Evaluations of resource use among native piscivores in natural lakes have consistently documented significant partitioning that supports coexistence. Partitioning may be less prominent in reservoirs where water-level fluctuations can compress habitat and trophic diversity, but studies are lacking. Stable isotopes and bioenergetic models were used to quantify trophic interactions within a native piscivore assemblage inhabiting a temperate irrigation reservoir and explore implications for coexistence with a focus on threatened bull trout (Salvelinus confluentus). As hypothesised, adult bull trout exhibited the greatest degree of trophic specialisation by consuming mostly coldwater pelagic forage fish, which were consumed seasonally by the more abundant burbot (Lota lota) and northern pikeminnow (Ptychocheilus oregonensis). Numerous trophic niche overlap probabilities exceeded 70%, were as high as 93% and greatest between bull trout and burbot. Bioenergetics simulations demonstrated the high seasonal consumption capacity of burbot relative to northern pikeminnow. As a result, threefold to fourfold fewer burbot were required to consume the annual productivity of coldwater prey important for bull trout, particularly in the absence of small-bodied mesothermic or eurythermal fish as a buffer. Collectively, our analysis elucidated relatively strong trophic niche overlap among similarly sized piscivores, the importance of maintaining a diverse forage fish community for promoting coexistence and the greatest potential for competitive interactions between adult bull trout and burbot if key prey were limited or less diverse. More studies in regulated systems are needed to test for consistent patterns and identify mechanisms that limit or promote coexistence amid growing human-induced environmental change and demands on freshwater.
Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021).
Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts.
The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information.
The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are:
(1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time.
Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise.
(2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced.
Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate.
(3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts.
Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity.
The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.
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U.S. Geological Survey
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Reston, VA 20192
The widespread application of directional drilling and hydraulic fracturing technologies expanded oil and gas (OG) development to previously inaccessible resources. A single OG well can generate millions of liters of wastewater, which is a mixture of brine produced from the fractured formations and injected hydraulic fracturing fluids (HFFs). With thousands of wells completed each year, safe management of OG wastewaters has become a major challenge to the industry and regulators. OG wastewaters are commonly disposed of by underground injection, and previous research showed that surface activities at an Underground Injection Control (UIC) facility in West Virginia affected stream biogeochemistry and sediment microbial communities immediately downstream from the facility. Because microbially driven processes can control the fate and transport of organic and inorganic components of OG wastewater, we designed a series of aerobic microcosm experiments to assess the influence of high total dissolved solids (TDS) and two common HFF additives—the biocide 2,2-dibromo-3-nitrilopropionamide (DBNPA) and ethylene glycol (an anti-scaling additive)—on microbial community structure and function. Microcosms were constructed with sediment collected upstream (background) or downstream (impacted) from the UIC facility in West Virginia. Exposure to elevated TDS resulted in a significant decrease in aerobic respiration, and microbial community analysis following incubation indicated that elevated TDS could be linked to the majority of change in community structure. Over the course of the incubation, the sediment layer in the microcosms became anoxic, and addition of DBNPA was observed to inhibit iron reduction. In general, disruptions to microbial community structure and function were more pronounced in upstream and background sediment microcosms than in impacted sediment microcosms. These results suggest that the microbial community in impacted sediments had adapted following exposure to OG wastewater releases from the site. Our findings demonstrate the potential for releases from an OG wastewater disposal facility to alter microbial communities and biogeochemical processes. We anticipate that these studies will aid in the development of useful models for the potential impact of UIC disposal facilities on adjoining surface water and shallow groundwater.
Juvenile tree survival will play an important role in the persistence of coniferous forests and woodlands in the southwestern United States (SWUS). Vulnerability to climatic and environmental stress declines as trees grow, such that larger, more deeply rooted juveniles are less likely to experience mortality. It is unclear how juvenile conifers partition the aboveground and belowground components of early growth, if growth differs between species and ecosystem types, and what environmental factors influence juvenile carbon allocation above- or belowground. We developed a novel data set for four juvenile conifer groups (junipers, piñon pines, ponderosa pines, firs; 1121 juveniles sampled, 221 destructively) in three height classes (<150 mm, 150–300 mm, and 300+ mm), across 25 SWUS sites. We compared growth characteristics across groups and height classes and related differences to climatic and environmental factors. As tree height increased from <150 mm to 300+ mm, belowground growth increased, root:shoot ratio declined, and specific leaf area declined for all conifers except firs. Maximum rooting depth was shallower than previous estimates (<˜400 mm). Lower elevation juveniles were frequently located in sheltered microsites that provided high shading, whereas mid- and higher elevation juveniles were frequently unsheltered. Across all forest and woodland sites, herbaceous cover was positively correlated with aboveground growth. At study locations comprised of multiple sites, differences in aboveground growth were best explained by ecosystem type (piñon pine-juniper woodland, ponderosa pine forest, mixed-conifer forest) and local environmental variation. Our results indicate generally more belowground early growth and more aboveground later growth, but specific allocation patterns varied among ecosystem (greater proportional shoot growth at lower and mid-elevations compared with higher elevations). Juvenile conifers had similar magnitudes of proportional growth across conifer groups, displaying limited capacity to acclimate growth to differences in climate that control ecosystem type. If juvenile conifers also do not acclimate physiologically to their environment, our findings suggest that local environmental variation will play a primary role in regulating forest and woodland persistence and modify the effects of climate change in the SWUS.
The disease white-nose syndrome (WNS) was first recognized in upstate New York in 2006 and has since spread across much of the United States (U.S.), causing severe mortality in several North American bat species. To aid in the identification and monitoring of at-risk bat populations, we evaluate factors associated with the presence of the causative fungal agent of WNS, Pseudogymnoascus destructans (Pd), in the continental United States. We obtained Pd samples through hibernaculum surveys conducted from 2013 to 2020, with all samples analyzed at the U.S. Geological Survey National Wildlife Health Center. Using generalized additive models, we estimated the likelihood of Pd presence under three different hypotheses: human-mediated, species-mediated, and hibernaculum type. In addition to hypothesis-related predictor variables, a subset of models included a smoothed nonseparable effect of longitude and latitude and a smoothed effect of time since study onset to account for spatial and temporal autocorrelation. Under all hypotheses, models indicated probability of Pd detection is best described by the smoothed nonseparable effect of longitude and latitude and a smoothed effect of time since onset of this study. After accounting for spatial and temporal autocorrelations, only hibernaculum type significantly affected Pd presence, with mines and culverts/tunnels less likely to contain Pd compared with caves. Reduced likelihood of Pd presence in mines and culverts/tunnels bodes well for bats of the western and southern United States, where use of these hibernaculum types is more common. While our findings can help guide monitoring and management efforts, the potential for long-distance dispersal combined with variation in community composition and hibernation ecology between the western and eastern United States necessitates the continued monitoring of Pd presence.
