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At least 541 records · Page 30Linked to original sources
USGS2020

Hydro-morphological characterization of coral reefs for wave runup prediction

Many coral reef-lined coasts are low-lying with elevations <4 m above mean sea level. Climate-change-driven sea-level rise, coral reef degradation, and changes in storm wave climate will lead to greater occurrence and impacts of wave-driven flooding. This poses a significant threat to their coastal communities. While greatly at risk, the complex hydrodynamics and bathymetry of reef-lined coasts make flood risk assessment and prediction costly and difficult. Here we use a large (>30,000) dataset of measured coral reef topobathymetric cross-shore profiles, statistics, machine learning, and numerical modeling to develop a set of representative cluster profiles (RCPs) that can be used to accurately represent the shoreline hydrodynamics of a large variety of coral reef-lined coasts around the globe. In two stages, the large dataset is reduced by clustering cross-shore profiles based on morphology and hydrodynamic response to typical wind and swell wave conditions. By representing a large variety of coral reef morphologies with a reduced number of RCPs, a computationally feasible number of numerical model simulations can be done to obtain wave runup estimates, including setup at the shoreline and swash separated into infragravity and sea-swell components, of the entire dataset. The predictive capability of the RCPs is tested against 5,000 profiles from the dataset. The wave runup is predicted with a mean error of 9.7–13.1%, depending on the number of cluster profiles used, ranging from 312 to 50. The RCPs identified here can be combined with probabilistic tools that can provide an enhanced prediction given a multivariate wave and water level climate and reef ecology state. Such a tool can be used for climate change impact assessments and studying the effectiveness of reef restoration projects, as well as for the provision of coastal flood predictions in a simplified (global) early warning system.

Frontiers in Marine Science↗
USGS2025

Interrogating process deficiencies in large-scale hydrologic models with interpretable machine learning

Large-scale hydrologic models are increasingly being developed for operational use in the forecasting and planning of water resources. However, the predictive strength of such models depends on how well they resolve various functions of catchment hydrology, which are influenced by gradients in climate, topography, soils, and land use. Most assessments of hydrologic model uncertainty have been limited to traditional statistical methods. Here, we present a proof-of-concept approach that uses interpretable machine learning techniques to provide post hoc assessment of model sensitivity and process deficiency in hydrologic models. We train a random forest model to predict the Kling–Gupta efficiency (KGE) of National Water Model (NWM) and National Hydrologic Model (NHM) streamflow predictions for 4383 stream gauges in the conterminous United States. Thereafter, we explain the local and global controls that 48 catchment attributes exert on KGE prediction using interpretable Shapley values. Overall, we find that soil water content is the most impactful feature controlling successful model performance, suggesting that soil water storage is difficult for hydrologic models to resolve, particularly for arid locations. We identify nonlinear thresholds beyond which predictive performance decreases for NWM and NHM. For example, soil water content less than 210 mm, precipitation less than 900 mm yr −1 , road density greater than 5 km km −2 , and lake area percent greater than 10 % contributed to lower KGE values. These results suggest that improvements in how these influential processes are represented could result in the largest increases in NWM and NHM predictive performance. This study demonstrates the utility of interrogating process-based models using data-driven techniques, which has broad applicability and potential for improving the next generation of large-scale hydrologic models.

conterminous United States↗
USGS2021

Introduced mangroves along the coast of Moloka‘i, Hawai‘i may represent novel habitats for megafaunal communities

