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At least 1,171 records · Page 65Linked to original sources

USGS2022

Can coastal habitats rise to the challenge? Resilience of estuarine habitats, carbon accumulation, and economic value to sea-level rise in a Puget Sound estuary

Sea-level rise (SLR) and obstructions to sediment delivery pose challenges to the persistence of estuarine habitats and the ecosystem services they provide. Restoration actions and sediment management strategies may help mitigate such challenges by encouraging the vertical accretion of sediment in and horizontal migration of tidal forests and marshes. We used a process-based soil accretion model (Coastal Wetland Equilibrium Model) combined with a habitat classification model (MOSAICS) to estimate the effects of SLR, suspended sediment, and inland habitat migration on estuarine habitats, soil carbon accumulation, and economic value of climate change mitigation of carbon accumulation (social cost of carbon dioxide) in a macrotidal estuary in the northwest USA over 100 years (2011 to 2110). Under present-day sediment levels, we projected that after 100 years, most high salt marsh would remain with < 100 cm SLR, but substantial area converted to transitional (low) salt marsh and mudflat with ≥ 100 cm SLR. Increasing sediment availability increased the projected resilience of transitional salt marsh to SLR but did not prevent declines in high marsh area. Projected total carbon accumulation plateaued or declined with ≥ 100 cm SLR, yet the economic value of carbon accumulation continued to rise over time, suggesting that the value of this ecosystem service was resilient to SLR. Doubling or tripling sediment availability increased projected carbon accumulation up to 7.69 and 14.2 kg m −2 and increased total economic value up to $373,000 and $710,000, respectively. Allowing marsh migration supported conversion of upland to freshwater marsh, with slight increases in carbon accumulation. These results inform climate adaptation planning for wetland managers seeking to understand the resilience of estuarine habitats and ecosystem services to SLR under multiple management strategies.

Washington↗

USGS2020

A new decision support tool for collaborative adaptive vegetation management in northern Great Plains national parks

National Park Service (NPS) units in the northern Great Plains (NGP) were established to preserve and interpret the history of America, protect and showcase unusual geology and paleontology, and provide a home for vanishing large wildlife. A unifying feature among these national parks, monuments, and historic sites is mixed-grass prairie, which not only provides background scenery but is the very foundation of many park missions. As recognition of the prairie’s importance to park fundamental resources and values has grown, so too has the realization that invasive plants threaten these values by reducing native species diversity, altering food webs, and marring the visitor experience. Parks manage invasive species despite uncertainties in treatment effectiveness because management cannot wait for research to provide definitive answers. Under these circumstances, adaptive management (AM) is an appropriate approach. In the NGP, we formed a collaborative adaptive vegetation management team to apply AM towards reducing invasive species (with a focus on exotic annual grasses) and improving native vegetation conditions. In our AM framework, the team uses a Bayesian model built from NPS Inventory & Monitoring and Fire Effects monitoring data and experimental results to predict the effects of management actions on park management units, according to those units’ vegetation condition and management history. These predictions inform management decisions, which are then applied.

Parks Stewardship Forum↗

USGS2014

Making decisions in complex landscapes: Headwater stream management across multiple federal agencies

Headwater stream ecosystems are vulnerable to numerous threats associated with climate and land use change. In the northeastern US, many headwater stream species (e.g., brook trout and stream salamanders) are of special conservation concern and may be vulnerable to climate change influences, such as changes in stream temperature and streamflow. Federal land management agencies (e.g., US Fish and Wildlife Service, National Park Service, USDA Forest Service, Bureau of Land Management and Department of Defense) are required to adopt policies that respond to climate change and may have longer-term institutional support to enforce such policies compared to state, local, non-governmental, or private land managers. However, federal agencies largely make management decisions in regards to headwater stream ecosystems independently. This fragmentation of management resources and responsibilities across the landscape may significantly impede the efficiency and effectiveness of conservation actions, and higher degrees of collaboration may be required to achieve conservation goals. This project seeks to provide an example of cooperative landscape decision-making to address the conservation of headwater stream ecosystems. We identified shared and contrasting objectives of each federal agency and potential collaboration opportunities that may increase efficient and effective management of headwater stream ecosystems in two northeastern US watersheds. These workshops provided useful insights into the adaptive capacity of federal institutions to address threats to headwater stream ecosystems. Our ultimate goal is to provide a decision-making framework and analysis that addresses large-scale conservation threats across multiple stakeholders, as a demonstration of cooperative landscape conservation for aquatic ecosystems. Additionally, we aim to provide new scientific knowledge and a regional perspective to resource managers to help inform local management decisions.

