Predicting when climate‐driven phenotypic change affects population dynamics

Species' responses to climate change are variable and diverse, yet our understanding of how different responses (e.g. physiological, behavioural, demographic) relate and how they affect the parameters most relevant for conservation (e.g. population persistence) is lacking. Despite this, studies that observe changes in one type of response typically assume that effects on population dynamics will occur, perhaps fallaciously. We use a hierarchical framework to explain and test when impacts of climate on traits (e.g. phenology) affect demographic rates (e.g. reproduction) and in turn population dynamics. Using this conceptual framework, we distinguish four mechanisms that can prevent lower‐level responses from impacting population dynamics. Testable hypotheses were identified from the literature that suggest life‐history and ecological characteristics which could predict when these mechanisms are likely to be important. A quantitative example on birds illustrates how, even with limited data and without fully‐parameterized population models, new insights can be gained; differences among species in the impacts of climate‐driven phenological changes on population growth were not explained by the number of broods or density dependence. Our approach helps to predict the types of species in which climate sensitivities of phenotypic traits have strong demographic and population consequences, which is crucial for conservation prioritization of data‐deficient species.     

Physical maturation,life‐history classes and age estimates of free‐ranging western gorillas—insights from Mbeli Bai,Republic of Congo

Physical maturation and life‐history parameters are seen as evolutionary adaptations to different ecological and social conditions. Comparison of life‐history patterns of closely related species living in diverse environments helps to evaluate the validity of these assumptions but empirical data are lacking. The two gorilla species exhibit substantial differences in their environment, which allows investigation into the role of increased frugivory in shaping western gorilla life histories. We present behavioral and morphological data on western gorilla physical maturation and life‐history parameters from a 12.5‐year study at Mbeli Bai, a forest clearing in the Nouabalé‐Ndoki National Park in northern Congo. We assign photographs of known individuals to different life‐history classes and propose new age boundaries for life‐history classes in western gorillas, which can be used and tested at other western gorilla research sites. Our results show that western gorillas are weaned at a later age compared with mountain gorillas and indicate slower physical maturation of immatures. These findings support the risk‐aversion hypothesis for more frugivorous species. However, our methods need to be applied and tested with other gorilla populations. The slow life histories of western gorillas could have major consequences for social structure, mortality patterns and population growth rates that will affect recovery from population crashes of this critically endangered species. We emphasize that long‐term studies can provide crucial demographic and life‐history data that improve our understanding of life‐history evolution and adaptation and help to refine conservation strategies. Am. J. Primatol. 71:106–119, 2009. © 2008 Wiley‐Liss, Inc.     

Dispersal: a central and independent trait in life history

The study of tradeoffs among major life history components (age at maturity, lifespan and reproduction) allowed the development of a quantitative framework to understand how environmental variation shapes patterns of biodiversity among and within species. Because every environment is inherently spatially structured, and in most cases temporally variable, individuals need to move within and among habitats to maximize fitness. Dispersal is often assumed to be tightly integrated into life histories through genetic correlations with other vital traits. This assumption is particularly strong within the context of a fast‐slow continuum of life‐history variation. Such a framework is to date used to explain many aspects of population and community dynamics. Evidence for a consistent and context‐independent integration of dispersal in life histories is, however, weak. We therefore advocate the explicit integration of dispersal into life history theory as a principal axis of variation influencing fitness, that is free to evolve, independently of other life history traits. We synthesize theoretical and empirical evidence on the central role of dispersal and its evolutionary dynamics on the spatial distribution of ecological strategies and its impact on population spread, invasions and coexistence. By applying an optimality framework we show that the inclusion of dispersal as an independent dimension of life histories might substantially change our view on evolutionary trajectories in spatially structured environments. Because changes in the spatial configuration of habitats affect the costs of movement and dispersal, adaptations to reduce these costs will increase phenotypic divergence among and within populations. We outline how this phenotypic heterogeneity is anticipated to further impact population and community dynamics.     

