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At least 1,279 records · Page 71Linked to original sources
USGS2012

The U.S. Geological Survey Amphibian Research and Monitoring Initiative-2011 Annual Update

Welcome to the inaugural issue of ARMI's Annual Update. This update provides highlights and significant milestones of this innovative program. ARMI is uniquely qualified to provide research and monitoring results that are scalable from local to national levels, and are useful to resource managers. ARMI has produced nearly 400 peer-reviewed publications, including 18 in 2011. Some of those publications are highlighted in this fact sheet. ARMI also has a new Website (armi.usgs.gov). You can now use it to explore an up-to-date list of ARMI products, to find summaries of research topics, to search for ARMI activities in your area, and to obtain amphibian photographs. ARMI's annual meeting was organized by Walt Sadinski, Upper Midwest Environmental Science Center, and held in St Louis, Missouri. We met with local scientists and managers in herpetology and were given a tour of the herpetology collection at the St. Louis Zoo.

Fact Sheet↗
USGS2008

Procedures for Collecting and Processing Aquatic Invertebrates and Fish for Analysis of Mercury as Part of the National Water-Quality Assessment Program

Mercury studies conducted as part of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program have included nationwide reconnaissance samplings of hundreds of stream sites, as well as detailed, process-oriented research at selected sites. These reconnaissance and detailed studies are intended to provide a better understanding of methylmercury bioaccumulation in stream ecosystems over a range of environmental settings. This publication describes trace-element-clean techniques used for collection and processing of aquatic invertebrates and fish to be analyzed for total mercury, methylmercury, and stable isotopes as part of NAWQA studies.

Open-File Report↗
USGS2017

DNA-based detection of the fungal pathogen Geomyces destructans in soil from bat hibernacula

White-nose syndrome (WNS) is an emerging disease causing unprecedented morbidity and mortality among bats in eastern North America. The disease is characterized by cutaneous infection of hibernating bats by the psychrophilic fungus Geomyces destructans . Detection of G. destructans in environments occupied by bats will be critical for WNS surveillance, management and characterization of the fungal lifecycle. We initiated an rRNA gene region-based molecular survey to characterize the distribution of G. destructans in soil samples collected from bat hibernacula in the eastern United States with an existing PCR test. Although this test did not specifically detect G. destructans in soil samples based on a presence/absence metric, it did favor amplification of DNA from putative Geomyces species. Cloning and sequencing of PCR products amplified from 24 soil samples revealed 74 unique sequence variants representing 12 clades. Clones with exact sequence matches to G. destructans were identified in three of 19 soil samples from hibernacula in states where WNS is known to occur. Geomyces destructans was not identified in an additional five samples collected outside the region where WNS has been documented. This study highlights the diversity of putative Geomyces spp. in soil from bat hibernacula and indicates that further research is needed to better define the taxonomy of this genus and to develop enhanced diagnostic tests for rapid and specific detection of G. destructans in environmental samples.

Connecticut, Indiana, Kentucky, Massachusetts, Min↗
USGS2013

The importance of mineralogical input into geometallurgy programs

Mineralogy is the link between ore formation and ore extraction. It is the most fundamental component of geomet programs, and the most important aspect of a life-of-project approach to mineral resource projects. Understanding orebodies is achieved by understanding the mineralogy and texture of the materials, throughout the process, because minerals hold the information required to unlock the value they contain. Geomet mineralogy programs absolutely require the appropriate expertise and at least three steps of mineral characterisation prior to using semi-automated or other methods: field examination, thorough core logging, and optical microscopy. Economic geological inputs for orebody characterisation are necessary for orebody understanding, and are exemplified by current research in the Zambian Copperbelt, where revised sequence stratigraphy and understanding of alteration, metasomatism and metamorphism can be used to predict topical issues at mine sites. Environmental inputs for sustainability characterisation are demonstrated by recent work on tailings from the Leadville, Colorado, USA area, including linking mineralogy to water quality issues. Risk assessments need to take into account the technical uncertainties around geological variability and mineral extractability, and mineralogy is the only metric that can be used to make this risk contribution.

Conference Paper↗
USGS2025

What is eDNA method standardization and why do we need it?