Maine, New Hampshire, Virginia, West Virginia↗

USGS2021

Optimizing preservation for multiple types of historic structures under climate change

Cultural resources in coastal parks and recreation areas are vulnerable to climate change. The US National Park Service (NPS) is facing the challenge of insufficient budget allocations for both maintenance and climate adaptation of historic structures. Research on adaptation planning for cultural resources has predominately focused on vulnerability assessments of heritage sites; however, few studies integrate multiple factors (e.g., vulnerability, cultural significance, use potential, and costs) that managers should consider when making tradeoff decisions about which cultural resources to prioritize for adaptation. Moreover, heritage sites typically include multiple types of cultural resources, and researchers have yet to examine such complex tradeoffs. This study applies the Optimal Preservation (OptiPres) Model as a decision support framework to evaluate the tradeoffs of adaptation actions among multiple types of historic structures—wooden buildings, masonry and concrete buildings, forts, and batteries—under varying budget scenarios. Results suggest that the resource values of different types of historic structures vary greatly under a range of budget scenarios, and tradeoffs have to be made among different types of historical structures to achieve optimal planning objectives. Moreover, periodic, incremental funding and partial maintenance are identified as optimal funding strategies for preservation needs of cost-intensive historic structures. Also, adaptative use of historical buildings (e.g., building occupancy) can improve the resource values when budgets are constrained. The OptiPres Model provides managers with a unique framework to inform adaptation planning efforts for a broad range of historic structures, which is transferable across coastal parks to enhance historic preservation planning under climate change.

Landscape and Urban Planning↗

USGS2015

A conceptual model for site-level ecology of the giant gartersnake ( Thamnophis gigas ) in the Sacramento Valley, California

Giant gartersnakes (Thamnophis gigas) comprise a species of semi-aquatic snakes precinctive to marshes in the Central Valley of California (Hansen and Brode, 1980; Rossman and others, 1996). Because more than 90 percent of their historical wetland habitat has been converted to other uses (Frayer and others, 1989; Garone, 2007), giant gartersnakes have been listed as threatened by the State of California (California Department of Fish and Game Commission , 1971) and the United States (U.S. Fish and Wildlife Service, 1993). Giant gartersnakes currently occur in a highly modified landscape, with most extant populations occurring in the rice - growing regions of the Sacramento Valley, especially near areas that historically were tule marsh habitat (Halstead and others, 2010, 2014). In ricelands and managed marshes, many operational decisions likely affect the health and viability of giant gartersnake populations. Land-use decisions, including the management of water, aquatic vegetation, terrestrial vegetation, and co-occurring species, have the potential to affect giant gartersnakes. Little is known, however, about the effects of these types of decisions on the viability of giant gartersnake populations. Bayesian network models are a useful tool to help guide decisions with uncertain outcomes. These models require the articulation of what experts think they know about a system, and facilitate learning about the hypothesized relations (Marcot and others, 2001; Uusitalo , 2007). Bayesian networks further provide a clear visual display of the model that facilitates understanding among various stakeholders (Marcot and others, 2001; Uusitalo , 2007). Empirical data and expert judgment can be combined, as continuous or categorical variables, to update knowledge about the system (Marcot and others, 2001; Uusitalo , 2007). Importantly, Bayesian network models allow inference from causes to consequences, but also from consequences to causes, so that data can inform the states of nodes (values of different random variables) in either direction (Marcot and others, 2001; Uusitalo , 2007). Because they can incorporate both decision nodes that represent management actions and utility nodes that quantify the costs and benefits of outcomes, Bayesian networks are ideally suited to risk analysis and adaptive management (Nyberg and others, 2006; Howes and others, 2010). Thus, Bayesian network models are useful in situations where empirical data are not available, such as questions concerning the responses of giant gartersnakes to management.

California↗

USGS2012

Radar analysis of fall bird migration stopover sites in the Northeastern U.S.

