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Frank T. van Manen

Publications and source records attributed to Frank T. van Manen.

71 records · Page 4Linked to original sources

Re-evaluation of Yellowstone grizzly bear population dynamics not supported by empirical data: response to Doak & Cutler

Doak and Cutler critiqued methods used by the Interagency Grizzly Bear Study Team (IGBST) to estimate grizzly bear population size and trend in the Greater Yellowstone Ecosystem. Here, we focus on the premise, implementation, and interpretation of simulations they used to support their arguments. They argued that population increases documented by IGBST based on females with cubs-of-the-year were an artifact of increased search effort. However, we demonstrate their simulations were neither reflective of the true observation process nor did their results provide statistical support for their conclusion. They further argued that survival and reproductive senescence should be incorporated into population projections, but we demonstrate their choice of extreme mortality risk beyond age 20 and incompatible baseline fecundity led to erroneous conclusions. The conclusions of Doak and Cutler are unsubstantiated when placed within the context of a thorough understanding of the data, study system, and previous research findings and publications.

Conservation Letters

Whitebark pine, population density, and home-range size of grizzly bears in the greater Yellowstone ecosystem

Changes in life history traits of species can be an important indicator of potential factors influencing populations. For grizzly bears ( Ursus arctos ) in the Greater Yellowstone Ecosystem (GYE), recent decline of whitebark pine (WBP; Pinus albicaulis ), an important fall food resource, has been paired with a slowing of population growth following two decades of robust population increase. These observations have raised questions whether resource decline or density-dependent processes may be associated with changes in population growth. Distinguishing these effects based on changes in demographic rates can be difficult. However, unlike the parallel demographic responses expected from both decreasing food availability and increasing population density, we hypothesized opposing behavioral responses of grizzly bears with regard to changes in home-range size. We used the dynamic changes in food resources and population density of grizzly bears as a natural experiment to examine hypotheses regarding these potentially competing influences on grizzly bear home-range size. We found that home-range size did not increase during the period of whitebark pine decline and was not related to proportion of whitebark pine in home ranges. However, female home-range size was negatively associated with an index of population density. Our data indicate that home-range size of grizzly bears in the GYE is not associated with availability of WBP, and, for female grizzly bears, increasing population density may constrain home-range size.

Idaho, Montana, Wyoming

Dietary breadth of grizzly bears in the Greater Yellowstone Ecosystem

Grizzly bears ( Ursus arctos ) in the Greater Yellowstone Ecosystem (GYE) are opportunistic omnivores that eat a great diversity of plant and animal species. Changes in climate may affect regional vegetation, hydrology, insects, and fire regimes, likely influencing the abundance, range, and elevational distribution of the plants and animals consumed by GYE grizzly bears. Determining the dietary breadth of grizzly bears is important to document future changes in food resources and how those changes may affect the nutritional ecology of grizzlies. However, no synthesis exists of all foods consumed by grizzly bears in the GYE. We conducted a review of available literature and compiled a list of species consumed by grizzly bears in the GYE. We documented >266 species within 200 genera from 4 kingdoms, including 175 plant, 37 invertebrate, 34 mammal, 7 fungi, 7 bird, 4 fish, 1 amphibian, and 1 algae species as well as 1 soil type consumed by grizzly bears. The average energy values of the ungulates (6.8 kcal/g), trout (Oncorhynchus spp., 6.1 kcal/g), and small mammals (4.5 kcal/g) eaten by grizzlies were higher than those of the plants (3.0 kcal/g) and invertebrates (2.7 kcal/g) they consumed. The most frequently detected diet items were graminoids, ants (Formicidae), whitebark pine seeds (Pinus albicaulis), clover (Trifolium spp.), and dandelion (Taraxacum spp.). The most consistently used foods on a temporal basis were graminoids, ants, whitebark pine seeds, clover, elk (Cervus elaphus), thistle (Cirsium spp.), and horsetail (Equisetum spp.). Historically, garbage was a significant diet item for grizzlies until refuse dumps were closed. Use of forbs increased after garbage was no longer readily available. The list of foods we compiled will help managers of grizzly bears and their habitat document future changes in grizzly bear food habits and how bears respond to changing food resources.