The noble gas temperature climate proxy is an established tool that has previously been applied to determine the source of groundwater recharge, however, unanswered questions remain. In fractured media (e.g., volcanic islands) recharge can be so rapid that groundwater is significantly depleted in heavy noble gases, indicating that the water has retained noble gas concentrations from higher elevations. Previous studies of rain samples have confirmed a match to patterns seen in fractured-rock groundwater for heavy noble gases along with a significant helium excess. Snow has been shown to be a credible source for both the helium excess and the observed heavy noble gas pattern. Here, liquid cloud water samples were collected at two mountainous sites and analyzed for noble gas concentrations. A pattern like that of rainwater was found. However, an analysis of diffusive uptake of noble gases into cloud water demonstrates that droplets of 1 mm diameter and smaller should be in constant solubility equilibrium with the atmosphere. To explain this, we present a novel hypothesis that relies on the assumption that liquid water consists of two types of water molecule clusters bounded by hydrogen bonds: a low-density ice-like structure and a high-density condensed structure. In this model, the pressure gradient near the surface of a droplet resulting from surface tension could allow for the formation of a surface layer that is rich in ice-like low density clusters. This can explain both the helium excess and the heavy noble gas depletion seen in the samples.
Indicator species are species which can be monitored as an index to measure the overall health of an ecosystem. Crocodylians have been shown to be good indicators of wetland condition as they respond to changes in hydrology, can be efficiently monitored, and are a key part of ecosystem trophic relationships. Eye shine surveys at night are a standard method used to sample alligators, but because some individuals that are present in a study area may go undetected and the proportion of individuals counted is not constant over time, appropriate modeling is required to convert counts to estimates of abundance. We analyzed 13 years of American alligator (Alligator mississippiensis) survey count data from South Florida using an N-mixture model. Alligator abundance estimates were assigned to quartiles that were then represented as color coded categories of red, yellow, or green to provide a straightforward rating of Everglades restoration based on familiar stoplight coloring. These results were then compared to a previously used method in which unadjusted counts of these same data were assigned to color coded quartile categories. Water depth played a major role in the detection probability of alligators and the stoplight colors between the two methods matched 76% of the time. This suggests that the original stoplight score method provided a good overall snapshot of the trends in alligator abundance in the Everglades; however, the hierarchical models estimate abundance and trends of alligator abundance by incorporating detection probability thus providing unbiased estimates of abundance.
Effective conservation for listed migratory species requires an understanding of how drivers of population decline vary spatially and temporally, as well as knowledge of range-wide connectivity between breeding and nonbreeding areas. Environmental conditions distant from breeding areas can have lasting effects on the demography of migratory species, yet these consequences are often the least understood. Our objectives were to 1) evaluate associations between survival and extreme environmental disturbances at nonbreeding areas, including hurricanes, harmful algal blooms, and oil spills, and 2) estimate migratory connectivity between breeding and nonbreeding areas of midcontinental piping plovers (Charadrius melodus). We used capture and resighting data from 5067 individuals collected between 2002 and 2019 from breeding areas across the midcontinent, and nonbreeding areas throughout the Gulf of Mexico and southern Atlantic coasts of North America. We developed a hidden Markov multistate model to estimate seasonal survival and account for unobservable geographic locations. Hurricanes and harmful algal blooms were negatively associated with nonbreeding season survival, but we did not detect a similarly negative relationship with oil spills. Our results indicated that individuals from separate breeding areas mixed across nonbreeding areas with low migratory connectivity. Mixing among individuals in the nonbreeding season may provide a buffering effect against impacts of extreme events on any one breeding region. Our results suggest that understanding migratory connectivity and linking seasonal threats to population dynamics can better inform conservation strategies for migratory shorebirds.
As science becomes increasingly cross-disciplinary and scientific models become increasingly cross-coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model performance are “good” or “bad.” This apparent weakness has led to a myriad of specialized error metrics, which are sometimes aggregated to form a composite score. Such scores are inherently subjective, however, and while their components may be interpretable, the composite itself is not. We contend that, a better approach to model benchmarking and interpretation is to decompose MSE into interpretable components. To demonstrate the versatility of this approach, we outline some fundamental types of decomposition and apply them to predictions at 1,021 streamgages across the conterminous United States from three streamflow models. Through this demonstration, we hope to show that each component in a decomposition represents a distinct concept, like “season” or “variability,” and that simple decompositions can be combined to represent more complex concepts, like “seasonal variability,” creating an expressive language through which to interrogate models and data.
Seismic attenuation is generally greater in the western United States (WUS) than the central and eastern United States (CEUS), but the nature of this transition or location of this boundary is poorly constrained. We conduct crustal seismic (Lg) attenuation tomography across a region that stretches from the CEUS across the Rocky Mountains to the Basin and Range using a total of 115,870 amplitude measurements from 106 earthquakes recorded on 544 stations across five frequency bands spanning 0.5–16 Hz. Similar to previous studies, we find higher attenuation in the WUS (Q0 ∼ 190) than the nominally CEUS (Q0 ∼ 250) and comparatively high attenuation on the Gulf Coast (Q0 ∼ 175). Our models defy simple east versus west regionalization, however. Heterogeneity within the Rocky Mountain region—low attenuation in the Colorado Plateau interior and Wyoming Craton (Q0 ∼ 230) compared to high attenuation in the southern Rockies (Q0 ∼ 110)—exceeds the gross differences between the CEUS and western United States. These province-scale patterns are readily interpreted in terms of intrinsic attenuation. The boundary between the Colorado Plateau and Basin and Range hosts the highest attenuation imaged in the study area (Q0 ∼ 90), consistent with localized scattering across contrasting crustal structure. Focused high attenuation in the southern Rockies may represent the effects of represent in situ partial crustal melt. Within the CEUS, second-order bands of comparatively high attenuation align with the Proterozoic Yavapai-Mazatzal suture zone and Midcontinent Rift. This complex attenuation structure defies broad regionalization and suggests a need for path-specific models near these boundaries and for critical infrastructure.