The national network of weather surveillance radars (WSR-88D/NEXRAD) detects birds in flight, and has proven to be a useful remote-sensing tool for ornithological study. We used data collected during Fall 2008 and 2009 by 16 WSR-88D and 3 terminal Doppler weather radars in the northeastern U.S. (U.S. Fish and Wildlife Service Region 5) to study the spatial distribution of landbirds shortly after they leave daytime stopover sites to embark on nocturnal migratory flights. The aerial density of birds, as estimated by radar reflectivity, was georeferenced to the approximate locations on the ground from which birds emerged. We classified bird stopover use by the magnitude and variation of radar reflectivity across nights; areas were considered ‘important’ stopover sites from a conservation perspective if relative bird density was consistently or occasionally high. These results were used to develop models to predict potentially important stopover sites in portions of the region not sampled by the radars, based on land cover, ground elevation, and geographic location. Locally important stopover sites generally were associated with deciduous forests embedded within landscapes dominated by developed or agricultural lands, or near the shores of major water bodies. Large areas of regionally important stopover sites were located along the coastlines of Long Island Sound, throughout the Delmarva Peninsula, in areas surrounding Baltimore and Washington, along the western edge of the Adirondack Mountains, and within the Appalachian Mountains of southwestern Virginia and West Virginia. Important stopover sites, both within and outside radar-sampled areas and on 34 national wildlife refuges sampled by the radars, were mapped in a Geographic Information System, providing base maps for conservation uses and a sampling frame for field surveys to ‘ground truth’ the radar and analytical results. Our analysis indicates that preserving patches of natural habitat, particularly deciduous forests, in developed or agricultural landscapes and along major coastlines should be a priority for conservation plans addressing the stopover requirements of migratory landbirds.

Connecticut, Delaware, Maine, Maryland, Massachuse↗

USGS2021

Reconnaissance of cumulative risk of pesticides and pharmaceuticals in Great Smoky Mountains National Park streams

The United States (US) National Park Service (NPS) manages protected public lands to preserve biodiversity. Exposure to and effects of bioactive organic contaminants in NPS streams are challenges for resource managers. Recent assessment of pesticides and pharmaceuticals in protected-streams within the urbanized NPS Southeast Region (SER) indicated the importance of fluvial inflows from external sources as drivers of aquatic contaminant-mixture exposures. Great Smoky Mountains National Park (GRSM), lies within SER, has the highest biodiversity and annual visitation of NPS parks, but, in contrast to the previously studied systems, straddles a high-elevation hydrologic divide; this setting limits fluvial-inflows of contaminants but potentially increases visitation-driven contaminant deliveries. We leveraged the unique characteristics of GRSM to test further the importance of fluvial contaminant inflows as drivers of protected-stream exposures and to inform the relative importance of potential additional contaminant transport mechanisms, by comparing the estimated risks of 328 pesticides and pharmaceuticals in water at 16 GRSM stream locations to those estimated previously in SER streams. Extensive mixtures (31 compounds) were only observed in an atypical reach on the boundary of GRSM downstream of a wastewater discharge, while limited mixtures (2–5 compounds) were observed in one stream with elevated visitation pressure (recreational “tube floating”). The insecticide, imidacloprid, used to eradicate hemlock woolly adelgid, was detected in 8 (50%) streams. Infrequent exceedances of a cumulative ToxCast-based, exposure-activity ratio (Σ EAR ) 0.001 screening-level of concern suggested limited risk to non-target, aquatic vertebrates, whereas exceedances of a cumulative benchmark-based, invertebrate toxicity quotient (Σ TQ ) 0.1 screening level at 8 locations indicated generally high risk to invertebrates. The results are consistent with the importance of fluvial transport from extra-park sources as a driver of bioactive-contaminant mixture exposures in protected streams and illustrate the potential additional risks from visitation-driven and tactical-use-pesticides.

