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Density dependent carry-over effects from one life history stage to another can affect the dynamics of populations. Here we study such carry-over effects from the tadpole to the postmetamorphic juvenile stage in an endangered amphibian, the natterjack toad (Epidalea calamita). We raised tadpoles in outdoor aquatic mesocosms at four densities and assessed juvenile performance after metamorphosis in terrestrial mesocosms. High larval density reduced mass at metamorphosis by 50 % and doubled the length of the larval period. Survival was reduced at the high densities. Larger metamorphs had higher survival in terrestrial mesocosms and remained larger than cohort members at the end of the 30-day experiment. Because juvenile survival drives amphibian population dynamics, density-dependent carry-over effects to the juvenile stage are likely to affect population viability. We discuss the implications of the results for amphibian conservation practice, both pond construction programs and surveys of amphibian populations.

Large mammals in temperate climates typically display seasonal patterns of habitat use. However, these patterns are often overlooked because large mammals are usually surveyed at annual intervals. In addition, most studies focus on a single species and ignore other species with which the focal species could interact. Knowing seasonal patterns of habitat use in multiple species and understanding factors that cause these patterns can provide further detail on population dynamics and guide effective conservation planning. Here, using dynamic occupancy modeling, we analyze 11 years of camera-trap data collected in northwestern Anatolia, Turkey, to investigate seasonal habitat use of 8 large-mammal species: Brown Bear (Ursus arctos), Eurasian Lynx (Lynx lynx), Gray Wolf (Canis lupus), Red Fox (Vulpes vulpes), Wild Boar (Sus scrofa), Roe Deer (Capreolus capreolus), European Hare (Lepus europaeus), and Red Deer (Cervus elaphus). For each species, we study the strength of seasonality in habitat use and its dependence on human population density and elevation, which have been shown to affect distributions of species in the region. Although all species exhibited seasonality in habitat use, the strength of this seasonality varied among species; it was strongest in Wild Boar, Roe Deer, and Brown Bear. Moreover, except for Brown Bear, all species tended to avoid sites close to humans. The species responded differently to changing elevation; increasing elevation had both positive and negative effects on species-specific colonization and desertion probabilities, and these effects were likely related to either feeding habits or tendency to avoid humans. These results indicate that seasonality should be taken into consideration in population studies. However, because species differ, seasonality patterns should be identified separately for each species of interest, as differences in these patterns can explain the underlying dynamics of habitat-use patterns more accurately.

Background: All behaviour requires energy, and measuring energy expenditure in standard units (joules) is key to linking behaviour to ecological processes. Animal-borne accelerometers are commonly used to infer proxies of energy expenditure, termed ‘dynamic body acceleration’ (DBA). However, converting acceleration proxies (m/s$^{2}$) to standard units (watts) involves costly in-lab respirometry measurements, and there is a lack of viable substitutes for empirical calibration relationships when these are unavailable. Methods: We used past allometric work quantifying energy expenditure during resting and locomotion as a function of body mass to calibrate DBA. We used the resulting ‘power calibration equation’ to estimate daily energy expenditure (DEE) using two models: (1) locomotion data-based linear calibration applied to the waking period, and Kleiber’s law applied to the sleeping period (ACTIWAKE), and (2) locomotion and resting data-based linear calibration applied to the 24-h period (ACTIREST24). Since both models require locomotion speed information, we developed an algorithm to estimate speed from accelerometer, gyroscope, and behavioural annotation data. We applied these methods to estimate DEE in free-ranging meerkats (Suricata suricatta), and compared model estimates with published DEE measurements made using doubly labelled water (DLW) on the same meerkat population. Results: ACTIWAKE’s DEE estimates did not differ significantly from DLW (t(19) = − 1.25; P = 0.22), while ACTIREST24’s estimates did (t(19) = − 2.38; P = 0.028). Both models underestimated DEE compared to DLW: ACTIWAKE by 14% and ACTIREST by 26%. The inter-individual spread in model estimates of DEE (s.d. 1–2% of mean) was lower than that in DLW (s.d. 33% of mean). Conclusions: We found that linear locomotion-based calibration applied to the waking period, and a ‘flat’ resting metabolic rate applied to the sleeping period can provide realistic joule estimates of DEE in terrestrial mammals. Th

In the majority of mammals, gestation length is relatively consistent and seldom varies by more than 3%. In a few species, females can adjust gestation length by delaying the development of the embryo after implantation. Delays in embryonic development allow females to defer the rising energetic costs of gestation when conditions are unfavourable, reducing the risk of embryo loss. Dispersal in mammals that breed cooperatively is a period when food intake is likely to be suppressed and stress levels are likely to be high. Here, we show that pregnant dispersing meerkats (Suricata suricatta), which have been aggressively evicted from their natal group and experience weight loss and extended periods of social stress, prolong their gestation by means of delayed embryonic development. Repeated ultrasound scans of wild, unanaesthetized females throughout their pregnancies showed that pregnancies of dispersers were on average 6.3% longer and more variable in length (52–65 days) than those of residents (54–56 days). The variation in dispersers shows that, unlike most mammals, meerkats can adapt to stress by adjusting their pregnancy length by up to 25%. By doing so, they potentially rearrange the costs of gestation during adverse conditions of dispersal and enhance offspring survival.

