Integrating learning into animal range dynamics under rapid human-induced environmental change.

Human-induced rapid environmental change (HIREC) is creating environments deviating considerably from natural habitats in which species evolved. Concurrently, climate warming is pushing species' climatic envelopes to geographic regions that offer novel ecological conditions. The persistence of species is likely affected by the interplay between the degree of ecological novelty and phenotypic plasticity, which in turn may shape an organism's range-shifting ability. Current modelling approaches that forecast animal ranges are characterized by a static representation of the relationship between habitat use and fitness, which may bias predictions under conditions imposed by HIREC. We argue that accounting for dynamic species-resource relationships can increase the ecological realism of range shift predictions. Our rationale builds on the concepts of ecological fitting, the process whereby individuals form successful novel biotic associations based on the suite of traits they carry at the time of encountering the novel condition, and behavioural plasticity, in particular learning. These concepts have revolutionized our view on fitness in novel ecological settings, and the way these processes may influence species ranges under HIREC. We have integrated them into a model of range expansion as a conceptual proof of principle highlighting the potentially substantial role of learning ability in range shifts under HIREC.

Impact of Phylogenetic Tree Completeness and Mis-specification of Sampling Fractions on Trait Dependent Diversification Models.

Understanding the origins of diversity and the factors that drive some clades to be more diverse than others are important issues in evolutionary biology. Sophisticated SSE (state-dependent speciation and extinction) models provide insights into the association between diversification rates and the evolution of a trait. The empirical data used in SSE models and other methods is normally imperfect, yet little is known about how this can affect these models. Here, we evaluate the impact of common phylogenetic issues on inferences drawn from SSE models. Using simulated phylogenetic trees and trait information, we fitted SSE models to determine the effects of sampling fraction (phylogenetic tree completeness) and sampling fraction mis-specification on model selection and parameter estimation (speciation, extinction, and transition rates) under two sampling regimes (random and taxonomically biased). As expected, we found that both model selection and parameter estimate accuracies are reduced at lower sampling fractions (i.e., low tree completeness). Furthermore, when sampling of the tree is imbalanced across sub-clades and tree completeness is ≤ 60%, rates of false positives increase and parameter estimates are less accurate, compared to when sampling is random. Thus, when applying SSE methods to empirical datasets, there are increased risks of false inferences of trait dependent diversification when some sub-clades are heavily under-sampled. Mis-specifying the sampling fraction severely affected the accuracy of parameter estimates: parameter values were over-estimated when the sampling fraction was specified as lower than its true value, and under-estimated when the sampling fraction was specified as higher than its true value. Our results suggest that it is better to cautiously under-estimate sampling efforts, as false positives increased when the sampling fraction was over-estimated. We encourage SSE studies where the sampling fraction can be reasonably estimated and provide recommended best practices for SSE modeling. [Trait dependent diversification; SSE models; phylogenetic tree completeness; sampling fraction.].

Experimental evolution of dispersal: Unifying theory, experiments and natural systems.

Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of populations and communities. The recent use of experimental evolution for the study of dispersal is a promising avenue for demonstrating valuable proofs of concept, bringing insight into alternative dispersal strategies and trade-offs, and testing the repeatability of evolutionary outcomes. Practical constraints restrict experimental evolution studies of dispersal to a set of typically small, short-lived organisms reared in artificial laboratory conditions. Here, we argue that despite these restrictions, inferences from these studies can reinforce links between theoretical predictions and empirical observations and advance our understanding of the eco-evolutionary consequences of dispersal. We illustrate how applying an integrative framework of theory, experimental evolution and natural systems can improve our understanding of dispersal evolution under more complex and realistic biological scenarios, such as the role of biotic interactions and complex dispersal syndromes.

Safeguarding Imperiled Biodiversity and Evolutionary Processes in the Wallacea Center of Endemism.

Wallacea-the meeting point between the Asian and Australian fauna-is one of the world's largest centers of endemism. Twenty-three million years of complex geological history have given rise to a living laboratory for the study of evolution and biodiversity, highly vulnerable to anthropogenic pressures. In the present article, we review the historic and contemporary processes shaping Wallacea's biodiversity and explore ways to conserve its unique ecosystems. Although remoteness has spared many Wallacean islands from the severe overexploitation that characterizes many tropical regions, industrial-scale expansion of agriculture, mining, aquaculture and fisheries is damaging terrestrial and aquatic ecosystems, denuding endemics from communities, and threatening a long-term legacy of impoverished human populations. An impending biodiversity catastrophe demands collaborative actions to improve community-based management, minimize environmental impacts, monitor threatened species, and reduce wildlife trade. Securing a positive future for Wallacea's imperiled ecosystems requires a fundamental shift away from managing marine and terrestrial realms independently.

