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Results for “Wildlife Monograph”

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43 records · Page 3Linked to original sources
USGS1990

Opportunities to protect instream flows and wetland uses of water in Florida

This document combines the efforts of several individuals, agencies, and organizations toward a common objective: the identification, description, and preliminary evaluation of promising opportunities for protecting instream uses of water under existing laws in Florida. this report is intended for the use of State and Federal planning and management personnel who need an overview of potential opportunities for preserving instream flows. It is not intended to replace or challenge the advice of agency counsel, nor is it written to provide legal advice. Instead, it is designed as a guide for the person trying to find his way among sometimes bewildering State statutes and administrative practices. This report is not, and should not be taken as, official policy or prediction of future actions by any agency. It is simply a summary of some potential opportunities for protecting instream uses. Toward these objectives, the U.S. Fish and Wildlife Service, through its Water Resource Analysis Project, contracted in 1977 with R. Dewsnup and D. Jensen to identify available strategies under State and Federal laws, interstate compacts, and water quality laws. A second firm, Enviro Control, Inc., was contracted to evaluate the most promising strategies. The resulting documents reported instream flow strategies for 11 States. These reports have been revised, updated, and combined in a number of new monographs, and the Service has added more States to this service over the years. The discussion of instream flow programs and opportunities for each State is written so that each report can be read independently, with minimal cross-referencing from one State report to another. The opportunities for Florida are summarized in the table.

Report↗
USGS2021

Sea otter population collapse in southwest Alaska: Assessing ecological covariates, consequences, and causal factors

Sea otter ( Enhydra lutris ) populations in southwest Alaska declined substantially between about 1990 and the most recent set of surveys in 2015. Here we report changes in the distribution and abundance of sea otters, and covarying patterns in reproduction, mortality, body size and condition, diet and foraging behavior, food availability, health profiles, and exposure to environmental contaminants over this 25-yr period. The population decline, which resulted in densities on the order of 5% of environmental carrying capacity, ranged from Attu Island in the west to about Castle Cape (on the south side of the Alaska Peninsula) in the east. Remaining sea otters moved closer to shore and into shallow, protected habitats. Reproductive rates appeared unchanged with the decline. Although the demographic cause of the decline was clearly elevated mortality, stranded carcasses were rare or absent. The net rate of energy gain by foraging sea otters, body length and condition, and prey biomass density, all increased after the decline and varied inversely with sea otter population density beyond the area of decline. Sea otters within the area of decline showed no increases in health anomalies, disease, contaminant exposure, or abnormal gene transcription patterns as compared to animals outside the area of decline. These collective findings are inconsistent with nutritional limitation, disease, or environmental contaminants, and consistent with predation (or possibly some other density-independent factor) as the reason for the sea otter population decline. Our approach and analyses provide a broad conceptual template for thinking about and assessing the causes of wildlife population declines.

Alaska↗
USGS2024

Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population trends

Estimating the abundance of unmarked animal populations from acoustic data is challenging due to the inability to identify individuals and the need to adjust for observation biases including detectability (false negatives), species misclassification (false positives), and sampling exposure. Acoustic surveys conducted along mobile transects were designed to avoid counting individuals more than once, where raw counts are commonly treated as an index of abundance. More recently, false-positive abundance models have been developed to estimate abundance while accounting for imperfect detection and misclassification. We adapted these methods to model summertime abundance and trends of three species of bats at multiple spatial scales using acoustic recordings collected along mobile transects by partners of the North American Bat Monitoring Program (NABat) from 2012 to 2020. This multiscale modeling spanned individual transect routes, larger NABat grid cells (10 km × 10 km), and across the entire extent of modeled species ranges. We estimated relationships between species abundances and a suite of abiotic and biotic predictors (landcover types, climatological variables, physiographic diversity, building density, and the impacts of white-nose syndrome [WNS]) and found varying levels of support between species. We present clear evidence of substantial declines in populations of tricolored bats ( Perimyotis subflavus ) and little brown bats ( Myotis lucifugus ), declines that corresponded in space and time with the progression of WNS, a devastating disease of hibernating bats. In contrast, our analysis revealed that similar population-wide declines probably have not occurred in big brown bats ( Eptesicus fuscus ), a species known to be less affected by WNS. This study provides the first abundance-based species distribution predictions and population trends for bats in their summer ranges in North America. These models will probably be applicable to assessing wildlife populations in other monitoring programs where acoustic data are used or where false-negative and false-positive detections are present. Finally, our abundance framework (as a spatial point pattern process) can serve as a foundation from which more sophisticated integrated species distribution models that incorporate additional streams of monitoring data (e.g., stationary acoustics, captures) can be developed for North American bats.

