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The study documented the interaction between hydrology and the biological dynamics within a single spring season at Lisbon Bottom in 1999. The study goal was to provide information necessary for resource managers to develop management strategies for this and other units of the Big Muddy National Fish and Wildlife Refuge. Researchers studied the hydrology, limnology, and biological dynamics of zooplankton, macroinvertebrates, fish and waterbird communities. Lisbon Bottom is one of several parcels of 1993 flood-damaged land that was purchased from willing sellers by the U.S. Fish and Wildlife Service as part of the Big Muddy National Fish and Wildlife Refuge. Lisbon Bottom is a loop bend in the river near Glasgow in Howard County, Missouri between approximately river mile (RM) 213 to RM 219. Flooding at Lisbon in 1993 and 1995 breeched local levees and created a diverse wetland complex.
Open-source intelligence (OSINT) evolved in spy agencies but now is rapidly changing many fields of study, from anthropology to zoology. Despite the fact that OSINT occasionally is used in conservation biology, there is little recognition that some tools and frameworks used by conservation professionals are drawn from this well-established field. The history and conceptual foundations of OSINT stem from the intelligence community, although OSINT tools are rapidly being applied in other fields. In conservation biology, OSINT is sometimes used to evaluate wildlife crime, human-wildlife and human-environment interactions, animal behavior, and questions of distribution and abundance. Recognizing the conceptual foundations of the field would allow expansion of conservation biology, not only in the areas noted above, but also, for example, in study of habitat use, habitat change, and animal behavior. This recognition would also provide frameworks for conceptual advancement, especially in terms of data and privacy management. Failure to recognize the underpinnings of OSINT tools in conservation biology harms the field because it limits how research is framed, thought about, and implemented. Likewise, taking an OSINT perspective to conservation problems, rather than simply thinking in terms of big data, can enrich the field, expand science, and increase knowledge and understanding of biology and biodiversity.
In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey Southwest Biological Science Center employed ground-based light detection and ranging (lidar) during February 2022 to help meet two resource management objectives at the Cabeza Prieta National Wildlife Refuge (CPNWR), Arizona. The two objectives are (1) characterize the water storage capacity for one developed and two modified tanks, which are bedrock catchments also referred to as tinajas, that are important water sources for desert bighorn sheep ( Ovis canadensis mexicana ) in designated wilderness at the CPNWR; and (2) develop a stage-storage model to estimate water volumes from monitoring observations of water surface levels in each tank. We measured storage capacity for the three tanks identified by refuge managers, Buckhorn, Senita, and Eagle, using ground-based lidar collected during February 2022. These data produced high-resolution (centimeter scale) topographic models that improved estimates of maximum water storage capacity over previous geometry-based estimates, permitting estimations of storage capacity at multiple water surface levels (stage heights). We found that the maximum water storage capacity for the Buckhorn, Senita, and Eagle tanks was 9,108.730, 8,623.308, and 6,039.603 US gallons (gal), respectively. For each tank we report a stage-storage model based on a polynomial function that best explained variability in water storage capacity as a function of water stage height. The results presented herein will permit the CPNWR managers to (1) easily estimate water available for wildlife at any point of time, (2) interpret tank recharge following rainstorms, and (3) decide whether and when to transport water via vehicles to mechanically refill the tanks in designated wilderness.
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Erosion of the nation's shoreline and loss and deterioration of our coastal wetlands are widespread and serious problems that affect all regions of the US. As a result of natural and human-induced factors, the coastal plain of Louisiana, which contains 40% of the tidal wetlands in the conterminous 48 States, is undergoing the greatest amount of coastal erosion and wetlands loss in the nation. The barrier islands that provide a natural buffer for Louisiana's deltaic plain environments are experiencing erosion rates of 20m/yr, while wetlands losses are about 100km2/yr. In response to these problems and the lack of scientific understanding of the processes causing erosion and land loss, the US Geological Survey has, since 1986, conducted field investigations in Louisiana, working closely with the US Fish and Wildlife Service and other Federal and State agencies.
