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At least 505 records · Page 28Linked to original sources
USGS2011

Detection probability in aerial surveys of feral horses

Observation bias pervades data collected during aerial surveys of large animals, and although some sources can be mitigated with informed planning, others must be addressed using valid sampling techniques that carefully model detection probability. Nonetheless, aerial surveys are frequently employed to count large mammals without applying such methods to account for heterogeneity in visibility of animal groups on the landscape. This often leaves managers and interest groups at odds over decisions that are not adequately informed. I analyzed detection of feral horse (Equus caballus) groups by dual independent observers from 24 fixed-wing and 16 helicopter flights using mixed-effect logistic regression models to investigate potential sources of observation bias. I accounted for observer skill, population location, and aircraft type in the model structure and analyzed the effects of group size, sun effect (position related to observer), vegetation type, topography, cloud cover, percent snow cover, and observer fatigue on detection of horse groups. The most important model-averaged effects for both fixed-wing and helicopter surveys included group size (fixed-wing: odds ratio = 0.891, 95% CI = 0.850–0.935; helicopter: odds ratio = 0.640, 95% CI = 0.587–0.698) and sun effect (fixed-wing: odds ratio = 0.632, 95% CI = 0.350–1.141; helicopter: odds ratio = 0.194, 95% CI = 0.080–0.470). Observer fatigue was also an important effect in the best model for helicopter surveys, with detection probability declining after 3 hr of survey time (odds ratio = 0.278, 95% CI = 0.144–0.537). Biases arising from sun effect and observer fatigue can be mitigated by pre-flight survey design. Other sources of bias, such as those arising from group size, topography, and vegetation can only be addressed by employing valid sampling techniques such as double sampling, mark–resight (batch-marked animals), mark–recapture (uniquely marked and identifiable animals), sightability bias correction models, and line transect distance sampling; however, some of these techniques may still only partially correct for negative observation biases.

Journal of Wildlife Management↗
USGS2011

The importance of within-year repeated counts and the influence of scale on long-term monitoring of sage-grouse

Long‐term population monitoring is the cornerstone of animal conservation and management. The accuracy and precision of models developed using monitoring data can be influenced by the protocols guiding data collection. The greater sage‐grouse ( Centrocercus urophasianus ) is a species of concern that has been monitored over decades, primarily, by counting the number of males that attend lek (breeding) sites. These lek count data have been used to assess long‐term population trends and for multiple mechanistic studies. However, some studies have questioned the efficacy of lek counts to accurately identify population trends. In response, monitoring protocols were changed to have a goal of counting lek sites multiple times within a season. We assessed the influence of this change in monitoring protocols on model accuracy and precision applying generalized additive models to describe trends over time. We found that at large spatial scales including >50 leks, the absence of repeated counts within a year did not significantly alter population trend estimates or interpretation. Increasing sample size decreased the model confidence intervals. We developed a population trend model for Wyoming greater sage‐grouse from 1965 to 2008, identifying significant changes in the population indices and capturing the cyclic nature of this species. Most sage‐grouse declines in Wyoming occurred between 1965 and the 1990s and lek count numbers generally increased from the mid‐1990s to 2008. Our results validate the combination of monitoring data collected under different protocols in past and future studies—provided those studies are addressing large‐scale questions. We suggest that a larger sample of individual leks is preferable to multiple counts of a smaller sample of leks.

