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At least 1,225 records · Page 68Linked to original sources

USGS1998

Estimating relative abundance from count data

Much of the available information on large-scale patterns of animal abundance is based on count surveys. The data provided by such surveys are often influenced by nuisance factors affecting the numbers of animals counted, but unrelated to population size. Temporal and spatial patterns in nuisance factors may exist, causing simple summaries of counts to give a misleading view of patterns in population size. We develop models for count data that allows the incorporation of such factors, and describe methods for estimating spatial patterns of relative abundance from counts. We carry out spatial analyses of North American Breeding Bird Survey data, in which observer ability is a nuisance parameter nested within sites. In light of evidence that new observers tend to count more birds than the observers they replace, we model observer ability as a random effect with mean depending on observer initiation year.

Austrian Journal of Statistics↗

USGS1997

Effects of drought and prolonged winter on Townsend's ground squirrel demography in shrubsteppe habitats

During a mark–recapture study of Townsend's ground squirrels ( Spermophilus townsendii ) on 20 sites in the Snake River Birds of Prey National Conservation Area, Idaho, in 1991 through 1994, 4407 animals were marked in 17639 capture events. This study of differences in population dynamics of Townsend's ground squirrels among habitats spanned a drought near the extreme of the 130-yr record, followed by prolonged winter conditions. Townsend's ground squirrels have a short active season (≈4 mo) in which to reproduce and store fat for overwintering. Their food consists largely of succulent grasses and forbs in this dry shrubsteppe and grassland habitat. The drought in the latter half of the 1992 active season produced early drying of Sandberg's bluegrass ( Poa secunda ) and was associated with low adult and juvenile body masses prior to immergence into estivation/hibernation. The following prolonged winter was associated with late emergence of females in 1993. Early-season body masses of adults were low in 1993 relative to 1992, whereas percentage of body fat in males was relatively high. These weather patterns in spring 1992 and winter 1993 also resulted in reduced adult persistence through the ≈7-mo inactive period, especially for adult females, and near-zero persistence of >1200 juveniles. Consequently, densities of Townsend's ground squirrels across the 20 livetrap sites declined. The demographic effects of drought and prolonged winter lasted at least through the subsequent breeding season. Adult females that survived these weather extremes produced fewer emergent young per female than did adult females prior to the event. Prior to the drought/prolonged winter, yearling female body masses were higher than, or indistinguishable from, those of adults. Females produced in 1993 had lower body masses as yearlings than did adult females. Demographic response to the drought and prolonged winter varied with habitat; ground squirrels in sagebrush habitat showed less decline in persistence and density and produced more young per female during the next active season following the drought (1993) than did ground squirrels in grassland habitat, where densities had been significantly higher prior to the drought and prolonged winter. Studies involving habitat comparisons of animal demography should always be placed in the context of long-term weather patterns, because habitat quality rankings based on density, reproduction, and survival may differ with environmental conditions. Physiological effects of environmental “crunches” on consumers may persist beyond the period of influence on food resources, reducing reproductive success and growth rates of future offspring.

Idaho↗

USGS1997

Tests for senescent decline in annual survival probabilities of common pochards, Aythya ferina

Senescent decline in survival probabilities of animals is a topic about which much has been written but little is known. Here, we present formal tests of senescence hypotheses, using 1373 recaptures from 8877 duckling (age 0) and 504 yearling Common Pochards (Aythya ferina) banded at a Latvian study site, 1975-1992. The tests are based on capture-recapture models that explicitly incorporate sampling probabilities that, themselves, may exhibit timeand age-specific variation. The tests provided no evidence of senescent decline in survival probabilities for this species. Power of the most useful test was low for gradual declines in annual survival probability with age, but good for steeper declines. We recommend use of this type of capture-recapture modeling and analysis for other investigations of senescence in animal survival rates.

