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The insurance effect of biodiversity—that diversity stabilises aggregate ecosystem properties—is mechanistically underlain by inter- and intraspecific trait variation in organismal responses to the environment. This variation, termedresponse diversity, is therefore a potentially critical determinant of ecological stability. However, response diversity has yet to be widely quantified, possibly due to difficulties in its measurement. Even when it has been measured, approaches have varied.Here, we review methods for measuring response diversity and from them distil a methodological framework for quantifying response diversity from experimental and/or observational data, which can be practically applied in lab and field settings across a range of taxa.Previous empirical studies on response diversity most commonly invoke response traits as proxies aimed at capturing species’ ecological responses to the environment. Our approach, which is based on environment-dependent ecological responses to any biotic or abiotic environmental variable, is conceptually simple and robust to any form of environmental response, including nonlinear responses. Given its derivation from empirical data on species’ ecological responses, this approach should more directly reflect response diversity than the trait-based approach dominant in the literature.By capturing even subtle inter- or intraspecific variation in environmental responses, and environment-dependencies in response diversity, we hope this framework will motivate tests of the diversity-stability relationship from a new perspective, and provide an approach for mapping, monitoring, and conserving this critical dimension of biodiversity.

There is growing awareness of pollinator declines worldwide. Conservation efforts have mainly focused on finding the direct causes, while paying less attention to building a systemic understanding of the fragility of these communities of pollinators. To fill this gap, we need operational measures of network resilience that integrate two different approaches in theoretical ecology. First, we should consider the range of conditions compatible with the stable coexistence of all of the species in a community. Second, we should address the rate and shape of network collapse once this safe operational space is exited. In this review, we describe this integrative approach and consider several mechanisms that may enhance the resilience of pollinator communities, chiefly rewiring the network of interactions, increasing heterogeneity, allowing variance, and enhancing coevolution. The most pressing need is to develop ways to reduce the gap between these theoretical recommendations and practical applications. This perspective shifts the emphasis from traditional approaches focusing on the equilibrium states to strategies that allow pollination networks to cope with global environmental change. Expected final online publication date for the

Major climatic changes in conjunction with animal movement may be associated with the spread of parasites and their vectors into new populations, with potentially important consequences for population persistence. Parasites can evolve to adapt to unsuitable ecological conditions and take up refuge within new host species, with consequences for the population growth of the new host species. One parasite species that has likely been increasing its geographic range, and potentially infecting new hosts, is the recently described air sac nematode Serratospiculoides amaculata, in great tits (Parus major) in Slovakia. In this study, we screened wild birds for potential air sac nematode infection in a woodland area of southern Germany. We identified four additional host species: Eurasian nuthatch, great spotted woodpecker, greenfinch and robin. As infection by this group of nematodes can be highly pathogenic, we recommend further investigation into its potential risk to these populations., International Journal for Parasitology. Parasites and Wildlife, 21, ISSN:2213-2244

Protecting nature’s contributions to people requires accelerating extinction risk assessment and better integrating evolutionary, functional and used diversity with conservation planning. Here, we report machine learning extinction risk predictions for 1,381 palm species (Arecaceae), a plant family of high socio-economic and ecological importance. We integrate these predictions with published assessments for 508 species (covering 75% of all palm species) and we identify top-priority regions for palm conservation on the basis of their proportion of threatened evolutionarily distinct, functionally distinct and used species. Finally, we explore palm use resilience to identify non-threatened species that could potentially serve as substitutes for threatened used species by providing similar products. We estimate that over a thousand palms (56%) are probably threatened, including 185 species with documented uses. Some regions (New Guinea, Vanuatu and Vietnam) emerge as top ten priorities for conservation only after incorporating machine learning extinction risk predictions. Potential substitutes are identified for 91% of the threatened used species and regional use resilience increases with total palm richness. However, 16 threatened used species lack potential substitutes and 30 regions lack substitutes for at least one of their threatened used palm species. Overall, we show that hundreds of species of this keystone family face extinction, some of them probably irreplaceable, at least locally. This highlights the need for urgent actions to avoid major repercussions on palm-associated ecosystem processes and human livelihoods in the coming decades.