With the rapid pace of global warming, there is an urgent need to understand survival responses to climate, particularly for large mammals that are already experiencing population declines associated with anthropogenic pressures such as poaching and habitat loss. We tested hypotheses about the interactive effects of local climatic anomalies (variations around a long-term mean) and proximity to edge of protected area boundaries on seasonal adult and juvenile survival in a population of 2,385 individually identified giraffes monitored over 8 years in the Tarangire Ecosystem of northern Tanzania. Temperature anomalies were positively correlated with seasonal survival of adult giraffes, suggesting these megaherbivores are adapted to hot conditions. Higher seasonal rainfall anomalies were negatively correlated with both juvenile and adult survival, and greater vegetation greenness was associated with lower adult survival. During seasons of anomalously high rainfall and vegetation greenness, higher parasite and disease abundance, poorer-quality nutrition in forage, and higher predation risk may all play a role in lowering giraffe survival. Furthermore, climate-associated reduction in survival was most pronounced during the short rainy season for adult giraffes living closer to the edge of protected areas, indicating that the influence of climate anomalies may be exacerbated by anthropogenic edge effects such as poaching or livestock keeping. Precipitation in East Africa is projected to increase substantially, with a greater proportion of rain falling during heavy events in the short rainy season, which may threaten persistence of giraffes in one of Earth’s most important landscapes for large mammals.

Strong phenological shifts in response to changes in climatic conditions have been reported for many species, including amphibians, which are expected to breed earlier. Phenological shifts in breeding are observed in a wide number of amphibian populations, but less is known about populations living at high elevations, which are predicted to be more sensitive to climate change than lowland populations. The goal of this study is to assess the main factors determining the timing of breeding in an alpine population of the common toad (Bufo bufo) and to describe the observed shifts in its breeding phenology. We modelled the effect of environmental variables on the start and peak dates of the breeding season using 39 years of individual-based data. In addition, we investigated the effect of the lunar cycle, as well as the individual variation in breeding phenology. Finally, to assess the individual heterogeneity in the timing of breeding, we calculated the repeatability of the timing of arrival at the breeding site. Breeding advanced to earlier dates in the first years of the study but the trend continued only until the mid 1990s, and stabilised afterwards. Overall, toads are now breeding on average around 30 days earlier than at the start of the study period. High temperatures and low snow cover in winter and spring, as well as reduced spring precipitation were all associated with earlier breeding. Additionally, we found evidence of males arriving on average before females at the breeding site but no clear and strong effect of the lunar cycle. We only found weak evidence of among-individual variation in shifts in the breeding phenology, as well as a low repeatability of arrival timing. Our findings show that the observed changes in breeding phenology are strongly associated with the environmental conditions. These results contribute to filling a knowledge gap on the effects of climate change on alpine amphibian populations. Moreover, we show that changes in phenology, es

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The forage maturation hypothesis (FMH) assumes that herbivores cope with the trade-off between digestibility and biomass in forage by selecting vegetation at intermediate growth. The green wave hypothesis (GWH) extends the FMH to suggest how spatiotemporal heterogeneity in plant quality shapes migratory movements of herbivores. Growing empirical support for these hypotheses mainly comes from studies in vast landscapes with large-scale habitat heterogeneity. It is unclear, however, to what extent ungulates surf green waves in human-altered landscapes with small-scale heterogeneity in terms of land use and topography. We used plant phenological proxies derived from Sentinel 2 satellite data to analyze the habitat selection of 93 collared red deer (Cervus elaphus) in montane and alpine habitats. Using a step selection analysis, we investigated how plant phenology, that is, the instantaneous rate of green-up (IRG) and normalized difference vegetation index (NDVI), and a set of variables describing topography and human presence influenced red deer resource selection in open habitats. We learned that red deer selected areas with high biomass at green-up and avoided habitats with possible exposure to human activity. Additionally, landscape structure and topography strongly influenced spatial behavior of red deer. We further compared cumulative access to high-quality forage across migrant strategies and found migrants gained better access than residents. Many migratory individuals surfed the green wave, and their surfing behavior, however, became less pronounced with decreasing distance to settlements. Within the constraints of topography and human land use, red deer track spring green-up on a fine spatiotemporal scale and follow the green wave across landscapes in migration movements. Thus, they benefit from high-quality forage even in human-dominated landscapes with small-scale heterogeneity and vegetation emerging in a heterogenic, dynamic mosaic.

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The ability of a species to cope with both long-term and short-term environmental fluctuations might vary with the species' life history. While some life-history characteristics promote large and stable population sizes despite interannual environmental fluctuations, other life-history strategies might allow to evolve quickly in response to long-term gradual changes. In a theoretical study, we show that there is a tradeoff between both properties. Life-history characteristics that promote fast rates of evolution come at the expense of a poor response to short-term environmental fluctuations, and vice versa. We demonstrated the presence of this tradeoff by the use of a mathematical analysis and individual-based simulations., The ability of a species to cope with both long-term and short-term environmental fluctuations might vary with the species' life history. While some life-history characteristics promote large and stable population sizes despite interannual environmental fluctuations, other life-history strategies might allow to evolve quickly in response to long-term gradual changes. In a theoretical study, we show that there is a tradeoff between both properties. Life-history characteristics that promote fast rates of evolution come at the expense of a poor response to short-term environmental fluctuations, and vice versa. We demonstrated the presence of this tradeoff by the use of a mathematical analysis and individual-based simulations.

The forage maturation hypothesis (FMH) assumes that herbivores cope with the trade-off between digestibility and biomass in forage by selecting vegetation at intermediate growth. The green wave hypothesis (GWH) extends the FMH to suggest how spatiotemporal heterogeneity in plant quality shapes migratory movements of herbivores. Growing empirical support for these hypotheses mainly comes from studies in vast landscapes with large-scale habitat heterogeneity. It is unclear, however, to what extent ungulates surf green waves in human-altered landscapes with small-scale heterogeneity in terms of land use and topography. We used plant phenological proxies derived from Sentinel 2 satellite data to analyze the habitat selection of 93 collared red deer (Cervus elaphus) in montane and alpine habitats. Using a step selection analysis, we investigated how plant phenology, that is, the instantaneous rate of green-up (IRG) and normalized difference vegetation index (NDVI), and a set of variables describing topography and human presence influenced red deer resource selection in open habitats. We learned that red deer selected areas with high biomass at green-up and avoided habitats with possible exposure to human activity. Additionally, landscape structure and topography strongly influenced spatial behavior of red deer. We further compared cumulative access to high-quality forage across migrant strategies and found migrants gained better access than residents. Many migratory individuals surfed the green wave, and their surfing behavior, however, became less pronounced with decreasing distance to settlements. Within the constraints of topography and human land use, red deer track spring green-up on a fine spatiotemporal scale and follow the green wave across landscapes in migration movements. Thus, they benefit from high-quality forage even in human-dominated landscapes with small-scale heterogeneity and vegetation emerging in a heterogenic, dynamic mosaic.

