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At least 973 records · Page 54Linked to original sources
USGS2025

Environmental drivers of productivity explain population patterns of an Arctic-nesting goose across a half-century

Joint estimation of demographic rates and population size has become an essential tool in ecology because it enables evaluating mechanisms for population change and testing hypotheses about drivers of demography in a single modeling framework. This approach provides a comprehensive perspective on population dynamics and how animal populations will respond to global pressures in future years. However, long-term data for such analyses are often limited in quantity and quality. We developed an integrated population model combining data on demography and population size from nine different sources to understand the population ecology of the lesser snow goose ( Anser caerulescens caerulescens ) in the Pacific Flyway in North America from 1970 to 2022. We divided the flyway population into Wrangel Island and Western Arctic subpopulations and assessed demographic mechanisms for population change and environmental and anthropogenic drivers that influenced demography. During 1970–2022, the estimated spring population of snow geese in the Pacific Flyway increased from ~300,000 to ~2,300,000. Short-term changes in population growth rate were primarily driven by changes in productivity in the Western Arctic and productivity and immigration in Wrangel Island. Changes in hunting and natural mortality had less influence on short-term but likely contributed to the pronounced long-term population growth. Early snowmelt positively influenced per capita productivity in both regions, and warm, rainy weather during the non-breeding season was associated with high per capita productivity in the Western Arctic. In the Western Arctic, per capita productivity was negatively associated with population size, and adult natural mortality was positively associated with population size, indicating density-dependent regulation in this subpopulation. In Wrangel Island, warm weather in early fall decreased juvenile natural mortality. Our results demonstrate that per capita productivity and immigration, rather than adult survival, were the primary mechanisms of short-term population change in this long-lived species. Our results also indicate that environmental conditions and density-dependent effects can impact population dynamics more than harvest, even for a long-lived, commonly harvested species. We demonstrate that a warming climate can have multiple effects on demography, emphasizing the importance of assessing a variety of spatial and temporal factors when predicting how populations might respond to large-scale environmental changes. This emphasizes the importance of conservation plans that consider these environmental drivers, although this may complicate direct management of such populations.

Ecological Applications↗
USGS2026

Status assessment of peregrine falcons in North America using integrated population models

Species status assessments require an understanding of underlying population dynamics and important drivers of species demography. Large-scale assessments can be difficult due to challenges collating data obtained through different methods and different sources at multiple scales. Integrated population models (IPMs) provide a unified framework to combine multiple data sources and jointly estimate population parameters over a large spatiotemporal scale. We developed separate IPMs to estimate abundance and demographic rates for a northern (NMP) and southern (SMP) management population of peregrine falcons ( Falco peregrinus ) in North America from 2008 through 2019 (SMP) and 2020 (NMP). An outbreak of highly pathogenic avian influenza (HPAI) starting in 2021 led us to extend our modeling effort to assess its impact on these management populations by updating both IPMs using index data of population size through 2024 in a predictive framework. Survival probabilities differed drastically between first-year and after-first-year individuals in both management populations. After-first-year survival was nearly identical between the NMP and SMP, but first-year survival was lower in the SMP. Mean productivity was significantly lower in the NMP compared to the SMP, whereas the probability of breeding was similar in both management populations. Estimated total abundance for the NMP was substantially larger than the SMP, representing most of the North American peregrine population. Population growth was positive for both management populations, albeit at a slower rate for the NMP. The NMP declined from 2017 to 2018 coinciding with a drop in 2018 estimated productivity. When we extended the IPMs with updated count data through 2024, the NMP slightly declined but estimated abundance remained above levels at the start of the time series analyzed. The SMP grew at a similar rate to that predicted during the period informed by demographic data. We did not detect a continental-scale change in population size or trajectory in either management population associated with the arrival of HPAI in 2021. Further monitoring can support determination of whether the declines in the NMP were temporary, can enhance understanding of the underlying mechanisms, and can be used to guide the conservation and management of the peregrine falcon population in North America.

