Search

The genetic characteristics of neutral loci in natural populations are shaped by the interplay between genetic drift and gene flow that themselves result from key ecological and evolutionary processes. Because of their influence on population size, habitats characteristics may influence substantially populations' genetic characteristics. However, past studies focused primarily on variables related to habitat quantity while habitat quality was largely overlooked. We therefore combined genetic data to detailed habitat descriptions of three sympatric butterfly species having different ecological needs to quantify the relative contribution of geographic distance and habitat quality/quantity on their genetic characteristics. In all species, the genetic diversity was greater in larger and good quality patches. The genetic differentiation of Lycaena helle (specialist species with limited dispersal) was mostly explained by geographical distances. This effect was dampened by habitat quality as populations inhabiting low quality patches had higher genetic differentiations indicating that the constraints set by local environmental factors increased genetic drift. In Boloria eunomia (specialist species with greater dispersal), the genetic differentiation was only influenced by geographic distance. Finally, in Brenthis ino (more generalist species with greater dispersal), isolation-by-distance was weak and habitat characteristics were unrelated to genetic differentiation. The different effect of habitat quality on these species' genetic characteristics suggests that fundamental ecological traits underpin their response to habitat degradation. In L. helle, a species with major conservation concerns, these results show that preserving habitat quality and connectivity among populations' are important to ensure the maintenance of fully functional metapopulations.

Background The mechanisms underlying the relationship between biodiversity and ecosystem functioning are still poorly understood. Although species richness is commonly used as a biodiversity measure, recent studies showed that functional diversity, i.e. the diversity of functional traits, might be a better proxy. Functional traits are defined as phenotypic traits that affect an organism's performance and shape ecosystem-level processes. The main challenge when using those traits to quantify biodiversity is to choose which ones to measure, since effort and money are limited. As one way of dealing with this, Hodgson et al. (1999) introduced the idea of two types of traits, with soft traits that are easy and quick to quantify, and hard traits that are directly linked to ecosystem functioning but difficult to measure. If a link exists between the two types of traits, then one could use soft traits as a proxy for hard traits for a quick but meaningful assessment of biodiversity. However, this framework is based on two assumptions: (1) hard and soft traits must be tightly connected to allow reliable prediction of one using the other; (2) the relationship between traits must be monotone and linear to be detected by the most common statistical techniques (e.g. GLM, PCA). Results Here we addressed those two assumptions by focusing on six functional traits of the protist species Tetrahymena thermophila, which vary both in their measurement difficulty and functional meaningfulness. They were classified as: easy traits (morphological traits), intermediate traits (movement traits) and hard traits (oxygen consumption and population growth rate). We were able to detect a high number (> 60%) of non-linear relationships between the traits, which can explain the low number of significant relationships found using PCA and GLM analysis. In the end, these analyses did not detect any relationship strong enough to predict one trait using another, but that does not imply there are none. Conclusions Our results highlighted the need for more complex statistical analyzes than the ones commonly used by the scientific community, to account for all the factors that might blur the relationships between traits (e.g. plasticity, non-linearity), and state about the soft/hard framework.

Dispersal is a key process for the dynamics and functioning of meta-communities and meta-ecosystems. Meta-ecosystem theory, however, does not fully integrate the possible effects of dispersal, largely assuming random diffusion of organisms and nutrients, contrasting with rising empirical evidence for intraspecific variability in dispersal strategies. Dispersal is often associated with a suite of phenotypic traits, forming dispersal syndromes. Since phenotypic variability is now acknowledged as a key factor mediating ecosystem dynamics, we argue that dispersal syndromes can link trait-based ecology and meta-ecosystem functioning together. We highlight that the dispersal of individuals can be associated with functional effect traits and can therefore alter trophic and nutrient-mediated interactions in ecosystems. We illustrate how the association between dispersal tendency and functional traits can modify the spatial heterogeneity of ecosystems.

Phenotypic plasticity, the ability of one genotype to produce different phenotypes in different environments, plays a central role in species' response to environmental changes. Transgenerational plasticity (TGP) allows the transmission of this environmentally-induced phenotypic variation across generations, and can influence adaptation. To date, the genetic control of TGP, its long-term stability, and its potential costs remain largely unknown, mostly because empirical demonstrations of TGP across many generations in several genetic backgrounds are scarce. Here, we examined how genotype determines the TGP of phenotypic traits related to dispersal, a fundamental process in ecology and evolution. We used an experimental approach in Tetrahymena thermophila, a ciliate model-species, to determine if and how phenotypic changes expressed following a dispersal treatment are inherited over multiple generations. Our results show that morphological and movement traits associated with dispersal are plastic, and that these modifications are inherited over at least 35 generations. The fitness costs and benefits associated with these plastic changes are also transmitted to further generations. We highlight that the genotype modulates the expression and reversibility of transgenerational plasticity of dispersal-related traits and its fitness outcomes. Our study thus suggests that genotype-dependent TGP could play an important role in eco-evolutionary dynamics as dispersal determines gene flow and the long-term persistence of natural populations.

Resident-disperser differences and genetic variability affect communities in microcosms

Dispersal is a central biological process tightly integrated into life-histories, morphology, physiology and behaviour. Such associations, or syndromes, are anticipated to impact the eco-evolutionary dynamics of spatially structured populations, and cascade into ecosystem processes. As for dispersal on its own, these syndromes are likely neither fixed nor random, but conditional on the experienced environment. We experimentally studied how dispersal propensity varies with individuals' phenotype and local environmental harshness using 15 species ranging from protists to vertebrates. We reveal a general phenotypic dispersal syndrome across studied species, with dispersers being larger, more active and having a marked locomotion-oriented morphology and a strengthening of the link between dispersal and some phenotypic traits with environmental harshness. Our proof-of-concept metacommunity model further reveals cascading effects of context-dependent syndromes on the local and regional organisation of functional diversity. Our study opens new avenues to advance our understanding of the functioning of spatially structured populations, communities and ecosystems.