Life‐history evolution under fluctuating density‐dependent selection and the adaptive alignment of pace‐of‐life syndromes

We present a novel perspective on life‐history evolution that combines recent theoretical advances in fluctuating density‐dependent selection with the notion of pace‐of‐life syndromes (POLSs) in behavioural ecology. These ideas posit phenotypic co‐variation in life‐history, physiological, morphological and behavioural traits as a continuum from the highly fecund, short‐lived, bold, aggressive and highly dispersive ‘fast’ types at one end of the POLS to the less fecund, long‐lived, cautious, shy, plastic and socially responsive ‘slow’ types at the other. We propose that such variation in life histories and the associated individual differences in behaviour can be explained through their eco‐evolutionary dynamics with population density – a single and ubiquitous selective factor that is present in all biological systems. Contrasting regimes of environmental stochasticity are expected to affect population density in time and space and create differing patterns of fluctuating density‐dependent selection, which generates variation in fast versus slow life histories within and among populations. We therefore predict that a major axis of phenotypic co‐variation in life‐history, physiological, morphological and behavioural traits (i.e. the POLS) should align with these stochastic fluctuations in the multivariate fitness landscape created by variation in density‐dependent selection. Phenotypic plasticity and/or genetic (co‐)variation oriented along this major POLS axis are thus expected to facilitate rapid and adaptively integrated changes in various aspects of life histories within and among populations and/or species. The fluctuating density‐dependent selection POLS framework presented here therefore provides a series of clear testable predictions, the investigation of which should further our fundamental understanding of life‐history evolution and thus our ability to predict natural population dynamics.     

Population changes in Czech passerines are predicted by their life‐history and ecological traits

A species’ susceptibility to environmental change might be predicted by its ecological and life‐history traits. However, the effects of such traits on long‐term bird population trends have not yet been assessed using a comprehensive set of explanatory variables. Moreover, the extent to which phylogeny affects patterns in the interspecific variability of population changes is unclear. Our study focuses on the interspecific variability in long‐term population trends and annual population fluctuations of 68 passerine species in the Czech Republic, assessing the effects of eight life‐history and five ecological traits. Ordination of life‐history traits of 68 species revealed a life‐history gradient, from ‘r‐selected’ (e.g. small body mass, short lifespan, high fecundity, large clutch size) to ‘K‐selected’ species. r‐selected species had more negative population trends than K‐selected species, and seed‐eaters declined compared with insectivores. We suggest that the r‐selected species probably suffer from widespread environmental changes, and the seed‐eaters from current changes in agriculture and land use. Populations of residents fluctuated more than populations of short‐distance migrants, probably due to the effect of winter climatic variability. Variance partitioning at three taxonomic levels showed that whereas population trends, population fluctuations and habitat specialization expressed the highest variability at the species level, most life‐history traits were more variable at higher taxonomic levels. These results explain the loss of statistical power in the relationship between life histories and population trends after controlling for phylogeny. However, we argue that a lack of significance after controlling for phylogeny should not reduce the value of such results for conservation purposes.     

How life‐history traits affect ecosystem properties: effects of dispersal in meta‐ecosystems

The concept of life‐history traits and the study of these traits are the hallmark of population biology. Acknowledging their variability and evolution has allowed us to understand how species adapt in response to their environment. The same traits are also involved in how species alter ecosystems and shape their dynamics and functioning. Some theories, such as the metabolic theory of ecology, ecological stoichiometry or pace‐of‐life theory, already recognize this junction, but only do so in an implicitly non‐spatial context. Meanwhile, for a decade now, it has been argued that ecosystem properties have to be understood at a larger scale using meta‐ecosystem theory because source–sink dynamics, community assembly and ecosystem stability are all modified by spatial structure. Here, we argue that some ecosystem properties can be linked to a single life‐history trait, dispersal, i.e. the tendency of organisms to live, compete and reproduce away from their birth place. By articulating recent theoretical and empirical studies linking ecosystem functioning and dynamics to species dispersal, we aim to highlight both the known connections between life‐history traits and ecosystem properties and the unknown areas, which deserve further empirical and theoretical developments.     

