Potential Misuse of Avian Density as a Conservation Metric

Abstract: Effective conservation metrics are needed to evaluate the success of management in a rapidly changing world. Reproductive rates and densities of breeding birds (as a surrogate for reproductive rate) have been used to indicate the quality of avian breeding habitat, but the underlying assumptions of these metrics rarely have been examined. When birds are attracted to breeding areas in part by the presence of conspecifics and when breeding in groups influences predation rates, the effectiveness of density and reproductive rate as indicators of habitat quality is reduced. It is beneficial to clearly distinguish between individual‐ and population‐level processes when evaluating habitat quality. We use the term reproductive rate to refer to both levels and further distinguish among levels by using the terms per capita fecundity (number of female offspring per female per year, individual level) and population growth rate (the product of density and per capita fecundity, population level). We predicted how density and reproductive rate interact over time under density‐independent and density‐dependent scenarios, assuming the ideal free distribution model of how birds settle in breeding habitats. We predicted population density of small populations would be correlated positively with both per capita fecundity and population growth rate due to the Allee effect. For populations in the density‐dependent growth phase, we predicted no relation between density and per capita fecundity (because individuals in all patches will equilibrate to the same success rate) and a positive relation between density and population growth rate. Several ecological theories collectively suggest that positive correlations between density and per capita fecundity would be difficult to detect. We constructed a decision tree to guide interpretation of positive, neutral, nonlinear, and negative relations between density and reproductive rates at individual and population levels.     

Integrating Landscape and Metapopulation Modeling Approaches: Viability of the Sharp-Tailed Grouse in a Dynamic Landscape

Abstract:  The lack of management experience at the landscape scale and the limited feasibility of experiments at this scale have increased the use of scenario modeling to analyze the effects of different management actions on focal species. However, current modeling approaches are poorly suited for the analysis of viability in dynamic landscapes. Demographic (e.g., metapopulation) models of species living in these landscapes do not incorporate the variability in spatial patterns of early successional habitats, and landscape models have not been linked to population viability models. We link a landscape model to a metapopulation model and demonstrate the use of this model by analyzing the effect of forest management options on the viability of the Sharp-tailed Grouse (  Tympanuchus phasianellus ) in the Pine Barrens region of northwestern Wisconsin (U.S.A.). This approach allows viability analysis based on landscape dynamics brought about by processes such as succession, disturbances, and silviculture. The landscape component of the model (LANDIS) predicts forest landscape dynamics in the form of a time series of raster maps. We combined these maps into a time series of patch structures, which formed the dynamic spatial structure of the metapopulation component (RAMAS). Our results showed that the viability of Sharp-tailed Grouse was sensitive to landscape dynamics and demographic variables such as fecundity and mortality. Ignoring the landscape dynamics gave overly optimistic results, and results based only on landscape dynamics (ignoring demography) lead to a different ranking of the management options than the ranking based on the more realistic model incorporating both landscape and demographic dynamics. Thus, models of species in dynamic landscapes must consider habitat and population dynamics simultaneously.     

Spectral properties and photosynthetic action in red-tide populations of Prorocentrum micans and Gonyaulax polyedra

Three sets of experiments were carried out between April and September 1987 to assess reproductive energetics in a laboratory population of the capitellid polychaete Capitella capitata type I. In the first experiment, the population was sampled intensively over a short period of 3 wk. Weight-specific reproductive output did not differ significantly between females and hermaphrodites. However, because hermaphrodites were significantly bigger than females, their fecundity was significantly higher. In the second experiment, fecundity and weight-specific reproductive output were monitored weekly over the oscillation cycle of the population (30 wk). Both fecundity and weight-specific reproductive output varied drastically (40 to 80 eggs per female and 17 to 57%, respectively). In the third experiment, non-sexed juveniles were reared for 15 d on six ration levels (normalized on the basis of organic nitrogen) of four different food sources. The maximum weight-specific reproductive output was 70% (for females). Both fecundity and weight-specific reproductive output were positively correlated with food ration and varied with food type. The data on weight-specific reproductive output recorded in the present study have been compared with those of other iteroparous polychaetes in the literature. Reproductive output in C. Capitata type I varies more widely and is greater than in other iteroparous polychaetes. In this species, reproductive output and population dynamics vary concomitently with the level of organic matter in the habitat.     