Ecology↗

USGS1998

Estimation of tiger densities in India using photographic captures and recaptures

The tiger ( Panthera tigris ) is an endangered, large felid whose demographic status is poorly known across its distributional range in Asia. Previously applied methods for estimating tiger abundance, using total counts based on tracks, have proved unreliable. Lack of reliable data on tiger densities not only has constrained our ability to understand the ecological factors shaping communities of large, solitary felids, but also has undermined the effective conservation of these animals. In this paper, we describe the use of a field method proposed by Karanth (1995), which combines camera-trap photography, to identify individual tigers, with theoretically well-founded capture–recapture models. We developed a sampling design for camera-trapping and used the approach to estimate tiger population size and density in four representative tiger habitats in different parts of India. The field method worked well and provided data suitable for analysis using closed capture–recapture models. The results suggest the potential for applying this methodology to rigorously estimate abundances, survival rates, and other population parameters for tigers and other low-density, secretive animal species in which individuals can be identified based on natural markings. Estimated probabilities of photo-capturing tigers present in the study sites ranged from 0.75 to 1.00. Estimated densities of tigers >1 yr old ranged from 4.1 ± 1.31 to 16.8 ± 2.96 tigers/100 km 2 (mean ± 1 se ). Simultaneously, we used line-transect sampling to determine that mean densities of principal tiger prey at these sites ranged from 56.1 to 63.8 ungulates/km 2 . Tiger densities appear to be positively associated with prey densities, except at one site influenced by tiger poaching. Our results generally support the prediction that relative abundances of large felid species may be governed primarily by the abundance and structure of their prey communities.

National Parks of Pench, Kanha, Kaziranga, and Nag↗

USGS2002

Demography of a population collapse: The Northern Idaho ground squirrel (Spermophilus brunneus brunneus)

We studied the demography of a population of Northern Idaho ground squirrels ( Spermophilus brunneus brunneus ) in Adams Co., Idaho. The population was completely censused yearly from 1987 to 1999, during which time it declined from 272 to 10 animals. The finite population growth rate, based on a Leslie matrix model of average life-history parameters, was only 0.72 (i.e., significantly <1.0). Growth rate was more sensitive to proportional changes in juvenile female survival than to any other single life-history parameter. Comparisons with self-sustaining populations of closely related ground squirrel species revealed that juvenile survival and breeding rates of yearling females were anomalously low. We believe that the ultimate cause of the population's collapse was inadequacy of food resources, particularly seeds, due to drying of the habitat and changes in plant species composition, likely the result of fire suppression and grazing. No 'rescue' by immigration occurred, probably because S. b. brunneus seldom disperse long distances and fire suppression has allowed conifers to encroach on inhabited meadows, shrinking them and closing dispersal routes. The proximate cause of the population's collapse was mortality of older breeding females, which reduced the mean age of breeders. Younger females had lower average pregnancy rates and litter sizes. To place our results in context we developed a new, general classification of anthropogenic population declines, based on whether they are caused by changes in the means of the life-history parameters (blatant disturbances), their variances (inappropriate variations), or the correlations among them (evolutionary traps). Many S. b. brunneus populations have disappeared in recent years, apparently due to blatant disturbances, especially loss of habitat and changes in food-plant composition, resulting in inadequate prehibernation nutrition and starvation overwinter. In addition, our study population may have been caught in an evolutionary trap, because the vegetational cues that could potentially enable the animals to adjust reproduction to the anticipated food supply no longer correlate with availability of fat-laden seeds.

Idaho↗

USGS2004

Modeling abundance effects in distance sampling

Distance-sampling methods are commonly used in studies of animal populations to estimate population density. A common objective of such studies is to evaluate the relationship between abundance or density and covariates that describe animal habitat or other environmental influences. However, little attention has been focused on methods of modeling abundance covariate effects in conventional distance-sampling models. In this paper we propose a distance-sampling model that accommodates covariate effects on abundance. The model is based on specification of the distance-sampling likelihood at the level of the sample unit in terms of local abundance (for each sampling unit). This model is augmented with a Poisson regression model for local abundance that is parameterized in terms of available covariates. Maximum-likelihood estimation of detection and density parameters is based on the integrated likelihood, wherein local abundance is removed from the likelihood by integration. We provide an example using avian point-transect data of Ovenbirds ( Seiurus aurocapillus ) collected using a distance-sampling protocol and two measures of habitat structure (understory cover and basal area of overstory trees). The model yields a sensible description (positive effect of understory cover, negative effect on basal area) of the relationship between habitat and Ovenbird density that can be used to evaluate the effects of habitat management on Ovenbird populations.