Mangrove forests are prevalent along tropical/subtropical coastlines and provide valuable ecosystem services including coastline stabilization, storm impact reduction, and enhanced coastal productivity. However, mangroves were absent from the Hawaiian Islands and their introduction to Moloka‘i in 1902 has provided an opportunity to examine their unique influence on coastal landscapes. Previous studies indicate an inability of native detritivores to utilize tannin-rich substrates, yielding poor cycling of mangrove-derived detritus in Hawaiian tidal zones. We hypothesize that in addition to altering detrital inputs, introduced mangroves facilitate the persistence of introduced species in the Hawaiian coastal zone by providing novel habitat for juvenile megafauna. To determine whether mangrove-dominated tidal zones harbor megafaunal assemblages distinct from open sandflats, we sampled in two mangrove (M1 and M2) and two adjacent sandflat (S1 and S2) sites along the southern coast of Moloka‘i, where the most mature mangrove forests occur in Hawai‘i. There were no statistical differences in total abundances between M1 and M2 or S1 and S2; therefore, results from individual deployments were pooled across the sites in order to conduct between-habitat (mangrove vs. sandflat) comparisons. Our mangrove study site had significantly higher abundances of megafauna, including several shrimp and crab species, compared to the sandflat site. The community composition within the mangrove site differed from the sandflat site, including higher abundances of non-native mangrove crabs ( Scylla serrata ), as well as native fish Bathygobius cocosensis and crustaceans ( Thalamita crenata , Palaemon pacificus , P. debilis ) than in the sandflat site, indicating that the mangrove site may provide niches for both invasive and native species. In addition, mean body length for several similar species was smaller in the mangrove site than in the sandflat site, suggesting that these mangroves may be providing a habitat for juvenile species. While our study was spatially limited to two mangrove and two adjacent sandflat sites, our results suggest that introduced mangroves in Moloka‘i may support small-bodied, native, and non-native megafauna, influencing coastal Hawaiian trophic dynamics. Our case study provides a baseline for megafaunal fish and invertebrate communities present prior to non-native mangrove removal as well as for monitoring potential community changes following expansion of mangrove habitats due to climate change.

Hawaii↗
USGS2009

New light on a dark subject: On the use of fluorescence data to deduce redox states of natural organic matter (NOM)

This paper reports the use of excitation-emission matrix fluorescence spectroscopy (EEMS), parallel factor statistical analysis (PARAFAC), and oxidation-reduction experiments to examine the effect of redox conditions on PARAFAC model results for aqueous samples rich in natural organic matter. Fifty-four aqueous samples from 11 different geographic locations and two plant extracts were analyzed untreated and after chemical treatments or irradiation were used in attempts to change the redox status of the natural organic matter. The EEMS spectra were generated and modeled using a PARAFAC package developed by Cory and McKnight (2005). The PARAFAC model output was examined for consistency with previously reported relations and with changes expected to occur upon experimental oxidation and reduction of aqueous samples. Results indicate the implied fraction of total sample fluorescence attributed to quinone-like moieties was consistent (0.64 to 0.78) and greater than that observed by Cory and McKnight (2005). The fraction of the quinone-like moieties that was reduced (the reducing index, RI) showed relatively little variation (0.46 to 0.71) despite attempts to alter the redox status of the natural organic matter. The RI changed little after reducing samples using zinc metal, oxidizing at high pH with air, or irradiating with a Xenon lamp. Our results, however, are consistent with the correlations between the fluorescence indices (FI) of samples and the ratio of PARAFAC fitting parameters suggested by Cory and McKnight (2005), though we used samples with a much narrower range of FI values.

Aquatic Sciences↗
USGS2013

A GIS and statistical approach to identify variables that control water quality in hydrothermally altered and mineralized watersheds, Silverton, Colorado, USA

Hydrothermally altered bedrock in the Silverton mining area, southwest Colorado, USA, contains sulfide minerals that weather to produce acidic and metal-rich leachate that is toxic to aquatic life. This study utilized a geographic information system (GIS) and statistical approach to identify watershed-scale geologic variables in the Silverton area that influence water quality. GIS analysis of mineral maps produced using remote sensing datasets including Landsat Thematic Mapper, advanced spaceborne thermal emission and reflection radiometer, and a hybrid airborne visible infrared imaging spectrometer and field-based product enabled areas of alteration to be quantified. Correlations between water quality signatures determined at watershed outlets, and alteration types intersecting both total watershed areas and GIS-buffered areas along streams were tested using linear regression analysis. Despite remote sensing datasets having varying watershed area coverage due to vegetation cover and differing mineral mapping capabilities, each dataset was useful for delineating acid-generating bedrock. Areas of quartz–sericite–pyrite mapped by AVIRIS have the highest correlations with acidic surface water and elevated iron and aluminum concentrations. Alkalinity was only correlated with area of acid neutralizing, propylitically altered bedrock containing calcite and chlorite mapped by AVIRIS. Total watershed area of acid-generating bedrock is more significantly correlated with acidic and metal-rich surface water when compared with acid-generating bedrock intersected by GIS-buffered areas along streams. This methodology could be useful in assessing the possible effects that alteration type area has in either generating or neutralizing acidity in unmined watersheds and in areas where new mining is planned.