Research presented in the preceding chapters emphasizes recent advancements in the research, management, and aquaculture of Walleye, Sauger, and Yellow Perch in North America. These percid fishes, along with the European Perch and Pikeperch, are economically and ecologically important fishes in their native geographic range. Advances in techniques to evaluate current habitat and predict future habitat conditions provide managers with detailed baseline information and biophysical models useful for evaluating adaptive management practices. Current habitat use and movement assessments have improved substantially with technological advancements in acoustic tags and extensive receiver array networks, which, combined with genetic and genomic tools, are improving percid stock assessments and management. Advances in percid aquaculture techniques have improved growth, survival, and disease resistance, enhancing percid stocking efforts and the production of marketable fish. The exchange of information between researchers and managers will continue to advance techniques of percid management for commercial and recreational exploitation and improve aquaculture practices to provide a lucrative commercial aquaculture industry.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Yellow Perch, Walleye, and Sauger: Aspects of ecology, management, and culture","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-80678-1_12","usgsCitation":"DeBruyne, R., and Roseman, E., 2021, International importance of Percids: Summary and looking forward, chap. of Yellow Perch, Walleye, and Sauger: Aspects of ecology, management, and culture, p. 309-320, https://doi.org/10.1007/978-3-030-80678-1_12.","productDescription":"12 p.","startPage":"309","endPage":"320","ipdsId":"IP-128480","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":392676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"DeBruyne, Robin L.","contributorId":139752,"corporation":false,"usgs":false,"family":"DeBruyne","given":"Robin L.","affiliations":[{"id":12902,"text":"MI State UNiversity","active":true,"usgs":false}],"preferred":false,"id":828102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":828103,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229763,"text":"70229763 - 2021 - Co-occurring lotic crayfishes exhibit variable long-term responses to extreme-flow events and temperature","interactions":[],"lastModifiedDate":"2022-03-17T16:45:05.624976","indexId":"70229763","displayToPublicDate":"2021-11-21T11:15:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Co-occurring lotic crayfishes exhibit variable long-term responses to extreme-flow events and temperature","docAbstract":"Crayfish serve critical roles in aquatic ecosystems as engineers, omnivores, and prey. It is unclear how increasingly frequent extreme-flow events and warming air temperatures will affect crayfish populations, partly because there are few long-term crayfish monitoring datasets. Using a unique 10-y dataset, we asked 1) whether recruitment of crayfishes in summer responded to extreme-flow events and air temperature during spring brooding and summer growing periods and 2) whether responses were similar among 3 co-occurring crayfish species. Golden (Faxonius luteus [Creaser, 1933]), Ozark (Faxonius ozarkae [Williams, 1952]), and Spothand (Faxonius punctimanus [Creaser, 1933]) crayfishes were sampled in quadrats at 2 sites each in the Big Piney (1993–2000) and Jacks Fork (1992–2001) rivers (Missouri, USA; n = 3355 1-m2 quadrats). We used zero-inflated generalized linear models to relate variability in quadrat-level age-0 counts to mean daily maximum air temperatures and flow metrics (variability, magnitude, and frequency of extreme high- and low-flow events). Species ranged from a small-bodied, abundant habitat generalist (Golden Crayfish) to large-bodied, uncommon habitat specialists (Ozark and Spothand crayfishes). Golden Crayfish occurred in higher-velocity habitats (riffles, runs) and had variable recruitment that increased during years with few spring and summer high-flow events and summers with lower flows and warmer temperatures. In contrast, annual recruitment variability of Ozark and Spothand crayfishes was low and explained by positive effects of cooler summers and by different flow metrics. Spothand Crayfish recruitment decreased in years with frequent spring and summer high-flow events, whereas lower summer minimum flow was the only flow metric that explained slight increases in Ozark Crayfish recruitment. Relationships with the preceding year’s recruitment were quadratic for Ozark and Spothand crayfishes, suggesting potential density dependence at higher recruitment levels. Species-specific responses suggest that closely related crayfishes could respond idiosyncratically to changes in temperature and flow. Temperature- and flow-related disturbances may be key mechanisms mediating competition and, thus, may help maintain crayfish diversity. However, warming air temperatures and increasingly frequent extreme-flow events could disadvantage some species, thereby altering future crayfish assemblages.
","language":"English","publisher":"Society for Freshwater Science","doi":"10.1086/717486","usgsCitation":"Dunn, C.G., Moore, M.J., Sievert, N., Paukert, C.P., and DiStefano, R., 2021, Co-occurring lotic crayfishes exhibit variable long-term responses to extreme-flow events and temperature: Freshwater Science, v. 40, no. 4, p. 626-643, https://doi.org/10.1086/717486.","productDescription":"18 p.","startPage":"626","endPage":"643","ipdsId":"IP-127694","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/717486","text":"Publisher Index Page"},{"id":397261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Big Piney River, Jacks Forks River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.84673309326172,\n 37.07791492175793\n ],\n [\n -91.80965423583984,\n 37.07791492175793\n ],\n [\n -91.80965423583984,\n 37.0921568267209\n ],\n [\n -91.84673309326172,\n 37.0921568267209\n ],\n [\n -91.84673309326172,\n 37.07791492175793\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.05821990966797,\n 37.15128685950638\n ],\n [\n -92.00122833251953,\n 37.15128685950638\n ],\n [\n -92.00122833251953,\n 37.2125580936087\n ],\n [\n -92.05821990966797,\n 37.2125580936087\n ],\n [\n -92.05821990966797,\n 37.15128685950638\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":838223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Michael J.","contributorId":274823,"corporation":false,"usgs":false,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":838224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sievert, Nicholas A. 0000-0003-3160-7596","orcid":"https://orcid.org/0000-0003-3160-7596","contributorId":177341,"corporation":false,"usgs":false,"family":"Sievert","given":"Nicholas A.","affiliations":[],"preferred":false,"id":838448,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DiStefano, Robert J.","contributorId":213268,"corporation":false,"usgs":false,"family":"DiStefano","given":"Robert J.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":838226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228224,"text":"70228224 - 2021 - Projecting climate dependent coastal flood risk with a hybrid statistical dynamical model","interactions":[],"lastModifiedDate":"2022-02-08T15:43:48.285368","indexId":"70228224","displayToPublicDate":"2021-11-21T09:38:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Projecting climate dependent coastal flood risk with a hybrid statistical dynamical model","docAbstract":"Numerical models for tides, storm surge, and wave runup have demonstrated ability to accurately define spatially varying flood surfaces. However these models are typically too computationally expensive to dynamically simulate the full parameter space of future oceanographic, atmospheric, and hydrologic conditions that will constructively compound in the nearshore to cause both extreme event and nuisance flooding during the 21st century. A surrogate modeling framework of waves, winds, and tides is developed in this study to efficiently predict spatially varying nearshore and estuarine water levels contingent on any combination of offshore forcing conditions. The surrogate models are coupled with a time-dependent stochastic climate emulator that provides efficient downscaling for hypothetical iterations of offshore conditions. Together, the hybrid statistical-dynamical framework can assess present day and future coastal flood risk, including the chronological characteristics of individual flood and wave-induced dune overtopping events and their changes into the future. The framework is demonstrated at Naval Base Coronado in San Diego, CA, utilizing the regional Coastal Storm Modeling System (CoSMoS; composed of Delft3D and XBeach) as the dynamic simulator and Gaussian process regression as the surrogate modeling tool. Validation of the framework uses both in-situ tide gauge observations within San Diego Bay, and a nearshore cross-shore array deployment of pressure sensors in the open beach surf zone. The framework reveals the relative influence of large-scale climate variability on future coastal flood resilience metrics relevant to the management of an open coast artificial berm, as well as the stochastic nature of future total water levels.