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USGS2014

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of vertical structure will be more accurate in plots having low herbaceous cover and high amounts of dense shrubs. Through the use of statistically derived correction factors or choosing field methods that better correlate with the imagery, vegetation heights from HR DSMs could be a valuable technique for broad-scale rangeland monitoring needs.

California;Nevada↗

USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗

USGS2012

Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro- N -ethyl- N' -(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro- N -(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 μg L -1 . These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring.

Journal of Environmental Quality↗

USGS2019

Diatom assemblage changes in agricultural alluvial plain streams and application for nutrient management

In large, alluvial floodplains dominated by agriculture, small streams have the potential to experience nutrient enrichment affecting algal assemblage structure and metabolism. Nutrient enrichment is largely driven by application of nutrients and altered hydrologic regimes. To inform stressor–response-based nutrient reduction goals for agricultural alluvial plain streams, diatom assemblages were sampled from 25 streams located within the Mississippi Alluvial Plain (MAP) with various land management practices and associated P and N inputs. From August through September 2015, epidendric diatom assemblage samples were collected from instream woody debris. Field nutrient gradients were skewed toward higher concentrations, and ranges of previously reported diatom assemblage response thresholds indicative of oligotrophic conditions were not well represented. Ordination analysis identified a gradient in species composition associated with increasing P and decreasing dissolved oxygen. A significant shift in diatom assemblage structure occurred when total P concentrations in the MAP streams exceeded 0.12 mg L− 1 . Phosphorus-enriched systems were represented by a distinct set of indicator species, lower abundances of ubiquitous species, greater abundances of highly tolerant species, and greater abundances of high-P indicator species. No relationships were observed among diatom assemblage measures or traits with increasing N. Current results do not address potential criteria for identifying high-quality, oligotrophic streams. However, measures of diatom assemblage structure have potential for helping set benchmarks to reduce nutrient impacts and monitor effects of agricultural best management practices on MAP streams.

Yazoo River basin↗

USGS2009

The influence of use-related, environmental, and managerial factors on soil loss from recreational trails

Recreational uses of unsurfaced trails inevitably result in their degradation, with the type and extent of resource impact influenced by factors such as soil texture, topography, climate, trail design and maintenance, and type and amount of use. Of particular concern, the loss of soil through erosion is generally considered a significant and irreversible form of trail impact. This research investigated the influence of several use-related, environmental, and managerial factors on soil loss on recreational trails and roads at Big South Fork National River and Recreation Area, a unit of the U.S. National Park Service. Regression modeling revealed that trail position, trail slope alignment angle, grade, water drainage, and type of use are significant determinants of soil loss. The introduction of individual and groups of variables into a series of regression models provides improved understanding and insights regarding the relative influence of these variables, informing the selection of more effective trail management actions. Study results suggest that trail erosion can be minimized by avoiding “fall-line” alignments, steep grades, and valley-bottom alignments near streams, installing and maintaining adequate densities of tread drainage features, applying gravel to harden treads, and reducing horse and all-terrain vehicle use or restricting them to more resistant routes. This research also sought to develop a more efficient Variable Cross-Sectional Area method for assessing soil loss on trails. This method permitted incorporation of CSA measures in a representative sampling scheme applied to a large (24%) sample of the park's 526 km trail system. The variety of soil loss measures derived from the Variable CSA method, including extrapolated trail-wide soil loss estimates, permit an objective quantification of soil erosion on recreational trails and roads. Such data support relational analyses to increase understanding of trail degradation, and long-term monitoring of the natural and recreational integrity of the trail system infrastructure.

Journal of Environmental Management↗

USGS2009

Osprey: Worldwide sentinel species for assessing and monitoring environmental contamination in rivers, lakes, reservoirs, and estuaries

In the United States, many fish and wildlife species have been used nationwide to monitor environmental contaminant exposure and effects, including carcasses of the bald eagle ( Haliaeetus leucocephalus ), the only top avian predator regularly used in the past. Unfortunately, bald eagles are sensitive to investigator intrusion at the nest. Thus, the osprey ( Pandion haliaetus ) is evaluated as a potential sentinel species for aquatic ecosystems. Several characteristics support the choice of the osprey as a sentinel species, including: (1) fish-eating diet atop the aquatic food web, (2) long-lived with strong nest fidelity, (3) adapts to human landscapes (potentially the most contaminated), (4) tolerates short-term nest disturbance, (5) nests spatially distributed at regular intervals, (6) highly visible nests easily located for study, (7) ability to accumulate most, if not all, lipophilic contaminants, (8) known sensitivity to many contaminants, and (9) nearly a worldwide distribution. These osprey traits have been instrumental in successfully using the species to understand population distribution, abundance, and changes over time; the effects of various contaminants on reproductive success; how contaminants in prey (fish on biomass basis) contribute to egg concentrations (i.e., biomagnification factors); and spatial residue patterns. Data summarized include nesting population surveys, detailed nesting studies, and chemical analyses of osprey egg, organ, blood, and feather samples for contaminants that bioaccumulate and/or biomagnify in aquatic food webs; and biochemical evaluations of blood and various organs. Studies in the United States, Canada, Mexico, Europe, and elsewhere have shown the osprey to be a useful sentinel species for monitoring selected environmental contaminants, including some emerging contaminants in lakes, reservoirs, rivers, and estuaries.

