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At least 1,747 records · Page 97Linked to original sources
USGS2023

BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species

Aquatic invasive species (AIS) present major ecological and economic challenges globally, endangering ecosystems and human livelihoods. Managers and policy makers thus need tools to predict invasion risk and prioritize species and areas of concern, and they often use native range climate matching to determine whether a species could persist in a new location. However, climate matching for AIS often relies on air temperature rather than water temperature due to a lack of global water temperature data layers, and predictive power of models is seldom evaluated. We developed 12 global lake (water) temperature-derived “BioLake” bioclimatic layers for distribution modeling of aquatic species and compared “climatch” climate matching predictions (from climatchR package) from BioLake with those based on BioClim temperature layers and with a null model. We did this for 73 established AIS in the United States, training the models on their ranges outside of the United States and Canada. Models using either set of climate layers outperformed the null expectation by a similar (but modest) amount on average, but some species were occasionally found in locations with low climatch scores. Mean US climatch scores were higher for most species when using air temperature. Including additional climate layers in models reduced mean climatch scores, indicating that commonly used climatch score thresholds are not absolute but can be context specific and may require calibration based upon climate data used. Although finer resolution global lake temperature data would likely improve predictions, our BioLake layers provide a starting point for aquatic species distribution modeling. Climate matching was most effective for some species that originated at low latitudes or had small ranges. Climatch scores remain useful but limited for predicting AIS risk, perhaps because current ranges seldom fully reflect climatic tolerances (fundamental niches). Managers could consider climate matching as one of a suite of tools that can be used in AIS prioritization.

Ecosphere↗
USGS2006

Importance of recent shifts in soil thermal dynamics on growing season length, productivity, and carbon sequestration in terrestrial high-latitude ecosystems

In terrestrial high-latitude regions, observations indicate recent changes in snow cover, permafrost, and soil freeze-thaw transitions due to climate change. These modifications may result in temporal shifts in the growing season and the associated rates of terrestrial productivity. Changes in productivity will influence the ability of these ecosystems to sequester atmospheric CO2. We use the terrestrial ecosystem model (TEM), which simulates the soil thermal regime, in addition to terrestrial carbon (C), nitrogen and water dynamics, to explore these issues over the years 1960-2100 in extratropical regions (30-90??N). Our model simulations show decreases in snow cover and permafrost stability from 1960 to 2100. Decreases in snow cover agree well with National Oceanic and Atmospheric Administration satellite observations collected between the years 1972 and 2000, with Pearson rank correlation coefficients between 0.58 and 0.65. Model analyses also indicate a trend towards an earlier thaw date of frozen soils and the onset of the growing season in the spring by approximately 2-4 days from 1988 to 2000. Between 1988 and 2000, satellite records yield a slightly stronger trend in thaw and the onset of the growing season, averaging between 5 and 8 days earlier. In both, the TEM simulations and satellite records, trends in day of freeze in the autumn are weaker, such that overall increases in growing season length are due primarily to earlier thaw. Although regions with the longest snow cover duration displayed the greatest increase in growing season length, these regions maintained smaller increases in productivity and heterotrophic respiration than those regions with shorter duration of snow cover and less of an increase in growing season length. Concurrent with increases in growing season length, we found a reduction in soil C and increases in vegetation C, with greatest losses of soil C occurring in those areas with more vegetation, but simulations also suggest that this trend could reverse in the future. Our results reveal noteworthy changes in snow, permafrost, growing season length, productivity, and net C uptake, indicating that prediction of terrestrial C dynamics from one decade to the next will require that large-scale models adequately take into account the corresponding changes in soil thermal regimes. ?? 2006 Blackwell Publishing Ltd.

Global Change Biology↗
USGS2009

Direct-current resistivity profiling at the Pecos River Ecosystem Project study site near Mentone, Texas, 2006

