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At least 217 records · Page 12Linked to original sources
USGS2014

Land-margin ecosystem hydrologic data for the coastal Everglades, Florida, water years 1996-2012

Mangrove forests and salt marshes dominate the landscape of the coastal Everglades (Odum and McIvor, 1990). However, the ecological effects from potential sea-level rise and increased water flows from planned freshwater Everglades restoration on these coastal systems are poorly understood. The National Park Service (NPS) proposed the South Florida Global Climate Change Project (SOFL-GCC) in 1990 to evaluate climate change and the effect from rising sea levels on the coastal Everglades, particularly at the marsh/mangrove interface or ecotone (Soukup and others, 1990). A primary objective of SOFL-GCC project was to monitor and synthesize the hydrodynamics of the coastal Everglades from the upstream freshwater marsh to the downstream estuary mangrove. Two related hypotheses were set forward (Nuttle and Cosby, 1993): 1. There exists hydrologic conditions (tide, local rainfall, and upstream water deliveries), which characterize the location of the marsh/mangrove ecotone along the marine and terrestrial hydrologic gradient; and 2. The marsh/mangrove ecotone is sensitive to fluctuations in sea level and freshwater inflow from inland areas. Hydrologic monitoring of the SOFL-GCC network began in 1995 after startup delays from Hurricane Andrew (August 1992) and organizational transfers from the NPS to the National Biological Survey (October 1993) and the merger with the U.S. Geological Survey (USGS) Biological Research Division in 1996 (Smith, 2004). As the SOFL-GCC project progressed, concern by environmental scientists and land managers over how the diversion of water from Everglades National Park would affect the restoration of the greater Everglades ecosystem. Everglades restoration scenarios were based on hydrodynamic models, none of which included the coastal zone (Fennema and others, 1994). Modeling efforts were expanded to include the Everglades coastal zone (Schaffranek and others, 2001) with SOFL-GCC hydrologic data assisting the ecological modeling needs. In 2002, as a response for a more interdisciplinary science approach to understanding the coastal Everglades ecological system, the SOFL-GCC hydrology project was integrated into the “Dynamics of Land-Margin Ecosystems: Historical Change, Hydrology, Vegetation, Sediment, and Climate” study (Smith and others, 2002). Data from the ongoing study has been useful in providing an empirical hydrologic baseline for the greater Everglades ecosystem restoration science and management needs. The hydrology network consisted of 13 hydrologic gaging stations installed in the southwestern coastal region of Everglades National Park along three transects: Shark River (Shark or SH) transect, Lostmans River (Lostmans or LO) transect, and Chatham River (Chatham or CH) transect (fig. 1). There were five paired surface-water/groundwater gaging stations on the Shark transect (SH1, SH2, SH3, SH4, and SH5) and one stage gaging station (BSC) in the Big Sable Creek; four paired surface-water/groundwater gaging stations on the Lostmans transect (LO1, LO2, LO3, and LO4); and three paired surface-water/groundwater gaging stations on the Chatham transect (CH1, CH2, and CH3). Both surface-water and groundwater levels, salinities, and temperatures were monitored at the paired gaging stations. Rainfall was recorded at marsh and open canopy gaging stations. This report details the study introduction, method, and description of data collected, which are accessible through the final instantaneous hydrologic dataset stored in the USGS South Florida Information Access (SOFIA) South Florida Hydrology Database website, http://sofia.usgs.gov/exchange/sfl_hydro_data/location.html#brdlandmargin .

Florida↗
USGS2017

Science advancements key to increasing management value of life stage monitoring networks for endangered Sacramento River winter-run Chinook salmon in California