Wyoming↗
USGS2017

Greater sage-grouse population trends across Wyoming

The scale at which analyses are performed can have an effect on model results and often one scale does not accurately describe the ecological phenomena of interest (e.g., population trends) for wide-ranging species: yet, most ecological studies are performed at a single, arbitrary scale. To best determine local and regional trends for greater sage-grouse ( Centrocercus urophasianus ) in Wyoming, USA, we modeled density-independent and -dependent population growth across multiple spatial scales relevant to management and conservation (Core Areas [habitat encompassing approximately 83% of the sage-grouse population on ∼24% of surface area in Wyoming], local Working Groups [7 regional areas for which groups of local experts are tasked with implementing Wyoming's statewide sage-grouse conservation plan at the local level], Core Area status (Core Area vs. Non-Core Area) by Working Groups, and Core Areas by Working Groups). Our goal was to determine the influence of fine-scale population trends (Core Areas) on larger-scale populations (Working Group Areas). We modeled the natural log of change in population size ( peak M lek counts) by time to calculate the finite rate of population growth ( λ ) for each population of interest from 1993 to 2015. We found that in general when Core Area status (Core Area vs. Non-Core Area) was investigated by Working Group Area, the 2 populations trended similarly and agreed with the overall trend of the Working Group Area. However, at the finer scale where Core Areas were analyzed separately, Core Areas within the same Working Group Area often trended differently and a few large Core Areas could influence the overall Working Group Area trend and mask trends occurring in smaller Core Areas. Relatively close fine-scale populations of sage-grouse can trend differently, indicating that large-scale trends may not accurately depict what is occurring across the landscape (e.g., local effects of gas and oil fields may be masked by increasing larger populations).

Wyoming↗
USGS2006

Patch size and landscape effects on density and nesting success of grassland birds

Current management recommendations for grassland birds in North America emphasize providing large patches of grassland habitat within landscapes that have few forest or shrubland areas. These Bird Conservation Areas are being proposed under the assumption that large patches of habitat in treeless landscapes will maintain viable populations of grassland birds. This assumption requires that patch size and landscape features affect density and nesting success of grassland birds, and that these effects are consistent among years and regions and across focal species. However, these assumptions have not yet been validated for grassland birds, and the relative importance of local vegetation structure, patch size, and landscape composition on grassland bird populations is not well known. In addition, factors influencing grassland bird nesting success have been investigated mostly in small-scale and short-duration studies. To develop management guidelines for grassland birds, we tested the spatial and temporal repeatability of the influence of patch size and landscape composition on density and nesting success of 3 grassland passerines, after controlling for local-scale vegetation structure, climate, and—when analyzing nest success—bird density. We conducted our study during 4 years (1998–2001) in 44 study plots that were set up in 3 regions of the northern tallgrass prairie in Minnesota and North Dakota, USA. In these study plots we measured density and nesting success of clay-colored sparrows ( Spizella pallida ), Savannah sparrows ( Passerculus sandwichensis ), and bobolinks ( Dolichonyx oryzivorus ). Statistical models indicated that density was influenced by patch size, landscape, region, and local vegetation structure more so than by local vegetation structure alone. Both magnitude and direction of the response of density to patch size varied among regions, years, and species. In contrast, the direction of landscape effects was consistent among regions, years, and between Savannah sparrows and bobolinks. In each species, this landscape effect was independent of patch size. Nesting success was not clearly influenced by patch size or landscape composition, and none of the factors that influenced avian density also influenced nesting success in any of the 3 species. General statements on “optimal habitat” for grassland birds should therefore be viewed cautiously. Instead, long-term studies in different regions as well as a deeper understanding of the local system are needed to determine which factors are most important for grassland birds in a particular area.

