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At least 1,603 records · Page 89Linked to original sources
USGS2023

The scale-dependent role of submerged macrophytes as drift-feeding lotic fish habitat

Although submerged macrophyte (hereafter, “macrophyte”) communities are globally prevalent in low-gradient rivers, the net reach-scale effect of macrophytes on drift-feeding fish microhabitat preference is poorly understood. We used snorkeling and bioenergetics to study fish habitat selection for rainbow trout ( Oncorhynchus mykiss ) in the Henrys Fork, ID, USA, investigating microhabitat preference across a reach-scale gradient of macrophyte growth. Fish preferred microhabitats with deep water, low velocity, and low macrophyte coverage. Preferences for microhabitats with higher net rate of energy intake (NREI) were modulated by reach-scale macrophyte coverage, higher coverage increasing preferences for higher NREI. Macrophyte coverage was a weak positive predictor for depth and NREI, and a weak negative predictor for water velocity and median substrate. Our results suggest trade-offs between fish predation risk and bioenergetic food intake, with macrophytes modulating these trade-offs across scales by affecting reach-scale geomorphology, bioenergetics, and predation risk. As such, this study highlights the important and dynamic role that macrophytes can play in fish population dynamics in rivers, with important implications for management decisions.

Idaho↗
USGS2024

Quantifying uncertainty when extrapolating the relationship between snorkel counts and mark-recapture estimates of juvenile salmonids

Snorkel surveys are frequently used to monitor stream-dwelling fish. Inferring local abundance from snorkel surveys is complicated by two primary factors: variable fish detection probabilities and the relative abundance of fish in habitat types below the recommended minimum depth for snorkeling. We examine these factors across three salmonid species ( Oncorhynchus spp . ), 4 years, and 113 location-years in Oregon coastal streams. We calibrate snorkel counts to mark-recapture estimates and develop mathematically explicit expressions that convert a new snorkel count into a probability density of abundance for streams containing mixed habitat types that were and were not snorkeled. Snorkelers detected 63%, 47%, and 39% of juvenile coho salmon ( Oncorhynchus kitsutch ), steelhead trout ( Oncorhynchus mykiss ), and cutthroat trout ( Oncorhynchus clarkii clarkia ) estimated by mark-recapture, respectively, but uncertainty within and among sampling units was high. Further, analytics developed here can be used to infer abundance and uncertainty for habitat types that were not snorkeled. Our quantification of uncertainty arising from using snorkel counts as a proxy for abundance will help managers balance biological risks with available resources.

Oregon↗
USGS2023

Marshes and mangroves as nature-based coastal storm buffers

Tidal marshes and mangroves are increasingly valued for nature-based mitigation of coastal storm impacts, such as flooding and shoreline erosion hazards, which are growing due to global change. As this review highlights, however, hazard mitigation by tidal wetlands is limited to certain conditions, and not all hazards are equally reduced. Tidal wetlands are effective in attenuating short-period storm-induced waves, but long-period storm surges, which elevate sea levels up to several meters for up to more than a day, are attenuated less effectively, or in some cases not at all, depending on storm conditions, wetland properties, and larger-scale coastal landscape geometry. Wetlands often limit erosion, but storm damage to vegetation (especially mangrove trees) can be substantial, and recovery may take several years. Longer-term wetland persistence can be compromised when combined with other stressors, such as climate change and human disturbances. Due to these uncertainties, nature-based coastal defense projects need to adopt adaptive management strategies.

Annual Review of Marine Science↗
USGS2012

Evaluating a fish monitoring protocol using state-space hierarchical models

Using data collected from three river reaches in Montana, we evaluated our ability to detect population trends and predict fish future fish abundance. Data were collected as part of a long-term monitoring program conducted by Montana Fish, Wildlife and Parks to primarily estimate rainbow (Oncorhynchus mykiss) and brown trout (Salmo trutta) abundance in numerous rivers across Montana. We used a hierarchical Bayesian mark-recapture model to estimate fish abundance over time in each of the three river reaches. We then fit a state-space Gompertz model to estimate current trends and future fish populations. Density dependent effects were detected in 1 of the 6 fish populations. Predictions of future fish populations displayed wide credible intervals. Our simulations indicated that given the observed variation in the abundance estimates, the probability of detecting a 30% decline in fish populations over a five-year period was less than 50%. We recommend a monitoring program that is closely tied to management objectives and reflects the precision necessary to make informed management decisions.