Maryland↗

USGS2005

Quantile regression reveals hidden bias and uncertainty in habitat models

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which heterogeneity and hidden bias were induced by confounding with missing variables associated with other improtant processes, a problem common in statistical modeling of ecological phenomena. Simulations for a large ( N = 10 000) finite population representing grid locations on a landscape demonstrated various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable. Quantile (0 ≤ τ ≤ 1) regression parameters for linear models that excluded the important, unmeasured variable revealed bias relative to parameters from the generating model. Depending on whether interactions of the measured and unmeasured variables were negative (interference interactions) or positive (facilitation interactions) in simulations without spatial structuring, either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Heterogeneous, nonlinear response patterns occurred with correlations between the measured and unmeasured variables. When the unmeasured variable was spatially structured, variation in parameters across quantiles associated with heterogeneous effects of the habitat variable was reduced by modeling the spatial trend surface as a cubic polynomial of location coordinates, but substantial hidden bias remained. Sampling ( n = 20–300) simulations demonstrated that regression quantile estimates and confidence intervals constructed by inverting weighted rank score tests provided valid coverage of these parameters. Local forms of quantile weighting were required for obtaining correct Type I error rates and confidence interval coverage. Quantile regression was used to estimate effects of physical habitat resources on a bivalve ( Macomona liliana ) in the spatially structured landscape on a sandflat in a New Zealand harbor. Confidence intervals around predicted 0.10 and 0.90 quantiles were used to estimate sampling intervals containing 80% of the variation in densities in relation to bed elevation. Spatially structured variation in bivalve counts estimated by a cubic polynomial trend surface remained after accounting for the nonlinear effects of bed elevation, indicating the existence of important spatially structured processes that were not adequately represented by the measured habitat variables.

Ecology↗

USGS2005

Effects of tag loss on direct estimates of population growth rate

The temporal symmetry approach of R. Pradel can be used with capture– recapture data to produce retrospective estimates of a population's growth rate, λ i , and the relative contributions to λ i from different components of the population. Direct estimation of λ i provides an alternative to using population projection matrices to estimate asymptotic λ and is seeing increased use. However, the robustness of direct estimates of λ i to violations of several key assumptions has not yet been investigated. Here, we consider tag loss as a possible source of bias for scenarios in which the rate of tag loss is (1) the same for all marked animals in the population and (2) a function of tag age. We computed analytic approximations of the expected values for each of the parameter estimators involved in direct estimation and used those values to calculate bias and precision for each parameter estimator. Estimates of λ i were robust to homogeneous rates of tag loss. When tag loss rates varied by tag age, bias occurred for some of the sampling situations evaluated, especially those with low capture probability, a high rate of tag loss, or both. For situations with low rates of tag loss and high capture probability, bias was low and often negligible. Estimates of contributions of demographic components to λ i were not robust to tag loss. Tag loss reduced the precision of all estimates because tag loss results in fewer marked animals remaining available for estimation. Clearly tag loss should be prevented if possible, and should be considered in analyses of λ i , but tag loss does not necessarily preclude unbiased estimation of λ i .

Ecology↗

USGS2007

Can modeling improve estimation of desert tortoise population densities?

