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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. Graphical abstract

Habitat selection is a dynamic biological process where species respond to spatiotemporal variation in resource availability. The resulting distribution patterns can be detected as presence–absence or heterogeneity in abundance and indicate habitat preferences based on environmental correlations at multiple scales. Variation in habitat selection by ungulates is constrained by trade-offs in top-down and bottom-up trophic processes arising from differences in forage requirements, water dependency, anthropogenic effects, and predation avoidance, and mediated by physiological (feeding guild) and morphological (body size) factors. We conducted distance sampling over 7 years in the Tarangire Ecosystem (TE) of northern Tanzania for six resident ungulate species: Kirk’s dik-dik (Madoqua kirkii), Grant’s gazelle (Nanger granti), Thomson’s gazelle (Eudorcas thomsonii), Masai giraffe (Giraffa camelopardalis tippelskirchi), impala (Aepyceros melampus), and common waterbuck (Kobus ellipsiprymnus), and tested hypotheses related to effects of top-down and bottom-up processes on ungulate presence and abundance. We modeled ecological correlates against two distributional responses to understand which environmental factors constrained these ungulate species at different scales; (i) presence–absence observations modeled in a logistic regression to assess habitat selection at an ecosystem scale; (ii) local abundances from presence-only observations modeled using a negative binomial distribution for finer-scale selection. Browser and grazer species in the TE selected suitable habitat proximal to rivers and avoided the Combretum–Azanza woody plant assemblage. Browsers and grazers also showed strong preference for habitat with more dense cover of preferred forage species, and abundance was influenced by the presence of specific forage species with significant seasonal variation. Mixed feeders were more heterogeneous in habitat suitability implying that broader diets allow avoidance of areas with high human activity. Small-bodied and dehydration-sensitive species selected areas near rivers and seasonal tributaries. Seasonal habitat selection was more pronounced among mixed feeders. Conservation strategies based on spatially and seasonally explicit resource selection studies such as ours can minimize impacts to biodiversity by protecting vital resources to ungulates through all seasons of the year.

Many ungulate species in Africa range in habitats that vary in type and quality over space and time, but ongoing environmental change is substantially altering their habitats. Identifying key environmental variables that regulate ungulate population densities can guide management actions for effective conservation. We studied the local population density responses of a community of sympatric ungulate species in the Tarangire Ecosystem of northern Tanzania, to a suite of environmental factors that vary over space and time, to quantify population trends, determine the primary environmental correlates of densities, and identify covariation in densities among species. We estimated seasonal densities of five commonly detected species (impala, dik-dik, Grant’s gazelle, eland, and waterbuck) based on 7 years of distance-sampling data from 41 replicate surveys of 237 line transects. We systematically analyzed the effects of spatial, seasonal, and annual environmental covariates on variation in transect species-specific densities across space and time. Despite large fluctuations in climatic factors, we documented more spatial than temporal variation in four of the five species, suggesting that spatial heterogeneity may provide some buffer against temporal variation in the environment. Protection of sufficient habitats and water sources should allow ungulates to respond to a temporally changing world by moving across space. Further, among-species covariation patterns identified two potential ungulate guilds (impala—dik-dik—waterbuck; eland—grant’s gazelle) that should aid in developing efficient and coordinated management actions.

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.

Data and code for Ozgul et al. 2023 (PNAS) Ozgul A, Fichtel C, Paniw M, Kappeler PM (2023) Destabilising effect of climate change on the persistence of a short-lived primate. Proceedings of the National Academy of Sciences USA (https://doi.org/10.1073/pnas.2214244120)

Funder: University of Zurich; Id: http://dx.doi.org/10.13039/501100006447, Funder: MAVA Foundation, Funder: Mammal Research Institute at the University of Pretoria, 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.

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 ssof climate change on alpine amphibian populations. Moreover, we show that changes in phenology, especially in the mountains, can be hard to predict as local microclimatic conditions do not necessarily reflect the observed global climatic trends.

