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At least 1,585 records · Page 88Linked to original sources

USGS2014

Establishing endangered species recovery criteria using predictive simulation modeling

Listing a species under the Endangered Species Act (ESA) and developing a recovery plan requires U.S. Fish and Wildlife Service to establish specific and measurable criteria for delisting. Generally, species are listed because they face (or are perceived to face) elevated risk of extinction due to issues such as habitat loss, invasive species, or other factors. Recovery plans identify recovery criteria that reduce extinction risk to an acceptable level. It logically follows that the recovery criteria, the defined conditions for removing a species from ESA protections, need to be closely related to extinction risk. Extinction probability is a population parameter estimated with a model that uses current demographic information to project the population into the future over a number of replicates, calculating the proportion of replicated populations that go extinct. We simulated extinction probabilities of piping plovers in the Great Plains and estimated the relationship between extinction probability and various demographic parameters. We tested the fit of regression models linking initial abundance, productivity, or population growth rate to extinction risk, and then, using the regression parameter estimates, determined the conditions required to reduce extinction probability to some pre-defined acceptable threshold. Binomial regression models with mean population growth rate and the natural log of initial abundance were the best predictors of extinction probability 50 years into the future. For example, based on our regression models, an initial abundance of approximately 2400 females with an expected mean population growth rate of 1.0 will limit extinction risk for piping plovers in the Great Plains to less than 0.048. Our method provides a straightforward way of developing specific and measurable recovery criteria linked directly to the core issue of extinction risk. Published by Elsevier Ltd.

Biological Conservation↗

USGS2015

Home in the heat: Dramatic seasonal variation in home range of desert golden eagles informs management for renewable energy development

Renewable energy is expanding quickly with sometimes dramatic impacts to species and ecosystems. To understand the degree to which sensitive species may be impacted by renewable energy projects, it is informative to know how much space individuals use and how that space may overlap with planned development. We used global positioning system–global system for mobile communications (GPS-GSM) telemetry to measure year-round movements of golden eagles ( Aquila chrysaetos ) from the Mojave Desert of California, USA. We estimated monthly space use with adaptive local convex hulls to identify the temporal and spatial scales at which eagles may encounter renewable energy projects in the Desert Renewable Energy Conservation Plan area. Mean size of home ranges was lowest and least variable from November through January and greatest in February–March and May–August. These monthly home range patterns coincided with seasonal variation in breeding ecology, habitat associations, and temperature. The expanded home ranges in hot summer months included movements to cooler, prey-dense, mountainous areas characterized by forest, grasslands, and scrublands. Breeding-season home ranges (October–May) included more lowland semi-desert and rock vegetation. Overlap of eagle home ranges and focus areas for renewable energy development was greatest when eagle home ranges were smallest, during the breeding season. Golden eagles in the Mojave Desert used more space and a wider range of habitat types than expected and renewable energy projects could affect a larger section of the regional population than was previously thought.

California↗

USGS2016

Impacts of climate change and renewable energy development on habitat of an endemic squirrel, Xerospermophilus mohavensis , in the Mojave Desert, USA

Predicting changes in species distributions under a changing climate is becoming widespread with the use of species distribution models (SDMs). The resulting predictions of future potential habitat can be cast in light of planned land use changes, such as urban expansion and energy development to identify areas with potential conflict. However, SDMs rarely incorporate an understanding of dispersal capacity, and therefore assume unlimited dispersal in potential range shifts under uncertain climate futures. We use SDMs to predict future distributions of the Mojave ground squirrel, Xerospermophilus mohavensis Merriam, and incorporate partial dispersal models informed by field data on juvenile dispersal to assess projected impact of climate change and energy development on future distributions of X. mohavensis . Our models predict loss of extant habitat, but also concurrent gains of new habitat under two scenarios of future climate change. Under the B1 emissions scenario- a storyline describing a convergent world with emphasis on curbing greenhouse gas emissions- our models predicted losses of up to 64% of extant habitat by 2080, while under the increased greenhouse gas emissions of the A2 scenario, we suggest losses of 56%. New potential habitat may become available to X. mohavensis , thereby offsetting as much as 6330 km 2 (50%) of the current habitat lost. Habitat lost due to planned energy development was marginal compared to habitat lost from changing climates, but disproportionately affected current habitat. Future areas of overlap in potential habitat between the two climate change scenarios are identified and discussed in context of proposed energy development.

