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At least 1,153 records · Page 64Linked to original sources
USGS2022

A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms

The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions, and the benefits that healthy coral reef ecosystems provide for many economies and societies. We developed a numeric (quantitative) BGC model for the coral reefs of Puerto Rico and the US Virgin Islands to transparently facilitate ecologically meaningful management decisions regarding these fragile resources. Here, reef conditions range from natural, undisturbed conditions to severely altered or degraded conditions. Numeric decision rules were developed by an expert panel for scleractinian corals and other benthic assemblages using multiple attributes to apply in shallow-water tropical fore reefs with depths <30 m. The numeric model employed decision rules based on metrics (e.g., % live coral cover, coral species richness, pollution-sensitive coral species, unproductive and sediment substrates, % cover by Orbicella spp.) used to assess coral reef condition. Model confirmation showed the numeric BCG model predicted the panel’s median site ratings for 84% of the sites used to calibrate the model and 89% of independent validation sites. The numeric BCG model is suitable for adaptive management applications and supports bioassessment and criteria development. It is a robust assessment tool that could be used to establish ecosystem condition that would aid resource managers in evaluating and communicating current or changing conditions, protect water and habitat quality in areas of high biological integrity, or develop restoration goals with stakeholders and other public beneficiaries.

Ecological Indicators↗
USGS2022

A biological condition gradient for coral reefs in the US Caribbean Territories: Part I. Coral narrative rules

As coral reef condition and sustainability continue to decline worldwide, losses of critical habitat and their ecosystem services have generated an urgency to understand and communicate reef response to management actions, environmental contamination, and natural disasters. Increasingly, coral reef protection and restoration programs emphasize the need for robust assessment tools for protecting high-quality waters and establishing conservation goals. Of equal importance is the need to communicate assessment results to stakeholders, beneficiaries, and the public so that environmental consequences of decisions are understood. The Biological Condition (BCG) model provides a structure to evaluate the condition of a coral reef in increments of change along a gradient of human disturbance. Communication of incremental change, regardless of direction, is important for decision makers and the public to better understand what is gained or lost depending on what actions are taken. We developed a narrative (qualitative) Biological Condition Gradient (BCG) from the consensus of a diverse expert panel to provide a framework for coral reefs in US Caribbean Territories. The model uses narrative descriptions of biological attributes for benthic organisms to evaluate reefs relative to undisturbed or minimally disturbed conditions. Using expert elicitation, narrative decision rules were proposed and deliberated to discriminate among six levels of change along a gradient of increasing anthropogenic stress. Narrative rules for each of the BCG levels are presented to facilitate the evaluation of benthic communities in coral reefs and provide specific narrative features to detect changes in coral reef condition and biological integrity. The BCG model can be used in the absence of numeric, or quantitative metrics, to evaluate actions that may encroach on coral reef ecosystems, manage endangered species habitat, and develop and implement management plans for marine protected areas, watersheds, and coastal zones. The narrative BCG model is a defensible model and communication tool that translates scientific results so the nontechnical person can understand and support both regulatory and non-regulatory water quality and natural resource programs.

Puerto Rico, U.S. Virgin Islands↗
USGS2022

Projected stream fish community risk to climate impacts in the Northeastern and Midwestern United States