Journal of Wildlife Management↗
USGS2025

Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications

Habitat features needed by wildlife can change in composition throughout the year, particularly in temperate ecosystems, leading to distinct seasonal spatial-use patterns. Studies of species-habitat associations therefore often focus on understanding relationships within discrete seasonal periods with common goals of prediction (e.g., habitat mapping) and inference (e.g., interpreting model coefficients). Across the range of the greater sage-grouse ( Centrocercus urophasianus ) of western North America, the increasing use of high-frequency tracking devices has led to a surge in habitat association studies covering multiple temporal periods and spatial extents. We reviewed the literature for seasonal habitat association studies corresponding to the second and third orders of selection (Johnson 1980). Our objectives were to summarize the methodological approaches used to estimate habitat associations to aid understanding in cross-study comparisons and identify common habitat features reported as selected or avoided within different seasonal periods. We reviewed 71 second- and third-order studies published from 2007–2023 that evaluated covariates collected in a geographic information system (GIS) and modeled probability of selection or intensity of use. The most common study design evaluated a single level of selection (third-order) and was multi-scale (i.e., covariates were measured at varying spatial grains). The most common model approach estimated habitat associations using resource selection functions (RSFs) fit with logistic regression. Studies mostly focused on the breeding periods and winter, but all seasons throughout the annual cycle were covered. There was clear support for selection of sagebrush and avoidance of trees and rugged terrain across seasons, and strong selection of mesic conditions in summer. However, habitat associations for most covariates were mixed, with proportionally equivalent selection and avoidance reported, even within the same seasons. Different factors hampered cross-study comparisons, including variation in study design, but additional contributors likely included important context-dependent habitat associations, such as functional responses to changing habitat availability. We suggest collaborative studies leveraging multiple datasets can help improve seasonal habitat inference by removing the effects of variable study designs.

Journal of Wildlife Management↗
USGS2000

Evaluating immunocontraception for managing suburban white-tailed deer in Irondequoit, New York

Immunocontraception is frequently proposed as an alternative to lethal removal of females for deer management. However, little information is available for evaluating the potential of applying immunocontraceptives to free-ranging populations. Our objectives were to estimate effort required to apply porcine zona pellucida (PZP) to individual deer and assess the utility of using immunocontraception to control growth of deer populations. The study was conducted in a 43-km2 suburban community with about 400 deer. Effort per deer was measured as time required to capture and mark deer, and then to apply booster immunocontraceptive treatments by remote injection. Estimates of numbers of females to treat to control population growth were based on the generalized sustained-yield (SY) model adapted for contraception of females. The SY curve was calibrated using data on deer abundance acquired from aerial population surveys and nutritional condition of females removed by a concurrent culling program. Effort was influenced by 4 factors: deer population density, approachability of individual deer, access to private and public land, and efficacy of the contraceptive treatment. Effort and deer density were inversely related. Cumulative effort for treatment increased exponentially because some deer were more difficult to approach than others. Potential of using immunocontraception at low deer population densities (<25% ecological carrying capacity) is limited by the interaction of the proportion of breeding-age females in the population and treatment efficacy, as well as encounter rates. Immunocontraception has the best potential for holding suburban deer populations between 30 and 70% of ecological carrying capacity, but is likely to be useful only in localized populations when the number of females to be treated is small (e.g., <200 deer).

New York↗
USGS1994

Seasonal and annual survival of emperor geese

Population levels of emperor geese ( Chen canagica ) in Alaska in 1993 were about half that estimated in the 1960s. Survival information is necessary for managers to decide how to best enhance recovery of this species to former levels. We calculated seasonal and annual estimates of emperor goose survival from resightings of neck-collared birds. Geese were neck collared in 1988-90 on their breeding grounds in the Yukon-Kuskokwim Delta, Alaska, and resighted each spring and fall, 1988-92, at staging areas on the Alaska Peninsula. Adult monthly survival rates during overwinter periods (1 Oct-30 Apr) were not different (P = 0.281) among years ( Ŝ' = 0.940, SE = 0.009), whereas monthly rates of oversummer (1 May-30 Sep) survival showed annual variation (P = 0.048). However, we constrained oversummer survival to a single estimate of 0.980 (0.010). Monthly survival estimates for juveniles during their first overwinter period did not vary among years (P = 0.999) and was 0.710 (0.018). Subsequent monthly survival for juveniles was 0.943 (0.010), similar to that for adults. We developed an adjustment procedure to account for philopatric behavior of geese and this enabled us to use data for postbanding (1 Aug-30 Sep) periods. Survival estimates were low compared with those for other goose species, particularly for juveniles. We addressed collar loss and heterogeneity in resighting probabilities and felt their contribution to potential model bias was insignificant. Annual survival among adults (Ŝ' = 0.631, SE = 0.023) was not different (P = 0.709) from that observed during 1982-85 (Petersen 1992). The similarity in survival rates in these studies suggests that harvest regimes did not differ between the 2 periods. This suggests that continued subsistence harvest has contributed to persistent low population levels in emperor geese.