The rapid advancement of environmental DNA ( eDNA ) science in the past two decades has inspired a concomitant growth in the development of eDNA sampling and analytical methods. However, these methods are often developed by individual laboratories or institutions, which can isolate protocols within programmes, agencies or regions and prevent the beneficial exchange of data and ideas. Recent efforts to advance national and international coordination have resulted in a groundswell of standardisation efforts, but there is still considerable confusion around the role of formal standards for regulatory or research applications. With this commentary, we hope to provide clarity on the terminology used in standardisation discussions, including the differences between formal standards and best practice guidelines. Additionally, we discuss how eDNA method choice may be informed by environmental management scenarios and review examples of formal eDNA method standards being used to inform management action. The eDNA community now has an opportunity to develop a roadmap for method development to help close standardisation gaps, advance eDNA method adoption and accelerate our ability to monitor biological life at the scales our current environmental challenges demand.

Metabarcoding and Metagenomics↗
USGS2013

Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework

[1] Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very “sharp”). Synthetic forecasts show that a modest “sharpening” can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement.

Montana↗
USGS2012

Changing Arctic ecosystems--research to understand and project changes in marine and terrestrial ecosystems of the Arctic

Ecosystems and their wildlife communities are not static; they change and evolve over time due to numerous intrinsic and extrinsic factors. A period of rapid change is occurring in the Arctic for which our current understanding of potential ecosystem and wildlife responses is limited. Changes to the physical environment include warming temperatures, diminishing sea ice, increasing coastal erosion, deteriorating permafrost, and changing water regimes. These changes influence biological communities and the ways in which human communities interact with them. Through the new initiative Changing Arctic Ecosystems (CAE) the U.S. Geological Survey (USGS) strives to (1) understand the potential suite of wildlife population responses to these physical changes to inform key resource management decisions such as those related to the Endangered Species Act, and (2) provide unique insights into how Arctic ecosystems are responding under new stressors. Our studies examine how and why changes in the ice-dominated ecosystems of the Arctic are affecting wildlife and will provide a better foundation for understanding the degree and manner in which wildlife species respond and adapt to rapid environmental change. Changes to Arctic ecosystems will be felt broadly because the Arctic is a production zone for hundreds of species that migrate south for the winter. The CAE initiative includes three major research themes that span Arctic ice-dominated ecosystems and that are structured to identify and understand the linkages between physical processes, ecosystems, and wildlife populations. The USGS is applying knowledge-based modeling structures such as Bayesian Networks to integrate the work.

Arctic↗
USGS2012

GRACEnet: addressing policy needs through coordinated cross-location research

GRACEnet (Greenhouse gas Reduction through Agricultural Carbon Enhancement network) was conceived to build upon ongoing USDA Agricultural Research Service (ARS) research to improve soil productivity, while addressing the challenges and opportunities of interest in C sequestration from a climate change perspective. The vision for GRACEnet was and remains: Knowledge and information used to implement scientifically based agricultural management practices from the field to national policy scales on C sequestration, greenhouse gas (GHG) emissions, and environmental benefits. The national focus of GRACEnet uses a standardized approach by ARS laboratories and university and land manager (e.g. farmer and rancher) cooperators to assess C sequestration and GHG emission from different crop and grassland systems. Since 2002, GRACEnet has significantly expanded GHG mitigation science and delivered usable information to agricultural research and policy organizations. Recent developments suggest GRACEnet will have international impact by contributing leadership and technical guidance for the Global Research Alliance on Agricultural Greenhouse Gases.

Book chapter↗
USGS2021

U.S. Geological Survey invasive species research—Improving detection, awareness, decision support, and control

More than 6,500 nonindigenous species are now established in the United States, posing risks to human and wildlife health, native plants and animals, and our valued ecosystems. The annual environmental, economic, and health-related costs of invasive species are substantial. Invasive species can drive native species onto the endangered species list, resulting in associated regulatory costs; exacerbate the threat of wildland fire, which destroys property and threatens lives; increase the cost of delivering water and power; damage infrastructure; and degrade recreation opportunities and discourage tourism. The U.S. Geological Survey (USGS) works with sister agencies in the U.S. Department of the Interior (DOI) and other Federal, State, and territorial agencies, Tribes, and other stakeholders to provide information and tools needed to help solve problems posed by invasive species across the country. Key components of USGS invasive species science include developing novel prevention, forecasting, early detection, decision support, and control tools.

