Integrated Population Models Research Articles

Adaptive Management Facilitates Increase in Northern Bobwhite Populations

Adaptive resource management (ARM) is an approach to managing that allows decision makers to learn about a system and subsequently change management actions based on new information about system processes (i.e., adapt) to better meet fundamental objectives. This is not to be confused with changing management actions when the state of the system changes. For example, changing a harvest regulation when populations decline is not ARM. This dynamic decision making may be fortuitously optimal, but if the effect of harvest is uncertain then changing regulations may be suboptimal—for example, weather may have caused the decline. Adaptive resource management can be implemented along a spectrum of passive to active to reduce system uncertainty. Active ARM is when explicit hypotheses are posited then implemented to test them, and monitoring occurs to elucidate whether the effect of the management action achieved a given result. Passive ARM uses current management practices, natural variation in the system, and monitoring to reduce uncertainty. Even though northern bobwhite (Colinus virginianus) have been studied for a century, uncertainty regarding optimal management strategies still exists. The Albany Quail Project (AQP) has used both modes of ARM to learn about northern bobwhite populations to better meet the hunting objectives of stakeholders. Between 1992 and 2019 the AQP radio-tagged 5,182 unique individuals and banded an additional 5,008 birds on the primary study area near Albany, Georgia, USA. Additionally, 1,724 nests have been monitored and population surveys conducted in the spring and autumn. Active ARM occurred with tests of supplemental feeding, hardwood cleanup, and predator control whereas passive ARM was used to learn about prescribed fire regimes, brood habitat preferences, small mammal cycles, and raptor migrations. We built an integrated population model (IPM) that combined known-fate survival data, nesting records, dead recoveries from harvest, and population surveys to model the system. The preliminary results of the IPM demonstrated that populations have increased during the project. The 5 most abundant autumn populations have occurred in the most recent 10 years of the project when bobwhite populations throughout their range have continued to decline. Unlike typical ARM applications, the AQP has not had an explicit model to predict consequences of future management actions; nonetheless, the essence of ARM has been followed. Since its inception uncertainty has been reduced, management actions have been changed, and bobwhite populations have responded. Improvements to AQP and similar projects could include explicit hypotheses and predictive models about the system

Is unreliable science guiding bobcat management in Wyoming and other western U.S. states?

Abstract Wildlife managers require defensible and transparent population estimates to justify species management. Statistical population reconstruction (SPR) is being widely adopted to estimate wildlife population sizes from hunter harvest data. We assessed factors influencing variation in SPR population estimates produced for bobcats in Wyoming, USA. Specifically, we tested whether prey availability, hunter/trapper effort, the number of bobcats killed or the methods used to classify the age and sex of bobcats (‘classification protocol’) best explained changing SPR abundance estimates. We then quantified the relative magnitude of these effects on SPR model outputs. Classification protocol had the strongest impact on SPR abundance estimates, such that a shift to visual age and sex classifications by trappers/hunters resulted in overestimates of bobcat abundance. The Wyoming bobcat SPR population estimates were likely unreliable and we suggest that spatially explicit integrated population models may be a better approach to obtaining defensible estimates upon which to establish scientific management of this charismatic carnivore.

Variation in Demography and Life-History Strategies Across the Range of a Declining Mountain Bird Species

Species- and population-specific responses to their environment may depend to a large extent on the spatial variation in life-history traits and in demographic processes of local population dynamics. Yet, those parameters and their variability remain largely unknown for many cold-adapted species, which are exposed to particularly rapid rates of environmental change. Here, we compared the demographic traits and dynamics for an emblematic bird species of European mountain ecosystems, the ring ouzel (Turdus torquatus). Using integrated population models fitted in a Bayesian framework, we estimated the survival probability, productivity and immigration of two populations from the Western European Alps, in France (over 11 years) and Switzerland (over 6 years). Juvenile apparent survival was lower and immigration rate higher in the Swiss compared to the French population, with the temporal variation in population growth rate driven by different demographic processes. Yet, when compared to populations in the northwestern part of the range, in Scotland, these two Alpine populations both showed a much lower productivity and higher adult survival, indicating a slower life-history strategy. Our results suggest that demographic characteristics can substantially vary across the discontinuous range of this passerine species, essentially due to contrasted, possibly locally evolved life-history strategies. This study therefore raises the question of whether flexibility in life-history traits is widespread among boreo-alpine species and if it might provide adaptive potential for coping with current environmental change.