The U.S. Geological Survey, in cooperation with Texas A&M University AgriLife, did a surface geophysical investigation at the Pecos River Ecosystem Project study site near Mentone in West Texas intended to determine shallow (to about 14 meters below the water [river] surface) subsurface composition (lithology) in and near treated (eradicated of all saltcedar) and control (untreated) riparian zone sites during June-August 2006. Land-based direct-current resistivity profiling was applied in a 240-meter section of the riverbank at the control site, and waterborne direct-current continuous resistivity profiling (CRP) was applied along a 2.279-kilometer reach of the river adjacent to both sites to collect shallow subsurface resistivity data. Inverse modeling was used to obtain a nonunique estimate of the true subsurface resistivity from apparent resistivity calculated from the field measurements. The land-based survey showed that the sub-surface at the control site generally is of relatively low resis-tivity down to about 4 meters below the water surface. Most of the section from about 4 to 10 meters below the water surface is of relatively high resistivity. The waterborne CRP surveys convey essentially the same electrical representation of the lithology at the control site to 10 meters below the water surface; but the CRP surveys show considerably lower resistivity than the land-based survey in the subsection from about 4 to 10 meters below the water surface. The CRP surveys along the 2.279-kilometer reach of the river adjacent to both the treated and control sites show the same relatively low resistivity zone from the riverbed to about 4 meters below the water surface evident at the control site. A slightly higher resistivity zone is observed from about 4 to 14 meters below the water surface along the upstream approximately one-half of the profile than along the downstream one-half. The variations in resistivity could not be matched to variations in lithology because sufficient rock samples were not available.

Texas↗
USGS2021

Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity

Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify predicted habitats for terrestrial vertebrates in the conterminous United States, to illustrate hotspots of biodiversity for the major taxonomic groups. This collection represents the first complete compilation of terrestrial vertebrate species models for the conterminous United States (U.S. Geological Survey (USGS), 2018a). We used the species models but not the available subspecies models; this resulted in the inclusion of 282 amphibian models, 621 bird models, 365 mammal models, and 322 reptiles in our analysis. We also used population trend information and made spatial queries to characterize species in three dimensions: geographic range (small or large), habitat breadth (narrow or wide), and population trend (decreasing vs stable or increasing). This characterization allowed us to divide the species into eight groups (A-H) with similar characteristics. Group A species (large geographic range, wide habitat breadth, and stable or increasing population trend) are species that are common now with no indication of becoming rare. Species B-H have theoretical or known characteristics that could lead them to become rare with the H species exhibiting small geographic range, narrow habitat breadth, and decreasing population trend. Finally, we evaluated the prevalence of mapped habitat on protected lands for each species, exploring the patterns of representation in the rare species groups by ecoregion. The species we identified with population and habitat use characteristics that potentially predispose them to being or becoming rare represented a large percentage of each taxon. Potentially rare species were widely distributed among ecoregions. Of the 20 ecoregions in the country, 14 have a greater number of rare species than the national average for at least one taxon. Protection of the habitat for the majority of these rare species is below that recommended (17% of available habitat) by the Convention on Biological Diversity (CBD). The Everglades ecoregion was the only ecoregion that protected more than half of its rare or potentially rare species.

Global Ecology and Conservation↗
USGS2015

Home range use and movement patterns of non-native feral goats in a tropical island montane dry landscape

Advances in wildlife telemetry and remote sensing technology facilitate studies of broad-scale movements of ungulates in relation to phenological shifts in vegetation. In tropical island dry landscapes, home range use and movements of non-native feral goats ( Capra hircus ) are largely unknown, yet this information is important to help guide the conservation and restoration of some of the world’s most critically endangered ecosystems. We hypothesized that feral goats would respond to resource pulses in vegetation by traveling to areas of recent green-up. To address this hypothesis, we fitted six male and seven female feral goats with Global Positioning System (GPS) collars equipped with an Argos satellite upload link to examine goat movements in relation to the plant phenology using the Normalized Difference Vegetation Index (NDVI). Movement patterns of 50% of males and 40% of females suggested conditional movement between non-overlapping home ranges throughout the year. A shift in NDVI values corresponded with movement between primary and secondary ranges of goats that exhibited long-distance movement, suggesting that vegetation phenology as captured by NDVI is a good indicator of the habitat and movement patterns of feral goats in tropical island dry landscapes. In the context of conservation and restoration of tropical island landscapes, the results of our study identify how non-native feral goats use resources across a broad landscape to sustain their populations and facilitate invasion of native plant communities.

Hawai‘i↗
USGS2020

Population and habitat analyses for greater sage-grouse (Centrocercus urophasianus) in the bi-state distinct population segment—2018 update

