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Modeling, mapping, and measuring the risk of freshwater invasive species across Alaska

Freshwater ecosystems of the Alaskan Arctic and Subarctic provide resources that are culturally, ecologically, and economically invaluable. Presently, these regions are relatively free of the impacts from invasive species compared to southern latitudes. To date, there have been relatively few verified introductions of aquatic invasive species (AIS) to freshwater ecosystems in Alaska. The expanding list and distribution of AIS has led to significant negative ecological and economic impacts (e.g., waterweed Elodea nuttalli ; E. canadensis and northern pike Esox Lucius introduced outside its native range in Alaska). Escalating human activity across Alaskan lands and waters, coupled with rapidly shifting environmental conditions, increases the potential for new species introductions and subsequent establishment. Creating a proactive framework for well-informed decision-making and action can improve the effectiveness of prevention efforts and bolster decision support tools that help resource managers direct limited resources. Prioritizing AIS that may be introduced and become established, as well as the locations at highest risk of invasion, is foundational to building a proactive invasive species management framework in Alaska. This project sought to identify and prioritize AIS known to be invasive in the contiguous United States, evaluate current and future habitat suitability for AIS in Alaska, and assess potential for AIS to be transported to habitats across Alaska, utilizing similar assessment methods as implemented for Bering Sea marine invasive species and non-native plants in Alaska. To accomplish this goal, the objectives of the project were to: 1) develop a formal ranked list of potential AIS to freshwater systems of Alaska; 2) assess the level of establishment risk for potential AIS by developing habitat suitability models for waterbodies across Alaska; and 3), identify potential pathways and specific vectors for high-risk AIS to invade Alaska and develop a framework for how vector analysis will be completed to understand transport risk. Overall, our goal is horizon scanning which is defined by Roy et al. (2019) as “a systematic examination of potential threats and opportunities, within a given context, and likely future developments, which are at the margin of current thinking and planning.” The scans include pathway analyses and risk screening of species present at pathway origin points, with a focus on identifying species at high risk of being introduced, becoming established, spreading, and causing harm. We refined a list of 28 AIS from a list of hundreds based on characterizations of species’ invasiveness and species’ proximity to Alaska (USGS 2020; GBIF 2022). Next, we evaluated the relative invasiveness of individual species to create an initial AIS ranking. We sought to characterize habitat suitability of AIS by selecting variables that were continental in scale, covering North America to include Alaska as well as the lower 48 states comparing natural discharge, sub-basin average terrain slope (degrees), average silt fraction, average organic carbon, lithological class, and human footprint in sub-basin in 2009. We estimated AIS habitat suitability across the entire state of Alaska using the physiological tolerances of the AIS (Appendix 2). We also evaluated pathways and vectors for the introduction of AIS (Appendix 2). Many pathways and vectors considered did not meet the criteria for Alaska or freshwater systems. Of the 28 ranked species that we categorized as very high, high, and moderate levels of invasiveness; all three risk groups included fish and mollusks (Appendix 2). One commonality of the very high-invasiveness-ranked species was the availability of Ecological Risk Screening Summary documents (USFWS, 2022) produced by U.S. Fish and Wildlife Service (USFWS), except for the goldfish ( Carassius auratus ) and the New Zealand mudsnail ( Potamopyrgus antipodarum ). The Ecological Risk Screening Summary is now available for New Zealand mudsnails. In general, fish species often ranked very high or high in invasiveness and included sportfish and aquarium fish, suggesting the importance of pathways such as aquarium trade, fishing industry, intentional (but illegal) introductions of sportfishes and aquarium fishes for establishment. The technique we used for habitat suitability models necessitated aquatic environmental datasets that were continental in scale, which was often interpolated from very coarse resolution source data layers, particularly in Alaska. Better spatial data representing aquatic environments would likely improve this approach. While the lack of introductions in Alaska and nearby provinces and states is encouraging, the lack of occurrence data for the focal species also created complications for habitat suitability modeling. Despite the challenges, the habitat suitability models indicated limited suitability for warmwater species while some species, such as Brook trout (S alvelinus fontinalis ), have high habitat suitability across Alaska no matter what threshold approach is taken. Some environmental predictors were more important than others. Specifically, the most important predictor variable, ‘frost free days,’ was critical for 15 out of 28 species as expected due to harsh winter conditions in Arctic and Subarctic regions. The second most important predictor was ‘subbasin land surface runoff’, a variable that indicates the amount of discharge and runoff, while the third most important predictor was ‘snow cover’ another indication of winter conditions. Overall, the ability to understand the effect of future climate scenarios on the establishment of AIS was challenging. A detailed dataset of freshwater temperatures and water chemistry (e.g., pH, calcium) would greatly improve the ability to predict invasiveness of freshwater species to Alaska’s ecosystems on a regional basis. Future studies may benefit from a more focused geographic scope examining a group of subbasins or a regional basin rather than the entire state. These drainages could be selected based upon the mostly likely locations of introduction pathways. The two most prevalent pathway risks for AIS are in-state transfer and stowaways/contaminants. Although there are examples of introductions from other pathways, the risk is somewhat mitigated by Alaska’s climate and regulations. However, variable application of protocols for inspection and cleaning of fishing gear, watercraft, and other similar items while traveling into Alaska as well as transferring from waterbody to waterbody within the state creates a substantial risk in introducing invasive species. We plot cumulative invasive vulnerability for all subbasins and for the top 10% of subbasins (Appendix 3).

