individual-based model to investigate the evolution of density dependent dispersal into empty habitat, such as during an invasion. The landscape is represented as a lattice and dispersal between Populations follows a stepping-stone pattern. Individuals carry three 'genes' that determine their dispersal strategy when experiencing different population densities. For a stationary range we obtain results consistent with previous theoretical studies: few individuals emigrate from patches that are below equilibrium density. However, during the range expansion of a previously stationary population, we observe evolution towards dispersal strategies where considerable emigration occurs well below equilibrium density. This is true even for moderate costs to dispersal, and always results in accelerating rates of range expansion. Importantly, the evolution we observe at an expanding front depends upon fitness integrated over several generations and cannot be predicted by a consideration of lifetime reproductive success alone. We argue that a better understanding of the role of density dependent dispersal, and its evolution, in driving population dynamics is required especially within the context of range expansions. Y1 - 2009 UR - http://www.sciencedirect.com/science/journal/00225193 U6 - https://doi.org/10.1016/j.jtbi.2009.03.008 SN - 0022-5193 ER - TY - JOUR A1 - Mustin, Karen A1 - Benton, Tim G. A1 - Dytham, Calvin A1 - Travis, Justin M. J. T1 - The dynamics of climate-induced range shifting : perspectives from simulation modelling N2 - Predicted future climate change will alter species' distributions as they attempt to track the most suitable 'climate window'. Climate envelope models indicate the direction of likely range changes but do not incorporate population dynamics, therefore observed responses may differ greatly from these projections. We use simulation modelling to explore the consequences of a period of environmental change for a species structured across an environmental gradient. Results indicate that a species' range may lag behind its climate envelope and demonstrate that the rate of movement of a range can accelerate during a period of climate change. We conclude that the inclusion of both population dynamics and spatial environmental variability is vital to develop models that can both predict, and be used to manage, the impact of changing climate on species' biogeography. Y1 - 2009 UR - http://www3.interscience.wiley.com/cgi-bin/issn?DESCRIPTOR=PRINTISSN&VALUE=0030-1299 U6 - https://doi.org/10.1111/j.1600-0706.2008.17025.x SN - 0030-1299 ER - TY - JOUR A1 - Holland, E. P. A1 - Burrow, Jennifer F. A1 - Dytham, Calvin A1 - Aegerter, James N. T1 - Modelling with uncertainty : introducing a probabilistic framework to predict animal population dynamics N2 - Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback-Leibier distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios. We illustrate the framework's power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results. Y1 - 2009 UR - http://www.sciencedirect.com/science/journal/03043800 U6 - https://doi.org/10.1016/j.ecolmodel.2009.02.013 SN - 0304-3800 ER -