Indexing starvation mortality to assess its role in the population regulation of Northern cod

Starvation is a ubiquitous process in nature as all animals depend on finite resources to survive. Limited food resources can lead to starvation-induced mortality and, depending on the scale of the limitation, population-level consequences may emerge. However, attempts to model starvation-induced mortality are rare as it is difficult to isolate the effects of specific sources of natural mortality. Using commonly collected data on body condition, we develop a statistical approach to index starvation-induced mortality by estimating the proportion of individuals experiencing severe emaciation in a fish population. This approach accounts for seasonal patterns in body condition, allowing data collected at any time of year to be included. Using Canada’s Northern cod (Gadus morhua) stock as a case study, we found a positive association between rates of natural mortality estimated by an integrated population model and the index of mortality derived from proportions of cod in poor condition. This index is also associated with the availability of two key prey species, capelin (Mallotus villosus) and Northern shrimp (Pandalus borealis). Taken together, our results indicate that starvation-induced mortality represents an important component of the natural mortality experienced by Northern cod, supporting the idea that insufficient food contributed to the collapse of the stock in the early 1990s and, subsequently, limited its recovery. These implications highlight the practical relevance of explicitly considering prey availability (e.g., through body condition or prey abundance indices) to improve stock assessment modeling and aid the development of actionable ecosystem-based fisheries management strategies.

Integrated population modelling reveals potential drivers of demography from partially aligned data: a case study of snowy plover declines under human stressors.

Knowledge of demography is essential for understanding wildlife population dynamics and developing appropriate conservation plans. However, population survey and demographic data (e.g., capture-recapture) are not always aligned in space and time, hindering our ability to robustly estimate population size and demographic processes. Integrated population models (IPMs) can provide inference for population dynamics with poorly aligned but jointly analysed population and demographic data. In this study, we used an IPM to analyse partially aligned population and demographic data of a migratory shorebird species, the snowy plover (Charadrius nivosus). Snowy plover populations have declined dramatically during the last two decades, yet the demographic mechanisms and environmental drivers of these declines remain poorly understood, hindering development of appropriate conservation strategies. We analysed 21 years (1998–2018) of partially aligned population survey, nest survey, and capture-recapture-resight data in three snowy plover populations (i.e., Texas, New Mexico, Oklahoma) in the Southern Great Plains of the US. By using IPMs we aimed to achieve better precision while evaluating the effects of wetland habitat and climatic factors (minimum temperature, wind speed) on snowy plover demography. Our IPM provided reasonable precision for productivity measures even with missing data, but population and survival estimates had greater uncertainty in years without corresponding data. Our model also uncovered the complex relationships between wetland habitat, climate, and demography with reasonable precision. Wetland habitat had positive effects on snowy plover productivity (i.e., clutch size and clutch fate), indicating the importance of protecting wetland habitat under climate change and other human stressors for the conservation of this species. We also found a positive effect of minimum temperature on snowy plover productivity, indicating potential benefits of warmth during night on their population. Based on our results, we suggest prioritizing population and capture-recapture surveys for understanding population dynamics and underlying demographic processes when data collection is limited by time and/or financial resources. Our modelling approach can be used to allocate limited conservation resources for evidence-based decision-making.

