Improving the forecast for biodiversity under climate change.

New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species' responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity.

A stochastic movement simulator improves estimates of landscape connectivity.

Conservation actions often focus on restoration or creation of natural areas designed to facilitate the movements of organisms among populations. To be efficient, these actions need to be based on reliable estimates or predictions of landscape connectivity. While circuit theory and least-cost paths (LCPs) are increasingly being used to estimate connectivity, these methods also have proven limitations. We compared their performance in predicting genetic connectivity with that of an alternative approach based on a simple, individual-based "stochastic movement simulator" (SMS). SMS predicts dispersal of organisms using the same landscape representation as LCPs and circuit theory-based estimates (i.e., a cost surface), while relaxing key LCP assumptions, namely individual omniscience of the landscape (by incorporating perceptual range) and the optimality of individual movements (by including stochasticity in simulated movements). The performance of the three estimators was assessed by the degree to which they correlated with genetic estimates of connectivity in two species with contrasting movement abilities (Cabanis's Greenbul, an Afrotropical forest bird species, and natterjack toad, an amphibian restricted to European sandy and heathland areas). For both species, the correlation between dispersal model and genetic data was substantially higher when SMS was used. Importantly, the results also demonstrate that the improvement gained by using SMS is robust both to variation in spatial resolution of the landscape and to uncertainty in the perceptual range model parameter. Integration of this individual-based approach with other developing methods in the field of connectivity research, such as graph theory, can yield rapid progress towards more robust connectivity indices and more effective recommendations for land management.

Prospecting and dispersal: their eco-evolutionary dynamics and implications for population patterns.

Dispersal is not a blind process, and evidence is accumulating that individual dispersal strategies are informed in most, if not all, organisms. The acquisition and use of information are traits that may evolve across space and time as a function of the balance between costs and benefits of informed dispersal. If information is available, individuals can potentially use it in making better decisions, thereby increasing their fitness. However, prospecting for and using information probably entail costs that may constrain the evolution of informed dispersal, potentially with population-level consequences. By using individual-based, spatially explicit simulations, we detected clear coevolutionary dynamics between prospecting and dispersal movement strategies that differed in sign and magnitude depending on their respective costs. More specifically, we found that informed dispersal strategies evolve when the costs of information acquisition during prospecting are low but only if there are mortality costs associated with dispersal movements. That is, selection favours informed dispersal strategies when the acquisition and use processes themselves were not too expensive. When non-informed dispersal strategies evolve, they do so jointly with the evolution of long dispersal distance because this maximizes the sampling area. In some cases, selection produces dispersal rules different from those that would be 'optimal' (i.e. the best possible population performance--in our context quantitatively measured as population density and patch occupancy--among all possible individual movement rules) for the population. That is, on the one hand, informed dispersal strategies led to population performance below its highest possible level. On the other hand, un- and poorly informed individuals nearly optimized population performance, both in terms of density and patch occupancy.

Risky movement increases the rate of range expansion.

The movement rules used by an individual determine both its survival and dispersal success. Here, we develop a simple model that links inter-patch movement behaviour with population dynamics in order to explore how individual dispersal behaviour influences not only its dispersal and survival, but also the population's rate of range expansion. Whereas dispersers are most likely to survive when they follow nearly straight lines and rapidly orient movement towards a non-natal patch, the most rapid rates of range expansion are obtained for trajectories in which individuals delay biasing their movement towards a non-natal patch. This result is robust to the spatial structure of the landscape. Importantly, in a set of evolutionary simulations, we also demonstrate that the movement strategy that evolves at an expanding front is much closer to that maximizing the rate of range expansion than that which maximizes the survival of dispersers. Our results suggest that if one of our conservation goals is the facilitation of range-shifting, then current indices of connectivity need to be complemented by the development and utilization of new indices providing a measure of the ease with which a species spreads across a landscape.

Mutation surfing and the evolution of dispersal during range expansions.