Montana↗
USGS2001

U.S. Geological Survey Information Sources

As the Nation's largest water, earth, and biological science and civilian mapping agency, the U.S. Geological Survey (USGS) works in cooperation with more than 2,000 organizations across the country to provide reliable, impartial scientific information to resource managers, planners, and other customers. This information is gathered in every State by USGS scientists to minimize the loss of life and property from natural disasters, to contribute to the conservation and the sound economic and physical development of the Nation's natural resources, and to enhance the quality of life by monitoring water, biological, energy, and mineral resources

Fact Sheet↗
USGS2008

Impacts of Low-Flow and Stream-Temperature Changes on Endangered Atlantic Salmon - Current Research

Recent climate studies in New England and the northeastern United States have shown evidence of physical changes over time, including trends toward earlier snowmelt runoff, decreasing river ice, and increasing spring water temperatures. A U.S. Geological Survey (USGS) study funded by the National Global Warming and Wildlife Science Center will be investigating changes in summer low streamflows and stream temperatures and the potential effects of those changes on endangered Atlantic salmon populations. The study also will evaluate management options that would be most likely to mitigate the effects of any changes in streamflow and temperature.

Fact Sheet↗
USGS2024

RE-ARMing salt marshes: A resilience-experimentalist approach to prescribed fire and bird conservation in high marshes of the Gulf of Mexico

Uncertainty, complexity, and dynamic changes present challenges for conservation and natural resource management. Evidence-based approaches grounded in reliable information and rigorous analysis can enhance the navigation of the uncertainties and trade-offs inherent in conservation problems. This study highlights the importance of collaborative efforts and evidence-based decision-making, specifically implementing the Resilience-Experimentalist school of adaptive management (RE-ARM), which emphasizes stakeholder involvement, shared understanding, and experimentation. Our goal was to develop an adaptive management framework to reduce the uncertainty around the use of prescribed fire to manage the habitat for eastern black rails ( Laterallus jamaicensis jamaicensis ) and mottled ducks ( Anas fulvigula ) in saltmarshes of the Gulf of Mexico. Supported by discussions at a series of workshops, we used a value of information analysis to select a fire management hypothesis to test, developed an influence diagram to represent the system under fire management, used the influence diagram to develop a Bayesian decision network (BDN), and conducted a power analysis to guide management experiments and monitoring. Value of information analysis identified fire return interval as the critical uncertainty. Our BDN provided valuable insight into how managers believe prescribed fire influences vegetation characteristics and how vegetation influences both eastern black rail occupancy and mottled duck abundance. The results of the power analysis indicated that a standard occupancy modeling framework was more useful to compare 2- and 5-year fire return intervals for black rails than two alternative designs (removal and conditional). Our BDN can be used to predict the probability of achieving the desirable vegetative response to increase the occupancy probability of black rails and abundance of mottled ducks, and monitoring data can be used to update the BDN (learn) and improve best management practices for prescribed burns (adapt). Linking the value of information, BDNs, and power analysis enhances our understanding of the system, improves management decision-making, and builds trust among scientists, interested parties, and decision-makers. This approach lays the groundwork for knowledge co-production and adaptive management.

Frontiers in Conservation Science↗
USGS2010

Developing an ecosystem services online decision support tool to assess the impacts of climate change and urban growth in the Santa Cruz watershed: Where we live, work, and play

Using respective strengths of the biological, physical, and social sciences, we are developing an online decision support tool, the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), to help promote the use of information relevant to water allocation and land management in a binational watershed along the U.S.-Mexico border. The SCWEPM will include an ES valuation system within a suite of linked regional driver-response models and will use a multicriteria scenario-evaluation framework that builds on GIS analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to climate patterns, regional water budgets, and regional LULC change in the SCW.

Arizona↗
USGS2015

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine ( Pinus albicaulis ). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae ), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

AIMS Environmental Science↗
USGS2023

Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA

Probabilistic models to inform landslide early warning systems often rely on rainfall totals observed during past events with landslides. However, these models are generally developed for broad regions using large catalogs, with dozens, hundreds, or even thousands of landslide occurrences. This study evaluates strategies for training landslide forecasting models with a scanty record of landslide-triggering events, which is a typical limitation in remote, sparsely populated regions. We evaluate 136 statistical models trained on a precipitation dataset with five landslide-triggering precipitation events recorded near Sitka, Alaska, USA, as well as > 6000 d of non-triggering rainfall (2002–2020). We also conduct extensive statistical evaluation for three primary purposes: (1) to select the best-fitting models, (2) to evaluate performance of the preferred models, and (3) to select and evaluate warning thresholds. We use Akaike, Bayesian, and leave-one-out information criteria to compare the 136 models, which are trained on different cumulative precipitation variables at time intervals ranging from 1 h to 2 weeks, using both frequentist and Bayesian methods to estimate the daily probability and intensity of potential landslide occurrence (logistic regression and Poisson regression). We evaluate the best-fit models using leave-one-out validation as well as by testing a subset of the data. Despite this sparse landslide inventory, we find that probabilistic models can effectively distinguish days with landslides from days without slide activity. Our statistical analyses show that 3 h precipitation totals are the best predictor of elevated landslide hazard, and adding antecedent precipitation (days to weeks) did not improve model performance. This relatively short timescale of precipitation combined with the limited role of antecedent conditions likely reflects the rapid draining of porous colluvial soils on the very steep hillslopes around Sitka. Although frequentist and Bayesian inferences produce similar estimates of landslide hazard, they do have different implications for use and interpretation: frequentist models are familiar and easy to implement, but Bayesian models capture the rare-events problem more explicitly and allow for better understanding of parameter uncertainty given the available data. We use the resulting estimates of daily landslide probability to establish two decision boundaries that define three levels of warning. With these decision boundaries, the frequentist logistic regression model incorporates National Weather Service quantitative precipitation forecasts into a real-time landslide early warning “dashboard” system ( https://sitkalandslide.org/ , last access: 9 October 2023). This dashboard provides accessible and data-driven situational awareness for community members and emergency managers.

