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At least 1,117 records · Page 62Linked to original sources
USGS2009

Plants and ventifacts delineate late Holocene wind vectors in the Coachella Valley, USA

Strong westerly winds that emanate from San Gorgonio Pass, the lowest point between Palm Springs and Los Angeles, California, dominate aeolian transport in the Coachella Valley of the western Sonoran Desert. These winds deposit sand in coppice dunes that are critical habitat for several species, including the state and federally listed threatened species Uma inornata , a lizard. Although wind directions are generally defined in this valley, the wind field has complex interactions with local topography and becomes more variable with distance from the pass. Local, dominant wind directions are preserved by growth patterns of Larrea tridentata (creosote bush), a shrub characteristic of the hot North American deserts, and ventifacts. Exceptionally long-lived, Larrea has the potential to preserve wind direction over centuries to millennia, shaped by the abrasive pruning of windward branches and the persistent training of leeward branches. Wind direction preserved in Larrea individuals and clones was mapped at 192 locations. Compared with wind data from three weather stations, Larrea vectors effectively reflect annual prevailing winds. Ventifacts measured at 24 locations record winds 10° more westerly than Larrea and appear to reflect the direction of the most erosive winds. Based on detailed mapping of local wind directions as preserved in Larrea , only the northern half of the Mission-Morongo Creek floodplain is likely to supply sand to protected U. inornata habitat in the Willow Hole ecological reserve.

California↗
USGS2007

Empirical evaluation of decision support systems: Needs, definitions, potential methods, and an example pertaining to waterfowl management

Decision support systems are often not empirically evaluated, especially the underlying modelling components. This can be attributed to such systems necessarily being designed to handle complex and poorly structured problems and decision making. Nonetheless, evaluation is critical and should be focused on empirical testing whenever possible. Verification and validation, in combination, comprise such evaluation. Verification is ensuring that the system is internally complete, coherent, and logical from a modelling and programming perspective. Validation is examining whether the system is realistic and useful to the user or decision maker, and should answer the question: “Was the system successful at addressing its intended purpose?” A rich literature exists on verification and validation of expert systems and other artificial intelligence methods; however, no single evaluation methodology has emerged as preeminent. At least five approaches to validation are feasible. First, under some conditions, decision support system performance can be tested against a preselected gold standard. Second, real-time and historic data sets can be used for comparison with simulated output. Third, panels of experts can be judiciously used, but often are not an option in some ecological domains. Fourth, sensitivity analysis of system outputs in relation to inputs can be informative. Fifth, when validation of a complete system is impossible, examining major components can be substituted, recognizing the potential pitfalls. I provide an example of evaluation of a decision support system for trumpeter swan ( Cygnus buccinator ) management that I developed using interacting intelligent agents, expert systems, and a queuing system. Predicted swan distributions over a 13-year period were assessed against observed numbers. Population survey numbers and banding (ringing) studies may provide long term data useful in empirical evaluation of decision support.

Environmental Modelling and Software↗
USGS2019

Using maintenance records from a long-term sensor monitoring network to evaluate the relationship between maintenance schedule and data quality

Sensor-based environmental monitoring networks are beginning to provide the large-scale, long-term data required to address important fundamental and applied questions in ecology. However, the data quality from deployed sensors can be difficult and costly to ensure. In this study, we use maintenance records from the 12-year history of Louisiana’s Coastwide Reference Monitoring System (CRMS) to assess the relationship between various dimensions of data quality and the frequency of field visits to the sensors. We use hierarchical Bayesian models to estimate the probability of missing data, the probability that a corrective offset of the sensor is required, and the magnitude of required offsets for water elevation and salinity data. We compared these estimates to predetermined risk thresholds to the help identify maintenance schedules that balanced the efficient use of labor resources without sacrificing data quality. We found that the relationship between data quality and increasing maintenance interval varied across metrics. Additionally, for most metrics, the maintenance interval when the metric’s credible interval and risk threshold intersected varied throughout the year and with wetland type. These results suggest that complex maintenance schedules, in which field visits vary in frequency throughout the year and with environmental context, are likely to provide the best tradeoff between labor cost and data quality. This analysis demonstrates that quantitative assessment of maintenance records can positively impact the sustainability of long-term data collection projects by helping identify new potential efficiencies in monitoring program management.