Circular↗
USGS2022

A framework for prioritizing contaminants in retrospective ecological assessments: Application in the Milwaukee Estuary (Milwaukee, WI)

Watersheds are subjected to diverse anthropogenic inputs, exposing aquatic biota to a wide range of chemicals. Detection of multiple, different chemicals can challenge natural resource managers who often have to determine where to allocate potentially limited resources. Here, we describe a weight-of-evidence framework for retrospectively prioritizing aquatic contaminants. To demonstrate framework utility, we used data from 96-h caged fish studies to prioritize chemicals detected in the Milwaukee Estuary (WI, USA; 2017–2018). Across study years, 77/178 targeted chemicals were detected. Chemicals were assigned prioritization scores based on spatial and temporal detection frequency, environmental distribution, environmental fate, ecotoxicological potential, and effect prediction. Chemicals were sorted into priority bins based on the intersection of prioritization score and data availability. Data-limited chemicals represented those that did not have sufficient data to adequately evaluate ecotoxicological potential or environmental fate. Seven compounds (fluoranthene, benzo[ a ]pyrene, pyrene, atrazine, metolachlor, phenanthrene, and DEET) were identified as high or medium priority and data sufficient and flagged as candidates for further effects-based monitoring studies. Twenty-one compounds were identified as high or medium priority and data limited and flagged as candidates for further ecotoxicological research. Fifteen chemicals were flagged as the lowest priority in the watershed. One of these chemicals (2-methylnaphthalene) displayed no data limitations and was flagged as a definitively low-priority chemical. The remaining chemicals displayed some data limitations and were considered lower-priority compounds (contingent on further ecotoxicological and environmental fate assessments). The remaining 34 compounds were flagged as low or medium priority. Altogether, this prioritization provided a screening-level (non-definitive) assessment that could be used to focus further resource management and risk assessment activities in the Milwaukee Estuary. Furthermore, by providing detailed methodology and a practical example with real experimental data, we demonstrated that the proposed framework represents a transparent and adaptable approach for prioritizing contaminants in freshwater environments. Integr Environ Assess Manag 2023;00:1–21. © 2022 SETAC

Wisconsin↗
USGS2024

2023-2024 Coastal sage scrub and chaparral community monitoring for western San Diego County

Western San Diego County is dominated by shrublands supporting biologically diverse native plant and animal communities. Widespread urbanization has led to regional habitat loss and fragmentation, and many species in these shrubland communities are rare, threatened, or endangered. Large-scale, multiple-species conservation planning has resulted in a regional preserve system that focuses on these shrubland communities. Several large-scale threats are leading to type conversion from shrub-dominated to non-native invasive annual grass-dominated vegetation. To understand the changes that are occurring to native shrublands, we have developed a vegetation monitoring program with several components at multiple spatial scales, focused on quantifying coastal sage scrub (CSS) and chaparral vegetation community characteristics. Several drivers of change associated with type conversion of native shrubland to non-native annual grassland have been identified by previous research including increasing fire frequency, nitrogen deposition from air pollution, and prolonged and intense drought associated with changing climate. Loss of ecological integrity indices have been proposed as useful measures of the threat of degradation and type conversion of shrublands in San Diego County. For this study, ecological integrity is defined as a system’s ability to maintain species’ relationships and functions comparable to natural habitat in the region. Previous studies have identified the percent cover of invasive non-native annual grasses as a proxy for overall ecological degradation (loss of integrity) that is consistent across native taxonomic groups. Increased cover of non-native grass is associated with lower integrity of the shrubland vegetation community as shrub-associated plant and animal species are replaced by species preferring grassy and disturbed habitats. The objectives of this CSS and chaparral vegetation community monitoring plan are to: 1) Determine the distribution, composition, structure, and integrity of CSS and chaparral vegetation communities on conserved lands in western San Diego County, 2) Identify whether these attributes of the vegetation communities are changing over time, and 3) Evaluate relationships of known drivers of change (threats) and environmental factors in association with changes in vegetation community attributes. The CSS and chaparral vegetation community monitoring program is divided into four components: 1) vegetation mapping, 2) GIS/remote sensing office analysis of landscape-scale data, 3) permanent field plots using Unmanned Aerial Systems (UAS) and field data collections, and 4) animal and target species surveys and rapid assessment protocols. The first component, which is not detailed in this vegetation monitoring plan, aims to map vegetation communities every 10-15 years based on a classification developed for western San Diego County. High resolution aerial imagery will be used to update the 2012 vegetation map and expand it across the entire study area. The second component uses remote sensing models to annually track ecological integrity of shrublands across the study area and will include a map of areas of change and areas of stability over several decades. These landscape-scale integrity classifications will be used to analyze ecological processes, threats, and abiotic factors relative to changes to shrubland ecological integrity over time and space. The third component includes field surveys of 100 permanent plots across areas historically mapped as shrublands. Surveys in the 1930s mapped vegetation types using plot data. By using this historical classification map, we included areas that have already type-converted from shrubland to non-native annual grassland. The plots were split between CSS (55 plots) and chaparral (45 plots) and stratified into four geographical eco-subregions to guarantee coverage over small patches of habitat along the heavily developed coast. Surveys will include the collection of UAS imagery at a very high resolution. Species-level identifications will be made from the imagery based on a plant list compiled of all species detected in the plot during a thorough field survey by botanists, combined with geo-referenced samples of plant species locations. In addition, herbaceous cover will be estimated in the field using nine 1-m diameter circles (one per subplot) to obtain ocular estimates of cover for each plant species within the circle frame. Soil samples will be collected and analyzed for important element compositions. These data will be analyzed to evaluate plot-level ecological integrity based on species composition and cover. Repeated monitoring will allow evaluation of changes in vegetation attributes over time with known drivers or threats and other environmental factors. In addition, analyses will focus on indicator species and various measures of biological diversity for the vegetation communities. Finally, animal species and rare plants will be assessed using either taxa-based rapid assessment protocols or specialized species-specific protocols for rarer species. The purpose of these assessments is to document the status, habitat, and threat covariates of specific species and confirm the species composition and diversity of animal taxonomic groups (e.g., pollinators). Diversity and abundance of animal species at vegetation plots will be used to refine measures and thresholds of ecological integrity. Rapid assessment protocols for animal taxonomic groups can include multiple detection methods such as, camera traps, cover boards, and bird point counts. Pollinators will be monitored at plots using a protocol currently being developed in conjunction with but separately from this plan. Target rare plant species will be monitored using the regional Inspect and Manage (IMG) protocol that measures the status of rare plant occurrences and habitat and threat covariates over time. Species-specific animal survey methods will be refined as these species are prioritized for future monitoring. The goal of this monitoring program is to classify CSS and chaparral vegetation community integrity, identify areas of degradation across western San Diego County, and characterize drivers, and environmental factors associated with loss of ecological integrity. A combination of vegetation mapping, landscape-scale remote sensing, and field plots will be used to address all the aspects of our research questions. Data compiled and collected will be available to conservation partners to help inform future management decisions.