Colorado↗
USGS2019

Water-quality trends in US rivers: Exploring effects from streamflow trends and changes in watershed management

We present a conceptual model that explores the relationship of streamflow trends to 15 water-quality parameters at 370 sites across the contiguous United States (US). Our analytical framework uses discrete water-quality data, daily streamflow records, and a statistical model to estimate water-quality trends between 1982 and 2012 and parse these trends into the amount of change attributed to trends in streamflow versus changes in watershed management , such as changes in point or non-point sources related to pollution control efforts. We conceptualize a water-quality trend as an additive function of these two trend components. We found that for most of these records the water-quality trends were more strongly affected by changes in watershed management as opposed to trends in streamflow. However, the importance of these trend components on water quality varied by estimate type (i.e. concentration versus load trends), parameter, and site. Trends in load were more influenced by changes in the streamflow regime than trends in concentration. Trends in major ions, salinity, and sediment were more sensitive to changes in streamflow than nutrients. When results were aggregated by site, 25% of the sites had at least 1 parameter where streamflow trends attributed >7.5% to the water-quality trend for concentrations. For loads, this was the case for 66% of the sites. The findings of this work have important implications for the analysis of water-quality trends. Understanding the relative role of streamflow and management changes can help to isolate the effects of pollution control efforts on water quality and provide clearer understanding of progress, or lack thereof, towards water-quality goals.

Science of the Total Environment↗
USGS2017

Seven recommendations to make your invasive alien species data more useful

Science-based strategies to tackle biological invasions depend on recent, accurate, well-documented, standardized and openly accessible information on alien species. Currently and historically, biodiversity data are scattered in numerous disconnected data silos that lack interoperability. The situation is no different for alien species data, and this obstructs efficient retrieval, combination, and use of these kinds of information for research and policy-making. Standardization and interoperability are particularly important as many alien species related research and policy activities require pooling data. We describe seven ways that data on alien species can be made more accessible and useful, based on the results of a European Cooperation in Science and Technology (COST) workshop: (1) Create data management plans; (2) Increase interoperability of information sources; (3) Document data through metadata; (4) Format data using existing standards; (5) Adopt controlled vocabularies; (6) Increase data availability; and (7) Ensure long-term data preservation. We identify four properties specific and integral to alien species data (species status, introduction pathway, degree of establishment, and impact mechanism) that are either missing from existing data standards or lack a recommended controlled vocabulary. Improved access to accurate, real-time and historical data will repay the long-term investment in data management infrastructure, by providing more accurate, timely and realistic assessments and analyses. If we improve core biodiversity data standards by developing their relevance to alien species, it will allow the automation of common activities regarding data processing in support of environmental policy. Furthermore, we call for considerable effort to maintain, update, standardize, archive, and aggregate datasets, to ensure proper valorization of alien species data and information before they become obsolete or lost.

Frontiers in Applied Mathematics and Statistics↗
USGS2000

Quantification and regionalization of groundwater recharge in South-Central Kansas: Integrating field characterization, statistical analysis, and GIS

A practical methodology for recharge characterization was developed based on several years of field-oriented research at 10 sites in the Great Bend Prairie of south-central Kansas. This methodology combines the soil-water budget on a storm-by-storm year-round basis with the resulting watertable rises. The estimated 1985-1992 average annual recharge was less than 50mm/year with a range from 15 mm/year (during the 1998 drought) to 178 mm/year (during the 1993 flood year). Most of this recharge occurs during the spring months. To regionalize these site-specific estimates, an additional methodology based on multiple (forward) regression analysis combined with classification and GIS overlay analyses was developed and implemented. The multiple regression analysis showed that the most influential variables were, in order of decreasing importance, total annual precipitation, average maximum springtime soil-profile water storage, average shallowest springtime depth to watertable, and average springtime precipitation rate. Therefore, four GIS (ARC/INFO) data "layers" or coverages were constructed for the study region based on these four variables, and each such coverage was classified into the same number of data classes to avoid biasing the results. The normalized regression coefficients were employed to weigh the class rankings of each recharge-affecting variable. This approach resulted in recharge zonations that agreed well with the site recharge estimates. During the "Great Flood of 1993," when rainfall totals exceeded normal levels by -200% in the northern portion of the study region, the developed regionalization methodology was tested against such extreme conditions, and proved to be both practical, based on readily available or easily measurable data, and robust. It was concluded that the combination of multiple regression and GIS overlay analyses is a powerful and practical approach to regionalizing small samples of recharge estimates.

