Dispersal and connectivity in increasingly extreme climatic conditions.

While climate change has been shown to impact several life-history traits of wild-living animal populations, little is known about its effects on dispersal and connectivity. Here, we capitalize on the highly variable flooding regime of the Okavango Delta to investigate the impacts of changing environmental conditions on the dispersal and connectivity of the endangered African wild dog (Lycaon pictus). Based on remote sensed flood extents observed over 20 years, we derive two extreme flood scenarios: a minimum and a maximum flood extent, representative of very dry and very wet environmental periods. These conditions are akin to those anticipated under increased climatic variability, as it is expected under climate change. Using a movement model parameterized with GPS data from dispersing individuals, we simulate 12,000 individual dispersal trajectories across the ecosystem under both scenarios and investigate patterns of connectivity. Across the entire ecosystem, surface water coverage during maximum flood extent reduces dispersal success (i.e., the propensity of individuals to disperse between adjacent subpopulations) by 12% and increases dispersal durations by 17%. Locally, however, dispersal success diminishes by as much as 78%. Depending on the flood extent, alternative dispersal corridors emerge, some of which in the immediate vicinity of human-dominated landscapes. Notably, under maximum flood extent, the number of dispersing trajectories moving into human-dominated landscapes decreases by 41% at the Okavango Delta's inflow, but increases by 126% at the Delta's distal end. This may drive the amplification of human-wildlife conflict. While predicting the impacts of climate change on environmental conditions on the ground remains challenging, our results highlight that environmental change may have significant consequences for dispersal patterns and connectivity, and ultimately, population viability. Acknowledging and anticipating such impacts will be key to effective conservation strategies and to preserve vital dispersal corridors in light of climate change and other human-related landscape alterations.

Higher Mortality Is Not a Universal Cost of Dispersal: A Case Study in African Wild Dogs.

AbstractMortality is considered one of the main costs of dispersal. A reliable evaluation of mortality, however, is often hindered by a lack of information about the fate of individuals that disappear under unexplained circumstances (i.e., missing individuals). Here, we addressed this uncertainty by applying a Bayesian mortality analysis that inferred the fate of missing individuals according to information from individuals with known fate. Specifically, we tested the hypothesis that mortality during dispersal is higher than mortality among nondispersers using 32 years of mark-resighting data from a free-ranging population of the endangered African wild dog (Lycaon pictus) in northern Botswana. Contrary to expectations, we found that mortality during dispersal was lower than mortality among nondispersers, indicating that higher mortality is not a universal cost of dispersal. Our findings suggest that group living can incur costs for certain age classes, such as limited access to resources as group density increases, that exceed the mortality costs associated with dispersal. By challenging the accepted expectation of higher mortality during dispersal, we urge for further investigations of this key life history trait and propose a robust statistical approach to reduce bias in mortality estimates.

Dispersal-induced social stress prolongs gestation in wild meerkats.

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.

Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable.

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/s2) 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. The underestimation and lower spread in model estimates compared to DLW likely arise because the accelerometer only captures movement-related energy expenditure, whereas DLW is an integrated measure. Our study offers new tools to incorporate body mass (through allometry), and changes in behavioural time budgets and intra-behaviour changes in intensity (through DBA) in acceleration-based field assessments of daily energy expenditure.

Destabilizing effect of climate change on the persistence of a short-lived primate.

Seasonal tropical environments are among those regions that are the most affected by shifts in temperature and rainfall regimes under climate change, with potentially severe consequences for wildlife population persistence. This persistence is ultimately determined by complex demographic responses to multiple climatic drivers, yet these complexities have been little explored in tropical mammals. We use long-term, individual-based demographic data (1994 to 2020) from a short-lived primate in western Madagascar, the gray mouse lemur (Microcebus murinus), to investigate the demographic drivers of population persistence under observed shifts in seasonal temperature and rainfall. While rainfall during the wet season has been declining over the years, dry season temperatures have been increasing, with these trends projected to continue. These environmental changes resulted in lower survival and higher recruitment rates over time for gray mouse lemurs. Although the contrasting changes have prevented the study population from collapsing, the resulting increase in life-history speed has destabilized an otherwise stable population. Population projections under more recent rainfall and temperature levels predict an increase in population fluctuations and a corresponding increase in the extinction risk over the next five decades. Our analyses show that a relatively short-lived mammal with high reproductive output, representing a life history that is expected to closely track changes in its environment, can nonetheless be threatened by climate change.