Spatial modeling of wildlife diseases can be used to describe patterns of disease risk, understand biological mechanisms of disease occurrence, and for spatial prediction. Risk of wildlife disease occurrence in relation to environmental variables is often modeled and predicted using Markov chain Monte Carlo (MCMC) methods, which are unsuitable for large datasets and those covering large spatial extents. Integrated nested Laplace approximation (INLA) and INLA using the stochastic partial differential equation (INLA-SPDE) approach have become popular alternatives to MCMC for Bayesian inference because of their fast computational time and ability to process large datasets. Studies investigating risk of disease occurrence in wildlife, to our knowledge, have not yet compared Bayesian hierarchical spatial models over large spatial extents using real world data. Using chronic wasting disease (CWD) surveillance data from white-tailed deer ( Odocoileus virginianus ) collected in Pennsylvania, United States, as a case study, we first demonstrate how parameter estimates compare among MCMC, INLA, and INLA-SPDE modeling frameworks. We then model CWD (detected/non-detected) using INLA-SPDE over a much larger spatial extent than has been conducted previously for this disease to determine how surveillance type (e.g., hunter harvest, roadkill, or all surveillance) influences model parameters and predicted risk of CWD occurrence at locations not sampled. Fixed effects considered in the models included deer age and sex, elevation, slope, distance to streams, percent clay, and proportion of two habitat classes (forest and open) known to influence deer movements. We found INLA to produce comparable estimates to MCMC and permit modeling large datasets covering expansive spatial extents much faster and more efficiently than MCMC. We identified potential biases in surveillance types, indicating the value of including all surveillance in models rather than only a single type. Comparing modeling tools available for mapping diseases of wildlife in relation to ecological variables at large spatial extents will guide future modeling efforts for CWD and other wildlife diseases. Understanding spatial patterns of CWD using different surveillance types can help improve understanding of CWD disease outbreaks, assist with control of CWD through geographical targeting, and inform future CWD surveillance efforts.
A diverse range of fauna could be exposed to active pharmaceutical ingredients (APIs) via diet, dermal absorption or bioconcentration. Low level exposures of free-ranging wildlife to APIs has only been demonstrated for a few pathways (e.g., ingestion of fish in estuaries by piscivorous birds), and many remain hypothetical (e.g., ingestion of invertebrates in sludge amended fields by terrestrial vertebrates). Our understanding of API dose-response relationships in wildlife have only been assessed for endocrine disrupting compounds and a few veterinary therapeutics. Drug specific responses at various levels of biological organization are poorly characterized for nearly all wildlife species, and thus our understanding of risk is limited. There is interest in using a read-across approach to fill knowledge gaps for risk. This approach, using data collected in laboratory mammals and humans, would enable predictions for likelihood of adverse effects in wildlife. Given the great diversities in physiologies among species, a combination of in vivo, in vitro and in silico approaches will be required to fill the knowledge gaps for exposure, hazard and risk.
Alaska Natives depend on local natural resources for nutritional and, for many, spiritual health. As a result, public health in Alaska is strongly influenced by the relationship between people and their surrounding physical, chemical, and biological environments. Alaska is vast with diverse wildlife and plant communities that are valued as subsistence foods (fig. 1). These resources are supported by equally diverse ecosystems and their underpinning landforms and geologies. The U.S. Geological Survey (USGS) is attempting to integrate physical, chemical, and biological information to better describe current (2013) environments and project scenarios for the future. Integrating ecological data into the public health dialogue is challenging for the more than 280 rural communities of Alaska. This fact sheet reviews a recent USGS effort, the Geographic Information System (GIS) Native Health Project, to better incorporate scientific information into such dialogue.