Modelling the responses of partially migratory metapopulations to changing seasonal migration rates: From theory to data.

Among-individual and within-individual variation in expression of seasonal migration versus residence is widespread in nature and could substantially affect the dynamics of partially migratory metapopulations inhabiting seasonally and spatially structured environments. However, such variation has rarely been explicitly incorporated into metapopulation dynamic models for partially migratory systems. We, therefore, lack general frameworks that can identify how variable seasonal movements, and associated season- and location-specific vital rates, can control system persistence. We constructed a novel conceptual framework that captures full-annual-cycle dynamics and key dimensions of metapopulation structure for partially migratory species inhabiting seasonal environments. We conceptualize among-individual variation in seasonal migration as two variable vital rates: seasonal movement probability and associated movement survival probability. We conceptualize three levels of within-individual variation (i.e. plasticity), representing seasonal or annual variation in seasonal migration or lifelong fixed strategies. We formulate these concepts as a general matrix model, which is customizable for diverse life-histories and seasonal landscapes. To illustrate how variable seasonal migration can affect metapopulation growth rate, demographic structure and vital rate elasticities, we parameterize our general models for hypothetical short- and longer-lived species. Analyses illustrate that elasticities of seasonal movement probability and associated survival probability can sometimes equal or exceed those of vital rates typically understood to substantially influence metapopulation dynamics (i.e. seasonal survival probability or fecundity), that elasticities can vary non-linearly, and that metapopulation outcomes depend on the level of within-individual plasticity. We illustrate how our general framework can be applied to evaluate the consequences of variable and changing seasonal movement probability by parameterizing our models for a real partially migratory metapopulation of European shags Gulosus aristotelis assuming lifelong fixed strategies. Given observed conditions, metapopulation growth rate was most elastic to breeding season adult survival of the resident fraction in the dominant population. However, given doubled seasonal movement probability, variation in survival during movement would become the primary driver of metapopulation dynamics. Our general conceptual and matrix model frameworks, and illustrative analyses, thereby highlight complex ways in which structured variation in seasonal migration can influence dynamics of partially migratory metapopulations, and pave the way for diverse future theoretical and empirical advances.

What you see is where you go: visibility influences movement decisions of a forest bird navigating a three-dimensional-structured matrix.

Animal spatial behaviour is often presumed to reflect responses to visual cues. However, inference of behaviour in relation to the environment is challenged by the lack of objective methods to identify the information that effectively is available to an animal from a given location. In general, animals are assumed to have unconstrained information on the environment within a detection circle of a certain radius (the perceptual range; PR). However, visual cues are only available up to the first physical obstruction within an animal's PR, making information availability a function of an animal's location within the physical environment (the effective visual perceptual range; EVPR). By using LiDAR data and viewshed analysis, we modelled forest birds' EVPRs at each step along a movement path. We found that the EVPR was on average 0.063% that of an unconstrained PR and, by applying a step-selection analysis, that individuals are 1.55 times more likely to move to a tree within their EVPR than to an equivalent tree outside it. This demonstrates that behavioural choices can be substantially impacted by the characteristics of an individual's EVPR and highlights that inferences made from movement data may be improved by accounting for the EVPR.

Maladapted Prey Subsidize Predators and Facilitate Range Expansion.

Dispersal of prey from predator-free patches frequently supplies a trophic subsidy to predators by providing more prey than are produced locally. Prey arriving from predator-free patches might also have evolved weaker defenses against predators and thus enhance trophic subsidies by providing easily captured prey. Using local models assuming a linear or accelerating trade-off between defense and population growth rate, we demonstrate that immigration of undefended prey increased predator abundances and decreased defended prey through eco-evolutionary apparent competition. In individual-based models with spatial structure, explicit genetics, and gene flow along an environmental gradient, prey became maladapted to predators at the predator's range edge, and greater gene flow enhanced this maladaptation. The predator gained a subsidy from these easily captured prey, which enhanced its abundance, facilitated its persistence in marginal habitats, extended its range extent, and enhanced range shifts during environmental changes, such as climate change. Once the predator expanded, prey adapted to it and the advantage disappeared, resulting in an elastic predator range margin driven by eco-evolutionary dynamics. Overall, the results indicate a need to consider gene flow-induced maladaptation and species interactions as mutual forces that frequently determine ecological and evolutionary dynamics and patterns in nature.