Alaska↗
USGS2004

Interannual variability in aboveground tree growth in Stehekin River watershed, North Cascade Range, Washington

Many forests in the Pacific Northwest region of North America are both highly productive and sensitive to climate. The combination of productivity and sensitivity makes forests vulnerable to changes in future climate and most likely to feed back to the regional carbon cycle. We reconstructed basal area increment (BAI) for 20 yr using tree-ring increments and diameter to identify species-specific responses of 14 forested vegetation types in the Stehekin River watershed in the North Cascade Range, to interannual climatic variability. Mean basal area increment (MBAI) for the 20-yr period is low when the standard error is low, but as MBAI increases, the standard error (SE) is more variable. Growth at sites with both low SE and MBAI may be related to climatic variables, however, some forest types dominated by Douglas-fir and mountain hemlock are both productive and responsive to climatic variability. Many forests in the Pacific Northwest are dominated by Douglas-fir, a commercially important timber species, and as a result, may play a major role in the regional carbon balance. Douglas-fir and mountain hemlock forests in the eastern portion of the North Cascades should be carefully monitored and managed in the context of both changing climatic conditions and regional carbon budgets.

Northwest Science↗
USGS2014

Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008

Ecosystems undergo dynamic changes owing to species invasions, fisheries management decisions, landscape modifications, and nutrient inputs. At Lake Michigan, new invaders (e.g., dreissenid mussels ( Dreissena spp.), spiny water flea ( Bythotrephes longimanus ), round goby ( Neogobius melanostomus )) have proliferated and altered energy transfer pathways, while nutrient concentrations and stocking rates to support fisheries have changed. We developed an ecosystem model to describe food web structure in 1987 and ran simulations through 2008 to evaluate changes in biomass of functional groups, predator consumption, and effects of recently invading species. Keystone functional groups from 1987 were identified as Mysis , burbot ( Lota lota ), phytoplankton, alewife ( Alosa pseudoharengus ), nonpredatory cladocerans, and Chinook salmon (Oncorhynchus tshawytscha ). Simulations predicted biomass reductions across all trophic levels and predicted biomasses fit observed trends for most functional groups. The effects of invasive species (e.g., dreissenid grazing) increased across simulation years, but were difficult to disentangle from other changes (e.g., declining offshore nutrient concentrations). In total, our model effectively represented recent changes to the Lake Michigan ecosystem and provides an ecosystem-based tool for exploring future resource management scenarios.

Lake Michigan↗
USGS2021

Angler-caught salmonid diets illustrate Lake Ontario Alewife population and predator-prey dynamics

Lake Ontario fisheries decision makers use information about the status and trajectory of prey fish populations, such as alewife, for salmonid sport fish management. In 2020, the April bottom trawl survey, typically used to assess alewife, was canceled the day after it began due to Coronavirus health concerns. This prompted NYSDEC and USGS science teams to initiate a diet study using angler-collected samples to provide information on the alewife population in 2020. Over 800 salmonid diets were collected from across Lake Ontario southern shore from May through September. Past diet studies illustrated alewife size distribution in piscivore diets overlapped April trawl survey-based distributions (proportion overlap = 0.51- 0.81, n = 5). In 2020 few age-1 sized alewife (40 - 140 mm) were observed in salmonid diets, suggesting that 2019 alewife reproduction was below average. Given that alewife reproductive success from 2017 and 2018 were also below average, the 2021 Lake Ontario adult alewife population will likely be at a record low for the 43-year time series. For all years and piscivore species, adult-sized Alewife ( total length > 140 mm) were the predominate size consumed by piscivores greater than 400 mm (~ 16 inches). Sizes of alewife in the diet were positively related to piscivore size. Diet composition, by dry weight, indicated alewife remain the dominant prey supporting salmonids and diets were generally similar to trawl-based estimates of prey fish community composition. The most notable deviation from this pattern included round goby, which comprised substantial portions of brown trout and lake trout diets in 2013 and 2020. These results inform decision making related to Lake Ontario salmonid stocking and predator prey dynamics and highlight the utility of angler-caught piscivore diets for indicating alewife population status.