California↗

USGS2023

Cryptic declines of small, cold-water specialists highlight potential vulnerabilities of headwater streams as climate refugia

Increasing temperatures and climate-driven disturbances like wildfire are a growing threat to many species, including cold-water specialists. Montane areas and cold streams are often considered climate refugia that buffer communities against change. However, climate refugia are often species-specific, and despite growing awareness that life histories and habitat requirements shape responses to change, small or non-game species are often under-represented in monitoring and planning programs. A recent study in Montana, USA, revealed much larger warming-related declines in occupancy for small, non-game slimy sculpin ( Cottus cognatus ) between 1993 and 1995 and 2011–2013 than for two socially valued salmonid fishes that shape regional conservation efforts. To broaden insight into climate change vulnerabilities of headwater stream communities, we analyzed data for Rocky Mountain tailed frogs ( Ascaphus montanus ) that were collected during those same electrofishing surveys for fishes from 241 stream reaches. Tailed frogs occupy small, cold streams and have several life-history traits that make them sensitive to environmental change. We used a Bayesian framework to estimate occupancy, colonization, and extinction dynamics relative to forest canopy, estimated stream temperature, and wildfire effects. Tailed frog occupancy decreased by 19 % from 1993 to 1995 to 2011–2013. Changes in occupancy were linked with increased extinction and reduced colonization where there were fire-driven reductions in canopy cover, and reduced colonization of stream reaches that warmed on average 0.8 °C during the study. Our results highlight extensive extirpations for oft-overlooked species and emphasize the importance of including species with diverse habitat requirements and life histories in conservation planning.

Idaho, Montana↗

USGS2023

Grizzly bear movement models predict habitat use for nearby populations

Conservation planning and decision-making can be enhanced by ecological models that reliably transfer to times and places beyond those where models were developed. Transferrable models can be especially helpful for species of conservation concern, such as grizzly bears ( Ursus arctos ). Currently, only four grizzly bear populations remain in the contiguous United States. We evaluated transferability of previously derived individual-based, integrated step selection functions (iSSFs) developed from GPS-collared grizzly bears in the Northern Continental Divide Ecosystem by applying them within the nearby Selkirk (SE), Cabinet-Yaak (CYE), and Greater Yellowstone Ecosystems (GYE). We simulated 100 replicates of 5000 steps for each iSSF in each ecosystem, summarized relative use into 10 equal-area classes for each sex, and overlaid GPS locations from bears in the SE, CYE, and GYE on resulting maps. Spearman rank correlations between numbers of locations and class rank were ≥ 0.96 within each study area, indicating models were highly predictive of grizzly bear space use in these nearby populations. Assessment of models using smaller subsets of data in space and time demonstrated generally high predictive accuracy for females. Although generally high across space and time, predictive accuracy for males was low within some watersheds and in summer within the SE and CYE, potentially due to seasonal effects, vegetation, and food assemblage differences. Altogether, these results demonstrated high transferability of our models to landscapes in the Northern Rocky Mountains, suggesting they may be used to evaluate habitat suitability and connectivity throughout the region to benefit conservation planning.

Idaho, Montana, Washington, Wyoming↗

USGS2026

A regional simulation modeling framework for evaluating invasive annual grass management across the sagebrush biome

Invasive annual grasses (IAG) continue to spread within the sagebrush biome of the western United States, degrading plant communities and wildlife habitat, decreasing forage for ranching livelihoods, and heightening wildfire risk. Effective management of IAGs requires action and long-term strategic planning across the sagebrush biome, but the cumulative effects of IAG treatments over time and space are not well understood, especially over broad extents defined for strategies like the Sagebrush Conservation Design. We developed a simulation model and sampling framework that allow local-scale actions to be ‘scaled up’ to evaluate large-scale regional and biome-wide management strategy outcomes. We worked with natural resource managers and experts to co-develop a spatially explicit state-and-transition simulation model of IAG dynamics in sagebrush landscapes that can be used to evaluate alternative management strategies. We evaluated our framework by contrasting two baseline scenarios in terms of their long-term effects on the sagebrush biome. We show that focusing management efforts on moderate to high IAG cover was effective at reducing full conversion to IAGs but failed to prevent widespread establishment of IAGs in core sagebrush areas, exposing them to increased risk of wildfire and wildlife habitat degradation. The results of our model help quantify the extent of the problem that IAGs pose to sagebrush ecosystems given current knowledge and management efforts. Our framework provides a platform to explore alternative management strategy outcomes and can help managers develop informed conservation plans with realistic expectations for return on investment of resources committed to sagebrush landscapes.