Offspring of translocated individuals drive the successful reintroduction of Columbian Sharp-tailed Grouse in Nevada, USA

Abstract Translocations of North American prairie-grouse (genus Tympanuchus) present a conservation paradox wherein they are performed to augment, restore, or reintroduce populations, but translocated individuals exhibit a diminished ability to contribute to population restoration. For reintroduced populations without immigration, persistence can only be achieved through reproductive contributions by translocated individuals and their progeny. Due to the disruptive nature of translocation (e.g., physiological chronic stress), progeny produced at restoration sites may outperform founder populations in terms of demographics, but this hypothesis has yet to be tested. We reintroduced Columbian Sharp-tailed Grouse (T. phasianellus columbianus; CSTG) to north central Nevada from 2013 to 2017 and used integrated population models (IPMs) to evaluate the process of population establishment and estimate latent contributions of progeny hatched at the restoration site to population rate of change (λ^). Specifically, we used annual lek (i.e. communal breeding arenas) counts and demographic data from translocated individuals to build two separate IPMs to estimate λ^. While keeping demographic contributions by translocated individuals identical between models, one IPM assumed local progeny performance was demographically similar to translocated individuals (i.e. the baseline-IPM), and the second assumed that local progeny performed demographically similar to non-translocated CSTG (i.e. the informative-IPM). The baseline-IPM predicted strong population declines following the conclusion of translocations and extirpation by 2020, and it failed to predict observed lek counts. Conversely, the informative-IPM predicted population growth rates (λ^ = 1.17, 95% credible interval [CI]: 0.74–1.50) that were more similar to field observations. Offspring of translocated individuals likely perform at similar levels to non-translocated populations, and by not accounting for demographic differences between translocated individuals and non-translocated progeny hatched at the restoration site, managers could underestimate population performance and persistence. Thus, translocation practices that maximize the number of offspring immediately recruited into restoration sites are likely to be the most successful.

Chick survival and hunting are important drivers for the dynamics of two Alpine black grouse Lyrurus tetrix populations

Alpine black grouse populations are generally declining, but the underlying demographic drivers are largely unknown. We studied the dynamics of two adjacent black grouse populations over a 20 years period in the Italian Alps that differ in hunting pressure to identify the main demographic process affecting these populations and to study the impact of hunting on males. We collected radio-tracking data and conducted population surveys in spring to count displaying cocks and in late summer to determine the breeding success by means of pointing dogs. These different data sets were jointly analysed using a seasonal integrated population model to estimate population sizes and various demographic rates. The two populations fluctuated in size and the number of males from one population increased after hunting intensity was reduced. The main demographic rates did not differ between the populations. Adult survival was relatively low and productivity was high, so the life history shows the feature of a fast turnover species. In both populations, the variability of survival from hatching to the age of five weeks (chick survival) contributed more to the variation of the population growth rates than the variability of survival in later life-history stages, and the former was positively affected by ambient temperatures in July, favouring chick survival. The adult sex ratio of the population where males hunting occurred was shifted towards females, but it evened over time with the reduction of hunting pressure. The adult sex ratio in the population without hunting and the chick sex ratios in both populations were even, suggesting that hunting acted as a mostly additive source of mortality.

Finding the perfect mismatch: Evaluating misspecification of population structure within spatially explicit integrated population models

AbstractSpatially stratified integrated population models (IPMs) can account for fine‐scale demographic processes and support spatial management for complex, heterogeneous populations. Although spatial IPMs may provide a more realistic representation of true population dynamics, few studies have evaluated the consequences associated with incorrect assumptions regarding population structure and connectivity. We utilized a simulation‐estimation framework to explore how mismatches between the true population structure (i.e. uniform, single population with spatial heterogeneity or metapopulation) and various parametrizations of an IPM (i.e. panmictic, fleets‐as‐areas or a spatially explicit, tag‐integrated model) impacted resultant fish population estimates. When population structure was incorrectly specified in the IPM, parameter estimates were generally unbiased at the system level, but were often biased for sub‐areas. Correctly specifying population structure in spatial IPMs led to strong performance, whereas incorrectly specified spatial IPMs performed adequately (and better than spatially aggregated counterparts). Allowing for flexible parametrization of movement rates (e.g. estimating age‐varying values) was more important than correctly identifying the population structure, and incorporation of tag‐recapture data helped movement estimation. Our results elucidate how incorrect population structure assumptions can influence the estimation of key parameters of spatial IPMs, while indicating that, even if incorrectly specified, spatial IPMs can adequately support spatial management decisions.

