Disentangling the effects of climate, density dependence, and harvest on an iconic large herbivore's population dynamics

Sporadic Events Have a Greater Influence on the Dynamics of Small, Isolated Populations Than Density Dependence and Environmental Conditions

AbstractDensity dependence is often assumed in population dynamics, but its importance in small, isolated populations has been questioned. We evaluated the relative influence of density dependence, environmental conditions, and sporadic events (disease outbreaks and specialist predators) on annual population growth rate, annual female reproduction, and annual survival of juveniles and adult females in three populations of mountain ungulates. We analyzed long-term (30-47 years) individual-based data on two bighorn sheep populations and one mountain goat population in Alberta, Canada. The effect of cougar predation episodes and pneumonia epizootics on annual population growth rate was twice as strong as that of population density. While pneumonia reduced adult female and juvenile survival and predation episodes decreased all demographic rates, high density lowered only juvenile survival. Long-term studies are pivotal for understanding the dynamics of large herbivore populations, but they are rarely duplicated. Our analysis of three mountain ungulate populations with similar life history and ecological characteristics provides evidence that infrequent sporadic events can have a greater relative influence on annual population growth than density-dependent factors in isolated populations. This result contrasts with studies of larger, well-connected populations, highlighting the importance of considering sporadic events in the management and conservation of isolated populations.

Maternal carryover, winter severity, and brown bear abundance relate to elk demographics

Ungulates are key components of ecosystems due to their effects on lower trophic levels, role as prey, and value for recreational and subsistence harvests. Understanding factors that drive ungulate population dynamics can inform protection of important habitat and successful management of populations. To ascertain correlates of ungulate population dynamics, we evaluated the effects of five non-exclusive hypotheses on ungulate abundance and recruitment: winter severity, spring nutritional limitation (spring bottleneck), summer-autumn maternal condition carryover, predation, and timber harvest. We used weather, reconstructed brown bear (Ursus arctos) abundance, and timber harvest data to estimate support for these hypotheses on early calf recruitment (calves per 100 adult females in July–August) and population counts of Roosevelt elk (Cervus canadensis roosevelti) on Afognak and Raspberry islands, Alaska, USA, 1958–2020. Increasing winter temperatures positively affected elk abundance, supporting the winter severity hypothesis, while a later first fall freeze had a positive effect on elk recruitment, supporting the maternal carry-over hypothesis. Increased brown bear abundance was negatively associated with elk recruitment, supporting the predation hypothesis. Recruitment was unaffected by spring climate conditions or timber harvest. Severe winter weather likely increased elk energy deficits, reducing elk survival and subsequent abundance in the following year. Colder and shorter falls likely reduced late-season forage, resulting in poor maternal condition which limited elk recruitment more than winter severity or late-winter nutritional bottlenecks. Our results additionally demonstrated potential negative effects of brown bears on elk recruitment. The apparent long-term decline in elk recruitment did not result in a decline of abundance, which suggests that less severe winters may increase elk survival and counteract the potential effects of predation on elk abundance.

Harvest and density-dependent predation drive long-term population decline in a northern ungulate

The relative effect of top-down versus bottom-up forces in regulating and limiting wildlife populations is an important theme in ecology. Untangling these effects is critical for a basic understanding of trophic dynamics and effective management. We examined the drivers of moose (Alces alces) population growth by integrating two independent sources of observations within a hierarchical Bayesian population model. We used one of the largest existing spatiotemporal data sets on ungulate population dynamics globally. We documented a 20% population decline over the period examined. There was negative density-dependent population growth of moose. Although we could not determine the mechanisms producing density-dependent suppression of population growth, the relatively low densities at which we documented moose populations suggested it could be due to density-dependent predation. Predation primarily limited population growth, except at low density, where it was regulating. After we simulated several harvest scenarios, it appeared that harvest was largely additive and likely contributed to population declines. Our results highlight how population dynamics are context dependent and vary strongly across gradients in climate, forest type, and predator abundance. These results help clarify long-standing questions in population ecology and highlight the complex relationships between natural and human-caused mortality in driving ungulate population dynamics.