Optimal reproductive strategies evolve from the interplay between an individual’s intrinsic state and extrinsic environment, both factors that are rarely fixed over its lifetime. Conditional breeding tactics might be one evolutionary trajectory allowing individuals to maximize fitness. We apply multi-state capture-mark-recapture analysis to a detailed 8-year data set of free-ranging house mice in a growing population to discern causes and fitness consequences of two alternative reproductive tactics in females, communal and solitary breeding. This allows us to integrate natural variation in life-history traits when analysing the expression of two alternative reproductive tactics in females. We find that communal breeding reduces average population fitness, but nevertheless increases over our 8-year study period. The tactic proves to be expressed conditionally dependent on both population density and female body mass – allowing females to breed under subpar conditions, i.e. at high density or when of low body mass. Our results contradict previous laboratory studies and emphasize the importance of studying cooperation under natural conditions, including natural variation in state-dependent survival and breeding probabilities.

Aldabrachelys gigantea (Aldabra giant tortoise) is one of only two giant tortoise species left in the world and survives as a single wild population of over 100,000 individuals on Aldabra Atoll, Seychelles. Despite this large current population size, the species faces an uncertain future because of its extremely restricted distribution range and high vulnerability to the projected consequences of climate change. Captive-bred A. gigantea are increasingly used in rewilding programs across the region, where they are introduced to replace extinct giant tortoises in an attempt to functionally resurrect degraded island ecosystems. However, there has been little consideration of the current levels of genetic variation and differentiation within and among the islands on Aldabra. As previous microsatellite studies were inconclusive, we combined low-coverage and double-digest restriction-associated DNA (ddRAD) sequencing to analyze samples from 33 tortoises (11 from each main island). Using 5426 variant sites within the tortoise genome, we detected patterns of within-island population structure, but no differentiation between the islands. These unexpected results highlight the importance of using genome-wide genetic markers to capture higher-resolution genetic structure to inform future management plans, even in a seemingly panmictic population. We show that low-coverage ddRAD sequencing provides an affordable alternative approach to conservation genomic projects of non-model species with large genomes.

One important but understudied way in which climate change may impact the fitness of individuals and populations is by altering the prevalence of infectious disease outbreaks. This is especially true in social species where endemic diseases are widespread. Here we use 22 years of demographic data from wild meerkats (Suricata suricatta) in the Kalahari, where temperatures have risen steadily, to project group persistence under interactions between weather extremes and fatal tuberculosis outbreaks caused by infection with Mycobacterium suricattae. We show that higher temperature extremes increase the risk of outbreaks within groups by increasing physiological stress as well as the dispersal of males, which are important carriers of tuberculosis. Explicitly accounting for negative effects of tuberculosis outbreaks on survival and reproduction in groups more than doubles group extinction risk in 12 years under projected temperature increases. Synergistic climate–disease effects on demographic rates may therefore rapidly intensify climate-change impacts in natural populations.

Understanding the relative contribution of different biotic interactions in shaping species assemblages constitutes a major goal in community ecology, and consequently, multiple methods aimed at inferring the nature of these associations have emerged during the last decade. In this framework, the stress-gradient hypothesis (SGH) predicts that prevalent biotic interactions shift from competition to facilitation as abiotic stress increases (and productivity decreases). This hypothesis originally raised by plant ecologists has been barely applied to faunal communities. Here, we take advantage of 20 years of abundance data to investigate pairwise patterns in species co-occurrence in alpine bird communities inhabiting two contrasting habitat types: forests (high productivity) and mountain grasslands (low productivity). We also integrate functional data with presence–absence and quantitative matrices in order to detect the signature of processes driving community assembly and test for limiting similarity. We employ a null model approach, probabilistic pairwise association tests and joint species distribution models; all methods revealed a higher frequency of positive interactions in mountain grasslands in agreement with SGH predictions. Both the frequency of positive and negative interactions remained moderately stable over the study period in both habitat types. There was no significant relationship between the degree of co-occurrence of species pairs and their functional distance in either habitat. However, when we only considered those combinations of species whose co-occurrence patterns deviated from that expected at random, we found that co-existing species are functionally more similar than those pairs that show segregated patterns in the forest assemblages. Such a relationship may arise via selective social information use and other processes, including microhabitat preferences. Overall, our findings suggest that interspecific competition does not constitute a majo

The Aldabra giant tortoise (Aldabrachelys gigantea) is one of only two remaining giant tortoise species worldwide. Captive-bred A. gigantea are being used in rewilding projects in the Western Indian Ocean to functionally replace the extinct endemic giant tortoise species and restore degraded island ecosystems. Furthermore, large-scale translocations may become necessary as rising sea levels threaten the only wild population on the low-lying Aldabra Atoll. Critical management decisions would be greatly facilitated by insights on the genetic structure of breeding populations. We used a double-digest restriction-associated DNA sequencing (ddRAD-seq) approach to identify single nucleotide polymorphisms (SNP) among the wild population and two additional captive populations of A. gigantea. A total of 1674 unlinked, putatively neutral genome-wide SNPs were identified. The values of expected heterozygosity ranged from 0.33 to 0.5, whereas the minor allele frequency ranged from 0.20 to 0.5. These novel SNP markers will serve as useful tools for informing the conservation of A. gigantea.