Climate change is expected to alter stream fish habitat potentially leading to changes in the composition and distribution of fish communities. In the Northeastern and Midwestern United States we identified the distribution and characteristics of those fish communities most and least at risk of experiencing changes in climate which deviate from the climate they are associated with. We classified stream fish communities based on a suite of climate and environmental variables with multivariate regression trees under both recent and future conditions based on eight climate models. Our findings showed that some areas, such as the majority of the Illinois, Wisconsin, and Iowa), have high levels of risk of change in stream class, while much of Kentucky, West Virginia, Virginia, Pennsylvania, Eastern Ohio, Southern Michigan, and the Atlantic Coast are at relatively low risk. Stream class shifts ranged from over 75% of segments lost (associated with cooler temperatures) to gains of over 40% (associated with warmer temperatures). Common warmwater species such as green sunfish ( Lepomis cyanellus ), bluegill ( Lepomis macrochirus ) and largemouth bass ( Micropterus salmoides ) are expected to have the largest net gains in associated stream classes, while species associated with cooler streams such as Southern redbelly dace ( Chrosomus erythrogaster ), slimy sculpin ( Cottus cognatus ), and Eastern blacknose dace ( Rhinichthys atratulus ) were expected to experience the largest proportional losses. By pairing our climate risk predictions with other stressors such anthropogenic land use, habitat fragmentation, and water quality impairment, we identified opportunities for preservation (low risk due to all threats), restoration (low risk due to climate, high risk due to other stressors), and adaptation (high climate risk with low risk from other stressors). Understanding which communities are at risk due to climate change will aid in developing adaptation strategies to help sustain them in the future.

Connecticut, Delaware, Illinois, Indiana, Iowa, Ke↗
USGS2022

Hydrologic and environmental thresholds in stream fish assemblage structure across flow regimes

The characteristic pattern of variation in flow magnitude, frequency, duration, timing, and rate of change defines the flow regime of rivers and streams and is a key driver of ecosystem processes in fluvial ecosystems. Understanding how freshwater biotic assemblages change across gradients of hydrology and anthropogenic-source disturbance in different streamflow regimes is crucial to managing for sustainable environmental flows and watershed conservation. We compiled long-term (1916–2016) occurrence records for fishes collected in the Ouachita-Ozark Interior Highlands and West Gulf Coastal Plain streams, together with hydrologic metrics calculated from daily streamflow data measured at USGS stream gauging stations (n = 111), to examine important drivers and thresholds for fish assemblage turnover in groundwater (GW), runoff (RO), and intermittent (INT) flow regimes. We also examined the importance of spatial gradients (latitude, longitude, elevation, drainage area) and anthropogenic-source stressors (Hydrologic Disturbance Index; HDI) for fish assemblage turnover using a gradient forest modeling approach. Watershed fragmentation was of high importance for fish assemblage turnover in RO and INT streams, while changes in dam storage were more important for fishes in GW streams. Hydrologic metrics describing seasonal and stochastic properties of daily streamflow (Mag6) were most important for fish assemblage turnover in INT streams. Timing of high flow events had significantly higher importance compared to flow magnitude, duration, and frequency metrics, especially for fish assemblages in GW and INT streams. The frequency and timing of low flow events had high importance for fish assemblage turnover across all stream flow classes, while the magnitude of low flows and the magnitude and rate of change of average flows was most important for INT stream fish assemblages. In addition to benefiting multi-species conservation and management actions through identification of local and regional flow-ecology relationships generalized across different flow regimes, the results of this study provide a better understanding of complex nonlinear threshold effects, which is critical to anticipating changes in aquatic ecosystems and communities.

Arkansas, Missouri, Oklahoma↗
USGS2023

Using taxa-based approaches to delineate stream macroinvertebrate assemblage responses to stressor gradients in modified alluvial agroecosystems