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 major force driving the structure of bird assemblages in this mountain region. This work also shows that association analyses should not be underestimated as they can provide clues to the mechanisms responsible for community structure., VGN was supported by a Forschungskredit (grant ref. FK-18-104) from University of Zurich, a CEEC Individual contract (ref. CEEIND/00086/2018) from the Fundação para a Ciência e a Tecnologia (Portugal), and a ‘Ramón y Cajal’ contract (ref. RYC2019-026703-I) from the Spanish Ministry of Science and Innovation.

1. 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).2. For such species, classical spatial measures of dispersal, such as distance moved, might not capture social dispersal.3. 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.4. 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.5. Our study highlights the potential importance of social structure in dispersal decisions, and of tracking social structure when studying dispersal in multi-level societies, as effective dispersal can be attained without large-scale spatial displacements. published

AimTo evaluate the utility of opportunistic data from citizen science programmes for forecasting species distributions against forecasts with a model of individual-based population dynamics.LocationSweden.MethodsWe 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.ResultsForecasts 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 benchmark models, sometimes with misleading rankings of future scenarios.Main conclusionsOur 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 recommend that citizen science projects incorporate procedures to evaluate reporting behaviour. Inferred absences may be especially useful for improving forecasts for species and regions poorly covered by systematic monitoring schemes. published

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.

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 of resilience of ecological systems in response to environmental perturbations.

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 represent a significant driver of community assembly in Alpine bird communities and support the notion that phylogeny may often not be a good proxy for traits subject to environmental filtering.

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.

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 characterize 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. published

BackgroundThe 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.FindingsWe 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.ConclusionsWe 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.

The supplementary analysis, figures and tables that supporting this article

In 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 (

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 5,426 variant sites within the tortoise genome, we detected patterns of population structure within two of the three studied islands, 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.

In socially structured animal populations, vital rates such as survival and reproduction, are affected by complex interactions among individuals of different social ranks and among social groups. Due to this complexity, mechanistic approaches to model vital rates may be preferred over commonly used structured population models. However, mechanistic approaches come at a cost of increased modelling complexity, computational requirements, and reliance on simulated metrics, while structured population models are analytically tractable. This chapter compares different approaches to modelling population dynamics of socially structured populations. It first simulates individual-based data based on the life cycle of a hypothetical cooperative breeder and then projects population dynamics using a matrix population model (MPM), an integral projection model (IPM), and an individual-based model (IBM). The authors demonstrate that, when projecting population size or structure, the relatively simpler MPM can outperform both the IPM and IBM. However, mechanistic details parametrised in the more complex IBM are required to accurately project interactions within social groups. The R scripts in this chapter provide a roadmap to both simulate data that best describe a socially structured system and assess the level of model complexity needed to capture the dynamics of the system.

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.

Temporal variation in vital rates (e.g., survival, reproduction) can decrease the long-term mean performance of a population. Species are therefore expected to evolve demographic strategies that counteract the negative effects of vital rate variation on the population growth rate. One key strategy, demographic buffering, is reflected in a low temporal variation in vital rates critical to population dynamics. However, comparative studies in plants have found little evidence for demographic buffering, and little is known about the prevalence of buffering in animal populations. Here, we used vital rate estimates from 31 natural populations of 29 animal species to assess the prevalence of demographic buffering. We modeled the degree of demographic buffering using a standard measure of correlation between the standard deviation of vital rates and the sensitivity of the population growth rate to changes in such vital rates across populations. We also accounted for the effects of life-history traits, i.e., age at first reproduction and spread of reproduction across the life cycle, on these correlation measures. We found no strong or consistent evidence of demographic buffering across the study populations. Instead, key vital rates could vary substantially depending on the specific environmental context populations experience. We suggest that it is time to look beyond concepts of demographic buffering when studying natural populations towards a stronger focus on the environmental context-dependence of vital-rate variation.