Effects of climate variability on the demography of wild geladas

Nonhuman primates are an essential part of tropical biodiversity and play key roles in many ecosystem functions, processes, and services. However, the impact of climate variability on nonhuman primates, whether anthropogenic or otherwise, remains poorly understood. In this study, we utilized age-structured matrix population models to assess the population viability and demographic variability of a population of geladas (Theropithecus gelada) in the Simien Mountains, Ethiopia with the aim of revealing any underlying climatic influences. Using data from 2008 to 2019 we calculated annual, time-averaged, and stochastic population growth rates (λ) and investigated relationships between vital rate variability and monthly cumulative rainfall and mean temperature. Our results showed that under the prevailing environmental conditions, the population will increase (λ s = 1.021). Significant effects from rainfall and/or temperature variability were widely detected across vital rates; only the first year of infant survival and the individual years of juvenile survival were definitively unaffected. Generally, the higher temperature in the hot-dry season led to lower survival and higher fecundity, while higher rainfall in the hot-dry season led to increased survival and fecundity. Overall, these results provide evidence of greater effects of climate variability across a wider range of vital rates than those found in previous primate demography studies. This highlights that although primates have often shown substantial resilience to the direct effects of climate change, their vulnerability may vary with habitat type and across populations.

Spatial patterns in the contribution of biotic and abiotic factors to the population dynamics of three freshwater fish species

BACKGROUND

Population dynamics are driven by a number of biotic (e.g., density-dependence) and abiotic (e.g., climate) factors whose contribution can greatly vary across study systems (i.e., populations). Yet, the extent to which the contribution of these factors varies across populations and between species and whether spatial patterns can be identified has received little attention.

METHODS

Here, we used a long-term (1982-2011), broad scale (182 sites distributed across metropolitan France) dataset to study spatial patterns in the population's dynamics of three freshwater fish species presenting contrasted life-histories and patterns of elevation range shifts in recent decades. We used a hierarchical Bayesian approach together with an elasticity analysis to estimate the relative contribution of a set of biotic (e.g., strength of density dependence, recruitment rate) and abiotic (mean and variability of water temperature) factors affecting the site-specific dynamic of two different size classes (0⁺ and >0⁺ individuals) for the three species. We then tested whether the local contribution of each factor presented evidence for biogeographical patterns by confronting two non-mutually exclusive hypotheses: the "range-shift" hypothesis that predicts a gradient along elevation or latitude and the "abundant-center" hypothesis that predicts a gradient from the center to the edge of the species' distributional range.

RESULTS

Despite contrasted life-histories, the three species displayed similar large-scale patterns in population dynamics with a much stronger contribution of biotic factors over abiotic ones. Yet, the contribution of the different factors strongly varied within distributional ranges and followed distinct spatial patterns. Indeed, while abiotic factors mostly varied along elevation, biotic factors-which disproportionately contributed to population dynamics-varied along both elevation and latitude.

CONCLUSIONS

Overall while our results provide stronger support for the range-shift hypothesis, they also highlight the dual effect of distinct factors on spatial patterns in population dynamics and can explain the overall difficulty to find general evidence for geographic gradients in natural populations. We propose that considering the separate contribution of the factors affecting population dynamics could help better understand the drivers of abundance-distribution patterns.

Ecological forecasts reveal limitations of common model selection methods: predicting changes in beaver colony densities

Over the past two decades, there have been numerous calls to make ecology a more predictive science through direct empirical assessments of ecological models and predictions. While the widespread use of model selection using information criteria has pushed ecology toward placing a higher emphasis on prediction, few attempts have been made to validate the ability of information criteria to correctly identify the most parsimonious model with the greatest predictive accuracy. Here, we used an ecological forecasting framework to test the ability of information criteria to accurately predict the relative contribution of density dependence and density-independent factors (forage availability, harvest, weather, wolf [Canis lupus] density) on inter-annual fluctuations in beaver (Castor canadensis) colony densities. We modeled changes in colony densities using a discrete-time Gompertz model, and assessed the performance of four models using information criteria values: density-independent models with (1) and without (2) environmental covariates; and density-dependent models with (3) and without (4) environmental covariates. We then evaluated the forecasting accuracy of each model by withholding the final one-third of observations from each population and compared observed vs. predicted densities. Information criteria and our forecasting accuracy metrics both provided strong evidence of compensatory density dependence in the annual dynamics of beaver colony densities. However, despite strong within-sample performance by the most complex model (density-dependent with covariates) as determined using information criteria, hindcasts of colony densities revealed that the much simpler density-dependent model without covariates performed nearly as well predicting out-of-sample colony densities. The hindcast results indicated that the complex model over-fit our data, suggesting that parameters identified by information criteria as important predictor variables are only marginally valuable for predicting landscape-scale beaver colony dynamics. Our study demonstrates the importance of evaluating ecological models and predictions with long-term data and revealed how a known limitation of information criteria (over-fitting of complex models) can affect our interpretation of ecological dynamics. While incorporating knowledge of the factors that influence animal population dynamics can improve population forecasts, we suggest that comparing forecast performance metrics can likewise improve our knowledge of the factors driving population dynamics.