A three-step approach for assessing landscape connectivity via simulated dispersal: African wild dog case study.

Context: Dispersal of individuals contributes to long-term population persistence, yet requires a sufficient degree of landscape connectivity. To date, connectivity has mainly been investigated using least-cost analysis and circuit theory, two methods that make assumptions that are hardly applicable to dispersal. While these assumptions can be relaxed by explicitly simulating dispersal trajectories across the landscape, a unified approach for such simulations is lacking. Objectives: Here, we propose and apply a simple three-step approach to simulate dispersal and to assess connectivity using empirical GPS movement data and a set of habitat covariates. Methods: In step one of the proposed approach, we use integrated step-selection functions to fit a mechanistic movement model describing habitat and movement preferences of dispersing individuals. In step two, we apply the parameterized model to simulate dispersal across the study area. In step three, we derive three complementary connectivity maps; a heatmap highlighting frequently traversed areas, a betweenness map pinpointing dispersal corridors, and a map of inter-patch connectivity indicating the presence and intensity of functional links between habitat patches. We demonstrate the applicability of the proposed three-step approach in a case study in which we use GPS data collected on dispersing African wild dogs (Lycaon pictus) inhabiting northern Botswana. Results: Using step-selection functions we successfully parametrized a detailed dispersal model that described dispersing individuals' habitat and movement preferences, as well as potential interactions among the two. The model substantially outperformed a model that omitted such interactions and enabled us to simulate 80,000 dispersal trajectories across the study area. Conclusion: By explicitly simulating dispersal trajectories, our approach not only requires fewer unrealistic assumptions about dispersal, but also permits the calculation of multiple connectivity metrics that together provide a comprehensive view of landscape connectivity. In our case study, the three derived connectivity maps revealed several wild dog dispersal hotspots and corridors across the extent of our study area. Each map highlighted a different aspect of landscape connectivity, thus emphasizing their complementary nature. Overall, our case study demonstrates that a simulation-based approach offers a simple yet powerful alternative to traditional connectivity modeling techniques. It is therefore useful for a variety of applications in ecological, evolutionary, and conservation research. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-023-01602-4.

Demographic consequences of changes in environmental periodicity.

The fate of natural populations is mediated by complex interactions among vital rates, which can vary within and among years. Although the effects of random, among-year variation in vital rates have been studied extensively, relatively little is known about how periodic, nonrandom variation in vital rates affects populations. This knowledge gap is potentially alarming as global environmental change is projected to alter common periodic variations, such as seasonality. We investigated the effects of changes in vital-rate periodicity on populations of three species representing different forms of adaptation to periodic environments: the yellow-bellied marmot (Marmota flaviventer), adapted to strong seasonality in snowfall; the meerkat (Suricata suricatta), adapted to inter-annual stochasticity as well as seasonal patterns in rainfall; and the dewy pine (Drosophyllum lusitanicum), adapted to fire regimes and periodic post-fire habitat succession. To assess how changes in periodicity affect population growth, we parameterized periodic matrix population models and projected population dynamics under different scenarios of perturbations in the strength of vital-rate periodicity. We assessed the effects of such perturbations on various metrics describing population dynamics, including the stochastic growth rate, log λS . Overall, perturbing the strength of periodicity had strong effects on population dynamics in all three study species. For the marmots, log λS decreased with increased seasonal differences in adult survival. For the meerkats, density dependence buffered the effects of perturbations of periodicity on log λS . Finally, dewy pines were negatively affected by changes in natural post-fire succession under stochastic or periodic fire regimes with fires occurring every 30 years, but were buffered by density dependence from such changes under presumed more frequent fires or large-scale disturbances. We show that changes in the strength of vital-rate periodicity can have diverse but strong effects on population dynamics across different life histories. Populations buffered from inter-annual vital-rate variation can be affected substantially by changes in environmentally driven vital-rate periodic patterns; however, the effects of such changes can be masked in analyses focusing on inter-annual variation. As most ecosystems are affected by periodic variations in the environment such as seasonality, assessing their contributions to population viability for future global-change research is crucial.