Environmental change can impact the stability of populations and can cause rapid declines in abundance. Abundance-based warning signals have been proposed to predict such declines, but these have been shown to have limited success, leading to the development of warning signals based on the distribution of fitness-related traits such as body size.The dynamics of such traits in response to external environmental perturbations are controlled by a range of underlying factors such as reproductive rate, genetic variation, and plasticity. However, it remains unknown how such ecological and evolutionary factors affect the stability landscape of populations and the detectability of abundance and trait-based warning signals of population decline.Here, we apply a trait-based demographic approach and investigate both trait and population dynamics in response to gradual changes in the environment. We explore a range of ecological and evolutionary constraints under which the stability of a population may be affected.We show both analytically and with model-based simulations that strength of abundance-based early warning signals is significantly affected by ecological and evolutionary factors.Finally, we show that a unified approach, combining trait- and abundance-based information, significantly improves our ability to predict population declines. Our study suggests that the inclusion of trait dynamic information alongside generic warning signals should provide more accurate forecasts of the future state of biological systems.

The study of mammals has promoted the development and testing of many ideas in contemporary ecology. Here we address recent developments in foraging and habitat selection, source–sink dynamics, competition (both within and between species), population cycles, predation (including apparent competition), mutualism, and biological invasions. Because mammals are appealing to the public, ecological insight gleaned from the study of mammals has disproportionate potential in educating the public about ecological principles and their application to wise management. Mammals have been central to many computational and statistical developments in recent years, including refinements to traditional approaches and metrics (e.g., capture-recapture) as well as advancements of novel and developing fields (e.g., spatial capture-recapture, occupancy modeling, integrated population models). The study of mammals also poses challenges in terms of fully characterizing dynamics in natural conditions. Ongoing climate change threatens to affect global ecosystems, and mammals provide visible and charismatic subjects for research on local and regional effects of such change as well as predictive modeling of the long-term effects on ecosystem function and stability. Although much remains to be done, the population ecology of mammals continues to be a vibrant and rapidly developing field. We anticipate that the next quarter century will prove as exciting and productive for the study of mammals as has the recent one.

Life‐history theory states that, during the lifetime of an individual, resources are allocated to either somatic maintenance or reproduction. Resource allocation tradeoffs determine the evolution and ecology of life‐history strategies and determine an organisms’ position along the fast–slow continuum. Theory predicts that environmental stochasticity is an important driver of resource allocation and therefore life‐history evolution. Highly stochastic environments are expected to increase uncertainty in reproductive success and select for iteroparity and a slowing down of the life history. To date, most empirical studies have used comparisons among species to examine these theoretical predictions. By contrast, few have investigated how environmental stochasticity affects life‐history strategies at the intraspecific level. In this study, we examined how variation in breeding site stochasticity (among‐year variability in pond volume and hydroperiod) promotes the co‐occurrence of different life‐history strategies in a spatially structured population, and determines life‐history position along the fast–slow continuum in the yellow‐bellied toad Bombina variegata. We collected mark–recapture data from a metapopulation and used multievent capture–recapture models to estimate survival, recruitment and breeding probabilities. We found higher survival and longer lifespans in populations inhabiting variable sites compared to those breeding in stable ones. In addition, probabilities of recruitment and skipping a breeding event were higher in variable sites. The temporal variance of survival and recruitment probabilities, as well as the probability to skip breeding, was higher in variable sites. Taken together, these findings indicate that populations breeding in variable sites experienced a slowing down of the life‐history. Our study thus revealed similarities in the macroevolutionary and microevolutionary processes shaping life‐history evolution.