The federally listed desert tortoise (Gopherus agassizii) is currently monitored using distance sampling to estimate population densities. Distance sampling, as with many other techniques for estimating population density, assumes that it is possible to quantify the proportion of animals available to be counted in any census. Because desert tortoises spend much of their life in burrows, and the proportion of tortoises in burrows at any time can be extremely variable, this assumption is difficult to meet. This proportion of animals available to be counted is used as a correction factor (g0) in distance sampling and has been estimated from daily censuses of small populations of tortoises (6-12 individuals). These censuses are costly and produce imprecise estimates of g0 due to small sample sizes. We used data on tortoise activity from a large (N = 150) experimental population to model activity as a function of the biophysical attributes of the environment, but these models did not improve the precision of estimates from the focal populations. Thus, to evaluate how much of the variance in tortoise activity is apparently not predictable, we assessed whether activity on any particular day can predict activity on subsequent days with essentially identical environmental conditions. Tortoise activity was only weakly correlated on consecutive days, indicating that behavior was not repeatable or consistent among days with similar physical environments. ?? 2007 by the Ecological Society of America.

Ecological Applications↗

USGS2007

Hierarchical spatial models of abundance and occurrence from imperfect survey data

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

Ecological Monographs↗

USGS2009

A less field-intensive robust design for estimating demographic parameters with Mark-resight data

The robust design has become popular among animal ecologists as a means for estimating population abundance and related demographic parameters with mark-recapture data. However, two drawbacks of traditional mark-recapture are financial cost and repeated disturbance to animals. Mark-resight methodology may in many circumstances be a less expensive and less invasive alternative to mark-recapture, but the models developed to date for these data have overwhelmingly concentrated only on the estimation of abundance. Here we introduce a mark-resight model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. The model may be implemented using standard statistical computing software, but it has also been incorporated into the freeware package Program MARK. We illustrate the use of our model with mainland New Zealand Robin (Petroica australis) data collected to ascertain whether this methodology may be a reliable alternative for monitoring endangered populations of a closely related species inhabiting the Chatham Islands. We found this method to be a viable alternative to traditional mark-recapture when cost or disturbance to species is of particular concern in long-term population monitoring programs. ?? 2009 by the Ecological Society of America.

Ecology↗

USGS2011

Migration delays caused by anthropogenic barriers: modeling dams, temperature, and success on migrating salmon smolts

Disruption to migration is a growing problem for conservation and restoration of animal populations. Anthropogenic barriers along migration paths can delay or prolong migrations, which may result in a mismatch with migration-timing adaptations. To understand the interaction of dams (as barriers along a migration path), seasonally changing environmental conditions, timing of Atlantic salmon ( Salmo salar ) downstream migration, and ultimate migration success, we used 10 years of river temperature and discharge data as a template upon which we simulated downstream movement of salmon. Atlantic salmon is a cool-water species whose downstream migrating smolts must complete migration before river temperatures become too warm. We found that dams had a local effect on survival as well as a survival effect that was spatially and temporally removed from the encounter with the dam. While smolts are delayed by dams, temperatures downstream can reach lethal or near-lethal temperatures; as a result, the match between completion of migration and the window of appropriate migration conditions can be disrupted. The strength of this spatially and temporally removed effect is at least comparable to the local effects of dams in determining smolt migration success in the presence of dams. We also considered smolts from different tributaries, varying in distance from the river mouth, to assess the potential importance of locally adapted migration timing on the effect of barriers. Migration-initiation temperature affected modeled smolt survival differentially across tributaries, with the success of smolts from upstream tributaries being much more variable across years than that of smolts with a shorter distance to travel. As a whole, these results point to the importance of broadening our spatial and temporal view when managing migrating populations. We must consider not only how many individuals never make it across migration barriers, but also the spatially and temporally removed consequences of delays at the barriers for those individuals that successfully navigate them.