An integrated population model to project viability of a northern bobwhite population in Ohio

AbstractIncreased variation in interannual weather due to climate change can exert a powerful influence on the population dynamics of a species. Understanding the influence of severe weather is important for managing weather‐sensitive species. While best management practices target vital rates that are affected by weather, focusing on a single vital rate may not be sufficient if other vital rates are secondarily limiting. A comprehensive modeling framework to forecast future population dynamics while incorporating weather scenarios and vital rate variation within observed ranges that can be affected by management actions are necessary. A potential approach is to combine an integrated population model (IPM) with a population viability analysis (PVA) to generate novel insights about population dynamics. We used the northern bobwhite (Colinus virginianus), a rapidly declining gamebird sensitive to snowfall along the northern extents of the species' range, to demonstrate the utility of a coupled IPM‐PVA framework for projecting the response of a population to weather, management, and changes in vital rates. We created an IPM using two sources of count data spanning seven years, five years of winter survival data, and two years of breeding season demographics for a declining bobwhite population in southwestern Ohio during 2007–2015. Quasi‐extinction probability at the end of the decadal projection during 2019–2029 was 0.384–0.410 for mild, average, and severe winter weather scenarios. Quasi‐extinction probability declined to 0.326 with 20% improvement in nest success and summer survival rates. A concurrent 20% increase in winter survival further reduced quasi‐extinction probability to 0.263, which is a ˜36% reduction in quasi‐extinction probability compared with the baseline scenario with no changes in vital rates. These results suggest that long‐term viability of this population may depend on extensive management of winter habitat to improve survival but will also require management actions to improve fecundity after severe winters. Our modeling approach demonstrated how IPMs can be used to project population responses to future weather conditions and overcome some of the pitfalls of traditional PVA. The coupled framework presented here can serve as a tool for managers to make climate‐informed management decisions.

Multiple‐model stock assessment frameworks for precautionary management and conservation on fishery‐targeted coastal dolphin populations off Japan

Abstract Stock assessment approaches are often oversimplified due to lack of biological knowledge and insufficient data. In spite of world‐wide attention, fishery‐targeted coastal dolphin species in Japan have lacked in‐depth quantitative stock assessments because of limited time series of population size and an absence of associated biological information. We consequently developed integrated population models that analysed multiple sources of data simultaneously with published biological information within a Bayesian framework. We estimate population status and trends for three main species targeted by fisheries, bottlenose dolphins Tursiops truncatus, Risso's dolphins Grampus griseu, and short‐finned pilot whales Globicephala macrorhynchus, using single‐species age‐aggregated and age‐structured population dynamics models. Models were fit to absolute abundance estimates from systematic line‐transect surveys, four series of abundance indices calculated from fisher's logbooks, and historical catch records. Published biological information was used to develop prior distributions for the biological parameters. We assessed the possible effects of ecological disturbance and competition using state‐space and multispecies models. The multispecies model was selected by the model selection both for the age‐aggregated and the age‐structured approaches. Single‐species assessments found that population size declined 4.2% (Risso's dolphin) to 8.0% (bottlenose dolphin) for three species since the late 1800s based on median posterior values, while the state‐space and multispecies models found that environmental disturbance and an interaction among species could have reduced population size more substantially. Policy implications. Simple single‐species models are often used to provide conservation and management advice for wild animals but, in this case, results from such models are overly optimistic because they overlook important ecological process. In contrast, current population status could be less favorable if environmental disturbance and interspecific competition actually control population dynamics. Even if that is not the case, considering ecological process in the model will provide more precautionary ways. Our approach of combining multiple modelling frameworks is applicable to many other management systems, and offers increased confidence in estimated status and trends over assessments that consider only a single model.