The Compass: Earth Science Journal of Sigma Gamma ↗
USGS2018

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

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

Maryland↗
USGS2016

Surface-air mercury fluxes across Western North America: A synthesis of spatial trends and controlling variables

Mercury (Hg) emission and deposition can occur to and from soils, and are an important component of the global atmospheric Hg budget. This paper focuses on synthesizing existing surface-air Hg flux data collected throughout the Western North American region and is part of a series of geographically focused Hg synthesis projects. A database of existing Hg flux data collected using the dynamic flux chamber (DFC) approach from almost a thousand locations was created for the Western North America region. Statistical analysis was performed on the data to identify the important variables controlling Hg fluxes and to allow spatiotemporal scaling. The results indicated that most of the variability in soil-air Hg fluxes could be explained by variations in soil-Hg concentrations, solar radiation, and soil moisture. This analysis also identified that variations in DFC methodological approaches were detectable among the field studies, with the chamber material and sampling flushing flow rate influencing the magnitude of calculated emissions. The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.

Science of the Total Environment↗
USGS2019

Current state of knowledge on biological effects from contaminants on arctic wildlife and fish

Since the last Arctic Monitoring and Assessment Programme (AMAP) effort to review biological effects of the exposure to organohalogen compounds (OHCs) in Arctic biota, there has been a considerable number of new Arctic effect studies. Here, we provide an update on the state of the knowledge of OHC, and also include mercury, exposure and/or associated effects in key Arctic marine and terrestrial mammal and bird species as well as in fish by reviewing the literature published since the last AMAP assessment in 2010. We aimed at updating the knowledge of how single but also combined health effects are or can be associated to the exposure to single compounds or mixtures of OHCs. We also focussed on assessing both potential individual as well as population health impacts using population-specific exposure data post 2000. We have identified quantifiable effects on vitamin metabolism, immune functioning, thyroid and steroid hormone balances, oxidative stress, tissue pathology, and reproduction. As with the previous assessment, a wealth of documentation is available for biological effects in marine mammals and seabirds, and sentinel species such as the sledge dog and Arctic fox, but information for terrestrial vertebrates and fish remain scarce. While hormones and vitamins are thoroughly studied, oxidative stress, immunotoxic and reproductive effects need further investigation. Depending on the species and population, some OHCs and mercury tissue contaminant burdens post 2000 were observed to be high enough to exceed putative risk threshold levels that have been previously estimated for non-target species or populations outside the Arctic. In this assessment, we made use of risk quotient calculations to summarize the cumulative effects of different OHC classes and mercury for which critical body burdens can be estimated for wildlife across the Arctic. As our ultimate goal is to better predict or estimate the effects of OHCs and mercury in Arctic wildlife at the individual, population and ecosystem level, there remain numerous knowledge gaps on the biological effects of exposure in Arctic biota. These knowledge gaps include the establishment of concentration thresholds for individual compounds as well as for realistic cocktail mixtures that in fact indicate biologically relevant, and not statistically determined, health effects for specific species and subpopulations. Finally, we provide future perspectives on understanding Arctic wildlife health using new in vivo, in vitro, and in silico techniques, and provide case studies on multiple stressors to show that future assessments would benefit from significant efforts to integrate human health, wildlife ecology and retrospective and forecasting aspects into assessing the biological effects of OHC and mercury exposure in Arctic wildlife and fish.

