Integral projection models perform better for small demographic data sets than matrix population models: a case study of two perennial herbs

1. Matrix population models are widely used to describe population dynamics, conduct population viability analyses and derive management recommendations for plant populations. For endangered or invasive species, management decisions are often based on small demographic data sets. Hence, there is a need for population models which accurately assess population performance from such small data sets.
2. We used demographic data on two perennial herbs with different life histories to compare the accuracy and precision of the traditional matrix population model and the recently developed integral projection model (IPM) in relation to the amount of data.
3. For large data sets both matrix models and IPMs produced identical estimates of population growth rate (λ). However, for small data sets containing fewer than 300 individuals, IPMs often produced smaller bias and variance for λ than matrix models despite different matrix structures and sampling techniques used to construct the matrix population models.
4. Synthesis and applications . Our results suggest that the smaller bias and variance of λ estimates make IPMs preferable to matrix population models for small demographic data sets with a few hundred individuals. These results are likely to be applicable to a wide range of herbaceous, perennial plant species where demographic fate can be modelled as a function of a continuous state variable such as size. We recommend the use of IPMs to assess population performance and management strategies particularly for endangered or invasive perennial herbs where little demographic data are available.     

Demographic factors affecting population growth in giant gartersnakes

Demographic models provide insight into which vital rates and life stages contribute most to population growth. Integral projection models (IPMs) offer flexibility in matching model structure to a species’ demography. For many rare species, data are lacking for key vital rates, and uncertainty might dissuade researchers from attempting to build a demographic model. We present work that highlights how the implications of uncertainties and unknowns can be explored by building and analyzing alternative models. We constructed IPMs for the threatened giant gartersnake (Thamnophis gigas) based on published studies to determine where management efforts could be targeted to have the greatest effect on population persistence and what unknowns remain for future research. Given uncertainty in the survival of snakes during their first year, and in the form of the size-survival relationship, we modeled a range of scenarios and evaluated where models agree about factors influencing population growth and where discrepancies exist. For most scenarios, the survival of large adult females had the greatest influence on population growth, but the relative importance of juvenile versus adult somatic growth for population growth was dependent on the recruitment probability and the shape of the size-survival function. More data on temporal variation and covariance among vital rates would improve stochastic models for the giant gartersnake. This paper demonstrates the effectiveness of IPMs for studying the demography of reptiles and the value of the model-building process for formalizing what is known and unknown about the demography of rare species. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.     

Nestboxes and immigration drive the growth of an urban Peregrine Falcon Falco peregrinus population

Drivers of wildlife population dynamics are generally numerous and interacting. Some of these drivers may impact demographic processes that are difficult to estimate, such as immigration into the focal population. Populations may furthermore be small and subject to demographic stochasticity. All of these factors contribute to blur the causal relationship between past management action and current population trends. The urban Peregrine Falcon Falco peregrinus population in Cape Town, South Africa, increased from three pairs in 1997 to 18 pairs in 2010. Nestboxes were installed over this period to manage the interface between new urban pairs of Falcons and the human users of colonized buildings, and incidentally to improve breeding success. We used integrated population models (IPMs) formally to combine information from a capture–mark–recapture study, monitoring of reproductive success and counts of population size. As all local demographic processes were directly observed, the IPM approach also allowed us to estimate immigration by difference. The provision of nestboxes, as a possible stimulant of population growth, improved breeding success and accounted for an estimated 3–26% of the population increase. The most important driver of growth, however, was immigration. Despite low sample sizes, the IPM approach allowed us to obtain relatively precise estimates of the population‐level impact of nestbox deployment. The goal of conservation interventions is often to increase population size, so the effectiveness of such interventions should ideally be assessed at the population level. IPMs are powerful tools in this context for combining demographic information that may be limited due to small population size or practical constraints on monitoring. Our study quantitatively documented both the immigration process that led to growth of a small population and the effect of a management action that helped the process.     

