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At least 1,189 records · Page 66Linked to original sources

USGS2004

In-flight validation and recovery of water surface temperature with Landsat-5 thermal infrared data using an automated high-altitude lake validation site at Lake Tahoe

The absolute radiometric accuracy of the thermal infrared band (B6) of the Thematic Mapper (TM) instrument on the Landsat-5 (L5) satellite was assessed over a period of approximately four years using data from the Lake Tahoe automated validation site (California-Nevada). The Lake Tahoe site was established in July 1999, and measurements of the skin and bulk temperature have been made approximately every 2 min from four permanently moored buoys since mid-1999. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the L5 overpass to predict the at-sensor radiance. The predicted radiance was then convolved with the L5B6 system response function to obtain the predicted L5B6 radiance, which was then compared with the radiance measured by L5B6. Twenty-four cloud-free scenes acquired between 1999 and 2003 were used in the analysis with scene temperatures ranging between 4/spl deg/C and 22/spl deg/C. The results indicate L5B6 had a radiance bias of 2.5% (1.6/spl deg/C) in late 1999, which gradually decreased to 0.8% (0.5/spl deg/C) in mid-2002. Since that time, the bias has remained positive (predicted minus measured) and between 0.3% (0.2/spl deg/C) and 1.4% (0.9/spl deg/C). The cause for the cold bias (L5 radiances are lower than expected) is unresolved, but likely related to changes in instrument temperature associated with changes in instrument usage. The in situ data were then used to develop algorithms to recover the skin and bulk temperature of the water by regressing the L5B6 radiance and the National Center for Environmental Prediction (NCEP) total column water data to either the skin or bulk temperature. Use of the NCEP data provides an alternative approach to the split-window approach used with instruments that have two thermal infrared bands. The results indicate the surface skin and bulk temperature can be recovered with a standard error of 0.6/spl deg/C. This error is larger than errors obtained with other instruments due, in part, to the calibration bias. L5 provides the only long-duration high spatial resolution thermal infrared measurements of the land surface. If these data are to be used effectively in studies designed to monitor change, it is essential to continue to monitor instrument performance in-flight and develop quantitative algorithms for recovering surface temperature.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2019

Updates to the Madison Lake (Minnesota) CE–QUAL–W2 water-quality model for assessing algal community dynamics

A previously developed CE–QUAL–W2 model for Madison Lake, Minnesota, simulated the algal community dynamics, water quality, and fish habitat suitability of Madison Lake under recent (2014) meteorological conditions. Additionally, this previously developed model simulated the complex interplay between external nutrient loading, internal nutrient loading from sediment release of phosphorus, and the organic matter decomposition of the algal biomass. However, the partitioning of Cyanophyta within the modeling framework was simplified to one group and did not account for how different Cyanophyta populations are affected by light conditions, use of nitrogen, temperature growth ranges, and differences in settling rates. Properly capturing Cyanophyta dynamics is important given the potential risks posed by potential large algal blooms. For example, when Cyanophyta form large blooms, recreational activities can become restricted in certain areas because of thick algal scums or algal mats, in addition to the possible production of a class of toxins, known as cyanotoxins, capable of threatening human health, domestic animals, and wildlife. Therefore, we updated the model to partition the Cyanophyta into a group that fixed nitrogen and a second, more buoyant Cyanophyta group that did not independently fix nitrogen. The U.S. Geological Survey, in cooperation with the St. Croix Watershed Research Station (Science Museum of Minnesota) with support from the Environmental and Natural Resources Trust Fund of Minnesota (Legislative-Citizen Commission on Minnesota Resources), updated the Madison Lake CE–QUAL–W2 model to address the shortcomings of simulating Cyanophyta in the previously developed model and better characterize Cyanophyta into two groups. In addition to updating the Cyanophyta group differentiation, the part of the model that handles the simulation of algal community dynamics was updated while preserving model predictive capabilities for nutrients, water temperature, and dissolved oxygen. The calibration and validation of the model was done under recent meteorological conditions with large and persistent Cyanophyta blooms (2014 and 2016). Overall, the model simulations predicted the persistently large total phosphorus concentrations in the hypolimnion of Madison Lake and key differences in nutrient concentrations between 2014 and 2016. The Cyanophyta bloom persistence throughout the summer was also simulated by the model in 2014 and 2016, a critical goal of the model update. Finally, monthly total phosphorus budgets were calculated for the updated Madison Lake model for 2014 and 2016.

