Population Ecology

Non-compliance with regulations threatens the sustainability of fisheries worldwide. Understanding the interconnected feedbacks of this complex social-ecological problem is key for sustainability but rarely integrated into fisheries management. We provide an adaptive stochastic modelling framework that integrates economic, social behavior, and ecological aspects of the Chilean kelp fishery, which plays a critical economic and ecological role in coastal social-ecological ecosystem. High levels of non-compliance is threatening sustainability, fishers well-being, and ecosystem health. Our model considers inherent environmental uncertainties and enables the assessment of different harvesting and compliance scenarios and the role of market-based economic incentives in reducing non-compliance. Results show that, unlike the sustainability obtained under an idealized full-compliance scenario, under dynamic compliance the social, economic, and ecological feedbacks leads to system collapse. Importantly, price premiums can promote compliance and sustainability, but the probability of collapse, albeit small, still exist. Our generalizable stochastic modeling framework evidenced that accounting for inherent uncertainty in natural resource management is key to designing interventions for sustainability.

Demographic models are crucial for uncovering the mechanisms underlying changing populations trajectories and structure and to identify the drivers of such changes. Common pochard populations of North east/North west Europe have experienced a sharp decline accompanied by an increase in male proportions among adults since the mid-1990. We used a two-sex, two-stage deterministic matrix population model, to perform a prospective perturbation analysis and to explore, through simulations, some plausible causes underlying the observed decline and change in sex structure. We show that Common pochard populations are more sensitive to changing survival than to changes in productivitys components (clutch size, nest survival...). However, due to an environmental variance much higher than that of survival, components of productivity, especially nest survival, would be the main drivers of Common pochard populations growth rate, a finding supported by empirical data. More importantly, we show that although sex-specific changes in survival at any stage of the life cycle are potent drivers of both population growth rate and changing sex ratio, there is no need to resort to them for explaining the increasing proportions of males such as observed in Common pochard. Because adult males display higher survival than adult females (0.74 against 0.64 on average), any factor affecting recruitment (nest or first year survival) increases the weight of adults into the populations and hence the proportion of males. Thus, in species displaying sex-biased mortality, such as many ducks, decreasing recruitment can underly declining population size and changes in sex structure at the same time, emphasising the importance of accounting for males in monitoring schemes and demographic models.

Accurate home range knowledge is essential for conserving species that are highly dependent on certain types of habitats. The critically endangered European mink (Mustela lutreola) is a wetland specialist whose movements are constrained by riparian and wetland habitats. In dendritic landscapes, conventional home range estimators such as Minimum Convex Polygons tend to include unsuitable habitats in estimated home ranges. Using VHF telemetry data from 16 individual-years tracked in France between 1996-1999 and 2020-2022, we compared four methods: Kernel Density Estimator (KDE), an adaptative sphere-of-influence local convex hull (a-LoCoH), a newly developed Ecological Home Range method (EHR), and a Generalized Additive Model (GAM) approach integrating hydrographic covariates. Our objective is to determine which method best accounts for the European minks specialization in wetlands, considering the spatial distribution of locations. Evaluation with wetland-specific metrics showed KDE consistently overestimated range extent and included unsuitable habitats, and a-LoCoH yielded mixed results, but these indicated that the method was not effective in excluding unused habitats. It was EHR and GAM methods that aligned more closely with ecological constraints. We therefore recommend GAM because it matches our objective and has the capacity to integrate additional environmental variables. Using the GAM, male home ranges averaged 3,074 ha--26 times larger than female ranges (116 ha)-- and were significantly larger in river than marsh landscapes. These are the largest ranges reported for the species. Large spatial requirements heighten vulnerability to road fatality and predation, both significant threats for remaining French populations. Our findings highlight the need for conservation strategies that integrate precise, habitat-based range estimates. The GAM method offers a robust, adaptable framework for managing European mink and other semi-aquatic species in complex landscapes.

