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USGS2021

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Methods in Ecology and Evolution↗

USGS2019

Standardized IMGT nomenclature of salmonidae IGH genes, the paradigm of Atlantic salmon and rainbow trout: From genomics to repertoires

In teleost fish as in mammals, humoral adaptive immunity is based on B lymphocytes expressing highly diverse immunoglobulins (IG). During B cell differentiation, IG loci are subjected to genomic rearrangements of V, D, and J genes, producing a unique antigen receptor expressed on the surface of each lymphocyte. During the course of an immune response to infections or immunizations, B cell clones specific of epitopes from the immunogen are expanded and activated, leading to production of specific antibodies. Among teleost fish, salmonids comprise key species for aquaculture. Rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) are especially important from a commercial point of view and have emerged as critical models for fish immunology. The growing interest to capture accurate and comprehensive antibody responses against common pathogens and vaccines has resulted in recent efforts to sequence the IG repertoire in these species. In this context, a unified and standardized nomenclature of salmonid IG heavy chain (IGH) genes is urgently required, to improve accuracy of annotation of adaptive immune receptor repertoire dataset generated by high-throughput sequencing (AIRRseq) and facilitate comparisons between studies and species. Interestingly, the assembly of salmonids IGH genomic sequences is challenging due to the presence of two large size duplicated IGH loci and high numbers of IG genes and pseudogenes. We used data available for Atlantic salmon to establish an IMGT standardized nomenclature of IGH genes in this species and then applied the IMGT rules to the rainbow trout IGH loci to set up a nomenclature, which takes into account the specificities of Salmonid loci. This unique, consistent nomenclature for Salmonid IGH genes was then used to construct IMGT sequence reference directories allowing accurate annotation of AIRRseq data. The complex issues raised by the genetic diversity of salmon and trout strains are discussed in the context of IG repertoire annotation.

Frontiers in Immunology↗

USGS2019

Future losses of playa wetlands decrease network structure and connectivity of the Rainwater Basin, Nebraska

Context The Rainwater Basin in south-central Nebraska once supported a complex network of ~ 12,000 spatially-isolated playa wetlands, but ~ 90% have been lost since European settlement. Future losses are likely and expected reductions in connectivity could further isolate populations, increasing local extinction rates of many wetland species. However, to what extent future losses will affect wildlife likely depends on the role of lost wetlands in maintaining connectivity. Objectives We compared the current Rainwater Basin network to future wetland loss scenarios to assess minimum, mean, and maximum effects of losses on network connectivity for a range of wildlife taxa. Methods We used network models to rank wetlands by their functionality and relative importance in maintaining connectivity. We then removed 10–50% of high-ranked, low-ranked, or random subsets of wetlands and assessed connectivity of the remaining network. Results A 10% loss of highly-ranked wetlands substantially decreased connectivity for species with dispersal capabilities < 5.5 km, while a 40–50% loss reduced connectivity for all tested dispersal distances (0.5–12.0 km). When large proportions of highly-ranked wetlands were lost, the eastern and western halves of the Rainwater Basin network were no longer connected for any dispersal distance. Loss of low-ranked wetlands had minimal effects on network connectivity, until at least the lowest-ranked 50% were removed. Conclusions Many highly-ranked playa wetlands in the Rainwater Basin are currently unprotected and might disappear from the landscape. Protecting wetlands that are key in maintaining connectivity especially benefits species with limited dispersal capabilities (< 5.5 km) for which consequences of future habitat losses might be worst.

Nebraska↗

USGS2025

Climate change and future water availability in the United States

The steady rise in global temperature as a result of human activity is causing changes in Earth’s water cycle. The balance of water stored within and moving between vapor, liquid, and frozen states in the water cycle is shifting, with consequences for water availability that include increases in drought, fire weather, flooding, and heavy precipitation, as well as cryosphere decline and sea-level rise. In this chapter of the U.S. Geological Survey Integrated Water Availability Assessment—2010–20, we provide an overview of climate-change observations and projections from Earth-system model simulations that relate to future water availability, from global and national climate assessments and from the published literature. Effects of climate change on primary water-cycle components are discussed in context of how global-scale hydroclimate drivers influence regional processes within the United States. Understanding the major climate drivers impacting the water cycle is crucial to predicting future changes in water availability and developing adaptation strategies to ensure human and ecosystem water supplies. First, we provide background information on the water cycle, the climate-model ensemble simulations developed to produce projections based on warming scenarios, and attribution and certainty levels. Tipping points, self-reinforcing feedbacks, cascading effects, and compound extremes are introduced. The framework of climatic impact drivers (CIDs) outlined in the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6) is used to show primary drivers of physical change to the water cycle and to understand and predict changes in future water availability. Specific climate-change related observations and projections are discussed for water cycle components of precipitation, evapotranspiration, soil moisture, streamflow, lakes and wetlands, ice and snow, and groundwater, as well as their implications for future water availability for humans and ecosystems. The chapter concludes with a synthesis discussion of three examples of complex regional-scale hydroclimate processes that influence water availability for populations in the United States, including (1) mountain and coastal precipitation, (2) aridification and drought, and (3) the influence of forest-cover change on terrestrial water-vapor recycling.