Minnesota↗

USGS2018

Current research in land, water, and agroecosystems: ASABE journals 2017 year in review

This article highlights current research into land and water resources, agroecosystems, and agricultural production systems published by the Natural Resources and Environmental Systems (NRES) community of ASABE journals (Transactions of the ASABE and Applied Engineering in Agriculture) in 2017. This article reviews the context, scope, and key results of the published articles and perhaps more importantly recommends areas for increased research attention. Experimental and modeling advances were described in hydrology, agroecosystems, climate-change effects, soil erosion, irrigation, drainage, forest resources, livestock systems, natural treatment systems, international water issues, and water quality topic areas. Three special collections were published (International Watershed Technology, Crop Modeling to Optimize Water Use, and Advances in Drainage). Other focal areas included 14 articles relating to livestock waste management, 13 concerning irrigated agricultural systems, 8 addressing climate change effects on land and water resources, and 16 on various aspects of soil erosion measurement and modeling. Building on the articles reviewed from 2017 and toward a vision of future agroecosystems research, the NRES community of ASABE journals strives to grow its role in making new knowledge accessible to sustain agricultural and natural systems in a changing world. In this vane, recommendations for future research direction are discussed with an emphasis on increased application of remote sensing data to agroecosystems research, improved assessment of agroecosystem resiliency and vulnerability to land and climate change, development of integrated models of agroecosystem services, meeting stubborn water management challenges in agricultural production systems, and focusing on publishing fully reproducible model results.

Transactions of the ASABE↗

USGS2015

Web based visualization of large climate data sets

We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

Environmental Modelling and Software↗

USGS2010

Land Disturbance Associated with Oil and Gas Development and Effects of Development-Related Land Disturbance on Dissolved-Solids Loads in Streams in the Upper Colorado River Basin, 1991, 2007, and 2025

Oil and gas resource development in the Upper Colorado River Basin (UCRB) has increased substantially since the year 2000. The UCRB encompasses several significant oil and gas producing areas that have the potential for continued oil and gas resource development. Land disturbance associated with oil and gas resource development is caused by activities related to constructing drill pads to contain drilling and well maintenance equipment and roads to access the drill pad. Land disturbed by oil and gas development has the potential to cause increased erosion, stream degradation, habitat fragmentation and alteration, and increase public use of areas that may be environmentally sensitive. Land disturbance resulting from oil and gas resource development has not been monitored and mapped on a regional scale in the UCRB. However, information on the location and age of oil and gas wells in the UCRB is available. These data combined with geographic data analysis and modeling techniques were used to estimate the total area of disturbed land associated with oil and gas resource development in 1991 and in 2007 in the UCRB. Additional information about anticipated oil and gas development in the UCRB was used to project land disturbance to the year 2025. Results of the analysis indicate that approximately 117,500 acres (183 mi2) of total land disturbance was associated with drill pads and related roads in the UCRB in 1991. The estimated area of disturbed land associated with oil and gas development increased 53 percent to 179,400 acres (280 mi2) in 2007. Projecting oil and gas development through 2025 results in a potential near doubling of the land surface disturbance to approximately 319,300 acres (500 mi2). Estimated land disturbance for 1991 and 2007 were input to a contaminant transport model developed for the UCRB to assess the statistical significance of energy-related land disturbance to contributing dissolved solids to basin streams. The statistical assessment was an observational study based on an existing model and available water-quality monitoring data for the basin. No new data were collected for the analysis. The source coefficient calibrated for the disturbed lands associated with oil and gas development in 2007 was zero, which indicated that estimated land disturbance from oil and gas development is not statistically significant in explaining dissolved solids in UCRB streams. The lack of significance in the contaminant transport modeling framework may be due to the amount of available monitoring data, the spatial distribution of monitoring sites with respect to land disturbance, or the overall quantity of land disturbance associated with oil and gas development basin wide. Finally, dissolved-solids loads derived from natural landscapes may be similar to loads derived from lands disturbed by oil and gas resource development. The model recalibration done for this study confirms calibration results from Kenney and others (2009): the most significant contributor to dissolved solids in the UCRB is irrigated agricultural land, which covers an area substantially larger than the estimated area disturbed by oil and gas development and is subjected to artificially applied water.