Models of Dispersal Evolution Highlight Several Important Issues in Evolutionary and Ecological Modeling.

Previous results showing that lack of information on local population density leads to higher emigration probabilities in unpredictable environments but to lower emigration probabilities in constant or highly predictable scenarios have recently been challenged by Poethke et al. By reimplementing both our model and that of Poethke and colleagues, we demonstrate that our original results indeed hold to the presented critiques and do not contradict previous findings. The comment by Poethke and colleagues does, however, present potentially intriguing results suggesting that negative density-dependent dispersal evolves under white noise for some model formulations. Here, through intermodel comparison, we seek to better understand the source of the differences in results obtained in our study and theirs. We conclude that the apparent negative density dependence reported by Poethke et al. is effectively density independence and that the shape of the reaction norm they obtain is a model artefact. Further, this response provides an opportunity to elaborate on some important issues in evolutionary and ecological modeling regarding (i) the importance of carefully considering different models' assumptions in comparisons among models, (ii) the need to consider the role of stochasticity and uncertainty when presenting and interpreting results from stochastic individual-based models, (iii) the adequate choice of the underlying ecological model that creates the selective pressures determining the evolution of behavioral reaction norms, and (iv) the appropriate choice of mutation models.

The Evolution of Male-Biased Dispersal under the Joint Selective Forces of Inbreeding Load and Demographic and Environmental Stochasticity.

Sex-biased natal dispersal is widespread, and its significance remains a central question in evolutionary biology. However, theory so far fails to predict some of the most common patterns found in nature. To address this, we present novel results from an individual-based model investigating the joint roles of inbreeding load, demographic stochasticity, environmental stochasticity, and dispersal costs for the evolution of sex-biased dispersal. Most strikingly, we found that male-biased natal dispersal evolved in polygynous systems as a result of the interplay between inbreeding avoidance and stochasticity, whereas previous theory, in contrast to empirical observations, predicted male philopatry and female-biased natal dispersal under inbreeding load alone. Furthermore, the direction of the bias varied according to the nature of stochasticity. Our results therefore provide a unification of previous theory, yielding a much better qualitative match with empirical observations of male-biased dispersal in mate defense mating systems.

A trait-based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?

Estimating population spread rates across multiple species is vital for projecting biodiversity responses to climate change. A major challenge is to parameterise spread models for many species. We introduce an approach that addresses this challenge, coupling a trait-based analysis with spatial population modelling to project spread rates for 15 000 virtual mammals with life histories that reflect those seen in the real world. Covariances among life-history traits are estimated from an extensive terrestrial mammal data set using Bayesian inference. We elucidate the relative roles of different life-history traits in driving modelled spread rates, demonstrating that any one alone will be a poor predictor. We also estimate that around 30% of mammal species have potential spread rates slower than the global mean velocity of climate change. This novel trait-space-demographic modelling approach has broad applicability for tackling many key ecological questions for which we have the models but are hindered by data availability.

Mutation accumulation and the formation of range limits.

The dynamics of range formation are important for understanding and predicting species distributions. Here, we focus on a process that has thus far been overlooked in the context of range formation; the accumulation of mutation load. We find that mutation accumulation severely reduces the extent of a range across an environmental gradient, especially when dispersal is limited, growth rate is low and mutations are of intermediate deleterious effect. Our results illustrate the important role deleterious mutations can play in range formation. We highlight this as a necessary focus for further work, noting particularly the potentially conflicting effects dispersal may have in reducing mutation load and simultaneously increasing migration load in marginal populations.

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.

Predictive systems ecology.

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

Ideal free distribution of fixed dispersal phenotypes in a wing dimorphic beetle in heterogeneous landscapes.