Chromosome-level genome assembly for the Aldabra giant tortoise enables insights into the genetic health of a threatened population.

BACKGROUND: The Aldabra giant tortoise (Aldabrachelys gigantea) is one of only two giant tortoise species left in the world. The species is endemic to Aldabra Atoll in Seychelles and is listed as Vulnerable on the International Union for Conservation of Nature Red List (v2.3) due to its limited distribution and threats posed by climate change. Genomic resources for A. gigantea are lacking, hampering conservation efforts for both wild and ex situpopulations. A high-quality genome would also open avenues to investigate the genetic basis of the species' exceptionally long life span. FINDINGS: We produced the first chromosome-level de novo genome assembly of A. gigantea using PacBio High-Fidelity sequencing and high-throughput chromosome conformation capture. We produced a 2.37-Gbp assembly with a scaffold N50 of 148.6 Mbp and a resolution into 26 chromosomes. RNA sequencing-assisted gene model prediction identified 23,953 protein-coding genes and 1.1 Gbp of repetitive sequences. Synteny analyses among turtle genomes revealed high levels of chromosomal collinearity even among distantly related taxa. To assess the utility of the high-quality assembly for species conservation, we performed a low-coverage resequencing of 30 individuals from wild populations and two zoo individuals. Our genome-wide population structure analyses detected genetic population structure in the wild and identified the most likely origin of the zoo-housed individuals. We further identified putatively deleterious mutations to be monitored. CONCLUSIONS: We establish a high-quality chromosome-level reference genome for A. gigantea and one of the most complete turtle genomes available. We show that low-coverage whole-genome resequencing, for which alignment to the reference genome is a necessity, is a powerful tool to assess the population structure of the wild population and reveal the geographic origins of ex situ individuals relevant for genetic diversity management and rewilding efforts.

Green-up selection by red deer in heterogeneous, human-dominated landscapes of Central Europe.

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.

Community structure determines the predictability of population collapse.

Early warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Although a growing body of work has shown the utility of EWS based on either statistics derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations. However, to predict reliably the future state of ecological systems, which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical. Here, reconciling quantitative trait evolution and Lotka-Volterra equations, which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi-trophic predator-prey communities. Using these simulations and warning signals derived from both population- and community-level data, we showed the utility of abundance-based EWS, as well as metrics derived from stability-landscape theory (e.g. width and depth of the basin of attraction), were fundamentally linked. Thus, the depth and width of such stability-landscape curves could be used to identify which species should exhibit the strongest EWS of collapse. The probability a species displays both trait and abundance-based EWS was dependent on its position in a community, with some species able to act as indicator species. In addition, our results also demonstrated that in general trait-based EWS were less reliable in comparison with abundance-based EWS in forecasting species collapses in our simulated communities. Furthermore, community-level abundance-based EWS were fairly reliable in comparison with their species-level counterparts in forecasting species-level collapses. Our study suggests a holistic framework that combines abundance-based EWS and metrics derived from stability-landscape theory that may help in forecasting species loss in a community context.

A Trade-Off between Robustness to Environmental Fluctuations and Speed of Evolution.

AbstractUnderstanding how a species' life history affects its capacity to cope with environmental changes is important in the context of rapid climate changes. Reinterpreting previous results from a well-developed theoretical framework, we show that a trade-off exists between a species' ability to genetically adapt to long-term gradual environmental changes and its ability to demographically resist short-term environmental perturbations, causing variation in its vital rates. Surprisingly, this important insight has not been made formally explicit before. Choosing archetypal life histories along the fast-slow pace-of-life continuum and modeling their eco-evolutionary dynamics, we further show that long-lived species have larger demographic robustness to interannual fluctuations but limited trait evolutionary responses in gradually changing environments. In contrast, short-lived species had larger evolvability but reduced demographic robustness. This trade-off bears heavily on extinction probabilities of populations tracking fast trait changes in stochastic environments. Faster trait evolution in short-lived species came at the expense of their higher sensitivity to short-term fluctuations, causing higher extinction rates than for long-lived species. Long-lived species persisted better on short timescales but built maladaptation and an extinction debt over time. This work shows how modeling species' eco-evolutionary dynamics can help to assess species vulnerability to environmental changes.

Cooperation by necessity: condition- and density-dependent reproductive tactics of female house mice.