The influence of size-dependent life-history traits on the structure and dynamics of populations and communities

Individual organisms often show pronounced changes in body size throughout life with concomitant changes in ecological performance. We synthesize recent insight into the relationship between size dependence in individual life history and population dynamics. Most studies have focused on size‐dependent life‐history traits and population size‐structure in the highest trophic level, which generally leads to population cycles with a period equal to the juvenile delay. These cycles are driven by differences in competitiveness of differently sized individuals. In multi‐trophic systems, size dependence in life‐history traits at lower trophic levels may have consequences for both the dynamics and structure of communities, as size‐selective predation may lead to the occurrence of emergent Allee effects and the stabilization of predator–prey cycles. These consequences are linked to that individual development is density dependent. We conjecture that especially this population feedback on individual development may lead to new theoretical insight compared to theory based on unstructured or age‐dependent models. Density‐dependent individual development may also cause individuals to realize radically different life histories, dependent on the state and dynamics of the population during their life and may therefore have consequences for individual behaviour or the evolution of life‐history traits as well.     

Life history variation in Barents Sea fish: implications for sensitivity to fishing in a changing environment

• Under exploitation and environmental change, it is essential to assess the sensitivity and vulnerability of marine ecosystems to such stress. A species' response to stress depends on its life history. Sensitivity to harvesting is related to the life history “fast–slow” continuum, where “slow” species (i.e., large, long lived, and late maturing) are expected to be more sensitive to fishing than “fast” ones. We analyze life history traits variation for all common fish species in the Barents Sea and rank fishes along fast–slow gradients obtained by ordination analyses. In addition, we integrate species' fast–slow ranks with ecosystem survey data for the period 2004–2009, to assess life history variation at the community level in space and time. Arctic fishes were smaller, had shorter life spans, earlier maturation, larger offspring, and lower fecundity than boreal ones. Arctic fishes could thus be considered faster than the boreal species, even when body size was corrected for. Phylogenetically related species possessed similar life histories. Early in the study period, we found a strong spatial gradient, where members of fish assemblages in the southwestern Barents Sea displayed slower life histories than in the northeast. However, in later, warmer years, the gradient weakened caused by a northward movement of boreal species. As a consequence, the northeast experienced increasing proportions of slower fish species. This study is a step toward integrating life history traits in ecosystem‐based areal management. On the basis of life history traits, we assess the fish sensitivity to fishing, at the species and community level. We show that climate warming promotes a borealization of fish assemblages in the northeast, associated with slower life histories in that area. The biology of Arctic species is still poorly known, and boreal species that now establish in the Arctic are fishery sensitive, which calls for cautious ecosystem management of these areas.

     

Differences in boldness are repeatable and heritable in a long‐lived marine predator

Animal personalities, composed of axes of consistent individual behaviors, are widely reported and can have important fitness consequences. However, despite theoretical predictions that life‐history trade‐offs may cause and maintain personality differences, our understanding of the evolutionary ecology of personality remains poor, especially in long‐lived species where trade‐offs and senescence have been shown to be stronger. Furthermore, although much theoretical and empirical work assumes selection shapes variation in personalities, studies exploring the genetic underpinnings of personality traits are rare. Here we study one standard axis of personality, the shy–bold continuum, in a long‐lived marine species, the wandering albatross from Possession Island, Crozet, by measuring the behavioral response to a human approach. Using generalized linear mixed models in a Bayesian framework, we show that boldness is highly repeatable and heritable. We also find strong differences in boldness between breeding colonies, which vary in size and density, suggesting birds are shyer in more dense colonies. These results demonstrate that in this seabird population, boldness is both heritable and repeatable and highlights the potential for ecological and evolutionary processes to shape personality traits in species with varying life‐history strategies.     