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EF002285","usgsCitation":"Anderson, D.L., Ruggiero, P., Mendez, F.J., Barnard, P.L., Erikson, L.H., O'Neill, A., Merrifield, M., Rueda, A., Cagigal, L., and Marra, J.M., 2021, Projecting climate dependent coastal flood risk with a hybrid statistical dynamical model: Earth's Future, v. 9, no. 12, e2021EF002285, 24 p., https://doi.org/10.1029/2021EF002285.","productDescription":"e2021EF002285, 24 p.","ipdsId":"IP-111912","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450163,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021ef002285","text":"External Repository"},{"id":395620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Diego","otherGeospatial":"Naval Base Coronado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.32986450195312,\n 32.54565554741415\n ],\n [\n -117.05795288085936,\n 32.54565554741415\n ],\n [\n -117.05795288085936,\n 32.87555050280593\n ],\n [\n -117.32986450195312,\n 32.87555050280593\n ],\n [\n -117.32986450195312,\n 32.54565554741415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, D. L.","contributorId":274874,"corporation":false,"usgs":false,"family":"Anderson","given":"D.","email":"","middleInitial":"L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":833469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruggiero, P.","contributorId":191579,"corporation":false,"usgs":false,"family":"Ruggiero","given":"P.","email":"","affiliations":[],"preferred":false,"id":833470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mendez, F. J.","contributorId":274876,"corporation":false,"usgs":false,"family":"Mendez","given":"F.","email":"","middleInitial":"J.","affiliations":[{"id":27840,"text":"Universidad de Cantabria","active":true,"usgs":false}],"preferred":false,"id":833471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":833472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":833473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Neill, Andrea C. 0000-0003-1656-4372 aoneill@usgs.gov","orcid":"https://orcid.org/0000-0003-1656-4372","contributorId":5351,"corporation":false,"usgs":true,"family":"O'Neill","given":"Andrea C.","email":"aoneill@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":833474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Merrifield, M.","contributorId":274878,"corporation":false,"usgs":false,"family":"Merrifield","given":"M.","email":"","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":833475,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rueda, A.","contributorId":274880,"corporation":false,"usgs":false,"family":"Rueda","given":"A.","email":"","affiliations":[{"id":27840,"text":"Universidad de Cantabria","active":true,"usgs":false}],"preferred":false,"id":833476,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cagigal, L.","contributorId":274882,"corporation":false,"usgs":false,"family":"Cagigal","given":"L.","affiliations":[{"id":27840,"text":"Universidad de Cantabria","active":true,"usgs":false}],"preferred":false,"id":833477,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marra, J. M.","contributorId":219619,"corporation":false,"usgs":false,"family":"Marra","given":"J.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":833478,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70226550,"text":"70226550 - 2021 - Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud","interactions":[],"lastModifiedDate":"2021-11-24T13:27:41.850893","indexId":"70226550","displayToPublicDate":"2021-11-21T07:23:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud","docAbstract":"Understanding the age and movement of groundwater is important for predicting the vulnerability of wells to contamination, constraining flow models that inform sustainable groundwater management, and interpreting geochemical signals that reflect past climate. Due to both the ubiquity of groundwater with order ten-thousand-year residence times and its importance for climate reconstruction of the last glacial period, there is a strong need for improving geochemical dating tools on this timescale. Whereas 14C of dissolved inorganic carbon and dissolved 4He are common age tracers for Late Pleistocene groundwater, each is limited by systematic uncertainties related to aquifer composition and lithology, and the extent of water-rock interaction. In principle, radiogenic 40Ar in groundwater acquired from decay of 40K in aquifer minerals should be insensitive to some processes that impact 14C and 4He and thus represent a useful, complementary age tracer. In practice, however, detection of significant radiogenic 40Ar signals in groundwater has been limited to a small number of studies of extremely old groundwater (>100 ka). Here we present the first high-precision (<1‰) measurements of triple Ar isotopes (40Ar, 38Ar, 36Ar) in groundwater. We introduce a model that distinguishes radiogenic 40Ar from atmospheric 40Ar by using the non-radiogenic Ar isotopes (36Ar, 38Ar) to correct for mass-dependent fractionation. Using this model, we investigate variability in radiogenic 40Ar excess (Δ40Ar) across 58 groundwater samples collected from 36 wells throughout California (USA). We find that Δ40Ar ranges from ~0‰ (the expected minimum value) to +4.2‰ across three study areas near Fresno, San Diego, and the western Mojave Desert. Based on measurements from a network of 23 scientific monitoring wells in San Diego, we find evidence for a strong dependence of Δ40Ar on aquifer lithology. We suggest that Δ40Ar is fundamentally controlled by the weathering of old K-bearing minerals and thus reflects both the degree of groundwater-rock interaction, which is related to groundwater age, and the integrated flow through different geological formations. Future studies of Late Pleistocene groundwater may benefit from high-precision triple Ar isotope measurements as a new tool to better interpret 14C- and 4He-based constraints on groundwater age and flow.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2021.120458","usgsCitation":"Seltzer, A., Krantz, J.A., Ng, J., Danskin, W.R., Bekaert, D., Barry, P.H., Kimbrough, D.L., Kulongoski, J.T., and Severinghaus, J.P., 2021, The triple argon isotope composition of groundwater on ten-thousand-year timescales: Chemical Geology, v. 583, 120458, 12 p., https://doi.org/10.1016/j.chemgeo.2021.120458.","productDescription":"120458, 12 p.","ipdsId":"IP-134673","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":450168,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/9kx1757b","text":"Publisher Index Page"},{"id":417210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"583","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Seltzer, Alan 0000-0003-2870-1215","orcid":"https://orcid.org/0000-0003-2870-1215","contributorId":270717,"corporation":false,"usgs":false,"family":"Seltzer","given":"Alan","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":873138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krantz, John A.","contributorId":305541,"corporation":false,"usgs":false,"family":"Krantz","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":66250,"text":"Woods Hole Oceanographic Institution, Marine Chemistry & Geochemistry Department, Woods Hole, MA, United States of America","active":true,"usgs":false}],"preferred":false,"id":873139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ng, Jessica","contributorId":268304,"corporation":false,"usgs":false,"family":"Ng","given":"Jessica","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":873140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danskin, Wesley R. 0000-0001-8672-5501 wdanskin@usgs.gov","orcid":"https://orcid.org/0000-0001-8672-5501","contributorId":1034,"corporation":false,"usgs":true,"family":"Danskin","given":"Wesley","email":"wdanskin@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bekaert, David 0000-0002-1062-6221","orcid":"https://orcid.org/0000-0002-1062-6221","contributorId":270718,"corporation":false,"usgs":false,"family":"Bekaert","given":"David","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":873142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barry, Peter H. 0000-0002-6960-1555","orcid":"https://orcid.org/0000-0002-6960-1555","contributorId":218244,"corporation":false,"usgs":false,"family":"Barry","given":"Peter","email":"","middleInitial":"H.