A macroecological approach to evolutionary rescue and adaptation to climate change

Despite the widespread use of ecological niche models (ENMs) for predicting the responses of species to climate change, these models do not explicitly incorporate any population‐level mechanism. On the other hand, mechanistic models adding population processes (e.g. biotic interactions, dispersal and adaptive potential to abiotic conditions) are much more complex and difficult to parameterize, especially if the goal is to predict range shifts for many species simultaneously. In particular, the adaptive potential (based on genetic adaptations, phenotypic plasticity and behavioral adjustments for physiological responses) of local populations has been a less studied mechanism affecting species’ responses to climatic change so far. Here, we discuss and apply an alternative macroecological framework to evaluate the potential role of evolutionary rescue under climate change based on ENMs. We begin by reviewing eco‐evolutionary models that evaluate the maximum sustainable evolutionary rate under a scenario of environmental change, showing how they can be used to understand the impact of temperature change on a Neotropical anuran species, the Schneider's toad Rhinella diptycha. Then we show how to evaluate spatial patterns of species’ geographic range shift using such models, by estimating evolutionary rates at the trailing edge of species distribution estimated by ENMs and by recalculating the relative amount of total range loss under climate change. We show how different models can reduce the expected range loss predicted for the studied species by potential ecophysiological adaptations in some regions of the trailing edge predicted by ENMs. For general applications, we believe that parameters for large numbers of species and populations can be obtained from macroecological generalizations (e.g. allometric equations and ecogeographical rules), so our framework coupling ENMs with eco‐evolutionary models can be applied to achieve a more accurate picture of potential impacts from climate change and other threats to biodiversity.     

Combining field experiments and individual-based modeling to identify the dynamically relevant organizational scale in a field system

Community ecologists continually strive to build analytical models that realistically describe long‐term dynamics of the systems they study. A key step in this process is identifying which details are relevant for predicting dynamics. Currently, this remains a limiting step in development of analytical theory because experimental field ecology, which provides the key empirical insight, and theoretical ecology, which translates empirical knowledge into analytical theory, remain weakly linked. I illustrate how an individual‐based computational model of species interactions is a useful way to bridge the gulf between empirical research and theory development. I built a computational model that reproduced key natural history and biological detail of an old‐field interaction web composed of a predator species, a herbivore species and two plant groups that had been the subject of extensive previous field research. I examined, using simulation experiments, how individual behavior of herbivores in response to changing resource and predator abundance scaled to long‐term population‐level and community‐level dynamics. The simulation experiments revealed that the long‐term community dynamics could be highly predictable because of two counterintuitive reasons. First, seasonality was a strong forcing variable on the system that removed the possibility of serial dependence in population abundance over time. Second, because of seasonality, short‐term behavioral responses of herbivores played a much stronger role in shaping community structure than longer‐term processes such as density responses. So, simply knowing the short‐term responses of herbivores at the evolutionary ecological level was sufficient to forecast the long‐term outcome of experimental manipulations. This study shows that an individual‐based model, once it is calibrated to the real‐world field system, can provide key insight into the biological detail that analytical models should include to predict long‐term dynamics.     

Phylogenetic approaches for studying diversification

Estimating rates of speciation and extinction, and understanding how and why they vary over evolutionary time, geographical space and species groups, is a key to understanding how ecological and evolutionary processes generate biological diversity. Such inferences will increasingly benefit from phylogenetic approaches given the ever‐accelerating rates of genetic sequencing. In the last few years, models designed to understand diversification from phylogenetic data have advanced significantly. Here, I review these approaches and what they have revealed about diversification in the natural world. I focus on key distinctions between different models, and I clarify the conclusions that can be drawn from each model. I identify promising areas for future research. A major challenge ahead is to develop models that more explicitly take into account ecology, in particular the interaction of species with each other and with their environment. This will not only improve our understanding of diversification; it will also present a new perspective to the use of phylogenies in community ecology, the science of interaction networks and conservation biology, and might shift the current focus in ecology on equilibrium biodiversity theories to non‐equilibrium theories recognising the crucial role of history.     