Science of the Total Environment↗
USGS2025

A geospatial analysis of water-quality threats from orphan wells in principal and secondary aquifers of the United States

Throughout the history of oil and gas production in the United States, millions of wells have been drilled for exploration and energy production. Hundreds of thousands of unplugged wells are no longer actively producing and are currently under orphan status, with no responsible party obligated for plugging. Orphan wells can pose threats to water resources by providing pathways for contaminants such as hydrocarbons and brines to migrate into water-supply aquifers. In this study, we investigate the potential threats to groundwater resources posed by orphan wells at the national scale. Water-quality data is extremely sparse in relation to orphan wells nationally and may not be suitable for identifying contamination from oil and gas development. We used geospatial and statistical methods to evaluate which principal and secondary aquifer systems may be most susceptible to contamination from orphan wells. Analysis involved three sets of susceptibility factors including: 1) factors related to the number and density of orphan wells; 2) factors that can threaten well integrity and contribute to transport of contaminants; and 3) factors related to groundwater withdrawal rates and the affected populations/communities in the event of water quality disturbances. From a dataset of 117,672 documented orphan wells, 64,203 fall within a principal aquifer system, while the remainder fall within a secondary aquifer system. By assessing the combination of well integrity and hydrogeologic factors within these aquifer systems, five groupings of principal aquifers were identified, where groups ranged from aquifer systems with high numbers of orphan wells, multiple well integrity threats and high withdrawals, to aquifers with a relatively low number of orphan wells, limited well integrity threats and minimal water use. Three regions of the country emerge containing aquifers with higher susceptibility to contamination from orphan oil and gas wells. These regions include 1) The Appalachian Basin (including the Pennsylvanian Aquifer System), 2) The Gulf Coast Aquifers (including the Coastal Lowlands Aquifer system) and 3) The California Aquifers (including the California Coastal Basin Aquifer system). This work is the first multivariate geospatial investigation of orphan wells and groundwater resources on a national scale, and sheds light on which aquifers are most susceptible to groundwater contamination from orphan wells.

Science of the Total Environment↗
USGS2024

Northern Mexican gartersnake demographics and movement ecology

The northern Mexican gartersnake ( Thamnophis eques ; hereafter NMGS) is a federally threatened species occurring in riparian areas in central and southeast Arizona and west-central New Mexico. While previous studies have examined the ecology of this species in central Arizona, less is known about NMGS ecology in grassland landscapes of southeast Arizona. This project continues a long-term mark-recapture study of NMGS in the upper Santa Cruz River in the San Rafael Valley of southeast Arizona. We analyzed mark-recapture data collected by Arizona Game and Fish Department from 2008–2019 and included data we collected during 2022 and 2023. We also studied NMGS movement ecology using a combination of externally attached GPS transmitters and surgically implanted VHF transmitters. We had 517 NMGS captures over 26 survey sessions across the entire study, 186 of which were captures of previously marked snakes. Most of our captures were females and evidence of a statistically significant female-biased sex ratio was present on three survey sessions. Trapping success was generally highest June-September and catch-per-unit-effort (CPUE) was strongly correlated with the number of individuals captured. We used mark-recapture data from 288 individuals to estimate annual apparent survival and session-specific recapture probabilities. Annual apparent survival was higher for females (0.72, 95% highest posterior density intervals [HPDI] = 0.630.81) than for males (0.58, 95% HPDI = 0.44–0.72). Session-specific recapture probabilities were similar for males and females and were highly correlated with CPUE. During 2023, we monitored the movements of 13 adult females using GPS transmitters, two adult males using VHF transmitters, and one adult female using a GPS transmitter followed by a VHF transmitter. GPS transmitters were deployed from 7-18 days at a time as limited by battery life. After filtering out low-quality GPS locations, we obtained a total of 1,688 hourly GPS locations. Mean and maximum distances moved per hour ranged from 5.54–10.92 m and 15.24–135.71 m, respectively, across GPS transmitter attachment periods. Space use estimates from 100% minimum convex polygons ranged from 0.04–1.16 ha across GPS transmitter attachment periods. All documented NMGS movements during 2023 were relatively close (< 100 m) to the Santa Cruz River. These results continue to build upon our knowledge of NMGS ecology and suggest the continued presence of a relatively robust population within the upper Santa Cruz River.