Individual heterogeneity in life histories and eco‐evolutionary dynamics

Individual heterogeneity in life history shapes eco‐evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population‐level processes. Recent developments have provided important steps towards their application to study eco‐evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long‐term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco‐evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco‐evolutionary dynamics.     

Contrasting age-specific recruitment and survival at different spatial scales: a case study with the European storm petrel

Evolutionary studies on optimal decisions or conservation guidelines are often derived by generalising patterns from a single population, while inter‐population variability in life‐history traits is seldom considered. We investigated here how survival and recruitment probabilities changed with age at different geographical scales using the encounter histories of 5523 European storm petrels from three Mediterranean colonies, and also how our estimates of these parameters might be expected to affect population growth rates using population matrix models. We recorded similar patterns among colonies, but also important biological differences. Local survival, recruitment and breeding success increased with age at all colonies; the most distant of three colonies (Marettimo Is.) showed the largest differences. Strikingly, differences in recruitment were also found between two adjacent colonies (two caves from Benidorm Is.). Birds marked as adults from Marettimo and Benidorm colonies had a different survival, whereas we found no differences within Benidorm. Differences in survival were no longer apparent between the two islands at the end of the study following a reduction in predation by specialist gulls at Benidorm. Since birds marked as fledglings mostly recruited near the end of the study, their overall survival was high and in turn similar among colonies. Results from our population matrix models suggested that different age‐dependent patterns of demographic parameters can lead to similar population growth rates. Variability appeared to be greater for recruitment and the most sensitive parameter was adult survival. Thus conservation actions targeting this vulnerable species should focus on factors influencing adult survival. Differences in survival and recruitment among colonies could reflect the spatial heterogeneity in mortality due to predation and colony‐specific density dependent processes. Results highlight the importance of taking into account the potential spatio‐temporal heterogeneity among populations in vital rates, even in those traits that life‐history theory considers less important in driving population dynamics.     

Diversity of juvenile Chinook salmon life history pathways

Life history variability includes phenotypic variation in morphology, age, and size at key stage transitions and arises from genotypic, environmental, and genotype-by-environment effects. Life history variation contributes to population abundance, productivity, and resilience, and management units often reflect life history classes. Recent evidence suggests that past Chinook salmon (Oncorhynchus tshawytscha) classifications (e.g., ‘stream’ and ‘ocean’ types) are not distinct evolutionary lineages, do not capture the phenotypic variation present within or among populations, and are poorly aligned with underlying ecological and developmental processes. Here we review recently reported variation in juvenile Chinook salmon life history traits and provide a refined conceptual framework for understanding the causes and consequences of the observed variability. The review reveals a broad continuum of individual juvenile life history pathways, defined primarily by transitions among developmental stages and habitat types used during freshwater rearing and emigration. Life history types emerge from discontinuities in expressed pathways when viewed at the population scale. We synthesize recent research that examines how genetic, conditional, and environmental mechanisms likely influence Chinook salmon life history pathways. We suggest that threshold models hold promise for understanding how genetic and environmental factors influence juvenile salmon life history transitions. Operational life history classifications will likely differ regionally, but should benefit from an expanded lexicon that captures the temporally variable, multi-stage life history pathways that occur in many Chinook salmon populations. An increased mechanistic awareness of life history diversity, and how it affects population fitness and resilience, should improve management, conservation, and restoration of this iconic species.     

Spatial scaling of population synchrony in marine fish depends on their life history

The synchrony of population dynamics in space has important implications for ecological processes, for example affecting the spread of diseases, spatial distributions and risk of extinction. Here, we studied the relationship between spatial scaling in population dynamics and species position along the slow‐fast continuum of life history variation. Specifically, we explored how generation time, growth rate and mortality rate predicted the spatial scaling of abundance and yearly changes in abundance of eight marine fish species. Our results show that population dynamics of species' with ‘slow’ life histories are synchronised over greater distances than those of species with ‘fast’ life histories. These findings provide evidence for a relationship between the position of the species along the life history continuum and population dynamics in space, showing that the spatial distribution of abundance may be related to life history characteristics.     