A robust monitoring network that provides quantitative information about the status of imperiled species at key life stages and geographic locations over time is fundamental for sustainable management of fisheries resources. For anadromous species, management actions in one geographic domain can substantially affect abundance of subsequent life stages that span broad geographic regions. Quantitative metrics (e.g., abundance, movement, survival, life history diversity, and condition) at multiple life stages are needed to inform how management actions (e.g., hatcheries, harvest, hydrology, and habitat restoration) influence salmon population dynamics. The existing monitoring network for endangered Sacramento River winterrun Chinook Salmon (SRWRC, Oncorhynchus tshawytscha) in California’s Central Valley was compared to conceptual models developed for each life stage and geographic region of the life cycle to identify relevant SRWRC metrics. We concluded that the current monitoring network was insufficient to diagnose when (life stage) and where (geographic domain) chronic or episodic reductions in SRWRC cohorts occur, precluding within- and among-year comparisons. The strongest quantitative data exist in the Upper Sacramento River, where abundance estimates are generated for adult spawners and emigrating juveniles. However, once SRWRC leave the upper river, our knowledge of their identity, abundance, and condition diminishes, despite the juvenile monitoring enterprise. We identified six system-wide recommended actions to strengthen the value of data generated from the existing monitoring network to assess resource management actions: (1) incorporate genetic run identification; (2) develop juvenile abundance estimates; (3) collect data for life history diversity metrics at multiple life stages; (4) expand and enhance real-time fish survival and movement monitoring; (5) collect fish condition data; and (6) provide timely public access to monitoring data in open data formats. To illustrate how updated technologies can enhance the existing monitoring to provide quantitative data on SRWRC, we provide examples of how each recommendation can address specific management issues.

California↗
USGS2017

Nutrients, phytoplankton, zooplankton, and macrobenthos

Lower trophic levels support the prey fish on which most sport fish depend. Therefore, understanding the production potential of lower trophic levels is integral to the management of Lake Ontario’s fishery resources. Lower trophic-level productivity differs among offshore and nearshore waters. In the offshore, there is concern about the ability of the lake to support Alewife (Table 1) production due to a perceived decline in productivity of phytoplankton and zooplankton whereas, in the nearshore, there is a concern about excessive attached algal production (e.g., Cladophora) associated with higher nutrient concentrations—the oligotrophication of the offshore and the eutrophication of the nearshore (Mills et al. 2003; Holeck et al. 2008; Dove 2009; Koops et al. 2015; Stewart et al. 2016). Even though the collapse of the Alewife population in Lake Huron in 2003 (and the associated decline in the Chinook Salmon fishery) may have been precipitated by a cold winter (Dunlop and Riley 2013), Alewife had not returned to high abundances in Lake Huron as of 2014 (Roseman et al. 2015). Failure of the Alewife population to recover from collapse has been attributed to declines in lower trophic-level production (Barbiero et al. 2011; Bunnell et al. 2014; but see He et al. 2015). In Lake Michigan, concerns of a similar Alewife collapse led to a decrease in the number of Chinook Salmon stocked. If lower trophic-level production declines in Lake Ontario, a similar management action could be considered. On the other hand, in Lake Erie, which supplies most of the water in Lake Ontario, eutrophication is increasing and so are harmful algal blooms. Thus, there is also a concern that nutrient levels and algal blooms could increase in Lake Ontario, especially in the nearshore. Solutions to the two processes of concern—eutrophication in the nearshore and oligotrophication in the offshore—may be mutually exclusive. In either circumstance, fisheries management needs information on the productivity of lower trophic levels in Lake Ontario. In this chapter, we review the status of lower trophic levels in Lake Ontario with special attention to the current (2008-2013) and previous (2003-2007) reporting periods. During the two reporting periods, three whole-lake surveys of lower trophic levels were conducted: the Lower Trophic Level Assessment (LOLA) in 2003 and 2008 (Makarewicz and Howell 2012; Munawar et al. 2015b) and the Cooperative Science and Management Initiative (CSMI) in 2013. Analyses of the CSMI data are ongoing. In addition to the three one-year sources of information on lower trophic levels, several multi-year sources of information are available, including data from the surveillance program conducted since 1965 by Environment Canada (EC) (Dove 2009), monitoring conducted since 1980 by the U.S. Environmental Protection Agency’s (EPA) Great Lakes National Program Office (GLNPO) (Barbiero et al. 2014; Reavie et al. 2014), sampling for a Bioindex Program at two stations, one offshore and one in the Eastern Basin, assessments of Mysis diluviana (formerly Mysis relicta) conducted since 1980 by Fisheries and Oceans Canada (Johannsson et al. 1998, 2011) and the Ontario Ministry of Natural Resources and Forestry (OMNRF), and monitoring conducted since 1995 by the Biomonitoring Program (BMP) on the New York side of the lake (Holeck et al. 2015b). The BMP is a collaboration of the New York State Department of Environmental Conservation (DEC), U.S. Fish and Wildlife Service, U.S. Geological Survey (USGS), and Cornell University.