Arizona, California, Colorado, Idaho, Montana, Nev↗

USGS2022

New projections of 21st century climate and hydrology for Alaska and Hawaiʻi

In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and Hawaiʻi. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaiʻi); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For Hawaiʻi, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.

Alaska, Hawaii↗

USGS2018

Wave attenuation across a tidal marsh in San Francisco Bay

Wave attenuation is a central process in the mechanics of a healthy salt marsh. Understanding how wave attenuation varies with vegetation and hydrodynamic conditions informs models of other marsh processes that are a function of wave energy (e.g. sediment transport) and allows for the incorporation of marshes into coastal protection plans. Here, we examine the evolution of wave height across a tidal salt marsh in San Francisco Bay. Instruments were deployed along a cross-shore transect, starting on the mudflat and crossing through zones dominated by Spartina foliosa and Salicornia pacifica . This dataset is the first to quantify wave attenuation for these vegetation species, which are abundant in the intertidal zone of California estuaries. Measurements were collected in the summer and winter to assess seasonal variation in wave attenuation. Calculated drag coefficients of S. foliosa and S. pacifica were similar, indicating equal amounts of vegetation would lead to similar energy dissipation; however, S. pacifica has much greater biomass close to the bed (<20 cm) and retains biomass throughout the year, and therefore, it causes more total attenuation. S. foliosa dies back in the winter, and waves often grow across this section of the marsh. For both vegetation types, attenuation was greatest for low water depths, when the vegetation was emergent. For both seasons, attenuation rates across S. pacifica were the highest and were greater than published attenuation rates across similar ( Spartina alterniflora ) salt marshes for the comparable depths. These results can inform designs for marsh restorations and management plans in San Francisco Bay and other estuaries containing these species.

California↗

USGS2017

Achieving full connectivity of sites in the multiperiod reserve network design problem

The conservation reserve design problem is a challenge to solve because of the spatial and temporal nature of the problem, uncertainties in the decision process, and the possibility of alternative conservation actions for any given land parcel. Conservation agencies tasked with reserve design may benefit from a dynamic decision system that provides tactical guidance for short-term decision opportunities while maintaining focus on a long-term objective of assembling the best set of protected areas possible. To plan cost-effective conservation over time under time-varying action costs and budget, we propose a multi-period mixed integer programming model for the budget-constrained selection of fully connected sites. The objective is to maximize a summed conservation value over all network parcels at the end of the planning horizon. The originality of this work is in achieving full spatial connectivity of the selected sites during the schedule of conservation actions.

Computers & Operations Research↗

USGS2019

Mapping research on hydropower and sustainability in the Brazilian Amazon: Advances, gaps in knowledge and future directions

In the last twenty years, multiple large and small hydroelectric dams have begun to transform the Amazonian region, spawning a growing volume of academic research across diverse disciplinary and interdisciplinary fields. In this article, we offer a critical review of recent research related to hydropower and sustainability with a focus on the Brazilian Amazon. We revisit the sustainability concept to include the contribution of various knowledge fields and perspectives for understanding, managing and making decisions about social-ecological systems transformed by dams. We conducted a literature review in Web of Science of academic publications centered in the past 5 years (2014–2019), on diverse aspects of hydropower planning, construction, operation and monitoring in the Brazilian Amazon. We present results of a co-occurrence network analysis of publications, highlighting bridging fields, network disconnections, and opportunities for interdisciplinary research. Finally, we report recent advances in the understanding and management of social-ecological systems in Amazonian watersheds, including biophysical, socio-economic, governance and development processes linked to hydropower planning and implementation. This review identifies knowledge gaps and future research directions, highlighting opportunities for improved communication among scientists, practitioners, decision-makers, indigenous peoples and local communities.