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":873143,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kimbrough, David L.","contributorId":211569,"corporation":false,"usgs":false,"family":"Kimbrough","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":873144,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873145,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Severinghaus, Jeffrey P.","contributorId":140715,"corporation":false,"usgs":false,"family":"Severinghaus","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":873146,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70225702,"text":"sir20205137 - 2021 - Numerical modeling of groundwater flow in the crystalline-rock aquifer in the vicinity of the Savage Municipal Water-Supply Well Superfund site, Milford, New Hampshire","interactions":[],"lastModifiedDate":"2022-04-14T16:02:52.30844","indexId":"sir20205137","displayToPublicDate":"2021-11-19T13:45:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5137","displayTitle":"Numerical Modeling of Groundwater Flow in the Crystalline-Rock Aquifer in the Vicinity of the Savage Municipal Water-Supply Well Superfund Site, Milford, New Hampshire","title":"Numerical modeling of groundwater flow in the crystalline-rock aquifer in the vicinity of the Savage Municipal Water-Supply Well Superfund site, Milford, New Hampshire","docAbstract":"In 2010, tetrachloroethylene (PCE), a chlorinated volatile organic compound, was detected in groundwater from deep (more than 300 feet below land surface) fractures in monitoring wells tapping a crystalline-rock aquifer. The aquifer underlies the Milford-Souhegan glacial-drift aquifer, a high water-producing aquifer, and the Savage Municipal Water-Supply Well Superfund site in Milford, New Hampshire. Between 30 and 40 residential water-supply wells are near (0.25 mile north of) the PCE-contaminated monitoring wells. Some of the residential water-supply wells are likely installed in similar rock types and formations as those of the monitoring wells installed as part of the Superfund site. As of 2020, periodic sampling by the U.S. Environmental Protection Agency and New Hampshire Department of Environmental Services (cooperative partners for this study) since 1996 had not detected PCE in groundwater from the residential water-supply wells. Nevertheless, understanding the vulnerability of the residential water wells to capture PCE contaminated groundwater was of concern.
A numerical groundwater flow model was developed by the U.S. Geological Survey to assess groundwater flow and advective transport of PCE-contaminated groundwater in the crystalline-rock aquifer of the Milford area. The model (called the area-wide model) encompasses a 26.5-square mile area to allow for more accurate computation of water fluxes near the PCE-contaminated monitoring wells and the residential water wells. Simulations with the area-wide model show that, with the 2016 configuration of residential wells, capture of PCE by the residential water wells appears unlikely for hydrologic conditions typical of 2010 based on steady-state, advective transport modeling. However, simulations also show that adding residential water wells to the north of the PCE-contaminated monitoring wells could affect the transport of PCE. Groundwater withdrawals at other adjacent wells in the overlying Milford-Souhegan glacial-drift aquifer affect advective transport in the crystalline-rock aquifer. Therefore, the potential for future changes in withdrawals in the area, as well as changes in hydrologic conditions, including groundwater recharge and streamflow amounts, should be considered in the remedial assessment process. The development of the area-wide model and linkages established by this study with previously developed Milford-Souhegan glacial-drift aquifer transport models will help facilitate the development of remedial strategies for this Superfund site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205137","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the New Hampshire Department of Environmental Services","usgsCitation":"Harte, P.T., 2021, Numerical modeling of groundwater flow in the crystalline-rock aquifer in the vicinity of the Savage Municipal Water-Supply Well Superfund site, Milford, New Hampshire: U.S. Geological Survey Scientific Investigations Report 2020–5137, 47 p., https://doi.org/10.3133/sir20205137.","productDescription":"Report: ix, 47 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-036649","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":391937,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205137/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391330,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5137/sir20205137.XML"},{"id":391326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5137/coverthb.jpg"},{"id":391329,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5137/images/"},{"id":391328,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7J102FK","text":"USGS data release","linkHelpText":"MODFLOW -2005, MODPATH, and MOC3D used for groundwater flow simulation, pathlines analysis, and solute transport in the crystalline-rock aquifer in the vicinity of the Savage Municipal Water-Supply Well Superfund site, Milford, New Hampshire"},{"id":391327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5137/sir20205137.pdf","text":"Report","size":"12.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5137"}],"country":"United States","state":"New Hampshire","city":"Milford","otherGeospatial":"Savage Municipal Water-Supply Well Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78741455078125,\n 42.798675589844414\n ],\n [\n -71.57524108886719,\n 42.798675589844414\n ],\n [\n -71.57524108886719,\n 42.938328528472546\n ],\n [\n -71.78741455078125,\n 42.938328528472546\n ],\n [\n -71.78741455078125,\n 42.798675589844414\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Eastern wild turkey (Meleagris gallopavo silvestris; hereafter turkey) is an important game species that is pursued by thousands of Alabama hunters each spring. Biologists in Alabama and other parts of the southeastern U.S. believe that turkey populations have been declining for at least two decades. Managers in many state agencies and organizations believe that liberal spring bag limits and the timing of hunting seasons are contributing to this decline. We used an expert-driven approach to develop models of turkey populations that predicted the outcomes of spring harvest management alternatives. The models were based on recent research and expert judgement regarding the effects of spring hunting regulations on turkey vital rates. We then used the relationship between the expected spring density of adult males and expected harvest elicited from experts to compare the values of the alternatives over a 30-year period. Our model suggests that if later opening dates result in increased turkey productivity and increased harvest, the result will be larger turkey populations, increased harvest, and greater value to stakeholders. In 84% of deterministic projections from 27,951 different initial populations, the highest valued alternative was to open seasons later, reduce bag limits, and shorten the season. This alternative also was best in 48% of projections that included parametric uncertainty. These results were used to produce a decision-support tool, that could be used to guide decisions about spring hunting regulations for turkeys in Alabama, and updated using the results of monitoring programs. Further research is needed to more precisely estimate the causes and effects of spring hunting seasons on turkey vital rates.