Special Publication↗
USGS2018

Batrachochytrium salamandriovrans (Bsal) in Appalachia—Using scenario building to proactively prepare for a wildlife disease outbreak caused by an invasive amphibian chytrid fungus

Batrachochytrium salamandrivorans ( Bsal ), a pathogenic chytrid fungus, is nonnative to the United States and poses a disease threat to vulnerable amphibian hosts. The Bsal fungus may lead to increases in threatened, endangered, and sensitive status listings at State, Tribal, and Federal levels, resulting in financial costs associated with implementing the Endangered Species Act of 1973. The United States is a global biodiversity hotspot for salamanders, an order of amphibians that is particularly vulnerable to developing a disease called chytridiomycosis when exposed to Bsal . Published Bsal risk assessments for North America have suggested that salamanders within the Appalachian region of the United States are at a high risk. In May 2017, a workshop was facilitated by the Department of the Interior’s Strategic Sciences Group. During the workshop, a discussion-based incident-response exercise focused on a hypothetical Bsal disease outbreak in Appalachia was led by U.S. Geological Survey staff members. Participants included representatives of the Eastern Band of the Cherokee Indians, U.S. Fish and Wildlife Service, National Park Service, Appalachian Landscape Conservation Cooperative, Tennessee Wildlife Resources Agency, and U.S. Department of Agriculture’s U.S. Forest Service. Scenario building was used to brainstorm cascading consequences (social, economic, and ecological) of a Bsal disease outbreak in the Appalachian region. This report highlights the management and science actions that could be undertaken to ensure an effective, rapid response to a Bsal introduction into the United States.

Open-File Report↗
USGS2023

CreelCat, a Catalog of United States Inland Creel and Angler Survey Data

The United States Inland Creel and Angler Survey Catalog (CreelCat) contains a national compilation of angler and creel survey data collected by natural resource management agencies across the United States (including Washington, D.C. and Puerto Rico). These surveys are used to help inform the management of recreational fisheries, by collecting information about anglers including what they are catching and harvesting, the amount of effort they expend, their angling preferences, and demographic information. As of May 1, 2023, CreelCat houses over 14,729 surveys from 33 states, Puerto Rico, and Washington, D.C., comprising 235 data fields across 8 tables. These tables contain 235,015 records of fish catch and harvest metrics, 27,250 angler preference metrics, 14,729 records of survey characteristics, 13,576 records of effort metrics, and 409 records of angler demographics. Though individual creel surveys are often deployed to meet local science and management objectives, creel data aggregated across jurisdictions has the potential to address larger scale research and management needs.

Scientific Data↗
USGS2018

Navigating the field of decision analysis

Managers, policy makers, and decision makers with responsibility for environmental decisions have an extraordinarily difficult job. The systems they manage are complex (coupled human-natural systems), with many dimensions and complicated dynamics. Our knowledge of how those systems respond to management actions is often limited, so many of the decisions have to be made in the face of uncertainty. The field of decision analysis provides a comprehensive set of tools for structuring, analyzing, and making decisions. Arising initially as a way to understand and manage risk, the field has expanded in the last 80 years to cover such topics as multipleobjective trade-offs, time-dependent linked decisions, the value of information, and competition among multiple decision makers. At the same time, cognitive psychologists and behavioural economists have studied human decisions to understand when our innate processes work and when they fail. Formal decision analysis is increasingly being used in many sectors, including economic, industrial, manufacturing, agricultural, transportation, and medical sectors, by individuals, corporations, non-profits, and government agencies. Occasional application of decision analysis to environmental decisions began in the mid-1970s, but the environmental science and management world was largely unaware of decision analysis until the late 1990s and early 2000s. (A major aim of the ARC Centre of Excellence for Environmental Decisions – CEED – was to better connect decision analysis and environmental management). Today, the field of environmental decision analysis is coming of age with the maturation of a rich set of tools to help decision makers frame, analyze, and implement decisions. Sometimes the wealth of tools is daunting, but there are core principles that tie decision analysis together. To help the reader navigate this complexity, we summarize the field of decision analysis in four key messages.

Decision Point Online↗
USGS2019

Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): A cross-system analysis

Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis ) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long‐term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long‐term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifically, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long‐term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1–2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large declines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long‐term dynamics of body size. The long‐term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long‐term data sets on dreissenid populations, although clearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support.