A growing body of empirical evidence demonstrates that at an expanding front, there can be strong selection for greater dispersal propensity, whereas recent theory indicates that mutations occurring towards the front of a spatially expanding population can sometimes 'surf' to high frequency and spatial extent. Here, we consider the potential interplay between these two processes: what role may mutation surfing play in determining the course of dispersal evolution and how might dispersal evolution itself influence mutation surfing? Using an individual-based coupled-map lattice model, we first run simulations to determine the fate of dispersal mutants that occur at an expanding front. Our results highlight that mutants that have a slightly higher dispersal propensity than the wild type always have a higher survival probability than those mutants with a dispersal propensity lower than, or very similar to, the wild type. However, it is not always the case that mutants with very high dispersal propensity have the greatest survival probability. When dispersal mortality is high, mutants of intermediate dispersal survive most often. Interestingly, the rate of dispersal that ultimately evolves at an expanding front is often substantially higher than that which confers a novel mutant with the greatest probability of survival. Second, we run a model in which we allow dispersal to evolve over the course of a range expansion and ask how the fate of a neutral or nonneutral mutant depends upon when and where during the expansion it arises. These simulations highlight that the success of a neutral mutant depends upon the dispersal genotypes that it is associated with. An important consequence of this is that novel mutants that arise at the front of an expansion, and survive, typically end up being associated with more dispersive genotypes than the wild type. These results offer some new insights into causes and the consequences of dispersal evolution during range expansions, and the methodology we have employed can be readily extended to explore the evolutionary dynamics of other life history characteristics.

Local adaptation and the evolution of species' ranges under climate change.

The potential impact of climate change on biodiversity is well documented. A well developed range of statistical methods currently exists that projects the possible future habitat of a species directly from the current climate and a species distribution. However, studies incorporating ecological and evolutionary processes remain limited. Here, we focus on the potential role that local adaptation to climate may play in driving the range dynamics of sessile organisms. Incorporating environmental adaptation into a stochastic simulation yields several new insights. Counter-intuitively, our simulation results suggest that species with broader ranges are not necessarily more robust to climate change. Instead, species with broader ranges can be more susceptible to extinction as locally adapted genotypes are often blocked from range shifting by the presence of cooler adapted genotypes that persist even when their optimum climate has left them behind. Interestingly, our results also suggest that it will not always be the cold-adapted phenotypes that drive polewards range expansion. Instead, range shifts may be driven by phenotypes conferring adaptation to conditions prevalent towards the centre of a species' equilibrium distribution. This may have important consequences for the conservation method termed predictive provenancing. These initial results highlight the potential importance of local adaptation in determining how species will respond to climate change and we argue that this is an area requiring urgent theoretical and empirical attention.

The effect of host movement on viral transmission dynamics in a vector-borne disease system.

Many vector-borne pathogens whose primary vectors are generalists, such as Ixodid ticks, can infect a wide range of host species and are often zoonotic. Understanding their transmission dynamics is important for the development of disease management programmes. Models exist to describe the transmission dynamics of such diseases, but are necessarily simplistic and generally limited by knowledge of vector population dynamics. They are typically deterministic SIR-type models, which predict disease dynamics in a single, non-spatial, closed patch. Here we explore the limitations of such a model of louping-ill virus dynamics by challenging it with novel field data. The model was only partially successful in predicting Ixodes ricinus density and louping-ill virus prevalence at 6 Scottish sites. We extend the existing multi-host model by forming a two-patch model, incorporating the impact of roaming hosts. This demonstrates that host movement may account for some of the discrepancies between the original model and empirical data. We conclude that insights into the dynamics of multi-host vector-borne pathogens can be gained by using a simple two-patch model. Potential improvements to the model, incorporating aspects of spatial and temporal heterogeneity, are outlined.

How range shifts induced by climate change affect neutral evolution.