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Grand, J.B., Silvano, A., Barnett, S., Moore, C., and Stewart, B., 2021, Comparing harvest management alternatives for Eastern Wild Turkeys in Alabama: Cooperator Science Series 137-2021, ii, 37 p.","productDescription":"ii, 37 p.","ipdsId":"IP-125260","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432130,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/comparing-harvest-management-alternatives-eastern-wild-turkeys-alabama","linkFileType":{"id":5,"text":"html"}},{"id":433564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Silvano, A.L.","contributorId":341811,"corporation":false,"usgs":false,"family":"Silvano","given":"A.L.","email":"","affiliations":[{"id":56927,"text":"Alabama Department of Conservation and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":908924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnett, S.","contributorId":341812,"corporation":false,"usgs":false,"family":"Barnett","given":"S.","email":"","affiliations":[{"id":56927,"text":"Alabama Department of Conservation and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":908925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, C.E.","contributorId":341815,"corporation":false,"usgs":false,"family":"Moore","given":"C.E.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":908926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, B.D.","contributorId":341818,"corporation":false,"usgs":false,"family":"Stewart","given":"B.D.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":908927,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226502,"text":"70226502 - 2021 - Clutch may predict growth of hatchling Burmese pythons better than food availability or sex","interactions":[],"lastModifiedDate":"2021-11-22T12:59:26.388202","indexId":"70226502","displayToPublicDate":"2021-11-19T06:56:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9930,"text":"Biology Open","active":true,"publicationSubtype":{"id":10}},"title":"Clutch may predict growth of hatchling Burmese pythons better than food availability or sex","docAbstract":"Identifying which environmental and genetic factors affect growth pattern phenotypes can help biologists predict how organisms distribute finite energy resources in response to varying environmental conditions and physiological states. This information may be useful for monitoring and managing populations of cryptic, endangered, and invasive species. Consequently, we assessed the effects of food availability, clutch, and sex on the growth of invasive Burmese pythons (Python bivittatus Kuhl) from the Greater Everglades Ecosystem in Florida, USA. Though little is known from the wild, Burmese pythons have been physiological model organisms for decades, with most experimental research sourcing individuals from the pet trade. Here, we used 60 hatchlings collected as eggs from the nests of two wild pythons, assigned them to High or Low feeding treatments, and monitored growth and meal consumption for 12 weeks, a period when pythons are thought to grow very rapidly. None of the 30 hatchlings that were offered food prior to their fourth week post-hatching consumed it, presumably because they were relying on internal yolk stores. Although only two clutches were used in the experiment, we found that nearly all phenotypic variation was explained by clutch rather than feeding treatment or sex. Hatchlings from clutch 1 (C1) grew faster and were longer, heavier, in better body condition, ate more frequently, and were bolder than hatchlings from clutch 2 (C2), regardless of food availability. On average, C1 and C2 hatchling snout-vent length (SVL) and weight grew 0.15 cm d−1 and 0.10 cm d−1, and 0.20 g d−1 and 0.03 g d−1, respectively. Additional research may be warranted to determine whether these effects remain with larger clutch sample sizes and to identify the underlying mechanisms and fitness implications of this variation to help inform risk assessments and management.
","language":"English","publisher":"The Company of Biologists","doi":"10.1242/bio.058739","usgsCitation":"Josimovich, J.M., Falk, B., Grajal-Puche, A., Hanslowe, E.B., Bartoszek, I., Reed, R., and Currylow, A.F., 2021, Clutch may predict growth of hatchling Burmese pythons better than food availability or sex: Biology Open, v. 10, no. 11, bio058739, 10 p., https://doi.org/10.1242/bio.058739.","productDescription":"bio058739, 10 p.","ipdsId":"IP-121446","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450169,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1242/bio.058739","text":"Publisher Index Page"},{"id":436113,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WHSSJ6","text":"USGS data release","linkHelpText":"Hatchling Growth Experiment Dataset from Invasive Burmese Pythons Captured in 2015 in Southern Florida"},{"id":391972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Josimovich, Jillian Maureen 0000-0002-7523-3496 jjosimovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7523-3496","contributorId":257058,"corporation":false,"usgs":true,"family":"Josimovich","given":"Jillian","email":"jjosimovich@usgs.gov","middleInitial":"Maureen","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falk, Bryan G. 0000-0002-9690-5626","orcid":"https://orcid.org/0000-0002-9690-5626","contributorId":265395,"corporation":false,"usgs":false,"family":"Falk","given":"Bryan G.","affiliations":[{"id":54672,"text":"National Park Service, Everglades National Park, 40001 SR 9336, Homestead, Florida 33034, USA","active":true,"usgs":false}],"preferred":false,"id":827123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grajal-Puche, Alejandro 0000-0003-1807-4799","orcid":"https://orcid.org/0000-0003-1807-4799","contributorId":265397,"corporation":false,"usgs":false,"family":"Grajal-Puche","given":"Alejandro","affiliations":[{"id":54677,"text":"Department of Biological Sciences, P.O. Box 5640, Northern Arizona University, Flagstaff, Arizona 86011, USA","active":true,"usgs":false}],"preferred":false,"id":827124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanslowe, Emma B. 0000-0003-4331-6729","orcid":"https://orcid.org/0000-0003-4331-6729","contributorId":265394,"corporation":false,"usgs":false,"family":"Hanslowe","given":"Emma","email":"","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":827125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bartoszek, Ian A.","contributorId":269426,"corporation":false,"usgs":false,"family":"Bartoszek","given":"Ian A.","affiliations":[{"id":55974,"text":"Conservancy of Southwest Florida, Naples, Florida, USA","active":true,"usgs":false}],"preferred":false,"id":827126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827127,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827128,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228203,"text":"70228203 - 2021 - Impacts of a non-indigenous ecosystem engineer, the American beaver (Castor canadensis), in a biodiversity hotspot","interactions":[],"lastModifiedDate":"2022-02-28T19:08:05.762991","indexId":"70228203","displayToPublicDate":"2021-11-18T09:38:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Impacts of a non-indigenous ecosystem engineer, the American beaver (Castor canadensis), in a biodiversity hotspot","title":"Impacts of a non-indigenous ecosystem engineer, the American beaver (Castor canadensis), in a biodiversity hotspot","docAbstract":"Non-native species having high per capita impacts in invaded communities are those that modulate resource availability and alter disturbance regimes in ways that are biologically incompatible with the native