Towards robust evolutionary inference with integral projection models

Integral projection models (IPMs) are extremely flexible tools for ecological and evolutionary inference. IPMs track the distribution of phenotype in populations through time, using functions describing phenotype‐dependent development, inheritance, survival and fecundity. For evolutionary inference, two important features of any model are the ability to (i) characterize relationships among traits (including values of the same traits across ages) within individuals, and (ii) characterize similarity between individuals and their descendants. In IPM analyses, the former depends on regressions of observed trait values at each age on values at the previous age (development functions), and the latter on regressions of offspring values at birth on parent values as adults (inheritance functions). We show analytically that development functions, characterized this way, will typically underestimate covariances of trait values across ages, due to compounding of regression to the mean across projection steps. Similarly, we show that inheritance, characterized this way, is inconsistent with a modern understanding of inheritance, and underestimates the degree to which relatives are phenotypically similar. Additionally, we show that the use of a constant biometric inheritance function, particularly with a constant intercept, is incompatible with evolution. Consequently, current implementations of IPMs will predict little or no phenotypic evolution, purely as artefacts of their construction. We present alternative approaches to constructing development and inheritance functions, based on a quantitative genetic approach, and show analytically and through an empirical example on a population of bighorn sheep how they can potentially recover patterns that are critical to evolutionary inference.     

Toward a conceptual synthesis for climate change responses

Aim To identify hypotheses for how climate change affects long‐term population persistence that can be used as a framework for future syntheses of ecological responses to climate change. Location Global. Methods We surveyed ecological and evolutionary concepts related to how a changing climate might alter population persistence. We organized established concepts into a two‐stage framework that relates abiotic change to population persistence via changes in the rates or outcomes of ecological and evolutionary processes. We surveyed reviews of climate change responses, and evaluated patterns in light of our conceptual framework. Results We classified hypotheses for population responses to climate change as one of two types: (1) hypotheses that relate rates of ecological and evolutionary processes (plasticity, dispersal, population growth and evolution) to abiotic change, and (2) hypotheses that relate changes in these processes to four fundamental population‐level responses (colonization, acclimatization, adaptation or extinction). We found that a disproportionate emphasis on response in the climate change literature is difficult to reconcile with ecological and evolutionary theories that emphasize processes. We discuss a set of 24 hypotheses that represent gaps in the literature that limit our ability determine whether observed climate change responses are sufficient to facilitate persistence through future climate change. Main conclusions Though theory relates environmental change to fundamental ecological and evolutionary processes and population‐level responses, clear hypotheses based on theory have not been systematically formulated and tested in the context of climate change. Stronger links between basic theory and observed impacts of climate change are required to assess which responses are common, likely or able to facilitate population persistence despite ongoing environmental change. We anticipate that a hypothesis‐testing framework will reveal that indirect effects of climate change responses are more pervasive than previously thought and related to a few general processes, even though the patterns they create are incredibly diverse.     

Perturbation approaches for integral projection models

Perturbation analysis of population models is fundamental to elucidating mechanisms of population dynamics and examining scenarios of change. The use of integral projection models (IPMs) has increased in the last decade, and while many of the tools and approaches developed for matrix models remain relevant, the nature of IPMs expands the framework of perturbation analysis, with different approaches often requiring important considerations. This article provides a review of – and practical guide to – different perturbation approaches for IPMs, formalizes methodologies for perturbing IPM size transition probabilities, and highlights areas where researchers should be particularly careful and critical when conducting and interpreting perturbation analysis. I use a simulated dataset to compare five hierarchical perturbation approaches for IPMs found within 63 published studies, and apply a combination of approaches to the example of an invasive perennial plant. Other perturbation approaches for IPMs are also highlighted. Most perturbation analyses for IPMs to date have focused on the response of the asymptotic population growth rate (λ) to changes in elements of the discretized projection kernel and/or the growth– survival and reproduction– recruitment sub‐kernels. Perturbations to vital rate functions and regression predictions underlying these kernels provide mechanistic insight, but are less common and can require important considerations regarding the perturbation of size transitions separate from survival and the nature of the state variable (used to represent size). The second most common approach is more specific to IPMs and examines the influence of vital rate regression parameters, each of which can have broad influence on the population growth rate. Researchers using IPMs have many perturbation options available and should carefully consider which approach or combination of approaches is most applicable and interpretable for their specific questions.     