According to the ideal free distribution (IFD) theory, individuals that are able to perceive the quality of different patches in a landscape and disperse freely are expected to redistribute themselves proportionally to the carrying capacities of heterogeneous patches. Here, we argue that, when dispersal is unconditional and genetically fixed, a coalition of sedentary and dispersing phenotypes can attain an IFD under spatiotemporally uncorrelated variation in fitness. This not only leads to a stable polymorphism of both dispersal phenotypes, but also implies that the number of dispersing individuals should on average be equal among patches and determined by the carrying capacity of the smallest local populations in the landscape. Differences in carrying capacity among patches are thus only reflected by changes in the number of sedentary individuals. Individual-based simulations show that this mechanism can be generalized over a wide range of spatiotemporal conditions and dispersal strategies. Moreover, these expectations are in strong agreement with empirical data on the density of both dispersal phenotypes of the wing dimorphic ground beetle Pterostichus vernalis within and among 10 different landscapes. Hence, for the first time, these results demonstrate that this mechanism serves as a plausible alternative to the competition-colonization model to explain the spatial distribution of fixed dispersal phenotypes in heterogeneous landscapes. Understanding of the frequency distributions of individuals expressing discrete dispersal morphs moreover improves our predictive and management capabilities for a broad range of species, for which we currently typically rely on using mean dispersal rates.

Eco-evolutionary dynamics of range shifts: elastic margins and critical thresholds.

It is widely recognised that the response of a population to environmental change will be determined by the eco-evolutionary dynamics of dispersal. Here, modelling the evolution of dispersal distance within a species structured across an environmental gradient yields some important general insights. First, it demonstrates that 'elastic' ranges are more likely features of range-shifting dynamics than has been recently reported; when dispersal distance, rather than simply emigration rate, is modelled elastic ranges occur regardless of the nature of the environmental gradient. Second, we start to identify critical survival thresholds beyond which even the evolution of greater dispersal distance is unlikely to rescue a population. The position of such thresholds depends on a combination of genetic, demographic and environmental parameters. We find simulated species rarely survive if the location of the range front of a range-shift falls behind the optimal environmental conditions of the species. Should similar thresholds exist for real species aggressive conservation actions such as assisted colonisation are likely to be required to reduce the risk of extinction. We believe simple models, such as the one presented in this study, will be essential for providing a theoretical underpinning for more tactical eco-evolutionary models and informing conservation strategies to be employed under rapid climate change.

When do young birds disperse? Tests from studies of golden eagles in Scotland.

BACKGROUND: Dispersal comprises three broad stages - departure from the natal or breeding locations, subsequent travel, and settlement. These stages are difficult to measure, and vary considerably between sexes, age classes, individuals and geographically. We used tracking data from 24 golden eagles, fitted with long-lived GPS satellite transmitters as nestlings, which we followed during their first year. We estimated the timing of emigration from natal sites using ten previously published methods. We propose and evaluate two new methods. The first of these uses published ranging distances of parents as a measure of the natal home range, with the requirement that juveniles must exceed it for a minimum of 10 days (a literature-based measure of the maximum time that a juvenile can survive without food from its parents). The second method uses the biggest difference in the proportion of locations inside and outside of the natal home range smoothed over a 30 day period to assign the point of emigration. We used the latter as the standard against which we compared the ten published methods. RESULTS: The start of golden eagle dispersal occurred from 39 until 250 days after fledging (based on method 12). Previously published methods provided very different estimates of the point of emigration with a general tendency for most to apparently assign it prematurely. By contrast the two methods we proposed provided very similar estimates for the point of emigration that under visual examination appeared to fit the definition of emigration much better. CONCLUSIONS: We have used simple methods to decide when an individual has dispersed - they are rigorous and repeatable. Despite one method requiring much more information, both methods provided robust estimates for when individuals emigrated at the start of natal dispersal. Considerable individual variation in recorded behaviour appears to account for the difficulty capturing the point of emigration and these results demonstrate the potential pitfalls associated with species exhibiting complex dispersal behaviour. We anticipate that coupled with the rapidly increasing availability of tracking data, our new methods will, for at least some species, provide a far simpler and more biologically representative approach to determine the timing of emigration.

Uncertainty and the role of information acquisition in the evolution of context-dependent emigration.

There is increasing empirical evidence that individuals utilize social and environmental cues in making decisions as to whether or not to disperse. However, we lack theory exploring the influence of information acquisition and use on the evolution of dispersal strategies and metapopulation dynamics. We used an individual-based, spatially explicit simulation model to explore the evolution of emigration strategies under varying precision of information about the natal patch, cost of information acquisition, and environmental predictability. Our findings show an interesting interplay between information use and the evolved emigration propensity. Lack of information led to higher emigration probabilities in more unpredictable environments but to lower emigration probabilities in constant or highly predictable scenarios. Somewhat-informed dispersal strategies were selected for in most cases, even when the acquisition of information was associated with a moderate reproductive cost. Notably, selection rarely favored investment in acquisition of high-precision information, and the tendency to invest in information acquisition was greatest in predictable environments when the associated cost was low. Our results highlight that information use can affect dispersal in a complex manner and also emphasize that information-acquisition behaviors can themselves come under strong selection, resulting in evolutionary dynamics that are tightly coupled to those of context-dependent behaviors.