Journal of Toxicology and Environmental Health, Pa↗

USGS2012

Distribution of potentially bioavailable natural organic carbon in aquifer sediments at a chloroethene-contaminated site

The distribution of natural organic carbon was investigated at a chloroethene-contaminated site where complete reductive dechlorination of tetrachloroethene (PCE) to vinyl chloride and ethene was observed. In this study, operationally defined potentially bioavailable organic carbon (PBOC) was measured in surficial aquifer sediment samples collected at varying depths and locations in the vicinity of a dense nonaqueous phase liquid (DNAPL) source and aqueous phase plume. The relationship between chloroethene concentrations and PBOC levels was examined by comparing differences in extractable organic carbon in aquifer sediments with minimal chloroethene exposure relative to samples collected in the source zone. Using performance-monitoring data, direct correlations with PBOC were also developed with chloroethene concentrations in groundwater. Results show a logarithm-normal distribution for PBOC in aquifer sediments with a mean concentration of 187 mg/kg. PBOC levels in sediments obtained from the underlying confining unit were generally greater when compared to sediments collected in the sandy surficial aquifer. Results demonstrated a statistically significant inverse correlation (p=0.007) between PBOC levels in aquifer sediments and chloroethene concentrations for selected monitoring wells in which chloroethene exposure was the highest. Results from laboratory exposure assays also demonstrated that sediment samples exhibited a reduction in PBOC levels of 35% and 73%, respectively, after a 72-h exposure period to PCE (20,000 μg/L). These results support the notion that PBOC depletion in sediments may be expected in chloroethene-contaminated aquifers, which has potential implications for the long-term sustainability of monitored natural attenuation.

South Carolina↗

USGS1999

Rice pesticide concentrations in the Colusa Basin Drain and the Sacramento River, California, 1990-1993

The pesticides molinate, thiobencarb, and carbofuran are applied to rice ( Oryza sativa L.) fields in the Sacramento Valley, California, each year during April through June. These pesticides are of concern because of their adverse effects on water quality and their potential adverse effects on aquatic life. Therefore, the California Regional Water Quality Control Board (CRWQCB) mandated the holding of irrigation-return water in rice fields to increase pesticide degradation and dissipation before the water is released to the Sacramento River. The CRWQCB also established performance goals to maintain drinking water quality for the city of Sacramento and to protect the habitat for aquatic life. The objectives of this study were to determine the effects of increased irrigation-return water holding times on rice pesticide concentrations and loads in the Colusa Basin Drain and the Sacramento River. Dissolved pesticide concentrations were measured in water samples collected in May through July during 1990–1993 at the Colusa Basin Drain at Road 99E near Knights Landing (Colosa Basin Drain) and at the Sacramento River at Sacramento. Pesticide concentrations and loads at both sites showed a decrease from 1990–1992 and an increase in 1993. This trend cannot be explained by the yearly holding time regulations but can be explained by the amount of yearly emergency releases. The yearly changes in pesticide concentration detected demonstrate that continued monitoring and management of pesticides is necessary to maintain water quality.

California↗

USGS2009

Sublethal effects of chronic lead ingestion in mallard ducks

Mallard drakes (Anas platyrhynchos) fed 1, 5, or 25 ppm lead nitrate were bled and sacrificed at 3‐wk intervals. No mortality occurred, and the pathologic lesions usually associated with lead poisoning were not found. Changes in hematocrit and hemoglobin concentration did not occur. After 3 wk ducks fed 25 ppm lead exhibited a 40% inhibition of blood δ‐aminolevulinic acid dehydratase activity that persisted through 12 wk exposure. After 12 wk treatment similar enzyme inhibition was present in the ducks fed 5 ppm lead. At 3 wk there was a small accumulation of lead (less than 1 ppm) in the liver and kidneys of ducks fed 25 ppm lead; no further increases occurred throughout the exposure. No significant accumulation of lead occurred in the tibiae or wing bones. Groups of ducks fed 5 and 25 ppm diets for 12 wk were placed on clean feed and examined through a 12 wk posttreatment period. After 3 wk on clean diet δ‐aminolevulinic acid dehydratase activity and lead concentrations in the blood had returned to pretreatment levels. Even though lead concentrations in the blood, soft organs, and bone were low, a highly significant negative correlation between blood lead and blood enzyme activity was obtained. This enzyme bioassay should provide a sensitive and precise estimate for monitoring lead in the blood for waterfowl.