Tennessee↗

USGS2023

Population dynamics and harvest management of eastern mallards

Managing sustainable harvest of wildlife populations requires regular collection of demographic data and robust estimates of demographic parameters. Estimates can then be used to develop a harvest strategy to guide decision-making. Mallards ( Anas platyrhynchos ) are an important species in the Atlantic Flyway for many users and they exhibited exponential growth in the eastern United States between the 1970s and 1990s. Since then, estimates of mallard abundance have declined 16%, prompting the Atlantic Flyway Council and United States Fish and Wildlife Service to implement more restrictive hunting regulations and develop a new harvest strategy predicated on an updated population model. Our primary objective was to develop an integrated population model (IPM) for use in an eastern mallard harvest management strategy. We developed an IPM using annual estimates of breeding abundance, 2-season banding and recovery data, and hunter-harvest data from 1998 to 2018. When developing the model, we used novel model selection methods to test various forms of a sub-model for survival including estimating the degree of harvest additivity and any age-specific trends. The top survival sub-model included a negative annual trend on juvenile survival. The IPM posterior estimates for population abundance tracked closely with the observed estimates and estimates of mean annual population growth rate ranged from 0.88 to 1.08. Our population model provided increased precision in abundance estimates compared to survey methods for use in an updated harvest strategy. The IPM posterior estimates of survival rates were relatively stable for adult cohorts, and annual growth rate was positively correlated with the female age ratio, a measure of reproduction. Either or both of those demographic parameters, juvenile survival or reproduction, could be a target for management efforts to address the population decline. The resulting demographic parameters provided information on the equilibrium population size and can be used in an adaptive harvest strategy for mallards in eastern North America.

Journal of Wildlife Management↗

USGS2022

Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi

Mauka-to-makai (mountain to sea in the Hawaiian language) hydrologic connectivity – commonly referred to as ridge-to-reef – directly affects biogeochemical processes and socioecological functions across terrestrial, freshwater, and marine systems. The supply of freshwater to estuarine and nearshore environments in a ridge-to-reef system supports the food, water, and habitats utilized by marine fauna . In addition, the ecosystem services derived from this land-to-sea connectivity support social and cultural practices (hereafter referred to as socio-cultural) including fishing, aquaculture, wetland agriculture, religious ceremonies, and recreational activities. To effectively guide island resource management, a better understanding of the linkages from ridge-to-reef across natural and social usages is critical, particularly in the context of climate change, with anticipated increasing temperature and shifting precipitation patterns. The objective of this study was to identify spatial linkages that promote multiple and diverse uses, following the ridge-to-reef concept, at an island-wide scale to identify regions of high conservation importance for aquatic resources. We selected the Island of Maui as a study representative of many Pacific islands. Diverse datasets, including agricultural lands within watersheds, wetland locations, presence of stream species, indicators of freshwater input from streams, coral cover, nearshore fish biomass, socio-cultural data such as fishpond locations, wetland taro cultivation, beach recreation use, and lastly the dynamically downscaled Coupled Model Intercomparison Project Phase (CMIP5) future climate projections scenarios (Representative Concentration Pathway (RCP) 4.5 & 8.5) were used to examine the spatial linkages through hydrological connectivity from land to the sea. Zonation spatial planning software was used to prioritize areas of high management and conservation value and to help inform aquatic resources management. The resulting prioritized areas included many minimally disturbed watersheds in east Maui and western nearshore and coastal zones that are adjacent to diverse coral reefs. These results are driven by the importance of fish biomass and coral reef distribution as well as traditional wetland taro cultivation and coastal access points for recreation. These results underline the importance of examining ridge-to-reef systems for aquatic resource management and including important social and cultural values in resource management upon planning adaptation strategies for climate change. Improving our understanding of diverse natural and socio-cultural influences on habitat conditions and their values in these areas provides an opportunity to strategically plan future management and conservation actions.

Hawaii↗

USGS1996

U.S. Geological Survey programs in Texas

The U.S. Geological Survey (USGS) is the Federal Government's primary source of data on the quantity and quality of the Nation's water resources, its principal civilian map making agency, and its primary provider of information on natural hazards and mineral, energy, and biological resources. The USGS makes unbiased scientific information available equally to all interested parties. Most USGS work in Texas involves the appraisal of the State's water resources in cooperation with more than 80 local, State, and Federal agencies. The foundation of a wide range of hydrologic data-collection and interpretive programs is the stream-gaging program. The Texas network of streamflow-gaging stations, which provides water data for water-resources planning and design, hydrologic research, and operation of water-resources projects, is part of a nationwide aggregation of networks that is unique because of nationally consistent, prescribed standards by which the data are collected and processed. The USGS continues to expand collection of data for paper and digital maps. The best-known products of the USGS in Texas are its 1:24,000-scale topographic maps. These maps depict basic natural and cultural features of the landscape. Maps at this scale (1 inch on the map represents 2,000 feet on the ground) are useful for civil engineering, land-use planning, and natural-resource monitoring, and have long been favorites with the general public for a wide variety of outdoor uses. The USGS also continues to monitor geologic conditions in Texas associated with rare but potentially dangerous earthquakes. Recently, the Nation Biological Service (now the Biological Resources Division) joined the USGS to continue their appraisal of the nation's biological resources.