Ecological Monographs↗
USGS2017

Altitudinal migration and the future of an iconic Hawaiian honeycreeper in response to climate change and management

Altitudinal movement by tropical birds to track seasonally variable resources can move them from protected areas to areas of increased vulnerability. In Hawaiʻi, historical reports suggest that many Hawaiian honeycreepers such as the ‘I‘iwi ( Drepanis coccinea ) once undertook seasonal migrations, but the existence of such movements today is unclear. Because Hawaiian honeycreepers are highly susceptible to avian malaria, currently minimal in high-elevation forests, understanding the degree to which honeycreepers visit lower elevation forests may be critical to predict the current impact of malaria on population dynamics and how susceptible bird populations may respond to climate change and mitigation scenarios. Using radio telemetry data, we demonstrate for the first time that a large fraction of breeding adult and juvenile ‘I‘iwi originating from an upper-elevation (1,920 m) population at Hakalau Forest National Wildlife Refuge exhibit post-breeding movements well below the upper elevational limit for mosquitoes. Bloom data suggest seasonal variation in floral resources is the primary driver of seasonal movement for ‘I‘iwi. To understand the demographic implications of such movement, we developed a spatial individual-based model calibrated using previously published and original data. ʻI‘iwi dynamics were simulated backward in time, to estimate population levels in the absence of avian malaria, and forward in time, to assess the impact of climate warming as well as two potential mitigation actions. Even in disease-free ‘refuge’ populations, we found that breeding densities failed to reach the estimated carrying capacity, suggesting the existence of a seasonal “migration load” as a result of travel to disease-prevalent areas. We predict that ‘I‘iwi may be on the verge of extinction in 2100, with the total number of pairs reaching only ~ 0.2–12.3% of the estimated pre-malaria density, based on an optimistic climate change scenario. The probability of extinction of ‘I‘iwi populations, as measured by population estimates for 2100, is strongly related to their estimated migration propensity. Long-term conservation strategies likely will require a multi-pronged response including a reduction of malaria threats, habitat restoration and continued landscape-level access to seasonally variable nectar resources.

Ecological Monographs↗
USGS2010

Linking process to pattern: estimating spatiotemporal dynamics of a wildlife epidemic from cross‐sectional data

Underlying dynamic event processes unfolding in continuous time give rise to spatiotemporal patterns that are sometimes observable at only a few discrete times. Such event processes may be modulated simultaneously over several spatial (e.g., latitude and longitude) and temporal (e.g., age, calendar time, and cohort) dimensions. The ecological challenge is to understand the dynamic latent processes that were integrated over several dimensions (space and time) to produce the observed pattern: a so‐called inverse problem. An example of such a problem is characterizing epidemiological rate processes from spatially referenced age‐specific prevalence data for a wildlife disease such as chronic wasting disease (CWD). With age‐specific prevalence data, the exact infection times are not observed, which complicates the direct estimation of rates. However, the relationship between the observed data and the unobserved rate variables can be described with likelihood equations. Typically, for problems with multiple timescales, the likelihoods are integral equations without closed forms. The complexity of the likelihoods often makes traditional maximum‐likelihood approaches untenable. Here, using seven years of hunter‐harvest prevalence data from the CWD epidemic in white‐tailed deer (Odocoileus virginianus) in Wisconsin, USA, we develop and explore a Bayesian approach that allows for a detailed examination of factors modulating the infection rates over space, age, and time, and their interactions. Our approach relies on the Bayesian ability to borrow strength from neighbors in both space and time. Synthesizing a number of areas of event time analysis (current‐status data, age/period/cohort models, Bayesian spatial shared frailty models), our general framework has very broad ecological applicability beyond disease prevalence data to a number of important ecological event time analyses, including general survival studies with multiple time dimensions for which existing methodology is limited. We observed strong associations of infection rates with age, gender, and location. The infection rate appears to be increasing with time. We could not detect growth hotspots, or location by time interactions, which suggests that spatial variation in infection rates is determined primarily by when the disease arrives locally, rather than how fast it grows. We emphasize assumptions and the potential consequences of their violations.