Professional Paper↗

USGS2023

A multi-ecosystem prioritization framework to balance competing habitat conservation needs of multiple species in decline

Context Individual species often drive habitat restoration action; however, management under this paradigm may negatively affect non-target species. Prioritization frameworks which explicitly consider benefits to target species while minimizing consequences for non-target species may improve management strategies and outcomes. Objectives We examined extents to which conifer removal, an approach frequently implemented to restore sagebrush ecosystems, can be conducted without detrimental effects to conifer-associated species, including the imperiled Pinyon Jay ( Gymnorhinus cyanocephalus ). Additionally, we prioritized sites for conifer removal, and predicted abundance responses for multiple species following simulated conifer removal at selected sites to achieve variable management objectives. Methods We used model-predicted changes in species’ densities following simulated conifer removal to identify optimal removal sites under single species, multi-species (ecosystem), and multi-ecosystem management scenarios. We simulated conifer removal at prioritized sites and evaluated resulting changes in abundance for six passerine species. Results Management prioritized for a single species (Brewer’s Sparrow) provided the greatest per-unit-effort benefits for that species but resulted in the lowest population outcomes for all other species considered. In comparison, prioritizations for multiple species within a single ecosystem (i.e., pinyon–juniper or sagebrush) resulted in larger population benefits for species associated with that ecosystem and reduced detrimental effects on non-target species associated with another ecosystem. For example, single species management for Brewer’s Sparrow resulted in an average increase of 1.38% for sagebrush-associated species and a 4.58% decrease for pinyon–juniper associated species. In contrast, when managing for multiple sagebrush-associated species sagebrush-associated songbird populations increased by 3.98% and pinyon–juniper associated species decreased by 2.36%, on average. Conclusions Our results illustrate single species management can result in detrimental outcomes and/or opportunity costs for non-target species compared to management designed to benefit multiple species. Our framework can be used to balance undesired consequences for non-target species and is adaptable for other systems and taxa.

Landscape Ecology↗

USGS2023

A synergistic future for AI and ecology

Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in computational and ecological research, we foresee a critical need for intentional synergy to meet current societal challenges against the backdrop of global change. These challenges include understanding the unpredictability of systems-level phenomena and resilience dynamics on a rapidly changing planet. Here, we spotlight both the promise and the urgency of a convergence research paradigm between ecology and AI. Ecological systems are a challenge to fully and holistically model, even using the most prominent AI technique today: deep neural networks. Moreover, ecological systems have emergent and resilient behaviors that may inspire new, robust AI architectures and methodologies. We share examples of how challenges in ecological systems modeling would benefit from advances in AI techniques that are themselves inspired by the systems they seek to model. Both fields have inspired each other, albeit indirectly, in an evolution toward this convergence. We emphasize the need for more purposeful synergy to accelerate the understanding of ecological resilience whilst building the resilience currently lacking in modern AI systems, which have been shown to fail at times because of poor generalization in different contexts. Persistent epistemic barriers would benefit from attention in both disciplines. The implications of a successful convergence go beyond advancing ecological disciplines or achieving an artificial general intelligence—they are critical for both persisting and thriving in an uncertain future.

Proceedings of the National Academy of Sciences↗

USGS2021

Biotic and abiotic determinants of finescale dace distribution at the southern edge of their range

Aim The factors that set range limits for animal populations can inform management plans aimed at maintaining regional biodiversity. We examine abiotic and biotic drivers of the distribution of finescale dace ( Chrosomus neogaeus ) in two Great Plains basins to identify limiting factors for a threatened freshwater fish population at the edge of their range. Location Great Plains, Nebraska, South Dakota and Wyoming, USA. Methods We investigated abiotic and biotic factors influencing the contemporary distribution of finescale dace in the Belle Fourche and Niobrara River basins with Random Forests classification models using fish surveys from multiple agencies spanning 2008–2019 and GIS-derived environmental data. Results In both basins, finescale dace occurrence exhibited a nonlinear response to mean August water temperature. Abiotic covariates, including streamflow, water temperature and channel slope, were important limiting factors in the final model fit with Belle Fourche River basin surveys ( n = 131). In contrast, a biotic covariate, native minnow richness, was the most important predictor of finescale dace occurrence in the Niobrara River basin model ( n = 27). In the Niobrara River, native minnow richness was lower at sites with non-native northern pike ( Esox lucius ). Main conclusions Basin-specific analyses revealed context dependencies for species–environment relationships, which can inform targeted restoration actions. Similar relationships between water temperature and finescale dace occurrence across both basins suggest summer thermal habitat as a regional limiting factor. The importance of biotic interactions in the Niobrara River highlights an emergent threat from invasive predators to a distinct assemblage of native prairie fishes.