Executive Summary The Bi-State Distinct Population Segment (Bi-State DPS) of greater sage-grouse ( Centrocercus urophasianus , hereinafter “sage-grouse”) represents a genetically distinct and geographically isolated population that straddles the border between Nevada and California. The primary threat to these sage-grouse populations is the expansion of single-leaf pinyon ( Pinus monophylla ) and Utah juniper ( Juniperus osteosperma ) into sagebrush ecosystems, which fragments and reduces population connectivity and survival. Other important threats include low water availability during brood-rearing, particularly during drought, and increased predation by common ravens ( Corvus corax ), a generalist predator often associated with anthropogenic resource subsidies. Although the Bi-State DPS occurs at high elevations relative to sage-grouse range-wide, changes in historical wildfire cycles and the conversion of native shrubs to invasive annual grasslands still threaten these populations. The Bi-State DPS has undergone multiple federal status assessments and associated litigation. For example, in October of 2013, the Bi-State DPS was proposed for listing as threatened under the Endangered Species Act of 1973 by the U.S. Fish and Wildlife Service (USFWS), then withdrawn in April 2015. The withdrawal decision was challenged, and in May 2018, a Federal district court ordered the withdrawal decision to be vacated, and USFWS was required to re-open the October 2013 listing evaluation. In response, the U.S. Geological Survey (USGS), with State and Federal collaborators, embarked on a multipronged analysis to provide current and best available science regarding population status of sage-grouse within the Bi-State DPS. Using data from a long-term monitoring program, we carried out four analytical study objectives, and here, we provide preliminary results of these analyses. First, we used integrated population modeling (IPM) to predict annual population abundance and annual finite rate of population change for the Bi-State DPS, as a whole, and for each subpopulation between 1995 and 2018. Because sage-grouse exhibit population cycles (periodic increases and decreases in abundance across approximately 6- to 10-year wavelengths), we estimated trends across three nested temporal scales that represent one (11 years), two (18 years), and three (24 years) complete population cycles. These estimates of relatively long-term averaged population change account for temporal (that is, interannual) variation. Our model predicted population abundance for the Bi-State DPS during 2018 at 3,305 individuals (2,247–4,683), with the majority occupying Bodie Hills and Long Valley. The model also predicted cyclic dynamics in abundance through time with evidence of 24-year population growth and slight trends of decline over the past 18 years. Specifically, across the Bi-State DPS as a whole, we estimated annual average at 0.99, 0.99, and 1.02 over the one, two, and three population cycles, which equated to a 10.5 percent, 16.6 percent decrease, and 60.0 percent increase in abundance over the 11-, 18-, and 24-year cycles. Estimated abundance in 2018 had not reached numbers lower than those predicted during 1995. However, we found spatial variation in population trends across the three cycles. Bodie Hills subpopulation comprised the greatest (1,521) and exhibited average annual greater than 1.0 across all periods resulting in average annual increases of 7 percent. This relatively large subpopulation has grown 5 times larger than what was predicted in 1995 while experiencing cyclical dynamics within that period. Conversely, other smaller subpopulations within the Bi-State DPS exhibited average annual equal to or less than 1.0 resulting in estimated 10-year risks of extirpation ranging from 2.0 to 76.1 percent. In general, evidence of decline among smaller subpopulations was greatest for the most recent period (2008–18) compared to a period that encompassed three full population cycles (24-year). This difference coincides with an intense period of drought that began in 2012. For comparative purposes as part of this first objective, we conducted a similar analysis for populations of sage-grouse within Nevada and California but outside the Bi-State DPS. We developed a region-wide and distance-weighted IPM using lek count from Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW) databases and with telemetry data collected by USGS across 12 sage-grouse subpopulations. Our models predicted similar patterns in population cycling outside the Bi-State DPS but with much stronger evidence of long-term declines across 24 years. Specifically, median averaged across each year of the 11-, 18-, and 24-year periods resulted in average annual values of 0.94, 0.97, and 0.99, respectively. These values equate to 41.0 percent, 38.5 percent, and 21.3 percent declines over the corresponding periods. Second, we used lek count data in a state-space modeling framework to compare trends in population abundance across different spatial scales (that is, leks versus Bi-State DPS). This hierarchical framework allowed us to disentangle declines associated with climate conditions as opposed to other local level factors that might signal the need for management intervention. Specifically, we identified 7 leks that were both declining and recently decoupled from larger spatial scale trends, typically governed by climatic conditions (referred to as soft or hard signals). The goal of this analysis was to provide an early warning system that might have implications for conservation actions at local scales. Third, we developed phenological (spring, summer–fall, and winter) and reproductive life stage (nesting, early brood-rearing, and late-brood rearing) based resource selection functions using various environmental covariates. We report rankings of variable importance for each season and life stage, developed maps of habitat selection indices (HSI), binned categories representing low, moderate, and high classes of quality (where any category greater than or equal to low indicated selected habitat) for each phenological season and life stage, and produced composite maps by selected phenological and reproductive stage to estimate annual habitat. Fourth, we used for each lek within the Bi-State DPS to carry out a spatial analysis that quantified substantial changes in the distribution of occupied habitat across long- (24-year) and short- (11-year) term periods. Owing to differences among available datasets, the long-term analysis primarily reflected spatial shifts among subpopulations comprising the majority of the Bi-State DPS (that is, Bodie Hills and Long Valley) while the short-term analysis also quantified changes among subpopulations along the periphery. Over long and short-term periods, the overall distribution of occupied habitat (as measured by 99 percent utilization distributions intersecting any quantified habitat) was reduced by 20,573 ha and 55,492 ha, respectively. Occupied core areas (as measured by 50 percent utilization distributions intersecting any quantified habitat) over long-term periods were solely located in Bodie Hills and Long Valley. Although nearly all subpopulations experienced contractions in occupied overall and core distribution, Bodie Hills experienced spatial expansion that occurred with concomitant spatial contraction at Long Valley over both periods. Subpopulations at the northern (Pine Nuts), central (Sagehen) and southern (White-Mountains) extents of the Bi-State DPS also experienced spatial contraction over the short-term period. These findings, coupled with those of population trends, indicate long-term patterns in redistribution of sage-grouse from Long Valley and peripheral subpopulations to Bodie Hills. That is, sage-grouse subpopulations at the periphery are declining while the largest population at the core is increasing, which could have meaningful impacts on overall metapopulation persistence. We provide evidence for loss of occupied habitat (reduced distribution) given local extirpation of subpopulations. Fifth, we calculated percentages of selected phenological, life stage, and annual habitat that each subpopulation contributed to the Bi-State DPS. We then intersected these maps with a composite estimate of occupied habitat from the fourth objective and calculated percentages of selected habitat likely occupied by sage-grouse that each subpopulation contributed to the Bi-State DPS. These values provide evidence for loss of occupied habitat and subsequent reductions in spatial distribution given reductions in abundance and, in some cases, extirpation of leks within subpopulations. Lastly, we carried out an initial in-depth analysis of selection for irrigated pastures and wet meadows during the brood-rearing stage for the Long Valley subpopulation. We chose this subpopulation because it represents a population core, representing 26.5 percent of total sage-grouse within the Bi-State DPS, and has exhibited long-term declines in abundance and distribution. This subpopulation is highly sensitive to precipitation and other factors that influence water availability. Models predicted higher use of the interior portions of irrigated pastures and wet meadows during late brood-rearing period, which represented a potentially risky use of habitat that was exacerbated during periods of low moisture (for example, drought, reduced water delivery, or both). Sage-grouse typically used edges of riparian areas and pastures, largely because the interior of these mesic areas consisted of considerably less overhead concealment cover (for example, shrubs) that likely resulted in a higher risk of mortality. We found that a lack of water delivery to pastures in the form of overwinter precipitation or diversion ditches increased the movements of sage-grouse to the interior of pastures. Although further investigation of water delivery impacts on chick survival are warrented, our initial findings regarding resource selection may explain recent declines in population growth at Long Valley.

