Biology subjects

Ozgul, A.

Publications and source records attributed to Ozgul, A..

16 recordsLinked to original sources

bioRxiv2026

Decomposing alarm-calling behaviour to investigate context-dependent threat discrimination and response escalation in a social mongoose

Prey can adjust their behaviour to perceived predation risk, which may induce non-consumptive fitness effects. However, quantifying perceived risk in field studies remains challenging as anti-predator behaviours often integrate multiple processes such as encounter probability and detection capacity. Partitioning prey responses into sub-processes may therefore provide novel insights on predation risk perception. To this end, we decomposed meerkat alarm-calling behaviour into threat discrimination, and response escalation. Using 23 years of data from a wild population in the Kalahari, we evaluated the context-dependence of both components in relation to landscape features, and group composition. We defined threat discrimination as the probability to emit an alarm call at predators (eagles) relative to non-predators (vultures) and response escalation as the strength and intensity of the ensuing collective reaction. We found that discrimination varied with habitat and vegetation productivity. Furthermore, larger groups and the presence of pups increased meerkat threat discrimination, but only during the dry season. Response escalation varied with habitat and group size, but pup presence only increased reaction strength. The contrasting context-dependence among the two alarm-calling components support decomposing compound behaviours rather than quantifying perceived risk from a single behaviour. Thus, we recommend future studies to use this approach, when possible, to improve inference on prey perception and responses to risk.

animal behavior and cognition↗

bioRxiv2026

Demographic change in an iconic dolphin population driven by habitat degradation following a marine heatwave

Extreme climate events are rapidly reshaping ecosystems and contributing to biodiversity loss, yet their long-term impacts remain poorly understood, particularly in marine systems. In 2011, an unprecedented marine heatwave (MHW) on the west coast of Australia drove declines in habitat-forming plants and across taxa spanning multiple trophic levels. Shark Bay, home to an iconic Indo-Pacific bottlenose dolphin (Tursiops aduncus) population, endured temperatures 3-5{degrees}C above long-term means, triggering catastrophic seagrass loss. Using 20 years (2003-2023) of dolphin photo-identification data, we fitted a Bayesian Hidden Markov Model to estimate annual, age-class specific survival probabilities, abundance and recruitment rate, and their association with MHW-mediated seagrass loss in the western (WSB) and eastern (ESB) gulfs of Shark Bay. Adult survival declined markedly, from 0.99 (0.98-1.00) pre-MHW to 0.85 (0.79-0.90) post-MHW in WSB, and from 0.96 (0.92-0.98) to 0.89 (0.85-0.95) in ESB, remaining below pre-MHW levels for several years, while juvenile and calf survival declined in both gulfs to a lesser extent. Recruitment declined in both gulfs and, although recovery was evident in WSB from 2019 onward, continued to decline in ESB until the end of the study. These sustained demographic declines drove substantial reductions in population growth and abundance in both WSB (39%) and ESB (36%). Demographic changes were associated with seagrass loss, here a proxy for habitat and prey availability, with clearest support for adult survival in WSB and a two-year-lagged recruitment response in ESB. This pathway is likely to operate across diverse ecosystems as climate change drives increasing loss of habitat-forming species. The severity and duration of these demographic impacts illustrate that habitat change can cascade through trophic systems to overwhelm demographic resilience in upper-trophic species. This has negative implications for even long-lived, K-selected species, whose slow demographic recovery may not keep pace with the accelerating frequency and intensity of climate disturbance.

ecology↗

bioRxiv2022

Four decades of phenology in an alpine amphibian: trends, stasis and climatic drivers

O_LIStrong 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. C_LIO_LIThe 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. C_LIO_LIWe 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. C_LIO_LIBreeding 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. C_LIO_LIOur 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. C_LI

ecology↗

bioRxiv2022

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

The Aldabra giant tortoise (Aldabrachelys gigantea) is one of only two giant tortoise species left in the world. The species is endemic to Aldabra Atoll in Seychelles and is considered vulnerable due to its limited distribution and threats posed by climate change. Genomic resources for A. gigantea are lacking, hampering conservation efforts focused on both wild and ex-situ populations. A high-quality genome would also open avenues to investigate the genetic basis of the exceptionally long lifespan. Here, we produced the first chromosome-level de novo genome assembly of A. gigantea using PacBio High-Fidelity sequencing and high-throughput chromosome conformation capture (Hi-C). We produced a 2.37 Gbp assembly with a scaffold N50 of 148.6 Mbp and a resolution into 26 chromosomes. RNAseq-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. We also performed a low-coverage re-sequencing 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. The high-quality chromosome-level reference genome for A. gigantea is one of the most complete turtle genomes available. It is a powerful tool to assess the population structure in the wild population and reveal the geographic origins of ex-situ individuals relevant for genetic diversity management and rewilding efforts.

genomics↗

bioRxiv2022

Community structure determines the predictability of population collapse

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

ecology↗

bioRxiv2021

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

Aldabrachelys gigantea (Aldabra giant tortoise) is one of only two giant tortoise species left in the world and survives as a single wild population of over 100,000 individuals on Aldabra Atoll, Seychelles. Despite this large current population size, the species faces an uncertain future because of its extremely restricted distribution range and high vulnerability to the projected consequences of climate change. Captive-bred A. gigantea are increasingly used in rewilding programs across the region, where they are introduced to replace extinct giant tortoises in an attempt to functionally resurrect degraded island ecosystems. However, there has been little consideration of the current levels of genetic variation and differentiation within and among the islands on Aldabra. As previous microsatellite studies were inconclusive, we combined low-coverage and double digest restriction associated DNA (ddRAD) sequencing to analyze samples from 33 tortoises (11 from each main island). Using 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.