Alaska↗
USGS2022

Integrating distance sampling survey data with population indices to separate trends in abundance and temporary immigration

Managers rely on accurate estimators of wildlife abundance and trends for management decisions. Despite the focus of contemporary wildlife science on developing methods to improve inference from wildlife surveys, legacy datasets often rely on index counts that lack information about the detection process. Data integration can be a useful tool for combining index counts with data collected under more rigorous designs (i.e., designs that account for the detection process), but care is required when datasets represent different population processes or are mismatched in space and time. This can be particularly problematic in cases where animals aggregate in response to a spatially or temporally limited resource because individuals may temporarily immigrate from outside the study area and be included in the abundance index. Abundance indices based on brown bear ( Ursus arctos ) feeding aggregations within coastal meadows in early summer in Lake Clark National Park and Preserve, Alaska, USA, are one such example. These indices reflect the target population (brown bears residing within the park) and temporary immigrants (i.e., bears drawn from outside the park boundary). To properly account for the effects of temporary immigration, we integrated the index data with abundance data collected via park-wide distance sampling surveys, the latter of which properly addressed the detection process. By assuming that the distance data provide inference on abundance and the index counts represent some combination of abundance and temporary immigration processes, we were able to decompose the relative contribution of each to overall trend. We estimated that the density of brown bears within our study area was 38–54 adults/1,000 km 2 during 2003–2019 and that abundance increased at a rate of approximately 1.4%/year. The contribution of temporary immigrants to overall trend in the index was low, so we created 3 hypothetical scenarios to more fully demonstrate how the integrated approach could be useful in situations where the composite trend in meadow counts may obscure trends in abundance (e.g., opposing trends in abundance and temporary immigration). Our work represents a conceptual advance supporting the integration of legacy index data with more rigorous data streams and is broadly applicable in cases where trends in index values may represent a mixture of population processes.

Alaska↗
USGS2005

Population genetics of Gunnison sage-grouse: Implications for management

The newly described Gunnison sage-grouse ( Centrocercus minimus ) is a species of concern for management because of marked declines in distribution and abundance due to the loss and fragmentation of sagebrush habitat. This has caused remaining populations to be unusually small and isolated. We utilized mitochondrial DNA sequence data and data from 8 nuclear microsatellites to assess the extent of population subdivision among Gunnison sage-grouse populations in southwestern Colorado and southeastern Utah, USA. We found a high degree of population structure and low amounts of gene flow among all pairs of populations except the geographically adjacent Gunnison and Curecanti populations. Population structure for Gunnison sage-grouse was significantly higher than has been reported for greater sage-grouse ( C. urophasianus ). Further, we documented low levels of genetic diversity in some populations (particularly Dove Creek/Monticello and Piñon Mesa with an average of only 3.00 and 2.13 alleles per locus respectively) indicating that translocations from larger, more genetically diverse populations may be warranted. Bayesian analysis identified 3 potential migrants (involving San Miguel, Dove Creek/Monticello, Crawford, and Curecanti). Further, this analysis showed that 4 individuals from Cerro/Cimarron were more closely related to birds from San Miguel than to its geographically closer neighbors Gunnison and Curecanti. This suggests the Cerro/Cimarron area may act as a stepping stone for gene flow between San Miguel and Gunnison and that habitat restoration and protection in areas between these 2 basins should be a priority in an attempt to facilitate natural movement among these populations. Conservation plans should include monitoring and maintaining genetic diversity, preventing future habitat loss and fragmentation, enhancing existing habitat, and restoring converted sagebrush communities.