Deconstructing environmental predictability: seasonality,environmental colour and the biogeography of marine life histories

Environmental predictability is predicted to shape the evolution of life histories. Two key types of environmental predictability, seasonality and environmental colour, may influence life‐history evolution independently but formal considerations of both and how they relate to life history are exceedingly rare. Here, in a global biogeographical analysis of over 800 marine invertebrates, we explore the relationships between both forms of environmental predictability and three fundamental life‐history traits: location of larval development (aplanktonic vs. planktonic), larval developmental mode (feeding vs. non‐feeding) and offspring size. We found that both dispersal potential and offspring size related to environmental predictability, but the relationships depended on both the environmental factor as well as the type of predictability. Environments that were more seasonal in food availability had a higher prevalence of species with a planktonic larval stage. Future studies should consider both types of environmental predictability as each can strongly affect life‐history evolution.     

Patterns and drivers of intraspecific variation in avian life history along elevational gradients: a meta‐analysis

Elevational gradients provide powerful natural systems for testing hypotheses regarding the role of environmental variation in the evolution of life‐history strategies. Case studies have revealed shifts towards slower life histories in organisms living at high elevations yet no synthetic analyses exist of elevational variation in life‐history traits for major vertebrate clades. We examined (i) how life‐history traits change with elevation in paired populations of bird species worldwide, and (ii) which biotic and abiotic factors drive elevational shifts in life history. Using three analytical methods, we found that fecundity declined at higher elevations due to smaller clutches and fewer reproductive attempts per year. By contrast, elevational differences in traits associated with parental investment or survival varied among studies. High‐elevation populations had shorter and later breeding seasons, but longer developmental periods implying that temporal constraints contribute to reduced fecundity. Analyses of clutch size data, the trait for which we had the largest number of population comparisons, indicated no evidence that phylogenetic history constrained species‐level plasticity in trait variation associated with elevational gradients. The magnitude of elevational shifts in life‐history traits were largely unrelated to geographic (altitude, latitude), intrinsic (body mass, migratory status), or habitat covariates. Meta‐population structure, methodological issues associated with estimating survival, or processes shaping range boundaries could potentially explain the nature of elevational shifts in life‐history traits evident in this data set. We identify a new risk factor for montane populations in changing climates: low fecundity will result in lower reproductive potential to recover from perturbations, especially as fewer than half of the species experienced higher survival at higher elevations.     

Evolution of spatially structured host–parasite interactions

Spatial structure has dramatic effects on the demography and the evolution of species. A large variety of theoretical models have attempted to understand how local dispersal may shape the coevolution of interacting species such as host–parasite interactions. The lack of a unifying framework is a serious impediment for anyone willing to understand current theory. Here, we review previous theoretical studies in the light of a single epidemiological model that allows us to explore the effects of both host and parasite migration rates on the evolution and coevolution of various life‐history traits. We discuss the impact of local dispersal on parasite virulence, various host defence strategies and local adaptation. Our analysis shows that evolutionary and coevolutionary outcomes crucially depend on the details of the host–parasite life cycle and on which life‐history trait is involved in the interaction. We also discuss experimental studies that support the effects of spatial structure on the evolution of host–parasite interactions. This review highlights major similarities between some theoretical results, but it also reveals an important gap between evolutionary and coevolutionary models. We discuss possible ways to bridge this gap within a more unified framework that would reconcile spatial epidemiology, evolution and coevolution.     

