Benchmarking novel approaches for modelling species range dynamics.

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species.

Contrasting changes in the abundance and diversity of North American bird assemblages from 1971 to 2010.

Although it is generally recognized that global biodiversity is declining, few studies have examined long-term changes in multiple biodiversity dimensions simultaneously. In this study, we quantified and compared temporal changes in the abundance, taxonomic diversity, functional diversity, and phylogenetic diversity of bird assemblages, using roadside monitoring data of the North American Breeding Bird Survey from 1971 to 2010. We calculated 12 abundance and diversity metrics based on 5-year average abundances of 519 species for each of 768 monitoring routes. We did this for all bird species together as well as for four subgroups based on breeding habitat affinity (grassland, woodland, wetland, and shrubland breeders). The majority of the biodiversity metrics increased or remained constant over the study period, whereas the overall abundance of birds showed a pronounced decrease, primarily driven by declines of the most abundant species. These results highlight how stable or even increasing metrics of taxonomic, functional, or phylogenetic diversity may occur in parallel with substantial losses of individuals. We further found that patterns of change differed among the species subgroups, with both abundance and diversity increasing for woodland birds and decreasing for grassland breeders. The contrasting changes between abundance and diversity and among the breeding habitat groups underscore the relevance of a multifaceted approach to measuring biodiversity change. Our findings further stress the importance of monitoring the overall abundance of individuals in addition to metrics of taxonomic, functional, or phylogenetic diversity, thus confirming the importance of population abundance as an essential biodiversity variable.

Between migration load and evolutionary rescue: dispersal, adaptation and the response of spatially structured populations to environmental change.

The evolutionary potential of populations is mainly determined by population size and available genetic variance. However, the adaptability of spatially structured populations may also be affected by dispersal: positively by spreading beneficial mutations across sub-populations, but negatively by moving locally adapted alleles between demes. We develop an individual-based, two-patch, allelic model to investigate the balance between these opposing effects on a population's evolutionary response to rapid climate change. Individual fitness is controlled by two polygenic traits coding for local adaptation either to the environment or to climate. Under conditions of selection that favour the evolution of a generalist phenotype (i.e. weak divergent selection between patches) dispersal has an overall positive effect on the persistence of the population. However, when selection favours locally adapted specialists, the beneficial effects of dispersal outweigh the associated increase in maladaptation for a narrow range of parameter space only (intermediate selection strength and low linkage among loci), where the spread of beneficial climate alleles is not strongly hampered by selection against non-specialists. Given that local selection across heterogeneous and fragmented landscapes is common, the complex effect of dispersal that we describe will play an important role in determining the evolutionary dynamics of many species under rapidly changing climate.

ALADYN - a spatially explicit, allelic model for simulating adaptive dynamics.

ALADYN is a freely available cross-platform C++ modeling framework for stochastic simulation of joint allelic and demographic dynamics of spatially-structured populations. Juvenile survival is linked to the degree of match between an individual's phenotype and the local phenotypic optimum. There is considerable flexibility provided for the demography of the considered species and the genetic architecture of the traits under selection. ALADYN facilitates the investigation of adaptive processes to spatially and/or temporally changing conditions and the resulting niche and range dynamics. To our knowledge ALADYN is so far the only model that allows a continuous resolution of individuals' locations in a spatially explicit landscape together with the associated patterns of selection.

Does probability of occurrence relate to population dynamics?

Hutchinson defined species' realized niche as the set of environmental conditions in which populations can persist in the presence of competitors. In terms of demography, the realized niche corresponds to the environments where the intrinsic growth rate (r) of populations is positive. Observed species occurrences should reflect the realized niche when additional processes like dispersal and local extinction lags do not have overwhelming effects. Despite the foundational nature of these ideas, quantitative assessments of the relationship between range-wide demographic performance and occurrence probability have not been made. This assessment is needed both to improve our conceptual understanding of species' niches and ranges and to develop reliable mechanistic models of species geographic distributions that incorporate demography and species interactions. The objective of this study is to analyse how demographic parameters (intrinsic growth rate r and carrying capacity K) and population density (N) relate to occurrence probability (Pocc ). We hypothesized that these relationships vary with species' competitive ability. Demographic parameters, density, and occurrence probability were estimated for 108 tree species from four temperate forest inventory surveys (Québec, Western US, France and Switzerland). We used published information of shade tolerance as indicators of light competition strategy, assuming that high tolerance denotes high competitive capacity in stable forest environments. Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with Pocc , while N, and for most regions K, was generally positively correlated with Pocc . Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models.

The influence of interspecific interactions on species range expansion rates.

Ongoing and predicted global change makes understanding and predicting species' range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species.

A road map for integrating eco-evolutionary processes into biodiversity models.

The demand for projections of the future distribution of biodiversity has triggered an upsurge in modelling at the crossroads between ecology and evolution. Despite the enthusiasm around these so-called biodiversity models, most approaches are still criticised for not integrating key processes known to shape species ranges and community structure. Developing an integrative modelling framework for biodiversity distribution promises to improve the reliability of predictions and to give a better understanding of the eco-evolutionary dynamics of species and communities under changing environments. In this article, we briefly review some eco-evolutionary processes and interplays among them, which are essential to provide reliable projections of species distributions and community structure. We identify gaps in theory, quantitative knowledge and data availability hampering the development of an integrated modelling framework. We argue that model development relying on a strong theoretical foundation is essential to inspire new models, manage complexity and maintain tractability. We support our argument with an example of a novel integrated model for species distribution modelling, derived from metapopulation theory, which accounts for abiotic constraints, dispersal, biotic interactions and evolution under changing environmental conditions. We hope such a perspective will motivate exciting and novel research, and challenge others to improve on our proposed approach.