California↗
USGS2010

Persistent organic pollutants in the blood of free-ranging sea otters (Enhydra lutris ssp.) in Alaska and California

As part of tagging and ecologic research efforts in 1997 and 1998, apparently healthy sea otters of four age-sex classes in six locations in Alaska and three in California were sampled for persistent organic pollutants (POPs) and other chemicals of ecologic or environmental concern (COECs). Published techniques for the detection of POPs (specifically Σpolychlorinated biphenyls [PCBs], ΣDDTs, Σhexachlorocyclohexanes [HCHs], Σpolycyclic aromatic hydrocarbons [PAHs], Σchlordanes [CHLs], hexachlorobenzene [HCB], dieldrin, and mirex) in the tissue of dead otters were modified for use with serum from live sea otters. Toxic equivalencies (TEQs) were calculated for POPs with proven bioactivity. Strong location effects were seen for most POPs and COECs; sea otters in California generally showed higher mean concentrations than those in Alaska. Differences in contaminant concentrations were detected among age and sex classes, with high levels frequently observed in subadults. Very high levels of ΣDDT were detected in male sea otters in Elkhorn Slough, California, where strong freshwater outflow from agricultural areas occurs seasonally. All contaminants except mirex differed among Alaskan locations; only ΣDDT, HCB, and chlorpyrifos differed within California. High levels of ΣPCB (particularly larger, more persistent congeners) were detected at two locations in Alaska where associations between elevated PCBs and military activity have been established, while higher PCB levels were found at all three locations in California where no point source of PCBs has been identified. Although POP and COEC concentrations in blood may be less likely to reflect total body burden, concentrations in blood of healthy animals may be more biologically relevant and less influenced by state of nutrition or perimortem factors than other tissues routinely sampled.

Alaska, California↗
USGS2022

Global genetic diversity status and trends: Towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: ( i ) Genetic Diversity; ( ii ) Genetic Differentiation; ( iii ) Inbreeding; and ( iv ) Effective Population Size ( N e ). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Biological Reviews↗
USGS2010

Embryo malposition as a potential mechanism for mercury-induced hatching failure in bird eggs