Nebraska, South Dakota, Wyoming↗

USGS2010

A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios

he Energy Independence and Security Act of 2007 (EISA), Section 712, mandates the U.S. Department of the Interior to develop a methodology and conduct an assessment of the Nation’s ecosystems, focusing on carbon stocks, carbon sequestration, and emissions of three greenhouse gases (GHGs): carbon dioxide, methane, and nitrous oxide. The major requirements include (1) an assessment of all ecosystems (terrestrial systems, such as forests, croplands, wetlands, grasslands/shrublands; and aquatic ecosystems, such as rivers, lakes, and estuaries); (2) an estimate of the annual potential capacities of ecosystems to increase carbon sequestration and reduce net GHG emissions in the context of mitigation strategies (including management and restoration activities); and (3) an evaluation of the effects of controlling processes, such as climate change, land-use and land-cover change, and disturbances such as wildfires. The concepts of ecosystems, carbon pools, and GHG fluxes follow conventional definitions in use by major national and international assessment or inventory efforts. In order to estimate current ecosystem carbon stocks and GHG fluxes and to understand the potential capacity and effects of mitigation strategies, the method will use two time periods for the assessment: 2001 through 2010, which establishes a current ecosystem carbon and GHG baseline and will be used to validate the models; and 2011 through 2050, which will be used to assess potential capacities based on a set of scenarios. The scenario framework will be constructed using storylines of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES), along with both reference and enhanced land-use and land-cover (LULC) and land-management parameters. Additional LULC and land-management mitigation scenarios will be constructed for each storyline to increase carbon sequestration and reduce GHG fluxes in ecosystems. Input from regional experts and stakeholders will be solicited to construct these scenarios. The methods for mapping the current LULC and ecosystem disturbances will require the extensive use of both remote-sensing data and field-survey data (for example, forest inventories) to capture and characterize landscape-changing events. For potential LULC changes and ecosystem disturbances, key drivers such as socioeconomic and climate changes will be used in addition to the biophysical data. The result of these analyses will be a series of maps for each future year for each scenario. These annual maps will form the basis for estimating carbon storage and GHG emissions. For terrestrial ecosystems, carbon storage, carbon-sequestration capacities, and GHG emissions under the present conditions and future scenarios will be assessed using the LULC-change and ecosystem-disturbance estimates in map format with a spatially explicit biogeochemical ensemble modeling system that incorporates properties of management activities (such as tillage or harvesting) and properties of individual ecosystems (such as energy exchange, vegetation characteristics, hydrological cycling, and soil attributes). For aquatic ecosystems, carbon burial in sediments and fluxes of GHG are functions of the present and future potential stream flow and sediment transport and will be assessed using empirical hydrological modeling methods. Validation and uncertainty analysis methods described in the methodology will follow established guidelines to assess the quality of the assessment results. The U.S. Environmental Protection Agency’s Level II ecoregions map will be the practical instrument for developing and delivering assessment results. Consequently, the ecoregion (there are 22 modified ecoregions) will be the reporting unit of the assessment because the scenarios, assessment results, validation, and uncertainty analysis will be produced at that scale. The implementation of these methods will require collaborations among various Federal agencies, State agencies, nongovernmental organizations, and the science community. Using the method described in this document, the assessment can be completed in approximately 3 to 4 years. The primary deliverables will be assessment reports containing tables, charts, and maps that will present the estimated GHG parameters annually for 2001 through 2050 by ecosystem, pool, and scenario. The results will permit the evaluation of a range of policies, mitigation options, and research topics, such as the demographic, LULC-change, or climate-change effects on carbon stocks, carbon sequestration, and GHG fluxes in ecosystems.

Scientific Investigations Report↗

USGS2011

Inference for occupancy and occupancy dynamics

This chapter deals with the estimation of occupancy as a state variable to assess the status of, and track changes in, species distributions when sampling with camera traps. Much of the recent interest in occupancy estimation and modeling originated from the models developed by MacKenzie et al. (2002, 2003), although similar methods were developed independently (Azuma et al. 1990; Bayley and Petersen 2001; Nichols and Karanth, 2002; Tyre et al. 2003), all of which deal with species occurrence information and imperfect detection. Less than a decade after these publications, the modeling and estimation of species occurrence and occupancy dynamics have increased significantly. Special features of scientific journals have explored innovative uses of detection–nondetection data with occupancy models (Vojta 2005), and an entire volume has synthesized the use and application of occupancy estimation methods (MacKenzie et al. 2006). Reviews of the topical concepts, philosophical considerations, and various sampling designs that can be used for occupancy estimation are now readily available for a range of audiences (MacKenzie and Royle 2005; MacKenzie et al. 2006; Bailey et al. 2007; Royle and Dorazio 2008; Conroy and Carroll 2009; Kendall and White 2009; Hines et al. 2010; Link and Barker 2010). As a result, it would be pointless here to recast all that these publications have so eloquently articulated, but that said, a review of any scientific topic requires sufficient context and relevant background information, especially when relatively new methodologies and techniques such as occupancy estimation and camera traps are involved. This is especially critical in a digital age where new information is published at warp speed, making it increasingly difficult to stay abreast of theoretical advances and research developments.