Alluvial plain landscapes are some of the most agriculturally productive lands in the world but often have modified stream ecosystems due to cultivation history. This context requires consideration when establishing water quality management goals. We analyzed state water quality databases to demonstrate that Mississippi Alluvial Plain (MAP) ecoregion streams have elevated specific conductivity (SC) and nutrients and lower macroinvertebrate local and regional taxa pools compared to streams in other ecoregions, potentially reducing the efficacy of traditional biomonitoring approaches within the region. To overcome these challenges, we used threshold indicator taxa analysis (TITAN) to compare macroinvertebrate assemblage responses to water quality gradients among ecoregions in Mississippi. We identified individual taxa and assemblage-level responses to increasing water quality degradation in MAP streams. Observed responses occurred at higher concentrations for SC, total organic carbon (TOC) and total phosphorus (TP), but not total nitrogen (TN) relative to other ecoregions. These responses appeared to be driven by a large proportion of indicator taxa considered tolerant or unresponsive in other ecoregions, responding negatively to increasing water quality stressors in MAP streams. Our observed assemblage-level stressor responses to WQ gradients in MAP streams demonstrate shifting tolerance in highly altered ecosystems may require adjustments to recovery expectations but also provide useful measures for monitoring improvements in regional water quality. For example, our observed macroinvertebrate assemblage response to increasing TP identified a management goal similar to guidance based on distributional analysis of water quality data within the MAP ecoregion (0.11 vs 0.128 mg L−1) and thus provide some biological basis for previously identified nutrient goals for the region. Our approach can guide and monitor success of nutrient reduction efforts in MAP watersheds and other alluvial plain agroecosystems where reference conditions do not exist, and local and regional taxa pools are less diverse and may not support full recovery of ecological assemblages. While our results are promising, they should also be compared with more sensitive and less habitat-limited biological assemblages (e.g., algae or bacteria) to better understand complex ecological responses to best management practices designed to increase sustainability of high production agricultural regions.

Mississippi↗
USGS2026

Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach

Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.

Arizona, New Mexico↗
USGS2007

Optimal control of Atlantic population Canada geese

Management of Canada geese ( Branta canadensis ) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size; limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy.

Ecological Modelling↗
USGS2007

Alternative community structures in a kelp-urchin community: A qualitative modeling approach

Shifts in interaction patterns within a community may result from periodic disturbances and climate. The question arises as to the extent and significance of these shifting patterns. Using a novel approach to link qualitative mathematical models and field data, namely using the inverse matrix to identify the community matrix, we reconstructed community networks from kelp forests off the Oregon Coast. We simulated all ecologically plausible interactions among community members, selected the models whose outcomes match field observations, and identified highly frequent links to characterize the community network from a particular site. We tested all possible biologically reasonable community networks through qualitative simulations, selected those that matched patterns observed in the field, and further reduced the set of possibilities by retaining those that were stable. We found that a community can be represented by a set of alternative structures, or scenarios. From 11,943,936 simulated models, 0.23% matched the field observations; moreover, only 0.006%, or 748 models, were highly reliable in their predictions and met conditions for stability. Predator-prey interactions as well as non-predatory relationships were consistently found in most of the 748 models. These highly frequent connections were useful to characterize the community network in the study site. We suggest that alternative networks provide the community with a buffer to disturbance, allowing it to continuously reorganize to adapt to a variable environment. This is possible due to the fluctuating capacities of foraging species to consume alternate resources. This suggestion is sustained by our results, which indicate that none of the models that matched field observations were fully connected. This plasticity may contribute to the persistence of these communities. We propose that qualitative simulations represent a powerful technique to raise new hypotheses concerning community dynamics and to reconstruct guidelines that may govern community patterns. ?? 2007 Elsevier B.V. All rights reserved.

Ecological Modelling↗
USGS2008

The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models ( Smith and Heath, 2001 and Allen et al., 2004 ). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.

Ecological Modelling↗
USGS2009

Modelling predation by transient leopard seals for an ecosystem-based management of Southern Ocean fisheries