International audience; Understanding the functioning of natural metapopulations at relevant spatial and temporal scales is necessary to accurately feed both theoretical eco-evolutionary models and conservation plans. One key metric to describe the dynamics of metapopulations is dispersal rate. It can be estimated with either direct field estimates of individual movements or with indirect molecular methods, but the two approaches do not necessarily match. We present a field study in a large natural metapopulation of the butterfly Boloria eunomia in Belgium surveyed over three generations using synchronized demographic and genetic datasets with the aim to characterize its genetic structure, its dispersal dynamics, and its demographic stability. By comparing the census and effective population sizes, and the estimates of dispersal rates, we found evidence of stability at several levels: constant inter-generational ranking of population sizes without drastic historical changes, stable genetic structure and geographically-influenced dispersal movements. Interestingly, contemporary dispersal estimates matched between direct field and indirect genetic assessments. We discuss the eco-evolutionary mechanisms that could explain the described stability of the metapopulation, and suggest that destabilizing agents like inter-generational fluctuations in population sizes could be controlled by a long adaptive history of the species to its dynamic local environment. We finally propose methodological avenues to further improve the match between demographic and genetic estimates of dispersal.

Dispersal is a key process mediating ecological and evolutionary dynamics. Its effects on metapopulations dynamics, population genetics or species range distribution can depend on phenotypic differences between dispersing and non-dispersing individuals (i.e., dispersal syndromes). However, scaling up to the importance of dispersal syndromes for meta-ecosystems have rarely been considered, despite intraspecific phenotypic variability is now recognised as an important factor mediating ecosystem functioning. In this study, we characterised the intraspecific variability of dispersal syndromes in twenty isolated genotypes of the ciliateTetrahymena thermophilato test their consequences for biomass productivity in communities composed of fiveTetrahymenaspecies. To do so, dispersers and residents of each genotype were introduced, each separately, in ciliate communities composed of four other competing species of the genusTetrahymenato investigate the effects of dispersal syndromes. We found that introducing dispersers led to a lower biomass compared to introducing residents. This effect was highly consistent across the twentyT. thermophilagenotypes despite their marked differences of dispersal syndromes. Finally, we found a strong genotypic effect on biomass production, confirming that intraspecific variability in general affected ecosystem functions in our system. Our study shows that intraspecific variability and the existence of dispersal syndromes can impact the functioning of spatially structured ecosystems in a consistent and therefore predictable way.

International audience; Phenotypic plasticity is increasingly recognized as a key element of eco-evolutionary dynamics, but it remains challenging to assess because of its multidimensional nature. Indeed, organisms live in complex environments where numerous factors can impact the phenotypic expression of traits (inter-environment axis), possess multiple traits that can influence each other's expression (inter-trait axis) and differ in their genetic background (inter-genotype axis), which can not only impact the traits' values but also their plasticity. We addressed six questions related to phenotypic plasticity: (a) do different environmental gradients show similar effects on a given trait? (b) Are the effects of two environmental gradients on a trait additive? (c) Do different traits show similar plastic response to a given environmental gradient? (d) Do the (co)variances between traits vary across environmental gradients? (e) Do genotypes differ in their plastic response to a given environmental gradient? (f) Are some genotypes more plastic than others across all traits? We designed a microcosm experiment using the protist Tetrahymena thermophila aimed at encompassing all these aspects of phenotypic plasticity. We exposed 15 distinct genotypes to 25 combinations of temperature and nutrient availability and assessed the plasticity of five phenotypic traits. Our results show strong differences in the plastic response depending on the environmental gradient, not only regarding the shape of the reaction norm of the different traits tested, but also in the overall plasticity of the organisms. We did not find any covariance between traits that was consistent across all environments. Overall, our results suggest independent impacts of the environmental dimension considered on the observed plastic response. These results underline potential difficulties in generalizing findings about plasticity to all environments and all traits.

International audience; There is growing evidence that anthropogenic landscapes can strongly influence the evolution of dispersal, particularly through fragmentation, and may drive organisms into an evolutionary trap by suppressing dispersal. However, the influence on dispersal evolution of anthropogenic variation in habitat patch turnover has so far been largely overlooked. In this study, we examined how human‐driven variation in patch persistence affects dispersal rates and distances, determines dispersal‐related phenotypic specialization, and drives neutral genetic structure in spatially structured populations. We addressed this issue in an amphibian, Bombina variegata, using an integrative approach combining capture–recapture modeling, demographic simulation, common garden experiments, and population genetics. B. variegata reproduces in small ponds that occur either in habitat patches that are persistent (i.e., several decades or more), located in riverine environments with negligible human activity, or in patches that are highly temporary (i.e., a few years), created by logging operations in intensively harvested woodland. Our capture–recapture models revealed that natal and breeding dispersal rates and distances were drastically higher in spatially structured populations (SSPs) in logging environments than in riverine SSPs. Population simulations additionally showed that dispersal costs and benefits drive the fate of logging SSPs, which cannot persist without dispersal. The common garden experiments revealed that toadlets reared in laboratory conditions have morphological and behavioral specialization that depends on their habitat of origin. Toadlets from logging SSPs were found to have higher boldness and exploration propensity than those from riverine SSPs, indicating transgenerationally transmitted dispersal syndromes. We also found contrasting patterns of neutral genetic diversity and gene flow in riverine and logging SSPs, with genetic diversity and effective population size considerably higher in logging than in riverine SSPs. In parallel, intrapatch inbreeding and relatedness levels were lower in logging SSPs. Controlling for the effect of genetic drift and landscape connectivity, gene flow was found to be higher in logging than in riverine SSPs. Taken together, these results indicate that anthropogenic variation in habitat patch turnover may have an effect at least as important as landscape fragmentation on dispersal evolution and the long‐term viability and genetic structure of wild populations.

International audience; Ecology and evolution unfold in spatially structured communities, where dispersal links dynamics across scales. Because dispersal is multicausal, identifying general drivers remains challenging. In a coordinated distributed experiment spanning organisms from protozoa to vertebrates, we tested whether two fundamental determinants of local dynamics, top-down and bottom-up control, generally explain active dispersal. We show that both factors consistently increased emigration rates and use metacommunity modelling to highlight consequences on local and regional dynamics.