North America↗
USGS2008

Wildlife values of North American ricelands

Ricelands have become an indispensable component of waterbird habitat and a leading example of integrating agricultural and natural resource management in the Mississippi Alluvial Valley, Gulf Coast, and Central California. Residual rice, weed seeds, and invertebrates provide food for many avian species during fall and winter. In North America, considerable information exists on the use of ricefields by wintering waterbirds, the value of ricelands as breeding habitat for birds, and the effects of organic chemicals on birds that- feed in ricefields. Recent research has also examined the influence of field management practices, such as winter flooding and post-harvest straw manipulation, on the suitability of ricefields for wildlife. Whereas early studies focused on detrimental effects of wildlife on rice production (e.g., crop depredation), it has become apparent that waterbirds may benefit producers by enhancing straw decomposition, reducing weed and pest pressure, and providing additional income through hunting and wildlife viewing opportunities. A comprehensive evaluation of agronomic and environmental issues is needed to meet the challenges of producing food and sustaining wildlife in twenty-first-century rice lands. Changes in agricultural markets, pressures of increased urban development, conflicting needs for limited resources such as water, endangered species constraints, and concerns over water quality must be addressed in developing a sustainable, mutually beneficial partnership among the rice industry, wildlife, and environmental interests. Research is also needed to evaluate potential reductions in the wildlife carrying capacity of ricelands resulting from new harvest and field management techniques, crop conversion, or loss of rice acreage. Key uncertainties include: (1) changes in waste grain abundance and availability due to various harvest and post-harvest management practices; (2) evaluating food depletion by birds feeding in rice6elds and derermining threshold food levels required to maintain bird use; (3) quantifying use of ricefields by nonwaterfowl species throughout the year; and (4) determining the amount and distribution of rice habitat needed to meet objectives of the North American Waterfowl Management Plan and the United States Shorebird Conservation Plan.

Book chapter↗
USGS2025

The relative influence of geographic and environmental factors on rare plant translocation outcomes

Conservation translocations are an established method for reducing the extinction risk of plant species through intentional movement within or outside the indigenous range. Unsuitable environmental conditions at translocation recipient sites and a lack of understanding of species–environment relationships are often identified as critical barriers to translocation success. However, previous syntheses have drawn these inferences from analyses of qualitative feedback rather than quantitative environmental data. In this study, we use a data set of 235 translocations conducted in the US to understand the influences of geographic and environmental factors on three metrics of translocation success: population persistence, next-generation recruitment and next-generation maturity. We use random forest models to quantify the relative importance of geographic and environmental factors that characterize dissimilarity between source and recipient locations, the position of recipient sites relative to species' ranges and niche metrics derived from these ranges. We also compare the importance of these variables with more conventional predictors (e.g. founder population size). Our results indicate that geographic and environmental variables can be as insightful as conventional variables for predicting plant translocation outcomes. The climate suitability of recipient sites, estimated using species distribution models, was the strongest relative predictor of whether a population persisted, with populations situated in more suitable climates displaying greater persistence. Next-generation recruitment and maturity were best predicted by niche metrics; species in more biotically limiting environments, including tropical regions and soils with high relative nutrient retention, as well as species with the broadest precipitation niches, were the least likely to attain these next-generation benchmarks. Synthesis and applications . Our study is one of the first to quantify the important role of spatial and climatic factors in rare plant translocation outcomes. We provide a novel geographic and environmental perspective on outcomes in plant translocations and demonstrate opportunities to improve translocation success not only by adhering to established best practice guidelines but also by integrating spatial modelling approaches into planning and management processes.

Journal of Applied Ecology↗
USGS1999

Assessing biological effects from highway-runoff constituents

Increased emphasis on evaluation of nonpoint-source pollution has intensified the need for techniques that can be used to discern the toxicological effects of complex chemical mixtures. In response, the use of biological assessment techniques is receiving increased regulatory emphasis. When applied with documented habitat assessment and chemical analysis, these techniques can increase our understanding of the influence of environmental contaminants on the biological integrity and ecological function of aquatic communities. The contaminants of greatest potential concern in highway runoff are those that arise from highway construction, maintenance, and use. The major contaminants of interest are deicers; nutrients; metals; petroleum-related organic compounds, such as polycyclic aromatic hydrocarbons (PAHs), benzene, toluene, ethylbenzene, and xylene (BTEX), and methyl tert -butyl ether (MTBE); sediment washed off the road surface; and agricultural chemicals used in highway maintenance. Hundreds, if not thousands, of biological endpoints (measurable responses of living organisms) may be either directly or associatively affected by contaminant exposure. Measurable effects can occur throughout ecosystem processes across the wide range of biological complexity, ranging from responses at the biochemical level to the community level. The challenge to the environmental scientist is to develop an understanding of the relationship of effects at various levels of biological organization in order to determine whether a causal relationship exists between chemical exposure and substantial ecological impairment. This report provides a brief history of the evolution of biological assessment techniques, a description of the major classes of contaminants that are of particular interest in highway runoff, an overview of representative biological assessment techniques, and a discussion of data-quality considerations. Published reports with a focus on the effects of highway runoff on the local ecosystem were reviewed to provide information on (1) the suitability of the existing data for a quantitative national synthesis, (2) the methods available to study the effects of highway runoff on local ecosystems, and (3) the potential for adverse effects on the roadside environment and receiving waters. Although many biological studies have been done, the use of different methods and a general lack of sufficient documentation precludes a quantitative national synthesis on the basis of the existing data. The Federal Highway Administration, the U.S. Environmental Protection Agency, the U.S. Geological Survey, the Intergovernmental Task Force on Monitoring Water Quality, and the National Resources Conservation Service all have developed and documented methods for assessing the effects of contaminants on ecosystems in receiving waters. These published methods can be used to formulate a set of protocols to provide consistent information from highway-runoff studies. Review of the literature indicates (qualitatively) that highway runoff (even from highways with high traffic volume) may not usually be acutely toxic. Tissue analysis and community assessments, however, indicate effects from highway- runoff sediments near discharge points (even from sites near highways with relatively low traffic volumes). At many sites, elevated concentrations of highway-runoff constituents were measured in tissues of species associated with aquatic sediments. Community assessments also indicate decreases in the diversity and productivity of aquatic ecosystems at some sites receiving highway runoff. These results are not definitive, however, and depend on many site-specific criteria that were not sufficiently documented in most of the studies reviewed.