Correctly quantifying the impacts of rare apex marine predators is essential to ecosystem-based approaches to fisheries management, where harvesting must be sustainable for targeted species and their dependent predators. This requires modelling the uncertainty in such processes as predator life history, seasonal abundance and movement, size-based predation, energetic requirements, and prey vulnerability. We combined these uncertainties to evaluate the predatory impact of transient leopard seals on a community of mesopredators (seals and penguins) and their prey at South Georgia, and assess the implications for an ecosystem-based management. The mesopredators are highly dependent on Antarctic krill and icefish, which are targeted by regional fisheries. We used a state-space formulation to combine (1) a mark-recapture open-population model and individual identification data to assess seasonally variable leopard seal arrival and departure dates, numbers, and residency times; (2) a size-based bioenergetic model; and (3) a size-based prey choice model from a diet analysis. Our models indicated that prey choice and consumption reflected seasonal changes in leopard seal population size and structure, size-selective predation and prey vulnerability. A population of 104 (90-125) leopard seals, of which 64% were juveniles, consumed less than 2% of the Antarctic fur seal pup production of the area (50% of total ingested energy, IE), but ca. 12-16% of the local gentoo penguin population (20% IE). Antarctic krill (28% IE) were the only observed food of leopard seal pups and supplemented the diet of older individuals. Direct impacts on krill and fish were negligible, but the "escapement" due to leopard seal predation on fur seal pups and penguins could be significant for the mackerel icefish fishery at South Georgia. These results suggest that: (1) rare apex predators like leopard seals may control, and may depend on, populations of mesopredators dependent on prey species targeted by fisheries; and (2) predatory impacts and community control may vary throughout the predator's geographic range, and differ across ecosystems and management areas, depending on the seasonal abundance of the prey and the predator's dispersal movements. This understanding is important to integrate the predator needs as natural mortality of its prey in models to set prey catch limits for fisheries. Reliable estimates of the variability of these needs are essential for a precautionary interpretation in the context of an ecosystem-based management. ?? 2009 Elsevier B.V.

Ecological Modelling↗
USGS2018

Quantifying population-level effects of water temperature, flow velocity and chemical-induced reproduction depression: A simulation study with smallmouth bass

Evaluating stochastic abiotic factors and their combined effects on fish and wildlife populations have been challenging in environmental sciences. Contributing to this challenge is the paucity of data describing how observations made on individuals related to exposure to chemical compounds ultimately effect population vital rates, and how this exposure interacts with other abiotic drivers. Using three smallmouth bass populations in Pennsylvania as a case study, we explored both single-factor and combined effects of water temperature, flow velocity and chemical exposure on populations through a model simulation. Although there are many pathways through which chemicals can affect population vital rates, we focused on one where chemical exposure leads to reduced reproduction. Among the three populations considered, two (the Juniata and Susquehanna populations) have experienced adverse health, including the potential adverse effects of environmental stress and chemical contamination that may cause disease and mortality of young-of-year (YOY), various skin lesions and a high prevalence of intersex or testicular oocytes in adults. The third population (The Alleghany population) has not encountered mortality events of YOY and intersex prevalence is much lower. The simulation involved projecting populations using a length-based model under different environmental conditions. In the simulations, abiotic factors influenced population dynamics through their impacts on growth, survival and recruitment. Response to the same environmental stress varied by population and life-stage of the species. Factors affecting young adult and adult life-stages had great influence on proportional stock density (PSD) and the probability of having PSD within the suggested range (PSD probability). Increases in water temperature had a negative effect and dominant role in the combined effect on population size structure (e.g., PSD and PSD probability) – increases in flow velocity during the spring season also had a negative effect on abundance. Populations with high recruitment rates sustained relatively large population size, even under high water temperature and/or high flow velocity, which suggests that factors and management strategies that benefit recruitment (such as reduced chemical contaminants) may compensate for the negative effects of warming water temperatures and high spring flow velocity on population size.

Ecological Modelling↗
USGS2022

Informing surveillance through the characterization of outbreak potential of chronic wasting disease in white-tailed deer