Louisiana↗
USGS2025

Spatiotemporal dynamics and habitat use of red snapper (Lutjanus campechanus) on the southeastern United States Atlantic continental shelf

Red snapper ( Lutjanus campechanus ) is an iconic marine fish species along the southeast United States coast. Despite its ecological and economic importance, surprisingly little is known about red snapper biology and habitat use on the southeast United States Atlantic continental shelf (SEUS). We used data from a long-term baited trap and video survey (2011–2022), as well as from remotely operated vehicle (ROV) sampling (2021–2023), to quantify temporal changes in relative abundance, patterns of spatial distribution, and habitat use of red snapper in the SEUS. Using generalized additive models, we showed that red snapper increased in relative abundance from 2011 to 2022 by 960% in traps and 1,141% in video samples. Red snapper relative abundance was highest in mid-shelf waters off the east coast of Florida, Georgia, and, to a lesser extent, off the Outer Banks of North Carolina; red snapper were less common off southern North Carolina and South Carolina. Highest relative abundance of red snapper occurred in locations with a moderate amount of natural structured habitat and high seafloor complexity and were never observed at randomly selected ROV stations (n = 197) lacking structured habitat. These results increase our understanding of the spatial and temporal distribution of red snapper, improve our knowledge of red snapper habitat use, and can be used when scaling local density estimates to the entire SEUS.

Florida, Georgia, North Carolina, South Carolina↗
USGS2017

Amphibian terrestrial habitat selection and movement patterns vary with annual life-history period

Identification of essential habitat is a fundamental component of amphibian conservation; however, species with complex life histories frequently move among habitats. To better understand dynamic habitat use, we evaluated Wood Frog ( Lithobates sylvaticus (LeConte, 1825)) habitat selection and movement patterns during the spring migration and foraging periods and described the spatiotemporal variability of habitats used during all annual life-history periods. We radio-tracked 71 frogs in Maine during 2011–2013 and evaluated spring migration, foraging activity center (FAC), and within-FAC habitat selection. Telemetered frogs spent the greatest percentage of each field season in hibernacula (≥54.4%), followed by FACs (≥25.5%), migration habitat (≥16.9%), and breeding sites (≥4.5%). FACs ranged 49 – 1 335 m 2 (568.0 ± 493.4 m 2 ) and annual home ranges spanned 1 413 – 32 165 m 2 (11 780.6 ± 12 506.1 m 2 ). During spring migration, Wood Frogs exhibited different movement patterns (e.g., turn angles), selected different habitat features, and selected habitat features less consistently than while occupying FACs, indicating that the migration and foraging periods are ecologically distinct. Habitat-use studies that do not discriminate among annual life-history periods may obscure true ecological relationships and fail to identify essential habitat necessary for sustaining amphibian populations.

Maine↗
USGS2025

Idiosyncratic spatial scaling of biodiversity–disease relationships

High host biodiversity is hypothesized to dilute the risk of vector-borne diseases if many host species are ‘dead ends' that cannot effectively transmit the disease and low-diversity areas tend to be dominated by competent host species. However, many studies on biodiversity–disease relationships characterize host biodiversity at single, local spatial scales, which complicates efforts to forecast disease risk if associations between host biodiversity and disease change with spatial scale. Here, our objective is to evaluate the spatial scaling of relationships between host biodiversity and Borrelia (the bacterial taxon which causes Lyme disease) infection prevalence in small mammals. We compared the associations between infection prevalence and small mammal host diversity for local communities (individual plots) and metacommunities (multiple plots aggregated within a landscape) sampled by the National Ecological Observatory Network (NEON), an emerging continental-scale environmental monitoring program with a hierarchical sampling design. We applied a multispecies, spatially-stratified capture–recapture model to a trapping dataset to estimate five small mammal biodiversity metrics, which we used to predict infection status for a subset of trapped individuals. We found that relationships between Borrelia infection prevalence and biodiversity did indeed vary when biodiversity was quantified at different spatial scales but that these scaling behaviors were idiosyncratic among the five biodiversity metrics. For example, species richness of local communities showed a negative (dilution) effect on infection prevalence, while species richness of the small mammal metacommunity showed a positive (amplification) effect on infection prevalence. Our modeling approach can inform future analyses as data from similar monitoring programs accumulate and become increasingly available through time. Our results indicate that a focus on single spatial scales when assessing the influence of biodiversity on disease risk provides an incomplete picture of the complexity of disease dynamics in ecosystems.