Scientific Investigations Report↗

USGS2021

Enhancing the application of Earth observations for improved environmental decision-making using the Early Warning eXplorer (EWX)

The mitigation of losses due to extreme climate events and long-term climate adaptation requires climate informed decision-making. In the past few decades, several remote sensing and modeled-based Earth observations (EOs) have been developed to provide an unprecedented global overview and routine monitoring of climate and its impacts on vegetation and hydrologic conditions, with the goal of supporting informed decision-making. However, their usage in decision-making is particularly limited in climate-risk vulnerable and in situ data-scarce regions such as sub-Saharan Africa, due to lack of access to EOs. Here, we describe the Early Warning eXplorer (EWX), which was developed to address this crucial limitation and facilitate the application of EOs in decision-making, particularly in the food and water-insecure regions of the world. First, the EWX's core framework, which includes (i) the Viewer, (ii) GeoEngine, and (iii) Support Applications, is described. Then, a comprehensive overview of the Viewer, which is a web-based interface used to access EOs, is provided. This includes a description of (i) the maps and associated features to access gridded EO data and anomalies for different temporal averaging periods, (ii) time series graphs and associated features to access EOs aggregated over polygons such as administrative boundaries, and (iii) commonly used EOs served by the EWX that provide assessments of climate and vegetation conditions. Next, examples are provided to demonstrate how EWX can be used to monitor development, progression, spatial extent, and severity of climate-driven extreme events to support timely decisions related to mitigation of food insecurity and flooding impacts. Finally, the value of a regional implementation of EWX at the Regional Centre for Mapping of Resources for Development (RCMRD) in Nairobi, Kenya, is highlighted. Regional implementation of the EWX facilitates access to regionally focused EOs and their availability at polygon boundaries most relevant to the local decision-makers. Similar instances of EWX implemented in other regions, especially those susceptible to food and water security, will likely further enhance the application of EOs for informed decision-making.

Frontiers in Climate↗

USGS2012

Evidence, models, conservation programs and limits to management

Walsh et al. (2012) emphasized the importance of obtaining evidence to assess the effects of management actions on state variables relevant to objectives of conservation programs. They focused on malleefowl Leipoa ocellata, ground-dwelling Australian megapodes listed as vulnerable. They noted that although fox Vulpes vulpes baiting is the main management action used in malleefowl conservation throughout southern Australia, evidence of the effectiveness of this action is limited and currently debated. Walsh et al. (2012) then used data from 64 sites monitored for malleefowl and foxes over 23 years to assess key functional relationships relevant to fox control as a conservation action for malleefowl. In one set of analyses, Walsh et al. (2012) focused on two relationships: fox baiting investment versus fox presence, and fox presence versus malleefowl population size and rate of population change. Results led to the counterintuitive conclusion that increases in investments in fox control produced slight decreases in malleefowl population size and growth. In a second set of analyses, Walsh et al. (2012) directly assessed the relationship between investment in fox baiting and malleefowl population size and rate of population change. This set of analyses showed no significant relationship between investment in fox population control and malleefowl population growth. Both sets of analyses benefited from the incorporation of key environmental covariates hypothesized to influence these management relationships. Walsh et al. (2012) concluded that "in most situations, malleefowl conservation did not effectively benefit from fox baiting at current levels of investment." In this commentary, I discuss the work of Walsh et al. (2012) using the conceptual framework of structured decision making (SDM). In doing so, I accept their analytic results and associated conclusions as accurate and discuss basic ideas about evidence, conservation and limits to management.