Understanding the role that an environmental prion reservoir plays in the outbreak dynamics of chronic wasting disease (CWD) in free ranging white-tailed deer ( Odocoileus virginianus ) is critical for the allocation of disease surveillance resources by state and provincial wildlife agencies. We hypothesized that demographic, ecological, and epidemiological configurations naturally attenuate epidemic risk despite the introduction of infectious prions into a susceptible population of deer, but the magnitude of infectious prions in the environmental prion reservoir complicate outbreak expectations. We developed a Susceptible-Latent-Exposed-Infective (SLEI) compartment model to represent the dynamics of CWD epidemics in free-ranging white-tailed deer, then used the basic reproductive ratio ( R 0 "> R0 ) to pinpoint counties under which pathogenic introduction (transport of infectious bodily fluids, tissues, and carcasses through natural or anthropogenic means) naturally produced (or failed to produce) an epidemic. We found that the outlook for an epidemic hinged on transmission rates, the magnitude of environmental contamination, and system type (density-, frequency-, or density/frequency-dependent). CWD can persistently infect individuals living in a contaminated environment even if direct transmission is insufficient to sustain circulation. Theoretical results show that transmission of CWD cannot be exclusively density dependent, and must behave as either a mix between frequency and density dependent, or strictly frequency dependent. While the compartment model is a simplistic representation of reality and did not contain many complicating biological considerations, it was immediately useful in hypothesis generation, motivating the collection of additional data for use in more biologically detailed models, and in the allocation of finite surveillance resources to place emphasis on data collection in areas where an introduction of infectious prions is comparatively more likely to result in an epidemic.

Ecological Modelling↗
USGS2024

Visualizing wading bird optimal foraging decisions with aggregation behaviors using individual-based modeling

Foragers on patchy landscapes must efficiently balance time between searching for and consuming resources to meet their daily energetic requirements. Spatial aggregation foraging behaviors may improve foraging efficiency by sharing information on locations of resource hotspots. Wading birds are an example of patch foragers that form colonial aggregations during the breeding season to obtain sufficient prey energy to sustain themselves and their offspring each day. Here, we describe a spatially-explicit simulation model of wading bird optimal foraging that represents information sharing through visual cues. The overall purpose of the model is to describe how wading bird daily foraging and reproductive success may change with alternative water control management practices that determine spatial availability of prey for wading birds on the landscape, throughout their breeding seasons. Wading birds are simulated as individuals that operate independently, sampling and selecting among patches based on a prey density tolerance threshold, but also use information from other birds to inform their selection decisions. Foraging success is evaluated against the fundamental objectives of (a) fulfilling daily energetic demands and (b) minimizing predation exposure, by tracking individual daily energetic intake and time spent foraging. In this way, the model approximates population level dynamics of wading bird aggregations that emerge through collective decision making of birds simulated at the lower individual level. Key results of this study suggest that aggregation behaviors may improve population-level foraging success rates, and the optimal settling threshold may modulate when resources become more scarce or difficult to find. Thus, the model addresses ecological theory on the advantages of foraging in groups versus independently. This technique is appropriate for evaluating wading bird populations that forage on patchy landscapes, such as seasonally-pulsed wetlands, wherever sufficient information is available to describe (1) foraging behavior (e.g., feeding rate, flight speeds, patch selection decisions), (2) key landscape characteristics, (3) spatial distributions of prey densities among foraging patches, and (4) changes in prey densities through time. The model was designed to predict qualitative, testable spatial patterns of wading bird foraging movements which can be compared with empirical observations and empirically-derived habitat suitability models. These techniques can also be applied to other bird species, such as shorebirds, or more generally to any species that transits between discrete foraging patches.

Ecological Modelling↗
USGS2025

Sediment transport modeling in Lake Ontario embayments: Impacts on fish spawning substrates

Anthropogenically-driven sedimentation changes have had adverse environmental impacts on aquatic environments, including reductions in fish spawning habitats in embayments worldwide. This study was motivated by the need to understand the impacts of waves and current-driven sedimentation patterns on traditional spawning areas and their effect on sustainable fish reproduction in the Great Lakes. Coupled hydrodynamic, wave, and sediment transport models were developed within the Delft3D-SWAN (DS) framework to predict sedimentation patterns in two embayments in Lake Ontario, Sodus Bay and Chaumont Bay, that have been historically important fish spawning habitats. These bays, with distinct geomorphic characteristics and connectivity to Lake Ontario, offer an opportunity to examine how wind-generated waves and currents impact bed shear stress and subsequent sedimentation patterns. Areas experiencing greater wave-induced bed shear stress were identified and compared between the two bays. Simulated sediment transport patterns showed notable erosion near the lake-bay connections and increased deposition in the inner areas of both embayments. Observed Cisco embryo deposition corresponded to regions of high sheer stress and lower sedimentation, indicating physical attributes in those areas that are important for embryo survival. These results show where sediment settling and erosion occur in the two bays and highlight potential impacts on traditional spawning areas.