The ever-increasing threats to riverine ecosystems call for novel approaches for highly resolved biodiversity assessments across taxonomic groups and spatio-temporal scales. Recent advances in the joint use of environmental DNA (eDNA) data and eDNA transport models in rivers (e.g., eDITH) allow uncovering the full structure of riverine biodiversity, hence elucidating ecosystem processes and supporting conservation measures. We applied eDITH to a metabarcoding dataset covering three taxonomic groups (fish, invertebrates, bacteria) and three seasons for a catchment sampled for eDNA at 73 sites. We upscaled eDNA-based biodiversity predictions to approximately 1900 reaches, and assessed α- and β-diversity patterns across seasons and taxonomic groups over the whole network. Genus richness predicted by eDITH was generally higher than values from direct eDNA analysis. Both predicted α- and β-diversity varied depending on season and taxonomic group. Predicted fish α-diversity increased downstream in all seasons, while invertebrate and bacteria α-diversity either decreased downstream or were unrelated to network position. Spatial β-diversity mostly decreased downstream, especially for bacteria. The eDITH model yielded a more refined assessment of freshwater biodiversity as compared to raw eDNA data, both in terms of spatial coverage, diversity patterns and effect of covariates, thus providing a more complete picture of freshwater biodiversity.

Ecosystem restoration is becoming a widely recognised solution to the biodiversity crisis. However, there is a gap between restoration science and practice. Specifically, we lack a theoretical framework which would improve our understanding of ecosystems’ recovery and allow us to optimise restoration design. Here, we narrow this gap by developing spatially explicit metacommunity models and studying the recovery dynamics of communities during restoration. We show that community response depends on how damaged the landscape is prior to restoration, with highly fragmented landscapes imposing greater challenges to community recovery. In such cases, we found that the recovery depends on the type of interaction and the structure of the interaction network. Finally, we demonstrate that community recovery can be maximised with careful spatial planning. When recovering communities composed of antagonistic interactions, restoration should target areas adjacent to the most species-rich sites. In the case of mutualistic communities, the same strategy should be adopted in the short-term, whereas in the long-term, restoration should be extended to sites that improve the overall connectivity of the landscape. Our results highlight the importance of considering interactions between species and spatial planning in restoration projects.

Frequency-dependent selection (FDS) drives an evolutionary regime that maintains or disrupts polymorphisms. Despite the increasing feasibility of genetic association studies on fitness components, there are a few methods to uncover the loci underlying FDS. Based on a simplified model of pairwise genotype–genotype interactions, we propose a linear regression that can infer FDS from observed fitness. The key idea behind our method is the inclusion of genotype similarity as a pseudo-trait in selection gradient analysis. Single-locus analysis of Arabidopsis and damselfly data could detect known negative FDS on visible polymorphism that followed Mendelian inheritance with complete dominance. By extending the singlelocus analysis to genome-wide association study (GWAS), our simulations showed that the regression coefficient of genotype similarity can distinguish negative or positive FDS without confounding other forms of balancing selection. Field GWAS of the branch number further revealed that negative FDS, rather than positive FDS, was enriched among the top-scoring single nucleotide polymorphisms (SNPs) in Arabidopsis thaliana. These results showed the wide applicability of our method for FDS on both visible polymorphism and genome-wide SNPs. Our study provides an effective method for selection gradient analysis to understand the maintenance or loss of polymorphism.

The assembly of microbial communities through sequential invasions of microbial species is challenging to study experimentally. Here, I used genome-scale metabolic models of multiple species to model community assembly. Each such model represents all known biochemical reactions that a species uses to build biomass from nutrients in the environment. Species interactions in such models emerge from first biochemical principles, either through competition for environmental nutrients, or through cross-feeding on metabolic by-products excreted by resident species. I used these models to study 250 community assembly sequences. In each such sequence, a community changes through successive species invasions. During the 250 assembly sequences, communities become more species-rich and invasion-resistant. Resistance against both constructive and destructive invasions - those that entail species extinction - is associated with high community productivity, high biomass, and low concentrations of unused carbon. Competition for nutrients outweighs the influence of cross-feeding on the growth rate of individual species. In a community assembly network of all communities that arise during the 250 assembly sequences, some communities occur more often than expected by chance. These include invasion resistant "attractor" communities with high biomass that arise late in community assembly and persist preferentially because of their invasion resistance. Genome-scale metabolic models can reveal generic properties of microbial communities that are independent of the resident species and the environment.