California, Nevada↗
USGS2020

Management of remnant tallgrass prairie by grazing or fire: Effects on plant communities and soil properties

Tallgrass prairie is a disturbance‐dependent ecosystem that has suffered steep declines in the midwestern United States. The necessity of disturbance, typically fire or grazing, presents challenges to managers who must apply them on increasingly small and fragmented parcels. The goal of this study was to compare effects of management using cattle grazing or fire on vegetation and soil characteristics to aid managers in making decisions regarding the kind of disturbance to apply. We selected 73 sites, of which 27 were managed solely by cattle grazing and 46 solely by fire, for at least 11 yr leading up to the study. We stratified the sites by prairie type (dry, mesic, and wet) and sampled frequency of plant species on randomly placed transects, supplemented with botanist‐directed walks, and collected and composited five soil cores on a randomly selected transect within each prairie type at each site. We calculated rarefied richness and Shannon evenness from the transect data and mean coefficient of conservatism (CofC) from the total list of species. Soil samples were analyzed for texture, bulk density, total N and C, and potential net N nitrification and mineralization. A nonmetric multidimensional scaling analysis of the plant community data revealed differences in species associated with mesic and wet prairies, but no separation by management type. Similarly, none of the vegetation variables we calculated varied by management type, as determined by mixed‐effects models, but soil bulk density was 17.5% higher and total N was 22% higher on grazed sites than burned sites. Sites burned more recently had higher species richness and mean CofC, but fire was not associated with any soil variables. Sites grazed more recently had higher bulk density, total N and C, and faster N cycling rates. Overall, 28% of plant species were found exclusively in one management type or the other, but these species did not vary in mean CofC. We conclude that, at the levels of burning and grazing intensity we studied, both management approaches produce similar C storage and vegetation responses. To maintain maximum diversity across the landscape, however, both approaches are necessary.