A life‐history perspective on the demographic drivers of structured population dynamics in changing environments

Current understanding of life‐history evolution and how demographic parameters contribute to population dynamics across species is largely based on assumptions of either constant environments or stationary environmental variation. Meanwhile, species are faced with non‐stationary environmental conditions (changing mean, variance, or both) created by climate and landscape change. To close the gap between contemporary reality and demographic theory, we develop a set of transient life table response experiments (LTREs) for decomposing realised population growth rates into contributions from specific vital rates and components of population structure. Using transient LTREs in a theoretical framework, we reveal that established concepts in population biology will require revision because of reliance on approaches that do not address the influence of unstable population structure on population growth and mean fitness. Going forward, transient LTREs will enhance understanding of demography and improve the explanatory power of models used to understand ecological and evolutionary dynamics.     

Toward an integration of evolutionary biology and ecosystem science

At present, the disciplines of evolutionary biology and ecosystem science are weakly integrated. As a result, we have a poor understanding of how the ecological and evolutionary processes that create, maintain, and change biological diversity affect the flux of energy and materials in global biogeochemical cycles. The goal of this article was to review several research fields at the interfaces between ecosystem science, community ecology and evolutionary biology, and suggest new ways to integrate evolutionary biology and ecosystem science. In particular, we focus on how phenotypic evolution by natural selection can influence ecosystem functions by affecting processes at the environmental, population and community scale of ecosystem organization. We develop an eco-evolutionary model to illustrate linkages between evolutionary change (e.g. phenotypic evolution of producer), ecological interactions (e.g. consumer grazing) and ecosystem processes (e.g. nutrient cycling). We conclude by proposing experiments to test the ecosystem consequences of evolutionary changes.     

The contribution of evening primrose (<Emphasis Type="Italic">Oenothera biennis</Emphasis>) to a modern synthesis of evolutionary ecology

In this review, I consider the contribution that common evening primrose (Oenothera biennis) has made towards integrating the ecology, evolution and genetics of species interactions. Oenothera biennis was among the earliest plant models in genetics and cytogenetics and it played an important role in the modern synthesis of evolutionary biology. More recently, population and ecological genetics approaches have provided insight into the patterns of genetic variation within and between populations, and how a combination of abiotic and biotic factors maintain and select on heritable variation within O. biennis populations. From an ecological perspective, field experiments show that genetic variation and evolution within populations can have cascading effects throughout communities. Plant genotype affects the preference and performance of individual arthropod populations, as well as the composition, biomass, total abundance and diversity of arthropod species on plants. A combination of experiments and simulation models show that natural selection on specific plant traits can drive rapid ecological changes in these same community variables. At the patch level, increasing genotypic diversity leads to a greater abundance and diversity of omnivorous and predaceous arthropods, which is also associated with increased biomass and fecundity of plants in genetically diverse patches. Finally, in questioning whether a community genetics perspective is needed in biology, I review several multifactorial experiments which show that plant genotype often explains as much variation in community variables as other ecological factors typically identified as most important in ecology. As a whole, research in the O. biennis system has contributed to a more complete understanding of the dynamic interplay between ecology, evolution and genetics.     