Journal of Toxicology and Environmental Health↗

USGS2015

Context-dependent survival, fecundity and predicted population-level consequences of brucellosis in African buffalo

Chronic infections may have negative impacts on wildlife populations, yet their effects are difficult to detect in the absence of long-term population monitoring. Brucella abortus , the bacteria responsible for bovine brucellosis, causes chronic infections and abortions in wild and domestic ungulates, but its impact on population dynamics is not well understood. We report infection patterns and fitness correlates of bovine brucellosis in African buffalo based on (1) 7 years of cross-sectional disease surveys and (2) a 4-year longitudinal study in Kruger National Park (KNP), South Africa. We then used a matrix population model to translate these observed patterns into predicted population-level effects. Annual brucellosis seroprevalence ranged from 8·7% (95% CI = 1·8–15·6) to 47·6% (95% CI = 35·1–60·1) increased with age until adulthood (>6) and varied by location within KNP. Animals were on average in worse condition after testing positive for brucellosis ( F = −5·074, P < 0·0001), and infection was associated with a 2·0 (95% CI = 1·1–3·7) fold increase in mortality (χ 2 = 2·039, P = 0·036). Buffalo in low body condition were associated with lower reproductive success ( F = 2·683, P = 0·034), but there was no association between brucellosis and pregnancy or being observed with a calf. For the range of body condition scores observed in the population, the model-predicted growth rate was λ = 1·11 (95% CI = 1·02–1·21) in herds without brucellosis and λ = 1·00 (95% CI = 0·85–1·16) when brucellosis seroprevalence was 30%. Our results suggest that brucellosis infection can potentially result in reduced population growth rates, but because these effects varied with demographic and environmental conditions, they may remain unseen without intensive, longitudinal monitoring.

Kruger National Park↗

USGS2015

How are your berries? Perspectives of Alaska’s environmental managers on trends in wild berry abundance

Background : Wild berries are a valued traditional food in Alaska. Phytochemicals in wild berries may contribute to the prevention of vascular disease, cancer and cognitive decline, making berry consumption important to community health in rural areas. Little was known regarding which species of berries were important to Alaskan communities, the number of species typically picked in communities and whether recent environmental change has affected berry abundance or quality. Objective : To identify species of wild berries that were consumed by people in different ecological regions of Alaska and to determine if perceived berry abundance was changing for some species or in some regions. Design : We asked tribal environmental managers throughout Alaska for their views on which among 12 types of wild berries were important to their communities and whether berry harvests over the past decade were different than in previous years. We received responses from 96 individuals in 73 communities. Results : Berries that were considered very important to communities differed among ecological regions of Alaska. Low-bush blueberry ( Vaccinium uliginosum and V. caespitosum ), cloudberry ( Rubus chamaemorus ) and salmonberry ( Rubus spectabilis ) were most frequently identified as very important berries for communities in the boreal, polar and maritime ecoregions, respectively. For 7 of the 12 berries on the survey, a majority of respondents indicated that in the past decade abundance had either declined or become more variable. Conclusions : Our study is an example of how environmental managers and participants in local observer networks can report on the status of wild resources in rural Alaska. Their observations suggest that there have been changes in the productivity of some wild berries in the past decade, resulting in greater uncertainty among communities regarding the security of berry harvests. Monitoring and experimental studies are needed to determine how environmental change may affect berry abundance.

Alaska↗

USGS2002

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to central plains stream conditions

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use–land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite–nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use–land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

Kansas, Missouri, Nebraska↗

USGS2016

A goodness-of-fit test for occupancy models with correlated within-season revisits

Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and specifically evaluates occupancy model lack of fit related to correlation among detections within a sample unit. Our diagnostic tool is available for practitioners that serially deploy survey equipment as a way to achieve cost savings.

Ecology and Evolution↗

USGS2010

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

Nonpoint source pollution is the leading cause of the U.S.'s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO3NO2-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO3NO2-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO3NO2-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution. ?? 2010 Elsevier Ltd.