A bio-inspired computing model as a new tool for modeling ecosystems: The avian scavengers as a case study

The models used for ecosystems modeling are generally based on differential equations. However, in recent years new computational models based on biological processes, or bioinspired models, have arisen, among which are P systems. These are inspired by the functions of cells and present important advantages with respect to traditional models, such as a high computational efficiency, modularity and their ability to work in parallel. They are simple, individual-based models that use biological parameters that can be obtained experimentally. In this work, we present the framework for a model based on P systems applied to the study of an ecosystem in which three avian scavengers (predators) interact with 10 wild and domestic ungulates (preys). The computation time for 100 repetitions, corresponding to 14 simulation years each, with an initial population composed of 385,422 individuals, was 30 min. Our results suggest that the model presented, based on P systems, correctly simulates the population dynamics in the period of time analyzed. We discuss the usefulness of this tool in simulating complex ecosystems dynamics to aid managers, conservationists and policy-makers in making appropriate decisions for the improvement of management and conservation programs.     

Growth and population dynamic model for the non-zooxanthellate temperate solitary coral Leptopsammia pruvoti (Scleractinia, Dendrophylliidae)

In corals where complex life history processes decoupling age from size (e.g., fragmentation, fusion, partial colony mortality) are rare or clearly detectable, individual age may be determined from size, and age-based growth and population dynamic models may be applied. One example is the solitary Mediterranean coral Leptopsammia pruvoti Lacaze-Duthiers 1897, whose population size and structure, and growth rates were determined at Calafuria (43°28′N and 10°20′E), Ligurian Sea, from December 2007 to June 2009. Growth rate decreased with increasing size. The growth curve derived from field measurements confirmed the one obtained by growth band analysis. The frequency of individuals decreased exponentially with age, indicating a steady state population. Turnover time was 2.3 years. Maximum life span was 13 years. Most reproductive output was from intermediate age classes (6 years), while older individuals (>7 years), although having higher fecundity, were rare and accounted for a minority of population reproductive output. In comparison with other solitary dendrophylliids, L. pruvoti life strategy was characterized by a reproduction with r-strategy correlates (high fecundity, short embryo incubation, small planula size, fast achievement of sexual maturity), and a rate of demographic renewal occurring halfway along the r–K continuum (intermediate turnover time and maximum longevity).     

Translating effects of inbreeding depression on component vital rates to overall population growth in endangered bighorn sheep

Evidence of inbreeding depression is commonly detected from the fitness traits of animals, yet its effects on population growth rates of endangered species are rarely assessed. We examined whether inbreeding depression was affecting Sierra Nevada bighorn sheep (Ovis canadensis sierrae), a subspecies listed as endangered under the U.S. Endangered Species Act. Our objectives were to characterize genetic variation in this subspecies; test whether inbreeding depression affects bighorn sheep vital rates (adult survival and female fecundity); evaluate whether inbreeding depression may limit subspecies recovery; and examine the potential for genetic management to increase population growth rates. Genetic variation in 4 populations of Sierra Nevada bighorn sheep was among the lowest reported for any wild bighorn sheep population, and our results suggest that inbreeding depression has reduced adult female fecundity. Despite this population sizes and growth rates predicted from matrix-based projection models demonstrated that inbreeding depression would not substantially inhibit the recovery of Sierra Nevada bighorn sheep populations in the next approximately 8 bighorn sheep generations (48 years). Furthermore, simulations of genetic rescue within the subspecies did not suggest that such activities would appreciably increase population sizes or growth rates during the period we modeled (10 bighorn sheep generations, 60 years). Only simulations that augmented the Mono Basin population with genetic variation from other subspecies, which is not currently a management option, predicted significant increases in population size. Although we recommend that recovery activities should minimize future losses of genetic variation, genetic effects within these endangered populations-either negative (inbreeding depression) or positive (within subspecies genetic rescue)-appear unlikely to dramatically compromise or stimulate short-term conservation efforts. The distinction between detecting the effects of inbreeding depression on a component vital rate (e.g., fecundity) and the effects of inbreeding depression on population growth underscores the importance of quantifying inbreeding costs relative to population dynamics to effectively manage endangered populations.     

Uncertainty, learning, and the optimal management of wildlife

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.     

Inverse modeling for effective dispersal: Do we need tree size to estimate fecundity?