Waterborne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS). A risk-based screening approach was used to prioritize chemicals and chemical mixtures, identify sites at greatest risk for biological impacts, and identify potential hazards to monitor at those sites. Analyses included 185 chemicals (143 detected) including polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, fire retardants, pharmaceuticals, and fragrances. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (toxicity quotients) or ToxCast database (exposure–activity ratios [EARs]). Mixture effects were estimated by summation of EAR values for chemicals that influence ToxCast assays with common gene targets. Nineteen chemicals—atrazine, N,N -diethyltoluamide, di(2-ethylhexyl)phthalate, dl-menthol, galaxolide, p-tert-octylphenol, 3 organochlorine pesticides, 3 PAHs, 4 pharmaceuticals, and 3 phosphate flame retardants—had toxicity quotients >0.1 or EARs for individual chemicals >10 –3 at 10% or more of the sites monitored. An additional 4 chemicals (tributyl phosphate, triethyl citrate, benz[ a ]anthracene, and benzo[ b ]fluoranthene) were present in mixtures with EARs >10 –3 . To evaluate potential apical effects and biological endpoints to monitor in exposed wildlife, in vitro bioactivity data were compared to adverse outcome pathway gene ontology information. Endpoints and effects associated with endocrine disruption, alterations in xenobiotic metabolism, and potentially neuronal development would be relevant to monitor at the priority sites. The EAR threshold exceedance for many chemical classes was correlated with urban land cover and wastewater effluent influence, whereas herbicides and fire retardants were also correlated to agricultural land cover. Environ Toxicol Chem 2021;40:2165–2182. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Hypothesis testing is fundamental to producing the rigorous biological inferences needed to reliably inform wildlife managemen
Atmospheric mercury (Hg) emissions and subsequent transport and deposition are major concerns within protected lands, including national parks, where Hg can bioaccumulate to levels detrimental to human and wildlife health. Despite this risk to biological resources, there is limited understanding of the relative importance of different Hg sources and delivery pathways within protected regions. Here, we used Hg stable isotope measurements of a single aquatic bioindicator, dragonfly larvae, to determine if these tracers can resolve spatial patterns in Hg sources, delivery mechanisms, and aquatic cycling at a national scale. Mercury isotope values in dragonfly tissues varied among habitat types (e.g., lentic, lotic, wetland) and geographic location. Photochemical-derived isotope fractionation was habitat-dependent and influenced by factors that impact light penetration directly or indirectly, including dissolved organic matter, canopy cover, and total phosphorus. Strong patterns for Δ 200 Hg emerged in the western US, highlighting the relative importance of wet deposition sources in arid regions in contrast to dry deposition delivery in forested regions. This work highlights the efficacy of dragonfly larvae as biosentinels for Hg isotope studies due to their ubiquity across freshwater ecosystems and ability to track variation in Hg sources and processing attributed to small-scale habitat and large-scale regional patterns.
The Yellowstone National Park bison herd is 1 of only 2 populations known to have continually persisted on their current landscape since pre-Columbian times. Over the last century, the census size of this herd has fluctuated from around 100 individuals to over 3000 animals. Previous studies involving radiotelemetry, tooth wear, and parturition timing provide evidence of at least 2 distinct groups of bison within Yellowstone National Park. To better understand the biology of Yellowstone bison, we investigated the potential for limited gene flow across this population using multilocus Bayesian clustering analysis. Two genetically distinct and clearly defined subpopulations were identified based on both genotypic diversity and allelic distributions. Genetic cluster assignments were highly correlated with sampling locations for a subgroup of live capture individuals. Furthermore, a comparison of the cluster assignments to the 2 principle winter cull sites revealed critical differences in migration patterns across years. The 2 Yellowstone subpopulations display levels of differentiation that are only slightly less than that between populations which have been geographically and reproductively isolated for over 40 years. The identification of cryptic population subdivision and genetic differentiation of this magnitude highlights the importance of this biological phenomenon in the management of wildlife species.
Wildlife diseases can present significant threats to ecological systems and biological diversity, as well as domestic animal and human health. However, determining the dynamics of wildlife diseases and understanding the impact on host populations is a significant challenge. In Hawai‘i, there is ample circumstantial evidence that introduced avian malaria ( Plasmodium relictum ) has played an important role in the decline and extinction of many native forest birds. However, few studies have attempted to estimate disease transmission and mortality, survival, and individual species impacts in this distinctive ecosystem. We combined multi-state capture-recapture (longitudinal) models with cumulative age-prevalence (cross-sectional) models to evaluate these patterns in Apapane, Hawai‘i Amakihi, and Iiwi in low-, mid-, and high-elevation forests on the island of Hawai‘i based on four longitudinal studies of 3–7 years in length. We found species-specific patterns of malaria prevalence, transmission, and mortality rates that varied among elevations, likely in response to ecological factors that drive mosquito abundance. Malaria infection was highest at low elevations, moderate at mid elevations, and limited in high-elevation forests. Infection rates were highest for Iiwi and Apapane, likely contributing to the absence of these species in low-elevation forests. Adult malaria fatality rates were highest for Iiwi, intermediate for Amakihi at mid and high elevations, and lower for Apapane; low-elevation Amakihi had the lowest malaria fatality, providing strong evidence of malaria tolerance in this low-elevation population. Our study indicates that hatch-year birds may have greater malaria infection and/or fatality rates than adults. Our study also found that mosquitoes prefer feeding on Amakihi rather than Apapane, but Apapane are likely a more important reservoir for malaria transmission to mosquitoes. Our approach, based on host abundance and infection rates, may be an effective alternative to mosquito blood meal analysis for determining vector-host contacts when mosquito densities are low and collection of blood-fed mosquitoes is impractical. Our study supports the hypothesis that avian malaria has been a primary factor influencing the elevational distribution and abundance of these three species, and likely limits other native Hawaiian species that are susceptible to malaria.