Journal of Wildlife Management↗
USGS2010

A sightability model for mountain goats

Unbiased estimates of mountain goat (Oreamnos americanus) populations are key to meeting diverse harvest management and conservation objectives. We developed logistic regression models of factors influencing sightability of mountain goat groups during helicopter surveys throughout the Cascades and Olympic Ranges in western Washington during summers, 20042007. We conducted 205 trials of the ability of aerial survey crews to detect groups of mountain goats whose presence was known based on simultaneous direct observation from the ground (n 84), Global Positioning System (GPS) telemetry (n 115), or both (n 6). Aerial survey crews detected 77 and 79 of all groups known to be present based on ground observers and GPS collars, respectively. The best models indicated that sightability of mountain goat groups was a function of the number of mountain goats in a group, presence of terrain obstruction, and extent of overstory vegetation. Aerial counts of mountain goats within groups did not differ greatly from known group sizes, indicating that under-counting bias within detected groups of mountain goats was small. We applied HorvitzThompson-like sightability adjustments to 1,139 groups of mountain goats observed in the Cascade and Olympic ranges, Washington, USA, from 2004 to 2007. Estimated mean sightability of individual animals was 85 but ranged 0.750.91 in areas with low and high sightability, respectively. Simulations of mountain goat surveys indicated that precision of population estimates adjusted for sightability biases increased with population size and number of replicate surveys, providing general guidance for the design of future surveys. Because survey conditions, group sizes, and habitat occupied by goats vary among surveys, we recommend using sightability correction methods to decrease bias in population estimates from aerial surveys of mountain goats.

Journal of Wildlife Management↗
USGS2020

Black bear movement and food conditioning in an exurban landscape

Conflicts between humans and wildlife have become increasingly important challenges for resource managers along the urban‐wildland interface. Food conditioning (i.e., reliance by an animal on anthropogenic foods) of American black bears (Ursus americanus ) is related to conflict behavior (i.e., being bold or aggressive toward humans, consuming human food or garbage, causing property damage) and often occurs in communities adjacent to Great Smoky Mountains National Park (GRSM or Park), USA. The goal of our study was to evaluate black bear space use in GRSM and in exurban areas on surrounding private lands and to identify factors associated with food conditioning and conflict behavior. We radio‐collared 53 bears (29 males, 24 females) from 2015 to 2017 to compare space use characteristics and used carbon isotopic signatures (δ13C) from bear hair to assess food conditioning. We then performed an integrated step selection function (iSSF) analysis to characterize and compare movement and resource use as related to food conditioning. Based on the stable isotope analyses, 24 bears were classified as food conditioned (FC; 16 males and 8 females) and 37 were not food conditioned (NFC; 14 males and 23 females). Annual 95% kernel density estimate (KDE) home ranges and 50% KDE core area estimates of female and male bears did not differ by level of food conditioning (i.e., mean δ13C), but 95% and 50% home ranges of FC females were smaller than NFC females when data from 2015, a year of food scarcity and abnormally large home ranges, were excluded. The mean proportion of exurban development (e.g., roads, buildings, openings) within 95% KDE and 50% KDE home ranges of females increased with mean δ13C (i.e., greater food conditioning). The iSSF models indicated that FC bears were more likely to use forest openings associated with higher levels of development than NFC bears. We used those models to demonstrate how landscape modifications can reduce bear use of exurban areas, particularly for NFC bears. Our stable isotope, movement, and resource use data indicate that conflict behaviors displayed by many bears within GRSM were learned in areas outside Park boundaries. © 2020 The Wildlife Society.