Ecosphere↗
USGS2014

Annual flood sensitivities to El Niño-Southern Oscillation at the global scale

Floods are amongst the most dangerous natural hazards in terms of economic damage. Whilst a growing number of studies have examined how river floods are influenced by climate change, the role of natural modes of interannual climate variability remains poorly understood. We present the first global assessment of the influence of El Niño–Southern Oscillation (ENSO) on annual river floods, defined here as the peak daily discharge in a given year. The analysis was carried out by simulating daily gridded discharges using the WaterGAP model (Water – a Global Assessment and Prognosis), and examining statistical relationships between these discharges and ENSO indices. We found that, over the period 1958–2000, ENSO exerted a significant influence on annual floods in river basins covering over a third of the world's land surface, and that its influence on annual floods has been much greater than its influence on average flows. We show that there are more areas in which annual floods intensify with La Niña and decline with El Niño than vice versa. However, we also found that in many regions the strength of the relationships between ENSO and annual floods have been non-stationary, with either strengthening or weakening trends during the study period. We discuss the implications of these findings for science and management. Given the strong relationships between ENSO and annual floods, we suggest that more research is needed to assess relationships between ENSO and flood impacts (e.g. loss of lives or economic damage). Moreover, we suggest that in those regions where useful relationships exist, this information could be combined with ongoing advances in ENSO prediction research, in order to provide year-to-year probabilistic flood risk forecasts.

Hydrology and Earth System Sciences↗
USGS2025

Hydrologic connectivity in floodplain systems: A multiscale review of concepts, metrics and management

Hydrologic connectivity (HC), particularly in floodplain systems, is pivotal in regulating ecosystem services by facilitating the movement of nutrients, sediments, chemicals, and biota. However, human interventions such as dam construction, levee installation, water management practices, and alterations in vegetation have significantly disrupted natural HC patterns globally. To provide a structured entry into the growing body of HC research, we conducted a systematic literature review of 1920 studies, analysing diverse definitions, influencing factors, quantification approaches, spatial and temporal scales, and management strategies. In addition to traditional review methods, our approach integrates keyword and cluster analysis to elucidate dominant research themes and trends across the literature. Our review reveals that the literature is heavily skewed towards research in North America and Europe (accounting for 72% of studies) and predominantly utilises field investigations, simulation modelling, and remote sensing integrated with geographic information systems. Although these methodologies have advanced our understanding, most studies focus on restricted spatial scales such as individual hillslopes, catchments, or stream networks and short temporal intervals, including single precipitation events or seasonal cycles. A narrow focus becomes a limitation when such studies do not contribute to broader efforts aimed at scaling insights across larger domains. These limitations highlight the potential benefits of innovative conceptual frameworks and quantification methods to better capture HC across broader environments and extended temporal scales. We conclude by discussing challenges in defining and quantifying floodplain HC and outlining potential future research directions to advance connectivity science and management, particularly in floodplain systems characterised by frequent hydrologic fluctuations, such as seasonal inundation and changing flow paths.

Hydrological Processes↗
USGS2019

Employing an ecosystem services framework to deliver decision ready science

Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects. In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework. This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for ecosystem services and supporting tools such as the dynamic ecosystem model.

Advances in Ecological Research↗
USGS2019

Giving ecological meaning to satellite-derived fire severity metrics across North American forests

Satellite-derived spectral indices such as the relativized burn ratio (RBR) allow fire severity maps to be produced in a relatively straightforward manner across multiple fires and broad spatial extents. These indices often have strong relationships with field-based measurements of fire severity, thereby justifying their widespread use in management and science. However, satellite-derived spectral indices have been criticized because their non-standardized units render them difficult to interpret relative to on-the-ground fire effects. In this study, we built a Random Forest model describing a field-based measure of fire severity, the composite burn index (CBI), as a function of multiple spectral indices, a variable representing spatial variability in climate, and latitude. CBI data primarily representing forested vegetation from 263 fires (8075 plots) across the United States and Canada were used to build the model. Overall, the model performed well, with a cross-validated R 2 of 0.72, though there was spatial variability in model performance. The model we produced allows for the direct mapping of CBI, which is more interpretable compared to spectral indices. Moreover, because the model and all spectral explanatory variables were produced in Google Earth Engine, predicting and mapping of CBI can realistically be undertaken on hundreds to thousands of fires. We provide all necessary code to execute the model and produce maps of CBI in Earth Engine. This study and its products will be extremely useful to managers and scientists in North America who wish to map fire effects over large landscapes or regions.