Sky islands are high-elevation ecosystems surrounded by lowland habitats that create isolated environments with distinct climatic conditions. These factors have driven the evolution of many endemic species, separated from their larger, contiguous populations. An Individual-Based Model (IBM) was used to simulate population dynamics by modeling the behaviors and interactions of Tamiasciurus hudsonicus grahamensis (Mount Graham Red Squirrel) a subspecies of the American red squirrel (Tamiasciurus hudsonicus) that is endemic to the Pinaleno Mountains in southeastern Arizona. This approach can help predict future population trends based on historical species data leading to better conservation decisions. Using species-specific ecological preferences--including temperature, precipitation, and vegetation indices (NDVI)--an IBM was developed to simulate population dynamics and spatial distribution projections through 2100. Climate change projections, based on the best- and worst-case scenarios outlined in the 2014 National Climate Assessment, were incorporated to assess potential future population trends under changing environmental conditions. The population faces a 45-62% probability of extinction by 2100, with a significant risk of extinction within the next 50 years. A translocation experiment was conducted to evaluate the viability of relocating individuals to the Chiricahua Mountains, another sky island with a larger habitable area. However, the risk of extinction remains even higher (87-89%) due to environmental disturbances affecting both the Chiricahua and Pinaleno regions. This highlights the challenges of conservation efforts in the face of climate change and emphasizes the need for targeted management strategies to preserve this critically endangered subspecies.

Arctic and Boreal raptor communities will continue to be affected by borealization and other climate change related processes, providing a challenge for ecologists predicting future sates. However, by using community assembly theory and species traits, future communities may be predictable. In this study, we analyzed variation in reproduction traits as a consequence of diet specialization for 29 raptors, 2 skuas and 3 corvids. We assessed and implemented foraging traits for specialists and generalists into predator-prey models from which successful invasion conditions were derived. Specialist raptors produced larger clutch sizes, had a higher proportion of fledged per clutch and also expressed more variation compared to generalist raptors. These results suggest a relationship between diet specialization and reproductive traits which was also observed within phylogenetic orders. Specialist owls (Strigiformes) produced higher clutch sizes with a larger clutch range compared to generalist owls. The same pattern was observed for falcons (Falconiformes). No clear difference in reproduction was observed for specialist and generalist hawks, kites and eagles (Accipitriformes). Corvids expressed clutch sizes similar to that of specialist raptors while having the lowest proportion of fledged per clutch. Differences in foraging traits between specialists and generalists could be distinguished using functional response curves. A predator-prey model parameterized with foraging trait data showed that a generalist can coexist with a resident specialist if it has access to prey unavailable to the resident specialist. Otherwise, the native specialist outcompetes the invading generalist due to foraging efficiency. The combined empirical and theoretical findings in this study show how diet specialization affects both reproduction and the potential invasion success of raptors.

Elucidating how habitat degradation facilitates extinction is critical for effective conservation efforts. Here, we propose integrating physiologically-structured population models into stochastic population viability analyses to assess how differing consequences of habitat degradation interact to drive extinction dynamics in a focal population. Using the isolated spectacled caiman Caiman crocodilus population/ecomorph from the Apaporis River as a case study, we find that threatening the resource base, which individuals increasingly rely upon, to outgrow vulnerable size ranges and mature accelerates extinction. We also found that when habitat degradation impacts both the primary adult and juvenile resource bases, this can have marked synergistic effects on threatening population viability. By contrast, destroying nesting sites has only a small effect on accelerating the impact of deteriorating prey availability. Through integrating community-level feedback between habitat degradation/change and population dynamics/structure, our approach provides a comparative framework for assessing the relative importance of distinct mechanisms through which habitat degradation ultimately drives extinction risk.

Minimum viable populations (MVPs) are population levels large enough to surmount risk from demographic, environmental, and genetic stochasticity. MVPs are estimated by biologists to guide conservation practices. However, MVPs are generally estimated for a target population without regard for how they interact with intra- and inter-species population dynamics in the broader ecological community. Thus, how and why population dynamics interact with MVPs imposed by conservation biologists remain unclear. When MVPs are imposed on a continuous population model, traditional analyses fail to capture the range of possible outcomes those MVPs create. Here, we describe viability space decomposition (VSD) as a mathematical tool to systematically analyze the potential crossing of MVPs during population dynamics. We demonstrate that different extinction and survival outcomes can be recovered from a model with imposed MVPs using three VSD concepts in junction with a traditional phase portrait: mortality manifolds which separate conditions that lead to different existential outcomes, ordering manifolds which determine the order of extinction events for multiple populations, and collapse manifolds which determine the survival or extinction of one species given the loss of another. We employ these methods with a standard consumer-resource model, and the methods can be scaled to systems with more species. VSD is a useful tool for conservation biologists and community ecologists concerned with boundary crossing problems in any dynamical system.