Ecography↗
USGS2010

BRIDGES: Evolution of basic and applied linkages in benthic science

Growing awareness of environmental degradation resulted in stricter environmental regulations and laws for aquatic ecosystems. These regulations were followed by an increase in applied research and monitoring beginning in the early 1970s. The number of applied scientists who were members of the North American Benthological Society grew at a commensurate rate. The editors of J-NABS recognized that, despite these increases, submitted manuscripts mostly addressed basic science. In response, the BRIDGES section of J-NABS was created in 1994 to provide a forum for linking basic ecological principles to applied science problems and issues. We examined the emergence of applied science topics in J-NABS and its predecessor, Freshwater Invertebrate Biology , from their beginning in 1982 to 2009. We classified papers among 11 categories that included a basic/applied science linkage. In the 1980s, applied papers were predominantly on effects of eutrophication/pollution and landuse changes. When BRIDGES was established in 1994, papers were solicited by editors and BRIDGES sections usually included >1 paper on a common theme to express complementary or alternate viewpoints. Forty-two papers appeared in BRIDGES between 1994 and 2009, but the number per issue declined after 2001. The total number of applied science papers in J-NABS has increased since ∼1994. Citation analysis of BRIDGES papers illustrates how information is being cited, but applied papers often are used in ways that might not lead to citations. BRIDGES transitioned to a new format in September 2009 to address new types of complex, multifaceted linkages. All new BRIDGES articles will be open access, and authors will be encouraged to produce lay-language fact sheets and to post them on the web.

Journal of the North American Benthological Societ↗
USGS2017

Reproductive ecology, spawning behavior, and juvenile distribution of Mountain Whitefish in the Madison River, Montana

Mountain Whitefish Prosopium williamsoni were historically common throughout much of the U.S. Intermountain West. However, within the last decade Mountain Whitefish have exhibited population-level declines in some rivers. In the Madison River, Montana, anecdotal evidence indicates Mountain Whitefish abundance has declined and the population is skewed toward larger individuals, which is typically symptomatic of recruitment problems. Describing reproductive development, spawning behavior, and juvenile distribution will form a foundation for investigating mechanisms influencing recruitment. We collected otoliths and gonadal samples from fish of all size-classes to characterize fecundity, age at maturity, and spawning periodicity. We implanted radio tags in mature Mountain Whitefish and relocated tagged fish in autumn 2012–2014. Timing of spawning was determined from spawning status of captured females and from density of eggs collected on egg mats. In spring 2014, we seined backwater and channel sites to describe age-0 whitefish distribution. Mountain Whitefish were highly fecund (18,454 eggs/kg body weight) annual spawners, and age at 50% maturity was 2.0 years for males and 2.6 years for females. In 2013 and 2014, spawning occurred between the third week of October and first week of November. During spawning, spawning adults and collected embryos were concentrated in the downstream 26 km of the study site, a reach characterized by a complex, braided channel. This reach had the highest CPUE of age-0 Mountain Whitefish, and the percentage of spawning adults in the 25 km upstream from a sampling site was positively associated with juvenile CPUE. Within this reach, age-0 Mountain Whitefish were associated with silt-laden backwater and eddy habitats. Future investigations on mechanisms influencing recruitment should be focused on the embryological phase and age-0 fish.

Montana↗
USGS2019

Spatially explicit network analysis reveals multi-species annual cycle movement patterns of sea ducks

Conservation of long-distance migratory species poses unique challenges. Migratory connectivity—that is, the extent to which groupings of individuals at breeding sites are maintained in wintering areas—is frequently used to evaluate population structure and assess use of key habitat areas. However, for species with complex or variable annual-cycle movements, this traditional bimodal framework of migratory connectivity may be overly simplistic. Like many other waterfowl, sea ducks often travel to specific pre- and post-breeding sites outside their nesting and wintering areas to prepare for migration and, in some cases, molt their flight feathers. These additional molt migrations may play a key role in population structure, but are not included in traditional models of migratory connectivity. Network analysis, which applies graph theory to assess landscape connectivity, offers a powerful tool for quantitatively assessing the contributions of different sites used throughout the annual cycle to complex spatial networks. We collected satellite telemetry data on annual cycle movements of over 500 individual sea ducks of five species from throughout eastern North America and the Great Lakes. From these data, we constructed a multi-species network model of migratory patterns and site use over the course of the breeding, molting, wintering, and migration periods. Our results highlight inter- and intra-specific differences in the patterns and complexity of annual-cycle movement patterns, including the central importance of staging and molting sites in James Bay and the St. Lawrence River to multi-species habitat connectivity. We also discuss potential applications of network migration models to conservation prioritization, identification of population units, and integrating different data streams.