Idaho, Montana, Wyoming

Capture-recapture of white-tailed deer using DNA from fecal pellet-groups

Traditional methods for estimating white-tailed deer population size and density are affected by behavioral biases, poor detection in densely forested areas, and invalid techniques for estimating effective trapping area. We evaluated a noninvasive method of capture—recapture for white-tailed deer (Odocoileus virginianus) density estimation using DNA extracted from fecal pellets as an individual marker and for gender determination, coupled with a spatial detection function to estimate density (spatially explicit capture—recapture, SECR). We collected pellet groups from 11 to 22 January 2010 at randomly selected sites within a 1-km2 area located on Arnold Air Force Base in Coffee and Franklin counties, Tennessee. We searched 703 10-m radius plots and collected 352 pellet-group samples from 197 plots over five two-day sampling intervals. Using only the freshest pellets we recorded 140 captures of 33 different animals (15M:18F). Male and female densities were 1.9 (SE = 0.8) and 3.8 (SE = 1.3) deer km-2, or a total density of 5.8 deer km-2 (14.9 deer mile-2). Population size was 20.8 (SE = 7.6) over a 360-ha area, and sex ratio was 1.0 M: 2.0 F (SE = 0.71). We found DNA sampling from pellet groups improved deer abundance, density and sex ratio estimates in contiguous landscapes which could be used to track responses to harvest or other management actions.

Tennessee

Use of isotopic sulfur to determine whitebark pine consumption by Yellowstone bears: a reassessment

Use of naturally occurring stable isotopes to estimate assimilated diet of bears is one of the single greatest breakthroughs in nutritional ecology during the past 20 years. Previous research in the Greater Yellowstone Ecosystem (GYE), USA, established a positive relationship between the stable isotope of sulfur (δ 34 S) and consumption of whitebark pine (Pinus albicaulis) seeds. That work combined a limited sample of hair, blood clots, and serum. Here we use a much larger sample to reassess those findings. We contrasted δ 34 S values in spring hair and serum with abundance of seeds of whitebark pine in samples collected from grizzly (Ursus arctos) and American black bears (U. americanus) in the GYE during 2000–2010. Although we found a positive relationship between δ 34 S values in spring hair and pine seed abundance for grizzly bears, the coefficients of determination were small ( R 2  ≤ 0.097); we failed to find a similar relationship with black bears. Values of δ 34 S in spring hair were larger in black bears and δ 34 S values in serum of grizzly bears were lowest in September and October, a time when we expect δ 34 S to peak if whitebark pine seeds were the sole source of high δ 34 S. The relationship between δ 34 S in bear tissue and the consumption of whitebark pine seeds, as originally reported, may not be as clean a method as proposed. Data we present here suggest other foods have high values of δ 34 S, and there is spatial heterogeneity affecting the δ 34 S values in whitebark pine, which must be addressed.

Yellowstone National Park

Body and diet composition of sympatric black and grizzly bears in the Greater Yellowstone Ecosystem

The Greater Yellowstone Ecosystem (GYE) has experienced changes in the distribution and availability of grizzly bear (Ursus arctos) food resources in recent decades. The decline of ungulates, fish, and whitebark pine seeds (Pinus albicaulis) has prompted questions regarding their ability to adapt. We examined body composition and diet of grizzly bears using bioelectrical impedance and stable isotopes to determine if 1) we can detect a change in diet quality associated with the decline in either ungulates or whitebark pine, and 2) the combined decline in ungulates, fish, and pine seeds resulted in a change in grizzly bear carrying capacity in the GYE. We contrasted body fat and mass in grizzly bears with a potential competitor, the American black bear (Ursus americanus), to address these questions. Grizzly bears assimilated more meat into their diet and were in better body condition than black bears throughout the study period, indicating the decline in ungulate resources did not affect grizzly bears more than black bears. We also found no difference in autumn fat levels in grizzly bears in years of good or poor pine seed production, and stable isotope analyses revealed this was primarily a function of switching to meat resources during poor seed-producing years. This dietary plasticity was consistent over the course of our study. We did not detect an overall downward trend in either body mass or the fraction of meat assimilated into the diet by grizzly bears over the past decade, but we did detect a downward trend in percent body fat in adult female grizzly bears after 2006. Whether this decline is an artifact of small sample size or due to the population reaching the ecological carrying capacity of the Yellowstone ecosystem warrants further investigation.