Using multiple data types and integrated population models to improve our knowledge of apex predator population dynamics

Current management of large carnivores is informed using a variety of parameters, methods, and metrics; however, these data are typically considered independently. Sharing information among data types based on the underlying ecological, and recognizing observation biases, can improve estimation of individual and global parameters. We present a general integrated population model (IPM), specifically designed for brown bears (Ursus arctos), using three common data types for bear (U. spp.) populations: repeated counts, capture–mark–recapture, and litter size. We considered factors affecting ecological and observation processes for these data. We assessed the practicality of this approach on a simulated population and compared estimates from our model to values used for simulation and results from count data only. We then present a practical application of this general approach adapted to the constraints of a case study using historical data available for brown bears on Kodiak Island, Alaska, USA. The IPM provided more accurate and precise estimates than models accounting for repeated count data only, with credible intervals including the true population 94% and 5% of the time, respectively. For the Kodiak population, we estimated annual average litter size (within one year after birth) to vary between 0.45 [95% credible interval: 0.43; 0.55] and 1.59 [1.55; 1.82]. We detected a positive relationship between salmon availability and adult survival, with survival probabilities greater for females than males. Survival probabilities increased from cubs to yearlings to dependent young ≥2 years old and decreased with litter size. Linking multiple information sources based on ecological and observation mechanisms can provide more accurate and precise estimates, to better inform management. IPMs can also reduce data collection efforts by sharing information among agencies and management units. Our approach responds to an increasing need in bear populations’ management and can be readily adapted to other large carnivores.     

Disentangling the spatial and temporal causes of decline in a bird population

The difficulties in understanding the underlying reasons of a population decline lie in the typical short duration of field studies, the often too small size already reached by a declining population or the multitude of environmental factors that may influence population trend. In this difficult context, useful demographic tools such as integrated population models (IPM) may help disentangling the main reasons for a population decline. To understand why a hoopoe Upupa epops population has declined, we followed a three step model analysis. We built an IPM structured with respect to habitat quality (approximated by the expected availability of mole crickets, the main prey in our population) and estimated the contributions of habitat‐specific demographic rates to population variation and decline. We quantified how much each demographic rate has decreased and investigated whether habitat quality influenced this decline. We tested how much weather conditions and research activities contributed to the decrease in the different demographic rates. The decline of the hoopoe population was mainly explained by a decrease in first‐year apparent survival and a reduced number of fledglings produced, particularly in habitats of high quality. Since a majority of pairs bred in habitats of the highest quality, the decrease in the production of locally recruited yearlings in high‐quality habitat was the main driver of the population decline despite a homogeneous drop of recruitment across habitats. Overall, the explanatory variables we tested only accounted for 19% of the decrease in the population growth rate. Among these variables, the effects of spring temperature (49% of the explained variance) contributed more to population decline than spring precipitation (36%) and research activities (maternal capture delay, 15%). This study shows the power of IPMs for identifying the vital rates involved in population declines and thus paves the way for targeted conservation and management actions.     

Implications from Monitoring Gopher Tortoises at Two Spatial Scales

Conservation biologists need to effectively monitor species given resource limitations and the inherent challenges of assessing long-term demographic processes. We assessed gopher tortoise (Gopherus polyphemus) abundance at a landscape scale and at the scale of 3 local populations within the Conecuh National Forest (CNF), Alabama, USA, between 1991 and 2017. We collected landscape-level data from line transect distance sampling arranged uniformly across the CNF during a single season (2011); we obtained data for local populations from long-term mark-recapture of individuals at 3 sites selected based on prior knowledge of high density at each. At a landscape scale, we estimated 5,242 (95% CI = 3,538–7,768) tortoises occurred across the approximately 34,000-ha forest, yielding a density of 0.14–0.32 tortoises/ha. These low densities across the landscape suggest that, on average, management activities across the property have not allowed tortoise populations to retain the social structure needed for long-term persistence. The 3 local populations, however, contained 25–60 individuals and densities of 1.9–6.9 tortoises/ha. Over the study period, populations at 2 sites were stable and the third experienced significant population growth. Mean annual survival of individuals was 0.89 and invariant across size classes. Overall, line transect distance sampling is important for assessing landscape-scale abundance of tortoises but may fail to detect local clusters of high-density sites important for population persistence. Our mark-recapture efforts at the local scale revealed that small populations on these high-density sites can exhibit long-term stability or growth even though they do not meet current established criteria for viability. Improved models that incorporate immigration and emigration and better reflect the dynamics of peripheral populations would assist in determining how such populations best contribute to species recovery and regional conservation targets. © 2020 The Wildlife Society.     