Ecological Applications↗

USGS2011

Estimating age from recapture data: Integrating incremental growth measures with ancillary data to infer age-at-length

Estimating the age of individuals in wild populations can be of fundamental importance for answering ecological questions, modeling population demographics, and managing exploited or threatened species. Significant effort has been devoted to determining age through the use of growth annuli, secondary physical characteristics related to age, and growth models. Many species, however, either do not exhibit physical characteristics useful for independent age validation or are too rare to justify sacrificing a large number of individuals to establish the relationship between size and age. Length‐at‐age models are well represented in the fisheries and other wildlife management literature. Many of these models overlook variation in growth rates of individuals and consider growth parameters as population parameters. More recent models have taken advantage of hierarchical structuring of parameters and Bayesian inference methods to allow for variation among individuals as functions of environmental covariates or individual‐specific random effects. Here, we describe hierarchical models in which growth curves vary as individual‐specific stochastic processes, and we show how these models can be fit using capture–recapture data for animals of unknown age along with data for animals of known age. We combine these independent data sources in a Bayesian analysis, distinguishing natural variation (among and within individuals) from measurement error. We illustrate using data for African dwarf crocodiles, comparing von Bertalanffy and logistic growth models. The analysis provides the means of predicting crocodile age, given a single measurement of head length. The von Bertalanffy was much better supported than the logistic growth model and predicted that dwarf crocodiles grow from 19.4 cm total length at birth to 32.9 cm in the first year and 45.3 cm by the end of their second year. Based on the minimum size of females observed with hatchlings, reproductive maturity was estimated to be at nine years. These size benchmarks are believed to represent thresholds for important demographic parameters; improved estimates of age, therefore, will increase the precision of population projection models. The modeling approach that we present can be applied to other species and offers significant advantages when multiple sources of data are available and traditional aging techniques are not practical.

Loango National Park↗

USGS2011

Could residual oil from the Exxon Valdez spill create a long-term population "sink" for sea otters in Alaska?

Over 20 years ago, the Exxon Valdez oil tanker spilled 42 million L of crude oil into the waters of Prince William Sound, Alaska, USA. At the time of the spill, the sea otter (Enhydra lutris) population inhabiting the spill area suffered substantial acute injuries and loss. Subsequent research has resulted in one of the best-studied species responses to an oil spill in history. However, the question remains: Is the spill still influencing the Prince William Sound sea otter population? Here we fit time-varying population models to data for the sea otter population of western Prince William Sound to quantify the duration and extent of mortality effects from the spill. We hypothesize that the patchy nature of residual oil left in the environment has created a source-sink population dynamic. We fit models using the age distributions of both living and dying animals and estimates of sea otter population size to predict the number of sea otters in the hypothesized sink population and the number lost to this sink due to chronic exposure to residual oil. Our results suggest that the sink population has remained at just over 900 individuals (95% CI: 606-960) between 1990 and 2009, during which time prime-age survival remained 2-6% below pre-spill levels. This reduced survival led to chronic losses of ???900 animals over the past two decades, which is similar in magnitude to the number of sea otter deaths documented in western Prince William Sound during the acute phase of the spill. However, the unaffected source population appears to be counterbalancing these losses, with the model indicating that the sea otter population increased from ???2150 individuals in 1990 to nearly 3000 in 2009. The most optimistic interpretation of our results suggests that mortality effects dissipated between 2005 and 2007. Our results suggest that residual oil can affect wildlife populations on time scales much longer than previously believed and that cumulative chronic effects can be as significant as acute effects. Further, source-sink population dynamics can explain the slow recovery observed in the spill-affected western Prince William Sound sea otter population and are consistent with available data. ??2011 by the Ecological Society of America.