Minnesota↗
USGS2010

A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

INTRODUCTION Land-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. Four main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification. The intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

Open-File Report↗
USGS2012

Water quality and landscape processes of four watersheds in eastern Puerto Rico

Humid tropical regions occupy about a quarter of Earth's land surface, yet they contribute a substantially higher fraction of the water, solutes, and sediment discharged to the world's oceans. Nearly half of Earth's population lives in the tropics, and development stresses can potentially harm soil resources, water quality, and water supply and in addition increase landslide and flood hazards. Owing to Puerto Rico's steep topography, low water storage capacity, and dependence on trade-wind precipitation, the island's people, ecosystems, and water supply are vulnerable to extreme weather such as hurricanes, floods, and droughts. Eastern Puerto Rico offers a natural laboratory for separating geologic and land-cover influences from regional- and global-scale influences because of its various bedrock types and the changing land cover surrounding intact, mature forest of the Luquillo Experimental Forest. Accordingly, a multiyear assessment of hydrological and biogeochemical processes was designed to develop an understanding of the effects of these differences on local climate, streamflow, water quality, and ecosystems, and to form the basis for a long-term and event-based program of climate and hydrologic monitoring. Because infrequent, large storms play a major role in this landscape, we focused on high-runoff events, sampling 263 storms, including all major hurricanes from 1991 through 2005. The largest storms have profound geomorphic consequences, such as landslides, debris flows, deep gullying on deforested lands, excavation and suspension of sediment in stream channels, and delivery of a substantial fraction of annual stream sediment load. Large storms sometimes entrain ocean foam and spray causing high concentrations of seasalt-derived constituents in stream waters during the storm. Past deforestation and agricultural activities in the Cayaguás and Canóvanas watersheds accelerated erosion and soil loss, and this material continues to be remobilized during large storms. Nearly 5,000 routine and event samples were analyzed for parameters that allow determination of denudation rates based on suspended and dissolved loads; 860 of these samples were analyzed for a comprehensive suite of chemical constituents. The rivers studied are generally similar in water-quality characteristics, and windward or leeward aspect appears to exert a stronger influence on water quality than geology or land cover. Of samples analyzed for comprehensive chemistry and for sediment, 543 were collected at runoff rates greater than 1 millimeter per hour, 256 at rates exceeding 10 millimeters per hour, and 3 at rates exceeding 90 millimeters per hour. Streams have rarely been sampled during events with such high runoff rates. Rates of physical and chemical weathering are especially high, and physical denudation rates, forested watersheds included, are considerably greater than is expected for a steady-state system. The elevated physical erosion drives an increased particulate organic carbon flux, one that is large, important to the carbon cycle, and sustainable, because soil-carbon regeneration is rapid. The 15-year Water, Energy, and Biogeochemical Budget dataset, which includes discharge, field parameters, suspended sediment, major cations and anions, and nutrients, is available from the U.S. Geological Survey's National Water Information System (http://waterdata.usgs.gov/nwis). The dataset provides a baseline for characterizing future environmental change and will improve our understanding of the interdependencies of land, water, and biological resources and their responses to changes in climate and land use. Because eastern Puerto Rico resembles many tropical regions in terms of geology and patterns of development, implications from this study are transferable to other tropical regions facing deforestation, rapid land-use change, and climate change.

Puerto Rico↗
USGS2024

Population and spatial dynamics of desert bighorn sheep in Grand Canyon during an outbreak of respiratory pneumonia