Incorporating Batch Mark–Recapture Data into an Integrated Population Model of Brown Trout

AbstractBrown Trout Salmo trutta are a popular sport fish, and numerous populations that are unable to successfully reproduce are maintained with supplemental stockings in waters with habitat that can support individual survival (e.g., appropriate thermal refuge). Long‐term management of these populations requires understanding of their population dynamics to determine harvest restrictions and stocking rates. The objective of this research was to describe population dynamics of a tailrace Brown Trout fishery using an integrated population model (IPM) that incorporates monitoring data and low‐cost batch mark–recapture data. Further, we evaluated the relationship between water temperature and survival. We hypothesized that annual survival would be lower at high water temperature. Additionally, we used the IPM to project the Brown Trout population based on two different management scenarios (no minimum length limit with seven‐fish bag limit and 356‐mm‐TL minimum length limit with two‐fish bag limit). Management outcomes explored include total population size, age frequencies, and length indices. The results of this study suggested that recreational harvest and water temperature were the two main factors influencing the Brown Trout population. Water temperature was found to be a major factor in determining survival of Brown Trout. Simulations under various minimum length limits indicated the minimum length limit of 356 mm TL and a two‐fish bag limit will substantially increase the population size but with a reduction in length indices. Integrated population models have been applied historically to large systems with significant amounts of data. Estimates of survival and detection are important components of an IPM; to our knowledge, the IPM used here is the first to integrate batch mark–recapture data to estimate these key parameters. The data and modeling approach used here demonstrate the value of using novel statistical methods to make the most efficient use of low‐cost survey data.

Population reinforcement and demographic changes needed to stabilise the population of a migratory vulture

Abstract One approach to stabilise small and declining populations is to breed individuals in captivity and release them into the wild to reinforce existing populations while working to reduce threats. Population reinforcement programmes require long‐term commitments to be successful and can divert limited resources from other conservation measures. A rigorous evaluation whether reinforcement can stabilise a population is therefore essential to justify investments. Many migratory species incur high mortality during their first migration, and releasing captive‐bred birds at an older age may therefore benefit reinforcement programmes for migratory birds. We examine whether a small and declining population of a long‐distance migratory raptor—the Egyptian Vulture Neophron percnopterus—can be stabilised using population reinforcement that reduces mortality during the first migration. We used an integrated population model to evaluate realistic reinforcement and survival improvement scenarios to estimate how many captive‐bred birds would need to be released to stabilise the population. Survival probability of wild juveniles during their first year (0.296; 95% CI 0.234–0.384) was too low for a stable population (population growth rate 0.949; 95% CI 0.940–0.956), but captive‐bred juveniles released in their second calendar year had improved survival (0.566; 95% CI 0.265–0.862) during their first year in the wild. Reinforcement of 15 birds per year for 30 years was insufficient to achieve a neutral or positive population growth rate. However, reinforcement reduced the probability of extinction by 2049 from 48% without reinforcement to <1% if 12 or more birds were released every year for 30 years. A 6% increase in annual survival probability would likely lead to a stable population without any reinforcement. Synthesis and applications. Although releasing captive‐bred birds can reduce high juvenile mortality during first migration and assist in postponing local extinction, further improvements of survival in the wild are required to safeguard a migratory population where threats in the wild will persist for decades despite management.

Integrated population models poorly estimate the demographic contribution of immigration