The ability of dispersing individuals to adjust their behaviour to changing conditions is instrumental in overcoming challenges and reducing dispersal costs, consequently increasing overall dispersal success. Understanding how dispersers' behaviour and physiology change during the dispersal process, and how they differ from resident individuals, can shed light on the mechanisms by which dispersers increase survival and maximise reproduction. By analysing individual behaviour and concentrations of faecal glucocorticoid metabolites (fGCM), a stress-associated biomarker, we sought to identify the proximate causes behind differences in survival and reproduction between dispersing and resident meerkats Suricata suricatta. We used data collected on 67 dispersing and 108 resident females to investigate (a) which individual, social and environmental factors are correlated to foraging and vigilance, and whether the role of such factors differs among dispersal phases, and between dispersers and residents; (b) how time allocated to either foraging or vigilance correlated to survival in dispersers and residents and (c) the link between aggression and change in fGCM concentration, and their relationship with reproductive rates in dispersing groups and resident groups with either long-established or newly established dominant females. Time allocated to foraging increased across dispersal phases, whereas time allocated to vigilance decreased. Time allocated to foraging and vigilance correlated positively and negatively, respectively, with dispersers' group size. We did not find a group size effect for residents. High proportions of time allocated to foraging correlated with high survival, and more so in dispersers, suggesting that maintaining good physical condition may reduce mortality during dispersal. Furthermore, while subordinate individuals rarely reproduced in resident groups, the conception rate of subordinates in newly formed dispersing groups was equal to that of their d

1. Experimental laboratory evidence suggests that animals with disrupted social systems express weakened relationship strengths and have more exclusive social associations, and that these changes have functional consequences. A key question is whether anthropogenic pressures have a similar impact on the social structure of wild animal communities. 2. We addressed this question by constructing a social network from 6 years of systematically collected photographic capture-recapture data spanning 1,139 individual adult female Masai giraffes inhabiting a large, unfenced, heterogeneous landscape in northern Tanzania. We then used the social network to identify distinct social communities, and tested whether social or anthropogenic and other environmental factors predicted differences in social structure among these communities. 3. We reveal that giraffes have a multilevel social structure. Local preferences in associations among individuals scale up to a number of distinct, but spatially overlapping, social communities, that can be viewed as a large interconnected metapopulation. We then find that communities that are closer to traditional compounds of indigenous Masai people express weaker relationship strengths and the giraffes in these communities are more exclusive in their associations. 4. The patterns we characterise in response to proximity to humans reflect the predictions of disrupted social systems. Near bomas, fuelwood cutting can reduce food resources, and groups of giraffes are more likely to encounter livestock and humans on foot, thus disrupting the social associations among group members. Our results suggest that human presence could potentially be playing an important role in determining the conservation future of this megaherbivore.

Conserving and managing large portions of land to connect wildlife reserves is an increasingly used strategy to maintain and restore connectivity among wildlife populations. Boundaries of such conservation areas are often determined based on expert opinion and socio-political constraints, yet the extent to which they match species' movement corridors is rarely examined. This is mainly due to a lack of data, particularly on wide-ranging movement behaviour such as dispersal. Nevertheless, empirically assessing the adequacy of protected areas is key for the implementation of targeted management actions and efficient use of limited conservation funds. Between 2011 and 2019, we collected high-resolution GPS data on 16 dispersing African wild dog Lycaon pictus coalitions from a free-ranging population in the Kavango–Zambezi Transfrontier Conservation Area (KAZA-TFCA). Spanning five countries and 520,000 km2, the KAZA-TFCA is the world's largest transboundary conservation area and a prime example for international conservation efforts. We used integrated step selection analysis to estimate habitat selection of dispersers and to create a permeability surface for the KAZA-TFCA. We compared landscape permeability across different regions within the KAZA-TFCA as well as outside its boundaries. Lastly, we calculated least-cost paths and corridors to verify that major movement routes were adequately encompassed within the KAZA-TFCA. Permeability within the boundaries of the KAZA-TFCA was more than double compared to areas outside it. Furthermore, we observed a fivefold permeability difference among the five KAZA-TFCA countries. We also showed that major movement corridors of wild dogs ran within the KAZA-TFCA, although some minor routes remained formally unprotected. Differences in permeability were mainly related to different degrees of human activities across regions, and to the presence or absence of rivers, swamps and open water. The relationship between permeability and oth

Understanding the relative contribution of different biotic interactions in shaping species assemblages constitutes a major goal in community ecology, and consequently, multiple methods aimed at inferring the nature of these associations have emerged during the last decade. In this framework, the stress-gradient hypothesis (SGH) pre-dicts that prevalent biotic interactions shift from competition to facilitation as abiotic stress increases (and productivity decreases). This hypothesis originally raised by plant ecologists has been barely applied to faunal communities. Here, we take advantage of 20 years of abundance data to investigate pairwise patterns in species co-occurrence in alpine bird communities inhabiting two contrasting habitat types: forests (high productivity) and mountain grasslands (low productivity). We also integrate functional data with presence–absence and quantitative matrices in order to detect the signature of processes driving community assembly and test for limiting similarity. We employ a null model approach, probabilistic pairwise association tests and joint species distribution models; all methods revealed a higher frequency of positive interactions in mountain grasslands in agreement with SGH predictions. Both the frequency of positive and negative interactions remained moderately stable over the study period in both habitat types. There was no significant relationship between the degree of co-occurrence of species pairs and their functional distance in either habitat. However, when we only considered those combinations of species whose co-occurrence patterns deviated from that expected at random, we found that co-existing species are functionally more similar than those pairs that show segregated patterns in the forest assemblages. Such a relationship may arise via selective social information use and other processes, including microhabitat preferences. Overall, our findings suggest that interspecific competition does not constitute a maj