Reconstruction of State-Dependent Diversification: Integrating Phenotypic Traits into Molecular Phylogenies.

The relative contribution of speciation and extinction into current diversity is certainly unknown, but mathematical frameworks that use genetic information have been developed to provide estimates of these processes. To that end, it is necessary to reconstruct molecular phylogenetic trees which summarize ancestor-descendant relationships as well as the timing of evolutionary events (i.e., rates). Nevertheless, diversification models show poor fit when assuming that single rate of speciation/extinction is constant over time and across lineages: species exhibit such a great variation in features that it is unlikely they give birth and die at the same pace. The state-dependent diversification framework (SSE) reconciles the species phenotypic variation with heterogeneous rates of diversification observed in a clade. This family of models allows testing contrasting hypotheses on mode of speciation, trait evolution, and its influence on speciation/extinction regimes. Although microbial species richness outnumbers diversity in plants and animals, diversification models are underused in microbiology. Here, we introduce microbiologists to models that estimate diversification rates and provide a detailed description of SSE models. Besides theoretical principles underlying the method, we also show how SSE analysis should be set up in R. We use pH evolution in Thaumarchaeota to explain its evolutionary dynamic in the light of SSE model. We hope this chapter spurs the study of trait evolution and evolutionary outcomes in microorganisms.

Thermal conditions during juvenile development affect adult dispersal in a spider.

Understanding the causes and consequences of dispersal is a prerequisite for the effective management of natural populations. Rather than treating dispersal as a fixed trait, it should be considered a plastic process that responds to both genetic and environmental conditions. Here, we consider how the ambient temperature experienced by juvenile Erigone atra, a spider inhabiting crop habitat, influences adult dispersal. This species exhibits 2 distinct forms of dispersal, ballooning (long distance) and rappelling (short distance). Using a half-sib design we raised individuals under 4 different temperature regimes and quantified the spiders' propensity to balloon and to rappel. Additionally, as an indicator of investment in settlement, we determined the size of the webs build by the spiders following dispersal. The optimal temperature regimes for reproduction and overall dispersal investment were 20 degrees C and 25 degrees C. Propensity to perform short-distance movements was lowest at 15 degrees C, whereas for long-distance dispersal it was lowest at 30 degrees C. Plasticity in dispersal was in the direction predicted on the basis of the risks associated with seasonal changes in habitat availability; long-distance ballooning occurred more frequently under cooler, spring-like conditions and short-distance rappelling under warmer, summer-like conditions. Based on these findings, we conclude that thermal conditions during development provide juvenile spiders with information about the environmental conditions they are likely to encounter as adults and that this information influences the spider's dispersal strategy. Climate change may result in suboptimal adult dispersal behavior, with potentially deleterious population level consequences.

Prospecting and informed dispersal: Understanding and predicting their joint eco-evolutionary dynamics.

The ability of individuals to leave a current breeding area and select a future one is important, because such decisions can have multiple consequences for individual fitness, but also for metapopulation dynamics, structure, and long-term persistence through non-random dispersal patterns. In the wild, many colonial and territorial animal species display informed dispersal strategies, where individuals use information, such as conspecific breeding success gathered during prospecting, to decide whether and where to disperse. Understanding informed dispersal strategies is essential for relating individual behavior to subsequent movements and then determining how emigration and settlement decisions affect individual fitness and demography. Although numerous theoretical studies have explored the eco-evolutionary dynamics of dispersal, very few have integrated prospecting and public information use in both emigration and settlement phases. Here, we develop an individual-based model that fills this gap and use it to explore the eco-evolutionary dynamics of informed dispersal. In a first experiment, in which only prospecting evolves, we demonstrate that selection always favors informed dispersal based on a low number of prospected patches relative to random dispersal or fully informed dispersal, except when individuals fail to discriminate better patches from worse ones. In a second experiment, which allows the concomitant evolution of both emigration probability and prospecting, we show the same prospecting strategy evolving. However, a plastic emigration strategy evolves, where individuals that breed successfully are always philopatric, while failed breeders are more likely to emigrate, especially when conspecific breeding success is low. Embedding information use and prospecting behavior in eco-evolutionary models will provide new fundamental understanding of informed dispersal and its consequences for spatial population dynamics.