Lake Ontario↗
USGS2022

Natives bite back! Are Burmese pythons beginning to encounter the resilience of the Everglades Ecosystem?

Burmese pythons ( Python bivittatus ) is a large, invasive reptile known in Florida for its devastating impacts on native species in the Greater Everglades Ecosystem. Several organizations and individuals are taking action to research and/or remove the snakes, including the U.S. Geological Survey (USGS). Since 2018, scientists from USGS’s Fort Collins Science Center have been working closely with the National Park Service (NPS) in Big Cypress National Preserve to use radiotelemetry and track Burmese pythons for various ecological research project and management (enabled by invaluable partnerships with the University of Florida and Zoo Miami). Over those years, we have encountered some incidental, but intriguing findings.

Florida↗
USGS2005

Water availability for the Western United States--Key scientific challenges

In the Western United States, the availability of water has become a serious concern for many communities and rural areas. Near population centers, surface-water supplies are fully appropriated, and many communities are dependent upon ground water drawn from storage, which is an unsustainable strategy. Water of acceptable quality is increasingly hard to find because local sources are allocated to prior uses, depleted by overpumping, or diminished by drought stress. Some of the inherent characteristics of the West add complexity to the task of securing water supplies. The Western States, including the arid Southwest, have the most rapid population growth in the United States. The climate varies widely in the West, but it is best known for its low precipitation, aridity, and drought. There is evidence that the climate is warming, which will have consequences for Western water supplies, such as increased minimum streamflow and earlier snowmelt events in snow-dominated basins. The potential for departures from average climatic conditions threatens to disrupt society and local to regional economies. The appropriative rights doctrine governs the management of water in most Western States, although some aspects of the riparian doctrine are being incorporated. The 'use it or lose it' provisions of Western water law discourage conservation and make the reallocation of water to instream environmental uses more difficult. The hydrologic sciences have defined the interconnectedness of ground water and surface water, yet these resources are still administered separately by most States. The definition of water availability has been expanded to include sustaining riparian ecosystems and individual endangered species, which are disproportionately represented in the Western States. Federal reserved rights, common in the West because of the large amount of Federal land, exist with quite senior priority dates whether or not water is currently being used. A major challenge for water users in the West is that these reserved rights may supersede other existing users. The minimum amount of water required, however, to sustain native peoples, a riparian system, or an endangered species eventually will need to be known in order to manage the available water supply. Periodic inventory and assessment of the amounts and trends of water available in surface water and ground water are needed to support water management. There is a widespread perception that the amount of available water is diminishing with time. This and other perceptions about water availability should be replaced by objective data and analysis. Some data are presented here for the major Western rivers that show that flows are not decreasing in most streams and rivers in the West. Systematic information is lacking to make broad assessments of ground-water availability, but available data for specific aquifers indicate that these aquifers are being depleted, especially near population centers. The complexity added to the issue of Western water availability by these and other factors gives rise to a significant role of science. Science has played a role in support of Western water development from the beginning, and the role has evolved and changed over time as society's values have changed. In this report, the role of science is discussed in three phases: (1) development and construction, (2) consequences and environmental awareness, and (3) sustainability. The development and construction phase includes some historical accounting of water development in the West and shows how some precedents set in those early days are still applied today.

western United States↗
USGS2009

Natural resource assessment: an approach to science based planning in national parks

We conducted a natural resource assessment at two national parks, New River Gorge National River and Shenandoah National Park, to help meet the goals of the Natural Resource Challenge-a program to help strengthen natural resource management at national parks. We met this challenge by synthesizing and interpreting natural resource information for planning purposes and we identified information gaps and natural significance of resources. We identified a variety of natural resources at both parks as being globally and/or nationally significant, including large expanses of unfragmented, mixed-mesophytic forests that qualify for wilderness protection, rare plant communities, diverse assemblages of neotropical migratory birds and salamanders, and outstanding aquatic recreational resources. In addition, these parks function, in part, as ecological reserves for plants in and wildlife. With these significant natural resources in mind, we also developed a suite of natural resource management recommendations in light of increasing threats from within and outside park boundaries. We hope that our approach can provide a blueprint for natural resource conservation at publicly owned lands.

Environmental Management↗
USGS2013

MODIS phenology image service ArcMap toolbox

Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales. A cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by implementing long-term conservation plans). In either case, it is important to first grasp the magnitude of natural variation so that it is not confused with actual trends. This work used existing and freely available remote sensing data, specifically the NASA-funded 250-meter (m) spatial resolution land-surface phenology product for North America. This product is calculated from an annual record of vegetation health observed by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The land-surface phenology product is, in essence, a method to summarize all the observations throughout a year into a few key, ecologically relevant “metrics”.

Open-File Report↗