Book chapter↗

USGS2022

Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi

Mauka-to-makai (mountain to sea in the Hawaiian language) hydrologic connectivity – commonly referred to as ridge-to-reef – directly affects biogeochemical processes and socioecological functions across terrestrial, freshwater, and marine systems. The supply of freshwater to estuarine and nearshore environments in a ridge-to-reef system supports the food, water, and habitats utilized by marine fauna . In addition, the ecosystem services derived from this land-to-sea connectivity support social and cultural practices (hereafter referred to as socio-cultural) including fishing, aquaculture, wetland agriculture, religious ceremonies, and recreational activities. To effectively guide island resource management, a better understanding of the linkages from ridge-to-reef across natural and social usages is critical, particularly in the context of climate change, with anticipated increasing temperature and shifting precipitation patterns. The objective of this study was to identify spatial linkages that promote multiple and diverse uses, following the ridge-to-reef concept, at an island-wide scale to identify regions of high conservation importance for aquatic resources. We selected the Island of Maui as a study representative of many Pacific islands. Diverse datasets, including agricultural lands within watersheds, wetland locations, presence of stream species, indicators of freshwater input from streams, coral cover, nearshore fish biomass, socio-cultural data such as fishpond locations, wetland taro cultivation, beach recreation use, and lastly the dynamically downscaled Coupled Model Intercomparison Project Phase (CMIP5) future climate projections scenarios (Representative Concentration Pathway (RCP) 4.5 & 8.5) were used to examine the spatial linkages through hydrological connectivity from land to the sea. Zonation spatial planning software was used to prioritize areas of high management and conservation value and to help inform aquatic resources management. The resulting prioritized areas included many minimally disturbed watersheds in east Maui and western nearshore and coastal zones that are adjacent to diverse coral reefs. These results are driven by the importance of fish biomass and coral reef distribution as well as traditional wetland taro cultivation and coastal access points for recreation. These results underline the importance of examining ridge-to-reef systems for aquatic resource management and including important social and cultural values in resource management upon planning adaptation strategies for climate change. Improving our understanding of diverse natural and socio-cultural influences on habitat conditions and their values in these areas provides an opportunity to strategically plan future management and conservation actions.

Hawaii↗

USGS2016

A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example

In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon ( Scaphirhynchus albus ) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.