Tennessee, North Carolina↗
USGS2015

Camera traps and mark-resight models: The value of ancillary data for evaluating assumptions

Unbiased estimators of abundance and density are fundamental to the study of animal ecology and critical for making sound management decisions. Capture–recapture models are generally considered the most robust approach for estimating these parameters but rely on a number of assumptions that are often violated but rarely validated. Mark-resight models, a form of capture–recapture, are well suited for use with noninvasive sampling methods and allow for a number of assumptions to be relaxed. We used ancillary data from continuous video and radio telemetry to evaluate the assumptions of mark-resight models for abundance estimation on a barrier island raccoon (Procyon lotor) population using camera traps. Our island study site was geographically closed, allowing us to estimate real survival and in situ recruitment in addition to population size. We found several sources of bias due to heterogeneity of capture probabilities in our study, including camera placement, animal movement, island physiography, and animal behavior. Almost all sources of heterogeneity could be accounted for using the sophisticated mark-resight models developed by McClintock et al. (2009b) and this model generated estimates similar to a spatially explicit mark-resight model previously developed for this population during our study. Spatially explicit capture–recapture models have become an important tool in ecology and confer a number of advantages; however, non-spatial models that account for inherent individual heterogeneity may perform nearly as well, especially where immigration and emigration are limited. Non-spatial models are computationally less demanding, do not make implicit assumptions related to the isotropy of home ranges, and can provide insights with respect to the biological traits of the local population.

North Carolina↗
USGS2019

Annual winter site fidelity of Barrow's goldeneyes in the Pacific

Coastal regions on the Pacific north coast of North America provide important wintering habitat for many species of sea ducks. Although winter range and habitat preferences are well described for most species, fidelity to coastal wintering sites is generally undocumented. Fidelity is an important factor necessary for understanding interactions with coastal developments and activities and corresponding management strategies. We used data from Barrow's goldeneyes (Bucephala islandica), a sea duck that winters predominantly in nearshore habitats along the Pacific north coast, to investigate inter‐annual fidelity to, and intra‐annual fidelity within, coastal wintering sites. Between 2006 and 2015, we marked goldeneyes on breeding, molting, and wintering sites with satellite transmitters. We retained 4,931 locations in coastal habitats from 221 goldeneyes across 4 coastal regions for our analyses. These birds demonstrated high inter‐annual fidelity to coastal wintering sites; 75% of selected wintering sites were within 29 km of sites used the previous winter. Inter‐annual fidelity to wintering sites was similar between sex and age classes but differed by coastal region. Goldeneyes from southcentral Alaska, USA, expressed greater inter‐annual fidelity relative to birds from northern or southern British Columbia, Canada, and southeast Alaska. Goldeneyes also expressed high intra‐annual fidelity within wintering sites, with 75% of individuals averaging within‐season movements of ≤9 km. Intra‐annual fidelity was lesser for female than male goldeneyes but did not differ between hatch‐year and after‐hatch‐year birds. We found regional variation in intra‐annual fidelity, with goldeneyes from southcentral Alaska expressing greater intra‐annual fidelity compared to birds from other regions. High inter‐ and intra‐annual winter site fidelity by Barrow's goldeneyes suggests that, at a population level, habitat use is predictable and can be used to inform risk assessment or to evaluate factors affecting habitat choice. Also, low dispersal among wintering sites suggests that recovery from population perturbations, whether caused by natural or anthropogenic events, will be protracted.