Animal Conservation↗

USGS2025

Ecological factors decouple Great Lakes fish mercury concentrations trends decadal declines in mercury emissions

Atmospheric mercury (Hg) deposition has been declining in North America but remains the dominant delivery mechanism to the Great Lakes. The Lakes are highly efficient at bioaccumulating methylmercury, making the fish excellent sentinels for tracking shifts in atmospheric Hg deposition. Invasive mussels have altered biogeochemical processes, prey populations and fish dietary strategies asynchronously and to varied extents across the lower four lakes, impacting fish Hg exposure. To test if fish are adapting to new biogeochemical conditions, we analyzed a 40 year fish archive for carbon and nitrogen isotope ratios and amino acid-specific nitrogen isotope ratios. To assess Hg sources, we measured Hg isotope ratios. We reconstructed and compared energetic pathways that impact fish Hg concentrations to Hg-source trends. We found fish-Hg concentrations are declining but not monotonically due to ecological disturbances. Fish-Hg isotope values, unimpacted by ecological disturbance, confirm that sources of bioaccumulated Hg shift contemporaneously with changes in atmospheric Hg concentrations. Across Lakes, the degree of responsiveness to changes in atmospheric Hg concentrations mirrors the proportion of atmospheric-delivered Hg we previously modeled. Changes in both fish concentrations and fish isotope values outpace paleolimnetic reconstructions suggesting declines in atmospheric Hg concentrations impact fish Hg more than sediment.

Great Lakes↗

USGS2010

Federal land management, carbon sequestration, and climate change in the Southeastern U.S.: a case study with fort benning

Land use activities can have a major impact on the temporal trendsandspatialpatternsofregionalland-atmosphereexchange of carbon. Federal lands generally have substantially different land management strategies from surrounding areas, and the carbon consequences have rarely been quantified and assessed. Using the Fort Benning Installation as a case study, we used the General Ensemble biogeochemical Modeling System (GEMS) to simulate and compare ecosystem carbon sequestration between the U.S. Army's Fort Benning and surrounding areas from 1992 to 2050. Our results indicate that the military installation sequestered more carbon than surrounding areas from 1992 to 2007 (76.7 vs 18.5 g C m -2 yr -1 ), and is projected to continue sequestering more carbon from 2008 to 2050 (75.7 vs 25.6 g C m -2 yr -1 ), mostly because of the proactive management approaches adopted on military training lands. Our results suggest that federal lands might play a positive and important role in sequestering and conserving atmospheric carbon because some anthropogenic disturbances (e.g., urbanization, forest harvesting, and agriculture) can be minimized or prevented on federal lands

Georgia↗

USGS2024

Improving ecosystem health in highly altered river basins: A generalized framework and its application to the Mississippi-Atchafalaya River Basin

Continued large-scale public investment in declining ecosystems depends on demonstrations of “success”. While the public conception of “success” often focuses on restoration to a pre-disturbance condition, the scientific community is more likely to measure success in terms of improved ecosystem health. Using a combination of literature review, workshops and expert solicitation we propose a generalized framework to improve ecosystem health in highly altered river basins by reducing ecosystem stressors, enhancing ecosystem processes and increasing ecosystem resilience. We illustrate the use of this framework in the Mississippi-Atchafalaya River Basin (MARB) of the central United States (U.S.), by (i) identifying key stressors related to human activities, and (ii) creating a conceptual ecosystem model relating those stressors to effects on ecosystem structure and processes. As a result of our analysis, we identify a set of landscape-level indicators of ecosystem health, emphasizing leading indicators of stressor removal (e.g., reduced anthropogenic nutrient inputs), increased ecosystem function (e.g., increased water storage in the landscape) and increased resilience (e.g., changes in the percentage of perennial vegetative cover). We suggest that by including these indicators, along with lagging indicators such as direct measurements of water quality, stakeholders will be better able to assess the effectiveness of management actions. For example, if both leading and lagging indicators show improvement over time, then management actions are on track to attain desired ecosystem condition. If, however, leading indicators are not improving or even declining, then fundamental challenges to ecosystem health remain to be addressed and failure to address these will ultimately lead to declines in lagging indicators such as water quality. Although our model and indicators are specific to the MARB, we believe that the generalized framework and the process of model and indicator development will be valuable in an array of altered river basins.

Mississippi-Atchafalaya River Basin↗

USGS2021

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems

Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R 2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha −1 . Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.