biota. In areas where it has been introduced by humans, American beaver (Castor canadensis) is an iconic example of such species due to its capacity to alter trophic dynamics of entire ecosystems and create new invasional pathways for other non-native species. The species is problematic in several watersheds within the Southern California-Northern Baja California Coast Ecoregion, a recognized hotspot of biodiversity, due to its ability to modify habitat in ways that favor invasive predators and competitors over the region's native species and habitat. Beaver was deliberately introduced across California in the mid-1900s and generally accepted as non-native to the region up to the early 2000s; however, articles promoting the idea that beaver may be a natural resident have gained traction in recent years, due in large part to the species' charismatic nature rather than by presentation of sound evidence. Here, we discuss the problems associated with beaver disturbance and its effects on conserving the region's native fauna and flora. We refute arguments underlying the claim that beaver is native to the region, and review paleontological, zooarchaeological, and historical survey data from renowned field biologists and naturalists over the past ~160 years to show that no evidence exists that beaver arrived by any means other than deliberate human introduction. Managing this ecosystem engineer has potential to reduce the richness and abundance of other non-native species because the novel, engineered habitat now supporting these species would diminish in beaver-occupied watersheds. At the same time, hydrologic functionality would shift toward more natural, ephemeral conditions that favor the regions' native species while suppressing the dominance of the most insidious invaders.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2021.752400","usgsCitation":"Richmond, J.Q., Swift, C.C., Wake, T.A., Brehme, C.S., Preston, K.L., Kus, B., Ervin, E., Tremor, S., Matsuda, T., and Fisher, R.N., 2021, Impacts of a non-indigenous ecosystem engineer, the American beaver (Castor canadensis), in a biodiversity hotspot: Frontiers in Conservation Science, v. 2, p. 1-14, https://doi.org/10.3389/fcosc.2021.752400.","productDescription":"752400, 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-134539","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":450174,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2021.752400","text":"Publisher Index Page"},{"id":395531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": 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cbrehme@usgs.gov","orcid":"https://orcid.org/0000-0001-8904-3354","contributorId":3419,"corporation":false,"usgs":true,"family":"Brehme","given":"Cheryl","email":"cbrehme@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preston, Kristine L. 0000-0002-6958-1128 kpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-6958-1128","contributorId":207765,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"kpreston@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833405,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kus, Barbara E. 0000-0002-3679-3044 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California","active":true,"usgs":false}],"preferred":false,"id":833408,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Matsuda, Tritia 0000-0001-9271-7671","orcid":"https://orcid.org/0000-0001-9271-7671","contributorId":213956,"corporation":false,"usgs":true,"family":"Matsuda","given":"Tritia","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833409,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833410,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70226776,"text":"70226776 - 2021 - Multi-model comparison of computed debris flow runout for the 9 January 2018 Montecito, California post-wildfire event","interactions":[],"lastModifiedDate":"2021-12-13T13:10:17.544528","indexId":"70226776","displayToPublicDate":"2021-11-18T07:00:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Multi-model comparison of computed debris flow runout for the 9 January 2018 Montecito, California post-wildfire event","docAbstract":"Hazard assessment for post-wildfire debris flows, which are common in the steep terrain of the western United States, has focused on the susceptibility of upstream basins to generate debris flows. However, reducing public exposure to this hazard also requires an assessment of hazards in downstream areas that might be inundated during debris flow runout. Debris flow runout models are widely available, but their application to hazard assessment for post-wildfire debris flows has not been extensively tested. Necessary inputs to these models include the total volume of the mobilized flow, flow properties (either inherent material properties or calibration coefficients), and site topography. Estimates of volume are possible in post-event (“back calculation”) studies, yet before an event, volume is an uncertain quantity. We simulated debris flow runout for the well-constrained 9 January 2018 Montecito event using three models (RAMMS, FLO2D, and D-Claw) to determine the relative importance of volume and flow properties. We broke the impacted area into three domains, and for each model-domain combination, we performed a numerical sampling study in which volume and flow properties varied within a wide, but plausible range. We assessed model performance based on inundation patterns and peak flow depths. We found all models could simulate the event with comparable results. Simulation performance was most sensitive to flow volume and less sensitive to flow properties. Our results emphasize the importance of reducing uncertainty in pre-event estimates of flow volume for hazard assessment.
Groundwater supplies 35 percent of drinking water in the United States. Mapping the quantity and quality of groundwater at the depths used for potable supplies requires an understanding of locational variation in the characteristics of drinking-water wells (depth and open interval). Typical depths of domestic- and public-drinking-water supply wells vary by and within aquifer across the United States. The depths to the top and bottom of the zones from which drinking water is withdrawn are important predictor variables in regional- and national-scale statistical water models, but spatially extensive maps of the depths to drinking-water-supply sources are not consistently available in modeled regions. Therefore, it was necessary to generate a set of grids representing surfaces of the approximate common depth and length of open intervals in the wells from which water is withdrawn for domestic- and public-drinking-water supply (withdrawal zones) within the conterminous United States.
Well data (about 7.6 million records) were compiled from several sources, including the U.S. Geological Survey’s National Water Information System (600,922 records), the U.S. Environmental Protection Agency’s Safe Drinking Water Information System dataset (66,540 records, primarily public-supply wells), a groundwater ambient monitoring dataset (31,448 records, primarily domestic-supply wells), individual State data (6,096,503 records), a national brackish aquifer study (96,885 records), and a glacial aquifer study (729,564 records).
Fifty-seven principal aquifers and 65 secondary hydrogeologic regions have been designated in the conterminous United States. The principal aquifers and secondary hydrogeologic regions vary in depth, thickness, lithology, and transmissivity characteristics. Some principal aquifers underlie secondary hydrogeologic regions, and may in turn be overlain by glacial sediment or basin and valley fill aquifers, which may also be used as drinking-water sources. The principal aquifer and secondary hydrogeologic region polygons were merged with overlying sediment polygons, where present, including glacial sediment, coarse glacial sediment, and stream valley alluvium (alluvium) polygons, to generate unique hydrogeologic settings across the conterminous United States. A total of 288 distinct hydrogeologic settings resulted from the merging of principal aquifer, secondary hydrogeologic region, glacial sediment, coarse glacial sediment, and alluvium polygons.