Pacific north coast↗
USGS1994

Waterbird use of saltmarsh ponds created for open marsh water management

Open Marsh Water Management (OMWM) as an alternative to pesticides for mosquito control in saltmarshes along the Atlantic Coast has created debate among biologists. We designed an experiment to determine waterbird (American black duck [ Anas rubripe ]) and other waterfowl, wading birds, shorebirds, gulls, and terns) use (during daylight) of ponds created for mosquito control compared with use of pre-existing water bodies (i.e., natural tidal ponds, creeks, old ditches) and refuge impoundments. We also evaluated the influence of pond size and depth on waterbird use of wetlands. We documented bird use of different habitats for 1 year. The highest densities of waterfowl, in autumn, occurred in 0.030.06ha ponds ( P < 0.05) versus ponds either <0.02 ha or > 0.08 ha; highest shorebird densities occurred in summer in ponds > 0.10 ha ( P < 0.05). Pond depth affected shorebird and other waterfowl use in some seasons. Comparisons of mean number of birds using created (OMWM) ponds with mean number of birds using other water bodies revealed that most species showed no pattern (P <0.05) of disproportionate use versus availability. At high tidal levels, most species groups used OMWM ponds in the marsh more often ( P < 0.05) than other water bodies. Black ducks and other waterfowl used nearby refuge impoundments in higher densities than they did OMWM ponds, for nesting and during autumn-winter (all P s < 0.05). Creating small (> 0.1 ha) ponds for mosquito control does not enhance waterbird habitat, at least not where large impoundments are in close proximity. We recommend that in areas where OMWM practices seem appropriate, fewer large (gt 0.10 ha) ponds be constructed with shallow (< 15 cm) basins and sloping sides.

New Jersey↗
USGS2024

No evidence hunting bait increases American black bear population growth in Maine, USA

American black bear ( Ursus americanus ) populations are increasing throughout much of North America. Use of multiple harvest methods, including hunting over bait, is intended to increase harvest success rates to meet harvest and population management objectives. However, black bear population growth can be influenced by food availability, and some speculate the use of bait may inadvertently increase bear abundance through food resource supplementation. We collected hair from black bears captured from 2005–2019 and a selection of potential food items, including those used as bait from 3 study areas in Maine, USA, with different levels of human influence. We used stable isotope analysis of the black bear hair and food item samples to evaluate the contribution of different identified food groups to the diet of individual bears. We found no evidence that greater contribution of human food resources, including bait, increased the number of cubs per litter for reproductive females or that human foods comprised a greater part of the diet in years when natural food resources were less abundant. Approximately 69% of black bear harvest occurred over bait. We found the probability of reproductive-age females to be harvested increased with average representation of human foods with high carbon enrichment (including bait) in their diet, but the relationship was weak, likely because of sampling constraints. Additionally, the probability of being harvested was greater in years when natural food resources were scarce. We conclude that bait is not available on the landscape in large enough amounts or for a sufficient amount of time in Maine to substantially influence female reproduction. Our results indicate hunting over bait is an effective tool in a state that is attempting to maintain a stable bear population via harvest, and dispels conjecture that hunting over bait may increase cub production and offset the intention of harvest.

Maine↗
USGS1995

Age-class separation of blue-winged ducks

Accurate determination of age is of fundamental importance to population and life history studies of waterfowl and their management. Therefore, we developed quantitative methods that separate adult and immature blue-winged teal ( Anas discors ), cinnamon teal ( A. cyanoptera ), and northern shovelers ( A. clypeata ) during spring and summer. To assess suitability of discriminant models using 9 remigial measurements, we compared model performance (% agreement between predicted age and age assigned to birds on the basis of definitive cloacal or rectral feather characteristics) in different flyways (Mississippi and Pacific) and between years (1990-91 and 1991-92). We also applied age-classification models to wings obtained from U.S. Fish and Wildlife Service harvest surveys in the Mississippi and Central-Pacific flyways (wing-bees) for which age had been determined using qualitative characteristics (i.e., remigial markings, shape, or wear). Except for male northern shovelers, models correctly aged lt 90% (range 70-86%) of blue-winged ducks. Model performance varied among species and differed between sexes and years. Proportions of individuals that were correctly aged were greater for males (range 63-86%) than females (range 39-69%). Models for northern shovelers performed better in flyway comparisons within year (1991-92, La. model applied to Calif. birds, and Calif. model applied to La. birds: 90 and 94% for M, and 89 and 76% for F, respectively) than in annual comparisons within the Mississippi Flyway (1991-92 model applied to 1990-91 data: 79% for M, 50% for F). Exclusion of measurements that varied by flyway or year did not improve model performance. Quantitative methods appear to be of limited value for age separation of female blue-winged ducks. Close agreement between predicted age and age assigned to wings from the wing-bees suggests that qualitative and quantitative methods may be equally accurate for age separation of male blue-winged ducks. We interpret annual and flyway differences in remigial measurements and reduced performance of age classification models as evidence of high variability in size of blue-winged ducks' remiges. Variability in remigial size of these and other small-bodied waterfowl may be related to nutrition during molt.