Partitioning the effects of species loss on community variability using multi‐level selection theory

The temporal variability of ecological communities may depend on species richness and composition due to a variety of statistical and ecological mechanisms. However, ecologists currently lack a general, unified theoretical framework within which to compare the effects of these mechanisms. Developing such a framework is difficult because community variability depends not just on how species vary, but also how they covary, making it unclear how to isolate the contributions of individual species to community variability. Here I develop such a theoretical framework using the multi‐level Price equation, originally developed in evolutionary biology to partition the effects of group selection and individual selection. I show how the variability of a community can be related to the properties of the individual species comprising it, just as the properties of an evolving group can be related to the properties of the individual organisms comprising it. I show that effects of species loss on community variability can be partitioned into effects of species richness (random loss of species), effects of species composition (non‐random loss of species with respect to their variances and covariances), and effects of context dependence (post‐loss changes in species’ variances and covariances). I illustrate the application of this framework using data from the Biodiversity II experiment, and show that it leads to new conceptual and empirical insights. For instance, effects of species richness on community variability necessarily occur, but often are swamped by other effects, particularly context dependence.     

Assessing variation in life‐history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists

Mixed models are now well‐established methods in ecology and evolution because they allow accounting for and quantifying within‐ and between‐individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi‐modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life‐history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life‐history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long‐term studies of large mammals to illustrate the potential of using mixture models for assessing within‐population variation in life‐history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life‐history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users.     

Eco‐oncology: Applying ecological principles to understand and manage cancer

Cancer is a disease of single cells that expresses itself at the population level. The striking similarities between initiation and growth of tumors and dynamics of biological populations, and between metastasis and ecological invasion and community dynamics suggest that oncology can benefit from an ecological perspective to improve our understanding of cancer biology. Tumors can be viewed as complex, adaptive, and evolving systems as they are spatially and temporally heterogeneous, continually interacting with each other and with the microenvironment and evolving to increase the fitness of the cancer cells. We argue that an eco‐evolutionary perspective is essential to understand cancer biology better. Furthermore, we suggest that ecologically informed therapeutic approaches that combine standard of care treatments with strategies aimed at decreasing the evolutionary potential and fitness of neoplastic cells, such as disrupting cell‐to‐cell communication and cooperation, and preventing successful colonization of distant organs by migrating cancer cells, may be effective in managing cancer as a chronic condition.     

Finalism in Darwinian and Lamarckian Evolution: Lessons from Epigenetics and Developmental Biology

Finalist (teleological) implications have been described for both Darwinian and Lamarckian theories, even though finalism appears to be more commonly associated with Lamarckism. Biologists have focused on finding final causes to explain evolutionary novelties through, for example, applying the ??what for??? question to address experimental observations. Now epigenetics, together with developmental biology, may allow us to focus on the efficient causes leading to evolutionary change, asking the ??how??? question, considering environmental influences as inducers of genomic change. This is a whole under-studied dimension in evolutionary studies. In this paper, I discuss how epigenetics and developmental biology can help integrate two important ways in which the environment affects evolution: through inducing or through restricting the emergence of new phenotypes. I also discuss which aspects of both theories should be reconsidered in the face of current knowledge in epigenetics and where the emphasis of evolutionary experiments should be placed. Important goals of evolution related epigenetic studies should be: (i) to experimentally consider the separation among the origin of characters in a lineage and its further fixation, in order to address these processes in a proper dimension, (ii) to build the cause-effect relation between the factors inducing epigenetic changes and consequent changes in population parameters, and (iii) to consider that the arising of new characters is modulated by physiological and developmental constraints, and that this process is not related to a purpose or focused to solve an ecological, physiological or evolutionary challenge.     