Ecological Applications↗
USGS1990

Growth and equilibrium in sea otter populations

(1) Counts through time were compiled for five sea otter ( Enhydra lutris ) populations in the north-east Pacific Ocean that were below equilibrium density: Attu Island, south-east Alaska, British Columbia, Washington State, and central California. Similar data were obtained from the equilibrium density population at Amchitka Island in 1971 and 1986. (2) Shorelines of Attu and Amchitka islands each were divided into forty-five segments, within which lineal (length of shore at mean higher high water) and areal (mean higher high water to the 10-fathom (18.3-m) depth contour) measures were made of the amount of habitat. (3) Rate of increase for the four northern populations was 17-20% year-1. Density- or size-dependent changes in rate of increase could not be demonstrated for any of these populations. The California population, in contrast, has undergone three apparent growth phases: the early 1900s to the mid-1970s when it increased about 5% year-1; the mid-1970s to the mid-1980s when it declined about 5% year-1; and the mid-1980s to 1988 when it increased about 7% year-1. An exponential growth model accounted for 92-98% of the variation in counts through time in all cases. (4) Population increase at Attu Island was achieved largely by range expansion as opposed to increased density. Range expansion in lineal and areal habitat occurred at 11% and 13% year-1, respectively; neither rate was lower (P > 0.25) than the observed rate of increase in numbers of animals counted. (5) Despite similarities in island size and physical environment, the most conservative estimates of population density at Amchitka Island were > 3 X greater than maximum density estimates for Attu Island. (6) Surveys of Amchitka Island from the mid-1930s through the mid-1980s indicate that the population increased to a peak in the 1940s; declined abruptly thereafter; and subsequently increased to a new and higher equilibrium in the 1960s, where it has since remained. (7) These population data, together with information on sea otter foraging and benthic community structure at Attu and Amchitka islands, suggest that multiple population equilibria exist in this system, emanating from complex trophic interactions low in the food web. I hypothesize that the lower population equilibrium is achieved largely or exclusively on an invertebrate diet consisting principally of herbivorous sea urchins. When unregulated by sea otter predation, the rocky benthos is deforested by sea urchin grazing. As growing otter populations compete increasingly for food, grazing intensity declines and the system shifts to one dominated by kelp beds, in turn leading to increased production, a shift in habitat structure, and population increases of kelp bed fishes. Apparently this new food resource elevates the sea otter population to a higher and more stable equilibrium.

Journal of Animal Ecology↗
USGS2003

Phosphorus in a ground-water contaminant plume discharging to Ashumet Pond, Cape Cod, Massachusetts, 1999

The discharge of a plume of sewagecontaminated ground water emanating from the Massachusetts Military Reservation to Ashumet Pond on Cape Cod, Massachusetts, has caused concern about excessive loading of nutrients, particularly phosphorus, to the pond. The U.S. Air Force is considering remedial actions to mitigate potentially adverse effects on the ecological characteristics of the pond from continued phosphorus loading. Concentrations as great as 3 milligrams per liter of dissolved phosphorus (as P) are in ground water near the pond's shoreline; concentrations greater than 5 milligrams per liter of phosphorus are in ground water farther upgradient. Temporary drive-point wells were used to collect water samples from 2 feet below the pond bottom to delineate concentration distributions in the pore waters of the pond-bottom sediments. Measurements in the field of specific conductance and colorimetrically determined orthophosphate concentrations provided real-time data to guide the sampling. The contaminant plume discharges to the Fishermans Cove area of Ashumet Pond as evidenced by elevated levels of specific conductance and boron, which are chemically conservative indicators of the sewage-contaminated ground water. Concentrations of nonconservative species, such as dissolved phosphorus, manganese, nitrate, and ammonium, also were elevated above background levels in ground water discharging to the pond, but in spatially complex distributions that reflect their distributions in ground water upgradient of the pond. Phosphorus concentrations exceeded background levels (greater than 0.10 milligram per liter) in the pond-bottom pore water along 875 feet of shoreline. Greatest concentrations (greater than 2 milligrams per liter) occurred within 30 feet of the shore in an area about 225 feet long. Calculations of phosphorus flux in the aquifer upgradient of Ashumet Pond, as determined from water-flux estimates from a steady-state ground-water-flow model and phosphorus concentrations (in 1999) from multilevel samplers about 75 feet upgradient of the pond, indicate that dissolved phosphorus moves towards the pond and discharges to it with the inflowing ground water at a rate as high as about 316 kilograms per year.