Mark-recapture analyses on the delineation of natural populations between areas often assume random sampling, with a between/within (B/W) area resighting ratio that declines towards zero as the population components of two areas become more-and-more isolated from one another, with fewer-and-fewer individuals mixing between areas. I use an individual based population model split in two areas to simulate this result, analysing also for the potential effects of the space-time fidelity of the mark-recapture sampling in the areas. I find that small B/W resighting ratios--that traditionally is taken as evidence of population isolation--can easily be observed within a completely mixing population if a random sampling scheme is restricted in space and/or time. Random sampling within restricted areas and time windows is not sufficient to estimate mixing rates and population isolation between areas, unless the resighting rates are analysed by a method that accounts both for the space-time fidelity of the scientific sampling scheme and the space-time fidelity of the distributional behaviour of the individuals in the population.

Synchronising birth timing with the adequate environmental conditions as well as with congeners can affect juvenile survival and at a later stage, recruitment. In the case of endangered species, understanding the factors driving birth phenology is therefore critical to implement effective conservation and reintroduction policies. Currently, 75% of the Perissodactyla species (odd-toed ungulates) are threatened and some even already had to be reintroduced in their natural habitat. Using a comparative analysis framework, we investigated the effect of nine environmental, life history and predation factors on the synchrony of births in 27 populations of wild Perissodactyla across Africa and Asia. We confirmed the positive effect of environmental seasonality and latitude, as well as the negative effect of environmental productivity on birth synchrony, but we found no significant effect of environmental unpredictability. Life history traits had limited effects on birth synchrony in this order: the intensity of daily reproductive effort and pace of life were non-significant, and migratory behaviour had an unexpected positive association with birth synchrony, suggesting that the link between migration and reproduction might be more complex than the relief of environmental constraints initially expected. We found a positive effect of group size on birth synchrony, in line with the swamping hypothesis to reduce predation risk on neonates, but we found no strong support for a positive effect of predation exposure, measured as a qualitative index combining species-specific sensitivity to predation and site-specific predator abundance. Overall, our findings suggest that individuals adjust reproductive cycles in response to local ecological and social conditions, suggesting that conservation efforts such as reintroductions could benefit from taking into account the extent of the differences between the site of origin and the reintroduction site.

Metacommunity theory explains how species distributions arise from local population dynamics and dispersal between habitat patches. Four conceptual paradigms--patch dynamics, species sorting, mass effects, and demographic stochasticity--have emerged as frameworks for understanding metacommunity structure and dynamics, but their integration remains an open problem. Here we introduce a probabilistic-stochastic-deterministic (PSD) modelling framework that unifies these paradigms within a single mathematical description. PSD approximates individual-based models (IBM) with computational efficiency comparable to ordinary differential equations (ODE) while capturing demographic stochasticity and permitting analytical treatment. Through validation against IBM simulations in single-patch communities and spatially explicit metacommunities with rock-paper-scissors dynamics, we demonstrate that PSD accurately reproduces IBM behaviour where ODE models fail, specifically when demographic stochasticity dominates during immigration. For metacommunities with long-distance dispersal, we analytically derive the period of a slow collective oscillations, revealing body-mass and dispersal-rate dependencies invisible to ODE theory. Our analysis shows that the four paradigms represent valid descriptions in different regions of parameter space, controlled by individual body-mass, immigration rate, and regional species richness. The PSD framework thus provides both a practical simulation tool and an analytical machinery for predicting metacommunity dynamics across ecological regimes.