New York↗
USGS2022

Analysis of provisioning ecosystem services and perceptions of climate change for indigenous communities in the Western Himalayan Gurez Valley, Pakistan

Climate change is a significant threat to people living in mountainous regions. It is essential to understand how montane communities currently depend especially on the provisioning ecosystem services (ES) and the ways in which climate change will impact these services, so that people can develop relevant adaptation strategies. The ES in the Gurez Valley, in the Western Himalayas of Pakistan, provide a unique opportunity to explore these questions. This understudied area is increasingly exposed not only to climate change but also to the overexploitation of resources. Hence, this study aimed to (a) identify and value provisioning ES in the region; (b) delineate indigenous communities’ reliance on ES based on valuation; and (c) measure the perceptions of indigenous communities of the impact of climate change on the ES in Gurez Valley. Semi-structured interviews and focus group discussions were used to classify the provisioning ES by using the ‘Common International Classification on Ecosystem Services’ (CICES) table and applying the ‘Total Economic Valuation (TEV)’ Framework. Results indicate that the indigenous communities are highly dependent on ES, worth 6730 ± 520 USD/Household (HH)/yr, and perceive climate change as a looming threat to water, crops, and rearing livestock ESS in the Gurez Valley. The total economic value of the provisioning ES is 3.1 times higher than a household’s average income. Medicinal plant collection is a significant source of revenue in the Valley for some households, i.e., worth 766 ± 134.8 USD/HH/yr. The benefits of the sustainable use of ES and of climate change adaptation and mitigation, are culturally, economically, and ecologically substantial for the Western Himalayans.

Gurez Valley, Himalaya↗
USGS2025

The Benefits Knowledges Learning Framework: A tool for learning across diverse knowledge systems in ecosystem valuation

Sustainable and just environmental management depends on meaningful consideration of the plural values of nature, as they arise in association with diverse worldviews and understandings of well-being. To achieve value pluralism in decision-making, we must also attend to knowledge pluralism, in terms of recognizing the validity and decision relevance of a broader suite of knowledge forms that convey diverse understandings of well-being and benefit. In this article, we outline a social learning tool – the Benefits Knowledges Learning Framework – that supports expanded thinking about decision-relevant, actionable knowledge, and the associated spectrum of available opportunities to learn from these diverse knowledge forms across phases of decision-making. It does so through: 1) cultivation of reflexivity and mutual learning about the knowledge systems of diverse actors involved in the decision process; 2) identification of diverse benefits knowledge forms that are available to inform decision-making; and 3) identification of opportunities to learn from these knowledge forms. Diverse forms of benefits knowledge include both knowledge products (documentation) and knowledge practices (lived and embodied). The framework can be applied to retrospective case analysis to understand and learn from constraints and enabling factors in past decision processes. It can also be applied to assess on-going decision-making and identify current opportunities for improvement. The framework begins with a start-up phase that encourages those applying the framework to address any concerns raised by stakeholders and rightsholders and determine whether framework application is appropriate in a particular context.