Open-File Report↗
USGS2016

Physical condition and stress levels during early development reflect feeding rates and predict pre- and post-fledging survival in a nearshore seabird

The effects of acute environmental stressors on reproduction in wildlife are often difficult to measure because of the labour and disturbance involved in collecting accurate reproductive data. Stress hormones represent a promising option for assessing the effects of environmental perturbations on altricial young; however, it is necessary first to establish how stress levels are affected by environmental conditions during development and whether elevated stress results in reduced survival and recruitment rates. In birds, the stress hormone corticosterone is deposited in feathers during the entire period of feather growth, making it an integrated measure of background stress levels during development. We tested the utility of feather corticosterone levels in 3- to 4-week-old nestling brown pelicans ( Pelecanus occidentalis ) for predicting survival rates at both the individual and colony levels. We also assessed the relationship of feather corticosterone to nestling body condition and rates of energy delivery to nestlings. Chicks with higher body condition and lower corticosterone levels were more likely to fledge and to be resighted after fledging, whereas those with lower body condition and higher corticosterone levels were less likely to fledge or be resighted after fledging. Feather corticosterone was also associated with intracolony differences in survival between ground and elevated nest sites. Colony-wide, mean feather corticosterone predicted nest productivity, chick survival and post-fledging dispersal more effectively than did body condition, although these relationships were strongest before fledglings dispersed away from the colony. Both reproductive success and nestling corticosterone were strongly related to nutritional conditions, particularly meal delivery rates. We conclude that feather corticosterone is a powerful predictor of reproductive success and could provide a useful metric for rapidly assessing the effects of changes in environmental conditions, provided pre-existing baseline variation is monitored and understood.

Gulf of Mexico↗
USGS2024

Merging integrated population models and individual-based models to project population dynamics of recolonizing species

Recolonizing species exhibit unique population dynamics, namely dispersal to and colonization of new areas, that have important implications for management. A resulting challenge is how to simultaneously model demographic and movement processes so that recolonizing species can be accurately projected over time and space. We introduce a framework for spatially explicit projection modeling that harnesses the rigorous parameter estimation made possible by an integrated population model (IPM) and the flexible movement modeling made possible by an individual-based model (IBM). Our framework has two components: [1] a Bayesian IPM-driven age- and state-structured population model that governs the population state process and estimation of demographic rates, and [2] an IBM-driven spatial model that allows for the projection of dispersal and habitat colonization. We applied this model framework to estimate current and project future dynamics of gray wolves ( Canis lupus ) in Washington State, USA. We used data from 74 telemetered wolves and yearly pup and pack counts to parameterize the model, and then projected statewide dynamics over 50 years. Mean population growth was 1.29 (95 % Bayesian Credible Interval = 1.26–1.33) during initial recolonization from 2009 to 2020 and decreased to 1.02 (95 % Prediction Interval = 0.98–1.04) in the projection period (2021–2070). Our results suggest that gray wolves have an ~100 % probability of colonizing the last of Washington State's three specified recovery regions by 2030, regardless of alternative assumptions about how dispersing wolves select new territories. Our spatially explicit projection model can be used to project the dynamics of any species for which spatial spread is an important driver of population dynamics.