Massachusetts↗
USGS1999

The role of adaptive management as an operational approach for resource management agencies

In making resource management decisions, agencies use a variety of approaches that involve different levels of political concern, historical precedence, data analyses, and evaluation. Traditional decision-making approaches have often failed to achieve objectives for complex problems in large systems, such as the Everglades or the Colorado River. I contend that adaptive management is the best approach available to agencies for addressing this type of complex problem, although its success has been limited thus far. Traditional decision-making approaches have been fairly successful at addressing relatively straightforward problems in small, replicated systems, such as management of trout in small streams or pulp production in forests. However, this success may be jeopardized as more users place increasing demands on these systems. Adaptive management has received little attention from agencies for addressing problems in small-scale systems, but I suggest that it may be a useful approach for creating a holistic view of common problems and developing guidelines that can then be used in simpler, more traditional approaches to management. Although adaptive management may be more expensive to initiate than traditional approaches, it may be less expensive in the long run if it leads to more effective management. The overall goal of adaptive management is not to maintain an optimal condition of the resource, but to develop an optimal management capacity. This is accomplished by maintaining ecological resilience that allows the system to react to inevitable stresses, and generating flexibility in institutions and stakeholders that allows managers to react when conditions change. The result is that, rather than managing for a single, optimal state, we manage within a range of acceptable outcomes while avoiding catastrophes and irreversible negative effects. Copyright ?? 1999 by The Resilience Alliance.

Conservation Ecology↗
USGS2015

Markov decision processes in natural resources management: observability and uncertainty

The breadth and complexity of stochastic decision processes in natural resources presents a challenge to analysts who need to understand and use these approaches. The objective of this paper is to describe a class of decision processes that are germane to natural resources conservation and management, namely Markov decision processes, and to discuss applications and computing algorithms under different conditions of observability and uncertainty. A number of important similarities are developed in the framing and evaluation of different decision processes, which can be useful in their applications in natural resources management. The challenges attendant to partial observability are highlighted, and possible approaches for dealing with it are discussed.

Ecological Modelling↗
USGS2022

A century of drought in Hawai‘i: Geospatial analysis and synthesis across hydrological, ecological, and socioeconomic scales

Drought is a prominent feature of Hawaiʻi’s climate. However, it has been over 30 years since the last comprehensive meteorological drought analysis, and recent drying trends have emphasized the need to better understand drought dynamics and multi-sector effects in Hawaiʻi. Here, we provide a comprehensive synthesis of past drought effects in Hawaiʻi that we integrate with geospatial analysis of drought characteristics using a newly developed 100-year (1920–2019) gridded Standardized Precipitation Index (SPI) dataset. The synthesis examines past droughts classified into five categories: Meteorological, agricultural, hydrological, ecological, and socioeconomic drought. Results show that drought duration and magnitude have increased significantly, consistent with trends found in other Pacific Islands. We found that most droughts were associated with El Niño events, and the two worst droughts of the past century were multi-year events occurring in 1998–2002 and 2007–2014. The former event was most severe on the islands of O’ahu and Kaua’i while the latter event was most severe on Hawaiʻi Island. Within islands, we found different spatial patterns depending on leeward versus windward contrasts. Droughts have resulted in over $80 million in agricultural relief since 1996 and have increased wildfire risk, especially during El Niño years. In addition to providing the historical context needed to better understand future drought projections and to develop effective policies and management strategies to protect natural, cultural, hydrological, and agricultural resources, this work provides a framework for conducting drought analyses in other tropical island systems, especially those with a complex topography and strong climatic gradients.