Missouri River↗

USGS1993

1993 Annual Report: San Francisco estuary regional monitoring program for trace substances

This first annual report of the San Francisco Estuary Regional Monitoring Program contains the results of monitoring measurements made in 1993. Measurements of conventional water quality parameters and trace contaminant concentrations were made at 16 stations throughout the Estuary three times during the year: the wet period (March), during declining Delta outflow (May), and during the dry period (September). Water toxicity tests were conducted at 8 of those stations. Measurements of sediment quality and contaminant concentrations were made at the same 16 stations during the wet and dry sampling periods. Sediment toxicity was measured at 8 of those stations. Transplanted, bagged bivalve bioaccumulation and condition was measured at 11 stations during the wet and dry sampling periods. Water Monitoring. Total or near-total (dissolved + particulate, see text) arsenic, cadmium, selenium, and dissolved (0.45 µm filtered) arsenic, cadmium, copper, nickel, silver, and zinc in water were highest in the South Bay. In general, dissolved metals in water were usually lowest in the Central Bay due to ocean influences. Near-total nickel and total mercury in water were highest in the northern estuary (San Pablo and Suisun Bays). Dissolved chromium and lead were highest at the Sacramento and San Joaquin River confluence stations. Six of the ten dissolved trace metals were highest in March during high runoff. Dissolved and total arsenic, selenium, and near-total cadmium were highest in September. Concentrations of trace organic contaminants are reported for the March sampling period. Total PAHs and PCBs were highest in the South Bay, but PCBs were also high in the Napa River. Dissolved PAHs were highest in the Central Bay, and dissolved PCBs were highest in the Napa River. Total and dissolved pesticides were highest in the Sacramento River and in the Extreme South Bay. Concentrations of trace elements in water (except selenium) were usually closely related with other environmental parameters. Total or near-total metals concentrations in water were most often associated with the amount of particulate material (TSS) in the water. Dissolved concentrations were usually associated with salinity or dissolved organic carbon (DOC) content. Dissolved PAHs were well correlated with TSS, but dissolved and total trace organic contaminants were poorly correlated with other water parameters. Based on deviations from conservative mixing of fresh and salt water, three different patterns of possible sources of metals were identified in 1993. For dissolved chromium and lead, rivers and local runoff appeared to be important sources. For dissolved arsenic, cadmium, copper, and nickel year-round inputs from the South Bay appeared to be important sources. Dissolved mercury, selenium, and zinc were associated with local runoff in the South Bay during the wet period. Dissolved silver did not fit any of these patterns. Although most contaminant concentrations were below water quality objectives, several trace contaminants were above the objectives at some stations. Comparisons to water quality objectives are used as a guide for evaluation of contaminant concentrations, but there are some differences in the way the RMP data are measured and that prescribed for regulatory purposes (see text). Concentrations of 5 metals in water were above EPA or Regional Basin Plan water quality objectives at six stations (see Table 30). Most of these elevated levels occurred at the northern estuary stations. Total PCB concentrations were above EPA human health objectives at all RMP stations. The pesticides chlordane, dieldrin, and DDTs were above the EPA objectives at several RMP stations, particularly at the northern-most, and river confluence stations. Although some of the contaminant concentrations were above water quality objectives, water toxicity tests (96 hour algal growth and 48 hour bivalve larval development tests) did not indicate toxicity (sometimes inconclusive) associated with the water samples collected at any of the RMP stations in 1993. Exposure to Bay San Francisco Estuary Regional Monitoring Program Regional Monitoring Program 1993 Report ii water actually enhanced algal growth at most stations. In addition to the Estuary-wide sampling, the Sacramento and San Joaquin Rivers were sampled upstream from their confluence. Stations in each river were sampled six times over a 6 week period of high flows. In the Sacramento River, seven of the ten dissolved metals measured had concentrations lower than those measured at the river confluence stations. Some metals concentrations in the San Joaquin River were higher, and some were lower than concentrations from the river confluence station. Metals concentrations in the Sacramento River were poorly related to river flow because the station at Rio Vista is under considerable tidal influence. In the San Joaquin River, flows were inversely related to 7 of 10 total metals concentrations. Sediment Monitoring. Concentrations of silver, mercury, and lead in sediment were highest in the South Bay. However, concentrations of most trace metals in sediments were highest in the northern estuary at stations with the finest (silt, clay) sediments. The northern estuary stations with the coarsest (sand, shell) sediments generally had the lowest metals concentrations. There were differences in concentrations of cadmium, lead, and selenium in sediments between the sampling periods, but no consistent trend as to which sampling period had higher values. In September, PAHs and PCBs in sediments were highest in the Central Bay, but pesticides in sediments were highest in the northern estuary and Extreme South Bay. NOAA’s Median Effects Ranges (ERM) for sediments were used as a guide for evaluation of sediment contaminant concentrations. Nickel was the only trace contaminant in sediment above the ERM guidelines, and it was high at all RMP stations. These high levels are probably due to natural, geologic sources. Although sediment contaminant concentrations were below ERMs, sediment toxicity tests (10 day amphipod mortality, and 48 hour bivalve larval development in elutriates) indicated toxicity at all stations tested. Sediment factors that could have caused the toxicity were not investigated. Bivalve Bioaccumulation. Mussels, oysters, and freshwater clams were transplanted to the RMP stations to evaluate bioaccumulation of trace substances. Trace metals were bioaccumulated at nearly all RMP stations. However, arsenic, lead, and mercury did not appear to bioaccumulate. There was generally more bioaccumulation during the dry season than during the wet season. In September, PAHs, PCBs, and pesticides accumulated in all samples. Bioaccumulation of PAHs and pesticides was generally highest at the river confluence stations, and the Napa River. PCBs accumulated most at Redwood Creek. There were substantial differences in the degree of bioaccumulation among the species. Oysters appeared to accumulate higher concentrations of trace metals than the other species, especially copper, which may be a natural phenomenon. There are no established tissue contaminant standards for trace metal and organic contaminants. Therefore, comparisons to Median International Standards (MIS) for human consumption, or U.S. Food and Drug Administration (USFDA) action levels for trace organics are used to evaluate the bioaccumulation results. Concentrations of selenium were higher than MIS guidelines at all stations during the wet season. Other trace metal concentrations were higher than MIS guidelines at various stations during one or the other sampling period. However, none of the bivalves contained concentrations above the USFDA or National Academy of Sciences (NAS) guidelines for trace organic contaminants. The transplanted bivalves survived well at all stations except in the Napa River where less than 35% survived during both sampling seasons. Measures of bivalve condition (dry weight, shell volume) indicated that bivalves deployed in the Central Bay grew significantly, but those at most other stations actually lost weight. Whether these differences were due to natural causes such as salinity or food supply, or to contamination, was not determined. Pilot Studies. Two pilot monitoring studies were conducted in 1993. A pilot study of Estuary hydrography and phytoplankton was conducted by scientists from the U.S. Summary Geological Survey in Menlo Park and U.C. Davis. Water column profiles at up to 37 stations were monitored along a transect of the Estuary run monthly between the South Bay and the Delta. The primary objective of this study was to define physical (salinity, temperature, suspended particulate matter, and light penetration), chemical (dissolved oxygen) and biological (chlorophyll a) characteristics of Estuary water that may influence other chemical and biological reactions. A second objective was to investigate planktonic indicators of ecosystem structure and function. The data collected in 1993 showed the extent and duration of the spring phytoplankton bloom in the South Bay, other localized blooms in the northern estuary, the stratification and mixing associated with the entrapment zone in the northern estuary, and mixing in the Estuary resulting from the high rainfall in 1993. Knowledge of the duration and extent of these natural features of the Estuary provide context for interpretation of the RMP contaminant data collected only 3 times per year. Another pilot study of suspended sediment transport processes was conducted by the USGS in Sacramento. This study used continuous recording sensors at Point San Pablo and the Bay Bridge to measure the amount of suspended sediment in the water at mid-depth and near the bottom, as well as tide height. The objectives of this study were to estimate which factors determine suspended solids concentrations in the Central Bay and to collect time series of suspended solids that are appropriate for continuous monitoring of suspended solids and for calibration and validation of numerical models. The investigators determined that spring tides accounted for most of the variation in suspended solids concentrations at the stations monitored, not runoff from the Sacramento or San Joaquin Rivers, or semidiurnal and diurnal tides. Comparisons were also made between measurements made by the continuous recordings and the RMP samples collected during the regular monitoring cruises. The different ways of measuring TSS were generally comparable, however only 3 measurements per year as made by the RMP could not provide the information of TSS variation actually occurring in the Estuary. This information is important because as shown by the RMP data, total contaminant concentrations in Estuary water is largely dependent on the TSS in the water. This implies that the RMP measurements alone cannot determine accurately the range of contaminant concentrations without better characterizing the dynamics of TSS. The RMP Pilot Studies are important to the developing RMP because they will help put RMP measurements into the perspective of Estuary processes and mechanisms at other time scales. The studies can relate those processes to the RMP measurements and will facilitate revision of sampling design and interpretation. Summaries of other monitoring activities pertinent to regional monitoring are also included in the Report: a description of the Regional Board’s Bay Protection Studies, the Sacramento Coordinated Monitoring Program, and a wetlands monitoring plan are included.