Introduction: Terrestrial species in riverine ecosystems face unique constraints leading to diverging patterns of population structure, connectivity, and disease dynamics. Desert bighorn sheep ( Ovis canadensis nelsoni ) in Grand Canyon National Park, a large native population in the southwestern USA, offer a unique opportunity to evaluate population patterns and processes in a remote riverine system with ongoing anthropogenic impacts. We integrated non-invasive, invasive, and citizen-science methods to address questions on abundance, distribution, disease status, genetic structure, and habitat fragmentation. Methods: We compiled bighorn sightings collected during river trips by park staff, commercial guides, and private citizens from 2000–2018 and captured bighorn in 2010–2016 to deploy GPS collars and test for disease. From 2011–2015, we non-invasively collected fecal samples and genotyped them at 9–16 microsatellite loci for individual identification and genetic structure. We used assignment tests to evaluate genetic structure and identify subpopulations, then estimated gene flow and recent migration to evaluate fragmentation. We used spatial capture-recapture to estimate annual population size, distribution, and trends after accounting for spatial variation in detection with a resource selection function model. Results and discussion: From 2010–2018, 3,176 sightings of bighorn were reported, with sightings of 56–145 bighorn annually on formal surveys. From 2012–2016, bighorn exhibiting signs of respiratory disease were observed along the river throughout the park. Of 25 captured individuals, 56% were infected by Mycoplasma ovipneumoniae , a key respiratory pathogen, and 81% were recently exposed. Pellet sampling for population estimation from 2011–2015 yielded 1,250 genotypes and 453 individuals. We detected 6 genetic clusters that exhibited mild to moderate genetic structure ( F ST 0.022–0.126). The river, distance, and likely topography restricted recent gene flow, but we detected cross-river movements in one section via genetic recaptures, no subpopulation appeared completely isolated, and genetic diversity was among the highest reported. Recolonization of one large stretch of currently empty habitat appears limited by the constrained topology of this system. Annual population estimates ranged 536–552 (95% CrI range 451–647), lamb:ewe ratios varied, and no significant population decline was detected. We provide a multi-method sampling framework useful for sampling other wildlife in remote riverine systems.

Arizona↗
USGS2017

Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems

Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.

Hawaii↗
USGS2018

Factors affecting long-term trends in surface-water quality in the Gwynns Falls watershed, Baltimore City and County, Maryland, 1998–2016

Factors affecting water-quality trends in urban streams are not well understood, despite current regulatory requirements and considerable ongoing investments in gray and green infrastructure. To address this gap, long-term water-quality trends and factors affecting these trends were examined in the Gwynns Falls, Maryland, watershed during 1998–2016 in cooperation with Blue Water Baltimore. Data on water-quality constituents and potential factors of influence were obtained from multiple sources and compiled for analysis, with a focus on data collected as part of the National Science Foundation funded Long-Term Ecological Research project, the Baltimore Ecosystem Study. Variability in climate (specifically, precipitation) and land cover can overwhelm actions taken to improve water quality and can present challenges for meeting regulatory goals. Analysis of land cover during 2001–11 in the Gwynns Falls watershed indicated minimal change during the study time frame; therefore, land-cover change is likely not a factor affecting trends in water quality. However, a modest increase in annual precipitation and a significant increase in winter precipitation were apparent in the region. A higher proportion of runoff producing storms was observed in the winter and a lower proportion in the summer, indicating that climate change may affect water quality in the watershed. The increase in precipitation was not reflected in annual or seasonal trends of streamflow in the watershed. Nonetheless, these precipitation changes may exacerbate the inflow and infiltration of water to gray infrastructure and reduce the effectiveness of green infrastructure. For streamflow and most water-quality constituents examined, no discernable trends were noted over the timeframe examined. Despite the increases in precipitation, no trends were observed for annual or seasonal discharge at the various sites within the study area. In some locations, nitrate, phosphate, and total nitrogen show downward trends, and total phosphorus and chloride show upward trends. Sanitary sewer overflows (gray infrastructure) and best management practices (green infrastructure) were identified as factors affecting water-quality change. The duration of sanitary sewer overflows was positively correlated with annual loads of nutrients and bacteria, and the drainage area of best management practices was negatively correlated with annual loads of phosphate and sulfate. Results of the study indicate that continued investments in gray and green infrastructure are necessary for urban water-quality improvement. Although this outcome is not unexpected, long-term datasets such as the one used in this study, allow the effects of gray and green infrastructures to be quantified. Results of this study have implications for the Gwynns Falls watershed and its residents and Baltimore City and County managers. Moreover, outcomes are relevant to other watersheds in the metropolitan region that do not have the same long-term dataset. Further, this study has established a framework for ongoing statistical analysis of primary factors affecting urban water-quality trends as regulatory programs mature.