The merging of community ecology and phylogenetic biology allows us to link broader evolutionary processes to local ecological processes, thereby increasing our understanding of community assembly. A recurrent way to test how species assemblages respond to different abiotic conditions and evaluate the role of evolutionary constraints in community assembly is through using environmental gradients as natural treatments. Here, we combine phylogenetic and trait-based methods to evaluate how the phylogenetic diversity and composition of bird assemblages and their community-weighted traits vary along an elevational gradient in the Swiss Alps. For this purpose, we used four life-history traits considered to be key indicators of individual species response to environmental changes: clutch size, number of breeding attempts, dispersal capacity and lifespan. Controlling for phylogeny, we determined whether environmental filters (elevation, habitat type) act on these traits independently of the level of relatedness among species. We found that phylogenetic dispersion decreases with elevation, but the signature of phylogenetic clustering was weak. Phylogenetic fuzzy weighting showed that the distribution of bird species across plots was related to the two environmental gradients; nonetheless, such influence was not determined by the phylogenetic relationships in either case. That is, there are no specific clades associated with particular elevation or habitat types. We also found that high elevation communities around the treeline were composed of species with lower reproductive rates, reduced lifespan, and lower dispersal capacity, which would make them less resilient to environmental change. Although traits showed moderate phylogenetic signal, only the lifespan was phylogenetically structured. In the remaining cases, the trait-environment association was not mediated by the phylogenetic relationships among taxa. Our study indicates that evolutionary constraints do not represen

The persistence of wildlife populations is under threat as a consequence of human activities, which are degrading natural ecosystems. Commercial forestry is the greatest threat to biodiversity in boreal forests. Forestry practices have degraded most available habitat, threatening the persistence of natural populations. Understanding population responses is, therefore, critical for their conservation. Population viability analyses are effective tools to predict population persistence under forestry management. However, quantifying the mechanisms driving population responses is complex as population dynamics vary temporally and spatially. Metapopulation dynamics are governed by local dynamics and spatial factors, potentially mediating the impacts of forestry e.g., through dispersal. Here, we performed a seasonal, spatially explicit population viability analysis, using long-term data from a group-living territorial bird (Siberian jay, Perisoreus infaustus). We quantified the effects of forest management on metapopulation dynamics, via forest type-specific demography and spatially explicit dispersal, and how forestry impacted the stability of metapopulation dynamics. Forestry reduced metapopulation growth and stability, through negative effects on reproduction and survival. Territories in higher quality natural forest contributed more to metapopulation dynamics than managed forests, largely through demographic processes rather than dispersal. Metapopulation dynamics in managed forest were also less resilient to disturbances and consequently, may be more vulnerable to environmental change. Seasonal differences in source-sink dynamics observed in managed forest, but not natural forests, were caused by associated seasonal differences in dispersal. As shown here, capturing seasonal source-sink dynamics allows us to predict population persistence under human disturbance and to provide targeted conservation recommendations.

Aim Mountains are biodiversity hotspots and are among the most sensitive ecosystems to ongoing global change being thus of conservation concern. Under this scenario, assessing how biological communities vary over time along elevational gradients and the relative effects of niche-based deterministic processes and stochastic events in structuring assemblages is essential. Here, we examined how the temporal trends of bird communities vary with elevation over a 20 year-period (1999–2018). We also tested for differences in temporal dynamics among habitat types (among-community variability) and functional groups (within-community variability). Taxon 97 species of common breeding birds. Location Swiss Alps. Methods We used abundance data from the Swiss breeding bird survey to compute different temporal dynamic metrics (temporal turnover, synchrony, rate of community change and community-level of covariance among species). We also examined the relative contribution of deterministic and stochastic processes in community assembly using the Raup-Crick method and the normalized stochasticity ratio. Results We found that, with greater elevation, temporal species turnover increased while the rate of overall community change over successive years decreased, suggesting that high-elevation communities display more erratic dynamics with no clear trend. Despite this, we found a more deterministic assembly of alpine communities in comparison to those located at lower elevations. Deterministic processes had greater influence than stochastic processes on community assembly along the entire elevational gradient (80% of communities). Forest communities exhibited higher synchrony in comparison to the remaining habitats likely because they consisted of species with greater functional redundancy, whereas alpine communities were the least stable as a result of their low taxonomic richness (‘portfolio’ effect). Main conclusions Community-level synchrony was overall positive supporting the idea

Approximately 25% of mammals are currently threatened with extinction, a risk that is amplified under climate change. Species persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development and reproduction), and hence, population dynamics. Thus, to quantify which species and regions on Earth are most vulnerable to climate-driven extinction, a global understanding of how different demographic rates respond to climate is urgently needed. Here, we perform a systematic review of literature on demographic responses to climate, focusing on terrestrial mammals, for which extensive demographic data are available. To assess the full spectrum of responses, we synthesize information from studies that quantitatively link climate to multiple demographic rates. We find only 106 such studies, corresponding to 87 mammal species. These 87 species constitute <1% of all terrestrial mammals. Our synthesis reveals a strong mismatch between the locations of demographic studies and the regions and taxa currently recognized as most vulnerable to climate change. Surprisingly, for most mammals and regions sensitive to climate change, holistic demographic responses to climate remain unknown. At the same time, we reveal that filling this knowledge gap is critical as the effects of climate change will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others, often depending on the specific environmental context, complicating simple projections of population fates. Assessments of population viability under climate change are in critical need to gather data that account for multiple demographic responses, and coordinated actions to assess demography holistically should be prioritized for mammals and other taxa.