Amazon↗

USGS2009

Impacts of stormwater runoff in the Southern California Bight: Relationships among plume constituents

The effects from two winter rain storms on the coastal ocean of the Southern California Bight were examined as part of the Bight '03 program during February 2004 and February-March 2005. The impacts of stormwater from fecal indicator bacteria, water column toxicity, and nutrients were evaluated for five major river discharges: the Santa Clara River, Ballona Creek, the San Pedro Shelf (including the Los Angeles, San Gabriel, and Santa Ana Rivers), the San Diego River, and the Tijuana River. Exceedances of bacterial standards were observed in most of the systems. However, the areas of impact were generally spatially limited, and contaminant concentrations decreased below California Ocean Plan standards typically within 2-3 days. The largest bacterial concentrations occurred in the Tijuana River system where exceedances of fecal indicator bacteria were noted well away from the river mouth. Maximum nitrate concentrations (~40 ??M) occurred in the San Pedro Shelf region near the mouth of the Los Angeles River. Based on the results of general linear models, individual sources of stormwater differ in both nutrient concentrations and the concentration and composition of fecal indicator bacteria. While nutrients appeared to decrease in plume waters due to simple mixing and dilution, the concentration of fecal indicator bacteria in plumes depends on more than loading and dilution rates. The relationships between contaminants (nutrients and fecal indicator bacteria) and plume indicators (salinity and total suspended solids) were not strong indicating the presence of other potentially important sources and/or sinks of both nutrients and fecal indicator bacteria. California Ocean Plan standards were often exceeded in waters containing greater than 10% stormwater (<28-30 salinity range). The median concentration dropped below the standard in the 32-33 salinity range (1-4% stormwater) for total coliforms and Enterococcus spp. and in the 28-30 salinity range (10-16% stormwater) for fecal coliforms. Nutrients showed a similar pattern with the highest median concentrations in water with greater than 10% stormwater. Relationships between colored dissolved organic matter (CDOM) and salinity and between total suspended solids and beam attenuation indicate that readily measurable, optically active variables can be used as proxies to provide at least a qualitative, if not quantitative, evaluation of the distribution of the dissolved, as well as the particulate, components of stormwater plumes. In this context, both CDOM absorption and the beam attenuation coefficient can be derived from satellite ocean color measurements of inherent optical properties suggesting that remote sensing of ocean color should be useful in mapping the spatial areas and durations of impacts from these contaminants. ?? 2009 Elsevier Ltd.

Continental Shelf Research↗

USGS2025

A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices

Wildlife conservation planning increasingly requires collaboration and integration of research from discrete studies spanning large geographic areas. Tracking datasets are essential for analyzing animal movements and species distributions in relation to environmental conditions and combining them can enable powerful analyses to further aid planning efforts. However, combining datasets necessitates addressing variation in study designs, tracking methodologies, location uncertainty, and data attributes. We outline a compilation pipeline to integrate ground-based and satellite-based telemetry tracking datasets, motivated from our work with greater sage-grouse ( Centrocercus urophasianus ), a highly imperiled species of western North America. Our objective was to create a database with a standardized set of attributes to facilitate filtering locations for spatial analyses. Our pipeline phases are: (1) dataset pre-processing, (2) formatting individual datasets to a common template, (3) dataset binding, (4) error checking, and (5) filtering. Our pipeline includes additional functionality to identify coordinates from recurrently visited locations (e.g., nest sites), which may be of special interest. The final compiled sage-grouse database included nearly 5 million locations collected from 53 datasets and over 19,000 birds tracked from 1980 to 2022, including over 11,000 nest locations. Our error checks flagged 3.9 % of locations as likely errors, predominantly collected from satellite-based telemetry transmissions. We demonstrate the ability of our pipeline to identify nest locations and flag erroneous locations by applying it to simulated tracking datasets. Overall, our workflow offers a transferable approach for researchers aiming to standardize wildlife telemetry datasets and conduct ecological analyses for both individual studies and large-scale collaborations.

California, Colorado, Idaho, Montana, Nevada, Nort↗

USGS2011

Development and assessment of a landscape-scale ecological threat index for the Lower Colorado River Basin