The estimation of the dispersal kernel for the seedling and sapling stages of the recruitment process was made possible through the application of inverse modeling to dispersal data. This method uses the spatial coordinates of adult trees and the counts of seedlings (or saplings) in small quadrats to estimate the dispersal kernel. The unknown number of recruits produced by an adult tree (the fecundity) is estimated - simultaneously with the dispersal kernel - via an allometric linear model relating the unknown quantity with a (easily) measured characteristic of the adult tree (usually the basal area). However, the allometric relation between tree size and reproductive success in the sapling (or seedling) stage may not be strong enough when numerous, well-documented, post-dispersal processes (such as safe-site limitation for recruitment) cause large post-dispersal seedling mortality, which is usually unrelated to the size of the tree that dispersed them. In this paper we hypothesize that when tree size and reproductive success in the seedling/sapling stage are not well correlated then the use of allometry in inverse modeling is counter-productive and may lead to poor model fits. For these special cases we suggest using a new model for effective dispersal that we term the unrestricted fecundity (UF) model that, contrary to allometric models, makes no assumptions on the fecundities; instead they are allowed to vary freely from one tree to another and even to be zero for trees that are reproductively inactive. Based on this model, we examine the hypothesis that when tree size and reproductive success are weakly correlated and the fecundities are estimated independently of tree size the goodness-of-fit and the ecological meaning of dispersal models (in the seedling or sapling stage) may be enhanced. Parameters of the UF model are estimated through the EM algorithm and their standard errors are approximated via the observed information matrix. We fit the UF model to a dataset from an expanding European beech population of central Spain as well as to a set of simulated dispersal data were the correlation between reproductive success and tree size was moderate. In comparisons with a simple allometric model, the UF model fitted the data better and the parameter estimates were less biased. We suggest using this new approach for modeling dispersal in the seedling and sapling stages when tree size (or other adult-specific covariates) is not deemed to be in strong relation to the reproductive success of adults. Models that use covariates for modeling the fecundity of adults should be preferred when reproductive success and tree size guard a strong relationship.     

Modelling coupled peach tree-aphid population dynamics and their control by winter pruning and nitrogen fertilization

Nitrogen fertilization and winter pruning are commonly used to control crop production in peach [Prunus persica (L.) Batsch] orchards. They are also known to affect the dynamics of Myzus persicae (Sulzer) (Homoptera: Aphididae) aphid populations via bottom-up regulation processes. Interactions between crops and pests can cause complex system behaviour in response to management practices. An integrated approach will therefore improve the understanding of the effects of these two cultural practices on aphid and peach performances.We developed a simulation model that describes the cultural control of interacting peach tree and aphid population dynamics. It uses the principles of common trophic models while gathering available knowledge and explicit assumptions on peach and aphid functioning and the effects of cultural practices.The model was able to qualitatively reproduce the system behaviour observed in the field. It accounted for actions and feedback such as stimulation of foliar growth by winter pruning, consecutive aphid population increase, subsequent damage to foliage, and partial compensatory growth of foliage. The model also reproduced low losses in fruit production due to aphid infestations. However, it called for further integration of ‘long-term’ effects. Analysis of the model showed the complexity of peach tree and aphid responses to leaf N × winter pruning interactions. Simulations indicated that fruit production losses remained low within a range of realistic values of leaf N and pruning intensity, whereas manipulating peach and aphid dynamics, their interactions and their relationships to practices could result in higher losses.The model is useful to evaluate the relevance of cultural practices for a bottom-up regulation of aphid dynamics in crop-pest management. After considering other control methods and fruit quality, it can be used to find a combination of practices that optimises trade-offs between fruit production and environmental conservation goals. A modelling approach that links crop growth and pest population dynamics and integrates management practice effects has strong potential for improving crop-pest management in an integrated crop production context.     

Use of individual-based models for population parameters estimation

A method for parameters estimation of stage-specific mortality and fecundity rate functions in poikilotherm organisms, and in particular for arthropod structured population, is proposed. The application of this method requires three types of information: stage-frequency data of a sampled population, development rate function and time evolution of forcing variables affecting the rate functions. By means of an individual-based model (a microscopic model) the number of eggs produced by the adults is generated starting from the number of individuals collected at each sampling time. Using a compartmental model (a macroscopic model) a stage-structured population dynamics is described and compared with observations. Non-linear regression methods based on least square principle are used to estimate the optimal parameters of the mortality and fecundity rate functions combining microscopic and macroscopic models. As a case study, the parameter estimation of the temperature-dependent mortality function of olives fruit fly Bactrocera oleae is presented.     