The genomic basis of eco‐evolutionary dynamics

Recent recognition that ecological and evolutionary processes can operate on similar timescales has led to a rapid increase in theoretical and empirical studies on eco‐evolutionary dynamics. Progress in the fields of evolutionary biology, genomics and ecology is greatly enhancing our understanding of rapid adaptive processes, the predictability of adaptation and the genetics of ecologically important traits. However, progress in these fields has proceeded largely independently of one another. In an attempt to better integrate these fields, the centre for ‘Adaptation to a Changing Environment’ organized a conference entitled ‘The genomic basis of eco‐evolutionary change’ and brought together experts in ecological genomics and eco‐evolutionary dynamics. In this review, we use the work of the invited speakers to summarize eco‐evolutionary dynamics and discuss how they are relevant for understanding and predicting responses to contemporary environmental change. Then, we show how recent advances in genomics are contributing to our understanding of eco‐evolutionary dynamics. Finally, we highlight the gaps in our understanding of eco‐evolutionary dynamics and recommend future avenues of research in eco‐evolutionary dynamics.     

Between semelparity and iteroparity: Empirical evidence for a continuum of modes of parity

The number of times an organism reproduces (i.e., its mode of parity) is a fundamental life‐history character, and evolutionary and ecological models that compare the relative fitnesses of different modes of parity are common in life‐history theory and theoretical biology. Despite the success of mathematical models designed to compare intrinsic rates of increase (i.e., density‐independent growth rates) between annual‐semelparous and perennial‐iteroparous reproductive schedules, there is widespread evidence that variation in reproductive allocation among semelparous and iteroparous organisms alike is continuous. This study reviews the ecological and molecular evidence for the continuity and plasticity of modes of parity—that is, the idea that annual‐semelparous and perennial‐iteroparous life histories are better understood as endpoints along a continuum of possible strategies. I conclude that parity should be understood as a continuum of different modes of parity, which differ by the degree to which they disperse or concentrate reproductive effort in time. I further argue that there are three main implications of this conclusion: (1) that seasonality should not be conflated with parity; (2) that mathematical models purporting to explain the general evolution of semelparous life histories from iteroparous ones (or vice versa) should not assume that organisms can only display either an annual‐semelparous life history or a perennial‐iteroparous one; and (3) that evolutionary ecologists should base explanations of how different life‐history strategies evolve on the physiological or molecular basis of traits underlying different modes of parity.     

EFFECTS OF CLIMATE CHANGE ON GLOBAL SEAWEED COMMUNITIES

Seaweeds are ecologically important primary producers, competitors, and ecosystem engineers that play a central role in coastal habitats ranging from kelp forests to coral reefs. Although seaweeds are known to be vulnerable to physical and chemical changes in the marine environment, the impacts of ongoing and future anthropogenic climate change in seaweed‐dominated ecosystems remain poorly understood. In this review, we describe the ways in which changes in the environment directly affect seaweeds in terms of their physiology, growth, reproduction, and survival. We consider the extent to which seaweed species may be able to respond to these changes via adaptation or migration. We also examine the extensive reshuffling of communities that is occurring as the ecological balance between competing species changes, and as top‐down control by herbivores becomes stronger or weaker. Finally, we delve into some of the ecosystem‐level responses to these changes, including changes in primary productivity, diversity, and resilience. Although there are several key areas in which ecological insight is lacking, we suggest that reasonable climate‐related hypotheses can be developed and tested based on current information. By strategically prioritizing research in the areas of complex environmental variation, multiple stressor effects, evolutionary adaptation, and population, community, and ecosystem‐level responses, we can rapidly build upon our current understanding of seaweed biology and climate change ecology to more effectively conserve and manage coastal ecosystems.     