Climate change–induced shifts in species phenology differ widely across trophic levels, which may lead to consumer–resource mismatches with cascading population and ecosystem consequences. Here, we examined the effects of different rainfall patterns (i.e., timing and amount) on the phenological asynchrony of population of a generalist herbivore and their food sources in semiarid steppe grassland in Inner Mongolia. We conducted a 10-y (2010 to 2019) rainfall manipulation experiment in 12 0.48-ha field enclosures and found that moderate rainfall increases during the early rather than late growing season advanced the timing of peak reproduction and drove marked increases in population size through increasing the biomass of preferred plant species. By contrast, greatly increased rainfall produced no further increases in vole population growth due to the potential negative effect of the flooding of burrows. The increases in vole population size were more coupled with increased reproduction of overwintered voles and increased body mass of young-of-year than with better survival. Our results provide experimental evidence for the fitness consequences of phenological mismatches at the population level and highlight the importance of rainfall timing on the population dynamics of small herbivores in the steppe grassland environment.

Dispersal is a critical process that shapes the structure of wild animal populations. In species that form multi-level societies, natal dispersal might be social (associating with a different social community while remaining near the natal area), spatial (moving away from the natal area while continuing to associate with the same community) or both social and spatial (associating with a different community and moving away from the natal area). For such species, classical spatial measures of dispersal, such as distance moved, might not capture social dispersal. We examined dispersal outcomes for 67 male and 70 female giraffe calves over 7 years in a large, unfenced, ecologically heterogeneous landscape. We tested predictions about the influence of sex, food availability, low- and high-impact human settlements, and local giraffe population density on social or spatial dispersal, dispersal distance, and age of dispersal. We found that dispersal is sex-specific, with females being predominately philopatric. When dispersing, both sexes did so at a mean of 4 years of age. Most (69% of total) young males dispersed, with 84% of male dispersers associating with a different adult female social community than that of their mother, but one in four of these dispersers remained spatially near to their natal area. For adolescent males that dispersed socially but not spatially, overlapping female social communities may represent a potential pool of unrelated mating partners without the risks of travelling to unfamiliar areas. Just 26% of young females dispersed and half of these continued to associate with the adult female social community into which they were born, confirming the importance of maintaining ties among females from calf to adulthood. Furthermore, individuals born farther from high-impact human settlements were more likely to spatially or socially-and-spatially disperse, move greater distances from their natal areas, and disperse at a younger age. Our study highlights

Loss of resilience in population numbers in response to environmental perturbations may be predicted with statistical metrics called early warning signals (EWS) that are derived from abundance time series. These signals, however, have been shown to have limited success, leading to the development of trait-based EWS that are based on information collected from phenotypic traits such as body size. Experimental work assessing the efficacy of EWS under varying ecological and environmental factors are rare. In addition, disentangling how such warning signals are affected under varying ecological and environmental factors is key to their application in biological conservation. Here, we experimentally test how different rates of environmental forcing (i.e. warming) and varying ecological factors (i.e. habitat quality and phenotypic diversity) affected population stability and predictive power of early warning signals of population collapse. We analyzed population density and body size time series data from three phenotypically different populations of a protozoan ciliate Askenasia volvox in two levels of habitat quality subjected to three different treatments of warming (i.e. no warming, fast warming and slow warming). We then evaluated how well abundance- and trait-based EWS predicted population collapses under different levels of phenotypic diversity, habitat quality and warming treatments. Our results suggest that habitat quality and warming treatments had more profound effects than phenotypic diversity had on both population stability and on the performance of abundance-based signals of population collapse. In addition, trait-based EWS generally performed well, were reliable and more robust in forecasting population collapse than abundance-based EWS, regardless of variation in environmental and ecological factors. Our study points towards the development of a predictive framework that includes information from phenotypic traits such as body size as an indicator of loss

Aim: To evaluate the utility of opportunistic data from citizen science programmes for forecasting species distributions against forecasts with a model of individual-based population dynamics. Location: Sweden. Methods: We evaluated whether alternative methods for building habitat suitability models (HSMs) based on opportunistic data from citizen science programmes produced forecasts that were consistent with forecasts from two benchmark models: (1) a HSM based on data from systematic monitoring and (2) an individual- based model for spatially explicit population dynamics based on empirical demographic and movement data. We forecasted population numbers and habitat suitability for three realistic, future forest landscapes for a forest bird, the Siberian jay (Perisoreus infaustus). We ranked simulated forest landscapes with respect to their benefits to Siberian jays for each modelling method and compared the agreement of the rankings among methods. Results: Forecasts based on our two benchmark models were consistent with each other and with expectations based on the species’ ecology. Forecasts from logistic regression models based on opportunistic data were consistent with the benchmark models if species detections were combined with high-quality inferred absences derived via retrospective interviews with experienced “super-reporters.” In contrast, forecasts with three other widely used methods were inconsistent with the bench-mark models, sometimes with misleading rankings of future scenarios. Main conclusions: Our critical evaluation of alternative HSMs against a spatially explicit IBM demonstrates that information on species absences critically improves forecasts of species distributions using opportunistic data from citizen science programmes. Moreover, high-quality information on species absences can be retrospectively inferred from surveys of the consistency of reporting of individual species and the identification skills of participating reporters. We recommen

The snow leopard (Panthera uncia) is one of the world's most elusive felids. In Bhutan, which is one of the 12 countries where the species still persists, reliable information on its distribution and habitat suitability is lacking, thus impeding effective conservation planning for the species. To fill this knowledge gap, we created a country-wide species distribution model using “presence-only” data from 420 snow leopard occurrences (345 from a sign survey and 77 from a camera-trapping survey) and 12 environmental covariates consisting of biophysical and anthropogenic factors. We analyzed the data in an ensemble model framework which combines the outputs from several species distribution models. To assess the adequacy of Bhutan's network of protected areas and their potential contribution toward the conservation of the species, we overlaid the output of the ensemble model on the spatial layers of protected areas and biological corridors. The ensemble model identified 7,206 km2 of Bhutan as suitable for the snow leopard: 3,647 km2 as highly suitable, 2,681 km2 as moderately suitable, and 878 km2 as marginally suitable. Forty percent of the total suitable habitat consisted of protected areas and a further 8% of biological corridors. These suitable habitats were characterized by a mean livestock density of 1.3 individuals per hectare, and a mean slope of 25°; they closely match the distribution of the snow leopard's main wild prey, the bharal (Pseudois nayaur). Our study shows that Bhutan's northern protected areas are a centre for snow leopard conservation both at the national and regional scale.