Wildlife population assessment: past developments and future directions

We review the major developments in wildlife population assessment in the past century. Three major areas are considered: mark-recapture, distance sampling, and harvest models. We speculate on how these fields will develop in the next century. Topics for which we expect to see methodological advances include integration of modeling with Geographic Information Systems, automated survey design algorithms, advances in model-based inference from sample survey data, a common inferential framework for wildlife population assessment methods, improved methods for estimating population trends, the embedding of biological process models into inference, substantially improved models for conservation management, advanced spatiotemporal models of ecosystems, and greater emphasis on incorporating model selection uncertainty into inference. We discuss the kind of developments that might be anticipated in these topics.     

Effect of Harvest on a Brown Bear Population in Alaska

There is a long and contentious history of brown bear (Ursus arctos) harvest management in Alaska, USA, the state that hosts the largest brown bear population in North America. In the mid-1990s, the Alaska Board of Game set the population objective for brown bears in Game Management Unit 13 A, located in interior southcentral Alaska, to be reduced by 50% to improve survival of moose (Alces alces) calves. The Board began further liberalizing brown bear harvest regulations for the unit beginning in regulatory year 1995, though adult females and their dependent offspring (i.e., cubs <2 yrs old) were protected. To evaluate progress toward this abundance objective, we captured and collared bears between 2006 and 2011 and conducted a capture-mark-resight density survey during summer 2011 for comparison to a similar baseline survey conducted in 1998. We report the results of the density survey and vital rates estimated from resight histories of collared bears and harvest information spanning from 1985 (10 years before establishment of the population objective) to 2012. There was a 25–40% reduction in abundance between 1998 and 2011. Population growth rates derived from density estimates and a matrix population projection model indicated that the population declined by 2.3–4.2% annually. We estimated harvest rates to be 8–15% annually, but harvest composition data indicated no changes in skull size, age distribution, or overall sex ratio. There was evidence of an increase in the proportion of older females in the harvest. Demographic analysis indicated high reproductive output and recruitment, potentially indicating a density-dependent compensatory response to reduced population size. Despite 13 years of harvest rates in excess of what had previously been considered to be sustainable for this population, the objective of reducing bear abundance by 50% had not been achieved as of 2011. The protection of females and dependent offspring in our study population appears to be a sufficient safeguard against a precipitous population decline while still permitting progress toward the population objective through high harvest on other segments of the population. © 2020 The Wildlife Society.     

An Integrated Population Model for Harvest Management of Atlantic Brant

Atlantic brant (Branta bernicla hrota) are important game birds in the Atlantic Flyway and several long-term monitoring data sets could assist with harvest management, including a count-based survey and demographic data. Considering their relative strengths and weaknesses, integrated analysis to these data would likely improve harvest management, but tools for integration have not yet been developed. Managers currently use an aerial count survey on the wintering grounds, the mid-winter survey, to set harvest regulations. We developed an integrated population model (IPM) for Atlantic brant that uses multiple data sources to simultaneously estimate population abundance, survival, and productivity. The IPM abundance estimates for data from 1975–2018 were less variable than annual mid-winter survey counts or Lincoln estimates, presumably reflecting better accounting for observer error and incorporation of demographic estimates by the IPM. Posterior estimates of adult survival were high (0.77–0.87), and harvest rates of adults and juveniles were positively correlated with more liberal hunting regulations (i.e., hunting days and the daily bag limit). Productivity was variable, with the percent of juveniles in the winter population ranging from 1% to >40%. We found no evidence for environmental relationships with productivity. Using IPM-predicted population abundances rather than mid-winter survey counts alone would have meant fewer annual changes to hunting regulations since 2004. Use of the IPM could improve harvest management for Atlantic brant by providing the ability to predict abundance before annual hunting regulations are set, and by providing more stable hunting regulations, with fewer annual changes. © 2021 The Wildlife Society.     