Alaska↗

Vegetation classification and distribution mapping report: Canyon de Chelly National Monument

Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.

Report↗

Determining low-flow conditions at select streams to Barnegat Bay-Little Egg Harbor as the first step towards the development of ecological-flow targets

Maintaining streamflow to support human water needs and ecosystem services requires a fundamental understanding of the relations between changes in streamflow processes and ecosystem responses. Changes in the natural patterns in flow, geology, and topography alter the habitats that aquatic organisms rely on for food, shelter, and reproduction. The U.S. Geological Survey (USGS) implemented an ecological-flow framework that encapsulates the basic principles of the Ecological Limits of Hydrologic Alteration (ELOHA) to compare the relations between hydrologic metrics and stream conditions and estimate ecological flow needs in the Barnegat Bay-Little Egg Harbor watershed. As a first step in the ELOHA process, streamflow from two historical time periods (occurring between 1933 and 1988) was compared to streamflow for a recent time period (from 2004-2020) for four major streams in the Barnegat Bay-Little Egg Harbor watershed (North Branch Metedeconk River, Toms River, Cedar Creek, and Westecunk Creek), to evaluate if there were statistically significant differences in streamflow metrics. Analysis of monthly, seasonal, and annual low-flow metrics; patterns in the streamflow record; and general land-use changes were used to develop a better understanding of flow conditions in the watershed. The comparative streamflow analysis indicated that notable changes in flow processes for the study streams occurred between the three periods of record (PORs) evaluated in this study: period of record 1 (POR1, from water years 1933–1958), period of record 2 (POR2, from water years 1974–1988), and period of record 3 (POR3, from water years 2004–2020). For example, the mean of the daily streamflow decreased between the historical POR to the current POR in Cedar Creek but increased in North Branch Metedeconk and Toms Rivers. Larger and more significant changes (p-value <0.10) occurred during specific months or were related to the variability or seasonality of flow. North Branch Metedeconk River and Toms River, the two northern and most developed sites, exhibited changes in low-flow metrics and decreases in minimum n-day moving averages. Decreases in the normalized 75th-percentile exceedance flows were evident at three of the four study sub-basins during POR2 and POR3. In comparison, there was little to no evidence of negative changes to low-flow metrics at Westecunk Creek, the southernmost and least developed site, where all low-flow duration metrics increased as well as seasonal minimum consecutive 7-day average flows. Significant increases in monthly minimums (p-value <0.05) at Cedar Creek for spring months (April, May, and June) also were observed. Natural and anthropogenic processes can alter the landscape resulting in concomitant changes in the streamflow regime. There is a need to assess these changes and synthesize the results into a scientifically defensible set of goals and standards that help support the management of environmental flows. This study represents the initial steps in building the hydrologic foundation to inform management and develop future ecological flow targets that balance water availability for human and ecosystem needs in the Barnegat Bay-Little Egg Harbor watershed.

New Jersey↗

Guidance documents: Continued support to improve operations of fish hatcheries and field sites to reduce the impact or prevent establishment of New Zealand Mudsnails and other invasive mollusks

This project tested and revised a risk assessment/management tool authored by Moffitt and Stockton designed to provide hatchery biologists and others a structure to measure risk and provide tools to control, prevent or eliminate invasive New Zealand mudsnails (NZMS) and other invasive mollusks in fish hatcheries and hatchery operations. The document has two parts: the risk assessment tool, and an appendix that summarizes options for control or management. The framework of the guidance document for risk assessment/hatchery tool combines approaches used by the Hazard Analysis and Critical Control Points (HACCP) process with those developed by the Commission for Environmental Cooperation (CEC), of Canada, Mexico, and the United States, in the Tri-National Risk Assessment Guidelines for Aquatic Alien Invasive Species. The framework approach for this attached first document assesses risk potential with two activities: probability of infestation and consequences of infestation. Each activity is treated equally to determine the risk potential. These two activities are divided into seven basic elements that utilize scientific, technical, and other relevant information in the process of the risk assessment. To determine the probability of infestation four steps are used that have scores reported or determined and averaged. This assessment follows a familiar HACCP process to assess pathways of entry, entry potential, colonization potential, spread potential. The economic, environmental and social consequences are considered as economic impact, environmental impact, and social and cultural influences. To test this document, the Principal Investigator worked to identify interested hatchery managers through contacts at regional aquaculture meetings, fish health meetings, and through the network of invasive species managers and scientists participating in the Western Regional Panel on Aquatic Nuisance Species and the 100th Meridian Initiative's Columbia River Basin Team, and the Western New Zealand Mudsnail Conference in Seattle. Targeted hatchery workshops were conducted with staff at Dworshak National Fish Hatchery Complex (ID), Similkameen Pond, Oroville WA, and Ringold Springs State Hatchery (WA). As a result of communications with hatchery staff, invasive species managers, and on site assessments of hatchery facilities, the document was modified and enhanced. Additional resources were added to keep it up to date. The result is a more simplified tool that can lead hatchery or management personnel through the process of risk assessment and provide an introduction to the risk management and communication process. In addition to the typical HACCP processes, this tool adds steps to rate and consider uncertainty and the weight of evidence regarding options and monitoring results . Uncertainty of outcome exists in most tools that can be used to control or prevent NZMS or other invasive mollusks from infesting an area. In additional this document emphasizes that specific control tools and plans must be tailored to each specific setting to consider the economic, environmental and social influences. From the testing and evaluation process, there was a strong recognition that a number of control and prevention tools previously suggested and reported in the literature from laboratory and small scale trials may not be compatible with regional and national regulations, economic constraints, social or cultural constraints, engineering or water chemistry characteristics of each facility. The options for control are summarized in the second document, Review of Control Measures for Hatcheries Infested with NZMS (Appendix A) that provides sources for additional resources and specific tools, and guidance regarding the feasibility and success of each approach. This tool also emphasizes that management plans need to be adaptive and incorporate oversight from professionals familiar with measuring risks of fish diseases, and treatments (e.g. the fish health practitioners and water quality and effluent management teams). Finally, with such a team, the adaptive management approach must be ongoing, and become a regular component of hatchery operations. Although it was the intent that this two part document would be included as part of the revised National Management and Control Plan for the NZMS proposed by the U.S. Fish and Wildlife Service (USFWS) and others, it is provided as a stand-alone document.