The development and use of cost-effective and appropriate survey methods to assess species distribution and to monitor range expansion and contraction of wild populations is crucial due to the limited financial resources for conservation. Of particular importance, yet little studied, is the ability to collect information before a wild population is well established, i.e. at the early stages of recolonisation. During 2018 and 2019, we used camera traps, audio recorders, and scat detection dogs simultaneously to investigate composition, detection probability, and territorial extent of a pack of wolves in the Swiss Alps. We compared the efficacy of these survey methods by assessing sampling effort, data obtained, and costs. We show that, under the presented setup, camera traps and scat detection dogs substantially outperformed audio recorders in detecting wolves, representing the packs’ territorial extent, and revealing the number of adult wolves. The detection dogs did not detect pups but, unlike the other methods, allowed the identification of single individuals. The use of four camera traps during 13 weeks, a 24-km-long transect walked with the detection dog, or the use of one audio recorder during 148 weeks were necessary to obtain a comparable wolf detection probability. Our results show that no single method was able to return all information that we hoped to collect. Comprehensive and cost-effective information was best obtained by combining data from camera traps and detection dogs. We suggest both methods to be simultaneously used to successfully investigate wolf recolonisation into historical range.

Contains fulltext : 219163.pdf (publisher's version ) (Open Access)

Contains fulltext : 219163.pdf (publisher's version ) (Open Access)

Contains fulltext : 219163.pdf (publisher's version ) (Open Access)

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics.

One of the largest causes of fluctuations in the size and structure of populations is changes in the environment. In nature, these changes are often temporally autocorrelated and the strength and direction of the autocorrelation can affect population dynamics. These effects are mediated by complex, simultaneously occurring ecological and evolutionary processes, such as phenotypic plasticity and selection. Determining how these processes interact to affect responses of different life histories to autocorrelated environmental fluctuations is of paramount importance to infer which taxa are likely to go extinct or become invasive under global change. Here, we assessed the effect of autocorrelation in environmental states on the trait and population dynamics of different life histories using an evolutionary explicit individual-based modeling approach. We found that, in general, higher positive temporal autocorrelation caused more variation in population size. Fast life histories were more affected than slow ones as they were able to adapt more quickly to varying environmental optima and therefore experienced larger initial decreases in population size when optima changed. Including adaptive phenotypic plasticity buffered the effects of autocorrelation on population dynamics while nonadaptive plasticity amplified them, especially for slow life histories, which recovered less from maladaptation. This study highlights that integration of phenotypic plasticity, selection, and population dynamics is important to improve our understanding of how different life histories deal with autocorrelated climate variability.

One of the largest causes of fluctuations in the size and structure of populations is changes in the environment. In nature, these changes are often temporally autocorrelated and the strength and direction of the autocorrelation can affect population dynamics. These effects are mediated by complex, simultaneously occurring ecological and evolutionary processes, such as phenotypic plasticity and selection. Determining how these processes interact to affect responses of different life histories to autocorrelated environmental fluctuations is of paramount importance to infer which taxa are likely to go extinct or become invasive under global change. Here, we assessed the effect of autocorrelation in environmental states on the trait and population dynamics of different life histories using an evolutionary explicit individual‐based modeling approach. We found that, in general, higher positive temporal autocorrelation caused more variation in population size. Fast life histories were more affected than slow ones as they were able to adapt more quickly to varying environmental optima and therefore experienced larger initial decreases in population size when optima changed. Including adaptive phenotypic plasticity buffered the effects of autocorrelation on population dynamics while nonadaptive plasticity amplified them, especially for slow life histories, which recovered less from maladaptation. This study highlights that integration of phenotypic plasticity, selection, and population dynamics is important to improve our understanding of how different life histories deal with autocorrelated climate variability.

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics.

Successful conservation of species that roam and disperse over large areas requires detailed understanding of their movement patterns and connectivity between subpopulations. But empirical information on movement, space use, and connectivity is lacking for many species, and data acquisition is often hindered when study animals cross international borders. The African wild dog (Lycaon pictus) exemplifies such species that require vast undisturbed areas to support viable, self‐sustaining populations. To study wild dog dispersal and investigate potential barriers to movements and causes of mortality during dispersal, between 2016 and 2019 we followed the fate of 16 dispersing coalitions (i.e., same‐sex group of ≥1 dispersing African wild dogs) in northern Botswana through global positioning system (GPS)‐satellite telemetry. Dispersing wild dogs covered ≤54 km in 24 hours and traveled 150 km to Namibia and 360 km to Zimbabwe within 10 days. Wild dogs were little hindered in their movements by natural landscape features, whereas medium to densely human‐populated landscapes represented obstacles to dispersal. Human‐caused mortality was responsible for >90% of the recorded deaths. Our results suggest that a holistic approach to the management and conservation of highly mobile species is necessary to develop effective research and evidence‐based conservation programs across transfrontier protected areas, including the need for coordinated research efforts through collaboration between national and international conservation authorities. © 2020 The Wildlife Society.