Remote Sensing in Ecology and Conservation↗

USGS2012

Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States

The National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS) is conducting a regional analysis of water quality in the principal aquifer systems across the United States. The Southwest Principal Aquifers (SWPA) study is building a better understanding of the susceptibility and vulnerability of basin-fill aquifers in the region to groundwater contamination by synthesizing baseline knowledge of groundwater-quality conditions in 16 basins previously studied by the NAWQA Program. The improved understanding of aquifer susceptibility and vulnerability to contamination is assisting in the development of tools that water managers can use to assess and protect the quality of groundwater resources. Human-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate contamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamination and relate nitrate and arsenic concentrations to explanatory variables representing local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions. The classifiers were unbiased and fit the observed data well, and misclassifications were primarily due to statistical sampling error in the training datasets. The classifiers were designed to predict concentrations to be in one of six classes for nitrate, and one of seven classes for arsenic. Each classification scheme allowed for identification of areas with concentrations that were equal to or exceeding the U.S. Environmental Protection Agency drinking-water standard. Whereas 2.4 percent of the area underlain by basin-fill aquifers in the study area was predicted to equal or exceed this standard for nitrate (10 milligrams per liter as N; mg/L), 42.7 percent was predicted to equal or exceed the standard for arsenic (10 micrograms per liter; μg/L). Areas predicted to equal or exceed the drinking-water standard for nitrate include basins in central Arizona near Phoenix; the San Joaquin, Inland, and San Jacinto basins of California; and the San Luis Valley of Colorado. Much of the area predicted to equal or exceed the drinking-water standard for arsenic is within a belt of basins along the western portion of the Basin and Range Physiographic Province in Nevada, California, and Arizona. Predicted nitrate and arsenic concentrations are substantially lower than the drinking-water standards in much of the study area—about 93.0 percent of the area underlain by basin-fill aquifers was less than one-half the standard for nitrate (5.0 mg/L), and 50.2 percent was less than one-half the standard for arsenic (5.0 μg/L).

Arizona, California, Colorado, Nevada, New Mexico,↗

USGS2023

Simulation of flow and eutrophication in the central Salem River, New Jersey

The central Salem River in New Jersey is subject to periods of water-quality impairment, marked by elevated concentrations of phosphorus and chlorophyll- a , and low concentrations of and large diurnal swings in concentrations of dissolved oxygen. These seasonal eutrophic conditions are controlling factors for water quality in lower reaches, where the river is more lacustrine than in upper reaches, as a result of downstream damming. This biological productivity is supported by nutrient wash-off from agricultural areas in the surrounding watershed. To investigate this impairment, flow measurement and water-quality sampling were conducted during 2007–08 in support of development of a one-dimensional surface-water-quality model that simulates nutrient cycling and transformation processes. The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection, used the U.S. Environmental Protection Agency Water Quality Analysis Simulation Program (WASP) to develop a receiving-water-quality model of the central Salem River between Woodstown and Deepwater, New Jersey, from April 2007 to October 2008. The main-stem river and largest tributary were simulated. In the flow model, kinematic wave flow is used to simulate flow in upper reaches and ponded weir flow is used to simulate flow in lower reaches. The water-quality model makes use of a mass-balance equation to simulate the fate and transport of nutrients, phytoplankton chlorophyll- a , dissolved oxygen, and oxygen demands (an indicator rather than a substance) in the river. Model input included channel characteristics, boundary conditions for flow and water quality, environmental parameters, vertical dispersion coefficients, settling rates, and kinetic constants. Inputs were estimated where field data were lacking, notably for tributary flows and nutrient loads. The model was calibrated to observed flow variables and concentrations of dissolved oxygen, chlorophyll- a , and nutrients at sampling locations, with emphasis on growing-season conditions. Calibration was achieved through graphical and statistical comparison of simulated results to observed data. Sensitivity analyses were performed, and model limitations and applicability were evaluated. Simulated results closely matched observed data in most cases, although some were overpredicted slightly. The most important causes of overprediction were estimated tributary flows for the flow model and estimated tributary watershed loads for the water-quality model. Calibration of dissolved-oxygen concentrations was closer, and predicted diurnal variations were consistent with high algal photosynthesis/respiration, although lack of continuous dissolved-oxygen data precluded verifying these predictions. A similar caveat applies to predicted diurnal variations in chlorophyll- a . Simulated limitations on algal growth were consistent with those based on observed data and indicated phosphorus was the main limiting nutrient, except during certain periods when nitrogen was limiting. Two water-quality management scenarios were simulated with the model to assess the effect of point- and nonpoint-source nutrient reductions on water-quality conditions in the river. Scenarios involved (1) a return of watershed land use to predevelopment natural conditions and (2) an extreme reduction in nutrient input. Although the extreme-nutrient-reduction scenario yielded improvements in water quality, the natural-conditions scenario yielded the largest improvements as indicated by minimal violations of surface-water-quality standards or thresholds. However, years may be needed to attain the full benefit of these management scenarios as a result of accumulation of phosphorus and organic carbon in riverbed sediments in lacustrine reaches. The results of this study indicate that the quality of water in the central Salem River will improve if management policies that mitigate the effects of nutrient-loading practices in the watershed, particularly those related to agriculture, are implemented.