Maryland↗
USGS2021

Vulnerability of Pacific salmon to invasion of northern pike (Esox lucius) in Southcentral Alaska

The relentless role of invasive species in the extinction of native biota requires predictions of ecosystem vulnerability to inform proactive management strategies. The worldwide invasion and range expansion of predatory northern pike ( Esox lucius ) has been linked to the decline of native fishes and tools are needed to predict the vulnerability of habitats to invasion over broad geographic scales. To address this need, we coupled an intrinsic potential habitat modelling approach with a Bayesian network to evaluate the vulnerability of five culturally and economically vital species of Pacific salmon ( Oncorhynchus spp.) to invasion by northern pike. This study was conducted along 22,875 stream km in the Southcentral region of Alaska, USA. Pink salmon ( O . gorbuscha ) were the most vulnerable species, with 15.2% (2,458 km) of their calculated extent identified as “highly” vulnerable, followed closely by chum salmon ( O . keta , 14.8%; 2,557 km) and coho salmon ( O . kisutch , 14.7%; 2,536 km). Moreover, all five Pacific salmon species were highly vulnerable in 1,001 stream km of shared habitat. This simple to implement, adaptable, and cost-effective framework will allow prioritizing habitats for early detection and monitoring of invading northern pike.

Alaska↗
USGS2016

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

California↗
USGS2018

The risk of rodent introductions from shipwrecks to seabirds on Aleutian and Bering Sea islands

Accidental introductions of rodents present one of the greatest threats to indigenous island biota, especially seabirds. On uninhabited remote islands, such introductions are likely to come from shipwrecks. Here we use a comprehensive database of shipwrecks in Western Alaska to model the frequency of shipwrecks per Aleutian and Bering Sea island, taken as a proxy for the threat of rodent introductions, using physical variables, and the intensity of nearby fishing traffic and activity as predictors. Using data spanning from 1950 to 2013, we found that shipwrecks were particularly common in the 1980s to early 2000s, with a major peak in wrecks during the late 1980s. Amount of fishing activity within 5 km of an island was the strongest predictor of shipwrecks, followed by the strength of tidal currents and density of large-vessel traffic. Islands with the highest frequency of shipwrecks are all in the eastern Aleutians, including Unimak, Unalaska, and Akun Islands. By contrast, the largest seabird colonies are in the western Aleutian and Pribilof Islands, including Buldir, Kiska, and Saint George islands. Multiplying the frequency of a shipwreck by the number of seabirds breeding per island provides a measure of risk. The risk of rodent introductions from shipwrecks to seabirds was then greatest for Saint George (Bering Sea), Buldir (Western Aleutians) and Saint Matthew islands (Bering Sea). Keeping these high-risk islands rodent free would maintain their high a conservation value. Most islands with a high predicted frequency of shipwrecks already have established rodent populations and therefore few remaining seabirds. Of those islands with established rodent populations, Attu and Kiska Islands would make suitable targets for eradication, given their relatively low expected frequency of shipwrecks for their size. Further improvements in rat prevention on vessels and shipping safety would benefit the economy, human health and safety, and to the long-term conservation of island ecosystems.

Alaska↗
USGS2021

Evaluating establishment success of non-native fishes introduced to inland aquatic habitats of tropical Pacific islands

An information-theoretic approach was used to evaluate non-native freshwater fish species introduced to insular habitats of Hawaii and Guam comparing successful establishments vs. failures. Since the late 1800s, as many as 81 non-native freshwater fish species have been recorded as introduced to Hawaii and Guam (combined) and 50 (62%) of these are documented as having one or more established populations. We examined eleven independent variables to investigate establishment success by creating 21 a priori logistic regression models ranked using Akaike's Information Criterion adjusted for small sample size. An additional eight post-hoc models were included that comprised the best a priori model and various combinations of individual variables. The best overall model of establishment probability included effects of taxonomic affinity (family membership), prior establishment success on other tropical islands, and hypoxia tolerance. Establishment success in Hawaii and Guam was highest for those species established on many other islands, and according to our best model air-breathing fishes were more likely to become established. Six fish families, each with from three to 18 species introduced to Pacific islands, were highly successful at establishment: Cichlidae (16 established of 18 species introduced), Poeciliidae (seven of eight), Cyprinidae (four of seven), Centrarchidae (four of four), Clariidae (three of three), and Loricariidae (three of four). Those that successfully established include both small and moderately large-bodied taxa, while representing a diverse array of other morphological and life-history traits. Pathways and motives associated with fish introductions in the Pacific have been linked to desires to develop aquaculture, enhance wild stocks of food, sport, and bait fishes, for use as biological control agents, or are linked to the ornamental fish trade. We found that many established species were introduced via multiple pathways (up to eight) and our analyses suggest that the combination of prior establishment success on other tropical islands and presence of non-native fishes in multiple pathways was indicative of high propagule pressure. Our study results and conclusions on Pacific tropical island introductions are in general agreement with previous studies on non-native freshwater fishes in other regions of the world and similar to observations in continental ecosystems and temperate zones.