California↗

USGS2014

Dissolved-solids sources, loads, yields, and concentrations in streams of the conterminous United States

Recent studies have shown that excessive dissolved-solids concentrations in water can have adverse effects on the environment and on agricultural, domestic, municipal, and industrial water users. Such effects motivated the U.S. Geological Survey’s National Water Quality Assessment Program to develop a SPAtially-Referenced Regression on Watershed Attributes (SPARROW) model that has improved the understanding of sources, loads, yields, and concentrations of dissolved solids in streams of the conterminous United States. Using the SPARROW model, long-term mean annual dissolved-solids loads from 2,560 water-quality monitoring stations were statistically related to several spatial datasets that are surrogates for dissolved-solids sources and land-to-water delivery processes. Specifically, sources in the model included variables representing geologic materials, road deicers, urban lands, cultivated lands, and pasture lands. Transport of dissolved solids from these sources was modulated by land-to-water delivery variables that represent precipitation, streamflow, soil, vegetation, terrain, population, irrigation, and artificial drainage characteristics. Where appropriate, the load estimates, source variables, and transport variables were statistically adjusted to represent conditions for the base year 2000. The nonlinear least-squares estimated SPARROW model was used to predict long-term mean annual conditions for dissolved-solids sources, loads, yields, and concentrations in a digital hydrologic network representing nearly 66,000 stream reaches and their corresponding incremental catchments that drain the Nation. Nationwide, the predominant source of dissolved solids yielded from incremental catchments and delivered to local streams is geologic materials in 89 percent of the catchments, road deicers in 5 percent of the catchments, pasture lands in 3 percent of the catchments, urban lands in 2 percent of the catchments, and cultivated lands in 1 percent of the catchments. Whereas incremental catchments with dissolved solids that originated predominantly from geologic sources or from urban lands are found across much of the Nation, incremental catchments with dissolved solids yields that originated predominantly from road deicers are largely found in the Northeast, and incremental catchments with dissolved solids that originated predominantly from cultivated or pasture lands are largely found in the West. The total amount of dissolved solids delivered to the Nation’s streams is 271.9 million metric tons (Mt) annually, of which 194.2 million Mt (71.4%) come from geologic sources, 37.7 million Mt (13.9%) come from road deicers, 18.2 million Mt (6.7%) come from pasture lands, 13.9 million Mt (5.1%) come from urban lands, and 7.9 million Mt (2.9%) come from cultivated lands. Nationwide, the median incremental-catchment yield delivered to local streams is 26 metric tons per year per square kilometer [(Mt/yr)/km 2 ]. Ten percent of the incremental catchments yield less than 4 (Mt/yr)/km 2 , and 10 percent yield more than 90 (Mt/yr)/km 2 . Incremental-catchment yields greater than 50 (Mt/yr)/km 2 mostly occur along the northern part of the West Coast and in a crescent shaped band south of the Great Lakes. For example, the median incremental-catchment yield is 81 (Mt/yr)/km 2 for the Great Lakes, 78 (Mt/yr)/km 2 for the Ohio, and 74 (Mt/yr)/km 2 for the Upper Mississippi water-resources regions. Incremental-catchment yields less than 10 (Mt/yr)/km 2 mostly occur in a wide band across the arid lowland of the interior West that excludes areas along the coast and the extensive, higher mountain ranges. For example, the median incremental-catchment yield is 3 (Mt/yr)/km 2 for the Lower Colorado, 5 (Mt/yr)/km 2 for the Rio Grande, and 8 (Mt/yr)/km 2 for the Great Basin water-resources regions. Predicted incremental loads were cascaded down through the reach network, with loads accumulating from reach to reach. For most stream reaches, the entire incremental load of dissolved solids delivered to the reach was transported to either the ocean or to one of the large streams flowing along the U.S. international boundary without losses occurring along the way. The exceptions to this include streams in the southwestern part of the country, such as the Colorado River, Rio Grande, and streams of internally drained drainages in the Great Basin, where dissolved-solids loads decreased through streamflow diversion for off-stream use, or by infiltration through the streambed. Long-term mean annual flow-weighted concentrations were derived from the predicted accumulated-load and stream-discharge data. Widespread low concentrations, generally less than 100 milligrams per liter (mg/L), occur in many reaches of the New England, South Atlantic-Gulf, and Pacific Northwest water-resources regions as a result of moderate dissolved-solids yields and high runoff rates. Widespread moderate concentrations, generally between 100 and 500 mg/L, occur in many reaches of the Great Lakes, Ohio, and Upper Mississippi River water-resources regions. Whereas dissolved-solids yields are generally high in these regions, runoff rates are also high, which helps moderate concentrations in these regions. Widespread higher concentrations, generally greater than 500 mg/L, occur across a belt of reaches that extends almost continuously from Canada to Mexico in the Midwest, cutting through the Souris-Red-Rainy, Missouri, Arkansas-White-Red, Texas-Gulf, and Rio Grande water-resources regions. Although dissolved-solids yields are moderate to low in these areas, low runoff rates result in the high concentrations for these areas. In 12.6 percent of the Nation’s stream reaches, predicted concentrations of dissolved solids exceed 500 mg/L, the U.S. Environmental Protection Agency’s secondary, nonenforceable drinking water standard. While this standard provides a metric for evaluating predicted concentrations in the context of drinking-water supplies, it should be noted that it only applies to drinking water actually served to customers by water utilities, and it does not apply to all stream reaches in the Nation nor does it apply during times when water is not being withdrawn for use. Exceedance of 500 mg/L is more pronounced in certain water-resources regions than others. For example, about half of the reaches in the Souris-Red-Rainy region have concentrations predicted to exceed 500 mg/L, and between 25 and 37 percent of the reaches in the Missouri, Arkansas-White-Red, Texas-Gulf, Rio Grande, and Lower Colorado regions are predicted to exceed 500 mg/L. Development of stream-load data for use in the SPARROW model also provided long-term temporal trend information in dissolved-solids concentrations at the monitoring stations for their period of record, which was constrained between 1980 and 2009. For the 2,560 monitoring stations used in this study, long-term trends in flow-adjusted dissolved-solids concentrations increased over time at 23 percent of the stations, decreased at 18 percent of the stations, and did not change over time at 59 percent of the stations. Long-term trends show a strong regional spatial pattern where from the western parts of the Great Plains to the West Coast, concentrations mostly either did not change or decreased over time, and from the eastern parts of the Great Plains to the East Coast, concentrations mostly either did not change or increased over time. Results from the trend analysis and from the SPARROW model indicate that, compared to monitoring stations with no trends or decreasing trends, stations with increasing trends are associated with a smaller percentage of the predicted dissolved-solids load originating from geologic sources, and a larger percentage originating from urban lands and road deicers. Conversely, compared to stations with increasing trends or no trends, stations with decreasing trends have a larger percentage of the predicted dissolved-solids load originating from geologic sources and a smaller percentage originating from urban lands and road deicers. Stations with decreasing trends also have larger percentages of predicted dissolved-solids load originating from cultivated lands and pasture lands, compared to stations with increasing trends or no trends.