Remote Sensing↗
USGS2021

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Methods in Ecology and Evolution↗
USGS2021

Identifying negative sentiment polarity in the Judas technique

In the context of conservation science and management, the Judas technique refers to outfitting an animal (a Judas animal) with a radio transmitter or other identifier so that its movements can be tracked to locate conspecifics. Although this term is commonly used, some consider it offensive due to historical associations of the word Judas with anti-Semitic sentiments. Thus, the term has a negative sentiment polarity (i.e., the assertion that words can have positive, negative, or neutral connotations). We investigated the etymology of the Judas term in peer-reviewed scientific literature to outline its contextual introduction and use. Prior to the term being co-opted by conservation scientists Judas [animal] was a common term in the livestock industry to describe animals used to lead herds to slaughter. Subsequently, the term has been published and promulgated through conservation-related research and the literature. Due to a negative sentiment polarity linked to this term, especially among members of the public, alternative nomenclature may be preferred to increase objective and dispassionate scientific communication.

Conservation Science and Practice↗
USGS2010

EAARL coastal topography-western Florida, post-Hurricane Charley, 2004: seamless (bare earth and submerged.

Project Description These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Coastal and Marine Geology Program (CMGP), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the western Florida coastline beachface, acquired post-Hurricane Charley on August 17 and 18, 2004. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website. Selected References Brock, J.C., Wright, C.W., Sallenger, A.H., Krabill, W.B., and Swift, R.N., 2002, Basis and methods of NASA airborne topographic mapper Lidar surveys for coastal studies: Journal of Coastal Research, v. 18, no. 1, p. 1-13. Crane, Michael, Clayton, Tonya, Raabe, Ellen, Stoker, Jason, Handley, Larry, Bawden, Gerald, Morgan, Karen, and Queija, Vivian, 2004, Report of the U.S. Geological Survey Lidar workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002: U.S. Geological Survey Open-File Report 2004-1456, 72 p. Nayegandhi, Amar, Brock, J.C., and Wright, C.W., 2009, Small-footprint, waveform-resolving Lidar estimation of submerged and sub-canopy topography in coastal environments: International Journal of Remote Sensing, v. 30, no. 4, p. 861-878. Sallenger, A.H., Wright, C.W., and Lillycrop, Jeff, 2005, Coastal impacts of the 2004 hurricanes measured with airborne Lidar; initial results: Shore and Beach, v. 73, nos. 2-3, p. 10-14. Resources Included Readme.txt File

Data Series↗
USGS2020

North Atlantic right whale (Eubalaena glacialis) scenario planning summary report

Scenario planning provides a structured framework that can be used in strategic planning to help manage risk and prioritize actions (Schwartz 1996; Peterson et al. 2003). By providing a mechanism to communicate about complex situations, scenario planning encourages “out-of-the-box” thinking to help groups assess the impacts of plausible future scenarios on a target or resource. The outcomes from scenario planning can be used to improve management decisions, highlight data gaps, and/or identify future science priorities (Star et al. 2015; Borggaard et al. 2019). The application of scenario planning by resource management organizations (e.g., Borggaard et al. 2019; Runyon et al. 2020; Star et al. 2015) and the urgency surrounding the recovery of the critically endangered North Atlantic right whale (Eubalaena glacialis), led to a 2018 NOAA Fisheries scenario planning initiative for the species. In addition to complementing the many management and conservation efforts already underway, this initiative was designed to address the uncertainties around future anthropogenic and environmental changes and how these uncertainties may impact species recovery. We used a scenario planning framework to explore plausible future conditions for North Atlantic right whales and to develop possible options to address those conditions and improve recovery. Specific objectives were to: 1) better understand the challenges of right whale management in a changing climate; 2) identify potential research activities and recovery needs across the species’ range; 3) increase coordination and collaboration related to recovery efforts; and 4) explore how scenario planning can be used to support decisions. Using projected changes in ocean conditions coupled with anthropogenic stressors, we built four plausible future scenarios for right whales. These scenarios helped identify priority research and management actions that NOAA Fisheries and our partners can undertake to improve right whale recovery. We identified priority actions related to science, management, and partnerships including, but not limited to, 1) research on shifting spatial and temporal distributions of right whales and prey in a changing climate; 2) development of technology to further reduce impacts from human activities; 3) continuation of ongoing management efforts related to vessel traffic and fishing; and 4) continued maintenance of existing and development of new partnerships (e.g., industry engagement in problem solving). This scenario planning exercise helped prioritize North Atlantic right whale management and science needs in light of changing ocean conditions and anthropogenic impacts. It can also serve as a reference for how NOAA Fisheries and its partners can better prepare for multiple plausible futures while complementing other on-going initiatives. Priorities identified here can be considered in conjunction with implementation and monitoring actions such as with the Atlantic Large Whale Take Reduction Team (ALWTRT) and/or regional Right Whale U.S. Implementation Teams. The framework can also be repeated and improved upon as additional information becomes available to support future exercises.