Abstract Estimating the contribution of demographic parameters to changes in population growth is essential for understanding why populations fluctuate. Integrated population models (IPMs) offer a possibility to estimate the contributions of additional demographic parameters, for which no data have been explicitly collected—typically immigration. Such parameters are often subsequently highlighted as important drivers of population growth. Yet, accuracy in estimating their temporal variation, and consequently their contribution to changes in population growth rate, has not been investigated. To quantify the magnitude and cause of potential biases when estimating the contribution of immigration using IPMs, we simulated data (using northern wheatear Oenanthe oenanthe population estimates) from controlled scenarios to examine potential biases and how they depend on IPM parameterization, formulation of priors, the level of temporal variation in immigration and sample size. We also used empirical data on populations with known rates of immigration: Soay sheep Ovis aries and Mauritius kestrel Falco punctatus with zero immigration and grey wolf Canis lupus in Scandinavia with near‐zero immigration. IPMs strongly overestimated the contribution of immigration to changes in population growth in scenarios when immigration was simulated with zero temporal variation (proportion of variance attributed to immigration = 63% for the more constrained formulation and real sample size) and in the wild populations, where the true number of immigrants was zero or near‐zero (kestrel 19.1%–98.2%, sheep 4.2%–36.1% and wolf 84.0%–99.2%). Although the estimation of the contribution of immigration in the simulation study became more accurate with increasing temporal variation and sample size, it was often not possible to distinguish between an accurate estimation from data with high temporal variation versus an overestimation from data with low temporal variation. Unrealistically, large sample sizes may be required to estimate the contribution of immigration well. To minimize the risk of overestimating the contribution of immigration (or any additional parameter) in IPMs, we recommend to: (a) look for evidence of variation in immigration before investigating its contribution to population growth, (b) simulate and model data for comparison to the real data and (c) use explicit data on immigration when possible.

Demographic responses to climate change in a threatened Arctic species.

The Arctic is undergoing rapid and accelerating change in response to global warming, altering biodiversity patterns, and ecosystem function across the region. For Arctic endemic species, our understanding of the consequences of such change remains limited. Spectacled eiders (Somateria fischeri), a large Arctic sea duck, use remote regions in the Bering Sea, Arctic Russia, and Alaska throughout the annual cycle making it difficult to conduct comprehensive surveys or demographic studies. Listed as Threatened under the U.S. Endangered Species Act, understanding the species response to climate change is critical for effective conservation policy and planning. Here, we developed an integrated population model to describe spectacled eider population dynamics using capture–mark–recapture, breeding population survey, nest survey, and environmental data collected between 1992 and 2014. Our intent was to estimate abundance, population growth, and demographic rates, and quantify how changes in the environment influenced population dynamics. Abundance of spectacled eiders breeding in western Alaska has increased since listing in 1993 and responded more strongly to annual variation in first‐year survival than adult survival or productivity. We found both adult survival and nest success were highest in years following intermediate sea ice conditions during the wintering period, and both demographic rates declined when sea ice conditions were above or below average. In recent years, sea ice extent has reached new record lows and has remained below average throughout the winter for multiple years in a row. Sea ice persistence is expected to further decline in the Bering Sea. Our results indicate spectacled eiders may be vulnerable to climate change and the increasingly variable sea ice conditions throughout their wintering range with potentially deleterious effects on population dynamics. Importantly, we identified that different demographic rates responded similarly to changes in sea ice conditions, emphasizing the need for integrated analyses to understand population dynamics.

Consequences of violating assumptions of integrated population models on parameter estimates

While ecologists know that models require assumptions, the consequences of their violation become vague as model complexity increases. Integrated population models (IPMs) combine several datasets to inform a population model and to estimate survival and reproduction parameters jointly with higher precision than is possible using independent models. However, accuracy actually depends on an adequate fit of the model to datasets. We first investigated bias of parameters obtained from integrated population models when specific assumptions are violated. For instance, a model may assume that all females reproduce although there are non-breeding females in the population. Our second goal was to identify which diagnostic tests are sensitive to detect violations of the assumptions of IPMs. We simulated data mimicking a short- and a long-lived species under five scenarios in which a specific assumption is violated. For each simulated scenario, we fitted an IPM that violates the assumption (simple IPM) and an IPM that does not violate each specific assumption. We estimated bias and uncertainty of parameters and performed seven diagnostic tests to assess the fit of the models to the data. Our results show that the simple IPM was quite robust to violation of many assumptions and only resulted in small bias of the parameter estimates. Yet, the applied diagnostic tests were not sensitive to detect such small bias. The violation of some assumptions such as the absence of immigrants resulted in larger bias to which diagnostic tests were more sensitive. The parameters informed by the least amount of data were the most biased in all scenarios. We provide guidelines to identify misspecified models and to diagnose the assumption being violated. Simple models should often be sufficient to describe simple population dynamics, and when data are abundant, complex models accounting for specific processes will be able to shed light on specific biological questions.