Interspecific niche complementarity is a key mechanism posited to explain positive species richness-productivity relationships in plant communities. However, the exact nature of the niche dimensions that plant species partition remains poorly known.Species may partition abiotic resources that limit their growth, but species may also be specialized with respect to their set of biotic interactions with other trophic levels, in particular with enemies including pathogens and consumers. The lower host densities present in more species-diverse plant communities may therefore result in smaller populations of specialized enemies, and in a smaller associated negative feedback these enemies exert on plant productivity.To test whether such host density-dependent effects of enemies drive diversity-productivity relationships in young forest stands, we experimentally manipulated leaf fungal pathogens and insect herbivores in a large subtropical forest biodiversity-ecosystem functioning experiment in China (BEF-China).We found that fungicide spraying of tree canopies removed the positive tree-species richness-productivity relationship present in untreated control plots. The tree species that contributed the most to this effect were the ones with the highest fungicide-induced growth increase in monoculture. Insecticide application did not cause comparable effects.

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.

Population bottlenecks can have dramatic consequences for the health and long-term survival of a species. Understanding of historic population size and standing genetic variation prior to a contraction allows estimating the impact of a bottleneck on the species' genetic diversity. Although historic population sizes can be modelled based on extant genomics, uncertainty is high for the last 10-20 millenia. Hence, integrating ancient genomes provides a powerful complement to retrace the evolution of genetic diversity through population fluctuations. Here, we recover 15 high-quality mitogenomes of the once nearly extinct Alpine ibex spanning 8601 BP to 1919 CE and combine these with 60 published modern whole genomes. Coalescent demography simulations based on modern whole genomes indicate population fluctuations coinciding with the last major glaciation period. Using our ancient and historic mitogenomes, we investigate the more recent demographic history of the species and show that mitochondrial haplotype diversity was reduced to a fifth of the prebottleneck diversity with several highly differentiated mitochondrial lineages having coexisted historically. The main collapse of mitochondrial diversity coincides with elevated human population growth during the last 1-2 kya. After recovery, one lineage was spread and nearly fixed across the Alps due to recolonization efforts. Our study highlights that a combined approach integrating genomic data of ancient, historic and extant populations unravels major long-term population fluctuations from the emergence of a species through its near extinction up to the recent past.

The pollution of freshwater ecosystems is threatening freshwater plant species diversity worldwide. Freshwater plants, such as the common duckweed (Lemna minor), are potentially sensitive to novel stressful environments. To test if ecotype diversity could increase resistance to stressful environments, I used seven L. minor populations and measured their growth rates with and without moderate salt stress across an ecotype diversity gradient. The L. minor populations were grown over 5 months in 92 experimental mesocosms, either in ecotype monocultures or in polyculture with either one or three conspecific ecotypes (23 unique compositions). After growing the duckweed in unperturbed conditions (phase 1), the cultures were subjected to moderate salt stress (50 mmol/L NaCl) for several weeks (phase 2). The experiment was conducted in the presence of the natural epimicrobial community associated with the different ecotypes. In phase 2, a subset of these algae added an unintentional second stressor to the experiment. The ecotypes differed in their growth rates, the fastest growing at twice the rate of others. The diversity context further shaped the ecotype growth rates. Ecotype polycultures showed higher abundances towards the end of the experiment, thus over time, as the environment deteriorated, ecotype diversity gained in importance. These findings show that within-species variation in growth rates can translate to a positive effect of ecotype diversity on population abundance. Exposure of L. minor to moderate salt levels did not significantly impact growth rates, although the effect may have been masked by reduced algal stress in the saline environments.

Genes encode information that determines an organism’s fitness. Yet we know little about whether genes of one species influence the persistence of interacting species in an ecological community. Here, we experimentally tested the effect of three plant defense genes on the persistence of an insect food web and found that a single allele at a single gene promoted coexistence by increasing plant growth rate, which in turn increased the intrinsic growth rates of species across multiple trophic levels. Our discovery of a “keystone gene” illustrates the need to bridge between biological scales, from genes to ecosystems, to understand community persistence.

Global change encompasses many co-occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction-norm perspective can improve our ability to make predictions of interactions at higher levels of organization-that is, community and food web. Building on the framework of consumer-resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof-of-concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.