New Jersey↗

USGS2025

The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi

Palila ( Loxioides bailleui ) are critically endangered Hawaiian honeycreepers specializing on māmane ( Sophora chrysophylla ) seeds and restricted to Mauna Kea volcano on the Island of Hawaiʻi. Recently, the population was estimated to decline by 89% between 1998 and 2021, despite decades of ungulate removal, fence construction, māmane regeneration, fire suppression, and predator control. To inform managers with the most recent update on the status and trends of the Palila population, we analyzed annual bird survey data collected using point-transect distance sampling since 1998, including new annual survey data from 2022, 2023, and 2024. Prior to analysis, we predicted the population trajectory would change between 2021 and 2024 because of continued management actions promoting habitat recovery. We used distance sampling, log-linear regression, and state-space modeling to produce the new estimates and analyze trends across the time series. The 2022 population estimate was 367 to 742 birds (95% confidence interval; point estimate: 545), the lowest in recorded history. The 2023 and 2024 estimates of 374 to 842 birds (point estimate: 596) and 412 to 970 birds (point estimate: 666) were the second and third lowest in our time series, respectively. Our estimates for years before 2022 show population fluctuations between 4000 to 6800 birds from 1998 to 2005, then a steep decline through 2010. For the next decade, abundance fluctuated around 1000 birds, before declining again in 2021 to less than 700 birds. From 1998 to 2024, the population declined by more than 90%, or 205 birds per year, with 100% statistical support for an overall downward trend, despite significant management efforts and research. The greatest threats facing the Palila, if familiar, are not being eliminated swiftly enough to promote their recovery. The currently small and range-limited population is vulnerable to future climate-related events such as drought and fire. Continued monitoring can help to assess the response of Palila to adaptive management actions and changing environmental conditions.

Hawaii↗

USGS2022

Nitrogen enrichment during soil organic matter burning and molecular evidence of maillard reactions

Wildfires in forested watersheds dramatically alter stored and labile soil organic matter (SOM) pools and the export of dissolved organic matter (DOM). Ecosystem recovery after wildfires depends on soil microbial communities and revegetation and therefore is limited by the availability of nutrients, such as nitrogen-containing and labile, water-soluble compounds. However, SOM byproducts produced at different wildfire intensities are poorly understood, leading to difficulties in assessing wildfire severity and predicting ecosystem recovery. In this work, water-extractable organic matter (WEOM) from laboratory microcosms of soil burned at discrete temperatures was characterized by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry to study the impacts of fire temperature on SOM and DOM composition. The molecular composition derived from different burn temperatures indicated that nitrogen-containing byproducts were enriched with heating and composed of a wide range of aromatic features and oxidation states. Mass difference-based analysis also suggested that products formed during heating could be modeled using transformations along the Maillard reaction pathway. The enrichment of N-containing SOM and DOM at different soil burning intensities has important implications for ecosystem recovery and downstream water quality.