Multispecies integrated population model reveals bottom‐up dynamics in a seabird predator–prey system

AbstractAssessing the effects of climate and interspecific relationships on communities is challenging because of the complex interplay between species population dynamics, their interactions, and the need to integrate information across several biological levels (individuals, populations, communities). Usually used to quantify single‐species demography, integrated population models (IPMs) have recently been extended to communities. These models allow fitting multispecies matrix models to data from multiple sources while simultaneously accounting for uncertainty in each data source. We used multispecies IPMs accommodating climatic variables to quantify the relative contribution of climate vs. interspecific interactions on demographic parameters, such as survival and breeding success, in the dynamics of a predator–prey system. We considered a stage‐structured predator–prey system combining 22 yr of capture–recapture data and population counts of two seabirds, the Brown Skua (Catharacta lönnbergi) and its main prey the Blue Petrel (Halobaena caerulea), both breeding on the Kerguelen Islands in the Southern Ocean. Our results showed that climate and predator–prey interactions drive the demography of skuas and petrels in different ways. The breeding success of skuas appeared to be largely driven by the number of petrels and to a lesser extent by intraspecific density dependence. In contrast, there was no evidence of predation effects on the demographic parameters of petrels, which were affected by oceanographic factors. We conclude that bottom‐up mechanisms are the main drivers of this skua–petrel system.

Efficient use of harvest data: a size‐class‐structured integrated population model for exploited populations

Many animal populations are subject to hunting or fishing in the wild. Detailed knowledge of demographic parameters (e.g. survival, reproduction) and temporal dynamics of such populations is crucial for sustainable management. Despite their relevance for management decisions, structure and size of exploited populations are often not known, and data limited. Recently, joint analysis of different types of demographic data, such as population counts, reproductive data and capture–mark–recapture data, within integrated population models (IPMs) has gained much popularity as it may allow estimating population size and structure, as well as key demographic rates, while fully accounting for uncertainty. IPMs built so far for exploited populations have typically been built as age‐structured population models. However, the age of harvested individuals is usually difficult and/or costly to assess and therefore often not available. Here, we introduce an IPM structured by body size classes, which allows making efficient use of data commonly available in exploited populations for which accurate information on age is often missing. The model jointly analyzes size‐at‐harvest data, capture–mark–recapture–recovery data and reproduction data from necropsies, and we illustrate its applicability in a case study involving heavily hunted wild boar. This species has increased in abundance over the last decades despite intense harvest, and the IPM analysis provides insights into the roles of natural mortality, body growth, maturation schedules and reproductive output in compensating for the loss of individuals to hunting. Early maturation and high reproductive output contributed to wild boar population persistence despite a strong hunting pressure. We thus demonstrate the potential of size‐class‐structured IPMs as tools to investigate the dynamics of exploited populations with limited information on age, and highlight both the applicability of this framework to other species and its potential for follow‐up analyses highly relevant to management.

Incorporating individual variation in survival, reproduction and detection rates when projecting dynamics of small populations