Fitting probability models to population dynamics data

Methods for modeling population dynamics in probability using the generalized point process approach are developed. The life history of these populations is such that seasonal reproduction occurs during a short time. Several models are developed and analyzed. Data about two species: colonial spiders (Stegodyphus dumicola) and a migratory bird (wood thrush, Hylocichla mustelina) are used to estimate model parameters with appropriate log maximum likelihood functions. For the spiders, the model is fitted to provide evolutionary feasible colony size based on maximum likelihood estimates of fecundity and survival data. For the migratory bird species, a maximum likelihood estimates are derived for the fecundity and survival rates of young and adult birds and immigration rate. The presented approach allows computation of quantities of interest such as probability of extinction and average time to extinction.     

Interactive effects of prey and p,p'-DDE on burrowing owl population dynamics.

We used population models to explore the effects of the organochlorine contaminant p,p'-DDE and fluctuations in vole availability on the population dynamics of Burrowing Owls (Athene cunicularia). Previous work indicated an interaction between low biomass of voles in the diet and moderate levels of p,p'-DDE in Burrowing Owl eggs that led to reproductive impairment. We constructed periodic and stochastic matrix models that incorporated three vole population states observed in the field: average, peak, and crash years. We modeled varying frequencies of vole crash years and a range of impairment of owl demographic rates in vole crash years. Vole availability had a greater impact on owl population growth rate than did reproductive impairment if vole populations peaked and crashed frequently. However, this difference disappeared as the frequency of vole crash years declined to once per decade. Fecundity, the demographic rate most affected by p,p'-DDE, had less impact on population growth rate than adult or juvenile survival. A life table response experiment of time-invariant matrices for average, peak, and crash vole conditions showed that low population growth under vole crash conditions was due to low adult and juvenile survival rates, whereas the extremely high population growth under vole peak conditions was due to increased fecundity. Our results suggest that even simple models can provide useful insights into complex ecological interactions. This is particularly valuable when temporal or spatial scales preclude manipulative experimental work in the field or laboratory.     

Density dependence vs. independence, and irregular population dynamics of a swallow-wort fruit fly

Although most long-term studies of consumer-resource (e.g., predator-prey) interactions select species showing cyclic population dynamics, strong consumer-resource interactions can also produce irregular, noncyclic dynamics. Here, we present a case in which a seed predator, the tephritid fruit fly Euphranta connexa, shows fluctuations in density of more than two orders of magnitude over a 22-year period. To explain these fluctuations, we analyzed a stage-specific data set to quantify the density-dependent and density-independent components of larval survivorship and realized fecundity. Both larval survivorship and realized fecundity were strongly density dependent. Larval survivorship dropped from 0.62 at low larval density to 0.081 at high larval density, whereas fecundity dropped from 84.3 to 0.32 eggs per individual, more than a 100-fold decrease. We divided density-independent variation in E. connexa population dynamics into components for variability in (1) larval survivorship, (2) realized fecundity, and (3) annual fruit abundance. Of these components, 96% of the density-independent variance in per capita population growth rates was caused by fluctuations in fruit abundance. This highlights the importance of the strong consumer-resource interactions in driving fluctuations in E. connexa abundance. It also demonstrates that E. connexa dynamics are remarkably simple, and aside from the 4% of unexplained variance in per capita population growth rates, our understanding of E. connexa dynamics is remarkably complete.     

Reproduction of the invasive slipper limpet, Crepidula fornicata, in the Bay of Brest, France

The reproduction of Crepidula fornicata was studied in the Bay of Brest in order to characterise the first step of the reproductive cycle of this invasive species. The survey was carried out from 2000 to 2003 and different parameters were measured, namely, the percentage of the different sexual stages, the straight length of the shell and the percentage of brooding females using a survey of the embryonic development and the fecundity. The juvenile frequency increases generally from mid-June or mid-August, depending on the year. In 2001 and 2003, a first peak was observed as early as May, but it was followed by a rapid disappearance of the individuals. The sex-ratio female/male increased from 0.22 to 0.46 between 2001 and 2003. The sex change between intermediates and females took place mainly in summer and was well marked in 2001 and 2003. The survey of the embryonic development in the egg capsules brooded by the females provided an annual phenology of the laying and hatching processes. The laying period extends from February to September with three to four major periods of egg-laying per year and corresponding hatching periods about 1 month later. Each female lays two to four times per year on average. The first egg-laying concerned fewer females than subsequent ones, except in 2003, and exhibited a higher fecundity. The annual mean of the number of eggs for each stage was not significantly different, thus indicating no significant mortality rate during embryonic development. For the C. fornicata population in the Bay of Brest, several reproductive characteristics tend to highlight its invasive capacity: (1) a long reproductive period, (2) reproduction in a ‘multi-trials’ process equivalent to a spreading out of the risks and (3) a relatively high fecundity.     