A fundamental challenge in experimental ecology is to capture nonlinearities of ecological responses to interacting environmental drivers. Here, we demonstrate that gradient designs outperform replicated designs for detecting and quantifying nonlinear responses. We report the results of (1) multiple computer simulations and (2) two purpose-designed empirical experiments. The findings consistently revealed that unreplicated sampling at a maximum number of sampling locations maximised prediction success (i.e. the R² to the known truth) irrespective of the amount of stochasticity and the underlying response surfaces, including combinations of two linear, unimodal or saturating drivers. For the two empirical experiments, the same pattern was found, with gradient designs outperforming replicated designs in revealing the response surfaces of underlying drivers. Our findings suggest that a move to gradient designs in ecological experiments could be a major step towards unravelling underlying response patterns to continuous and interacting environmental drivers in a feasible and statistically powerful way.

International audience; Local adaptation is assumed to occur under limited gene flow. However, habitat-matching theory predicts dispersal should favour rather than hinder local adaptation when individuals selectively disperse towards habitats maximizing their performance. We provide experimental evidence that local adaptation to the upper margin of a species' thermal niche is favoured by dispersal with habitat choice, but hindered under random dispersal. Our study challenges the idea that high gene flow precludes local adaptation, and provides unique experimental evidence of habitat choice as an overlooked mechanism responsible for adaptation under rapid environmental changes.

Landscape-scale population dynamics are driven in part by movement within and dispersal among habitat patches. Predicting these processes requires information about how movement behavior varies among land cover types. We investigated how butterfly movement in a heterogeneous landscape varies within and between habitat and matrix land cover types, and the implications of these differences for within-patch residence times and among-patch connectivity. We empirically measured movement behavior in the Baltimore checkerspot butterfly (Euphydryas phaeton) in three land cover classes that broadly constitute habitat and two classes that constitute matrix. We also measured habitat preference at boundaries. We predicted patch residence times and interpatch dispersal using movement parameters estimated separately for each habitat and matrix land cover subclass (5 categories), or for combined habitat and combined matrix land cover classes (2 categories). We evaluated the effects of including edge behavior on all metrics. Overall, movement was slower within habitat land cover types, and faster in matrix cover types. Butterflies at forest edges were biased to remain in open areas, and connectivity and patch residence times were most affected by behavior at structural edges. Differences in movement between matrix subclasses had a greater effect on predictions about connectivity than differences between habitat subclasses. Differences in movement among habitat subclasses had a greater effect on residence times. Our findings highlight the importance of careful classification of movement and land cover in heterogeneous landscapes, and reveal how subtle differences in behavioral responses to land cover can affect landscape-scale outcomes.

1. Measuring functional connectivity, the ability of species to move between resource patches, is essential for conservation in fragmented landscapes. However, current methods are highly time consuming and expensive. 2. Population synchrony- the correlation in time series of counts between two long-term population monitoring sites, has been suggested as a possible proxy measure of functional connectivity. To date, population synchrony has been shown to correlate with proxies for movement frequency such as the coverage of suitable habitat types in intervening landscapes, and also least cost distances around hostile land cover types. 3. This provides tentative evidence that synchrony is directly driven by movements of the focal species, but an alternative explanation is that these land cover types affect the movement of interacting species (e.g. natural enemies of the focal species) which can also drive synchronous population dynamics. Therefore, what is needed is a test directly relating population synchrony to movement frequencies of a focal species. 4. Here we use data from a 21 year mark-release-recapture study and show that population synchrony does indeed predict movements of a focal butterfly species Boloria eunomia (Esper). 5. There is growing evidence that population synchrony can be a useful conservation tool to measure functional connectivity.

Habitat fragmentation is expected to reduce dispersal movements among patches as a result of increased inter-patch distances. Furthermore, since habitat fragmentation is expected to raise the costs of moving among patches in the landscape, it should hamper the ability or tendency of organisms to perform informed dispersal decisions. Here, we used microcosms of the ciliate Tetrahymena thermophila to test experimentally whether habitat fragmentation, manipulated through the length of corridors connecting patches differing in temperature, affects habitat choice. We showed that a twofold increase of inter-patch distance can as expected hamper the ability of organisms to choose their habitat at immigration. Interestingly, it also increased their habitat choice at emigration, suggesting that organisms become choosier in their decision to either stay or leave their patch when obtaining information about neighbouring patches gets harder. This study points out that habitat fragmentation might affect not only dispersal rate but also the level of non-randomness of dispersal, with emigration and immigration decisions differently affected. These consequences of fragmentation might considerably modify ecological and evolutionary dynamics of populations facing environmental changes.

There is growing evidence that anthropogenic landscapes can strongly influence the evolution of dispersal, particularly through fragmentation, and may drive organisms into an evolutionary trap by suppressing dispersal. However, the influence on dispersal evolution of anthropogenic variation in habitat patch turnover has so far been largely overlooked. In this study, we examined how human-driven variation in patch persistence affects dispersal rates and distances, determines dispersal-related phenotypic specialization, and drives neutral genetic structure in spatially structured populations. We addressed this issue in an amphibian, Bombina variegata, using an integrative approach combining capture–recapture modeling, demographic simulation, common garden experiments, and population genetics. B. variegata reproduces in small ponds that occur either in habitat patches that are persistent (i.e. several decades or more), located in riverine environments with negligible human activity, or in patches that are highly temporary (i.e. a few years), created by logging operations in intensively harvested woodland. Our capture–recapture models revealed that natal and breeding dispersal rates and distances were drastically higher in spatially structured populations (SSPs) in logging environments than in riverine SSPs. Population simulations additionally showed that dispersal costs and benefits drive the fate of logging SSPs, which cannot persist without dispersal. The common garden experiments revealed that toadlets reared in laboratory conditions have morphological and behavioral specialization that depends on their habitat of origin. Toadlets from logging SSPs were found to have higher boldness and exploration propensity than those from riverine SSPs, indicating transgenerationally transmitted dispersal syndromes. We also found contrasting patterns of neutral genetic diversity and gene flow in riverine and logging SSPs, with genetic diversity and effective population size considerably higher in logging than in riverine SSPs. In parallel, intra-patch inbreeding and relatedness levels were lower in logging SSPs. Controlling for the effect of genetic drift and landscape connectivity, gene flow was found to be higher in logging than in riverine SSPs. Taken together, these results indicate that anthropogenic variation in habitat patch turnover may have an effect at least as important as landscape fragmentation on dispersal evolution and the long-term viability and genetic structure of wild populations.