We investigate neutral evolution during range shifts in a strategic model of a metapopulation occupying a climate gradient. Using heritable, neutral markers, we track the spatio-temporal fate of lineages. Owing to iterated founder effects ('mutation surfing'), survival of lineages derived from the leading range limit is enhanced. At trailing limits, where habitat suitability decreases, survival is reduced (mutations 'wipe out'). These processes alter (i) the spatial spread of mutations, (ii) origins of persisting mutations and (iii) the generation of diversity. We show that large changes in neutral evolution can be a direct consequence of range shifting.

Landscape structure and boundary effects determine the fate of mutations occurring during range expansions.

The interplay between the spatial dynamics of range expansion and evolutionary processes is receiving considerable attention. Recent theory has demonstrated that mutations occurring towards the front of a spatially expanding population can sometimes 'surf' to high frequency and spatial extent. Here, we extend this work to consider how the fate of a novel mutation is influenced by where and when it occurs. Specifically, we are interested in establishing how the origin of a mutation relative to a habitat edge influences its dynamics, and in understanding how this is mediated by the behaviour of individuals at those boundaries. Using a coupled-map lattice model, we demonstrate that the survival probability, abundance and spatial extent of surviving mutants can depend on their origin. An edge effect is often observed and can be quite different both qualitatively and quantitatively depending on the behavioural rules assumed. Mutations, especially those that are deleterious, that arise at a habitat edge with reflective boundary conditions can be many more times likely to survive for substantial periods of time than those that arise away from the edge. Conversely, with absorbing boundary conditions, their survival is greater when they arise well away from the edge. Our results clearly illustrate that landscape structure, habitat edges and boundary conditions have a considerable influence on the likely fate of mutations that occur during a period of range expansion.

The distribution of positive and negative species interactions across environmental gradients on a dual-lattice model.

There has been considerable recent interest in understanding the role of positive inter-specific interactions within ecology, and significant progress has been made both empirically and theoretically. Similarly, considerable progress has been made in improving our understanding of the mechanisms that limit species' ranges. In this contribution, we seek to understand the setting of species' borders when some species within the assemblage exhibit positive inter-specific interactions. We use a spatially explicit dual-lattice simulation model to explore the distribution of different interactions across environmental gradients. We first simulate community dynamics when there is either a gradient in reproductive rate or in mortality. We then consider what happens when gradients in reproduction and mortality run in parallel or perpendicular to one another. If the stress gradient impacts on reproductive potential, positive interactions are found where there is high abiotic stress. In this instance, the mutualists are able to tolerate an environment that the cheaters cannot. However, when the stress gradient influences mortality, we find that the mutualists occur as a stripe surrounded by cheaters both towards the better and the harsher ends of the gradient. Previous theory and most empirical evidence tend to indicate that net positive interactions are likely to occur in environments characterized by high abiotic stress. However, evidence from some stress gradients suggests that the distribution of positive and negative interactions can be more complex, with the most stressful environments being occupied by individuals engaging in negative rather than positive interactions. Our results provide a potential theoretical explanation for these recent field observation, and highlight the need for further theoretical and empirical work to better our understanding of how positive and negative interactions act to determine the limits to species' ranges.

The interplay of positive and negative species interactions across an environmental gradient: insights from an individual-based simulation model.

Positive interspecific interactions are commonplace, and in recent years ecologists have begun to realize how important they can be in determining community and ecosystem dynamics. It has been predicted that net positive interactions are likely to occur in environments characterized by high abiotic stress. Although empirical field studies have started to support these predictions, little theoretical work has been carried out on the dynamic nature of these effects and their consequences for community structure. We use a simple patch-occupancy model to simulate the dynamics of a pair of species living on an environmental gradient. Each of the species can exist as either a mutualist or a cheater. The results confirm the prediction: a band of mutualists tends to occur in environmental conditions beyond the limits of the cheaters. The region between mutualists and cheaters is interesting: population density here is low. Mutualists periodically occupy this area, but are displaced by cheaters, who themselves go extinct in the absence of the mutualists. Furthermore, the existence of mutualists extends the area occupied by the cheaters, essentially increasing their realized niche. Our approach has considerable potential for improving our understanding of the balance between positive and negative interspecific interactions and for predicting the probable impacts of habitat loss and climate change on communities dominated by positive interspecific interactions.