Washington↗
USGS2021

Navigating the science-policy interface

As a wildlife population ecologist who wants to conduct useful science, I find the Endangered Species Act (ESA), like other federal wildlife statutes, an intriguing read. The topic is in my wheelhouse—fish, wildlife, and plants, with a focus at the population and species levels. There is an emphasis on science, in fact, the “best scientific and commercial data available.” And there are intriguing questions: what threats does a species face? What habitat would be critical for its survival? Could any federal actions put the species or critical habitat in greater peril? I am not alone in this attraction. Hundreds of scientists continue to consider the types of scientific analysis suggested by the ESA. The enthusiasm is palpable. If the first cursory read of the ESA is intriguing to me as a scientist, the second close read is tantalizing—I realize that something very attractive is just out of reach. I know how to estimate the probability of extinction, but I do not know what “in danger of extinction” means. I know how to evaluate the incremental change in status that might arise from some level of proposed take, but I do not know what “is not likely to jeopardize the continued existence” of a species means. The standards expressed in the statute are not stated in purely scientific terms. Thus, ESA decisions cannot be based solely on science, and require additional policy interpretation. Clarity about these policy interpretations—even awareness that they are needed—can be hard to find, leaving a gap between what I can provide as a scientist and what an ESA decision maker needs. This awareness of the interaction between science and policy is also occurring in the larger field of conservation science, where there has been an increasing recognition of a research-implementation gap, the need for actionable science, and the promise of translational ecology. All of these terms emphasize that science alone does not result in action; instead, action arises out of decisions that are informed both by science and by values. At the interface of science and policy, a scientist can deliver relevant knowledge, and a decision maker can explain the policy context in which that science is needed. As a scientist wanting to conduct useful science, I crave this two-way conversation. But how can this conversation be structured in a meaningful and appropriate way? In this chapter, I explore how decision analysis can be used to navigate the science-policy interface for ESA decisions. Decision analysis is a large, well-established field that studies how decisions are made and how they could be made, with explicit attention given to clarifying and separating the values-based and science-based elements of a decision; identifying the impediments that make a decision difficult; and providing tools to overcome those impediments. There have been concerted efforts to apply formal decision analysis to ESA decisions, but the practice is not yet widespread across both the U.S. Fish and Wildlife Service and the National Marine Fisheries Service (the Services). The chapter begins with an introduction to decision analysis and how it seeks to bridge the science-policy interface. In subsequent sections, I explore how a decision analyst might frame listing and reclassification decisions, recovery planning, section 7 consultation, budget allocations, and a few other ESA decisions, with an emphasis on two questions: for each type of decision, what policy clarifications does the decision maker need to make; and knowing the policy context, what type of scientific assessment is needed. In the final discussion, I identify common themes among the types of decisions, and offer thoughts on how decision analysis could be more widely used to integrate science into ESA decisions.

Book chapter↗
USGS2015

The Everglades Depth Estimation Network (EDEN) surface-water model, version 2

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that generate daily water-level and water-depth data, and applications that compute derived hydrologic data across the freshwater part of the greater Everglades landscape. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for EDEN in order for EDEN to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The EDEN surface-water model, version 2 (V2), interpolates water-level data from a network of 240 gages to generate gridded daily water-level surfaces for the freshwater domain of the Everglades. When these spatiotemporal continuous surfaces are combined with EDEN’s digital elevation model of ground surface, derived hydrologic data provide scientists and water managers working in the Everglades with data necessary to analyze ecological and biotic responses to hydrologic changes in the Everglades. Derived datasets include water depth, recession rates, days since last dry, water-surface slopes, and hydroperiod. The V2 model includes enhancements from the previous model (version 1; V1) to accommodate changes in the water-level gage network, adjustments to water-level data, improved understanding of the flow dynamics (particularly near canals), and installation of an elevation benchmark network. Enhancements to the V2 model included Expansion of the EDEN domain: The model domain was expanded to include a part of southern Big Cypress National Preserve and northwestern Everglades National Park upstream of the marsh mangrove wetlands, thus completing the coastal connection along the southwestern boundary of the model; and Development of subdomain models: To account for insufficient water-control structure gage data at some subbasin boundaries, subdomain models were developed for five subdomains, and the resulting water-level surfaces were merged to generate the final water-level surface. Model performance statistics show a general improvement in the V2 model as compared to the V1 model. Overall, the root mean squared error (RMSE) was reduced by 2.42 centimeters (cm) to 4.68 cm. In Water Conservation Area 3A North and Water Conservation Area 3B, the RMSE was reduced by 10.88 and 9.15 cm, respectively. In addition to evaluating model performance statistics, 2-cm water-level maps were generated and evaluated for irregular contours that would indicate a potential problem either with data input or water-level estimates. Three applications of the EDEN-modeled water surfaces and other EDEN datasets are presented in the report to show how scientists and resource managers are using EDEN datasets to analyze biological and ecological responses to hydrologic changes in the Everglades. The biological responses of two important Everglades species, alligators and wading birds, to changes in hydrology are described. The effects of hydrology on fire dynamics in the Everglades are also discussed.