Extinction risk assessment of a Patagonian ungulate using population dynamics models under climate change scenarios

Climate change affects population cycles of several species, threatening biodiversity. However, there are few long-term studies on species with conservation issues and restricted distributions. Huemul is a deer endemic to the southern Andes in South America and it is considered endangered mostly due to a 50% reduction of its distribution over the last 500 years. To assess environmental variables potentially affecting huemul population viability and the impact of climate change, we developed population dynamics models. We used a 14-year survey data from Bernardo O'Higgins National Park, coastal Chilean Patagonia. We used Ricker models considering winter and spring temperatures and precipitation as variables influencing huemul population dynamics. We used the Bayesian information criterion (BIC) to select models with the greatest predictive power. The two best models (ΔBIC < 2) included winter temperature and density-dependence population growth drivers. The best model considered a lateral effect, where winter temperature influences carrying capacity and the second best a vertical effect with winter temperature influencing R_max and carrying capacity. Population viability was evaluated using those models, projecting them over a 100-year period: (a) under current conditions and (b) under conditions estimated by Global Climate Models for 2050 and 2070. The extinction risk and quasi-extinction were estimated for this population considering two critical huemul abundance levels (15 and 30 individuals) for persistence. The population is currently in a quasi-extinction process, with extinction probabilities increasing with climate change. These results are crucial for conservation of species like huemul that have low densities and are threatened by climate change.

Detrimental impacts of climate change may be exacerbated by density-dependent population regulation in blue mussels

The climate on our planet is changing and the range distributions of organisms are shifting in response. In aquatic environments, species might not be able to redistribute poleward or into deeper water when temperatures rise because of barriers, reduced light availability, altered water chemistry or any combination of these. How species respond to climate change may depend on physiological adaptability, but also on the population dynamics of the species. Density dependence is a ubiquitous force that governs population dynamics and regulates population growth, yet its connections to the impacts of climate change remain little known, especially in marine studies. Reductions in density below an environmental carrying capacity may cause compensatory increases in demographic parameters and population growth rate, hence masking the impacts of climate change on populations. On the other hand, climate-driven deterioration of conditions may reduce environmental carrying capacities, making compensation less likely and populations more susceptible to the effects of stochastic processes. Here we investigate the effects of climate change on Baltic blue mussels using a 17-year dataset on population density. Using a Bayesian modelling framework, we investigate the impacts of climate change, assess the magnitude and effects of density dependence, and project the likelihood of population decline by the year 2030. Our findings show negative impacts of warmer and less saline waters, both outcomes of climate change. We also show that density dependence increases the likelihood of population decline by subjecting the population to the detrimental effects of stochastic processes (i.e. low densities where random bad years can cause local extinction, negating the possibility for random good years to offset bad years). We highlight the importance of understanding, and accounting for both density dependence and climate variation when predicting the impact of climate change on keystone species, such as the Baltic blue mussel.

Territoriality drives preemptive habitat selection in recovering wolves: Implications for carnivore conservation

According to the ideal-free distribution (IFD), individuals within a population are free to select habitats that maximize their chances of success. Assuming knowledge of habitat quality, the IFD predicts that average fitness will be approximately equal among individuals and between habitats, while density varies, implying that habitat selection will be density dependent. Populations are often assumed to follow an IFD, although this assumption is rarely tested with empirical data, and may be incorrect when territoriality indicates habitat selection tactics that deviate from the IFD (e.g. ideal-despotic distribution or ideal-preemptive distribution). When territoriality influences habitat selection, species' density will not directly reflect components of fitness such as reproductive success or survival. In such cases, assuming an IFD can lead to false conclusions about habitat quality. We tested theoretical models of density-dependent habitat selection on a species known to exhibit territorial behaviour in order to determine whether commonly applied habitat models are appropriate under these circumstances. We combined long-term radiotelemetry and census data from grey wolves Canis lupus in the Upper Peninsula of Michigan, USA to relate spatiotemporal variability in wolf density to underlying classifications of habitat within a hierarchical state-space modelling framework. We then iteratively applied isodar analysis to evaluate which distribution of habitat selection best described this recolonizing wolf population. The wolf population in our study expanded by >1,000% during our study (~50 to >600 individuals), and density-dependent habitat selection was most consistent with the ideal-preemptive distribution, as opposed to the ideal-free or ideal-despotic alternatives. Population density of terrestrial carnivores may not be positively correlated with the fitness value of their habitats, and density-dependent habitat selection patterns may help to explain complex predator-prey dynamics and cascading indirect effects. Source-sink population dynamics appear likely when species exhibit rapid growth and occupy interspersed habitats of contrasting quality. These conditions are likely and have implications for large carnivores in many systems, such as areas in North America and Europe where large predator species are currently recolonizing their former ranges.