Resource availability plays a key role in driving variation in somatic growth and body condition, and the factors determining access to resources vary considerably across life stages. Parents and carers may exert important influences in early life, when individuals are nutritionally dependent, with abiotic environmental effects having stronger influences later in development as individuals forage independently. Most studies have measured specific factors influencing growth across development or have compared relative influences of different factors within specific life stages. Such studies may not capture whether early-life factors continue to have delayed effects at later stages, or whether social factors change when individuals become nutritionally independent and adults become competitors for, rather than providers of, food. Here, we examined variation in the influence of the abiotic, social and maternal environment on growth across life stages in a wild population of cooperatively breeding meerkats. Cooperatively breeding vertebrates are ideal for investigating environmental influences on growth. In addition to experiencing highly variable abiotic conditions, cooperative breeders are typified by heterogeneity both among breeders, with mothers varying in age and social status, and in the number of carers present. Recent rainfall had a consistently marked effect on growth across life stages, yet other seasonal terms only influenced growth during stages when individuals were growing fastest. Group size and maternal dominance status had positive effects on growth during the period of nutritional dependence on carers, but did not influence mass at emergence (at 1 month) or growth at independent stages (>4 months). Pups born to older mothers were lighter at 1 month of age and subsequently grew faster as subadults. Males grew faster than females during the juvenile and subadult stage only. Our findings demonstrate the complex ways in which the external environment influences development in a cooperative mammal. Individuals are most sensitive to social and maternal factors during the period of nutritional dependence on carers, whereas direct environmental effects are relatively more important later in development. Understanding the way in which environmental sensitivity varies across life stages is likely to be an important consideration in predicting trait responses to environmental change.

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., We studied how rotifer vital rates respond to increasing copper pollution and whether these responses alter population fitness. We identified juvenile survival as the key component in the rotifers' copper response: juvenile survival declined with increasing copper pollution, and population fitness was sensitive to that decline.

Studies increasingly show that social connectedness plays a key role in determining survival, in addition to natural and anthropogenic environmental factors. Few studies, however, integrated social, non-social and demographic data to elucidate what components of an animal's socio-ecological environment are most important to their survival. Female giraffes ( Giraffa camelopardalis ) form structured societies with highly dynamic group membership but stable long-term associations. We examined the relative contributions of sociability (relationship strength, gregariousness and betweenness), together with those of the natural (food sources and vegetation types) and anthropogenic environment (distance from human settlements), to adult female giraffe survival. We tested predictions about the influence of sociability and natural and human factors at two social levels: the individual and the social community. Survival was primarily driven by individual- rather than community-level social factors. Gregariousness (the number of other females each individual was observed with on average) was most important in explaining variation in female adult survival, more than other social traits and any natural or anthropogenic environmental factors. For adult female giraffes, grouping with more other females, even as group membership frequently changes, is correlated with better survival, and this sociability appears to be more important than several attributes of their non-social environment.

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.

When facing an emerging infectious disease of conservation concern, we often have little information on the nature of the host-parasite interaction to inform management decisions. However, it is becoming increasingly clear that the life-history strategies of host species can be predictive of individual- and population-level responses to infectious disease, even without detailed knowledge on the specifics of the host-parasite interaction. Here, we argue that a deeper integration of life-history theory into disease ecology is timely and necessary to improve our capacity to understand, predict and mitigate the impact of endemic and emerging infectious diseases in wild populations. Using wild vertebrates as an example, we show that host life-history characteristics influence host responses to parasitism at different levels of organisation, from individuals to communities. We also highlight knowledge gaps and future directions for the study of life-history and host responses to parasitism. We conclude by illustrating how this theoretical insight can inform the monitoring and control of infectious diseases in wildlife.