Idaho, Montana, Wyoming

Effects of sampling conditions on DNA-based estimates of American black bear abundance

DNA-based capture-mark-recapture techniques are commonly used to estimate American black bear ( Ursus americanus ) population abundance (N). Although the technique is well established, many questions remain regarding study design. In particular, relationships among N, capture probability of heterogeneity mixtures A and B (p A and p B , respectively, or p , collectively), the proportion of each mixture (π), number of capture occasions (k), and probability of obtaining reliable estimates of N are not fully understood. We investigated these relationships using 1) an empirical dataset of DNA samples for which true N was unknown and 2) simulated datasets with known properties that represented a broader array of sampling conditions. For the empirical data analysis, we used the full closed population with heterogeneity data type in Program MARK to estimate N for a black bear population in Great Smoky Mountains National Park, Tennessee. We systematically reduced the number of those samples used in the analysis to evaluate the effect that changes in capture probabilities may have on parameter estimates. Model-averaged N for females and males were 161 (95% CI = 114–272) and 100 (95% CI = 74–167), respectively (pooled N = 261, 95% CI = 192–419), and the average weekly p was 0.09 for females and 0.12 for males. When we reduced the number of samples of the empirical data, support for heterogeneity models decreased. For the simulation analysis, we generated capture data with individual heterogeneity covering a range of sampling conditions commonly encountered in DNA-based capture-mark-recapture studies and examined the relationships between those conditions and accuracy (i.e., probability of obtaining an estimated N that is within 20% of true N), coverage (i.e., probability that 95% confidence interval includes true N), and precision (i.e., probability of obtaining a coefficient of variation ≤20%) of estimates using logistic regression. The capture probability for the larger of 2 mixture proportions of the population (i.e., p A or p B , depending on the value of π) was most important for predicting accuracy and precision, whereas capture probabilities of both mixture proportions (p A and p B ) were important to explain variation in coverage. Based on sampling conditions similar to parameter estimates from the empirical dataset (p A  = 0.30, p B  = 0.05, N = 250, π = 0.15, and k = 10), predicted accuracy and precision were low (60% and 53%, respectively), whereas coverage was high (94%). Increasing p B , the capture probability for the predominate but most difficult to capture proportion of the population, was most effective to improve accuracy under those conditions. However, manipulation of other parameters may be more effective under different conditions. In general, the probabilities of obtaining accurate and precise estimates were best when p ≥ 0.2. Our regression models can be used by managers to evaluate specific sampling scenarios and guide development of sampling frameworks or to assess reliability of DNA-based capture-mark-recapture studies.

Tennessee

Response of Yellowstone grizzly bears to changes in food resources: A synthesis. Final report to the Interagency Grizzly Bear Committee and Yellowstone Ecosystem Subcommittee

The Yellowstone grizzly bear ( Ursus arctos ) was listed as a threatened species in 1975 (Federal Register 40 FR:31734-31736). Since listing, recovery efforts have focused on increasing population size, improving habitat security, managing bear mortalities, and reducing bear-human conflicts. The Interagency Grizzly Bear Committee (IGBC; partnership of federal and state agencies responsible for grizzly bear recovery in the lower 48 states) and its Yellowstone Ecosystem Subcommitte (YES; federal, state, county, and tribal partners charged with recovery of grizzly bears in the Greater Yelowston Ecosystem [GYE]) tasked the Interagency Grizzly Bear Study Team to provide information and further research relevant to three concerns arising from the 9th Circuit Court of Appeals November 2011 decision: 1) the ability of grizzly bears as omnivores to find alternative foods to whitebark pine seeds; 2) literature to support their conclusions; and 3) the non-intuitive biological reality that impacts can occur to individuals without causing the overall population to decline. Specifically, the IGBC and YES requested a comprehensive synthesis of the current state of knowledge regarding whitebark pinbe decline and individual and population-level responses of grizzly bears to changing food resources in the GYE. This research was particularly relevant to grizzly bear conservation given changes in the population trajectory observed during the last decade.