Environmental Science and Technology↗

USGS2006

Integration of coral reef ecosystem process studies and remote sensing

Worldwide, local-scale anthropogenic stress combined with global climate change is driving shifts in the state of reef benthic communities from coral-rich to micro- or macroalgal-dominated (Knowlton, 1992; Done, 1999). Such phase shifts in reef benthic communities may be either abrupt or gradual, and case studies from diverse ocean basins demonstrate that recovery, while uncertain (Hughes, 1994), typically involves progression through successional stages (Done, 1992). These transitions in benthic community structure involve changes in community metabolism, and accordingly, the holistic evaluation of associated biogeochemical variables is of great intrinsic value (Done, 1992). Effective reef management requires advance prediction of coral reef alteration in the face of anthropogenic stress and change in the global environment (Hatcher, 1997a). In practice, this goal requires techniques that can rapidly discern, at an early stage, sublethal effects that may cause long-term increases in mortality (brown, 1988; Grigg and Dollar, 1990). Such methods would improve our understanding of the differences in the population, community, and ecosystem structure, as well as function, between pristine and degraded reefs. This knowledge base could then support scientifically based management strategies (Done, 1992). Brown (1988) noted the general lack of rigor in the assessment of stress on coral reefs and suggested that more quantitative approaches than currently exist are needed to allow objective understanding of coral reef dynamics. Sensitive techniques for the timely appraisal of pollution effects or generalized endemic stress in coral reefs are sorely lacking (Grigg and Dollar, 1990; Wilkinsin, 1992). Moreover, monitoring methods based on population inventories, sclerochronology, or reproductive biology tend to myopic and may give inconsistent results. Ideally, an improved means of evaluating reef stress would discriminate mortality due to natural causes from morality to anthropogenic causes (Brown, 1988). Models of coral reef ecosystems, parameterized by process measurements and scaled in time-space using remote sensing, have the potential to address pressing research questions that are central to devising valid management strategies (Grigg el al., 1984; Hatcher, 1997b). To attain this goal, ecosystem-level models that integrate studies of physical and chemical forcing with observed biological and geological responses are required. This interdisciplinary approach to understanding reef biogeochemical dynamics can allow investigations that integrate the scales of time and space (Hatcher, 1997a), thereby enabling prediction of coral reef change (Andréfouët and Payri, 2001). In turn, prediction of holistic ecosystem function within various environmental focusing scenarios has substantial promise in mitigating future disturbance. Indeed, management of coral reefs at the ecosystem level has been suggested as the only meaningful approach to preserving coral reefs (Bohnsack and Ault, 1996; Christensen et al., 1996).

Florida↗

USGS2011

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models.

Maine↗

USGS2015

Geochemical conditions and the occurrence of selected trace elements in groundwater basins used for public drinking-water supply, Desert and Basin and Range hydrogeologic provinces, 2006-11: California GAMA Priority Basin Project