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.

Distinct body-size responses to warming climate in three rodent species.

In mammals, body-size responses to warming climates are diverse, and the mechanisms underlying these different responses have been little investigated. Using temporal and spatial datasets of three rodent species distributed across different climatic zones in China, we investigated temporal and spatial trends of body size (length and mass), identified the critical drivers of these trends, and inferred the potential causes underlying the distinct body-size responses to the critical drivers. We found that body mass of all species remained stable over time and across space. Body length, however, increased in one species over time and in two species across space. Generally, body-length variation was predicted best by minimum ambient temperature. Moreover, in two species, body length changed linearly with temperature differences between ancestral and colonization areas. These distinct temperature-length patterns may jointly be caused by species-specific temperature sensitivities and experienced magnitudes of warming. We hypothesize that species or populations distributed across distinct temperature gradients evolved different intrinsic temperature sensitivities, which affect how their body sizes respond to warming climates. Our results suggest that size trends associated with climate change should be explored at higher temporal and spatial resolutions, and include clades of species with similar distributions.

Dispersal Decreases Survival but Increases Reproductive Opportunities for Subordinates in a Cooperative Breeder.

AbstractIn most socially structured populations, the formation of new groups depends on the survival and reproduction of dispersing individuals. Quantifying vital rates in dispersers, however, is difficult because of the logistic challenges of following wide-ranging animals. Here, using data from free-ranging meerkats (Suricata suricatta), we estimate survival and reproduction of dispersing females and compare these estimates to data for established residents. Meerkat groups consist of a dominant pair and several subordinate helpers. Female helpers are evicted from their resident groups by the dominant female, allowing her to monopolize reproduction, and evicted females may form small dispersing coalitions. We show that, as in established resident groups, one female is behaviorally dominant in parties of dispersing females. During dispersal and the first 4 months after new group formation, survival is lower for all females compared with established resident groups. At the same time, subordinates in disperser groups have higher birth rates than those in established groups, which rarely breed successfully. This may partly offset the survival costs of dispersal to subordinate females. Further studies of dispersal based on direct observation of dispersing animals are needed to explore the costs and benefits of dispersal in species with contrasting breeding systems.

Low-coverage reduced representation sequencing reveals subtle within-island genetic structure in Aldabra giant tortoises.

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.

Timing outweighs magnitude of rainfall in shaping population dynamics of a small mammal species in steppe grassland.

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.

Life-history responses of a freshwater rotifer to copper pollution.

In organisms with dormant stages, life-history responses to past pollution can be studied retrospectively. Here, we study such responses in a rotifer (Brachionus calyciflorus) from the once heavily copper-polluted Lake Orta (Italy). We extracted resting eggs from sediments, established clonal lineages from hatchlings, and exposed newborns of these lineages to one of three copper concentrations that each mimicked a specific period in the lake's pollution history. For each rotifer, we daily collected life-table data. We then estimated treatment-specific vital rates and used a stage-structured population model to project population growth rate λ. We also estimated elasticities of λ to vital rates and contributions of vital rates to observed Δλ between copper treatments. As expected, λ decreased with increasing copper concentration. This decrease resulted mostly from a decline in juvenile survival rate (SJ ) and partly from a decline in the survival rate of asexually reproducing females (SA ). Maturation rate, and with one exception fecundity, also declined but did not contribute consistently to Δλ. λ was most elastic to SJ and SA , indicating that survival rates were under stronger selection than maturation rate and fecundity. Together, our results indicate that variation in juvenile survival is a key component in the rotifers' copper response. The consistent decrease in SJ with increasing copper stress and the sensitivity of λ to that decrease also suggest that juvenile survival is a useful indicator of population performance under environmental pollution.

Behavioural change during dispersal and its relationship to survival and reproduction in a cooperative breeder.

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 dominant individuals. Mirroring conception rates, in resident groups, fGCM concentrations were lower in subordinates than in dominants, whereas in disperser groups, fGCM concentrations did not differ between subordinates and dominants. Our results, which highlight the relationship between behavioural and physiological factors and demographic rates, provide insights into some of the mechanisms that individuals of a cooperative species can use to increase overall dispersal success.

Forest management affects seasonal source-sink dynamics in a territorial, group-living bird.

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.