Fact Sheet↗

USGS2020

Monitoring and real-time modeling of Escherichia coli bacteria for the Chattahoochee River, Chattahoochee River National Recreation Area, Georgia, 2000–2019

The Chattahoochee River National Recreation Area (CRNRA) is a National Park Service unit/park with 48 miles of urban waterway in the Atlanta metropolitan area. The Chattahoochee River within the CRNRA is a popular place for water-based recreation but is known to periodically experience elevated levels of fecal-coliform bacteria associated with warm-blooded animals that can result in a variety of pathogen-related human illnesses. In 2000, the National Park Service entered into a public-private partnership with the U.S. Geological Survey (USGS) and the Chattahoochee Riverkeeper, called the Chattahoochee River BacteriALERT program, to monitor Escherichia coli ( E. coli ), which is a fecal indicator bacteria and a proxy for human health risk from waterborne pathogens. The BacteriALERT network monitors E. coli densities at three stations on the Chattahoochee River within the CRNRA, at Norcross (USGS station 02335000), Powers Ferry (USGS station 02335880), and Atlanta (USGS station 02336000). E. coli densities determined from water samples were compared to the U.S. Environmental Protection Agency’s Beach Action Value (BAV) of 235 colony forming units per 100 milliliters to assess whether conditions were considered safe for freshwater, primary contact recreational use. Sample E. coli densities exceeded the BAV for 15.5 percent of the samples collected at Norcross (n = 1,969) and 30.3 percent of the samples at Atlanta (n = 1,938) for the study period October 23, 2000, to May 23, 2019, and 33.6 percent of the samples from Powers Ferry (n = 134) for the study period May 5, 2016, to May 23, 2019. Models to predict E. coli densities in near real-time were developed for the three BacteriALERT stations. Models were developed using forward-stepwise multiple linear regression with the Bayesian Information Criteria and were calibrated with samples collected between October 4, 2007, and May 23, 2019. Explanatory variables included season, turbidity, water temperature, streamflow, upstream tributary streamflows, and temporal trend. The most statistically significant explanatory variables in the models were turbidity, upstream tributary streamflows, and season. The Norcross model had an increasing trend in E. coli densities of 2.3 percent per year. A significant trend was not detected for the Atlanta station, while trends were not assessed for Powers Ferry models due to the short (3-year) calibration period. Model adjusted R 2 s ranged from 0.686 (Atlanta) to 0.795 (Norcross with time trend) indicating that the models explained a substantial portion of the variations in E. coli densities. Evaluation of model predictions and residuals indicated that models were well posed and exhibited little bias. The models performed well in accurately determining compliance and exceedance of the BAV with low misidentification rates ranging from 3.5 percent (Norcross) to 11.3 percent (Powers Ferry). Misidentification was most common for densities near the BAV, and misidentification rates in the study were low despite fairly low model precisions because E. coli densities were infrequently near the BAV. The precisions of the models developed herein were comparable to the more complex models developed by Lawrence (2012) that were never implemented in the BacteriALERT program due to their computational complexity. The predictive E. coli models developed herein will improve the ability to assess the health risks of water-based recreational activities in the CRNRA in near real-time.