Local density regulates migratory songbird reproductive success through effects on double-brooding and nest predation

Knowledge of the density-dependent processes that regulate animal populations is key to understanding, predicting, and conserving populations. In migratory birds, density-dependence is most often studied during the breeding season, yet we still lack a robust understanding of the reproductive traits through which density influences individual reproductive success. We used 27-yr of detailed, individual-level productivity data from an island-breeding population of Savannah sparrows Passerculus sandwichensis to evaluate effects of local and total annual population density on female reproductive success. Local density (number of neighbors within 50 m of a female's nest) had stronger effects on the number of young fledged than did total annual population density. Females nesting in areas of high local density were more likely to suffer nest predation and less likely to initiate and fledge a second clutch, which led to fewer young fledged in a season. Fledging fewer young subsequently decreased the likelihood of a female recruiting offspring into the breeding population in a subsequent year. Collectively, these results provide insight into the scale and reproductive mechanisms mediating density-dependent reproductive success and fitness in songbirds.

Assessing the importance of demographic parameters for population dynamics using Bayesian integrated population modeling

To successfully respond to changing habitat, climate or harvest, managers need to identify the most effective strategies to reverse population trends of declining species and/or manage harvest of game species. A classic approach in conservation biology for the last two decades has been the use of matrix population models to determine the most important vital rates affecting population growth rate (λ), that is, sensitivity. Ecologists quickly realized the critical role of environmental variability in vital rates affecting λ by developing approaches such as life-stage simulation analysis (LSA) that account for both sensitivity and variability of a vital rate. These LSA methods used matrix-population modeling and Monte Carlo simulation methods, but faced challenges in integrating data from different sources, disentangling process and sampling variation, and in their flexibility. Here, we developed a Bayesian integrated population model (IPM) for two populations of a large herbivore, elk (Cervus canadensis) in Montana, USA. We then extended the IPM to evaluate sensitivity in a Bayesian framework. We integrated known-fate survival data from radio-marked adults and juveniles, fecundity data, and population counts in a hierarchical population model that explicitly accounted for process and sampling variance. Next, we tested the prevailing paradigm in large herbivore population ecology that juvenile survival of neonates <90 d old drives λ using our Bayesian LSA approach. In contrast to the prevailing paradigm in large herbivore ecology, we found that adult female survival explained more of the variation in λ than elk calf survival, and that summer and winter elk calf survival periods were nearly equivalent in importance for λ. Our Bayesian IPM improved precision of our vital rate estimates and highlighted discrepancies between count and vital rate data that could refine population monitoring, demonstrating that combining sensitivity analysis with population modeling in a Bayesian framework can provide multiple advantages. Our Bayesian LSA framework will provide a useful approach to addressing conservation challenges across a variety of species and data types.

Weather, habitat composition, and female behavior interact to modify offspring survival in Greater Sage-Grouse

Weather is a source of environmental variation that can affect population vital rates. However, the influence of weather on individual fitness is spatially heterogeneous and can be driven by other environmental factors, such as habitat composition. Therefore, individuals can experience reduced fitness (e.g., decreased reproductive success) during poor environmental conditions through poor decisions regarding habitat selection. This requires, however, that habitat selection is adaptive and that the organism can correctly interpret the environmental cues to modify habitat use. Greater Sage-Grouse (Centrocercus urophasianus) are an obligate of the sagebrush ecosystems of western North America, relying on sagebrush for food and cover. Greater Sage-Grouse chicks, however, require foods with high nutrient content (i.e., forbs and insects), the abundance of which is both temporally and spatially dynamic and related primarily to water availability. Our goal was to assess whether nest site selection and movements of broods by females reduced the negative effect of drought on offspring survival. As predicted, chick survival was negatively influenced by drought severity. We found that sage-grouse females generally preferred to nest and raise their young in locations where their chicks would experience higher survival. We also found that use of habitats positively associated with chick survival were also positively associated with drought severity, which suggests that females reduced drought impacts on their dependent young by selecting more favorable environments during drought years. Although our findings suggest that female nest site selection and brood movement rates can reduce the negative effects of drought on early offspring survival, the influence of severe drought conditions was not completely mitigated by female behavior, and that drought conditions should be considered a threat to Greater Sage-Grouse population persistence.