Phenotypic plasticity, the ability of one genotype to produce different phenotypes in different environments, plays a central role in species’ response to environmental changes. Transgenerational plasticity (TGP) allows the transmission of this environmentally-induced phenotypic variation across generations, and can influence adaptation. To date, the genetic control of TGP, its long-term stability, and its potential costs remain largely unknown, mostly because empirical demonstrations of TGP across many generations in several genetic backgrounds are scarce. Here, we examined how genotype determines the TGP of dispersal, a fundamental process in ecology and evolution. We used an experimental approach involving ~200 clonal generations in a model-species of ciliate to determine if and how TGP influences the expression of dispersal-related traits in several genotypes. Our results show that morphological and movement traits associated with dispersal are plastic, and that these modifications are inherited over at least 35 generations. We also highlight that genotype modulates the fitness costs and benefits associated with plastic dispersal strategies. Our study suggests that genotype-dependent TGP could play a critical role in eco-evolutionary dynamics as dispersal determines gene flow and the long-term persistence of natural populations. More generally, it outlines the tremendous importance that genotype-dependent TGP could have in the ability of organisms to cope with current and future environmental changes.SignificanceThe genetic control of the transgenerational plasticity is still poorly understood despite its critical role in species responses to environmental changes. We examined how genotype determines transgenerational plasticity of a complex trait (i.e., dispersal) in a model-species of ciliate across ~200 clonal generations. Our results provide evidence that plastic phenotypic variation linked to dispersal is stably inherited over tens of generations and that cell genotype modulates the expression and fitness cost of transgenerational plasticity.

Understanding how and why individual movement translates into dispersal between populations is a long-term goal in ecology. Movement is broadly defined as “any change in the spatial location of an individual”, whereas dispersal is more narrowly defined as a movement that may lead to gene flow. Because the former may create the condition for the latter, behavioural decisions that lead to dispersal may be detectable in underlying movement behaviour. In addition, dispersing individuals also have specific sets of morphological and behavioural traits that help them coping with the costs of movement and dispersal, and traits that mitigate costs should be under selection and evolve if they have a genetic basis. Here we experimentally study the relationships between movement behaviour, morphology and dispersal across 44 genotypes of the actively dispersing unicellular, aquatic model organism Tetrahymena thermophila. We used two-patch populations to quantify individual movement trajectories, as well as activity, morphology and dispersal rate. First, we studied variation in movement behaviour among and within genotypes (i.e. between dispersers and residents) and tested whether this variation can be explained by morphology. Then, we address how much the dispersal rate is driven by differences in the underlying movement behaviour. Genotypes expressed different movements in terms of speed and path tortuosity. We also detected marked movement differences between resident and dispersing individuals, mediated by the genotype. Movement variation was partly explained by morphological properties such as cell size and shape, with larger cells consistently showing higher movement speed and lower tortuosity. Genetic differences in activity and diffusion rates were positively related to the observed dispersal and jointly explained 45% of the variation in dispersal rate. Our study shows that a detailed understanding of the interplay between morphology, movement and dispersal may have potential to improve dispersal predictions over broader spatio-temporal scales.

We studied the consequences of behaviour at habitat patch boundaries on dispersal for the bog fritillary butterfly Proclossiana eunomia Esper in two networks of habitat differing in fragmentation and matrix quality. We tested for differences in responses to patch boundaries according to the fragmentation level of the network by analysing movement paths of adult butterflies. Butterflies systematically engaged in U-turns when they reached a boundary in the fragmented network while they crossed over boundaries in more than 40% of boundary encounters in the continuous one. We applied the Virtual Migration model (Hanski, AlhoMoilanen 2000) to capture-mark-recapture data collected in both networks. The model indicated (i) a lower dispersal rate and (ii) a lower survival during dispersal in the fragmented network. This latter difference is likely to be the key biological process leading to behavioural avoidance of patch boundary crossings. On the basis of this behavioural difference, we designed an individual-based simulation model to explore the relationship between patch area, boundary permeability and emigration rate. Predictions of the model fitted observed results of the effect of patch area on emigration rate according to fragmentation: butterflies are more likely to leave small patches than large ones in fragmented landscapes (where patch boundary permeability is low), while this relationship disappears in more continuous landscapes (where patch boundary permeability is high).

It is widely recognized that ecological dynamics influence evolutionary dynamics, and conversely that evolutionary changes alter ecological processes. Because fragmentation impacts all biological levels (from individuals to ecosystems) through isolation and reduced habitat size, it strongly affects the links among evolutionary and ecological processes such as population dynamics, local adaptation, dispersal and speciation. Here, we review our current knowledge of the eco-evolutionary dynamics in fragmented landscapes, focusing on both theory and experimental studies. We then suggest future experimental directions to study eco-evolutionary dynamics and/or feedbacks in fragmented landscapes, especially to bridge the gap between theoretical predictions and experimental validations. This article is protected by copyright. All rights reserved.

Kin selection theory predicts that costly cooperative behaviors evolve most readily when directed toward kin. Dispersal plays a controversial role in the evolution of cooperation: dispersal decreases local population relatedness and thus opposes the evolution of cooperation, but limited dispersal increases kin competition and can negate the benefits of cooperation. Theoretical work has suggested that plasticity of dispersal, where individuals can adjust their dispersal decisions according to the social context, might help resolve this paradox and promote the evolution of cooperation. Here, we experimentally tested the hypothesis that conditional dispersal decisions are mediated by a cooperative strategy: we quantified the density-dependent dispersal decisions and subsequent colonization efficiency from single cells or groups of cells among six genetic strains of the unicellular Tetrahymena thermophila that differ in their aggregation level (high, medium, and low), a behavior associated with cooperation strategy. We found that the plastic reaction norms of dispersal rate relative to density differed according to aggregation level: highly aggregative genotypes showed negative density-dependent dispersal, whereas low-aggregation genotypes showed maximum dispersal rates at intermediate density, and medium-aggregation genotypes showed density-independent dispersal with intermediate dispersal rate. Dispersers from highly aggregative genotypes had specialized long-distance dispersal phenotypes, contrary to low-aggregation genotypes; medium-aggregation genotypes showing intermediate dispersal phenotype. Moreover, highly aggregation genotypes showed evidence for beneficial kin-cooperation during dispersal. Our experimental results should help to resolve the evolutionary conflict between cooperation and dispersal: cooperative individuals are expected to avoid kin-competition by dispersing long distances, but maintain the benefits of cooperation by dispersing in small groups.