Consequences of past and present harvest management in a declining flyway population of common eiders Somateria mollissima

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Integrating Genetic Data and Demographic Modeling to Facilitate Conservation of Small,Isolated Mountain Goat Populations

Acquisition of field data and analytical methods needed for conservation and management of wildlife populations represent significant challenges, particularly for species that inhabit landscapes that are difficult to access or species that persist in small, isolated populations. In such instances, integrating diverse and complementary data streams, such as genetic and non-genetic data, can advance our understanding of population dynamics and associated management implications. We examined how genetic and morphologic data can be used to articulate population structure of a low-density, peninsular population of mountain goats (Oreamnos americanus) on the Cleveland Peninsula, Alaska, USA, and surrounding areas, 2005–2018. We then use a population demographic modeling approach to examine how the use of population structure information influences sustainable harvest quotas, as compared to a panmictic, null model. Specifically, we conducted extensive field sampling of genetic (n = 446) and morphologic (i.e., horn length, n = 371) data to characterize population structure. We conducted demographic analyses and examined harvest modeling scenarios using a sex- and age-specific matrix population modeling approach. Genetic and morphologic data analyses suggested peninsular subpopulations were demographically isolated, relative to surrounding mainland populations. Specifically, genetic structuring was evident and followed an isolation-by-distance, stepping-stone pattern indicating limited interchange, low effective population sizes, and reduced genetic diversity along a peninsular extremity to mainland gradient. Harvest modeling indicated that overharvest would likely occur if the panmictic, null model was used to guide harvest because the smallest genetically defined population at the peninsular extremity was too small to permit any level of sustainable harvest. Our analyses illustrate the importance of using genetic and morphologic data, in combination with demographic modeling, to quantitatively delineate population boundaries and dynamics for ensuring viability of small, isolated populations. © 2020 The Wildlife Society.     

Distance sampling surveys: using components of detection and total error to select among approaches

Wildlife population estimators often require formal adjustment for imperfect detection of individuals during surveys. Conventional distance sampling (CDS) and its extensions (mark-recapture distance sampling [MRDS], temporary emigration distance sampling [TEDS]) are popular approaches for producing unbiased estimators of wildlife abundance. However, despite extensive discussion and development of distance sampling theory in the literature, deciding which of these alternatives is most appropriate for a particular scenario can be confusing. Some of this confusion may stem from an incomplete understanding of how each approach addresses the components of the detection process. Here we describe the proper application of CDS, MRDS, and TEDS approaches and use applied examples to help clarify their differing assumptions with respect to the components of the detection process. To further aid the practitioner, we summarize the differences in a decision tree that can be used to identify cases where a more complex alternative (e.g., MRDS or TEDS) may be appropriate for a given survey application. Although the more complex approaches can account for additional sources of bias, in practical applications one also must consider estimator precision. Therefore, we also review the concept of total estimator error in the context of comparing competing methods for a given application to aid in the selection of the most appropriate distance sampling approach. Finally, we detail how the use of more advanced techniques (i.e., informed priors, open-population distance sampling models, and integrated modeling approaches) can further reduce total estimator error by leveraging information from existing and ongoing data collection. By synthesizing the existing literature on CDS, MRDS, TEDS and their extensions, in conjunction with the concepts of total estimator error and the components of the detection process, we provide a comprehensive guide that can be used by the practitioner to more efficiently, effectively, and appropriately apply distance sampling in a variety of settings.     