Scientific Investigations Report↗

USGS2025

Automated methods for processing camera trap video data for distance sampling

Context Population monitoring is an essential need for tracking biodiversity and judging efficacy of conservation management actions, both globally and in the Pacific. However, population monitoring efforts are often temporally inconsistent and limited to small scales. Motion-activated cameras (‘camera traps’) offer a way to cost-effectively monitor populations, but they also generate large amounts of data that are time intensive to process. Aims To develop an automated pipeline for processing videos of ungulates (Philippine deer, Rusa marianna ; and pigs, Sus scrofa ) on Andersen Air Force Base in Guam. Methods We processed camera videos with a machine learning model for object detection and classification. To estimate density using distance sampling methods, we used a separate machine learning model to estimate the distance of target animals from the camera. We compared density estimates generated using manual versus automated methods and assessed accuracy and processing time saved. Key results The object detection and classification model achieved an overall accuracy >80% and F1 score ≥0.9 and saved 36.9 h of processing time. The automated distance estimation was fairly accurate, with a 1.1 m (±1.4 m) difference from manual distance estimates, and saved 16.8 h of processing time. Density estimates did not differ substantially between manual and automated distance estimation. Conclusions Machine learning models accurately processed camera videos, allowing efficient estimates of density from camera data. Implications Further adoption of motion-activated cameras coupled with automated processing could lead to continuous, large-scale monitoring of populations, helping to understand and address changes in biodiversity.

Guam↗

USGS2010

Estimating migratory game-bird productivity by integrating age ratio and banding data