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The Central Arizona Basins study area in central and southern Arizona and northern Mexico is one of 60 study units that are part of the U.S. Geological Survey's National Water-Quality Assessment program. The purpose of this report is to describe the physical, chemical, and environmental characteristics that may affect water quality in the Central Arizona Basins study area and present an overview of water quality. Covering 34,700 square miles, the study area is characterized by generally north to northwestward-trending mountain ranges separated by broad, gently sloping alluvial valleys. Most of the perennial rivers and streams are in the northern part of the study area. Rivers and streams in the south are predominantly intermittent or ephemeral and flow in response to precipitation such as summer thunderstorms. Effluent-dependent streams do provide perennial flow in some reaches. The major aquifers in the study area are in the basin-fill deposits that may be as much as 12,000 feet thick. The 1990 population in the study area was about 3.45 million, and about 61 percent of the total was in Maricopa County (Phoenix and surrounding cities). Extensive population growth over the past decade has resulted in a twofold increase in urban land areas and increased municipal water use; however, agriculture remains the major water use. Seventy-three percent of all water with drawn in the study area during 1990 was used for agricultural purposes. The largest rivers in the study area-the Gila, Salt, and Verde-are perennial near their headwaters but become intermittent downstream because of impoundments and artificial diversions. As a result, the Central Arizona Basins study area is unique compared to less arid basins because the mean surface-water outflow is only 528 cubic feet per second from a total drainage area of 49,650 square miles. Peak flows in the northern part of the study area are the result of snowmelt runoff; whereas, summer thunderstorms account for the peak flows in the southern part. Ground water is the primary water supply in most of Arizona and the only source of drinking water used by communities in the southern half of the study area. Years of overpumping have caused water tables in basin fill to drop below once-perennial streams leaving streambeds dry, water too deep to pump economically, pumping of poorer quality water with depth, and earth fissures resulting from subsidence after dewatering of sediments. Natural processes-such as leaching of trace elements and major ions from geologic formations-and human activities-such as mining, agriculture, and urban development-have major effects on the quality of surface-water and ground-water resources in the Central Arizona Basins study area. Surface-water quality standards in Arizona are based on the designated use of the water such as full or partial body contact, fish consumption, aquatic and wildlife uses, and agriculture. Maintaining the biological integrity (health) of surface waters in Arizona is an important part of ensuring that these waters are suitable for designated uses. Important water-quality issues for surface water that are somewhat unique to Arizona include: (1) streamflows and riparian environments sustained by effluent from municipal wastewater-treatment plants that contains high concentrations of nutrients, potentially toxic trace elements and organic compounds, and fecal bacteria; (2) industrial, mining, agricultural, and municipal sources of contamination from Mexico; and (3) unpredictable high flows from major summer thunder storms causing stream-channel changes; high suspended-sediment concentrations and loads; sewage overflows; and breaching, erosion, and washout of landfills and mining operations. The quality of water in aquifers that are protected for drinking- water use is subject to standards that are in most cases equal to or more stringent than the primary drinking-water regulations of the U.S. Environmental Protection Agency. The general che
This compilation was designed to help U.S. Fish and Wildlife Service contaminant specialists evaluate the degree of contamination of a soil, based on chemical analyses. Included are regulatory criteria, opinions, brief descriptions of scientific articles, and miscellaneous information that might be useful in making risk assessments. The intent was to make hard-to-obtain material readily available to contaminant specialists, but not to critique the material or develop new criteria. The compilation is to be used with its index, which includes about 200 contaminants. There are several entries for a few of the most thoroughly studied contaminants, but for most of them the information available is meager. Entries include soil contaminant criteria from other countries, contaminant guidelines for applying sewage sludge to soil, guidelines for evaluating sediments, background soil concentrations for various elements, citations to scientific articles that may help estimate the potential movement of soil contaminants into wildlife food chains, and a few odds and ends. Articles on earthworms were emphasized because they are a natural bridge between soil and many species of wildlife.