We examined the prevalence of embryo malpositions and deformities in relation to total mercury (THg) and selenium (Se) concentrations in American avocet ( Recurvirostra americana ), black‐necked stilt ( Himantopus mexicanus ), and Forster's tern ( Sterna forsteri ) eggs in San Francisco Bay (CA, USA) during 2005 to 2007. Overall, 11% of embryos were malpositioned in eggs ≥18 d of age ( n = 282) and 2% of embryos were deformed in eggs ≥13 d of age ( n = 470). Considering only those eggs that failed to hatch ( n = 62), malpositions occurred in 24% of eggs ≥18 d of age and deformities occurred in 7% of eggs ≥13 d of age. The probability of an embryo being malpositioned increased with egg THg concentrations in Forster's terns, but not in avocets or stilts. The probability of embryo deformity was not related to egg THg concentrations in any species. Using a reduced dataset with both Se and THg concentrations measured in eggs ( n = 87), we found no interaction between Se and THg on the probability of an embryo being malpositioned or deformed. Results of the present study indicate that embryo malpositions were prevalent in waterbird eggs that failed to hatch and the likelihood of an embryo being malpositioned increased with egg THg concentrations in Forster's terns. We hypothesize that malpositioning of avian embryos may be one reason for mercury‐related hatching failure that occurs late in incubation, but further research is needed to elucidate this potential mechanism.

Environmental Toxicology and Chemistry↗
USGS2012

Nonsteroidal anti-inflammatory drugs in raptors

The use of analgesia has become standard, and appropriate, practice in avian medicine. As in mammals, pain control in avian patients is usually accomplished with opioids and nonsteroidal anti-inflammatory drugs (NSAIDs) used singly or in combination for a multimodal approach. Despite their usefulness, widespread use, and relative safety in clinical use, few controlled studies in birds have been conducted on efficacy, safety, and dosing. The guidelines for the use of NSAIDs in raptors and other birds have mainly been empirical. More recently, NSAIDs in free-living raptors have emerged as a major conservation issue with the discovery that diclofenac sodium was responsible for the population crash of three species of Gyps vultures in southern Asia. In this context, residues of veterinary NSAIDs in domestic animals are now considered environmental contaminants that can be significantly toxic to vultures and possibly other avian scavengers. Ironically, the disaster with Asian vultures has led to a considerable body of research on NSAIDs in raptors to the benefit of clinicians who now have scientific information available to help assess dosing, safety, toxicity, and pharmacokinetics of NSAIDs in their raptor patients.

Book chapter↗
USGS2021

Heed the data gap: Guidelines for using incomplete datasets in annual stream temperature analyses

Stream temperature data are useful for deciphering watershed processes important for aquatic ecosystems. Accurately extracting signal trends from stream temperature is essential for predicting responses of environmental and ecological indicators to change. Missing data periods are common for various reasons, and pose a challenge for scientists using temperature signal analysis to support stream research and ecological management objectives. However, the sensitivity of estimated temperature signal patterns to missing data has not been thoroughly evaluated, despite the potentially large impact on interpretation. In this study, we explored the effects of simulated missing daily data on the characterization of annual water temperature signals measured at headwater sites in the Pacific Northwest and Mid-Atlantic regions of the USA. For each site, we used linear regressions of sine-waves fitted to complete (365-d) and partial (7–357 consecutive missing data points) annual datasets of daily mean water temperature and computed three thermal parameters (mean, phase, and amplitude), which together can indicate thermally and ecologically influential watershed processes (e.g., depth and magnitude of groundwater discharge). Expected values (derived from complete datasets) ranged from 7.0 to 12.6 °C, 205 to 254 d, and 1.9 to 9.5 °C for annual mean, phase, and amplitude, respectively. While annual phase and amplitude could be accurately estimated (i.e., within 95–99% confidence intervals of expected values) with up to approximately two months of consecutively missing data, annual mean temperature required more complete datasets. We found that datasets with less than seven weeks of consecutively missing data enabled estimation of all annual signal parameters with reasonable accuracy (>75% probability of being within the 95–99% confidence intervals of expected values). Imputation of missing data expanded this range to approximately 20 weeks, with the greatest improvements in parameter estimation between 9 and 27 weeks of imputed missing data. However, caution should be exercised when applying this technique. For example, imputation improved the accuracy of parameter estimation for most sites, but accuracy decreased for some sites exhibiting strong groundwater influence. The timing of consecutive missing data points within a year had inconsistent effects on annual thermal parameter estimates among regions, years, and individual parameters. Utilizing sites with more than approximately seven consecutive weeks of missing data or 20 weeks of imputed data increases the probability of mischaracterization of annual stream thermal regimes. Understanding this limitation is vital for identifying the potential of streams to serve as climate refugia for ecological indicator species and effective future management of stream systems.

Ecological Indicators↗
USGS2021

Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning

Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.

Water Resources Research↗
USGS2010

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

International Journal of Remote Sensing↗