1. In polymorphic species, two or more discrete phenotypes co-occur simultaneously. Sex-limited polymorphism is a particular case of polymorphism, in which several discrete morphs coexist within one of the two sexes only. Several hypotheses were proposed to explain the existence and the maintenance of sex-limited polymorphism in insects: (i) the morphs have similar fitness, such as similar survival and expected fecundity, and their frequencies vary randomly (i.e. the null hypothesis); (ii) harassment by males is reduced towards the less common female morph, in this case andromorph females (i.e. the male mimicry and learned mate recognition hypotheses); (iii) morphs differ in predation risk (i.e. the predation hypothesis); or (iv) morphs differ in thermoregulation ability (i.e. the thermoregulation hypothesis). 2. Field observations and experiments were employed to compare the relative support of these hypotheses using dimorphic females of the bog fritillary butterfly. Differences were detected between morphs in survival, fecundity, harassment by males, predation pressure and thermal properties, thereby rejecting the null hypothesis. 3. The lifestyle of both morphs is associated with different costs and benefits, with advantages in daily survival and precocious emergence for the gynomorph females, and advantages in fecundity, predation and male harassment for the andromorph females. Besides, as the bog fritillary butterfly is protandrous (i.e. males emerge before females), the longer development of andromorph females puts them at risk of emerging when all the males are dead. The results raise the question as to which mechanisms control the ontogenetic pathways driving the production of the two morphs (i.e. genetic polymorphism or phenotypic plasticity).

Population viability analysis (PVA) models are used to estimate population extinction risk under different scenarios. Both simple and complex PVA models are developed and have their specific pros and cons; the question therefore arises whether we always use the most appropriate model type. Generally, the specific purpose of a model and the availability of data are listed as determining the choice of model type, but this has not been formally tested yet. We quantified the relative importance of model purpose and nine metrics of data availability and resolution for the choice of a PVA model type, while controlling for effects of the different life histories of the modelled species. We evaluated 37 model pairs: each consisting of a generally simpler, population-based model (PBM) and a more complex, individual-based model (IBM) developed for the same species. The choice of model type was primarily affected by the availability and resolution of demographic, dispersal and spatial data. Low-resolution data resulted in the development of less complex models. Model purpose did not affect the choice of the model type. We confirm the general assumption that poor data availability is the main reason for the wide use of simpler models, which may have limited predictive power for population responses to changing environmental conditions. Conservation biology is a crisis discipline where researchers learned to work with the data at hand. However, for threatened and poorly-known species, there is no short-cut when developing either a PBM or an IBM: investments to collect appropriately detailed data are required to ensure PVA models can assess extinction risk under complex environmental conditions.

International audience; A functional definition of the habitat-concept based on ecological resources incorporates three interconnected parameters: composition, configuration, and availability of the resources. The intersection of those parameters represents the functional habitat of a given population or species. Resource composition refers to the co-occurrence of the resources required by each individual to complete its life cycle. Resource configuration refers both to the way individual resources are spatially distributed within the habitat and the way all the resources are organized in the habitat space. Resource availability refers to the accessibility and procureability of resources. Variation in these variables is predicted to influence the demography of the population. To test the suitability of this definition and its transferability across landscapes, we first conducted a very detailed study on habitat and resource use of five butterfly species within a large nature reserve. Second, we conducted a larger-scale study, focusing on metapopulations of two species. We monitored demography for each species and tested whether its variation can be explained by (1) the vegetation type, (2) the vegetation composition or (3) the availability and configuration of the species-specific ecological resources. To confirm that resource availability and configuration reflect habitat quality, we also assessed their impacts on individual morphology. Whatever the investigated spatial scale, our results quantitatively demonstrate the overall better performance of the resource-based habitat approach compared to other most commonly used approaches. Our analysis allowed us to assess the relative importance of each ecological resource in terms of both their availability and organization relative to the species' abundance, demography and individual fitness measures. Resource availability did not play the predominant role in defining habitat quality as it was in most cases overruled by resource organization. Finally, we confirmed the between-population transferability of the habitat definition and quality estimates while adopting a resource-based habitat approach. Our study clearly demonstrates the suitability of the resource-based definition of the habitat. Therefore, we argue that this approach should be favored for species of conservation concern. Although most conclusions so far have emerged from butterfly studies, the resource-based definition of the habitat should also be ecologically relevant to many other organisms.

Whilst the overall geographic range of the lesser marbled fritillary, Brenthis ino (Rottemburg, 1775), is currently expanding, this species is patchily distributed at a local spatial scale due to its use of flower rich semi-natural meadows and the aggregated distribution of its host plant. Therefore, understanding the dispersal patterns of this butterfly and the effect of increasing fragmentation of the landscapes in central and Western Europe on its population dynamics is key to determining whether this patchy distribution can lead to metapopulation structuring and dynamics. One way to determine the degree to which local populations are isolated from one another is to use high resolution molecular genetic markers and thence quantify gene flow and genetic drift. Eleven microsatellite loci have previously been developed for this species, but six showed evidence of null alleles, effectively violating key assumptions of the models used to infer gene flow. We therefore developed a set of new primer pairs to amplify a suite of 16 highly polymorphic microsatellite loci (number of alleles ranged from 2-30) of which nine were found to conform to the Hardy-Weinberg's expectations, whilst at the same time not showing any clear signature for the presence of null alleles. We further describe how these primers were optimized for landscape and metapopulation genetics studies in Belgian Ardenne.