Challenges and opportunities for estimating abundance of a low-density moose population

Monitoring large herbivores across their core range has been readily accomplished using aerial surveys and traditional distance sampling. But for peripheral populations, where individuals may occur in patchy, low-density populations, precise estimation of population size and trend remains logistically and statistically challenging. For moose (Alces alces) along their southern range margin in northern New York, USA, we sought robust estimates of moose distribution, abundance, and population trend (2016–2019) using a combination of aerial surveys (line transect distance-sampling), repeated surveys in areas where moose were known to occur to boost the number of detections, and density surface modeling (DSM) with spatial covariates. We achieved a precise estimate of density (95% CI = 0.00–0.29 moose/km²) for this small population (656 moose, 95% CI = 501–859), which was patchily distributed across a large and heavily forested region (the 24,280-km² Adirondack Park). Local moose abundance was positively related to active timber management, elevation, and snow cover, and negatively related to large bodies of water. As expected, moose abundance in this peripheral population was low relative to its core range in other northern forest states. Yet, in areas where abundance was greatest, moose densities in New York approached those where epizootics of winter tick (Dermacentor albipictus) have been reported, underscoring the need for effective and efficient monitoring. By incorporating autocorrelation in observations and landscape covariates, DSM provided spatially explicit estimates of moose density with greater precision and no additional field effort over traditional distance sampling. Combined with repeated surveys of areas with known moose occurrence to achieve viable sample sizes, DSM is a useful tool for effectively monitoring low density and patchy populations.     

Monitoring coyote population dynamics by genotyping faeces

Reliable population estimates are necessary for effective conservation and management, and faecal genotyping has been used successfully to estimate the population size of several elusive mammalian species. Information such as changes in population size over time and survival rates, however, are often more useful for conservation biology than single population estimates. We evaluated the use of faecal genotyping as a tool for monitoring long-term population dynamics, using coyotes (Canis latrans) in the Alaska Range as a case study. We obtained 544 genotypes from 56 coyotes over 3 years (2000-2002). Tissue samples from all 15 radio-collared coyotes in our study area had > or = 1 matching faecal genotypes. We used flexible maximum-likelihood models to study coyote population dynamics, and we tested model performance against radio telemetry data. The staple prey of coyotes, snowshoe hares (Lepus americanus), dramatically declined during this study, and the coyote population declined nearly two-fold with a 1(1/2)-year time lag. Survival rates declined the year after hares crashed but recovered the following year. We conclude that long-term monitoring of elusive species using faecal genotyping is feasible and can provide data that are useful for wildlife conservation and management. We highlight some drawbacks of standard open-population models, such as low precision and the requirement of discrete sampling intervals, and we suggest that the development of open models designed for continuously collected data would enhance the utility of faecal genotyping as a monitoring tool.     

Noninvasive Hair Sampling and Genetic Tagging of Co-Distributed Fishers and American Martens

ABSTRACT Estimation of abundance is important for assessing population responses to management actions. Accurate abundance estimates are particularly critical for monitoring temporal variation following reintroductions when the management goal is to attain population sizes capable of sustaining harvest. Numerous reintroductions have taken place in the Great Lakes region of North America, including efforts to restore extirpated fishers (Martes pennanti) and American martens (M. americana). We used a DNA-based noninvasive hair-snaring method based on one trap design and trapping -grid configuration, and evaluated capture—mark—recapture (CMR) analytical approaches to simultaneously estimate population size for co-distributed fishers and American martens in a 671-km² area of the Ottawa National Forest in the western Upper Peninsula of Michigan, USA. We included harvest as a final recapture period to increase probability of recapture and to evaluate potential violations of geographic closure assumptions. We used microsatellite markers to identify target species, eliminate congener species, and provide individual identity for estimation of abundance. Population estimates for fishers and martens on the study area ranged from 35 to 60 and 8 to 28, respectively. Estimators incorporating harvest data resulted in up to a 40% increase in abundance estimates relative to estimators without harvest. We considered population estimates not including harvest data the most appropriate for the study due to timing of sampling and environmental factors, but inclusion of harvested individuals was shown to be useful as a means to detect violations of the assumption of geographic closure. We suggest improvements on future CMR sampling designs for larger landscape scales of relevance to management through incorporation of habitat or historical harvest data. Noninvasive genetic methods that simultaneously estimate the numerical abundance of co-distributed species can greatly decrease assessment costs relative to traditional methods, and increase resulting demographic and ecological information.     