Georgia↗

USGS2009

Watershed Boundary Dataset for Mississippi

The U.S. Geological Survey, in cooperation with the Mississippi Department of Environmental Quality, U.S. Department of Agriculture-Natural Resources Conservation Service, Mississippi Department of Transportation, U.S. Department of Agriculture-Forest Service, and the Mississippi Automated Resource Information System developed a 1:24,000-scale Watershed Boundary Dataset for Mississippi including watershed and subwatershed boundaries, codes, names, and areas. The Watershed Boundary Dataset for Mississippi provides a standard geographical framework for water-resources and selected land-resources planning. The original 8-digit subbasins (Hydrologic Unit Codes) were further subdivided into 10-digit watersheds (62.5 to 391 square miles (mi2)) and 12-digit subwatersheds (15.6 to 62.5 mi2) - the exceptions being the Delta part of Mississippi and the Mississippi River inside levees, which were subdivided into 10-digit watersheds only. Also, large water bodies in the Mississippi Sound along the coast were not delineated as small as a typical 12-digit subwatershed. All of the data - including watershed and subwatershed boundaries, subdivision codes and names, and drainage-area data - are stored in a Geographic Information System database, which are available at: http://ms.water.usgs.gov/. This map shows information on drainage and hydrography in the form of U.S. Geological Survey hydrologic unit boundaries for water-resource 2-digit regions, 4-digit subregions, 6-digit basins (formerly called accounting units), 8-digit subbasins (formerly called cataloging units), 10-digit watershed, and 12-digit subwatersheds in Mississippi. A description of the project study area, methods used in the development of watershed and subwatershed boundaries for Mississippi, and results are presented in Wilson and others (2008). The data presented in this map and by Wilson and others (2008) supersede the data presented for Mississippi by Seaber and others (1987) and U.S. Geological Survey (1977).

Scientific Investigations Map↗

USGS2012

Simulating future uncertainty to guide the selection of survey designs for long-term monitoring

A goal of environmental monitoring is to provide sound information on the status and trends of natural resources (Messer et al. 1991, Theobald et al. 2007, Fancy et al. 2009). When monitoring observations are acquired by measuring a subset of the population of interest, probability sampling as part of a well-constructed survey design provides the most reliable and legally defensible approach to achieve this goal (Cochran 1977, Olsen et al. 1999, Schreuder et al. 2004; see Chapters 2, 5, 6, 7). Previous works have described the fundamentals of sample surveys (e.g. Hansen et al. 1953, Kish 1965). Interest in survey designs and monitoring over the past 15 years has led to extensive evaluations and new developments of sample selection methods (Stevens and Olsen 2004), of strategies for allocating sample units in space and time (Urquhart et al. 1993, Overton and Stehman 1996, Urquhart and Kincaid 1999), and of estimation (Lesser and Overton 1994, Overton and Stehman 1995) and variance properties (Larsen et al. 1995, Stevens and Olsen 2003) of survey designs. Carefully planned, “scientific” (Chapter 5) survey designs have become a standard in contemporary monitoring of natural resources. Based on our experience with the long-term monitoring program of the US National Park Service (NPS; Fancy et al. 2009; Chapters 16, 22), operational survey designs tend to be selected using the following procedures. For a monitoring indicator (i.e. variable or response), a minimum detectable trend requirement is specified, based on the minimum level of change that would result in meaningful change (e.g. degradation). A probability of detecting this trend (statistical power) and an acceptable level of uncertainty (Type I error; see Chapter 2) within a specified time frame (e.g. 10 years) are specified to ensure timely detection. Explicit statements of the minimum detectable trend, the time frame for detecting the minimum trend, power, and acceptable probability of Type I error (α) collectively form the quantitative sampling objective.

Book chapter↗

USGS2025

Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets

Coastal marsh wetlands experience variations in vertical gains and losses through time, which have allowed them to infill relict topography and record variations in drivers. The stratigraphic unit associated with the development of the marsh also reflects the long-term importance of key ecosystem services supplied by the marsh environment, including carbon storage and storm mitigation. Mapping these coastal wetland sediments and the marsh unit thickness is challenging as traditional coastal geophysical tools are not easily deployable (acoustic methods) or are unreliable in saline-soil environments (e.g., ground-penetrating radar), leaving core-based methods the most viable mapping method. In the present study, we utilized prior information on the geologic architecture of the region to select spatial and physical metrics that likely persisted throughout evolution of the marsh during the late Holocene. We then assessed the individual and collective power of these metrics to predict marsh thickness observed from cores. Employing regressive predictive models powered by these data, we improve the quantification of marsh thickness for a coastal fringing marsh within the Grand Bay estuary in Mississippi and Alabama (USA). The information gained from this approach yields improved estimates of the carbon stocks in this environment. Additionally, the stored sediment masses reflect the past, and potential future, persistence of the Grand Bay marsh under historical and present marsh-estuarine sediment exchange fluxes. Such improvements to both the sediment budget of recent marsh stratigraphic units and the spatial extent provide new resources for comparison with large-scale landscape models, the latter of which may be used, when validated, to predict future change and ecosystem transformations.