Context: Reproduction is a critical component of fitness, and understanding factors that influence temporal and spatial dynamics in reproductive output is important for effective management and conservation. Although several indices of reproductive output for wide-ranging species, such as migratory birds, exist, there has been no theoretical justification for their estimators or associated measures of variance. Aims: The aims of our research were to develop statistical justification for an estimator of reproduction and associated variances on the basis of an existing national wing-collection survey and banding data, and to demonstrate the applicability of this estimator to a migratory game bird. Methods: We used a Bayesian hierarchical modelling approach to integrate wing-collection data, which provides information on population age ratios, and band-recovery data, which provides information on recovery probabilities of various age classes, for American woodcock ( Scolopax minor ) to estimate productivity and associated measures of variance. We present two models of relative vulnerability between age classes: one model assumed that adult recovery probabilities were higher, but that annual fluctuations were synchronous between the two age classes (i.e. an additive effect of age and year). The second model assumed that adults, on average, had higher recovery probabilities than did juveniles and that annual fluctuations were asynchronous through time (i.e. an interaction between age and year). Key results: Fitting our models within a hierarchical Bayesian framework efficiently incorporates the two data types into a single estimator and derives appropriate variances for the productivity estimator. Further, use of Bayesian methods enabled us to derive credible intervals that avoid the reliance on asymptotic assumptions. When applied to American woodcock data, the additive model resulted in biologically realistic and more precise age-ratio estimates each year and is adequate when the relative vulnerability to sampling only slightly varies or does not vary among components of a population (e.g. age, sex class) among years. Therefore, we recommend using woodcock indices from our analysis based on this model. Conclusions: We provide a flexible modelling framework for estimating productivity and associated variances that can incorporate ecological covariates to explore various factors that could drive annual dynamics in productivity. Applying our model to the American woodcock data indicated that assumptions about the variability in relative recovery probabilities could greatly influence the precision of our productivity estimator. Therefore, researchers should carefully consider the assumption of temporally variable relative recovery probabilities (i.e. ratio of juvenile to adults' recovery probability) for different age classes when applying this estimator. Implications: Several national and international management strategies for migratory game birds in North America rely on measures of productivity from harvest survey parts collections, without a justification of the estimator or providing estimates of precision. We derive an estimator of productivity with realistic measures of uncertainty that can be directly incorporated into management plans or ecological studies across large spatial scales.

Wildlife Research↗

USGS2019

Left out in the rain: Comparing productivity of two associated species exposes a leak in the umbrella species concept

Multi-species approaches to wildlife management have become commonplace and purport to benefit entire biological communities. These strategies aim to manage different, often taxonomically distant species under a single regime based on shared habitat associations and/or co-occurrence in the landscape. We tested the efficacy of multi-species management in the context of creating and maintaining early-successional forest cover types using two species of migratory birds that breed in eastern North America and are each the focus of intensive, concurrent, and overlapping management. American woodcock ( Scolopax minor ) and golden-winged warblers ( Vermivora chrysoptera ) breed in similar diverse-forest landscapes. Each species purportedly benefits from management for the other species and both are often used as flagship species for the creation of young forest and the conservation of associated avian communities. However, the landscape-species relationships that drive reproductive success and population stability in these species have not been explicitly compared. Here, we use previously published spatially-explicit models of productivity (the number of juveniles raised to a biologically significant milestone) to identify the relationship(s) between productivity of American woodcock and golden-winged warblers across a shared landscape. We found productivity to be negatively associated between these species on the same landscape at all spatial scales we modelled (1 m 2 –100 ha). Our results suggest that, with regards to productivity, American woodcock and golden-winged warblers have opposing relationships with the composition of the landscapes in which they coexist and therefore should not be assumed to benefit similarly from any individual management action at any relevant spatial scale.

Biological Conservation↗

USGS2017

A Bayesian method for assessing multiscalespecies-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Nebraska↗

USGS2016

Lake oxygen isotopes as recorders of North American Rocky Mountain hydroclimate: Holocene patterns and variability at multi-decadal to millennial time scales

Lake sediment oxygen isotope records (calcium carbonate-δ 18 O) in the western North American Cordillera developed during the past decade provide substantial evidence of Pacific ocean–atmosphere forcing of hydroclimatic variability during the Holocene. Here we present an overview of 18 lake sediment δ 18 O records along with a new compilation of lake water δ 18 O and δ 2 H that are used to characterize lake sediment sensitivity to precipitation-δ 18 O in contrast to fractionation by evaporation. Of the 18 records, 14 have substantial sensitivity to evaporation. Two records reflect precipitation-δ 18 O since the middle Holocene, Jellybean and Bison Lakes, and are geographically positioned in the northern and southern regions of the study area. Their comparative analysis indicates a sequence of time-varying north–south precipitation-δ 18 O patterns that is evidence for a highly non-stationary influence by Pacific ocean–atmosphere processes on the hydroclimate of western North America. These observations are discussed within the context of previous research on North Pacific precipitation-δ 18 O based on empirical and modeling methods. The Jellybean and Bison Lake records indicate that a prominent precipitation-δ 18 O dipole (enriched-north and depleted-south) was sustained between ~ 3.5 and 1.5 ka, which contrasts with earlier Holocene patterns, and appears to indicate the onset of a dominant tropical control on North Pacific ocean–atmosphere dynamics. This remains the state of the system today. Higher frequency reversals of the north–south precipitation-δ 18 O dipole between ~ 2.5 and 1.5 ka, and during the Medieval Climate Anomaly and the Little Ice Age, also suggest more varieties of Pacific ocean–atmosphere modes than a single Pacific Decadal Oscillation (PDO) type analogue. Results indicate that further investigation of precipitation-δ 18 O patterns on short (observational) and long (Holocene) time scales is needed to improve our understanding of the processes that drive regional precipitation-δ 18 O responses to Pacific ocean–atmosphere variability, which in turn, will lead to a better understanding of internal Pacific ocean–atmosphere variability and its response to external climate forcing mechanisms.

North American Rocky Mountain↗