Arizona↗
USGS2014

The digital global geologic map of Mars: Chronostratigraphic ages, topographic and crater morphologic characteristics, and updated resurfacing history

A new global geologic map of Mars has been completed in a digital, geographic information system (GIS) format using geospatially controlled altimetry and image data sets. The map reconstructs the geologic history of Mars, which includes many new findings collated in the quarter century since the previous, Viking-based global maps were published, as well as other discoveries that were made during the course of the mapping using new data sets. The technical approach enabled consistent and regulated mapping that is appropriate not only for the map's 1:20,000,000 scale but also for its widespread use by diverse audiences. Each geologic unit outcrop includes basic attributes regarding identity, location, area, crater densities, and chronostratigraphic age. In turn, units are grouped by geographic and lithologic types, which provide synoptic global views of material ages and resurfacing character for the Noachian, Hesperian, and Amazonian periods. As a consequence of more precise and better quality topographic and morphologic data and more complete crater-density dating, our statistical comparisons identify significant refinements for how Martian geologic terrains are characterized. Unit groups show trends in mean elevation and slope that relate to geographic occurrence and geologic origin. In comparison with the previous global geologic map series based on Viking data, the new mapping consists of half the number of units due to simpler, more conservative and globally based approaches to discriminating units. In particular, Noachian highland surfaces overall have high percentages of their areas now dated as an epoch older than in the Viking mapping. Minimally eroded (i.e., pristine) impact craters ≥3 km in diameter occur in greater proportion on Hesperian surfaces. This observation contrasts with a deficit of similarly sized craters on heavily cratered and otherwise degraded Noachian terrain as well as on young Amazonian surfaces. We interpret these as reflecting the relatively stronger, lava-rich, yet less-impacted materials making up much of the younger units. Reconstructions of resurfacing of Mars by its eight geologic epochs using the Hartmann and Neukum chronology models indicate high rates of highland resurfacing during the Noachian (peaking at 0.3 km 2 /yr during the Middle Noachian), modest rates of volcanism and transition zone and lowland resurfacing during the Hesperian (∼0.1 km 2 /yr), and low rates of mainly volcanic and polar resurfacing (∼0.01 km 2 /yr) for most of the Amazonian. Apparent resurfacing increased in the Late Amazonian (∼0.03 km 2 /yr), perhaps due to better preservation of this latest record.

Planetary and Space Science↗
USGS2022

Validation of a vulnerability index of exposure to chemicals of emerging concern in surface water and sediment of Great Lakes tributaries of the United States

Widespread occurrence of emerging contaminants in Great Lakes tributaries led to the development and publication of a vulnerability index (VI) to assess the potential exposure of aquatic communities to chemicals of emerging concern (CEC) in the Great Lakes basin. The robust nature of the VI was tested to evaluate the underlying statistical model and expand the spatial domain of the index. Data collected at 131 new sampling sites (Test 1) and published data from independent studies (Test 2) were used to test the model predictions. Test 1 water and sediment samples were analyzed for the same classes of CEC chemicals and compared to the predictions for the original VI. Concentrations and numbers of unique CECs detected in water and sediment samples were similar between the original data and the two test datasets, although CECs tended to have higher detection frequencies in the original dataset compared to the Test 1 and Test 2 datasets. For example, 69 CECs were detected in ≥30% of water samples in the original dataset compared with 17 CECs in the Test 1 data and 59 in the Test 2 data. Predicted vulnerability for test sites agreed with actual vulnerability 64% of the time for water and 71% of the time for sediment. Agreement percentage results were greater when individual sites were grouped by river, with 82% agreement between predictions and actual vulnerability for water and 78% agreement for sediment. For the entire dataset, the VI ranks correlated with an independent estimate of potential biological impact. Agreement percentage was the greatest for low or high vulnerability index values but highly variable for sites that are classified as having medium vulnerability. Despite the underlying variability, there is a significant correlation (R 2 = 0.26; p < 0.01) between the VI ranking of tributaries and the independent ranking of potential negative biological impact.

Illinois, Indiana, Michigan, Minnesota, New York, ↗
USGS2024

Trends in plant cover derived from vegetation plot data using ordinal zero-augmented beta regression