Spatial processes can determine the relationship between prey encounter rate and prey density.

Theoretical models frequently assume that the rate at which a searching predator encounters prey increases linearly with prey density. In a recent experiment using great tits searching for winter moth caterpillars, the time to find the first prey item did not decline as quickly with density as the standard theory assumes. Using a spatial simulation model, we show that prey aggregation and/or spatially correlated searching behaviour by the predator can generate a range of relationships, including results that are qualitatively similar to those found in the great tit experiment. We suggest that further experiments are required to determine whether the explanation proposed here is correct, and that theoretical work is needed to determine how this behaviour is likely to influence the ecological and evolutionary dynamics of predator-prey communities.

Mutators in space: the dynamics of high-mutability clones in a two-patch model.

Clones of bacteria possessing high-mutability rates (or mutators) are being observed in an increasing number of species. In a constant environment most mutations are deleterious, and hence the spontaneous mutation rate is generally low. However, mutators may play an important role in the adaptation of organisms to changing environments. To date, theoretical work has focused on temporal variability in the environment, implicitly assuming that environmental conditions are constant through space. Here, we develop a two-patch model to investigate how spatiotemporal environmental variability and dispersal might influence mutator dynamics. Environmental conditions in each patch fluctuate between two states; the rate of fluctuation varies in each patch at differing phase angles. We find that at low and intermediate rates of fluctuation, an increase in dispersal results in a decrease in the density of mutators. However, at high rates of environmental change, dispersal causes an increase in mutator density. For all frequencies of environmental fluctuation these trends are enhanced as the phase angle approaches 180 degrees. We argue that future work, both empirical and theoretical, is needed to improve our understanding of how spatiotemporal variability impacts on mutator densities and dynamics.

Climate change and habitat destruction: a deadly anthropogenic cocktail.

Climate change and habitat destruction are two of the greatest threats to global biodiversity. Lattice models have been used to investigate how hypothetical species with different characteristics respond to habitat loss. The main result shows that a sharp threshold in habitat availability exists below which a species rapidly becomes extinct. Here, a similar modelling approach is taken to establish what determines how species respond to climate change. A similar threshold exists for the rate of climate change as has been observed for habitat loss-patch occupancy remains high up to a critical rate of climate change, beyond which species extinction becomes likely. Habitat specialists, especially those of relatively poor colonizing ability are least able to keep pace with climate change. The interaction between climate change and habitat loss might be disastrous. During climate change, the habitat threshold occurs sooner. Similarly, species suffer more from climate change in a fragmented habitat.

Mutator dynamics in fluctuating environments.

Populations with high mutation rates (mutator clones) are being found in increasing numbers of species, and a clear link is being established between the presence of mutator clones and drug resistance. Mutator clones exist despite the fact that in a constant environment most mutations are deleterious, with the spontaneous mutation rate generally held at a low value. This implies that mutator clones have an important role in the adaptation of organisms to changing environments. Our study examines how mutator dynamics vary according to the frequency of environmental fluctuations. Although recent studies have considered a single environmental switch, here we investigate mutator dynamics in a regularly varying environment, seeking to mimic conditions present, for example, under certain drug or pesticide regimes. Our model provides four significant new insights. First, the results demonstrate that mutators are most prevalent under intermediate rates of environmental change. When the environment oscillates more rapidly, mutators are unable to provide sufficient adaptability to keep pace with the frequent changes in selection pressure and, instead, a population of 'environmental generalists' dominates. Second, our findings reveal that mutator dynamics may be complex, exhibiting limit cycles and chaos. Third, we demonstrate that when each beneficial mutation provides a greater gain in fitness, mutators achieve higher densities in more rapidly fluctuating environments. Fourth, we find that mutators of intermediate strength reach higher densities than very weak or strong mutators.