Each well was assigned to a hydrogeologic setting on the basis of location. Hydrogeologic setting well groupings were used to guide calculations of the median value for well depth and depth to and length of open intervals across the hydrogeologic setting. Where well data were sparse or missing, wells from hydrogeologic settings with similar well construction properties, geology, physiography, and topography were grouped and used to calculate the moving median depth (if less than five wells in a 100-kilometer [62.1-mile] radius) and to estimate open interval length (if not available within hydrogeologic setting). Grids were generated to represent what might be considered as the “typical” or “median” domestic- and public-supply well in an area. The well properties are defined with moving median grids of top depth, bottom depth, and length of open interval at a 1-square-kilometer (0.38-square-mile) grid cell scale.
Median depths and open intervals of domestic- and public-supply wells varied by lithology of the hydrogeologic setting and overlying sediment. Overall, the median depths were 142 feet (43.3 meters) for all domestic-supply wells and 202 feet (61.6 meters) for all public-supply wells. The median open intervals were 21 feet (6.4 meters) for domestic-supply wells and 49 feet (14.9 meters) for public-supply wells. The shallowest median bottom open interval depths for domestic-supply wells were in the secondary hydrogeologic regions with coarse glacial sediment, which suggests that the wells are most commonly completed in the permeable coarse glacial sediment and not in the underlying secondary hydrogeologic region. Public-supply wells were completed at relatively shallow median depths when drilled in permeable sediment that overlie secondary hydrogeologic regions. When public-supply wells were completed in principal aquifers, the median depths were typically greater than wells completed in secondary hydrogeologic regions.
Well data used in this study were limited to those available from national or State digital databases. Several quality-assurance checks were performed during data compilation, but a comprehensive quality assurance inspection for each of the data sources was outside the scope of this study. Grids defining typical open intervals in domestic- and public-supply wells are presented. Although there are many places where multiple aquifers are stacked, these results correspond primarily to the aquifer with the highest documented number of wells for each use.
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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Turtle body size is associated with demographic and other traits like mating success, reproductive output, maturity, and survival. As such, growth analyses are valuable for testing life history theory, demographic modeling, and conservation planning. Two important but unsettled research areas relate to growth after maturity and growth rate variation. If individuals exhibit indeterminate growth after maturity, older adults may have an advantage in fecundity, survival, or both over younger/smaller adults. Similarly, depending on how growth varies, a portion of the population may mature earlier, grow larger, or both. We used 23-years of capture-mark-recapture data to study growth and maturity in the Spotted Turtle (Clemmys guttata), a species suffering severe population declines and for which demographic data are needed for development of effective conservation and management strategies. There was strong support for models incorporating sex as a factor, with the interval growth model reparametrized for capture-mark-recapture data producing later mean maturation estimates than the age-based growth model. We found most individuals (94%) continued growing after maturity, but the instantaneous relative annual plastral growth rate was low. We recommend future studies examine the possible contribution of such slow, continued adult growth to fecundity and survival. Even seemingly negligible amounts of annual adult growth can have demographic consequences affecting the population vital rates for long-lived species.
Arid and semiarid ecosystems drive year-to-year variability in the strength of the terrestrial carbon (C) sink, yet there is uncertainty about how soil C gains and losses contribute to this variation. To address this knowledge gap, we embedded C-depleted soil mesocosms, containing litter or biocrust C inputs, within an in situ dryland ecosystem warming experiment. Over the course of one year, changes in microbial biomass and total soil organic C pools were monitored alongside hourly measurements of soil CO2 flux. We also developed a biogeochemical model to explore the mechanisms that gave rise to observed soil C dynamics. Field data and model simulations demonstrated that water exerted much stronger control on soil biogeochemistry than temperature, with precipitation events triggering large CO2 pulses and transport of litter- and biocrust-derived C into the soil profile. We expected leaching of organic matter would result in steady accumulation of C within the mineral soil over time. Instead, the size of the total organic C pool fluctuated throughout the year, largely in response to microbial growth: increases in the size of microbial biomass were negatively correlated with the quantity of C residing in the top 2 cm, where most biogeochemical changes were observed. Our data and models suggest that microbial responses to precipitation events trigger rapid metabolism of dissolved organic C inputs, which strongly limit accumulation of autotroph-derived C belowground. Accordingly, changes in the magnitude and/or frequency of precipitation events in this dryland ecosystem could have profound impacts on the strength of the soil C sink.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JG006492","usgsCitation":"Waring, B.G., Smith, K.R., Grote, E.E., Howell, A.J., Reibold, R.H., Tucker, C.L., and Reed, S., 2021, Climatic controls on soil carbon accumulation and loss in a dryland ecosystems: Journal of Geophysical Research, v. 126, no. 12, e2021JG006492, 13 p., https://doi.org/10.1029/2021JG006492.","productDescription":"e2021JG006492, 13 p.","ipdsId":"IP-133338","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450184,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1978553","text":"External Repository"},{"id":393749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Castle Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.46605682373047,\n 38.58896696823242\n ],\n [\n -109.30744171142578,\n 38.58896696823242\n ],\n [\n -109.30744171142578,\n 38.718465403583835\n ],\n [\n -109.46605682373047,\n 38.718465403583835\n ],\n [\n -109.46605682373047,\n 38.58896696823242\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Waring, Bonnie G. 0000-0002-8457-5164","orcid":"https://orcid.org/0000-0002-8457-5164","contributorId":245284,"corporation":false,"usgs":false,"family":"Waring","given":"Bonnie","email":"","middleInitial":"G.","affiliations":[{"id":49130,"text":"Utah State University, Department of Biology and Ecology Center, Logan UT 84322","active":true,"usgs":false}],"preferred":false,"id":829892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Kenneth R","contributorId":270738,"corporation":false,"usgs":false,"family":"Smith","given":"Kenneth","email":"","middleInitial":"R","affiliations":[{"id":49130,"text":"Utah State University, Department of Biology and Ecology Center, Logan UT 84322","active":true,"usgs":false}],"preferred":false,"id":829893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grote, Edmund E. 0000-0002-9103-9482 ed_grote@usgs.gov","orcid":"https://orcid.org/0000-0002-9103-9482","contributorId":4271,"corporation":false,"usgs":true,"family":"Grote","given":"Edmund","email":"ed_grote@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reibold, Robin H. 0000-0002-3323-487X","orcid":"https://orcid.org/0000-0002-3323-487X","contributorId":207499,"corporation":false,"usgs":true,"family":"Reibold","given":"Robin","email":"","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tucker, Colin L","contributorId":270737,"corporation":false,"usgs":false,"family":"Tucker","given":"Colin","email":"","middleInitial":"L","affiliations":[{"id":56205,"text":"U.S. National Forest Service, Northern Research Station, Houghton, MI 49931","active":true,"usgs":false}],"preferred":false,"id":829897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829898,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}