Metabarcoding of environmental DNA (eDNA) is a powerful tool for describing biodiversity, such as finding keystone species or detecting invasive species in environmental samples. Continuous improvements in the method and the advances in sequencing platforms over the last decade have meant this approach is now widely used in biodiversity sciences and biomonitoring. For its general use, the method hinges on a correct identification of taxa. However, past studies have shown how this crucially depends on important decisions during sampling, sample processing, and subsequent handling of sequencing data. With no clear consensus as to the best practice, particularly the latter has led to varied bioinformatic approaches and recommendations for data preparation and taxonomic identification. In this study, using a large freshwater fish eDNA sequence dataset, we compared the frequently used zero-radius Operational Taxonomic Unit (zOTU) approach of our raw reads and assigned it taxonomically (i) in combination with publicly available reference sequences (open databases) or (ii) with an OSU (Operational Sequence Units) database approach, using a curated database of reference sequences generated from specimen barcoding (closed database). We show both approaches gave comparable results for common species. However, the commonalities between the approaches decreased with read abundance and were thus less reliable and not comparable for rare species. The success of the zOTU approach depended on the suitability, rather than the size, of a reference database. Contrastingly, the OSU approach used reliable DNA sequences and thus often enabled species-level identifications, yet this resolution decreased with the recent phylogenetic age of the species. We show the need to include target group coverage, outgroups and full taxonomic annotation in reference databases to avoid misleading annotations that can occur when using short amplicon sizes as commonly used in eDNA metabarcoding studies. Finally, we make general suggestions to improve the construction and use of reference databases for metabarcoding studies in the future., Environmental DNA, 5 (2), ISSN:2637-4943

Interactions between humans and nature have profound consequences, which rarely are mutually beneficial. Further, behavioral and environmental changes can turn human–wildlife cooperative interactions into conflicts, threatening their continued existence. By tracking fine-scale behavioral interactions between artisanal fishers and wild dolphins targeting migratory mullets, we reveal that foraging synchrony is key to benefiting both predators. Dolphins herd mullet schools toward the coast, increasing prey availability within the reach of the net-casting fishers, who gain higher foraging success—but only when matching the casting behavior with the dolphins’ foraging cues. In turn, when dolphins approach the fishers’ nets closely and cue fishers in, they dive for longer and modify their active foraging echolocation to match the time it takes for nets to sink and close over mullets—but only when fishers respond to their foraging cues appropriately. Using long-term demographic surveys, we show that cooperative foraging generates socioeconomic benefits for net-casting fishers and ca. 13% survival benefits for cooperative dolphins by minimizing spatial overlap with bycatch-prone fisheries. However, recent declines in mullet availability are threatening these short- and long-term benefits by reducing the foraging success of net-casting fishers and increasing the exposure of dolphins to bycatch in the alternative fisheries. Using a numerical model parametrized with our empirical data, we predict that environmental and behavioral changes are pushing this traditional human–dolphin cooperation toward extinction. We propose two possible conservation actions targeting fishers’ behavior that could prevent the erosion of this century-old fishery, thereby safeguarding one of the last remaining cases of human–wildlife cooperation.

Nongenetic parental effects can contribute to the adaptation of species to changing environments by circumventing some of the limitations of genetic inheritance. A clearer understanding of the influence of nongenetic inheritance and its potentially sex-specific responses in daughters and sons is needed to better predict the evolutionary trajectories of species. However, whereas nongenetic maternal effects have long been recognized and widely studied, comparatively little is known about corresponding paternal effects. Here, by following 30 isogenic lines of Drosophila melanogaster across two generations, each reared under two dietary regimes in each generation, we tested how protein restriction during larval development of the fathers affects the fitness and health of their daughters and sons. We then quantified genetic and non-genetic paternal, and direct environmental, effects across multiple axes of offspring fitness. Daughters and sons responded differently to their father’s developmental history. While isolines differed in mean trait values, their specific responses to protein restriction generally varied little. The sex- and trait-specific responses to paternal effects emphasize the complexity of inter-generational parental effects, which raise important questions about their mode of transmission and adaptive value, including the potential for conflict between the sexes.

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.