Mate choice in a changing world

Human activities by altering environmental conditions are influencing the mate choice of animals. This is by impacts on: (i) the production and expression of traits evaluated by mate choosers; (ii) the transmission of information about potential mates to choosers; (iii) the reception and processing of the information by choosers; and (iv) the final mate choice. Here, I first discuss how these four stages of the mate‐choice process can be altered by environmental change, and how these alterations, in turn, can influence individuals, populations, and communities. Much evidence exists for human‐induced environmental changes influencing mate choice, but the consequences for the fitness of courters and choosers are less well known, and even less is known about the impact on population dynamics, species interactions and community composition. More evidence exists for altered mate‐choice systems influencing interspecific matings and thereby community composition and biodiversity. I then consider whether plastic adjustments and evolutionary changes can rescue adaptive mate‐choice systems, and reflect on the possibility of non‐adaptive mate‐choice systems becoming less maladaptive under environmental change. Much evidence exists for plastic adjustments of mate‐choice systems, but whether these are adaptive is seldom known, as is the contribution of genetic changes. Finally, I contemplate the possibility of mate‐choice systems rescuing populations from decline in changing environments. I explain how this is context dependent with both positive and negative outcomes possible. In summary, while much evidence exists for human‐induced environmental changes influencing mate‐choice systems, less is known about the consequences for ecological and evolutionary processes. Considering the importance that mate choice plays in determining individual fitness and population viability, the effects of environmental change on mate‐choice systems should be considered in studies on the ecological and evolutionary consequences of human disturbances to habitats.     

Bioclimatic transect networks: Powerful observatories of ecological change

Transects that traverse substantial climate gradients are important tools for climate change research and allow questions on the extent to which phenotypic variation associates with climate, the link between climate and species distributions, and variation in sensitivity to climate change among biomes to be addressed. However, the potential limitations of individual transect studies have recently been highlighted. Here, we argue that replicating and networking transects, along with the introduction of experimental treatments, addresses these concerns. Transect networks provide cost‐effective and robust insights into ecological and evolutionary adaptation and improve forecasting of ecosystem change. We draw on the experience and research facilitated by the Australian Transect Network to demonstrate our case, with examples, to clarify how population‐ and community‐level studies can be integrated with observations from multiple transects, manipulative experiments, genomics, and ecological modeling to gain novel insights into how species and systems respond to climate change. This integration can provide a spatiotemporal understanding of past and future climate‐induced changes, which will inform effective management actions for promoting biodiversity resilience.     

Waddington redux: models and explanation in stem cell and systems biology

Stem cell biology and systems biology are two prominent new approaches to studying cell development. In stem cell biology, the predominant method is experimental manipulation of concrete cells and tissues. Systems biology, in contrast, emphasizes mathematical modeling of cellular systems. For scientists and philosophers interested in development, an important question arises: how should the two approaches relate? This essay proposes an answer, using the model of Waddington’s landscape to triangulate between stem cell and systems approaches. This simple abstract model represents development as an undulating surface of hills and valleys. Originally constructed by C. H. Waddington to visually explicate an integrated theory of genetics, development and evolution, the landscape model can play an updated unificatory role. I examine this model’s structure, representational assumptions, and uses in all three contexts, and argue that explanations of cell development require both mathematical models and concrete experiments. On this view, the two approaches are interdependent, with mathematical models playing a crucial but circumscribed role in explanations of cell development.     

Advances in ecological genomics in forest trees and applications to genetic resources conservation and breeding

Forest trees are an unparalleled group of organisms in their combined ecological, economic and societal importance. With widespread distributions, predominantly random mating systems and large population sizes, most tree species harbour extensive genetic variation both within and among populations. At the same time, demographic processes associated with Pleistocene climate oscillations and land‐use change have affected contemporary range‐wide diversity and may impinge on the potential for future adaptation. Understanding how these adaptive and neutral processes have shaped the genomes of trees species is therefore central to their management and conservation. As for many other taxa, the advent of high‐throughput sequencing methods is expected to yield an understanding of the interplay between the genome and environment at a level of detail and depth not possible only a few years ago. An international conference entitled ‘Genomics and Forest Tree Genetics’ was held in May 2016, in Arcachon (France), and brought together forest geneticists with a wide range of research interests to disseminate recent efforts that leverage contemporary genomic tools to probe the population, quantitative and evolutionary genomics of trees. An important goal of the conference was to discuss how such data can be applied to both genome‐enabled breeding and the conservation of forest genetic resources under land use and climate change. Here, we report discoveries presented at the meeting and discuss how the ecological genomic toolkit can be used to address both basic and applied questions in tree biology.