Alabama. Mississippi↗

USGS2014

Connecting the dots: a collaborative USGS-NPS effort to expand the utility of monitoring data

The Natural Resource Challenge (National Park Service 1999) was a call to action. It constituted a mandate for monitoring based on the twin premises that (1) natural resources in national parks require active management and stewardship if we are to protect them from gradual degradation, and (2) we cannot protect what we do not understand. The intent of the challenge was embodied in its original description: We must expand existing inventory programs and develop efficient ways to monitor the vital signs of natural systems. We must enlist others in the scientific community to help, and also facilitate their inquiry. Managers must have and apply this information to preserve our natural resources. In this article, we report on ongoing collaborative work between the National Park Service (NPS) and the US Geological Survey (USGS) that seeks to add to our scientific understanding of the ecological processes operating behind vital signs monitoring data. The ultimate goal of this work is to provide insights that can facilitate an understanding of the systems and identify potential opportunities for active stewardship by NPS managers (Bennetts et al. 2007; Mitchell et al. 2014). The bulk of the work thus far has involved Acadia and Rocky Mountain national parks, but there are plans for extending the work to additional parks. Our story stats with work designed to consider ways of assessing the status and condition of natural resources and the potential for historical or ongoing influences of human activities. In the 1990s, the concept of "biotic integrity" began to take hold as an aspiration for developing quantitative indices describing how closely the conditions at a site resemble those found at pristine, unimpacted sites. Quantitative methods for developing indices of biotic integrity (IBIs) and elaborations of that idea (e.g., ecological integrity) have received considerable attention and application of these methods to natural resources has become widespread (Karr 1991; Barbour et al. 1999; Stoddard et al. 2008). Despite widespread use, many questions remain about how metrics are combined to form effective indices and about how to interpret both. Scientists and natural resource specialists within NPS and USGS have joined forces to critique the current analysis methods, with the collaboration involving the Rocky Mountain and Northeast Temperate NPS Inventory and Monitoring (I & M) networks, along with others, and USGS scientists from the National Wetlands Research Center and Patuxent Wildlife Research Center. Funding that initiated the project was from a joint-partnership fund managed by the USGS Ecosystems Program for National Park Monitoring research and the work was focused at Acadia National Park and Rocky Mountain National Park. Here we present synopses of two major issues addressed by the group.

The George Wright Forum↗

USGS2021

The North American Breeding Bird Survey in Mexico, 2008 to 2018—A status report

Collection of avian population data has repeatedly been identified as a high priority for bird conservation in Mexico. To meet this need, in 2008 the North American Breeding Bird Survey (BBS), a volunteer-based survey, was expanded to include northern Mexico. The BBS in Mexico (Mexican BBS) is managed by the North American Bird Conservation Initiative (NABCI), Mexico’s National Coordination Office inside the Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO). During 2008–18, 252 surveys were conducted along 68 routes in Mexico, with geographic coverage varying from year to year. Of these 68 routes, 36 were surveyed three or more times. Thirty-one observers conducted the surveys, and 21 of these observers conducted two or more surveys. Just two observers conducted more than one-third of the 252 surveys, and both observers were paid to conduct the surveys. The low availability of local observers who are qualified, willing, and able to volunteer their services to conduct BBS surveys may prove to be the biggest obstacle to the success of the Mexican BBS program, especially in the context of Mexico’s ongoing safety and security concerns. Apart from the amount of data collected, many surveys did not adhere to pre-established quality-control requirements, and this would result in the exclusion of a large percentage of the data from potential trend analyses. Only 31 percent of the surveys met all the quality-control criteria. Additional observer training may help resolve this issue. Of greater concern is the selection of region-specific sampling date windows during which the surveys are conducted. Observers consistently conducted surveys outside the preliminarily prescribed sampling date window, reflecting the need to re-evaluate the regional appropriateness of this date window. Regardless of the quality of the data, the quantity of data available from 2008 to 2018 is insufficient for trend analysis using methods typically employed by U.S. Geological Survey BBS analysts. Reaching minimum sample size thresholds for statistical analysis will require a substantial increase in effort. During 2008–18, no strata (defined as the intersection of State and Bird Conservation Region boundaries) reached the suggested minimum of 14 sampled routes, and most routes were not run consistently. This report provides information needed for an evaluation of the merits of continuing to invest in the Mexican BBS program in its current form. Such an evaluation should consider the likelihood of achieving the primary project goal of producing reliable long-term population trend estimates, a projected timeline for meeting this goal, and include an assessment of the potential value of any additional data products.