1. The nitrogen limitation hypothesis posits that phytophagous insects benefit from nitrogen enrichment of their host plants through a reduction of the concentration of toxic compounds and an increase of free amino acids and proteins. However, species' response to nitrogen enrichment varies substantially and high nitrogen levels are associated with population decline, suggesting there are major costs to feeding on nitrogen‐rich host plants. 2. To test the hypothesis that larval growth performance is maximal at intermediate nitrogen enrichment, nitrogen levels were measured in 18 populations of the host plant of Lycaena helle, a specialist butterfly inhabiting nutrient‐poor wet meadows. The nitrogen content of host plants was then modified to mirror average natural nitrogen levels (C), highest field‐recorded levels (T1), and levels higher than those observed across our study populations (T2). 3. Caterpillars fed with T1 leaves had a greater maximum body mass than caterpillars of the C group because of their improved food assimilation during the early stages of their development. Caterpillars of C and T2 groups had similar growth patterns but high nitrogen content had detrimental effects, as caterpillars fed with T2 leaves had a slower ingestion rate than C and T1 groups. 4. Quantifying the fitness consequences of these changes in growth performance is necessary to fully understand the implications of nitrogen enrichment for L. helle (rapid growth may result in fitness costs). However, conservation plans for this emblematic glacial relict species should also consider the preservation of its host plant quality to ensure its persistence.

International audience; Obtaining an accurate quantification of population size is often of prime importance in ecology and conservation biology (e.g. population viability analysis, a basic step for assessing species and population status in a given area and guiding effective conservation). When obtaining a reliable quantification of absolute (vs. relative) population size is required, Mark–Release–Recapture (MRR) is a method of choice for many organisms. This is a highly reliable but costly procedure in terms of time and potential impact on species and sites. Consequently, less costly alternatives are highly desirable for conservation and population ecologists.We present here a simplified MRR protocol to mitigate this cost of repeated MRR sampling with little compromise on the quality of the population size estimation. Using one of the largest existing butterfly MRR databases, collected on two fritillary species over a period of 20 years and >20 populations in Belgium, we assessed the possibility to reduce the effort of collecting MRR data while keeping accurate quantification of total population size. By downsampling from the full datasets and calculating a range of demographic census metrics, we specifically investigated whether marking individuals is necessary, and whether the number of sampling sessions can be reduced.We found that counting individuals is not enough: some individual marking, even in a simplistic way to differentiate newly recorded from previously seen individuals, is essential for estimating population size. A simple linear conversion function (number of “missed” individuals for each marked one) can be used to compute population size from the number of individuals marked over a small number of MRR sampling sessions. Parameterizing this function is system specific, because it depends on detectability of individuals, but only requires an initial effort of traditional high‐effort MRR in a few populations encompassing the expected range of population size, combined with previous knowledge on the species about potential factors affecting detectability.Our simplified MRR protocol should allow scientists to obtain absolute population size estimates almost as good as with traditional high‐effort MRR, but at a cost lowered in both the marking procedure and the intensity of field visits.

Organisms rarely experience a homogeneous environment. Rather, ecological and evolutionary dynamics unfold in spatially structured and fragmented landscapes, with dispersal as the central process linking these dynamics across spatial scales. Because dispersal is a multi-causal and highly plastic life-history trait, finding general drivers that are of importance across species is challenging but highly relevant for ecological forecasting.We here tested whether two fundamental ecological forces and main determinants of local population dynamics, top-down and bottom-up control, generally explain dispersal in spatially structured communities. In a coordinated distributed experiment spanning a wide range of actively dispersing organisms, from protozoa to vertebrates, we show that bottom-up control, that is resource limitation, consistently increased dispersal. While top-down control, that is predation risk, was an equally important dispersal driver as bottom-up control, its effect depended on prey and predator space use and whether dispersal occurred on land, in water or in the air: species that routinely use more space than their predators showed increased dispersal in response to predation, specifically in aquatic environments. After establishing these general causes of dispersal, we used a metacommunity model to show that bottom-up and top-down control of dispersal has important consequences for local population fluctuations as well as cascading effects on regional metacommunity dynamics. Context-dependent dispersal reduced local population fluctuations and desynchronized dynamics between communities, two effects that increase population and community stability.Our study provides unprecedented insights into the generality of the positive resource dependency of dispersal as well as a robust experimental test of current theory predicting that predator-induced dispersal is modulated by prey and predator space use. Our experimental and theoretical work highlights the critical importance of the multi-causal nature of dispersal as well as its cascading effects on regional community dynamics, which are specifically relevant to ecological forecasting.

Studies explaining the choice of model structure for population viability analysis (PVA) are rare and no such study exists for butterfly species, a focal group for conservation. Here, we describe in detail the development of a model to predict population viability of a glacial relict butterfly species, Boloria eunomia, under climate change. We compared four alternative formulations of an individual-based model, differing in the environmental factors acting on the survival of immature life stages: temperature (only temperature impact), weather (temperature, precipitation, and sunshine), temperature and parasitism, and weather and parasitism. Following pattern-oriented modeling, four observed patterns were used to contrast these models: one qualitative (response of population size to habitat parameters) and three quantitative ones describing population dynamics during eight years (mean and variability of population size, and magnitude of the temporal autocorrelation in yearly population growth rates). The four model formulations were not equally able to depict population dynamics under current environmental conditions; the model including only temperature was selected as the most parsimonious model sufficiently well reproducing the empirical patterns. We used all four model formulations to test a range of climate change scenarios that were characterized by changes in both mean and variability of the weather variables. All models predicted adverse effects of climate change and resulted in the same ranking of mean climate change scenarios. However, models differed in their absolute values of population viability measures, underlining the need to explicitly choose the most appropriate model formulation and avoid arbitrary usage of environmental drivers in a model. We conclude that further applications of pattern-oriented modeling to butterfly and other species are likely to help in identifying the key factors impacting the viability of certain taxa, which, ultimately, will aid and speed up informed management decisions for endangered species under climate change.