Survival, reproduction and detection rates may vary greatly amongst individuals. Failure to account for this variation results in biased inferences about age effects and population size. However, individual variation is not normally considered in population viability analysis, potentially leading to misleading projections for small populations. We present a novel data-augmentation approach for incorporating individual variation in rates in integrated population models. By adding rows to survival and reproduction matrices for hypothetical individuals in both the past and future, inferences about individual variation derived from Bayesian hierarchical modelling are propagated into population projections. We apply this method to a small reintroduced population of hihi (Notiomystis cincta) at Bushy Park, New Zealand, where individuals vary greatly in reproductive success, longevity and detection probability, and ongoing management decisions depend on modelling projections. We compare the results to those from an alternative model that ignores individual variation but incorporates sex and age effects. The modelling confirmed pronounced individual variation in all rates, and greatly altered their interpretation. Estimated survival and reproduction rates of average individuals became much lower and apparent age effects disappeared. In addition, the estimated proportion of fledglings produced by unmonitored females dropped from 23% to 9%. Incorporation of individual variation in the integrated population model resulted in more optimistic population projections over the next four years although the difference was minor in relation to the 95% prediction limits. The methodology presented has broad potential for assessing whether population projections used to guide management of small populations are sensitive to individual variation.

Contributions from terrestrial and marine resources stabilize predator populations in a rapidly changing climate

AbstractClimate change has different and sometimes divergent effects on terrestrial and marine food webs, and in coastal ecosystems, these effects are tightly interlinked. Responses of opportunistic coastal predators and scavengers to climate change may thus be complex and potentially highly flexible, and can simultaneously serve as indicators of, and have profound impacts on, lower trophic levels. Gaining mechanistic understanding of these responses is therefore important, but often not feasible due to lack of long‐term data from marked individuals. Here, we used a Bayesian integrated population model (IPM) to elucidate the effects of arctic warming and concurrent changes in terrestrial and marine resource availability on population dynamics of the opportunistic arctic fox (Vulpes lagopus) in Svalbard. Joint analysis of four types of data (den survey, age‐at‐harvest, placental scars, mark‐recovery) revealed relatively stable population size and age structure over the last 22 yr (1997–2019) despite rapid environmental change linked to climate warming. This was related to the fact that terrestrial resources (reindeer carcasses, geese) became more abundant while the availability of marine resources (seal pups/carrion) decreased, and was driven by divergent trends in different vital rates (e.g., increased pregnancy rate but decreased pup survival). Balanced contributions of survival vs. reproduction and of immigration vs. local demography further stabilized population size. Our study thus sheds light on the mechanisms underlying population dynamics of opportunistic carnivores exploiting terrestrial and marine resources and suggests that exploitation of resources across different ecosystems can buffer predators against climate change. Additionally, it highlights the large potential of IPMs as tools to understand and predict the effects of environmental change on wildlife populations, even when data on marked individuals are sparse.

Reversing tree expansion in sagebrush steppe yields population‐level benefit for imperiled grouse

AbstractWoody plant expansion into shrub and grasslands is a global and vexing ecological problem. In the Great Basin of North America, the expansion of pinyon–juniper (Pinus spp.–Juniperus spp.) woodlands is threatening the sagebrush (Artemisia spp.) biome. The Greater Sage‐grouse (Centrocercus urophasianus; sage‐grouse), a sagebrush obligate species, is widespread in the Great Basin and considered an indicator for the condition of sagebrush ecosystems. To assess the population response of sage‐grouse to landscape‐scale juniper removal, we analyzed a long‐term telemetry data set and lek counts with a Bayesian integrated population model in a before‐after‐control‐impact design. Population growth rates (λ) in a treatment area (Treatment) with juniper removal and a control area (Control) without juniper removal indicated the two areas generally experienced population increase, decrease, and stability in the same years. However, the difference in λ between study areas indicated a steady increase in the Treatment relative to the Control starting in 2013 (removals initiated in 2012), with differences of 0.13 and 0.11 in 2016 and 2017, respectively. Retrospective sensitivity analysis suggested the dynamics in λ were driven by increases in juvenile, adult, first nest, and yearling survival in the Treatment relative to the Control. These findings demonstrate the effectiveness of targeted conifer removal as a management strategy for conserving sage‐grouse populations in sagebrush steppe affected by conifer expansion. Examples of positive, population‐level responses to habitat management are exceptionally rare for terrestrial vertebrates, and this study provides promising evidence of active management that can be implemented to aid recovery of an imperiled species and biome.