Climate variability has been widely documented to have bottom-up effects on the population dynamics of animals1,2, but the mechanisms underlying these effects have been rarely investigated through field manipulative experiments that control for confounding factors3. Here, we examined the effects of different rainfall patterns (i.e. timing and amount) on the population size of Brandt’s voles Lasiopodomys brandtii in semi-arid steppe grassland in Inner-Mongolia by conducting a 10-year (2010-2019) rainfall manipulation experiment in twelve 0.48 ha field enclosures. We found that moderate rainfall increase during the early rather than late growing season drove marked increases in population size through increasing the biomass of preferred plant species, whereas heavily increased rainfall produced no further increase in vole population growth. The increase in vole population size was more coupled with increased reproduction of overwintered voles and increased body mass of young-of-year than with better survival. Our results provide the first experimental evidence for the bottom-up effects of changing rainfall on the population growth of small mammals, and highlight the importance of rainfall timing on the population dynamics of wildlife in the steppe grassland environment.

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.

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.

Natural populations are increasingly threatened with collapse at the hands of anthropogenic effects. Predicting population collapse with the help of generic early warning signals (EWS) may provide a prospective tool for identifying species or populations at highest risk. However, pattern-to-process methods such as EWS have a multitude of challenges to overcome to be useful, including the low signal-to-noise ratio of ecological systems and the need for high quality time series data. The inclusion of trait dynamics with EWS has been proposed as a more robust tool to predict population collapse. However, the length and resolution of available time series are highly variable from one system to another, especially when generation time is considered. As yet, it remains unknown how this variability with regards to generation time will alter the efficacy of EWS. Here we take both a simulation- and experimental-based approach to assess the impacts of relative time series length and resolution on the forecasting ability of EWS. We show that EWS' performance decreases with decreasing time-series length. However, there was no evident decrease in EWS performance as resolution decreased. Our simulations suggest a relative time series length between 10 and five generations as a minimum requirement for accurate forecasting by abundance-based EWS. However, when trait information is included alongside abundance-based EWS, we find positive signals at lengths one-half of what was required without them. We suggest that, in systems where specific traits are known to affect demography, trait data should be monitored and included alongside abundance data to improve forecasting reliability.

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.

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.

Global climate change is leading to decreased climatic predictability. Theoretical work indicates that changes in the climate’s intrinsic predictability will affect population dynamics and extinction, but experimental evidence is scarce. Here, we experimentally tested whether differences in intrinsic precipitation predictability affect population dynamics of the European common lizard (Zootoca vivipara) by simulating more predictable (MP) and less predictable (LP) precipitation in 12 seminatural populations over 3 years and measuring different vital rates. A seasonal age-structured matrix model was parametrized to assess treatment effects on vital rates and asymptotic population growth (λ). There was a nonsignificant trend for survival being higher in MP than in LP precipitation, and no differences existed in reproductive rates. Small nonsignificant survival differences in adults explained changes in λ, and survival differences among age classes were in line with predictions from cohort resonance. As a result, λ was significantly higher in MP than in LP precipitation. This experimentally shows that small effects have major consequences on λ, that forecasted decreases in precipitation predictability are likely to exacerbate the current rate of population decline and extinction, and that stage-structured matrix models are required to unravel the aftermath of climate change., The Spanish Ministry of Education through the Formación de Profesorado Universitario grant (FPU 13/03291) supported G.M. Funds were provided by the Spanish Ministry of Education and Science (CGL2008-01522, CGL2012-32459,and CGL2016-76918P to P.S.F.) and the Swiss National Science Foundation (PPOOP3_128375 and PP00P3_152929/1to P.S.F.).

For highly social species, population dynamics depend on hierarchical demography that links local processes, group dynamics, and population growth. Here, we describe a stage-structured matrix model of hierarchical demography, which provides a framework for understanding social influences on population change. Our approach accounts for dispersal and affords insight into population dynamics at multiple scales. The method has close parallels to integral projection models but focuses on a discrete characteristic (group size). Using detailed long-term records for meerkats (Suricata suricatta), we apply our model to explore patterns of local density dependence and implications of group size for group and population growth. Taking into account dispersers, the model predicts a per capita growth rate for social groups that declines with group size. It predicts that larger social groups should produce a greater number of new breeding groups; thus, dominant breeding females (responsible for most reproduction) are likely to be more productive in larger groups. Considering the potential for future population growth, larger groups have the highest reproductive value, but per capita reproductive value is maximized for individuals in smaller groups. Across a plausible range of dispersal conditions, meerkats' long-run population growth rate is maximized when individuals form groups of intermediate size.