1. Experimental laboratory systems (ELS) are widely applied research tools to test theoretical predictions in ecology and evolution. Combining ELS with automated image analysis could significantly boost information acquisition due to the ease at which abundance and morphological data is collected. Despite the advantages of image analysis, the technology has not been fully adopted yet, presumably due to the difficulties of technical implementation. 2. The tools needed to integrate image analysis in ELS are nowadays readily available: digital camera equipment is purchased at limited costs and free software solutions which allow sophisticated image processing and analysis exist. Here, we give a concise description how to integrate these pieces into a largely automated image analysis workflow. We provide researchers with necessary background information on the principles of image analysis,explaining how to standardize image acquisition and how to validate the results to reduce bias. 3. Three cross-platform and open-source software solutions for image analysis are compared: ImageJ, the EB-Image package in R, and Python with the SciPy/scikit image libraries. The relative strengths and limitations of each solution are compared and discussed. In addition, a set of test images and three scripts are provided in the Online Supplementary Material to illustrate the use of image analysis and help biologists to implement image analysis in their own systems. 4. To demonstrate the reliability and versatility of a validated image analysis workflow, we introduce our own Tetrahymena thermophila ELS. Then, examples from evolutionary ecology are provided showing the advantages of image analysis to study different ecological questions, aiming at both the population and individual level. 5. Experimental laboratory systems that integrate the advantages of image analysis extend their application and versatility compared with regular ELS. Such improvements are necessary to understand complex processes such as eco-evolutionary feedbacks, community dynamics and individual behaviour in ELS.

1. Population genetics is used in a wide variety of fields such as ecology and biodiversity conservation. How estimated genetic characteristics of natural populations can be influenced by the sampling design has been a long-standing concern. Multiple simulation and empirical studies illustrated the influence of both sample size and polymorphism of markers. However, our review of studies on butterfly population genetics indicates no consensus on sample size for the estimation of genetic diversity or differentiation. Furthermore, other aspects of sampling design (sex ratio and timing of sampling) were not addressed and their potential impact on genetic parameter estimates rarely explored. 2. Using a large empirical dataset (with spatial and temporal replicates) collected on a butterfly species, Boloria aquilonaris, as well as simulated datasets reflecting (1) three scenarios of migration–genetic drift equilibrium and (2) one scenario of parameter stabilization after 100,000 generations, we quantified the impacts of three aspects of genetic sampling design (namely, sample size, sex ratio and timing of sampling) on the estimation of allele frequencies and its potential downstream impact on the estimation of genetic parameters. 3. With empirical data, we found that sample size and timing of sampling strongly affected the accuracy of allele frequencies and the downstream analyses, while sex ratio did not. Our results were consistent across spatial and temporal replicates. Also, with simulated data, we showed that the genetic sampling design had limited effect in systems where dispersal outweighs genetic drift, while it can have major consequences on our understanding of the genetic diversity and population differentiation in systems dominated by genetic drift (such as most study systems with conservation concerns). 4. We advocate for careful consideration of all aspects of the sampling design in population genetics studies, that is a sufficient number of samples, while ensuring similar sex ratio among sampling locations and collecting with timing appropriate to the question under study. This is particularly important when the study aims at species conservation.

Most organisms are able to use social information to adjust key behaviours in their lifecycle including dispersal and cooperation. Ciliate microcosms provide a highly powerful tool to study the role of biocommunication in ecology and evolution because they allow simultaneous study of the chemical carriers of information and their eco-evolutionary consequences within short spatial and temporal scales. Here, we review what is known about the existence of social information use and its consequences on dispersal and cooperation in Tetrahymena, and point out the usefulness of Tetrahymena microcosms to further develop our understanding of the mechanisms and implications of information use in eco-evolutionary dynamics.

1. As ectothermic organisms, butterflies have widely been used as models to explore the predicted impacts of climate change. However, most studies explore only one life stage; to our best knowledge, none have integrated the impact of temperature on the vital rates of all life stages for a species of conservation concern. 2. Besides, most population viability analysis models for butterflies are based on yearly population growth rate,precluding the implementation and assessment of important climate change scenarios, where climate change occurs mainly, or differently, during some seasons. 3. Here, we used a combination of laboratory and field experiments to quantify the impact of temperature on all life stages of a vulnerable glacial relict butterfly. Next, we integrated these impacts into an overall population response using a deterministic periodic matrix model and explored the impact of several climate change scenarios. 4. Temperature positively affected egg, pre-diapause larva and pupal survival, and the number of eggs laid by a female ; only the survival of overwintering larva was negatively affected by an increase in temperature. Despite the positive impact of warming on many life stages, population viability was reduced under all scenarios, with predictions of much shorter times to extinction than under the baseline (current temperature situation) scenario. Indeed, model predictions were the most sensitive to changes in survival of overwintering larva, the only stage negatively affected by warming. 5. A proper consideration of every stage of the life cycle is important when designing conservation guidelines in the light of climate change. This is in line with the resource-based habitat view, which explicitly refers to the habitat as a collection of resources needed for all life stages of the species. We, therefore, encourage adopting a resource-based habitat view for population viability analysis and development of conservation guidelines for butterflies, and more generally, other organisms. Life stages that are cryptic or difficult to study should not be forsaken as they may be key determinants in the overall response to climate change, as we found with overwintering Boloria eunomia larvae.

Pacific salmon (Oncorhynchus spp.) exemplify the ways in which populations are structured by homing and the abiotic factors affecting their dynamics in discrete breeding and rearing habitats. What is the finest spatial scale of their population structure, and where do clusters of spatially proximate breeding groups lie along the continuum from isolated populations – metapopulation – patchy panmictic population? To investigate these questions, we monitored sockeye salmon, Oncorhynchus nerka, spawning in a complex of habitats ~1 km apart, joining to form a single stream flowing into Iliamna Lake, Alaska, USA. Annual surveys revealed levels of asynchrony in productivity that were comparable with values reported for sockeye salmon spawning in separate streams flowing into lakes elsewhere in Bristol Bay. A mark–recapture study revealed very little movement of spawning adults among habitats. The ponds occupied at highest density varied among years, and salmon consistently arrived and spawned later in one pond than the others. These results are consistent with the hypothesis that the salmon structured as a small-scale metapopulation rather than a single panmictic population.