Technical Memorandum↗
USGS2014

Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach

Effective science-based management of water resources in large basins requires a qualitative understanding of hydrologic conditions and quantitative measures of the various components of the water budget, including difficult to measure components such as baseflow discharge to streams. Using widely available discharge and continuously collected specific conductance (SC) data, we adapted and applied a long established chemical hydrograph separation approach to quantify daily and representative annual baseflow discharge at fourteen streams and rivers at large spatial (> 1,000 km 2 watersheds) and temporal (up to 37 years) scales in the Upper Colorado River Basin. On average, annual baseflow was 21-58% of annual stream discharge, 13-45% of discharge during snowmelt, and 40-86% of discharge during low-flow conditions. Results suggest that reservoirs may act to store baseflow discharged to the stream during snowmelt and release that baseflow during low-flow conditions, and that irrigation return flows may contribute to increases in fall baseflow in heavily irrigated watersheds. The chemical hydrograph separation approach, and associated conceptual model defined here provide a basis for the identification of land use, management, and climate effects on baseflow.

Colorado, Utah↗
USGS2015

River corridor science: Hydrologic exchange and ecological consequences from bedforms to basins

Previously regarded as the passive drains of watersheds, over the past 50 years, rivers have progressively been recognized as being actively connected with off-channel environments. These connections prolong physical storage and enhance reactive processing to alter water chemistry and downstream transport of materials and energy. Here we propose river corridor science as a concept that integrates downstream transport with lateral and vertical exchange across interfaces. Thus, the river corridor, rather than the wetted river channel itself, is an increasingly common unit of study. Main channel exchange with recirculating marginal waters, hyporheic exchange, bank storage, and overbank flow onto floodplains are all included under a broad continuum of interactions known as “hydrologic exchange flows.” Hydrologists, geomorphologists, geochemists, and aquatic and terrestrial ecologists are cooperating in studies that reveal the dynamic interactions among hydrologic exchange flows and consequences for water quality improvement, modulation of river metabolism, habitat provision for vegetation, fish, and wildlife, and other valued ecosystem services. The need for better integration of science and management is keenly felt, from testing effectiveness of stream restoration and riparian buffers all the way to reevaluating the definition of the waters of the United States to clarify the regulatory authority under the Clean Water Act. A major challenge for scientists is linking the small-scale physical drivers with their larger-scale fluvial and geomorphic context and ecological consequences. Although the fine scales of field and laboratory studies are best suited to identifying the fundamental physical and biological processes, that understanding must be successfully linked to cumulative effects at watershed to regional and continental scales.

Water Resources Research↗
USGS2019

Spatially-structured statistical network models for landscape genetics

A basic understanding of how the landscape impedes, or creates resistance to, the dispersal of organisms and hence gene flow is paramount for successful conservation science and management. Spatially structured ecological networks are often used to represent spatial landscape‐genetic relationships, where nodes represent individuals or populations and resistance to movement is represented using non‐binary edge weights. Weights are typically assigned or estimated by the user, rather than observed, and validating such weights is challenging. We provide a synthesis of current methods used to estimate edge weights and an overview of common model types, stressing the advantages and disadvantages of each approach and their ability to model landscape‐genetic data. We further explore a set of spatial‐statistical methods that provide ecologists with alternative approaches for modeling spatially explicit processes that may affect genetic structure. This includes an overview of spatial autoregressive models, with a particular focus on how correlation and partial correlation are used to represent neighborhood structure with the inverse of the covariance matrix (i.e., precision matrix). We then demonstrate how to model resistance by specifying an appropriate statistical model on the nodes, conditioned on the edge weights, through the precision matrix. This integration of network ecology and spatial statistics provides a practical analytical framework for landscape‐genetic studies. The results can be used to make statistical inferences about the relative importance of individual landscape characteristics, such as the vegetative cover, hillslope, or the presence of roads or rivers, on gene flow. In addition, the R code we include allows readers to explore landscape‐genetic structure in their own datasets, which will potentially provide new insights into the evolutionary processes that generated ecological networks, as well as valuable information about the optimal characteristics of conservation corridors.

Ecological Monographs↗