Idaho, Montana, Wyoming

Short-term impacts of a 4-lane highway on black bears in eastern North Carolina

Among numerous anthropogenic impacts on terrestrial landscapes, expanding transportation networks represent one of the primary challenges to wildlife conservation worldwide. Larger mammals may be particularly vulnerable because of typically low densities, low reproductive rates, and extensive movements. Although numerous studies have been conducted to document impacts of road networks on wildlife, inference has been limited because of experimental design limitations. During the last decade, the North Carolina Department of Transportation (NCDOT) rerouted and upgraded sections of United States Highway 64 between Raleigh and the Outer Banks to a 4-lane, divided highway. A new route was selected for a 24.1-km section in Washington County. The new section of highway included 3 wildlife underpasses with adjacent wildlife fencing to mitigate the effects of the highway on wildlife, particularly American black bears (Ursus americanus). We assessed the short-term impacts of the new highway on spatial ecology, population size, survival, occupancy, and gene flow of black bears. We tested our research hypotheses using a before-after control-impact (BACI) study design. We collected data during 2000–2001 (preconstruction phase) and 2006–2007 (postconstruction phase) in the highway project area and a nearby control area (each approx. 11,000 ha), resulting in 4 groups of data (i.e., pre- or postconstruction study phase, treatment or control area). We captured and radiocollared 57 bears and collected 5,775 hourly locations and 4,998 daily locations. Using mixed-model analysis of variance and logistic regression, we detected no differences in home ranges, movement characteristics, proximity to the highway alignment, or habitat use between the 2 study phases, although minimum detectable effect sizes were large for several tests. However, after completion of the new highway, bears on the treatment area became less inactive in morning, when highway traffic was low, compared with bears on the control area (F 1, 43 = 6.05, P = 0.018). We used DNA from hair samples to determine if population size and site occupancy decreased following highway construction. For each study phase, we collected black bear hair from 70 hair snares on each study area during 7 weekly sampling periods and generated genotypes using 10 microsatellite loci. We used the multilocus genotypes to obtain capture histories for 226 different bears and used capture-mark-recapture models to estimate population size. Model-averaged estimates of population size decreased on the treatment area from 87.7 bears before construction to 31.6 bears after construction (64% reduction) and on the control area from 163.6 bears to 108.2 bears (34% reduction). Permutation procedures indicated this reduction was proportionally greater for the treatment area (P = 0.086). We also applied a spatially explicit capture-recapture technique to test our research hypothesis. The model with the most support indicated a greater change in density on the treatment area (69% reduction) compared with the control area (24% reduction). We did not observe a treatment effect based on survival of radiocollared bears. We used bear visits to hair snares as detections in multi-season occupancy models and found that occupancy decreased more on the treatment area (preconstruction: Ψ = 0.84; postconstruction: Ψ = 0.44; 48% decline) than the control area (preconstruction: Ψ = 0.91; postconstruction: Ψ = 0.81; 11% decline), primarily as a function of a greater probability of site extinctions (ε) on the treatment area (ε = 0.57) than the control area (ε = 0.17). Finally, individual- and population-based analyses of contemporary gene flow did not indicate the highway was a barrier to movements. Black bear use of the 3 wildlife underpasses was infrequent (17 verified crossings based on remote cameras, track surveys, and telemetry). Only 4 of 8 bears with home ranges near the highway were documented crossing the highway (n = 36 crossings), of which 2 were killed in vehicle collisions. Six additional bears were killed in vehicle collisions from May 2007 to November 2008, after we completed field work. Harvest data indicated that hunting mortality alone could explain the population decline on the control area. On the treatment area, however, hunting mortality only accounted for an approximately 40% population decline; the additional 30% decline we observed likely was caused by other mortality. We speculate vehicle collisions were primarily responsible. We conclude that impacts of the new highway on resident black bears occurred at the population level, rather than the individual or genetic level, but that the impact was smaller than harvest mortality. Increased activity by remaining bears when traffic volumes were low indicated behavioral plasticity. Bear use of the underpasses seemed sufficient to maintain gene flow between areas north and south of the new highway. Effectiveness of wildlife underpasses to reduce mortality of black bears may be enhanced if mitigation includes continuous fencing between crossing structures. For small, isolated populations of threatened or endangered large mammals, the potential demographic impacts of highways are an essential consideration in the transportation planning process. Control of mortality factors and maintaining demographic connectivity are particularly important.