Dispersal costs can be classified into energetic, time, risk and opportunity costs and may be levied directly or deferred during departure, transfer and settlement. They may equally be incurred during life stages before the actual dispersal event through investments in special morphologies. Because costs will eventually determine the performance of dispersing individuals and the evolution of dispersal, we here provide an extensive review on the different cost types that occur during dispersal in a wide array of organisms, ranging from micro-organisms to plants, invertebrates and vertebrates. In general, costs of transfer have been more widely documented in actively dispersing organisms, in contrast to a greater focus on costs during departure and settlement in plants and animals with a passive transfer phase. Costs related to the development of specific dispersal attributes appear to be much more prominent than previously accepted. Because costs induce trade-offs, they give rise to covariation between dispersal and other life-history traits at different scales of organismal organisation. The consequences of (i) the presence and magnitude of different costs during different phases of the dispersal process, and (ii) their internal organisation through covariation with other life-history traits, are synthesised with respect to potential consequences for species conservation and the need for development of a new generation of spatial simulation models.

Purpose: Temperature profoundly impacts on distribution and habitat-use of organisms. The development of ectothermous caterpillars does not depend on host plant quality only, but also on the availability of suitable thermal conditions. Selection for thermally favorable microclimates (i.e. behavioral thermoregulation) is a primary mechanism of temperature control, and caterpillars can be either (or alternately) temperature conformers (i.e. passively adopting ambient temperature conditions) or thermoregulators (i.e. able to some extent to elevate or decrease their body temperature relative to ambient temperature). Here, we addressed the functional significance of different structural vegetation elements for the behavioral thermoregulation by caterpillars of two butterfly species. Results: Weather conditions influenced the caterpillar detection probability within host plant patches,indicating that caterpillars can hide and use suitable microclimates provided by vegetation structures to cope with weather variations. This is why we (1) evaluated the heterogeneity in temperature conditions provided by these structures, (2) quantified the influence of ambient temperature and light intensity on caterpillar body temperature, and (3) tested how position on structure, substrate color and exposition influenced caterpillar body temperature. As expected, vegetation structures provided heterogeneous temperature and sun exposition conditions, while caterpillar body temperature was dependent on ambient temperature and light intensity. But body temperature was additionally influenced by the position on vegetation structures, substrate color and exposition. Conclusions: These results suggest that there is no unique and fixed structure in the vegetation subsuming the best thermal conditions for caterpillars. We argue that a better understanding of the thermal properties of vegetation structures is essential for correctly understanding caterpillar habitatuse and the behavioral mechanisms driving their body thermoregulation. Conceptually this means that thermal conditions should be included in the definition of a species’ functional habitat. Practically this may influence the choice of appropriate habitat management for species of conservation concern.

Habitat quality and habitat geometry are two crucial factors driving metapopulation dynamics. However, their intricacy has prevented so far a reliable test of their relative impact on local population dynamics and persistence. Here we report on a long-term study in which we manipulated habitat quality within a butterfly metapopulation, whereas habitat geometry was kept constant. The treatment consisted in lowering the quality of certain habitat patches while others were kept untreated, using the same spatial design over years. The effect of the treatment on metapopulation dynamics was assessed by comparing residence probability and dispersal rates within the same habitat network on 11 and 6 independent butterfly generations before and after treatment, respectively. Results showed that the experimental decrease in habitat quality generated significantly higher emigration rates from treated patches. This increase was associated with a significant decrease in dispersal rates out of untreated patches, and a significant higher residence probability in these patches. The direct relation between lower habitat quality and higher dispersal propensity in treated patches was expected. However, the lower dispersal from untreated patches after treatment was opposite to the expectation of positive density dependent dispersal generally observed in butterflies. Such negative density-dependent dispersal would allow a rapid fine-tuning of dispersal rates to changes in habitat quality, particularly when the spatial autocorrelation of the environmental is low. Accordingly,dispersal would promote an ideal free distribution of individuals in the landscape according to their fitness expectation.

Genetic variability, kin structure and demography of a population are mutually dependent. Population genetic theory predicts that under demographically stable conditions, neutral genetic variability reaches equilibrium between gene flow and drift. However, density fluctuations and non-random mating, resulting e.g. from kin clustering, may lead to changes in genetic composition over time. Theoretical models also predict that changes in kin structure may affect aggression level and recruitment, leading to density fluctuations. These predictions have been rarely tested in natural populations. The aim of this study was to analyse changes in genetic variability and kin structure in a local population of the root vole (Microtus oeconomus) that underwent a fourfold change in mean density over a 6-year period. Intensive live-trapping resulted in sampling 88% of individuals present in the study area, as estimated from mark-recapture data. Based on 642 individual genotypes at 20 microsatellite loci, we compared genetic variability and kin structure of this population between consecutive years. We found that immigration was negatively correlated with density, while the number of kin groups was positively correlated with density. This is consistent with theoretical predictions that changes in kin structure play an important role in population fluctuations. Despite the changes in density and kin structure, there was no genetic differentiation between years. Population-level genetic diversity measures did not significantly vary in time and remained relatively high (H-E range: 0.72-0.78). These results show that a population that undergoes significant demographic and social changes may maintain high genetic variability and stable genetic composition.

Arbuscular mycorrhizal (AM) fungi obligatorily depend on carbon (C) resources provided via the plant and therefore fluctuations in C availability may strongly and differently affect AM fungi with different life-history strategies (LHS). In the present study, we examined the effect of repeated defoliation of in vitro grown barrel medic (Medicago truncatula) on the spore and auxiliary cell (AC) production dynamics of a presumed r-strategist (Glomus intraradices) and a presumed K-strategist (Dentiscutata reticulata). Glomus intraradices modulated the production of spores directly to C availability, showing direct investment in reproduction as expected for r-strategists. In contrast, AC production of D. reticulata was not affected after a single defoliation and thus showed higher resistance to fluctuating C levels, as expected for K-strategists. Our results demonstrate that plant defoliation affects the production of extraradical C storage structures of G. intraradices and D. reticulata differently. Our results contribute towards revealing differences in LHS among AM fungal species, a step further towards understanding their community dynamics in natural ecosystems and agroenvironments.