Estimating abundance and population trends when detection is low and highly variable: A comparison of three methods for the Hermann's tortoise

Assessing population trends is a basic prerequisite to carrying out adequate conservation strategies. Selecting an appropriate method to monitor animal populations can be challenging, particularly for low-detection species such as reptiles. This study compares 3 detection-corrected abundance methods (capture–recapture, distance sampling, and N-mixture) used to assess population size of the threatened Hermann's tortoise. We used a single dataset of 432 adult tortoise observations collected at 118 sampling sites in the Plaine des Maures, southeastern France. We also used a dataset of 520 tortoise observations based on radiotelemetry data collected from 10 adult females to estimate and model the availability (g0) needed for distance sampling. We evaluated bias for N-mixture and capture–recapture, by using simulations based on different values of detection probabilities. Finally, we conducted a power analysis to estimate the ability of the 3 methods to detect changes in Hermann's tortoise abundances. The abundance estimations we obtained using distance sampling and N-mixture models were respectively 1.75 and 2.19 times less than those obtained using the capture–recapture method. Our results indicated that g0 was influenced by temperature variations and can differ for the same temperature on different days. Simulations showed that the N-mixture models provide unstable estimations for species with detection probabilities <0.5, whereas capture–recapture estimations were unbiased. Power analysis showed that none of the 3 methods were precise enough to detect slow population changes. We recommend that great care should be taken when implementing monitoring designs for species with large variation in activity rates and low detection probabilities. Although N-mixture models are easy to implement, we would not recommend using them in situations where the detection probability is very low at the risk of providing biased estimates. Among the 3 methods allowing estimation of tortoise abundances, capture–recapture should be preferred to assess population trends. © 2013 The Wildlife Society.     

Perturbation approaches for integral projection models

Perturbation analysis of population models is fundamental to elucidating mechanisms of population dynamics and examining scenarios of change. The use of integral projection models (IPMs) has increased in the last decade, and while many of the tools and approaches developed for matrix models remain relevant, the nature of IPMs expands the framework of perturbation analysis, with different approaches often requiring important considerations. This article provides a review of – and practical guide to – different perturbation approaches for IPMs, formalizes methodologies for perturbing IPM size transition probabilities, and highlights areas where researchers should be particularly careful and critical when conducting and interpreting perturbation analysis. I use a simulated dataset to compare five hierarchical perturbation approaches for IPMs found within 63 published studies, and apply a combination of approaches to the example of an invasive perennial plant. Other perturbation approaches for IPMs are also highlighted. Most perturbation analyses for IPMs to date have focused on the response of the asymptotic population growth rate (λ) to changes in elements of the discretized projection kernel and/or the growth– survival and reproduction– recruitment sub‐kernels. Perturbations to vital rate functions and regression predictions underlying these kernels provide mechanistic insight, but are less common and can require important considerations regarding the perturbation of size transitions separate from survival and the nature of the state variable (used to represent size). The second most common approach is more specific to IPMs and examines the influence of vital rate regression parameters, each of which can have broad influence on the population growth rate. Researchers using IPMs have many perturbation options available and should carefully consider which approach or combination of approaches is most applicable and interpretable for their specific questions.     

Rejection of Schmidt et al.'s estimators for bear population size

Aerial distance sampling of bears to estimate population size has been used throughout many parts of Alaska. The distance sampling models are complex since they need to account for undetected bears and differences in detection probabilities. This will require covariates and mark‐recapture data. The models proposed by Schmidt et al. do not use covariates or mark‐recapture data and are inappropriate for these surveys.     

Black Brant Harvest,Density Dependence,and Survival: A Record of Population Dynamics