California

Assessing sloth bears as surrogates for carnivore conservation in Sri Lanka

Bears are large, charismatic mammals whose presence often garners conservation attention. Because healthy bear populations typically require large, contiguous areas of habitat, land conservation actions often are assumed to benefit co-occurring species, including other mammalian carnivores. However, we are not aware of an empirical test of this assumption. We used remote camera data from 2 national parks in Sri Lanka to test the hypothesis that the frequency of detection of sloth bears (Melursus ursinus) is associated with greater richness of carnivore species. We focused on mammalian carnivores because they play a pivotal role in the stability of ecological communities and are among Sri Lanka's most endangered species. Seven of Sri Lanka's carnivores are listed as endangered, vulnerable, or near threatened, and little empirical information exists on their status and distribution. During 2002–03, we placed camera traps at 152 sites to document carnivore species presence. We used Poisson regression to develop predictive models for 3 categories of dependent variables: species richness of (1) all carnivores, (2) carnivores considered at risk, and (3) carnivores of least conservation concern. For each category, we analyzed 8 a priori models based on combinations of sloth bear detections, sample year, and study area and used Akaike's information criterion (AIC c ) to test our research hypothesis. We detected sloth bears at 55 camera sites and detected 13 of Sri Lanka's 14 Carnivora species. Species richness of all carnivores showed positive associations with the number of sloth bear detections, regardless of study area. Sloth bear detections were also positively associated with species richness of carnivores at risk across both study years and study areas, but not with species richness of common carnivores. Sloth bears may serve as a valuable surrogate species whose habitat protection would contribute to conservation of other carnivores in Sri Lanka.

Ursus

Habitat assessment for giant pandas in the Qinling Mountain region of China

Because habitat loss and fragmentation threaten giant pandas (Ailuropoda melanoleuca), habitat protection and restoration are important conservation measures for this endangered species. However, distribution and value of potential habitat to giant pandas on a regional scale are not fully known. Therefore, we identified and ranked giant panda habitat in Foping Nature Reserve, Guanyinshan Nature Reserve, and adjacent areas in the Qinling Mountains of China. We used Mahalanobis distance and 11 digital habitat layers to develop a multivariate habitat signature associated with 247 surveyed giant panda locations, which we then applied to the study region. We identified approximately 128 km 2 of giant panda habitat in Foping Nature Reserve (43.6% of the reserve) and 49 km 2 in Guanyinshan Nature Reserve (33.6% of the reserve). We defined core habitat areas by incorporating a minimum patch-size criterion (5.5 km 2 ) based on home-range size. Percentage of core habitat area was higher in Foping Nature Reserve (41.8% of the reserve) than Guanyinshan Nature Reserve (26.3% of the reserve). Within the larger analysis region, Foping Nature Reserve contained 32.7% of all core habitat areas we identified, indicating regional importance of the reserve. We observed a negative relationship between distribution of core areas and presence of roads and small villages. Protection of giant panda habitat at lower elevations and improvement of habitat linkages among core habitat areas are important in a regional approach to giant panda conservation.

Qinling Mountains

Identifying suitable sites for Florida panther reintroduction

A major objective of the 1995 Florida Panther ( Puma concolor cory ) Recovery Plan is the establishment of 2 additional panther populations within the historic range. Our goal was to identify prospective sites for Florida panther reintroduction within the historic range based on quantitative landscape assessments. First, we delineated 86 panther home ranges using telemetry data collected from 1981 to 2001 in south Florida to develop a Mahalanobis distance (D 2 ) habitat model, using 4 anthropogenic variables and 3 landscape variables mapped at a 500-m resolution. From that analysis, we identified 9 potential reintroduction sites of sufficient size to support a panther population. We then developed a similar D 2 model at a higher spatial resolution to quantify the area of favorable panther habitat at each site. To address potential for the population to expand, we calculated the amount of favorable habitat adjacent to each prospective reintroduction site within a range of dispersal distances of female panthers. We then added those totals to the contiguous patches to estimate the total amount of effective panther habitat at each site. Finally, we developed an expert-assisted model to rank and incorporate potentially important habitat variables that were not appropriate for our empirical analysis (e.g., area of public lands, livestock density). Anthropogenic factors heavily influenced both the landscape and the expert-assisted models. Of the 9 areas we identified, the Okefenokee National Wildlife Refuge, Ozark National Forest, and Felsenthal National Wildlife Refuge regions had the highest combination of effective habitat area and expert opinion scores. Sensitivity analyses indicated that variability among key model parameters did not affect the high ranking of those sites. Those sites should be considered as starting points for the field evaluation of potential reintroduction sites.