Baja California, Baja California Sur, Chihuahua, C↗

USGS1978

MOSS user's manual

The Map Overlay and Statistical System (MOSS) Users' Manual is specialized document has been designed for trained users of the MOSS interactive graphics software. Those totally unfamiliar with MOSS or Geographic Information Systems are referred elsewhere as described below: -- If you know nothing about MOSS or what it can do for you, and you wish introductory information on MOSS, or you want to deign an application and data entry process compatible with MOSS, or you want "hands-on" training, contact the WELUT Team Leader at the address below for a "hands-on" GIS training session. -- If you have been introduced to MOSS, have your application defined, data entered, and want to know how to use MOSS, start reading at Section 1 of this Manual. --If you are interested in the MOSS data structure, refer to Section 2 of this Manual. --If you have some experience in using MOSS and want to refer to the general types of MOSS commands, read Section 3 of this Manual. --If you are an experience MOSS user and want details on individual MOSS commands, refer to Section 4.3 of this Manual. --If you are interested in the Federation of Rocky Mountain States -- WELUT 02 Project contractual background results, turn to Appendices D and E of this Manual. MOSS has been operation for less than 3 months, and has received limited operational testing at the date of this printing (October 1978). Undiscovered software limitations and bugs may yet appear. All such bugs as well as documentation errors, obscurities, and inadequacies should be reported to: Team Leader Western Energy and Land Use Team (WELUT) U.S. Fish and Wildlife Service Drake Creekside Building 2625 Redwing Road Fort Collins, Colorado 80526

FWS/OBS↗

USGS2002

Threats to desert tortoise populations: a critical review of the literature

Decision in resource management are generally based on a combination of sociopolitical, economic, and environmental factors, and may be biased by personal values. These three components often contradict each other resulting in controversy. Controversies can usually be reduced when solid scientific evidence is used to support or refute a decision. However, it is important to recognize that data often do little to alter antagonists' positions when differences in values are the bases if the dispute. But, supporting data can make the decision more defensible, both legally and ethically, especially if the data supporting all opposing viewpoints are included in the decision-making process. Resource management decisions must be made using the best scientific information currently available. However, scientific data vary in two important measures of quality: reliability and validity. The reliability of the data is a measure of the degree to which the observations or conclusion can be repeated. Validity of the data is a measure of the degree to which the observation or conclusion reflects what actually occurs in nature. How the data are collected strongly affects the reliability of validity of ecological conclusions that can be made. Research data potentially relevant to management come from different sources, and the source often provides clues to the reliability and, to a certain extent, validity of data. Understanding the quality of data being used to make management decisions helps to separate the philosophical or value-based aspects of arguments from the objective ones, thus helping to clarify the decisions and judgments that need to be made. The West Mojave Plan is a multispecies, bioregional plan for the management of natural resources within a 9.4 million-acre area of the Mojave Desert in California. The plan addresses the legal requirements for the recovery of the desert tortoise ( Gopherus agazzizii ), a threatened species, but also covers an additional approximately 80 species of plants and animals assigned special status by the Bureau of Land Management, U. S. Fish and Wildlife Service, and California Department of Fish and Game. Within the planning area, 28 separate jurisdictions (counties, cities, towns, military installations, etc.) seek programmatic prescriptions that will facilitate streamlined environmental review, result in expedited authorization for development projects, and protect listed and unlisted species into the foreseeable future to avoid or minimize conflicts between proposed development and species' conservation and recovery. All of the scientific data available concerning the biology and management of these approximately 80 species and their habitats must be evaluated to develop a scientifically credible plan. This document provides an overview and evaluation of the knowledge of the major threats to the persistence and recovery of desert tortoise populations. I was specifically asked to evaluate the scientific veracity of the data and reports available. I summarize the data presently available with particular focus on the West Mojave Desert, evaluate the scientific integrity of the data. and identify major gaps in the available knowledge. I do not attempt to provide in-depth details on each study or threat; for more details I encourage the reader to consult the individual papers or reports city throughout this report (many of which are available at most university libraries and at the West Mojave Plan office in Riverside, California). I also do not attempt to characterize or evaluate the past or present management actions, except where they have direct bearing on evaluation of threats, nor do I attempt, for the most part, to acquire, generate, or evaluate new or existing, but uninterpreted data.

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