Questions Plant cover values in vegetation plot data are bounded between 0 and 1, and cover is typically recorded in discrete classes with non-equal intervals. Consequently, cover data are skewed and heteroskedastic, which hampers the application of conventional regression methods. Recently developed ordinal beta regression models consider these statistical difficulties. Our primary question is whether we can detect species trends in vegetation plot time series data with this modelling approach. A second question is whether trends in cover have additional value compared to trends in occurrence, which are easier to assess for practitioners. Location The Netherlands, Western Europe. Methods We used vegetation plot data collected from 10,000 fixed plots which were surveyed once every four years during 1999–2022. We used the ordinal zero-augmented beta regression (OZAB) model, a hierarchical model consisting of a logistic regression for presence and an ordinal beta regression for cover. We adapted the OZAB model for longitudinal data and produced estimates of cover and occurrence for each four-year period. Thereafter we assessed trends in cover and in occurrence across all periods. Results We found evidence of a trend in cover in 318 out of the 721 species (44%) with sufficient data. Most species showed similar directional trends in occurrence and percent cover. No trend in occurrence was detected for 64 species that had evidence of a trend in cover. Declining species had stronger relative changes in cover than in occurrence. Conclusions Our model enables researchers to detect trends in cover using longitudinal vegetation plot data. Cover trends often corroborated trends in occurrence, but we also regularly found trends in cover even in the absence of evidence for trends in occurrence. Our approach thus contributes to a more complete picture of (changes in) vegetation composition based on large monitoring data sets.

Journal of Vegetation Science↗
USGS2021

Robust projections of future fire probability for the conterminous United States

Globally increasing wildfires have been attributed to anthropogenic climate change. However, providing decision makers with a clear understanding of how future planetary warming could affect fire regimes is complicated by confounding land use factors that influence wildfire and by uncertainty associated with model simulations of climate change. We use an ensemble of statistically downscaled Global Climate Models in combination with the Physical Chemistry Fire Frequency Model (PC2FM) to project changing potential fire probabilities in the conterminous United States for two scenarios representing lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emission futures. PC2FM is a physically-based and scale-independent model that predicts mean fire return intervals from both fire reactant and reaction variables, which are largely dependent on a locale's climate. Our results overwhelmingly depict increasing potential fire probabilities across the conterminous US for both climate scenarios. The primary mechanism for the projected increases is rising temperatures, reflecting changes in the chemical reaction environment commensurate with enhanced photosynthetic rates and available thermal molecular energy. Existing high risk areas, such as the Cascade Range and the Coastal California Mountains, are projected to experience greater annual fire occurrence probabilities, with relative increases of 122% and 67%, respectively, under RCP 8.5 compared to increases of 63% and 38% under RCP 4.5. Regions not currently associated with frequently occurring wildfires, such as New England and the Great Lakes, are projected to experience a doubling of occurrence probabilities by 2100 under RCP 8.5. This high resolution, continental-scale modeling study of climate change impacts on potential fire probability accounts for shifting background environmental conditions across regions that will interact with topographic drivers to significantly alter future fire probabilities. The ensemble modeling approach presents a useful planning tool for mitigation and adaptation strategies in regions of increasing wildfire risk.

Science of the Total Environment↗
USGS2023

Forage fish species prefer habitat within designated offshore wind energy areas on the US Northeast Shelf ecosystem

As the world develops sources of renewable energy, there is an intensifying interest in offshore wind energy production. The Northeast U.S. Continental Shelf (NES) ecosystem has favorable wind dynamics, with active development of wind energy. In this study, we present species distribution models that consider both occupancy and biomass responses for a broad spectrum of fish and macroinvertebrate taxa ( n = 177). Building upon prior analyses, habitat was differentiated into overall and core habitats based on statistical distributions of habitat scores. Overall habitat was used to show each species' regional distribution based on fishery-independent survey captures between 1976 and 2019, whereas core habitat represented where the focus of the species' abundance was located as a subset of overall habitat. Wind energy developments may modify the water column in ways that impact lower-trophic-level productivity; therefore, added attention was given to the response of forage species. Over 20% of species showed preferential use of putative and potential wind development areas, including a disproportionate number of forage taxa. Principal usage varied by season, with forage species like Atlantic Menhaden Brevoortia tyrannus and Atlantic Mackerel Scomber scombrus preferentially using the lease areas in spring and Round Herring Etrumeus teres and longfin inshore squid Doryteuthis pealeii using lease areas in autumn. For species with relatively low usage of the lease areas, there was a tendency for the usage related to overall habitat to be lower than usage for core habitat; in contrast, for species with high usage of the lease areas, that usage was higher for overall habitat than for core habitat. The area of habitat tended to have positive trends across species, with these positive trends being disproportionately higher among forage taxa. These results frame the importance of wind lease areas for species in the NES, particularly forage taxa that fulfill many important ecological functions.

Marine and Coastal Fisheries: Dynamics, Management↗