Coexistence of multiple predators in ecological communities and their combined effects on the abundance and diversity of shared prey are often difficult to predict. In some theoretical models, predator coexistence is limited by antagonistic interactions, especially in the form of intraguild predation (IGP) that typically leads to out-competition between predators and high prey densities. However, empirical studies show that predator coexistence is common even in the presence of IGP. This discrepancy between theoretical expectations and empirical observations can be highly relevant for practical applications like using multiple natural enemies for pest suppression in agriculture. It is proposed that greater functional differences between natural enemies (i.e. predators) could reduce competition and overcome the negative effects of IGP, thereby promoting their coexistence and enhancing herbivore (i.e. prey) suppression. In this study, we theoretically explore this proposition. We develop a theoretical model based on the types of natural enemies of aphids to identify how functional differences between predators in IGP modules affect predator coexistence and herbivore suppression. We show that pairwise combinations of four functional predator types (ladybird, predatory bug, hoverfly, and parasitoid) can increase the coexistence range for different intraguild predation and competition strengths between predators (IGP symmetry), along a productivity gradient. This outcome depends on the external food input rate for the predatory bug and hoverfly types, and on their position as IG predator or IG prey. Herbivore suppression was primarily driven by IGP symmetry (i.e. the relative intraguild predation and exploitative competition strength between predators) and was especially pronounced in competitive-like modules where the IG predator was excluded for most scenarios. However, for some competitive-like IGP modules with predatory bug and hoverfly types, both predators can persist and provide a high herbivore suppression across increasing productivity. Our results can help explain experimental findings in conservation biocontrol, where coexistence between natural enemies is joined with effective herbivore suppression, and offer additional support for the role of functional diversity in reconciling theoretical predictions with experimental observations in multiple-predator communities.

Age-dependent survival is central to understanding population dynamics and life-history evolution. We analysed carcass weight and age-at-harvest data from 6022 red foxes (Vulpes vulpes) collected across Sweden between 1967 and 1971 to evaluate latitudinal effects on body mass and age-dependent survival. Carcass weights decreased from south to north in both adults and sub-adults, contrary to Bergmann's rule, with southern foxes weighing approximately 1.27 times more than northern foxes. The latitudinal weight gradient exceeded the sex difference in both age classes, and no sex x region interaction was detected. The decrease in weight with latitude is consistent with reduced prey availability and harsher winter conditions in the north, which limit growth and body size during development. Using a Bayesian age-at-harvest model with region-specific population growth rates (lambda), we estimated age-dependent survival probabilities for four latitudinal regions and both sexes. Despite the strong latitudinal gradient in weight, survival did not show a corresponding pattern - regional differences were uncertain, with all credible intervals spanning zero. Regional population growth rates were consistent with slight decline in the north and near-stability in the south-central region, which suggests that body condition and population dynamics are coupled at the regional scale despite no survival gradient. The decoupling of body condition and survival across regions suggests that mortality patterns are similar across the latitudinal gradient. We discuss these patterns in terms of latitudinal productivity gradients, prey availability, and life-history trade-offs in a widely distributed carnivore.

Human land use has greatly affected the natural landscapes in most parts of the world, and Scandinavian industrial forestry has substantially altered the age structure of the boreal forest over the last 75 years. In this study, we analyzed 44 years of line transect counts of Capercaillie and Black grouse collected in an industrial forest landscape in central Sweden between 1980 and 2024. The area was heavily logged in the 1960s and 1970s, followed by large-scale replanting. A hierarchical Gompertz state-space model to assess long-term population dynamics of both species. The adult state model included a brood production submodel, and forest age structure, snow depth, vole abundance, and spring frost were covariates. Our results reveal strong density dependence and temporally variable environmental effects. Capercaillie and Black grouse exhibited contrasting decadal trends: Capercaillie increased markedly during the early study years, whereas Black grouse declined steeply before recovering later in the series. Increasing proportions of forest aged 21-40 years had a clearly positive effect on Capercaillie, whereas snow depth in the previous winter negatively influenced Capercaillie but not Black grouse. Brood production exhibited substantial interannual unexplained variation, although late spring frost reduced brood size in Capercaillie. Toward the end of the study, the two species reached similar levels of latent adult abundance, demonstrating that both can persist at sustainable densities across a broader range of forest structures than suggested in earlier studies.

SO_SCPLOWUMMARYC_SCPLOWAge is a fundamental life-history parameter in animal ecology and wildlife management. Age informs key ecological characteristics including population age structure, recruitment strength, extinction risk, reproductive maturity, and mortality rates. This importance has necessitated the development of chronological age estimation methods for wild animals. However, estimating chronological age is challenging for wild species, with noisy and potentially biased measures typically gathered from morphometrics, physical characteristics or, more recently, molecular methods like DNA methylation. These measures of age require at least some initial validation set of known-age individuals, or known time intervals, which is difficult to obtain for many species. Here, we present a solution to inferring the relationship between chronological age and error-prone observed age that does not require known-age individuals. The model couples the formulae for occurrence rates of half-sibling pairs, which decrease as a function of the birth-year gap between two sampled individuals, with time of capture. A pseudo-likelihood framework is developed for parameter estimation that can resolve linear and non-linear relationships and provide variance parameter estimates. We explore the methods efficacy for estimating chronological age using forward-in-time simulation and validate prior estimates of the relationship between vertebral band counts and chronological age for 3,000 school shark (Galeorhinus galeus) from an Australian fishery.