ABSTRACT We analyzed 53 years of banding and band recovery data along with estimates of harvest and population size to assess the role of harvest and density dependence in survival patterns and population dynamics of black brant (Branta bernicla nigricans) over the period 1950–2003. The black brant population has declined steadily since complete annual surveys began in 1960, so the role of harvest in the dynamics of this population is of considerable interest. We used Brownie models implemented in Program MARK to analyze banding data. In some models, we incorporated estimated sport harvest to test hypotheses about the role of harvest in survival. We also examined the hypothesis of density-dependent regulation of mortality by incorporating estimates of population size as a covariate into models of survival. For a shorter period (1985–2003), we also assessed hypotheses about the role of subsistence harvest and predation as sources of mortality. The best supported model of variation in survival and band recovery allowed survival rates to vary among 2 age classes (juv, second-yr plus ad brant) and the 2 sexes. We constrained survival probabilities to be constant within decades but allowed them to vary among decades. We also constrained band recovery rates to be constant within decades and to vary in parallel among age and sex classes. We were limited to decade-specific estimates of survival and band recovery rates because some years before 1984 lacked any banding, and banding in some other years was sparse. A competitive model constrained survival estimates to be the same for males and females. No model containing harvest or population size was competitive with models lacking these covariates (relative quasi-Akaike's Information Criterion adjusted for small sample size [βQAIC_c] > 13). In the best supported model, band recovery rates declined from 0.038 ± 0.0028 (F) and 0.040 ± 0.0031 (M) to 0.007 ± 0.0007 (F) and 0.007 ± 0.0007 (M) between the 1950s and 2000s, a clear indication that harvest rates declined over this period. Survival rates increased from 0.70 ± 0.02 and 0.71 ± 0.02 for adult males and females, respectively, in the 1950s to 0.88 ± 0.009 and 0.88 ± 0.01 for males and females, respectively, in the 1990s. Survival rates in the 1990s were among the highest estimated for brant and did not increase in the 2000s with additional reductions in sport harvest. For the shorter data set from 1985 to 2003, models containing covariates for either sport or subsistence harvest were less competitive than models lacking these terms (βQAIC_c > 3). For the best model containing subsistence harvest, the estimate of β linking subsistence harvest to survival, although imprecisely estimated, was near zero (β = −0.04 ± 0.30), consistent with the hypothesis that subsistence harvest had little impact on survival during this period. We conclude that while harvest likely influenced survival and population dynamics in earlier decades, it is most likely that continued population decline at least since 1990 is a result of low recruitment.     

White-Tailed Deer Population Dynamics Following Louisiana Black Bear Recovery

Changing predator communities have been implicated in reduced survival of white-tailed deer (Odocoileus virginianus) fawns. Few studies, however, have used field-based age-specific estimates for survival and fecundity to assess the relative importance of low fawn survival on population growth and harvest potential. We studied white-tailed deer population dynamics on Tensas River National Wildlife Refuge (TRNWR) in Louisiana, USA, where the predator community included bobcats (Lynx rufus), coyotes (Canis latrans), and a restored population of Louisiana black bear (Ursus americanus luteolus). During 2013–2015, we radio-collared and monitored 70 adult (≥2.5 yrs) and 21 yearling (1.5-yr-old) female deer. Annual survival averaged 0.815 (95% CI = 0.734–0.904) for adults and 0.857 (95% CI = 0.720–1.00) for yearlings. We combined these estimates with concurrently collected fawn survival estimates (0.27; 95% CI = 0.185–0.398) to model population trajectories and elasticities. We used estimates of nonhunting survival (annual survival estimated excluding harvest mortality) to project population growth (λ) relative to 4 levels of harvest (0, 10%, 20%, 30%). Finally, we investigated effects of reduced fawn survival on population growth under current management and with elimination of female harvest. Despite substantial fawn predation, the deer population on TRNWR was increasing (λ = 1.06) and could sustain additional female harvest; however, the population was expected to decline at 20% (λ = 0.98) and 30% (λ = 0.94) female harvest. With no female harvest, the population was projected to increase with observed (λ = 1.15) and reduced fawn survival (λ = 1.02), but the population could not sustain current female harvest (10%) if fawn survival declined (λ = 0.90). For all scenarios, adult female survival was the most elastic parameter. Given the importance of adult female survival, the relative predictability in response of adult survival to harvest management, and the difficulty in altering fawn survival, reducing female harvest is likely the most efficient approach to compensate for low fawn survival. On highly productive sites such as ours, reduction, but not necessarily elimination, of harvest can mitigate effects of low fawn survival on population growth. © 2020 The Wildlife Society.