The geochemical conditions, occurrence of selected trace elements, and processes controlling the occurrence of selected trace elements in groundwater were investigated in groundwater basins of the Desert and Basin and Range (DBR) hydrogeologic provinces in southeastern California as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA PBP is designed to provide an assessment of the quality of untreated (raw) groundwater in the aquifer systems that are used for public drinking-water supply. The GAMA PBP is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey and the Lawrence Livermore National Laboratory. The DBR hydrogeologic provinces consist of 141 defined groundwater basins separated by mountain ranges, faults, and other features. This report presents analyses of data collected from nine study areas within the DBR hydrogeologic provinces: Antelope Valley, Borrego Valley, the Central Desert area, Coachella Valley, Colorado River, Indian Wells Valley, Low-Use Basins of the Mojave and Sonoran Deserts, the Mojave, and Owens Valley. Collectively, these nine study areas are referred to as the DBR study unit. The study unit covers approximately 7,000 square miles and includes the 63 groundwater basins in the DBR hydrogeologic provinces in which groundwater is used for public drinking-water supply. The vast majority of the 223 wells sampled for this study were long-screened production wells used primarily for public supply. Uncorrected carbon-14 ( 14 C) groundwater ages for samples collected in the DBR study unit ranged from less than (<) 100 to 33,700 years before present (BP). Sixty-six percent of sample ages were greater than (>) 100 years BP, and 40 percent were >3,800 years BP. Samples collected from wells located adjacent to mountain-front recharge areas or major surface-water features generally had younger groundwater ages than did samples collected from wells located away from mountain fronts or towards the distal ends of basin groundwater flow paths. Most groundwater sampled in the DBR study unit had alkaline pH: 89 percent of sample pH values ranged from 7.1 to 9.8, with 37 percent greater than or equal to (≥) 7.9. Groundwater age was significantly correlated (positively) with pH, likely because silicate weathering is a primary control on groundwater pH and is a slow process. The oxidation-reduction (redox) condition of the groundwater sampled in the DBR study unit was predominantly oxic (71 percent), except in the Colorado River study area where organic-rich fluvial aquifers provide the electron donors necessary to support iron-reducing (anoxic-Fe) redox processes. The cation type of 78 percent of the samples was either sodium- or mixed-type, and the anion type of 83 percent of the samples was either bicarbonate- or mixed-type. Sodium-type groundwaters generally were older and more alkaline than calcium-type groundwaters, consistent with the change in water chemistry expected from cation exchange between groundwater and aquifer sediments over long periods of time. Because of the correlation with young groundwater, calcium-type groundwater was predominantly from wells located adjacent to mountain-front recharge areas. Arsenic (As), boron (B), fluoride (F), molybdenum (Mo), strontium (Sr), uranium (U), and vanadium (V) were selected for assessment in this study because they occurred at concentrations greater than California Department of Public Health or U.S. Environmental Protection Agency regulatory or non-regulatory drinking-water-quality benchmarks in more than 2 percent of the 223 samples collected in the DBR study unit. As and F were detected most commonly (18 and 13 percent, respectively) at concentrations above associated water-quality benchmarks and Sr and V least frequently (both at 3 percent). Given that 14 C groundwater ages are predominantly >100 years BP, land use in the study unit is primarily undeveloped, and chemicals derived from anthropogenic sources, such as volatile organic compounds, were infrequently detected, high concentrations of these trace elements in groundwater were most likely the result of natural factors and not anthropogenic factors. As, F, Mo, and V concentrations showed significant positive correlations to groundwater age and to pH. This relation is partly due to the sources of trace elements likely being the weathering of primary minerals, such as silicate minerals, which is a slow process that takes place over hundreds to thousands of years. This relation also reflects the positive correlation between groundwater age and pH. Geochemical modeling predicted that the dominant species of As, Mo, and V in solution were oxyanions (HAsO 4 2– , MoO 4 2– , and H 2 VO 4– ), which are likely to be mobile in alkaline groundwater because mineral surfaces composing aquifer matrices have a predominantly negative surface charge under alkaline conditions. F also exists predominantly as a negatively charged ion (F – ). At pH values >7.5, saturation indices generated by the geochemical modeling program PHREEQC indicated that F solubility may be somewhat limited by the precipitation of the mineral fluorapatite [Ca 5 (PO 4 ) 3 F]. Speciation modeling of As in anoxic-Fe groundwater (iron-reducing conditions) showed that samples were supersaturated with orpiment (As 2 S 3 ), indicating that mineral precipitation may be responsible for low As concentrations observed in reducing groundwater. In contrast, U concentrations showed significant negative correlations to groundwater age and to pH. Higher U concentrations generally occurred in samples for which geochemical modeling indicated that the uncharged ternary complex Ca 2 UO 2 (CO 3 ) 3 was the dominant aqueous U species. This uncharged complex is not attracted to the charged surfaces of minerals and thus increases U solubility. Formation of Ca 2 UO 2 (CO 3 ) 3 was greater in younger groundwaters because calcium and uranium concentrations generally were lower in older groundwaters, likely due to cation-exchange processes and precipitation of the mineral calcite as groundwater pH increased. Co-precipitation of U with the calcite (CaCO 3 ) may remove U from the aqueous phase. Saturation indices indicated that the anoxic-Fe groundwaters from the Colorado River study area were supersaturated with the mineral uraninite (UO 2 ), suggesting that UO 2 precipitation may be responsible for the low concentrations of U observed in these samples. Concentrations of strontium, which exists primarily in a cationic form (Sr 2+ ), were not significantly correlated with either groundwater age or pH. Strontium concentrations showed a strong positive correlation with total dissolved solids (TDS). Dissolved constituents, such as Sr, that interact with mineral surfaces through outer-sphere complexation become increasingly soluble with increasing TDS concentrations of groundwater. Boron concentrations also showed a significant positive correlation with TDS, indicating the B may interact to a large degree with mineral surfaces through outer-sphere complexation.

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