Philippine freshwater ecosystems are considered one of the most diverse ecosystems harboring numerous fish species. However, in the Philippines, these ecosystems are threatened by invasive species that potentially disrupt ecological balance. In this study, we focused on the vermiculated sailfin catfish Pterygoplichthys disjunctivus, an invasive aquarium species reported in several Philippine aquatic ecosystems. Despite its documented spread, its potential range under a rapidly changing climate remains poorly understood for the country. Hence, in this study, we utilized the MaxEnt model to predict its near-current and future habitat suitability in the Philippines. Using 11 reported occurrences, our model showed high predictive accuracy (AUC = 0.882{+/-} .034, TSS = 0.7394 {+/-} 0.154, SEDI = 0.971 {+/-} 0.019). Across the current and future scenarios, slope was the primary contributor (78.7% - 81.3%), followed by BIO 10 or the mean temperature of the warmest quarter(18% - 27.8%), and flow accumulation (0% - 5.2%). However, for the SSP126 scenario, BIO10 is projected to triple by 2050 (18 - 48%). Current projections identify high-risk regions, particularly central Luzon (Laguna de Bay and Lake Taal), the Cagayan River Valley, and portions of eastern Mindanao (Agusan Marsh and Lake Mainit). Sankey transition analysis confirms a high habitat stability rate (>73%) for high-suitability pixels in both SSPs, indicating persistent invasion risk. Overall, our study provides a framework for invasive species management and contributes to the conservation of Philippine aquatic ecosystems.

1Effective population size (Ne) is a critical parameter for evaluating the evolutionary and persistence potential of endangered populations and for designing sustainable conservation strategies. Captive breeding and release programs are widely used across taxa to reduce risk of extinction when natural reproduction is insufficient or no longer possible, making it essential to assess their consequences. We used the case study of the landlocked Saimaa salmon (Salmo salar), one of the most critically en-dangered salmonid populations in Europe, with unique evolutionary significance due to its isolation from other populations since the last glaciation. Using long-term demographic data (1969-2024) from wild-caught founders of a captive breeding and release program, we estimated the effective population size under multiple scenarios of variance in reproductive success. Across scenarios, Ne ranged from 33 to 81 individuals, representing 32%-75% of the census size. Captive breeding practices aimed at equalizing parental contributions during fertilization and early life stages increased Ne by 12% compared to natural reproductive conditions. However, variation in survival after early developmental stages, typically beyond direct management control, remained a key determinant of Ne. Despite recent increases in the number of founders, the population remains genetically vulnerable due to historical bottlenecks. These results highlight that while captive breeding programs can partially mitigate genetic risks, their effectiveness depends critically on both controlled and uncontrolled sources of variance in reproductive success. Strengthening such programs may require combining breeding management with habitat restoration and, where appropriate, genetic rescue to ensure the long-term evolutionary potential of such unique and endangered populations.