ecology↗

bioRxiv2021

Beyond demographic buffering: Context dependence in demographic strategies across animals

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.

ecology↗

bioRxiv2019

Global analysis reveals complex demographic responses of mammals to climate change

Approximately 25 % of mammals are threatened globally with extinction, a risk that is amplified under climate change1. Persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development, reproduction), and hence, on population dynamics2. Thus, to quantify which species and places on Earth are most vulnerable to climate-driven extinction, a global understanding of how demographic rates respond to climate is needed3. We synthesise information on such responses in terrestrial mammals, where extensive demographic data are available4. Given the importance of assessing the full spectrum of responses, we focus on studies that quantitatively link climate to multiple demographic rates. We identify 106 such studies, corresponding to 86 mammal species. We reveal a strong mismatch between the locations of demographic studies and the regions and taxa currently recognised as most vulnerable to climate change5,6. Moreover, we show that the effects of climate change on mammals will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others. Assessments of population viability under climate change therefore need to account for multiple demographic responses. We advocate to prioritise coordinated actions to assess mammal demography holistically for effective conservation worldwide.

ecology↗

bioRxiv2019

A tradeoff between robustness to environmental fluctuations and speed of evolution

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

evolutionary biology↗

bioRxiv2019

Seasonal Effects of Environmental Change on Yellow-Bellied Marmot Population Dynamics

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development, reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneous, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.

ecology↗

bioRxiv2019

Effect of time-series length and resolution on abundance- and trait-based early warning signals of population declines

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 length and resolution. Our simulations suggest a relative time-series length between ten and five generations and a resolution of half a generation are the minimum requirements for accurate forecasting by abundance-based EWS. However, when trait information is included alongside abundance-based EWS, we find positive signals at lengths and resolutions 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.

ecology↗

bioRxiv2018

Co-occurrence of contrasting life-history strategies in a metapopulation inhabiting temporally variable and stable breeding sites

Life-history theory states that, during the lifetime of an individual, resources are allocated to either somatic maintenance or reproduction. Resource allocation trade-offs 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.

ecology↗

bioRxiv2018

When do shifts in trait dynamics precede population declines?

Predicting population responses to environmental change is an on-going challenge in ecology. Studies investigating the links between fitness-related phenotypic traits and demography have shown that trait dynamic responses to environmental change can sometimes precede population dynamic responses, and thus, can be used as an early warning signal. However, it is still unknown under which ecological and evolutionary circumstances, shifts in fitness-related traits can precede population responses to environmental perturbation. Here, we take a trait-based demographic approach and investigate both trait and population dynamics in a density-regulated population in response to a gradual change in the environment. We explore the ecological and evolutionary constraints under which shifts in a fitness-related trait precedes a decline in population size. We show both analytically and with experimental data that under medium-to-slow rate of environmental change, shifts in trait value can precede population decline. We further show the positive influence of environmental predictability, average reproductive rate, plasticity, and genetic variation on shifts in trait dynamics preceding potential population declines. These results still hold under non-constant genetic variation and environmental stochasticity. Our study highlights ecological and evolutionary circumstances under which a fitness-related trait can be used as an early warning signal of an impending population decline.

ecology↗

bioRxiv2018

Eco-evolutionary processes underlying early warning signals of population declines

O_LIEnvironmental 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. C_LIO_LIThe 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. C_LIO_LIHere, 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. C_LIO_LIWe show both analytically and with model-based simulations that strength of abundance-based early warning signals is significantly affected by ecological and evolutionary factors. C_LIO_LIFinally, 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. C_LI

ecology↗

bioRxiv2018

Weighted trait-abundance early warning signals better predict population collapse

Predicting population collapse in the face of unprecedented anthropogenic pressures is a key challenge in conservation. Abundance-based early warning signals have been suggested as a possible solution to this problem; however, they are known to be susceptible to the spatial and temporal subsampling ubiquitous to abundance estimates of wild population. Recent work has shown that composite early warning methods that take into account changes in fitness-related phenotypic traits - such as body size - alongside traditional abundance-based signals are better able to predict collapse, as trait dynamic estimates are less susceptible to sampling protocols. However, these previously developed composite early warning methods weighted the relative contribution of abundance and trait dynamics evenly. Here we present an extension to this work where the relative importance of different data types can be weighted in line with the quality of available data. Using data from a small-scale experimental system we demonstrate that weighted indicators can improve the accuracy of composite early warning signals by >60%. Our work shows that non-uniform weighting can increase the likelihood of correctly detecting a true positive early warning signal in wild populations, with direct relevance for conservation management.

ecology↗

bioRxiv2016

Adaptive and Non-adaptive Responses of Populations to Environmental Change

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population level plastic and evolutionary responses, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change, or whether simpler non-evolutionary models that are now widely constructed may be sufficient.

evolutionary biology↗