The importance of space, time, and stochasticity to the demography and management of Alliaria petiolata

As population modeling is increasingly called upon to guide policy and management, it is important that we understand not only the central tendencies of our study systems, but the consequences of their variation in space and time as well. The invasive plant Alliaria petiolata (garlic mustard) is actively managed in the United States and is the focus of a developing biological control program. Two weevils (Coleoptera: Curculionidae: Ceutorhynchus) that reduce fecundity (C. alliariae) and rosette survival plus fecundity (C. scrobicollis) are under consideration for release pending host specificity testing. We used a demographic modeling approach to (1) quantify variability in A. petiolata growth and vital rates and (2) assess the potential for single- or multiple-agent biocontrol to suppress growth of 12 A. petiolata populations in Illinois and Michigan studied over three plant generations. We used perturbation analyses and simulation models with stochastic environments to estimate stochastic growth rates (lambda(S)) and predict the probability of successful management using either a single biocontrol agent or two agent species together. Not all populations exhibited invasive dynamics. Estimates of lambda(S) ranged from 0.78 to 2.21 across sites, while annual, deterministic growth (lambda) varied up to sevenfold within individual sites. Given our knowledge of the biocontrol agents, this analysis suggests that C. scrobicollis alone may control A. petiolata at up to 63% of our study sites where lambda >1, with the combination of both agents predicted to succeed at 88% of sites. Across sites and years, the elasticity rankings were dependent on lambda. Reductions of rosette survival, fecundity, or germination of new seeds are predicted to cause the greatest reduction of lambda in growing populations. In declining populations, transitions affecting seed bank survival have the greatest effect on lambda. This contrasts with past analyses that varied parameters individually in an otherwise constant matrix, which may yield unrealistic predictions by decoupling natural parameter covariances. Overall, comparisons of stochastic and deterministic growth rates illustrate how analyses of individual populations or years could misguide management or fail to characterize complex traits such as invasiveness that emerge as attributes of populations rather than species.     

Demography of central and marginal populations of monkeyflowers (Mimulus cardinalis and M. lewisii)

Every species occupies a limited geographic area, but how spatiotemporal environmental variation affects individual and population fitness to create range limits is not well understood. Because range boundaries arise where, on average, populations are more likely to go extinct than to persist, range limits are an inherently population-level problem for which a demographic framework is useful. In this study, I compare demographic parameters and population dynamics between central and marginal populations of monkeyflowers, Mimulus cardinalis and M. lewisii, along an elevation gradient spanning both species' ranges. Central and marginal populations of both species differed in survival and fecundity. For M. lewisii, these components of fitness were higher in central than in marginal populations, but for M. cardinalis the converse was true. To assess spatiotemporal variation in population dynamics, I used transition matrix models to estimate asymptotic population growth rates (lambda) and found that population growth rates of M. lewisii were highest at the range center and reduced at the range margin. Population growth rates of M. cardinalis were highest at the range margin and greatly reduced at the range center. Life table response analysis decomposed spatiotemporal variation in lambda into contributions from each transition between life stages, finding that transitions from large nonreproductive and reproductive plants to the seed class and stasis in the reproductive class made the largest contributions to spatial differences in lambda. These transitions had only low to moderate sensitivities, indicating that differences in projected population growth rates resulted mainly from observed differences in transition matrix parameters and their underlying vital rates.     

Stereological methods applied to reproductive cycle of Tapes rhomboides

A population of Tapes rhomboides (Pennant) in the Bay of St. Malo, France, was studied for one and a half years (July 1984–October 1985) to determine spawning frequency and fecundity under natural conditions, using the techniques of qualitative histological staging, condition index calculation and quantitative stereology. Spawning took place twice a year, in late May and in July/September. There was an extended winter resting period. Gonad development and oocyte production were positively correlated with female body size. The annual fecundity in a 40 mm clam was about 5x10⁵. Stereological techniques provided accurate information on oocyte dynamics within a gonad and the relationship with atretic processes. Each oocyte generation from the onset of the cycle to the winter resting stage was spawned eventually if conditions were suitable, or the oocytes were resorbed. Atresia of oocytes was seen throughout the reproductive period, but especially after the spring spawning and at the end of the summer.     