Anthropogenic disturbances impact freshwater biota but are rarely incorporated into conservation planning due to the difficulties in quantifying threats. There is currently no widely accepted method to quantify disturbances, and determining how to measure threats to upstream catchments using disturbance metrics can be time consuming and subjective. We compared four watershed-scale ecological threat indices for the Lower Colorado River Basin (LCRB) using landscape-level threats of land use (e.g., agricultural and urban lands), waterway development and diversions (e.g., number of canals, dams), and human development (e.g., road and railroads density, pollution sites). The LCRB is an ideal region to assess ecological threat indices because of the increasing need for conservation to ensure the persistence of native fishes in highly altered habitat. Each threat was measured for severity (i.e., level of influence on the upstream watershed) and frequency throughout each watershed; both severity and frequency were measured using two different methods. Severity values were based either on peer-reviewed literature and weighted in accordance to their published ecological impact, or assumed equal severity across stressors. Threat frequency was calculated according to either the presence/absence of each stressor, or on the relative density of each stressor in the watershed. Each measure of severity was combined with a measure of frequency, creating four ecological threat indices, and transformed to a 0–100 scale. Threat indices were highly correlated (slopes of 0.94–1.63; R 2 of 0.82–0.98), and were highest for watersheds close to urban centers, including Phoenix, Tucson, and Flagstaff, Arizona, and Las Vegas, Nevada. Road crossings and density appeared to be the most influential stressors in the index, but the removal of any individual stressor only changed the index by <5.1 units. Our results indicate that a simpler index with less subjectivity (i.e., presence/absence of a stressor in a watershed) provides similar results to the more subjective measure of threats (i.e., peer-reviewed threat severity). Because these threats have been linked to ecological health, the development of the index should be a useful tool to identify regions of greatest potential threat to aquatic biota and can aid in conservation planning for the Lower Colorado River Basin.

Ecological Indicators↗

USGS2021

Mapping climate change vulnerability of aquatic-riparian ecosystems using decision-relevant indicators

Climate change has and is projected to continue to alter historical regimes of temperature, precipitation, and hydrology. To assess the vulnerability of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with land managers to develop a climate change vulnerability map for the midwestern United States with a focus on riparian systems. The map is intended for use by regional administrators to help them work across various program areas (e.g. fisheries, endangered species) to prioritize locations needing support for adaptation planning. The tool can also be utilized locally by managers to better understand the effects that projected climate scenarios have on the hydrology of management units as they develop adaptation strategies. The vulnerability map is watershed-based (360 watershed units within the region) and combines 15 climate change indicators that were selected by U.S. Fish and Wildlife Service natural resource managers based upon known and anticipated effects to species and habitats. The projected change in each of these indicators from the historical period (1986–2005) to the future period (2040–2059) was aggregated into a composite score for each watershed. Landscape-scale metrics reflective of a watershed’s adaptive capacity were combined with the climate change indicators to produce a vulnerability score. We found sub-regional variation in vulnerability to climate change with the greatest vulnerability in Iowa, central Illinois, and northwest Ohio. Greater vulnerability was seen in the higher greenhouse gas concentration scenario, Representative Concentration Pathway (RCP) 8.5 compared to the lower greenhouse gas concentration scenario RCP 4.5, when looking at the mean of the five downscaled climate models used in this study. By quantifying and mapping climate change vulnerability, natural resource managers can better understand the degree of vulnerability for individual watersheds and identify areas of prioritization in regional and local planning efforts.

Iowa, Illinois, Indiana, Michigan, Minnesota, Miss↗

USGS2007

Using simulated historical time series to prioritize fuel treatments on landscapes across the United States: The LANDFIRE prototype project

Canopy and surface fuels in many fire-prone forests of the United States have increased over the last 70 years as a result of modern fire exclusion policies, grazing, and other land management activities. The Healthy Forest Restoration Act and National Fire Plan establish a national commitment to reduce fire hazard and restore fire-adapted ecosystems across the USA. The primary index used to prioritize treatment areas across the nation is Fire Regime Condition Class (FRCC) computed as departures of current conditions from the historical fire and landscape conditions. This paper describes a process that uses an extensive set of ecological models to map FRCC from a departure statistic computed from simulated time series of historical landscape composition. This mapping process uses a data-driven, biophysical approach where georeferenced field data, biogeochemical simulation models, and spatial data libraries are integrated using spatial statistical modeling to map environmental gradients that are then used to predict vegetation and fuels characteristics over space. These characteristics are then fed into a landscape fire and succession simulation model to simulate a time series of historical landscape compositions that are then compared to the composition of current landscapes to compute departure, and the FRCC values. Intermediate products from this process are then used to create ancillary vegetation, fuels, and fire regime layers that are useful in the eventual planning and implementation of fuel and restoration treatments at local scales. The complex integration of varied ecological models at different scales is described and problems encountered during the implementation of this process in the LANDFIRE prototype project are addressed.