Florida↗
USGS2019

Isolation by a hydroelectric dam induces minimal impacts on genetic diversity and population structure in six fish species

Reduced connectivity created by artificial barriers can influence the genetic integrity of isolated subpopulations by reducing local population sizes and altering patterns of gene flow. We investigated the genetic impacts of one such barrier, the Prairie du Sac dam, Wisconsin, USA, using microsatellite data from six fish species with varying life history traits sampled above and below the dam. Contrary to many past studies in other systems, we did not detect any significant differences in genetic diversity between populations found above and below the Prairie du Sac dam. Our results also revealed low genetic differentiation ( F ST = 0–0.008) between populations above and below the dam for all species. In fact, we found that more genetic variation was partitioned among sampling years than between above and below dam populations for all but one of the species. Results from coalescent simulations designed to model our study system indicated that the genetic impacts of the dam will likely be detectable approximately 40–60 generations after the dam was constructed, and that it is possible to largely mitigate these impacts with a fish passage strategy that facilitates a migration rate of ≥ 1% between above and below dam populations. In summary, our findings suggest the genetic impacts of dams can be relatively minimal on short time scales, and that fish passage strategies can significantly reduce genetic impacts if designed appropriately.

Wisconsin↗
USGS2014

Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska

Water resources in the North and South Platte River valleys of Nebraska, including the valley of Lodgepole Creek, are critical to the social and economic health of the area, and for the recovery of threatened and endangered species in the Platte River Basin. Groundwater and surface water are heavily used resources, and uses are regulated in the study area. Irrigation is the dominant water use and, in most instances, is supplied by both groundwater and surface-water sources. The U.S. Geological Survey and its partners have collaborated to use airborne geophysical surveys for areas of the North and South Platte River valleys including the valley of Lodgepole Creek in western Nebraska. The objective of the surveys was to map the aquifers and underlying bedrock topography of selected areas to help improve the understanding of groundwater–surface-water relations to guide water-management decisions. This project was a cooperative study involving the North Platte Natural Resources District, the South Platte Natural Resources District, the Twin Platte Natural Resources District, the Conservation and Survey Division of the University of Nebraska-Lincoln, and the Nebraska Environmental Trust. This report presents the interpreted base-of-aquifer surface for part of the area consisting of the North Platte Natural Resources District, the South Platte Natural Resources District, and the Twin Platte Natural Resources District. The interpretations presented herein build on work done by previous researchers from 2008 to 2009 by incorporating additional airborne electromagnetic survey data collected in 2010 and additional test holes from separate, related studies. To make the airborne electromagnetic data useful, numerical inversion was used to convert the measured data into a depth-dependent subsurface resistivity model. An interpretation of the elevation and configuration of the base of aquifer was completed in a geographic information system that provided x, y, and z coordinates. The process of interpretation involved manually picking locations (base-of-aquifer elevations) on the displayed airborne electromagnetic-derived resistivity profile by the project geophysicist, hydrologist, and geologist. These locations, or picks, of the base-of-aquifer elevation (typically the top of the Brule Formation of the White River Group) were then stored in a georeferenced database. The pick was made by comparing the inverted airborne electromagnetic-derived resistivity profile to the lithologic descriptions and borehole geophysical logs from nearby test holes. The database of interpretive picks of the base-of-aquifer elevation was used to create primary input for interpolating the new base-of-aquifer contours. The automatically generated contours were manually adjusted based on the interpreted location of paleovalleys eroded into the base-of-aquifer surface and associated bedrock highs, many of which were unmapped before this study. When contours are overlain by the water-table surface, the saturated thickness of the aquifer can be computed, which allows an estimate of total water in storage. The contours of the base-of-aquifer surface presented in this report may be used as the lower boundary layer in existing and future groundwater-flow models. The integration of geophysical data into the contouring process facilitated a more continuous and spatially comprehensive view of the hydrogeologic framework.

Nebraska↗
USGS2024

Survey effort and targeted landbird community metrics at Indiana lowland forest restoration sites

Many sampling and analytical methods can estimate the abundance, distributions, and diversity of birds and other wildlife. However, challenges with sample size and analytical capacity can make these methods difficult to implement for resource-limited monitoring programs. To apprise efficient and attainable sampling designs for landbird monitoring programs with limited observational data, we used breeding season bird point survey data collected in 2016 at four forest restoration sites in Indiana, USA. We evaluated three subsets of observed species richness, total possibly breeding landbirds, Partners in Flight Regional Conservation Concern (PIF RCC) landbirds, and interior forest specialists (IFSs). Simulated surveys based on field data were used to conduct Bayesian Michaelis–Menten curve analyses estimating observed species as a function of sampling effort. On comparing simulated survey sets with multiple habitat types versus those with one habitat, we found that those with multiple habitat types had estimated 39%–83% greater observed PIF RCC species richness and required 41%–55% fewer visits per point to observe an equivalent proportion of PIF RCC species. Even with multiple habitats in a survey set, the number of visits per point required to detect 50% of observable species was 30% higher for PIF RCC species than for total breeding landbird species. Low detection rates of IFS species at two field sites made precise estimation of required effort to observe these species difficult. However, qualitatively, we found that only sites containing mature forest fragments had detections of several bird species designated as high-confidence IFS species. Our results suggest that deriving specialized species diversity metrics from point survey data can add value when interpreting those data. Additionally, designing studies to collect these metrics may require explicitly planning to visit multiple habitat types at a monitoring site and increasing the number of visits per survey point.

Indiana↗
USGS2020

The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011. The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies. Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.

Florida↗
USGS1994

San Francisco Bay/delta regional monitoring program plankton and water quality pilot study, 1993, in 1993 Annual Report, San Francisco Estuary Regional Monitoring Program for Trace Substances: San Francisco Estuary Institute

The pilot program described here is motivated by a fundamental principle of the Regional Monitoring Strategy, namely “...the development of data that will provide information on status and trends in the Estuary.” As pointed out in the Strategy, knowledge of status and trends serves two primary purposes: (1) to become aware of or anticipate deleterious conditions in the Estuary, and (2) to assess the effectiveness of management actions. This program addresses these two purposes by focusing on aquatic resources, one of the five key management issues identified by the Comprehensive Conservation and Management Plan and central to the Regional Monitoring Strategy. It also bears on at least two of the other management issues - pollutants and water use. A regional monitoring program must cover many types of resources, including pelagic and benthic channel habitat, shoal habitat, wetlands, river channels, sloughs, and small bays and harbors. This particular program centers on the pelagic channel habitat. However, because of the intimate connection between channel habitat and many or most of these other habitats, channel measurements reflect to some extent the status of and trends in other resource types as well. A primary aim of this program is to provide a high-resolution description of critical aspects of habitat quality, which can be used along with other information (1) to determine the suitability of habitat for aquatic resources; (2) to monitor responsiveness of the habitat to freshwater flow variability; and (3) to provide a context for understanding pollutant distributions. In a single transect, measurements are made throughout the water column at up to 37 stations to define physical (salinity, temperature, suspended particulate matter, and light penetration), chemical (dissolved oxygen) and biological (chlorophyll a ) characteristics that influence both chemical and biological reactions. A second aim of the program is to investigate planktonic indicators of ecosystem structure and function. Phytoplankton production is the major single source of energy for the San Francisco Bay food web. Our measurements of chlorophyll and light penetration can be used to provide an estimate of this production, and therefore the availability of food for organisms at higher trophic levels. Phytoplankton community composition at the species level, which can be a sensitive indicator of habitat change, is also a standard component of this program. Community composition data enable detection of species known to be responsible for harmful or nuisance algal blooms. In 1993, two other indicators were also evaluated, photosynthetic parameters and water column respiration . Photosynthetic parameters partially characterize the physiological state of the phytoplankton and may provide indirect evidence of nutrient deficiency or the effects of pollutants. Water column respiration serves as a simple integrated measure of organic matter metabolism by the plankton, including bacteria, phytoplankton, and microzooplankton. It therefore reflects the total supply of organic matter, whether from photosynthesis, tidal marsh efflux, point sources, or upstream in the Delta. These biological indicators therefore contain much information about the flow of energy into the food web.

California↗
USGS2013

A natural resource condition assessment for Sequoia and Kings Canyon National Parks: Appendix 14: plants of conservation concern

Sequoia and Kings Canyon National Parks are located in the California Floristic Province, which has been named one of world‘s hotspots of endemic biodiversity (Myers et al. 2000). The California Floristic Province is the largest and most important geographic floristic unit in California and extends from the Klamath Mountains of southwestern Oregon to the northwestern portion of Baja California (Hickman 1993). The Sierra Nevada, one of six regions that make up the California Floristic Province, covers nearly 20% of the land in California yet contains over 50% of its flora. Within the Sierra Nevada, the southern Sierra supports more Sierran endemic and rare plant taxa than the central and northern portions of the region (Shevock 1996). Sequoia and Kings Canyon National Parks (SEKI) encompass roughly 20% of the southern Sierra Nevada region. The parks overlap three floristic subregions (central Sierra Nevada High, southern Sierra Nevada High, and southern Sierra Nevada Foothills), and border the Great Basin Floristic Province. The parks support a rich and diverse vascular flora composed of over 1,560 taxa. Of these, 150 taxa are identified as having special status. The term special status is applied here to include taxa that are state or federally listed, rare in California, or at risk because they have a limited distribution. Only one species from these parks is listed under the state or federal Endangered Species Acts ( Carex tompkinsii , Tompkins‘ sedge, is listed as a rare species under the California Endangered Species Act), and one species is under review for federal endangered listing ( Pinus albicaulis , whitebark pine). However, an absence of threatened and endangered species recognized by Endangered Species Acts is not equivalent to an absence of species at risk. There are 83 plant taxa documented as occurring in SEKI that are considered imperiled or vulnerable in the state by the California Department of Fish and Game‘s California Natural Diversity Database (CNDDB 2010a). There are an additional 66 taxa not formally listed by CNDDB that are recognized as having special status because their distribution is restricted to the Sierra Nevada. Special status plants are distributed throughout the two parks and inhabit a wide range of environments along the length of the elevation gradient that characterizes these parks. Ideally, we would assess the condition (status and trends) of each of the taxa on the SEKI special status plant list, documenting current population sizes, demographic rates and demographic trends. We would also hope to quantify the effects of individual stressors on each species based on existing monitoring and research. However, no data are available for most of the species on the special status plant list. For those few species (12 herbaceous species and two tree species) for which we possess some change over time information, the data are not adequate to make a competent assessment. Note that we have not explored the tree demographic information in any detail, as is covered in the NRCA Intact Forest/Five Needle Pines and Sequoia chapters. In general, we are unable to present an ‗integrity‘ metric for special status species in the parks, since the data to quantify the condition of each species in such a manner is not available. In contrast, the park does possess substantial data describing biodiversity in the parks. Therefore, our analysis focuses on describing the distribution and rarity of special status plants within the parks, with a particular focus on assessing the spatial distribution of species richness. We hope that such information will prove useful to park managers in determining which areas in the parks merit the most attention (for example in developing monitoring protocols). We also assess potential vulnerability of special status species to the stressors chosen by the NRCA working group, using both park data and available literature. As a first step, we spent considerable effort updating and refining the criteria for the special status plant list, as this list defines which taxa are considered in our assessment. Observation data of these species was then compiled from all known sources in order to provide a comprehensive view of where special status plants have been documented and, ultimately, to enable the most informed determinations of areas in the parks that potentially support the highest number of rare and endemic taxa. These ‗hot spot‘ analyses are presented by geographic region, vegetation type and elevation. For these and other analyses presented in this report, we place more focus on summarizing findings for the herbaceous and shrub special status taxa than on special status trees. The trees which qualify as special status are the focus of other NRCA chapters, including Giant Sequoia and Intact Forests/Five-needle Pines. We do, however, present their mapped distributions and provide overviews of research related to the special status tree taxa in the Stressors section of this report.

California↗
USGS2010

Analysis and simulation of water-level, specific conductance, and total phosphorus dynamics of the Loxahatchee National Wildlife Refuge, Florida, 1995-2006

The Arthur R. Marshall Loxahatchee Wildlife Refuge (Refuge) was established in 1951 through a license agreement between the South Florida Water Management District and the U.S. Fish and Wildlife Service (USFWS) as part of the Migratory Bird Conservation Act. Under the license agreement, the State of Florida owns the land of the Refuge and the USFWS manages the land. Fifty-seven miles of levees and borrow canals surround the Refuge. Water in the canals surrounding the marsh is controlled by inflows and outflows through control structures. The transport of canal water with higher specific conductance and nutrient concentrations to the interior marsh has the potential to alter critical ecosystem functions of the marsh. Data-mining techniques were applied to 12 years (1995-2006) of historical data to systematically synthesize and analyze the dataset to enhance the understanding of the hydrology and water quality of the Refuge. From the analysis, empirical models, including artificial neural network (ANN) models, were developed to answer critical questions related to the relative effects of controlled releases, precipitation, and meteorological forcing on water levels, specific conductance, and phosphorous concentrations of the interior marsh. Data mining is a powerful tool for converting large databases into information to solve complex problems resulting from large numbers of explanatory variables or poorly understood process physics. For the application of the linear regression and ANN models to the Refuge, data-mining methods were applied to maximize the information content in the raw data. Signal processing techniques used in the data analysis and model development included signal decomposition, digital filtering, time derivatives, time delays, and running averages. Inputs to the empirical models included time series, or signals, of inflows and outflows from the control structures, precipitation, and evapotranspiration. For a complex hydrologic system like the Refuge, the statistical accuracy of the models and predictive capability were good. The water-level models have coefficient of determination (R 2 values ranging from 0.90 to 0.98. The R 2 for the specific conductance model is 0.82, and the R2 for the total phosphorus model is 0.51. The accuracy of the models was attributable to the quantity and quality of the available data. To make the models directly available to all stakeholders, an easy-to-use decision support system (DSS) called the Loxahatchee Artificial Neural Network Model (LOXANN) DSS was developed as a spreadsheet application that integrates the historical database, linear regression and ANN models, model controls, streaming graphics, and model output. The LOXANN DSS allows Refuge managers and other users to easily execute the water level, specific conductance, and phosphorous models to evaluate various water-resource management scenarios. The user is able to choose from three options in setting the control-structure flows: as a percentage of historical flow, as a constant flow, or as a user-defined hydrograph. Output from the LOXANN DSS includes tabular time series of predictions of the measured data and predictions of the user-specified conditions. A three-dimensional visualization routine also was developed that displays longitudinal specific conductance conditions. Two scenarios were simulated with the LOXANN DSS. One scenario increased the historical flows at four control structures by 40 percent. The second scenario used a user-defined hydrograph to set the outflow from the Refuge to the weekly average inflow to the Refuge delayed by 2 days. Both scenarios decreased the potential of canal water intruding into the marsh by decreasing the slope of the water level between the canals and the marsh.

Scientific Investigations Report↗
USGS2004

Status of sea otter populations in southcentral and southeast Alaska, 2002-2003

During the years 2002-2004 estimated sea otter population sizes were calculated for Southeast Alaska, Prince William Sound, and the Kenai Peninsula and Cook Inlet regions of Alaska. Aerial surveys were conducted by a single observer from a float-equipped Bellanca Scout fixed-wing aircraft flying at 91 m altitude and 65 mph. The surveys followed protocols written by Bodkin and Udevitz (1999). The survey design consisted of systematic sampling of 400 m wide transects that were uniformly placed throughout the survey area. Selection and sampling of transects was proportional to expected sea otter abundance, with most effort taking place in transects over waters 0-40 m in depth. Intensive searches were periodically conducted within transects to estimate the proportion of sea otters not detected on strips. To obtain an adjusted population size estimate, strip counts are adjusted for the area not surveyed and by a correction factor.

Alaska↗
USGS2014

Using passive integrated transponder (PIT) systems for terrestrial detection of blue-spotted salamanders (Ambystoma laterale) in situ

Pure-diploid Blue-spotted Salamanders ( Ambystoma laterale ) are the smallest members of the family Ambystomatidae which makes tracking with radio-transmitters difficult because of small battery capacity. Passive integrated transponder (PIT) tags provide another tracking approach for small fossorial animals such as salamanders. We evaluated the use of portable PIT tag readers (PIT packs) to detect PIT tag-implanted pure-diploid Blue-spotted Salamanders in situ. We also examined the detection probability of salamanders with PIT tags held in enclosures in wetland and terrestrial habitats, as well as the underground detection range of PIT packs by scanning for buried tags not implanted into salamanders. Of the 532 PIT tagged salamanders, we detected 6.84% at least once during scanning surveys. We scanned systematically within a 13.37 ha area surrounding a salamander breeding pool on 34 occasions (~119 hours of survey time) and detected PIT tags 74 times. We detected 55% of PITs in tagged salamanders and 45%were expelled tags. We were able to reliably detect buried PIT tags from 1–22cm below the ground surface. Because nearly half the locations represented expelled tags, our data suggest this technique is inappropriate for future studies of pure-diploid Blue-spotted Salamanders, although it may be suitable for polyploid Blue-spotted Salamanders and other ambystomatid species, which are larger in size and may exhibit higher tag retention rates. It may also be prudent to conduct long-term tag retention studies in captivity before tagging and releasing salamanders for in situ study, and to double-mark individuals.

Herpetological Conservation and Biology↗