Florida

Bait stations, hard mast, and black bear population growth in Great Smoky Mountains National Park

Bait-station surveys are used by wildlife managers as an index to American black bear ( Ursus americanus ) population abundance, but the relationship is not well established. Hard mast surveys are similarly used to assess annual black bear food availability which may affect mortality and natality rates. We used data collected in Great Smoky Mountains National Park (GSMNP) from 1989 to 2003 to determine whether changes in the bait-station index (ΔBSI) were associated with estimated rates of bear population growth (λ) and whether hard mast production was related to bear visitation to baits. We also evaluated whether hard mast production from previous years was related to λ. Estimates of λ were based on analysis of capture-recapture data with the Pradel temporal symmetry estimator. Using the Akaike's Information Criterion (AIC), our analysis revealed no direct relationship between ΔBSI and λ. A simulation analysis indicated that our data were adequate to detect a relationship had one existed. Model fit was marginally improved when we added total oak mast production of the previous year as an interaction term suggesting that the BSI was confounded with environmental variables. Consequently the utility of the bait-station survey as a population monitoring technique is questionable at the spatial and temporal scales we studied. Mast survey data, however, were valuable covariates of λ. Population growth for a given year was negatively related to oak mast production 4 and 5 years prior. That finding supported our hypothesis that mast failures can trigger reproductive synchrony, which may not be evident from the trapped sample until years later.

North Carolina, Tennessee

Predicting rare plant occurrence in Great Smoky Mountains National Park, USA

We investigated the applicability of biometric habitat modeling to rare plant inventory and conservation by developing and field testing a geographically explicit model for Cardamine clematitis Shuttleworth ex A. Gray (mountain bittercress), an endemic plant of the southern Blue Ridge Mountains, USA. For each of 187 confirmed coordinates for C. clematitis in Great Smoky Mountains National Park, 13 habitat variables were measured with a geographic information system. These data were used to calculate Mahalanobis distances for each 30-m x 30-m pixel within the study area; small values of Mahalanobis distance represented site conditions similar to those of known locations of C. clematitis , whereas larger distance values represented dissimilar conditions. Following model development, we tested model performance by sampling 120 randomly distributed plots for C. clematitis presence. Logistic regression showed that Mahalanobis distance values were strongly related to C. clematitis occurrence (P = 0.039). Overall, 75% of all known occurrences of C. clematitis had associated Mahalanobis distance values below 17.7, and 95% of all occurrences were below 33.8; the median Mahalanobis distance value for the study area as a whole was 40.0. A habitat suitability cutoff value was defined which identified roughly 23,640 ha (19.5% of the study area) as suitable habitat. Although the model successfully predicted species absence in test plots with high Mahalanobis distance values, many sites with low values did not contain C. clematitis . Only 16.2% of test plots below the habitat suitability cutoff contained C. clematitis . The absence of C. clematitis from sites with low Mahalanobis distance values (low specificity) is not necessarily indicative of a poor model; metapopulation processes (e.g., recolonizations, local extinctions) have been shown to play a major role in presence or absence of many plant species. That may be partially the case with our model as evidenced by a relationship between C. clematitis presence and habitat patch size.

North Carolina, Tennesse

Predicting red wolf release success in the southeastern United States

Although the red wolf ( Canis rufus ) was once found throughout the southeastern United States, indiscriminate killing and habitat destruction reduced its range to a small section of coastal Texas and Louisiana. Wolves trapped from 1973 to 1980 were taken to establish a captive breeding program that was used to repatriate 2 mainland and 3 island red wolf populations. We collected data from 320 red wolf releases in these areas and classified each as a success or failure based on survival and reproductive criteria, and whether recaptures were necessary to resolve conflicts with humans. We evaluated the relations between release success and conditions at the release sites, characteristics of released wolves, and release procedures. Although <44% of the variation in release success was explained, model performance based on jackknife tests indicated a 72-80% correct prediction rate for the 4 operational models we developed. The models indicated that success was associated with human influences on the landscape and the level of wolf habituation to humans prior to release. We applied the models to 31 prospective areas for wolf repatriation and calculated an index of release success for each area. Decision-makers can use these models to objectively rank prospective release areas and compare strengths and weaknesses of each.

Journal of Wildlife Management