Ecological Modelling↗

USGS2015

Linking resource selection and mortality modeling for population estimation of mountain lions in Montana

To be most effective, the scale of wildlife management practices should match the range of a particular species’ movements. For this reason, combined with our inability to rigorously or regularly census mountain lion populations, several authors have suggested that mountain lions be managed in a source-sink or metapopulation framework. We used a combination of resource selection functions, mortality estimation, and dispersal modeling to estimate cougar population levels in Montana statewide and potential population level effects of planned harvest levels. Between 1980 and 2012, 236 independent mountain lions were collared and monitored for research in Montana. From these data we used 18,695 GPS locations collected during winter from 85 animals to develop a resource selection function (RSF), and 11,726 VHF and GPS locations from 142 animals along with the locations of 6343 mountain lions harvested from 1988–2011 to validate the RSF model. Our RSF model validated well in all portions of the State, although it appeared to perform better in Montana Fish, Wildlife and Parks (MFWP) Regions 1, 2, 4 and 6, than in Regions 3, 5, and 7. Our mean RSF based population estimate for the total population (kittens, juveniles, and adults) of mountain lions in Montana in 2005 was 3926, with almost 25% of the entire population in MFWP Region 1. Estimates based on a high and low reference population estimates produce a possible range of 2784 to 5156 mountain lions statewide. Based on a range of possible survival rates we estimated the mountain lion population in Montana to be stable to slightly increasing between 2005 and 2010 with lambda ranging from 0.999 (SD = 0.05) to 1.02 (SD = 0.03). We believe these population growth rates to be a conservative estimate of true population growth. Our model suggests that proposed changes to female harvest quotas for 2013–2015 will result in an annual statewide population decline of 3% and shows that, due to reduced dispersal, changes to harvest in one management unit may affect population growth in neighboring units where smaller or even no changes were made. Uncertainty regarding dispersal levels and initial population density may have a significant effect on predictions at a management unit scale (i.e. 2000 km 2 ), while at a regional scale (i.e. 50,000 km 2 ) large differences in initial population density result in relatively small changes in population growth rate, and uncertainty about dispersal may not be as influential. Doubling the presumed initial density from a low estimation of 2.19 total animals per 100 km 2 resulted in a difference in annual population growth rate of only 2.6% statewide when compared to high density of 4.04 total animals per 100 km 2 (low initial population estimate λ = 0.99, while high initial population estimate λ = 1.03). We suggest modeling tools such as this may be useful in harvest planning at a regional and statewide level.

Ecological Modelling↗

USGS2017

Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production

There remains much debate regarding the perceived tradeoffs of using freshwater and sediment diversions for coastal restoration in terms of balancing the need for wetland restoration versus preserving eastern oyster ( Crassostrea virginica ) production. Further complicating the issue, climate change-induced sea-level rise (SLR) and land subsidence are also expected to affect estuarine water quality. In this study, we developed a process-based numerical modeling system that couples hydrodynamic, water quality, and oyster population dynamics. We selected Breton Sound Estuary (BSE) (∼2740 km 2 ) in the eastern Mississippi River Deltaic Plain since it is home to several of the largest public oyster seed grounds and private leases for the Gulf coast. The coupled oyster population model was calibrated and validated against field observed oyster growth data. We predicted the responses of oyster population in BSE to small- (142 m 3 s −1 ) and large-scale (7080 m 3 s −1 ) river diversions at the Caernarvon Freshwater Diversion structure planned in the 2012 Coastal Master Plan (Louisiana) under low (0.38 m) and high (1.44 m) relative sea-level rise (RSLR = eustatic SLR + subsidence) compared to a baseline condition (Year 2009). Model results showed that the large-scale diversion had a stronger negative impact on oyster population dynamics via freshening of the entire estuary, resulting in reduced oyster growth rate and production than RSLR. Under the large-scale diversion, areas with optimal oyster growth rates (>15 mg ash-free dry weight (AFDW) oyster −1 wk −1 ) and production (>500 g AFDW m −2 yr −1 ) would shift seaward to the southeastern edge of the estuary, turning the estuary into a very low oyster production system. RSLR however played a greater role than the small-scale diversion on the magnitude and spatial pattern of oyster growth rate and production. RSLR would result in an overall estuary-wide decrease in oyster growth rate and production as a consequence of decreased salinities in the middle and lower estuary because rising sea level likely causes increased stage and overbank flow downstream along the lower Mississippi River.

Louisiana↗

USGS2021

The Chesapeake Bay program modeling system: Overview and recommendations for future development

The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.

Chesapeake Bay estuary and watershed↗