Dispersal is a key ecological process that influences the dynamics of spatially and socially structured populations and consists of three stages-emigration, transience, and settlement-and each stage is influenced by different social, individual, and environmental factors. Despite our appreciation of the complexity of the process, we lack a firm empirical understanding of the mechanisms underlying the different stages. Here, using data from 65 GPS-collared dispersing female coalitions of the cooperatively breeding meerkat (Suricata suricatta), we present a comprehensive analysis of the effects of population density, mate availability, dispersing coalition size, and individual factors on each of the three stages of dispersal in a wild population. We expected a positive effect of density on dispersal due to increased kin competition at high densities. We further anticipated positive effects of mate availability, coalition size, and body condition on dispersal success. We observed increasing daily emigration and settlement probabilities at high population densities. In addition, we found that emigration and settlement probabilities also increased at low densities and were lowest at medium densities. Daily emigration and settlement probabilities increased with increasing female coalition size and in the presence of unrelated males. Furthermore, the time individuals spent in the transient stage increased with population density, whereas coalition size and presence of unrelated males decreased dispersal distance. The observed nonlinear relationship between dispersal and population density is likely due to limited benefits of cooperation at low population densities and increased kin competition at high densities. Our study provides empirical validation for the theoretical predictions that population density is an important factor driving the evolution of delayed dispersal and philopatry in cooperative breeders.

We studied the temperature relations of wild and zoo Aldabra giant tortoises (Aldabrachelys gigantea) focusing on (1) the relationship between environmental temperature and tortoise activity patterns (n = 8 wild individuals) and (2) on tortoise body temperature fluctuations, including how their core and external body temperatures vary in relation to different environmental temperature ranges (seasons; n = 4 wild and n = 5 zoo individuals). In addition, we surveyed the literature to review the effect of body mass on core body temperature range in relation to environmental temperature in the Testudinidae. Diurnal activity of tortoises was bimodally distributed and influenced by environmental temperature and season. The mean air temperature at which activity is maximized was 27.9°C, with a range of 25.8–31.7°C. Furthermore, air temperature explained changes in the core body temperature better than did mass, and only during the coldest trial, did tortoises with higher mass show more stable temperatures. Our results, together with the overall Testudinidae overview, suggest that, once variation in environmental temperature has been taken into account, there is little effect of mass on the temperature stability of tortoises. Moreover, the presence of thermal inertia in an individual tortoise depends on the environmental temperatures, and we found no evidence for inertial homeothermy. Finally, patterns of core and external body temperatures in comparison with environmental temperatures suggest that Aldabra giant tortoises act as mixed conformer–regulators. Our study provides a baseline to manage the thermal environment of wild and rewilded populations of an important island ecosystem engineer species in an era of climate change.

Temporal autocorrelation in demographic processes is an important aspect of population dynamics, but a comprehensive examination of its effects on different life-history strategies is lacking. We use matrix population models from 454 plant and animal populations to simulate stochastic population growth rates (log lambda(s)) under different temporal autocorrelations in demographic rates, using simulated and observed covariation among rates. We then test for differences in sensitivities, or changes of log lambda(s) to changes in autocorrelation among two major axes of life-history strategies, obtained from phylogenetically informed principal component analysis: the fast-slow and reproductive-strategy continua. Fast life histories exhibit highest sensitivities to simulated autocorrelation in demographic rates across reproductive strategies. Slow life histories are less sensitive to temporal autocorrelation, but their sensitivities increase among highly iteroparous species. We provide cross-taxonomic evidence that changes in the autocorrelation of environmental variation may affect a wide range of species, depending on complex interactions of life-history strategies.