Organisms must cope with both short- and long-term environmental changes to persist. In this study we investigated whether life histories trade-off between their robustness to short-term environmental perturbations and their ability to evolve directional trait changes. We could confirm the tradeoff by modeling the eco-evolutionary dynamics of life-histories along the fast-slow pace-of-life continuum. Offspring dormancy and high adult survival rates allowed for large population sizes to be maintained in face of interannual environmental fluctuations but limited the speed of trait evolution with ongoing environmental change. In contrast, precocious offspring maturation and short-living adults promoted evolvability while lowering demographic robustness. This tradeoff had immediate consequences on extinction dynamics in variable environments. High evolvability allowed short-lived species to cope with long-lasting gradual environmental change, but came at the expense of more pronounced population declines and extinction rates from environmental variability. Higher robustness of slow life-histories helped them persist better on short timescales.

Aim Describing the spatio‐temporal dynamics of biotic communities is critical for understanding how environmental change can affect biodiversity. Mountains are especially susceptible to such changes (e.g., climate change) and, consequently, have been identified as ecosystems of conservation concern. With their sharp physical and ecological transitions, altitudinal gradients allow examining the influence of different climatic conditions and land use types on species assemblages across small spatial extents, and thus, they constitute natural laboratories to study diversity–environment relationships. Location Switzerland. Methods We take advantage of long‐term (20 years) monitoring data and an extensive trait dataset (100 traits) to examine spatial patterns, temporal trends, and spatio‐temporal dynamics in functional and beta diversity of bird communities in the Swiss Alps. Results Functional diversity indices showed a congruent pattern over time and across space; most indices decreased over the study period and were strongly correlated with altitude. In agreement with studies from the tropics, we found that communities in the lowlands were functionally over‐dispersed, whereas communities at higher elevations were functionally clustered. High‐altitude communities exhibited high functional originality, low levels of niche differentiation and a high turnover rate. Beta diversity declined over the study period. Conclusions Our findings suggest that pastoral abandonment does not result in an increase in avian functional diversity as most species colonizing woody‐encroached grasslands are functionally redundant, whereas alpine meadows are inhabited by species exhibiting a high degree of habitat specialization and unique functional traits. Hence, the tree line constitutes a boundary between two well‐differentiated functional groups: one representing a functional continuum from lowlands dominated by agricultural landscape to high‐mountain forests, and the other one composed o

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

Data from animal‐borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have been the tool of choice for characterising animal behaviour. Although machine learning models perform reasonably well, they may not rely on meaningful features, nor lend themselves to physical interpretation of the classification rules. This lack of interpretability and control over classification outcomes is of particular concern where different behaviours have different frequency of occurrence and duration, as in most natural systems, and calls for the development of alternative methods. Biomechanical approaches to human activity classification could overcome these shortcomings, yet their full potential remains untapped for animal studies. We propose a general framework for behaviour recognition using accelerometers, and develop a hybrid model where (a) biomechanical features characterise movement dynamics, and (b) a node‐based hierarchical classification scheme employs simple machine learning algorithms at each node to find feature‐value thresholds separating different behaviours. Using triaxial accelerometer data collected on 10 wild Kalahari meerkats, and annotated video recordings of each individual as groundtruth, this hybrid model was validated in three scenarios: (a) when each behaviour was equally represented (EQDIST), (b) when naturally imbalanced datasets were considered (STRAT) and (c) when data from new individuals were considered (LOIO). A linear‐kernel Support Vector Machine at each node of our classification scheme yielded an overall accuracy of >95% for each scenario. Our hybrid approach had a 2.7% better average overall accuracy than top‐performing classical machine learning approaches. Further, we showed that not all models with high overall accuracy returned accurate behaviour‐specific performance

Background Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magnetometers have recently been shown to detect specific behaviours that accelerometers miss. The prevalent constraint of limited training data necessitates the importance of identifying behaviours with high robustness to data from new individuals, and may require fusing data from both these sensors. However, no study yet has developed an end-to-end approach to recognise common animal behaviours such as foraging, locomotion, and resting from magnetometer data in a common classification framework capable of accommodating and comparing data from both sensors. Methods We address this by first leveraging magnetometers’ similarity to accelerometers to develop biomechanical descriptors of movement: we use the static component given by sensor tilt with respect to Earth’s local magnetic field to estimate posture, and the dynamic component given by change in sensor tilt with time to characterise movement intensity and periodicity. We use these descriptors within an existing hybrid scheme that combines biomechanics and machine learning to recognise behaviour. We showcase the utility of our method on triaxial magnetometer data collected on ten wild Kalahari meerkats (Suricata suricatta), with annotated video recordings of each individual serving as groundtruth. Finally, we compare our results with accelerometer-based behaviour recognition. Results The overall recognition accuracy of > 94% obtained with magnetometer data was found to be comparable to that achieved using accelerometer data. Interestingly, higher robustness to inter-individual variability in dynamic behaviour was achieved with the magnetometer, while the accelerometer was be

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

Species in extreme habitats increasingly face changes in seasonal climate, but the demographic mechanisms through which these changes affect population persistence remain unknown. We investigated how changes in seasonal rainfall and temperature influence vital rates and viability of an arid environment specialist, the Kalahari meerkat, through effects on body mass. We show that climate change–induced reduction in adult mass in the prebreeding season would decrease fecundity during the breeding season and increase extinction risk, particularly at low population densities. In contrast, a warmer nonbreeding season resulting in increased mass and survival would buffer negative effects of reduced rainfall during the breeding season, ensuring persistence. Because most ecosystems undergo seasonal climate variations, a full understanding of species vulnerability to global change relies on linking seasonal trait and population dynamics.

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.