Ecological Applications↗

USGS2011

Seasonal productivity in a population of migratory songbirds: why nest data are not enough

Population models for many animals are limited by a lack of information regarding juvenile survival. In particular, studies of songbird reproductive output typically terminate with the success or failure of nests, despite the fact that adults spend the rest of the reproductive season rearing dependent fledglings. Unless fledgling survival does not vary, or varies consistently with nest productivity, conclusions about population dynamics based solely on nest data may be misleading. During 2007 and 2008, we monitored nests and used radio telemetry to monitor fledgling survival for a population of Ovenbirds ( Seiurus aurocapilla ) in a managed-forest landscape in north-central Minnesota, USA. In addition to estimating nest and fledgling survival, we modeled growth for population segments partitioned by proximity to edges of non-nesting cover types (regenerating clearcuts). Nest survival was significantly lower, but fledgling survival was significantly higher, in 2007 than in 2008. Despite higher nest productivity in 2008, seasonal productivity (number of young surviving to independence per breeding female) was higher in 2007. Proximity to clearcut edge did not affect nest productivity. However, fledglings from nests near regenerating sapling-dominated clearcuts (7–20 years since harvest) had higher daily survival (0.992 ± 0.005) than those from nests in interior forest (0.978 ± 0.006), which in turn had higher daily survival than fledglings from nests near shrub-dominated clearcuts (≤6 years since harvest; 0.927 ± 0.030) in 2007, with a similar but statistically non-significant trend in 2008. Our population growth models predicted growth rates that differed by 2–39% ( x¯ = 25%) from simpler models in which we replaced our estimates of first-year survival with one-half adult annual survival (an estimate commonly used in songbird population growth models). We conclude that nest productivity is an inadequate measure of songbird seasonal productivity, and that results based exclusively on nest data can yield misleading conclusions about population growth and clearcut edge effects. We suggest that direct estimates of juvenile survival could provide more accurate information for the management and conservation of many animal taxa.

Ecosphere↗

USGS2012

Occupancy in continuous habitat

The probability that a site has at least one individual of a species ('occupancy') has come to be widely used as a state variable for animal population monitoring. The available statistical theory for estimation when detection is imperfect applies particularly to habitat patches or islands, although it is also used for arbitrary plots in continuous habitat. The probability that such a plot is occupied depends on plot size and home-range characteristics (size, shape and dispersion) as well as population density. Plot size is critical to the definition of occupancy as a state variable, but clear advice on plot size is missing from the literature on the design of occupancy studies. We describe models for the effects of varying plot size and home-range size on expected occupancy. Temporal, spatial, and species variation in average home-range size is to be expected, but information on home ranges is difficult to retrieve from species presence/absence data collected in occupancy studies. The effect of variable home-range size is negligible when plots are very large (>100 x area of home range), but large plots pose practical problems. At the other extreme, sampling of 'point' plots with cameras or other passive detectors allows the true 'proportion of area occupied' to be estimated. However, this measure equally reflects home-range size and density, and is of doubtful value for population monitoring or cross-species comparisons. Plot size is ill-defined and variable in occupancy studies that detect animals at unknown distances, the commonest example being unlimited-radius point counts of song birds. We also find that plot size is ill-defined in recent treatments of "multi-scale" occupancy; the respective scales are better interpreted as temporal (instantaneous and asymptotic) rather than spatial. Occupancy is an inadequate metric for population monitoring when it is confounded with home-range size or detection distance.

Ecosphere↗

USGS2014

Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions

Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou ( Rangifer tarandus granti ) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.

Alaska↗

USGS2003

Effects of desert wildfires on desert tortoise (Gopherus agassizii) and other small vertebrates

We report the results of standardized surveys to determine the effects of wildfires on desert tortoises (Gopherus agassizii) and their habitats in the northeastern Mojave Desert and northeastern Sonoran Desert. Portions of 6 burned areas (118 to 1,750 ha) were examined for signs of mortality of vertebrates. Direct effects of fire in desert habitats included animal mortality and loss of vegetation cover. A range of 0 to 7 tortoises was encountered during surveys, and live tortoises were found on all transects. In addition to desert tortoises, only small (<1 kg) mammals and reptiles (11 taxa) were found dead on the study areas. We hypothesize that indirect effects of fire on desert habitats might result in changes in the composition of diets and loss of vegetation cover, resulting in an increase in predation and loss of protection from temperature extremes. These changes in habitat also might cause changes in vertebrate communities in burned areas.

Southwestern Naturalist↗