The Influence of Model Structure on Conclusions about the Viability and Harvesting of Serengeti Wildebeest

We investigate how the viability and harvestability predicted by population models are affected by details of model construction. Based on this analysis we discuss some of the pitfalls associated with the use of classical statistical techniques for resolving the uncertainties associated with modeling population dynamics. The management of the Serengeti wildebeest (Connochaetes taurinus) is used as a case study. We fitted a collection of age-structured and unstructured models to a common set of available data and compared model predictions in terms of wildebeest viability and harvest. Models that depicted demographic processes in strikingly different ways fitted the data equally well. However, upon further analysis it became clear that models that fit the data equally well could nonetheless have very different management implications. In general, model structure had a much larger effect on viability analysis (e.g., time to collapse) than on optimal harvest analysis (e.g., harvest rate that maximizes harvest). Some modeling decisions, such as including age-dependent fertility rates, did not affect management predictions, but others had a strong effect (e.g., choice of model structure). Because several suitable models of comparable complexity fitted the data equally well, traditional model selection methods based on the parsimony principle were not practical for judging the value of alternative models. Our results stress the need to implement analytical frameworks for population management that explicitly consider the uncertainty about the behavior of natural systems.     

Setting Realistic Recovery Targets for Two Interacting Endangered Species,Sea Otter and Northern Abalone

Failure to account for interactions between endangered species may lead to unexpected population dynamics, inefficient management strategies, waste of scarce resources, and, at worst, increased extinction risk. The importance of species interactions is undisputed, yet recovery targets generally do not account for such interactions. This shortcoming is a consequence of species‐centered legislation, but also of uncertainty surrounding the dynamics of species interactions and the complexity of modeling such interactions. The northern sea otter (Enhydra lutris kenyoni) and one of its preferred prey, northern abalone (Haliotis kamtschatkana), are endangered species for which recovery strategies have been developed without consideration of their strong predator–prey interactions. Using simulation‐based optimization procedures from artificial intelligence, namely reinforcement learning and stochastic dynamic programming, we combined sea otter and northern abalone population models with functional‐response models and examined how different management actions affect population dynamics and the likelihood of achieving recovery targets for each species through time. Recovery targets for these interacting species were difficult to achieve simultaneously in the absence of management. Although sea otters were predicted to recover, achieving abalone recovery targets failed even when threats to abalone such as predation and poaching were reduced. A management strategy entailing a 50% reduction in the poaching of northern abalone was a minimum requirement to reach short‐term recovery goals for northern abalone when sea otters were present. Removing sea otters had a marginally positive effect on the abalone population but only when we assumed a functional response with strong predation pressure. Our optimization method could be applied more generally to any interacting threatened or invasive species for which there are multiple conservation objectives. Definición de Metas de Recuperación Realistas para Dos Especies en Peligro Interactuantes, Enhydra lutris y Haliotis kamtschatkana     

Evaluating mortality rates with a novel integrated framework for nonmonogamous species

The conservation of wildlife requires management based on quantitative evidence, and especially for large carnivores, unraveling cause‐specific mortalities and understanding their impact on population dynamics is crucial. Acquiring this knowledge is challenging because it is difficult to obtain robust long‐term data sets on endangered populations and, usually, data are collected through diverse sampling strategies. Integrated population models (IPMs) offer a way to integrate data generated through different processes. However, IPMs are female‐based models that cannot account for mate availability, and this feature limits their applicability to monogamous species only. We extended classical IPMs to a two‐sex framework that allows investigation of population dynamics and quantification of cause‐specific mortality rates in nonmonogamous species. We illustrated our approach by simultaneously modeling different types of data from a reintroduced, unhunted brown bear (Ursus arctos) population living in an area with a dense human population. In a population mainly driven by adult survival, we estimated that on average 11% of cubs and 61% of adults died from human‐related causes. Although the population is currently not at risk, adult survival and thus population dynamics are driven by anthropogenic mortality. Given the recent increase of human‐bear conflicts in the area, removal of individuals for management purposes and through poaching may increase, reversing the positive population growth rate. Our approach can be generalized to other species affected by cause‐specific mortality and will be useful to inform conservation decisions for other nonmonogamous species, such as most large carnivores, for which data are scarce and diverse and thus data integration is highly desirable.