Washington↗
USGS2009

Coastal groundwater dynamics off Santa Barbara, California: combining geochemical tracers, electromagnetic seepmeters, and electrical resistivity

This paper presents repeat field measurements of 222 Rn and 223,224,226,228 Ra, electromagnetic seepage meter-derived advective fluxes, and multi-electrode, stationary and continuous marine resistivity surveys collected between November 2005 and April 2007 to study coastal groundwater dynamics within a marine beach in Santa Barbara, California. The study provides insight into magnitude and dynamics of submarine groundwater discharge (SGD) and associated nutrient loadings into near-shore coastal waters, where the predominant SGD drivers can be both spatially and temporally separated. Rn-222 and 223,224,226,228 Ra were utilized to quantify the total and saline contribution, respectively, of SGD. The two short-lived 224,223 Ra isotopes provided an estimate of apparent near-shore water mass age, as well as an estimate of the Ra-derived eddy diffusion coefficient, K h ( 224 Ra = 2.86 ± 0.7 m 2 s −1 ; 223 Ra = 1.32 ± 0.5 m 2 s −1 ). Because 222 Rn ( t ½ = 3.8 day) and 224 Ra ( t ½ = 3.66 day) have comparable half-lives and production terms, they were used in concert to examine respective water column removal rates. Electromagnetic seepage meters recorded the physical, bi-directional exchange across the sediment/water interface, which ranged from −6.7 to 14.5 cm day −1 , depending on the sampling period and position relative to the low tide line. Multi-day time-series 222 Rn measurements in the near-shore water column yielded total (saline + fresh) SGD rates that ranged from 3.1 ± 2.6 to 9.2 ± 0.8 cm day −1 , depending on the sampling season. Offshore 226 Ra ( t ½ = 1600 year) and 222 Rn gradients were used with the calculated K h values to determine seabed flux estimates (dpm m −2 day −1 ), which were then converted into SGD rates (7.1 and 7.9 cm day −1 , respectively). Lastly, SGD rates were used to calculate associated nutrient loads for the near-shore coastal waters off Santa Barbara. Depending on both the season and the SGD method utilized, the following SGD-derived nutrient inputs were computed (mol per day per meter of shoreline): NH 4 + = 0.06–0.29 mol day −1 m −1 ; SiO 4 = 0.22–0.29 mol day −1 m −1 ; PO 4 3− = 0.04–0.17 mol day −1 m −1 ; [NO 2 − + NO 3 − ] = 0–0.52 mol day −1 m −1 ; dissolved inorganic nitrogen (DIN) = 0.01–0.17 mol day −1 m −1 , and dissolved organic nitrogen (DON) = 0.08–0.09 mol day −1 m −1 . Compared to the ephemeral nature of fluvial and marine inputs into this region, such SGD-derived loadings can provide a sustained source of select nutrients to the coastal waters off Santa Barbara, California that should be accounted for in mass balance estimates.

California↗
USGS2011

Elevation trends and shrink-swell response of wetland soils to flooding and drying

Given the potential for a projected acceleration in sea-level rise to impact wetland sustainability over the next century, a better understanding is needed of climate-related drivers that influence the processes controlling wetland elevation. Changes in local hydrology and groundwater conditions can cause short-term perturbations to marsh elevation trends through shrink–swell of marsh soils. To better understand the magnitude of these perturbations and their impacts on marsh elevation trends, we measured vertical accretion and elevation dynamics in microtidal marshes in Texas and Louisiana during and after the extreme drought conditions that existed there from 1998 to 2000. In a Louisiana marsh, elevation was controlled by subsurface hydrologic fluxes occurring below the root zone but above the 4 m depth (i.e., the base of the surface elevation table benchmark) that were related to regional drought and local meteorological conditions, with marsh elevation tracking water level variations closely. In Texas, a rapid decline in marsh elevation was related to severe drought conditions, which lowered local groundwater levels. Unfragmented marshes experienced smaller water level drawdowns and more rapid marsh elevation recovery than fragmented marshes. It appears that extended drawdowns lead to increased substrate consolidation making it less resilient to respond to future favorable conditions. Overall, changes in water storage lead to rapid and large short-term impacts on marsh elevation that are as much as five times greater than the long-term elevation trend, indicating the importance of long-term, high-resolution elevation data sets to understand the prolonged effects of water deficits on marsh elevation change.

Louisiana, Texas↗