Wisconsin↗
USGS2025

Pan-amphibia distribution of the fungal parasite Batrachochytrium dendrobatidis varies with species and temperature

Batrachochytrium dendrobatidis (Bd) is a globally distributed fungal pathogen of amphibians that has contributed to one of the largest disease-related biodiversity losses in wildlife. Bd is regularly viewed through the lens of a global wildlife epizootic because the spread of highly virulent genetic lineages has resulted in well-documented declines and extinctions of multiple amphibian species. However, the current state of Bd occurrence, host range, host impacts, and ecological drivers remains poorly understood outside of the most negatively affected amphibian species and regions. Our objective was to describe the macroecology of Bd occurrence and infection intensity on caudates (salamanders) across the United States and to compare these patterns with better-studied anurans (frogs and toads). We collected swabs from 11,183 amphibians at 609 sites from 54 species across the United States from 2015 to 2017. We analyzed the prevalence and intensity of Bd infection jointly using a Bayesian hurdle model with covariates of site-level temperature and precipitation, as well as individual characteristics and species identification. Bd was distributed widely across sites and species sampled across the spatial extent of the conterminous United States. We found that Bd prevalence and intensity were most strongly influenced by temperature in the month preceding sampling and by differences among taxon groups. We estimated that temperature had a strong and nonlinear influence on both Bd prevalence and intensity with peak infection at intermediate temperatures and lower infection at low and high temperatures. We found Caudate hosts tended to have higher prevalence than Anuran hosts and Anuran hosts tended to have higher intensity at optimal temperatures for Bd infection. Our findings suggest that Bd has an amphibian-wide host range, temperature gradients exert a strong influence on Bd, and enzootic transmission likely encompasses a much larger spatial and species distribution than previously recognized across North America.

conterminous United States↗
USGS2003

Small-mammal density estimation: A field comparison of grid-based vs. web-based density estimators

Statistical models for estimating absolute densities of field populations of animals have been widely used over the last century in both scientific studies and wildlife management programs. To date, two general classes of density estimation models have been developed: models that use data sets from capture–recapture or removal sampling techniques (often derived from trapping grids) from which separate estimates of population size ( NÌ‚ ) and effective sampling area ( AÌ‚ ) are used to calculate density ( DÌ‚ = NÌ‚ / AÌ‚ ); and models applicable to sampling regimes using distance-sampling theory (typically transect lines or trapping webs) to estimate detection functions and densities directly from the distance data. However, few studies have evaluated these respective models for accuracy, precision, and bias on known field populations, and no studies have been conducted that compare the two approaches under controlled field conditions. In this study, we evaluated both classes of density estimators on known densities of enclosed rodent populations. Test data sets ( n = 11) were developed using nine rodent species from capture–recapture live-trapping on both trapping grids and trapping webs in four replicate 4.2-ha enclosures on the Sevilleta National Wildlife Refuge in central New Mexico, USA. Additional “saturation” trapping efforts resulted in an enumeration of the rodent populations in each enclosure, allowing the computation of true densities. Density estimates ( DÌ‚ ) were calculated using program CAPTURE for the grid data sets and program DISTANCE for the web data sets, and these results were compared to the known true densities ( D ) to evaluate each model's relative mean square error, accuracy, precision, and bias. In addition, we evaluated a variety of approaches to each data set's analysis by having a group of independent expert analysts calculate their best density estimates without a priori knowledge of the true densities; this “blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web-based uniform and half-normal models in program DISTANCE, and the grid-based models M b and M bh in program CAPTURE (with AÌ‚ adjusted by species-specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web-based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid-based DÌ‚ analyses using full MMDM values for WÌ‚ area adjustments required a number of theoretical assumptions of uncertain validity, and we therefore viewed their empirical successes with caution. Finally, density estimates from the independent analysts were highly variable, but estimates from web-based approaches had smaller mean square errors and better achieved confidence-interval coverage of D than did grid-based approaches. Our results support the contention that web-based approaches for density estimation of small-mammal populations are both theoretically and empirically superior to grid-based approaches, even when sample size is far less than often recommended. In view of the increasing need for standardized environmental measures for comparisons among ecosystems and through time, analytical models based on distance sampling appear to offer accurate density estimation approaches for research studies involving small-mammal abundances.

Ecological Monographs↗