Louisiana↗
USGS2010

Evaluating abundance estimate precision and the assumptions of a count-based index for small mammals

Conservation and management of small mammals requires reliable knowledge of population size. We investigated precision of markrecapture and removal abundance estimates generated from live-trapping and snap-trapping data collected at sites on Guam (n 7), Rota (n 4), Saipan (n 5), and Tinian (n 3), in the Mariana Islands. We also evaluated a common index, captures per unit effort (CPUE), as a predictor of abundance. In addition, we evaluated cost and time associated with implementing live-trapping and snap-trapping and compared species-specific capture rates of selected live- and snap-traps. For all species, markrecapture estimates were consistently more precise than removal estimates based on coefficients of variation and 95 confidence intervals. The predictive utility of CPUE was poor but improved with increasing sampling duration. Nonetheless, modeling of sampling data revealed that underlying assumptions critical to application of an index of abundance, such as constant capture probability across space, time, and individuals, were not met. Although snap-trapping was cheaper and faster than live-trapping, the time difference was negligible when site preparation time was considered. Rattus diardii spp. captures were greatest in Haguruma live-traps (Standard Trading Co., Honolulu, HI) and Victor snap-traps (Woodstream Corporation, Lititz, PA), whereas Suncus murinus and Mus musculus captures were greatest in Sherman live-traps (H. B. Sherman Traps, Inc., Tallahassee, FL) and Museum Special snap-traps (Woodstream Corporation). Although snap-trapping and CPUE may have utility after validation against more rigorous methods, validation should occur across the full range of study conditions. Resources required for this level of validation would likely be better allocated towards implementing rigorous and robust methods.

Journal of Wildlife Management↗
USGS2011

Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach

Gunnison sage-grouse (Centrocercus minimus) is a species of special concern and is currently considered a candidate species under Endangered Species Act. Careful management is therefore required to ensure that suitable habitat is maintained, particularly because much of the species' current distribution is faced with exurban development pressures. We assessed hierarchical nest site selection patterns of Gunnison sage-grouse inhabiting the western portion of the Gunnison Basin, Colorado, USA, at multiple spatial scales, using logistic regression-based resource selection functions. Models were selected using Akaike Information Criterion corrected for small sample sizes (AIC c ) and predictive surfaces were generated using model averaged relative probabilities. Landscape-scale factors that had the most influence on nest site selection included the proportion of sagebrush cover >5%, mean productivity, and density of 2 wheel-drive roads. The landscape-scale predictive surface captured 97% of known Gunnison sage-grouse nests within the top 5 of 10 prediction bins, implicating 57% of the basin as crucial nesting habitat. Crucial habitat identified by the landscape model was used to define the extent for patch-scale modeling efforts. Patch-scale variables that had the greatest influence on nest site selection were the proportion of big sagebrush cover >10%, distance to residential development, distance to high volume paved roads, and mean productivity. This model accurately predicted independent nest locations. The unique hierarchical structure of our models more accurately captures the nested nature of habitat selection, and allowed for increased discrimination within larger landscapes of suitable habitat. We extrapolated the landscape-scale model to the entire Gunnison Basin because of conservation concerns for this species. We believe this predictive surface is a valuable tool which can be incorporated into land use and conservation planning as well the assessment of future land-use scenarios.

Colorado↗