Journal of Environmental Management↗

USGS2019

A 50-year Sr/Ca time series from an enclosed, shallow-water Guam coral: In situ monitoring and extraction of a temperature trend, annual cycle, and ENSO and PDO signals

Located on the northern edge of the West Pacific Warm Pool and having a developed economy and modern infrastructure, Guam is well positioned and equipped for obtaining natural records of the west Pacific maritime paleoclimate. This study was a proof of concept to explore whether useful climate proxy records might be obtained from coral at readily accessible, even if geochemically nonoptimal, coastal sites. A 50-year Sr/Ca record (1960–2010) was thus obtained from a shallow-water, near-shore Porites lutea colony at a recreational facility inside Guam's Apra Harbor and compared with local and regional meteorological records, including the El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) indices. The accessibility of the site enabled documentation of relevant environmental variables for 16 months (September 2009–December 2010): seawater δ 18 O, pH, seawater cations, and nitrate. Time series of seawater δ 18 O, pH, and cations show evidence of freshwater input from direct rainfall and stream discharge into the harbor. An anomalously higher mean and variable concentrations of Ba suggest the presence of river-borne, fine-grained terrigenous sediment. Nevertheless, the Sr/Ca time series reproduces a long-term warming trend seen in historical records of local air temperature and regional sea-surface temperature (SST) and closely tracks the ENSO and PDO indices over the entire 50-year record. The consistency of the results with Guam's historical instrumental records, previous coral δ 18 O results from Guam obtained by others, and previous Sr/Ca proxy results for SST in similar environments elsewhere demonstrate that accessible near-shore sites—where environmental conditions can be monitored—can produce useful Sr/Ca records of local and regional climate phenomena.

Journal of Coastal Research↗

USGS2023

A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT ( A ustralia-wide M achine L earning ET for T rees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R 2 of 0.94 (RMSE 6.63 mm period −1 ) and 0.92 (RMSE 6.89 mm period −1 ), respectively. In comparison, correlation between in-situ ET and a national ET product returned R 2 of 0.44 (RMSE 34.08 mm period −1 ) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

The Journal of Environmental Management↗

USGS2015

Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development

Extraction of oil and gas via unconventional methods is becoming an important aspect of energy production worldwide. Studying the effects of this development in countries where these technologies are being widely used may provide other countries, where development may be proposed, with some insight in terms of concerns associated with development. A fairly recent expansion of unconventional oil and gas development in North America provides such an opportunity. Rapid increases in energy development in North America have caught the attention of managers and scientists as a potential stressor for wildlife and their habitats. Of particular concern in the Northern Great Plains of the U.S. is the potential for chloride-rich produced water associated with unconventional oil and gas development to alter the water chemistry of wetlands. We describe a landscape scale modeling approach designed to examine the relationship between potential chloride contamination in wetlands and patterns of oil and gas development. We used a spatial Bayesian hierarchical modeling approach to assess multiple models explaining chloride concentrations in wetlands. These models included effects related to oil and gas wells (e.g. age of wells, number of wells) and surficial geology (e.g. glacial till, outwash). We found that the model containing the number of wells and the surficial geology surrounding a wetland best explained variation in chloride concentrations. Our spatial predictions showed regions of localized high chloride concentrations. Given the spatiotemporal variability of regional wetland water chemistry, we do not regard our results as predictions of contamination, but rather as a way to identify locations that may require more intensive sampling or further investigation. We suggest that an approach like the one outlined here could easily be extended to more of an adaptive monitoring approach to answer questions about chloride contamination risk that are of interest to managers.

Montana, North Dakota↗

USGS2007

Use of a wetland index to evaluate changes in riparian vegetation after livestock exclusion

A method was developed to characterize ecological integrity of riparian sites based on the abundance of hydric species. This wetland index can be calculated with species data, or with community type data as performed here. Classified riparian community types were used to describe vegetation at 14 livestock exclosures and adjacent grazed areas. Community type wetland index values were generated and used to calculate site wetland index values. It was hypothesized that removal of livestock would result in higher wetland index values because of release from herbivory and decreased physical disturbance of vegetation, streambanks, and soil. The wetland index for exclosures was about 12% higher than grazed sites; differences were statistically significant (p < 0.01) based on paired t-tests. The increase in hydric vegetation after livestock exclusion may have contributed to the greater bank stability (p = 0.002) and smaller width-to-depth ratio (p = 0.005) in exclosures. Challenges were encountered in using community types to describe and compare site vegetation, which could be avoided with species data collection. The wetland index can be a tool to monitor sites over time, compare sites with similar environments, or compare sites for which environmental differences can be accounted.

Journal of the American Water Resources Associatio↗