Hawaii↗
USGS2022

Lessons learned from wetlands research at the Cottonwood Lake Study Area, Stutsman County, North Dakota, 1967–2021

Depressional wetlands in the Prairie Pothole Region of North America have a long history of investigation owing to their importance in maintaining migratory-bird populations, especially waterfowl. One area of particularly intensive study is the Cottonwood Lake study area in Stutsman County, North Dakota. Studies at the Cottonwood Lake study area began in 1967 and continue through the present (2022). During this period of scientific discovery, meteorological conditions at the Cottonwood Lake study area varied greatly and included one of the most severe droughts of the 20th century and one of the wettest periods in the past 500 years. Persistent wet conditions that began in 1993 have contributed to state changes in many of the study area’s larger wetlands to lake-like conditions, whereas the smaller wetlands returned to seasonally ponded conditions during relatively dry years interspersed within the longer-term wet period. Additionally, some nonwetland areas of the study area developed wetland plant, hydrology, and soil characteristics during the 1993-to-present (2022) wet period. The persistently high stages of water in the larger wetlands since 1993 contributed to a buildup of dissolved solids and increases in salinity with time following an initial decrease in salinity caused by the dilution of dissolved solids within a larger volume of water. During 2021, drought conditions similar to the 1988 to 1992 period may develop if conditions persist. However, meteorological changes during the past 30 years have persisted long enough to be considered a change in climate conditions at the study area and, if such wet conditions continue, would represent a change from conditions that occurred in the past two millennia. During the period of study covered in this report (1967–2021), biotic communities responded in a variety of ways to subtle and marked changes in ponded-water depths, permanence, and salinity among the different wetland types in the study area. This report provides background information on the Cottonwood Lake study area and its context within the Prairie Pothole Region, documents techniques used to quantify environmental conditions and biotic communities, describes major trends that have been observed, presents significant findings as “lessons learned,” discusses recent modeling advances, and highlights key messages to managers. The Wetland Continuum concept was used as a framework to place research findings within an ecological context and to highlight the dynamic nature of prairie-pothole wetland ecosystems.

North Dakota↗
USGS2012

Report on the reptiles of Upland Savai’i

The reptile team conducted a 21 kilometre transect from the coast east of Asau to the uplands ending near Mauga Silisili at over 1720 m elevation. This transect covered the main habitats on Savai’i and allowed the team to determine where various reptile species and invasive species occurred across this elevational gradient. No previous reptile research had taken place on Savai’i above the elevation of A’opo Village. Limited sampling was also done around the Forestry Station in Asau. The team detected 11 species of lizards during these surveys, which is the majority of species known from Samoa. Noticeably absent was the Pacific black skink (Emoia nigra), which is a dominant element of the Samoan lizard fauna. Also no individuals of the Pacific boa (Candoia bibroni) were detected despite the concentrated effort spent looking for them. One boa was detected by the avifauna team at their Site 1, by the TV tower on a log in a marsh. The invasive house gecko (Hemidactylus frenatus) was also not detected along the main transect, but was the most abundant gecko on buildings in Asau. No reptiles were found above 1320 m elevation and most species were found significantly below there. Snakeeyed skinks (Cryptoblepharus poecilopleurus) were detected on Savai’i for the first time at Asau Getaway Resort then above the sawmill on the way to A’opo. Since western Savai’i is so poorly known for reptiles, this is the first time many of these species were recorded from this part of the island. Surveys for invasive species detected mammalian species (cats, rats, and pigs) and invertebrate species (Yellow Crazy ants and Big-headed ants). The mammals were found at various sites along the transect, including high elevations. The ants were found at lower elevations along the transect, but the Yellow Crazy ants appear to be irrupting currently on Savai’i and were swamping our traps from sea level to 500 m elevation. The low elevation lizard occurrences from sea level to 500 m appeared impaired by the invasive ants. Although habitat looked good in many places along the transect, certain species were rare or absent when the invasive ants were present, e.g. the Samoan skink (Emoia samoensis) which only occurred at elevations higher than the ants, whereas elsewhere in its range it occurs down to sea level. Currently the uplands over 500 m are free of invasive ants. We know from Hawai’i that invasive ants occur to over 2,000 m elevation and are ecologically very destructive to native flora and fauna. There is an immediate need to try to stop this upward ant invasion to protect this at-risk ecosystem, and to study the intact system now prior to an invasion.

Report↗