Contrasting demographic history and gene flow patterns of two mangrove species on either side of the Central American Isthmus

Comparative phylogeography offers a unique opportunity to understand the interplay between past environmental events and life‐history traits on diversification of unrelated but co‐distributed species. Here, we examined the effects of the quaternary climate fluctuations and palaeomarine currents and present‐day marine currents on the extant patterns of genetic diversity in the two most conspicuous mangrove species of the Neotropics. The black (Avicennia germinans, Avicenniaceae) and the red (Rhizophora mangle, Rhizophoraceae) mangroves have similar geographic ranges but are very distantly related and show striking differences on their life‐history traits. We sampled 18 Atlantic and 26 Pacific locations for A. germinans (N = 292) and R. mangle (N = 422). We performed coalescence simulations using microsatellite diversity to test for evidence of population change associated with quaternary climate fluctuations. In addition, we examined whether patterns of genetic variation were consistent with the directions of major marine (historical and present day) currents in the region. Our demographic analysis was grounded within a phylogeographic framework provided by the sequence analysis of two chloroplasts and one flanking microsatellite region in a subsample of individuals. The two mangrove species shared similar biogeographic histories including: (1) strong genetic breaks between Atlantic and Pacific ocean basins associated with the final closure of the Central American Isthmus (CAI), (2) evidence for simultaneous population declines between the mid‐Pleistocene and early Holocene, (3) asymmetric historical migration with higher gene flow from the Atlantic to the Pacific oceans following the direction of the palaeomarine current, and (4) contemporary gene flow between West Africa and South America following the major Atlantic Ocean currents. Despite the remarkable differences in life‐history traits of mangrove species, which should have had a strong influence on seed dispersal capability and, thus, population connectivity, we found that vicariant events, climate fluctuations and marine currents have shaped the distribution of genetic diversity in strikingly similar ways.     

Do human ‘life history strategies’ exist?

Interest in incorporating life history research from evolutionary biology into the human sciences has grown rapidly in recent years. Two core features of this research have the potential to prove valuable in strengthening theoretical frameworks in the health and social sciences: the idea that there is a fundamental trade-off between reproduction and health; and that environmental influences are important in determining how life histories develop. However, the literature on human life histories has increasingly travelled away from its origins in biology, and become conceptually diverse. For example, there are differences of opinion between evolutionary researchers about the extent to which behavioural traits associate with life history traits to form ‘life history strategies’. Here, I review the different approaches to human life histories from evolutionary anthropologists, developmental psychologists and personality psychologists, in order to assess the evidence for human ‘life history strategies’. While there is precedent in biology for the argument that some behavioural traits, notably risk-taking behaviour, may be linked in predictable ways with life history traits, there is little theoretical or empirical justification for including a very wide range of behavioural traits in a ‘life history strategy’. Given the potential of life history approaches to provide a powerful theoretical framework for understanding human health and behaviour, I then recommend productive ways forward for the field: 1) greater focus on the life history trade-offs which underlie proposed strategies; 2) greater precision when using the language of life history theory and life history strategies; 3) collecting more empirical data, from a diverse range of populations, on linkages between life history traits, behavioural traits and the environment, including the underlying mechanisms which generate these linkages; and 4) greater integration with the social and health sciences.     

Individual heterogeneity and capture–recapture models: what,why and how?

Variation between and within individuals in life history traits is ubiquitous in natural populations. When affecting fitness‐related traits such as survival or reproduction, individual heterogeneity plays a key role in population dynamics and life history evolution. However, it is only recently that properly accounting for individual heterogeneity when studying population dynamics of free‐ranging populations has been made possible through the development of appropriate statistical models. We aim here to review case studies of individual heterogeneity in the context of capture–recapture models for the estimation of population size and demographic parameters with imperfect detection. First, we define what individual heterogeneity means and clarify the terminology used in the literature. Second, we review the literature and illustrate why individual heterogeneity is used in capture–recapture studies by focusing on the detection of life‐history tradeoffs, including senescence. Third, we explain how to model individual heterogeneity in capture–recapture models and provide the code to fit these models ( https://github.com/oliviergimenez/indhet_in_CRmodels ). The distinction is made between situations in which heterogeneity is actually measured and situations in which part of the heterogeneity remains unobserved. Regarding the latter, we outline recent developments of random‐effect models and finite‐mixture models. Finally, we discuss several avenues for future research.     

A general modeling framework for describing spatially structured population dynamics

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network‐based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life‐history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network‐based population is modeled with discrete time steps. Using both theoretical and real‐world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network‐based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles.