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USGS2000

Climate change impacts on southeastern U.S. basins

The work described herein aims to assess the impacts of potential climate change on the Apalachicola-Chattahoochee-Flint (ACF) and Alabama-Coosa-Talapoosa (ACT) river basins in the Southeastern US. The assessment addresses the potential impacts on watershed hydrology (soil moisture and streamflow) and on major water uses including water supply, drought management, hydropower, environmental and ecological protection, recreation, and navigation. This investigation develops new methods, establishes and uses an integrated modeling framework, and reaches several important conclusions that bear upon river basin planning and management. Although the specific impacts vary significantly with the choice of the GCM scenario, some general conclusions are that (1) soil moisture and streamflow variability is expected to increase, and (2) flexible and adaptive water sharing agreements, management strategies, and institutional processes are best suited to cope with the uncertainty associated with future climate scenarios.

Open-File Report↗

USGS2023

Evaluating management alternatives for Wyoming elk feedgrounds in consideration of chronic wasting disease

Executive Summary The authors used decision and modeling analyses to evaluate management alternatives for a decision on whether to permit Cervus canadensis (elk) feeding on two sites on Bridger-Teton National Forest, Dell Creek and Forest Park. Supplemental feeding of elk could increase the transmission of chronic wasting disease (CWD) locally and disease spread regionally, potentially impacting elk populations over time with wider implications for Odocoileus hemionus (mule deer) and Odocoileus virginianus (white-tailed deer) populations and hunting, tourism, and regional revenue. Supplemental feeding is thought to improve overwinter elk survival and reduce the commingling of elk with cattle during months when brucellosis transmission risk is highest. We worked with the U.S. Department of Agriculture Forest Service to identify their fundamental objectives and associated performance metrics related to this feedground decision. We then developed disease and habitat selection models to quantify the effect of four management alternatives on select performance metrics. The four alternatives were to continue to permit feeding, phaseout permits to feed in three years, permit feeding on an emergency basis, or stop permitting feeding. In this report, we present methods and summarized results on disease and habitat selection models and summaries of other performance metrics analyzed by BIO-WEST, Inc. and Cirrus Ecological Solutions as part of an Environmental Impact Statement. Data from Wyoming Game and Fish Department (WGFD) supported the assumption that supplemental elk feeding allows for larger elk populations in a region. We documented that herd units (HU) without feedgrounds had 23 percent lower densities of elk per area of winter range when compared against HUs with feedgrounds, after accounting for differences in sightability of elk during counts on and off feedgrounds. Thus, throughout our analyses, we assumed feedground closures would reduce elk carrying capacity resulting in an average decline of previously fed elk population segments by 23 percent (5th and 95th percentiles = [11 percent, 35 percent]) by year 20. Most of that decline occurred within the first few years after a feedground ceases to operate. We used a panel of CWD experts to help estimate CWD trans-mission in fed and unfed elk population segments. In aggregate, the expert panel estimated that median values of direct and indirect transmission of CWD are expected to be 1.9 and 4 times higher, respectively, in fed elk populations compared to unfed elk. We used these disease transmission estimates in combination with local elk demographic rates and carrying capacity estimates to project disease and population dynamics. In year 20, we predicted CWD prevalence would increase to 42 percent (5th and 95th percentiles = [29 percent, 55 percent]), and 13 percent (5th and 95th percentiles = [4 percent, 26 percent]) on average for fed and unfed elk population segments, respectively, given a starting prevalence of 1.6 percent. The prevalence estimates for the unfed elk population segments are in the range of previous observations of CWD in elk in the western United States. The average CWD prevalence from 2016 to 2018 in the unfed elk population of Wind Cave National Park in South Dakota was 18 percent overall but up to 30 percent in some regions (Sargeant and others, 2021). Meanwhile, CWD prevalence in the Iron Mountain and Laramie Peak elk herds in Wyoming from 2016 to 2018 was 14 percent and 7 percent, respectively, despite being present since at least 2002 (Wyoming Game and Fish Department, 2020b). From 2016 to 2020, elk that were fed at Dell Creek and Forest Park constituted on average 12–20 percent of the total elk on their respective HUs. As a result, the differences between management alternatives are modest when considering the closure of only one feedground on a HU. The no feeding alternative for Forest Park resulted in a CWD prevalence of 17 percent (SD = 7 percent) in the Afton HU compared to 20 percent (SD = 7 percent) with continued feeding by year 20. In the Upper Green River HU, no feeding on Dell Creek resulted in a CWD prevalence of 27 percent (SD = 6 percent) compared to 30 percent (SD = 5 percent) with continued feeding. In terms of disease-associated mortality, we predicted the closure of Forest Park and Dell Creek feedgrounds would reduce the total number of CWD mortalities by 9 percent in the Upper Green River HU and 26 percent in the Afton HU during the 20-year timespan. Our spatial analyses predicted that management alternative effects vary by HU as a function of private property and other wildlife winter ranges proximity relative to feedground location. The predicted number of elk abortions on private land, as a proxy for brucellosis risk to cattle, may increase by 8–21 percent in the absence of feeding at Dell Creek and Forest Park. Eight feedgrounds are located on Bridger-Teton National Forest, all of which have permits that have expired or will expire prior to 2028. In addition, WGFD could change their management of feedgrounds given new information; therefore, we also assessed the cumulative effects of continued feeding, phaseout, and no feeding management alternatives across five HUs south of Jackson, Wyoming (Afton HU, Fall Creek HU, Piney HU, Pinedale HU, and Upper Green River HU). These five HUs ranged from about 41 to 85 percent of the elk herd using feedgrounds, which corresponded to a CWD prevalence at year 20 of 23–34 percent if all feedgrounds in those five HUs remained open relative to 12 to 14 percent if all feedgrounds were closed. We predicted feedground closures may result in immediate reductions in population size relative to alternatives that continue feeding (for example, continued feeding and emergency feeding alternatives); however, over longer periods of time, CWD-associated mortality leads to larger population reductions. The no feeding alternative resulted in higher elk population sizes compared to the continued feeding alternative after about 10 years of implementation. Delayed action under a phaseout alternative resulted in increasing the CWD prevalence to 20 percent relative to 12 to 14 percent, on average, without feeding on HUs with a large population of fed elk such as the Upper Green River HU. Summarizing our cumulative results across all five of the analyzed HUs, we predicted continued feeding will lead to fewer elk by year 20 (mean = 8,300, standard deviation [SD] = 740) compared to no feeding at U.S. Department of Agri-culture Forest Service sites (10,700, SD = 890). The closure of all feedgrounds was projected to result in the largest elk populations at year 20 (12,500, SD = 980). No feeding at all sites also resulted in the largest cumulative harvest of 57,700 (SD = 2,600) compared to 51,100 (SD = 3,800) for continued feeding at all current feedground sites on the five HUs. Continued feeding also resulted in the lowest brucellosis costs to producers ($194,600, SD = $11,500) compared to no feeding on all feedgrounds ($243,000, SD = $13,700). Assuming moderate reductions in hunter interest because of increasing CWD prevalence in elk, we predicted that no feeding resulted in regional revenues generated by hunting activities of $190 million (SD = $10 million) compared to $173 million (SD = $10 million) for continued feeding over the 20-year timeframe. Recent CWD detections in mule deer and elk in Grand Teton National Park has elevated the importance of the cur-rent decision on whether, and how, to permit elk feeding on Dell Creek and Forest Park and the management of the other feedgrounds. Aggressive male harvest has slowed, but not stopped, the increasing prevalence of CWD in mule deer (Conner and others, 2021). It is unclear whether harvest management can be an effective tool to slow the spread of CWD in elk. There are also no effective treatments or vaccines for CWD, and it is unlikely that any will be developed that can be easily deployed in the near future. Thus, reducing artificial aggregations is one of the few management approaches suggested by the Western Association of Fish and Wildlife Agencies (Almberg and others, 2017). Future surveillance and monitoring can be designed to resolve uncertainties that can improve future decision-making. If feedgrounds close, research could quantify elk population reductions in the absence of feeding, the redistribution of fed elk to other places, or the consequences of elk movement on private property. If feedgrounds remain open, research could assess how rapidly CWD spreads in artificial aggregations of elk; however, surveillance programs would need to be designed with sufficient power to detect initial changes of CWD prevalence. Delaying action on feedground management was projected to be costly. Results of the phaseout alternative relative to the no feeding alternative suggested a 3-year delay was enough for substantial long-term changes in CWD prevalence. The long-term persistence of infectious CWD prions in the environment suggests that feedground management decisions may have long-lasting consequences. Our results indicated tradeoffs in the ability of a management agency to achieve all their objectives, and all management alternatives resulted in significant reductions in elk population size. This report contains the foundational elements for formal decision analysis methods, which can be implemented to help decision makers transparently evaluate the consequences of decision alternatives and identify the set of actions that best achieve agency and stakeholder priorities.

Wyoming↗

USGS2021

Sediment budget for watersheds of West Maui, Hawaii

Episodic runoff brings suspended sediment to West Maui’s nearshore waters, turning them from blue to brown. This pollution degrades the ecological, cultural, and recreational value of these iconic nearshore waters. We used mapping, monitoring, and modeling to identify and quantify the watershed sources for fine sediment that pollutes the nearshore each year. These results focus strategies to reduce pollution on the outstanding sources for this sediment. Terrestrial runoff causing coastal plumes now occurs when two or more hours of rain falls at rates greater than 10–20 millimeter (mm) per hour in source watersheds. Analysis of recent and historical rainfall indicates that West Maui communities can expect rainfalls to bring coastal plumes at least 3–5 times per year. Former agricultural fields and some unimproved roads are possible sources for the fine sediment of these plumes. We found, however, that these obvious sources do not produce plumes during small annual storms, because they drain water at rates that far exceed most annual rainfalls and because there is no evidence for runoff from rains that caused recent plumes. Streambanks now eroding into historic fill terraces of sands, silts, and clays are a more plausible source. These terraces are found only downstream of historical agricultural fields and are composed of silt and fine sand. Surveys show that the fill terraces occupy ~40 percent of streambank length, making them extensive. During 2015–2016, these deposits eroded at median rates of 5–24 mm per year. Summed over West Maui’s watersheds, these rates imply sediment loads carried to the coast that can be ten times or more than modeled pre-human values. A sediment budget indicates that bank erosion of fill terraces from a few watersheds likely dominates the current annual fine-sediment load to the nearshore, with Kahana Stream watershed producing the largest annual input of 285 metric tons, the equivalent of 29 dump-truck loads every year. Although past large storms have contributed to sediment loading, annual plume generation is now caused by smaller rainfalls eroding these near-stream terrace deposits, a legacy of historic agriculture. Treatments of former agricultural fields, roads, and reserve forests are consequently not likely to measurably effect sediment pollution from smaller, more frequent storms. Increased runoff from residential and commercial development of West Maui has the potential to exacerbate sediment plumes from such storms.

Hawaii↗

USGS2019

Let’s agree to disagree: Comparing auto-acoustic identification programs for northeastern bats

With the declines in abundance and changing distribution of white-nose syndrome–affected bat species, increased reliance on acoustic monitoring is now the new “normal.” As such, the ability to accurately identify individual bat species with acoustic identification programs has become increasingly important. We assessed rates of disagreement between the three U.S. Fish and Wildlife Service–approved acoustic identification software programs (Kaleidoscope Pro 4.2.0, Echoclass 3.1, and Bat Call Identification 2.7d) and manual visual identification using acoustic data collected during summers from 2003 to 2017 at Fort Drum, New York. We assessed the percentage of agreement between programs through pairwise comparisons on a total nightly count level, individual file level (e.g., individual echolocation pass call file), and grouped maximum likelihood estimate level (e.g., probability values that a species is misclassified as present when in fact it is absent) using preplanned contrasts, Akaike Information Criterion, and annual confusion matrices. Interprogram agreement on an individual file level was low, as measured by Cohen's Kappa (0.2–0.6). However, site-night level pairwise comparative analysis indicated that program agreement was higher (40–90%) using single season occupancy metrics. In comparing analytical outcomes of our different datasets (i.e., how comparable programs and visual identification are regarding the relationship between environmental conditions and bat activity), we determined high levels of congruency in the relative rankings of the model as well as the relative level of support for each individual model. This indicated that among individual software packages, when analyzing bat calls, there was consistent ecological inference beyond the file-by-file level at the scales used by managers. Depending on objectives, we believe our results can help users choose automated software and maximum likelihood estimate thresholds more appropriate for their needs and allow for better cross-comparison of studies using different automated acoustic software.

Journal of Fish and Wildlife Management↗

USGS1997

Water quality variability in San Francisco Bay, Some gGeneral lessons from 1996 sampling: 1996 annual report, San Francisco estuary regional monitoring program for trace substances

This report describes the results from the 1996 Regional Monitoring Program for Trace Substances (RMP). It is the fourth Annual Report from the RMP which began in 1993 and attempts to synthesize the most obvious data patterns from the last four years. This report includes data from Base Program monitoring activities, as well as results of Pilot and Special Studies conducted or completed in 1996. Additionally, several articles contributed by RMP investigators and others, are included. These articles provide perspective and insight on important contaminant issues identified by the RMP. This summary addresses which kinds of pollutants measured by the RMP appear to be at levels that warrant concern, what kinds of trends may be discerned, and which stations have consistently shown elevated contaminant levels. The goals or general objectives of the RMP are: 1. To obtain high quality baseline data describing the concentrations of toxic and potentially toxic trace elements and organic contaminants in the water and sediment of the San Francisco Estuary. 2. To determine seasonal and annual trends in chemical and biological water quality in the San Francisco Estuary. 3. To continue to develop a data set that can be used to determine long-term trends in the concentrations of toxic and potentially toxic trace elements and organic contaminants in the water and sediments of the San Francisco Estuary. 4. To determine whether water quality and sediment quality in the Estuary at large are in compliance with objectives established by the Basin Plan (the regulatory planning document used by the Regional Water Quality Control Board). 5. To provide a database on water and sediment quality in the Estuary which is compatible with data being developed in other ongoing studies, including wasteload allocation studies and model development, sediment quality objectives development, in-bay studies of dredged material disposal, Interagency Ecological Program (IEP) water quality studies, primary productivity studies, local effects biomonitoring programs, and state and federal mussel watch programs.

California↗

USGS2022

Distribution probability of the Virginia northern flying squirrel in the High Allegheny Mountains

In the central Appalachians of Virginia and West Virginia, the Virginia northern flying squirrel ( Glaucomys sabrinus fuscus ; VNFS) is a subspecies of northern flying squirrel generally associated with red spruce ( Picea rubens )-dominated forests at high elevations. Listed as endangered by the U.S. Fish and Wildlife Service from 1985 to 2013, the VNFS currently is the subject of a 10-year post-delisting assessment. Still considered a state-listed species in Virginia and a species of greatest conservation need in West Virginia, the VNFS serves as a focal target for red spruce restoration activities in the High Allegheny Region (HAR) of the two states. Owing to the cryptic nature of VNFS and its low detection probability in live-capture surveys, managers in the region rely on habitat models to assess probable presence. Using long-term nest-box, live-trapping, and radio-telemetry data matched with updated high elevation forest-type coverage data for the region, we created a new VNFS resource selection function and spatial coverage map. Inputting red spruce cover, increasing elevation, and decreasing landform index (increasing site shelteredness) composed the best model explaining VNFS occurrence. The calculated amount of low-quality habitat was congruent with previous modeling efforts; however, inclusion of more VNFS occurrence records in the current effort indicated that previous efforts substantially underestimated the amount (>400%) of extant high quality VNFS habitat. We estimate the HAR to contain approximately 197,952 ha with ≥0.50 predicted probability of occurrence of VNFS. In addition to potentially improving current and future VNFS live-capture surveys, with this model managers may better target forests for red spruce restoration to increase high elevation forest ecological integrity and to improve habitat patch connectedness for VNFS.

Maryland, Virginia, West Virginia↗

USGS2021

Evaluation of hydrologic simulation models for fields with subsurface drainage to mitigated wetlands in Barnes, Dickey, and Sargent Counties, North Dakota

Proper identification of wetlands, along with a better understanding of the hydrology of mitigated wetlands, is needed to assist with conservation efforts aimed at maintaining the productivity and ecological function (wetland mitigation) of agricultural lands. The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, completed a study to evaluate two models for simulating hydrologic conditions in fields with subsurface drainage to mitigated wetlands at several sites in North Dakota. These two models were evaluated as possible tools for water resource managers to use for designing wetland mitigation projects in the area in the future. The Soil-Plant-Atmosphere-Water (SPAW) model simulates the daily hydrologic water budgets of agricultural landscapes by two linked routines, one for farm fields (field hydrology) and one for impoundments such as wetlands and ponds (pond model). The DRAINMOD model was used in conjunction with the SPAW model because although the SPAW model can be used to simulate the hydrology of small drainage basins containing wetlands, the SPAW model does not contain routines to simulate drainage, either subsurface drainage or surface (drainage ditches), that can directly affect the wetland hydrology. The wetlands in the study areas in this report are all downstream from and adjacent to drained agricultural fields. SPAW and DRAINMOD models were developed and calibrated at three study areas (study areas B, D, and S) to evaluate how the models simulated field-scale hydrologic characteristics and the water balance in wetlands from January 1, 2003, through December 31, 2018. The SPAW model developed for study area B included five modeled fields in the field hydrology portion of SPAW that contributed inflow to one wetland simulated in the pond model portion of SPAW. Simulated wetland water depths were most similar to water depths measured at site BWET1, with an absolute mean error of 0.10 foot and a root mean square error of 0.14 foot. Site BWET2 had slightly larger errors, with an absolute mean error of 0.22 foot and a root mean square error of 0.28 foot. Simulated water depths were similar to the pattern of measured water depths at BWET1 and BWET2 from about mid-April 2018 through about mid-September 2018, but overpredicted water depths in the fall from about mid-September 2018 through about mid-October 2018. The SPAW model developed for study area D included six modeled fields in the field hydrology portion of SPAW that contributed inflow to five wetlands connected in series in the pond model portion of SPAW. Simulated water depths compared relatively well to water depths in the five wetlands, with the absolute mean error ranging from 0.17 foot (DWET1) to 0.39 foot (DWET2), and the root mean square error ranging from 0.28 foot (DWET1) to 0.56 foot (DWET5). The SPAW model developed for study area S included one modeled field in the field hydrology portion of SPAW that contributed inflow to one wetland in the pond model portion of SPAW. Among the SPAW models developed for the three study areas, the model for study area S had the best comparison between simulated and measured water depths, with an absolute mean error of 0.06 foot and a root mean square error of 0.10 foot. DRAINMOD models were developed and calibrated at the three study areas and provided inflow from subsurface drainage discharge to the SPAW models for simulating water levels in wetlands in the study areas. The calibrated DRAINMOD model for study area B showed the variability of hydrologic processes in the modeled field throughout the wide range of hydrologic conditions from January 1, 2003, through December 31, 2018. In general, the discharge through the modeled subsurface drainage system was in the spring and early summer (April through June) most years, with little to no discharge later in the year. Although the subsurface drainage system in study area D was the most complex among the three study areas and was simplified into a uniform system within DRAINMOD, simulated water table depths at study area D correlated better to measured water table depths compared to results from the model applications at the other two study areas. Simulated water table depths had an absolute mean error of 0.30 foot and root mean square error of 0.37 foot at site DGW1 and an absolute mean error of 0.29 foot and a root mean square error of 0.34 foot at site DGW2. Although the subsurface drainage system in study area S was the simplest and the modeled field was the smallest among the three study areas, simulated water table depths at study area S did not correlate as well to measured water table depths compared to results from the model applications at the other two study areas. The SPAW and DRAINMOD model applications at the three study areas in southeast North Dakota adequately simulated the hydrologic processes for fields with subsurface drainage that are connected to adjacent wetlands. However, more measured data would be needed to fully evaluate the models throughout the range of possible climatic conditions.

North Dakota↗

USGS2024

Predictor importance in habitat suitability models for invasive terrestrial plants

Aim Due to the socioeconomic and environmental damages caused by invasive species, predicting the distribution of invasive plants is fundamental for effectively targeting management efforts. A habitat suitability model (HSM) is a powerful tool to predict potential habitat of invasive species to help guide the early detection of invasive plants. Despite numerous studies of the predictors used in HSMs, there is little consensus about the most appropriate predictors to use in creating ecologically realistic predictions from HSMs. Location The contiguous United States. Methods We explore 220 invasive terrestrial plant species' existing HSMs constructed with consistent modelling algorithms, background generation methods, predictor resolution, and geographic extent, and calculate the relative importance of predictors for each species. We sort predictors into eight groups (topography, temperature, disturbance, atmospheric water, landscape water, substrate, biotic interaction, and radiation) and compare the importance of predictor groups by plant lifeforms and phylogenetic relatedness. Results Human modification and minimum winter temperature were generally the two highest performing individual predictors across the species studied. The highest-performing predictor groups were disturbance, temperature, and atmospheric water. Across lifeforms, there were minimal differences in the influences of predictor groups, although woody plant models exhibited the largest differences in predictor importance when compared with non-woody plant models. Additionally, we found no significant relationship between the importance of predictor groups and phylogenetic relatedness. Main Conclusions This study has implications for informing predictor selection in invasive plant HSMs, leading to more reliable and accurate models of invasive terrestrial plants. Our results emphasize the need to critically select predictors included in HSMs, with special consideration to temperature and disturbance predictors, to accurately predict habitat of invasive plant for detection and response of invasive plant species. With more accurate predictions, managers will be better prepared to address invasive species and reduce their threats to landscapes.

Diversity and Distributions↗

USGS2016

A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation

Conserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 days of flight with a mean seasonal survivorship of 90.5% (95% CI = 89.2%, 91.9%) whereas spring migration took a mean of 23.5 days of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1,036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.

Ecological Applications↗

USGS2013

Seasonal climate variation and caribou availability: Modeling sequential movement using satellite-relocation data

Livelihood systems that depend on mobile resources must constantly adapt to change. For people living in permanent settlements, environmental changes that affect the distribution of a migratory species may reduce the availability of a primary food source, with the potential to destabilize the regional social-ecological system. Food security for Arctic indigenous peoples harvesting barren ground caribou ( Rangifer tarandus granti ) depends on movement patterns of migratory herds. Quantitative assessments of physical, ecological, and social effects on caribou distribution have proven difficult because of the significant interannual variability in seasonal caribou movement patterns. We developed and evaluated a modeling approach for simulating the distribution of a migratory herd throughout its annual cycle over a multiyear period. Beginning with spatial and temporal scales developed in previous studies of the Porcupine Caribou Herd of Canada and Alaska, we used satellite collar locations to compute and analyze season-by-season probabilities of movement of animals between habitat zones under two alternative weather conditions for each season. We then built a set of transition matrices from these movement probabilities, and simulated the sequence of movements across the landscape as a Markov process driven by externally imposed seasonal weather states. Statistical tests showed that the predicted distributions of caribou were consistent with observed distributions, and significantly correlated with subsistence harvest levels for three user communities. Our approach could be applied to other caribou herds and could be adapted for simulating the distribution of other ungulates and species with similarly large interannual variability in the use of their range.

Alaska, Yukon Territory↗

USGS2022

Ecologically relevant moisture and temperature metrics for assessing dryland ecosystem dynamics

In drylands, water-limited regions that cover ~40% of the global land surface, ecosystems are primarily controlled by access to soil moisture and exposure to simultaneously hot and dry conditions. Quantifying ecologically relevant environmental metrics is difficult in drylands because the response of vegetation to moisture and temperature conditions is not easily explained solely by climate-based metrics. To address this knowledge gap, we developed and examined 27 climate and ecological drought metrics across dryland areas of the western U.S. Included in the 27 metrics is a suite of 19 largely new “ecological drought metrics” that are designed to quantify multiple aspects of environmental limitation in drylands, including overall growing conditions, seasonal fluctuations, seasonal moisture timing, exposure to extreme drought, and recruitment potential for perennial plants. To quantify these metrics, we simulated water balance pools and fluxes of daily soil moisture at multiple depths with historical weather from 1970-2010 using the SOILWAT2 ecosystem water balance model. We assessed the relationships among these metrics and their spatial and temporal patterns. We found that the inclusion of ecological drought metrics substantially increased the dimensionality of the climate metrics dataset; the number of independent variables needed to explain 90% of the variance in the dataset increased with the addition of ecological drought metrics. Spatial patterns in overall growing conditions represented well-known differences among ecoregions, for example high temperatures and low precipitation in the southwest and cool temperatures and greater precipitation in the northeast. Seasonal fluctuation in soil water availability (SWA) was greatest in the southwest (Mojave Desert) while fluctuation in climatic water deficit (CWD) was greatest in the northwest (northern Great Basin and Columbia Plateau). Seasonal timing of moisture also differed among metrics; the timing of wet degree days (WDD), SWA and CWD were only weakly related to seasonal timing of precipitation. Plant recruitment metrics varied strongly across western drylands. In the Great Plains, recruitment events occurred more frequently and lasted longer than in the intermountain regions, where recruitment events were comparatively rare and short. These ecological drought metrics provide new insight into patterns of soil moisture and temperature that shape the structure and function of dryland ecosystems. The metrics will be useful for assessing the potential impact of climate change on dryland ecosystems and developing adaptive resource management strategies to sustain dryland ecosystem services in a changing world.

Ecohydrology↗

USGS2007

A Quantitative Threats Analysis for the Florida Manatee ( Trichechus manatus latirostris )

The Florida manatee (Trichechus manatus latirostris) is an endangered marine mammal endemic to the southeastern United States. The primary threats to manatee populations are collisions with watercraft and the potential loss of warm-water refuges. For the purposes of listing, recovery, and regulation under the Endangered Species Act (ESA), an understanding of the relative effects of the principal threats is needed. This work is a quantitative approach to threats analysis, grounded in the assumption that an appropriate measure of status under the ESA is based on the risk of extinction, as quantified by the probability of quasi-extinction. This is related to the qualitative threats analyses that are more common under the ESA, but provides an additional level of rigor, objectivity, and integration. In this approach, our philosophy is that analysis of the five threat factors described in Section 4(a)(1) of the ESA can be undertaken within an integrated quantitative framework. The basis of this threats analysis is a comparative population viability analysis. This involves forecasting the Florida manatee population under different scenarios regarding the presence of threats, while accounting for process variation (environmental, demographic, and catastrophic stochasticity) as well as parametric and structural uncertainty. We used the manatee core biological model (CBM) for this viability analysis, and considered the role of five threats: watercraft-related mortality, loss of warm-water habitat in winter, mortality in water-control structures, entanglement, and red tide. All scenarios were run with an underlying parallel structure that allowed a more powerful estimation of the effects of the various threats. The results reflect our understanding of manatee ecology (as captured in the structure of the CBM), our estimates of manatee demography (as described by the parameters in the model), and our characterization of the mechanisms by which the threats act on manatees. As an example of the type of results generated, we estimated that the probability of the manatee population falling to less than 250 adults on either the Atlantic or Gulf coasts (from a current statewide population size of near 3300) within 100 years is 8.6%. Complete removal of the watercraft threat alone would reduce this risk to 0.4%; complete removal of the warm-water threat to 4.2%; removal of both threats would reduce the risk to 0.1%. The modeling approach we have taken also allows us to consider partial removal of threats, as well as removal of multiple threats simultaneously. We believe the measure we have proposed (probability of quasi-extinction over y years, with quasi-extinction defined as dropping below a threshold of z on either coast) is a suitable measure of status that integrates a number of the elements that are relevant to interpretation under the ESA (it directly integrates risk of extinction and reduction of range, and indirectly integrates loss of genetic diversity). But the identification of the time frame of interest and the tolerable risk of quasi-extinction are policy decisions, and an ecology-based quasi-extinction threshold has not yet been determined. We have endeavored to provide results over a wide range of these parameters to give decision-makers useful information to assess status. This assessment of threats suggests that watercraft-related mortality is having the greatest impact on manatee population growth and resilience. Elimination of this single threat would greatly reduce the probability of quasi-extinction. Loss of warm-water is also a significant threat, particularly over the long-term. Red tide and entanglement, while noticeable threats, have had less of an impact on the manatee population. The effect of water control structures may have already been largely mitigated. We did not, however, consider an exhaustive list of threats. Other threats (e.g., reduction of food resources due to storms and development) may play a

Open-File Report↗

USGS2013

Estimation of perennial vegetation cover distribution in the Mojave Desert using MODIS-EVI data

This paper details a method to create regional models of perennial vegetation cover using pre-existing field data and satellite imagery. Total cover of perennial vegetation is an important ecological attribute of desert ecosystems, including the Mojave Desert, USA, an area of 125,000 km2. Moderate-Resolution Imaging Spectroradiometer Enhanced Vegetation Index (MODIS-EVI) data were coupled with measurements of total perennial cover and plot elevation using stepwise linear regression and linear regression techniques to create two models of cover. The final models produced R2 of 0.82 and 0.81, respectively, and yielded maps of perennial cover distribution in the Mojave Desert at 250 m spatial resolution. Copyright ?? 2008 by Bellwether Publishing, Ltd. All rights reserved.

GIScience and Remote Sensing↗

USGS2020

Expert-informed habitat suitability analysis for at-risk species assessment and conservation planning

The U.S. Fish and Wildlife Service (USFWS) is responsible for reviewing the biological status of hundreds of species to determine federal status designations under the Endangered Species Act. The longleaf pine Pinus palustris ecological system supports many priority at-risk species designated for review, including five species of herpetofauna: gopher tortoise Gopherus polyphemus , southern hognose snake Heterodon simus , Florida pine snake Pituophis melanoleucus mugitus , gopher frog Lithobates ( Rana ) capito , and striped newt Notophthalmus perstriatus . To inform status decisions and conservation planning, we developed habitat suitability models to 1) identify habitat features that best predict species presence and 2) estimate the amount and distribution of suitable habitat across each species' range under current conditions. We incorporated expert judgment from federal, state, and other partners to capture variation in ecological settings across species' ranges, prioritize predictor variables to test in models, mitigate data limitations by informing the selection of pseudoabsence points, qualitatively evaluate model estimates, and improve the likelihood that experts will trust and use model predictions for conservation. Soil characteristics, land cover, and fire interval strongly influenced habitat suitability for all species. Suitable habitat was distributed on known species strongholds, as well as private lands without known species records. Between 4.7% (gopher frog) and 14.6% (gopher tortoise) of the area in a species' range was classified as suitable habitat, and between 28.1% (southern hognose snake) and 47.5% (gopher frog) of suitable habitat was located in patches larger than 1 km 2 (100 ha) on publicly owned lands. By overlaying predictions for each species, we identified areas of suitable habitat for multiple species on protected and unprotected lands. These results have direct applications to management and conservation planning: partners can tailor site-level management based on attributes associated with high habitat suitability for species of concern; allocate survey effort in areas with suitable habitat but no known species records; and identify priority areas for management, land acquisitions, or other strategies based on the distribution of species records, suitable habitat, and land protection status. These results can aid regional partners in implementing effective conservation strategies and inform status designation decisions of the USFWS.

Alabama, Florida, Georgia, Louisiana, Mississippi,↗

USGS2012

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

Landscape Ecology↗

USGS2015

Comparing spatial capture–recapture modeling and nest count methods to estimate orangutan densities in the Wehea Forest, East Kalimantan, Indonesia

Accurate information on the density and abundance of animal populations is essential for understanding species' ecology and for conservation planning, but is difficult to obtain. The endangered orangutan ( Pongo spp.) is an example; due to its elusive behavior and low densities, researchers have relied on methods that convert nest counts to orangutan densities and require substantial effort for reliable results. Camera trapping and spatial capture–recapture (SCR) models could provide an alternative but have not been used for primates. We compared density estimates calculated using the two methods for orangutans in the Wehea Forest, East Kalimantan, Indonesia. Camera trapping/SCR modeling produced a density estimate of 0.16 ± 0.09–0.29 indiv/km 2 , and nest counts produced a density estimate of 1.05 ± 0.18–6.01 indiv/km 2 . The large confidence interval of the nest count estimate is probably due to high variance in nest encounter rates, indicating the need for larger sample size and the substantial effort required to produce reliable results using this method. The SCR estimate produced a very low density estimate and had a narrower but still fairly wide confidence interval. This was likely due to unmodeled heterogeneity and small sample size, specifically a low number of individual captures and recaptures. We propose methodological fixes that could address these issues and improve precision. A comparison of the overall costs and benefits of the two methods suggests that camera trapping/SCR modeling can potentially be a useful tool for assessing the densities of orangutans and other elusive primates, and warrant further investigation to determine broad applicability and methodological adjustments needed.

East Kalimantan↗

USGS2013

Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data

In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.

PLoS ONE↗

USGS2017

Food abundance, prey morphology, and diet specialization influence individual sea otter tool use

Sea otters are well-known tool users, employing objects such as rocks or shells to break open invertebrate prey. We used a series of generalized linear mixed effect models to examine observational data on prey capture and tool use from 211 tagged individuals from 5 geographically defined study areas throughout the sea otter’s range in California. Our best supported model was able to explain 75% of the variation in the frequency of tool use by individual sea otters with only ecological and demographic variables. In one study area, where sea otter food resources were abundant, all individuals had similar diets focusing on preferred prey items and used tools at low to moderate frequencies (4–38% of prey captures). In the remaining areas, where sea otters were food-limited, individuals specialized on different subsets of the available prey and had a wider range of average tool-use frequency (0–98% of prey captures). The prevalence of difficult-to-access prey in individual diets was a major predictor of tool use and increased the likelihood of using tools on prey that were not difficult to access as well. Age, sex, and feeding habitat also contributed to the probability of tool use but to a smaller extent. We developed a conceptual model illustrating how food abundance, the prevalence of difficult-to-access prey, and individual diet specialization interacted to determine the likelihood that individual sea otters would use tools and considered the model’s relevance to other tool-using species.

Behavioral Ecology↗