Beyond the competition-colonization trade-off: linking multiple trait response to disturbance characteristics.

Disturbances' role in shaping communities is well documented but highly disputed. We suggest replacing the overused two-trait trade-off approach with a functional group scheme, constructed from combinations of four key traits that represent four classes of species' responses to disturbances. Using model results and field observations from sites affected by two highly different disturbances, we demonstrated that popular dichotomous trade-offs are not sufficient to explain community dynamics, even if some emerge under certain conditions. Without disturbances, competition was only sufficient to predict species survival but not relative success, which required some escape mechanism (e.g., long-term dormancy). With highly predictable and large-scale disturbances, successful species showed a combination of high individual tolerance to disturbance and, more surprisingly, high competitive ability. When disturbances were less predictable, high individual tolerance and long-term seed dormancy were favored, due to higher environmental uncertainty. Our study demonstrates that theories relying on a small number of predefined trade-offs among traits (e.g., competition-colonization trade-off) may lead to unrealistic results. We suggest that the understanding of disturbance-community relationships can be significantly improved by employing sets of relevant trait assemblies instead of the currently common approach in which trade-offs are assumed in advance.

Root plasticity buffers competition among plants: theory meets experimental data.

Morphological plasticity is a striking characteristic of plants in natural communities. In the context of foraging behavior particularly, root plasticity has been documented for numerous species. Root plasticity is known to mitigate competitive interactions by reducing the overlap of the individuals' rhizospheres. But despite its obvious effect on resource acquisition, plasticity has been generally neglected in previous empirical and theoretical studies estimating interaction intensity among plants. In this study, we developed a semi-mechanistic model that addresses this shortcoming by introducing the idea of compensatory growth into the classical-zone-of influence (ZOI) and field-of-neighborhood (FON) approaches. The model parameters describing the belowground plastic sphere of influence (PSI) were parameterized using data from an accompanying field experiment. Measurements of the uptake of a stable nutrient analogue at distinct distances to the neighboring plants showed that the study species responded plastically to belowground competition by avoiding overlap of individuals' rhizospheres. An unexpected finding was that the sphere of influence of the study species Bromus hordeaceus could be best described by a unimodal function of distance to the plant's center and not with a continuously decreasing function as commonly assumed. We employed the parameterized model to investigate the interplay between plasticity and two other important factors determining the intensity of competitive interactions: overall plant density and the distribution of individuals in space. The simulation results confirm that the reduction of competition intensity due to morphological plasticity strongly depends on the spatial structure of the competitive environment. We advocate the use of semi-mechanistic simulations that explicitly consider morphological plasticity to improve our mechanistic understanding of plant interactions.

Is the cask of facilitation ready for bottling? A symposium on the connectivity and future directions of positive plant interactions.

The 2009 British Ecological Society's Annual Symposium entitled 'Facilitation in Plant Communities' was held at the University of Aberdeen, Scotland, from 20 to 22 April 2009. This was the first ever international meeting dedicated to the rapidly expanding field of facilitation. The aim of the symposium was to assess the current 'state-of-play' by contrasting findings from different systems and by looking outwards in an attempt to integrate this field with other related fields. It was also aimed at understanding how knowledge of facilitation can help understand community dynamics and be applied to ecosystem restoration. The symposium identified several key areas where future work is likely to be most profitable.

Limited evolutionary rescue of locally adapted populations facing climate change.

Dispersal is a key determinant of a population's evolutionary potential. It facilitates the propagation of beneficial alleles throughout the distributional range of spatially outspread populations and increases the speed of adaptation. However, when habitat is heterogeneous and individuals are locally adapted, dispersal may, at the same time, reduce fitness through increasing maladaptation. Here, we use a spatially explicit, allelic simulation model to quantify how these equivocal effects of dispersal affect a population's evolutionary response to changing climate. Individuals carry a diploid set of chromosomes, with alleles coding for adaptation to non-climatic environmental conditions and climatic conditions, respectively. Our model results demonstrate that the interplay between gene flow and habitat heterogeneity may decrease effective dispersal and population size to such an extent that substantially reduces the likelihood of evolutionary rescue. Importantly, even when evolutionary rescue saves a population from extinction, its spatial range following climate change may be strongly narrowed, that is, the rescue is only partial. These findings emphasize that neglecting the impact of non-climatic, local adaptation might lead to a considerable overestimation of a population's evolvability under rapid environmental change.

An open source simulation model for soil and sediment bioturbation.

Bioturbation is one of the most widespread forms of ecological engineering and has significant implications for the structure and functioning of ecosystems, yet our understanding of the processes involved in biotic mixing remains incomplete. One reason is that, despite their value and utility, most mathematical models currently applied to bioturbation data tend to neglect aspects of the natural complexity of bioturbation in favour of mathematical simplicity. At the same time, the abstract nature of these approaches limits the application of such models to a limited range of users. Here, we contend that a movement towards process-based modelling can improve both the representation of the mechanistic basis of bioturbation and the intuitiveness of modelling approaches. In support of this initiative, we present an open source modelling framework that explicitly simulates particle displacement and a worked example to facilitate application and further development. The framework combines the advantages of rule-based lattice models with the application of parameterisable probability density functions to generate mixing on the lattice. Model parameters can be fitted by experimental data and describe particle displacement at the spatial and temporal scales at which bioturbation data is routinely collected. By using the same model structure across species, but generating species-specific parameters, a generic understanding of species-specific bioturbation behaviour can be achieved. An application to a case study and comparison with a commonly used model attest the predictive power of the approach.