Wildfire regimes in Mediterranean landscapes are undergoing significant changes due to the combined effects of land-use transitions and climate change. In particular, land abandonment increased fuel availability, the expansion of the wildland-urban interface increased ignition frequency, while climate change increases the chances of fire-weather conditions and reduces vegetation recovery capacity. This study presents a modelling framework to investigate the coupled dynamics of fire and vegetation under different fire regimes scenarios, using a case study in central Italy (Monte Pisano). The approach integrates two cellular automata models for vegetation dynamics (Batllori et al., 2017) and for fire-spread (PROPAGATOR; Trucchia et al., 2020). The vegetation model represents succession among six functional classes, including grasslands, shrubs, and trees with different fire-response strategies (seeders and resprouters), while explicitly accounting for post-fire recovery processes. The model was calibrated for the area using historical fire perimeters and vegetation maps over 40 years. Fire spread is simulated probabilistically using PROPAGATOR, driven by fuel types, topography, and weather conditions. A stochastic coupling was implemented by sampling fuel classes from vegetation composition, and by feeding simulated burned areas back into the vegetation model, thus enabling dynamic fire-vegetation feedback. Future wildfire scenarios are constructed by linking ignition probability to fire-weather conditions derived from historical reanalysis data (1981-2023). Extreme fire events are defined based on thresholds of wind speed and fuel moisture, and their probability of occurrence is varied across scenarios to represent increasing climate-driven risk. Simulations are performed over a 100-year horizon starting from current vegetation conditions. Results show that, in the absence of fire, vegetation dynamics lead to dominance of late-successional, fire-resilient species (resprouters). This is particularly evident for low probabilities of extreme fire events, with fire impacts diminishing over time as landscapes become less flammable. However, increasing the frequency of extreme fire conditions resulted in persistent disturbance, maintaining higher proportions of shrubs and early successional vegetation, and sustaining elevated burned areas over time. Overall, the study shows that coupling fire spread and vegetation dynamics provides a useful framework for exploring long-term ecosystem trajectories under climate change. The results highlight the critical role of extreme fire events in shaping landscape resilience and suggest that future management strategies should account for fire-vegetation feedbacks to support more stable and less fire-prone ecosystems.

Humans are efficient and deadly predators, yet they may also interact with wildlife in non-lethal ways. This study explores how interactions with lethal and non-lethal human "superpredators" alter predator-prey dynamics using an agent-based modelling approach. Our model incorporates both the consumptive (lethal) and non-consumptive (behavioural) effects of humans, as well as of predators on prey. We explored how the replacement of apex predators by humans affects mesopredator-prey dynamics, with particular emphasis on trophic targeting and differences between lethal and non-lethal interactions. We found that human superpredators have a greater effect on model outcomes than apex predators. When superpredators consume mesopredators alone or with prey, the probability of mesopredator-prey coexistence increases to a greater extent than when apex predators consume mesopredators. In contrast, superpredators consuming only prey slightly increases overall extinction risks and reduces coexistence. Non-lethal superpredators, despite eliciting anti-predator responses in mesopredators and prey, had a negligible effect on population dynamics. Our findings demonstrate that human superpredators may functionally replace apex predators when they are lethal. However, non-lethal interactions with humans may not be as ecologically significant as lethal interactions, even when humans induce anti-predator responses.

Environmental variability can strongly alter coexistence among competing species and their extinction risk, particularly when population dynamics are shaped by behavioral interactions, such as fear. In this work, we develop a novel stochastic differential equation competition model that incorporates both non-consumptive fear effects and environmental variability to investigate how behavioral interactions influence species coexistence under random fluctuations. Our result reveals that environmental stochasticity can drive species to extinction even when the corresponding deterministic system admits coexistence. In particular, under an explicit stability condition on the fear and competition parameters and sufficiently strong averaged noise intensities, we prove that both competing species become extinct exponentially almost surely. Conversely, we derive a stochastic persistence criterion in terms of fear, competition, and noise-induced suppression parameters for the fearful species. We further demonstrate that environmental noise may reverse classical competition-exclusion outcomes, leading to qualitatively different long-term dynamics from those predicted deterministically. These results provide rigorous thresholds separating stochastic extinction from persistence and highlight the critical role of environmental variability in fear-mediated competitive ecosystems. From an applied perspective, these results provide insight into how behavioral interactions and environmental variability influence species survival, with potential applications in ecological management and conservation.

Understanding and predicting extinction risk is a central challenge in population biology. Mathematical models incorporating Allee thresholds are commonly used to understand population dynamics and to assess extinction risks. Inaccurate predictions can have serious consequences for conservation management. In this simulation study, we develop a likelihood-based inference and prediction workflow to estimate parameters, including the Allee threshold and population diffusivity parameters, using noisy count data generated using a well-defined discrete model. Although parameters are identifiable according to commonly used criteria, the accuracy of resulting predictions depends strongly on the quantity, quality, collection time and spatial resolution of the data. Our workflow demonstrates that seemingly reliable parameter estimates can lead to inaccurate predictions, highlighting the need for careful consideration of data quality and quantity to guide extinction-risk modelling and prediction. Open source software is provided on GitHub to replicate and extend all results considered.