Microbes are responsible for cycling carbon (C) through soils, and the predictions of how soil C stocks change with warming are highly sensitive to the assumptions made about the mechanisms controlling the microbial physiology response to climate warming. Two mechanisms, microbial thermal-acclimation and changes in the quantity and quality of substrates available for microbial metabolism have been suggested to explain the long-term warming impact on microbial physiology. Yet studies disentangling these two mechanisms are lacking. To resolve the drivers of changes in microbial physiology in response to long-term warming, we sampled soils from 13- and 28-year old soil warming experiments in different seasons. We performed short-term laboratory incubations across a range of temperatures to measure the relationship between temperature sensitivity of physiology (growth, respiration, carbon use efficiency and extracellular enzyme activity) and the chemical composition of soil organic matter. We observed apparent thermal acclimation in microbial processes important for C cycling, but only when warming had exacerbated the seasonally-induced, already small soil organic matter pools. Irrespective of warming, greater quantity and quality of soil carbon enhanced the extracellular enzymatic pool and its temperature sensitivity. We suggest that fresh litter input into the system seasonally cancels apparent thermal acclimation of C-cycling processes. Our findings reveal that long-term warming has indirectly affected microbial physiology via reduced C availability in this system, implying that earth system models including these negative feedbacks may be best suited to describe long-term warming impact in soils.

Assessment of biodiversity using metabarcoding data, such as from bulk or environmental DNA sampling, is becoming increasingly relevant in ecology, biodiversity sciences and monitoring. Thereby, the taxonomic identification of species from their DNA sequences relies strongly on reference databases that link genetic sequences to taxonomic names. These databases vary in completeness and availability, depending on the taxonomic group studied and the genetic region targeted. The incompleteness of reference databases is an important argument to explain the nondetection by metabarcoding of species supposedly present. However, there exist further and generally overlooked problems with reference databases that can lead to false or inaccurate inferences of taxonomic assignment. Here, we synthesize all possible problems inherent to reference databases. In particular, we identify a complete, mutually nonexclusive list of seven classes of challenges when it comes to selecting, developing and using a reference database for taxonomic assignment. These are: (i) mislabelling, (ii) sequencing errors, (iii) sequence conflict, (iv) taxonomic conflict, (v) low taxonomic resolution, (vi) missing taxa and (vii) missing intraspecific variants. For each problem identified, we provide a description of possible consequences on the taxonomic assignment process. We illustrate the respective problem with examples taken from the literature or obtained by quantitative analyses of public databases, such as GenBank or BOLD. Finally, we discuss possible solutions to the identified problems and how to navigate them. Only by raising users' awareness of the limitations of metabarcoding data and DNA reference databases will adequate interpretations of these data be achieved.

How individuals’ prior experience and population evolutionary history shape emergent patterns in animal collectives remains a major gap in the study of collective behaviour. One reason for this is that the processes that can shape individual contributions to collective actions can happen over very different timescales from each other and from the collective actions themselves, resulting in mismatched timescales. For example, a preference to move towards a specific patch might arise from phenotype, memory or physiological state. Although providing critical context to collective actions, bridging different timescales remains conceptually and methodologically challenging. Here, we briefly outline some of these challenges, and discuss existing approaches that have already generated insights into the factors shaping individual contributions in animal collectives. We then explore a case study of mismatching timescales—defining relevant group membership—by combining fine-scaled GPS tracking data and daily field census data from a wild population of vulturine guineafowl ( Acryllium vulturinum ). We show that applying different temporal definitions can produce different assignments of individuals into groups. These assignments can then have consequences when determining individuals' social history, and thus the conclusions we might draw on the impacts of the social environment on collective actions. This article is part of a discussion meeting issue ‘Collective behaviour through time’.

Actuarial senescence, the increase in adult mortality risk with increasing age, is a widespread phenomenon across the animal kingdom. Although between-species variation in the rate of increase in mortality as organisms age (i.e. ageing rate) is now well documented, the occurrence of variation in ageing rate within a given species remains much more debatable. We evaluated the level of within-species variation in ageing rate in four populations of the southern Darwin’s frog (Rhinoderma darwinii) from Chile. Our results revealed strong among-population variation in ageing rates, and these were correlated with the population-specific generation time. A higher ageing rate occurred in populations where individuals exhibited a faster pace of life. Our results, along with recent studies in evolutionarily distant amphibian species, indicate that there can be substantial within-species variation in the rate of ageing, highlighting amphibians as emerging models to study the patterns and mechanisms of intraspecific variation in ageing rate.