Hawaii↗
USGS2023

A big data–model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus ) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host–pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Arizona, Colorado, Kansas, Montana, Nebraska, New ↗
USGS2023

2023 Coastal master plan: ICM-wetlands – Submerged aquatic vegetation (SAV) updates

Submerged aquatic vegetation (SAV) provides critical structural habitat for valuable nekton and wildlife species across coastal ecosystems and can buffer the negative effects of land loss. Landscape change and restoration efforts across coastal Louisiana can impact the occurrence, coverage, and species assemblages of SAV, and changes to these foundational species can have cascading impacts across food webs. To support the 2023 Coastal Master Plan efforts, a unique SAV model was developed to assess coverage and occurrence of SAV across aquatic waterbodies in response to environmental variables evaluated. This effort created a spatial model describing the probability of presence of SAV across the study area in response to changing conditions over the modeled time period. To develop the initial coverage data layer, we used remotely sensed Normalized Difference Vegetation Index (NDVI) and modified Normalized Difference Water Index (mNDWI) data from 2015-2018 to identify areas containing variable vegetation and water spectral reflectance. Key environmental variables evaluated included total suspended sediments (TSS), salinity, and physical exposure. Seasonal estimates for TSS and salinity were used, as research indicates that seasonal environmental variability is a significant driver for SAV establishment. Seasonal salinity was derived from Coast-wide Reference Monitoring Station (CRMS) data, and seasonal TSS was estimated from hyperspectral imagery. Estimates of physical exposure have previously been provided by calculating fetch (the distance across water over which waves can propagate), but this proved to be too computationally intensive to be feasible, and we found distance to land to be a reasonable proxy for exposure. To represent geographic conditions and historical factors influences on SAV establishment and occurrence (e.g., variables too numerous and complex to model) we developed a basin variable that served as a proxy for complex historical, or prior, conditions, determined by the forested, fresh, intermediate, brackish, or saline (FFIBS) score. The final model included spring TSS, spring salinity, distance to land, and the basin prior. The model performed well for the area evaluated, correctly classifying SAV (as present or absent) 89% of the time (Kappa = 580). SAV probability of presence responded as expected to change in these environmental variables, with likelihood of occurrence decreasing in response to increasing spring TSS, spring salinity, and distance to land. However, the model was more accurate at predicting absence (true negative = 0.940) than predicting presence (true positive = 0.626), suggesting that the scale of the model may limit the ability to predict presence. Moreover, the simplicity of the model limited the accuracy in highly dynamic environments, for example near the outflow of diversions or areas of significant changes in salinity or TSS. Through incorporating underwater communities like SAV, this master plan provides a holistic view of coastal change and restoration. To create healthy ecological structure and function in wetland habitats, the submergent communities must be considered alongside the emergent habitats. As the benefits of SAV are increasingly recognized, both here in Louisiana and beyond, SAV restoration and the use of SAV communities in assessing and improving ecological condition are becoming more common.

Louisiana↗
USGS2025

Real-time oil spill concentration assessment through fluorescence imaging and deep learning

Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R² score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.

Journal of Hazardous Materials↗
USGS2023

Changes in abiotic drivers of green sea urchin demographics following the loss of a keystone predator

Sea urchin population demographics can respond to changes in keystone species abundances, with the magnitude of these responses varying depending on environmental influences. In this study, sea urchin populations were surveyed across 15 Aleutian archipelago islands over a 30-year period to understand how patterns of sea urchin demography (density, biomass, and size structure) varied through different ecological regimes that were caused by changes in the abundance of sea otters, a keystone species in this system. To examine long-term changes in sea urchin demographics, four time periods across the recent decline of sea otters were examined: during sea otter presence (1987-1994), nearing absence at the end of the decline (1997-2000), 10 years postdecline (2008-2010), and 15-20 years following the loss of sea otters from the ecosystem (2014-2017). Our results show that when sea otters were broadly present, sea urchin demographics were generally similar across the archipelago, with few urchins that had large-sized bodies. During this time, bottom-up environmental controls were muted relative to top-down forces from keystone predation. However, as sea otters declined and remained absent from the system, abiotic factors became more influential on sea urchin biomass, density, and size structure. In particular, differences among island groups during these periods were correlated with variation in ocean temperature, bathymetric complexity, and habitat availability. Sea urchin recruitment also varied among island groups, corresponding to ecoregions delineated by oceanic passes across the archipelago. The functional extinction of sea otters revealed an increasing influence of abiotic forcing in the absence of top-down control. This study further highlights the importance of understanding how keystone predators regulate herbivore demographics.

Alaska↗