Cooperator Science Series↗

Demography and behavior of polar bears summering on land in Alaska

Polar bears (Ursus maritimus) in the southern Beaufort Sea population (SB) are spending increased time on the coastal North Slope of Alaska between July and October (Gleason and Rode 2010). The duration spent on land by polar bears, satellite collared on the sea-ice in the spring, during the summer and fall has also increased (USGS, unpublished data; Figure 1). This change in polar bear ecology has relevance for human-bear interactions, subsistence harvest, prevalence of defense kills, and disturbance associated with existing land-based development [e.g., National Petroleum Reserve of Alaska (NPRA), Arctic National Wildlife Refuge (ANWR)], Native Alaskan communities, recreation (ANWR) and tourism (e.g., bear viewing in Kaktovik, AK). These activities have the potential to impact, in new ways, the status of the entire SB population. Concomitantly, the change in polar bear ecology will impact these human activities, and a base-line characterization of this phenomenon can better inform mitigation (e.g., industry permitting under the Endangered Species Act and Marine Mammal Protection Act). In this study we aim to characterize the demography, habitat-use, and aspects of foraging ecology and health of polar bears spending fall on land. The SB population is characterized by a divergent-sea ice ecology, where polar bears typically spend most of the year on the sea-ice, even as the pack ice retreats northward, away from the coast, to its minimal extent in September (Amstrup et al. 2008; Durner et al. 2009). From 2000 &ndash; 2005, using coastal aerial surveys, Schliebe et al. (2008) observed between 3.7 and 8% of polar bears from SB (~ 60 &ndash; 120 of 1526, Regher et al. 2006) on land during the autumn. Sighting probability was not estimated in these surveys, and therefore the numbers represent minimum numbers of bears on land. Our analysis of USGS data suggest an annual average of 15% (&plusmn; 3%, SE) of polar bears satellite-tagged on the spring-time sea ice (total n = 18 of 124 satellite tags, 2003 &ndash; 2009) come to land during July &ndash; October. Based on these data, and an assumption that bears satellite-tagged on the spring time sea ice are representative of the entire SB population of independent bears, there would be an average of 230 bears on land each fall. In contrast to the SB population, in five of the world&rsquo;s 19 polar bear populations (Obbard et al. 2010), polar bears spend significant periods of time on land (1 &ndash; 5 months) when ice completely melts. In these seasonal-ice populations (Amstrup et al. 2008), polar bears are largely in a hypophagic condition (e.g., Hobson et al. 2009), relying on fat stores from the spring hyperphagic season, when ringed seals (Phoca hispida) pup. In general, these seasonal-ice populations are demographically productive (Taylor et al. 2005), although recently an increase in the ice-free season has resulted in a population decline in western Hudson Bay (Stirling et al. 1999; Regehr et al. 2007). There have been measured declines in the body condition and productivity of polar bears in SB, and changes in these parameters have been linked to declining optimal ice habitat (e.g., Durner et al. 2009; Regehr et al. 2010). We do not understand the relationship between land-use and the overall status of the population. Individual polar bears that use land may have increased or decreased fitness, in comparison to polar bears that remain on ice in the autumn. This project, which focuses on the biology of animals that spend time on-shore, will help address this question. This project is funded by the Bureau of Ocean Energy Management (BOEM) under Agreement No. M09PG00025 and the USGS Outer Continental Shelf Program (OCS) for FY 2009-2014. Parts of this study are also funded by US Fish and Wildlife Service, Office of Marine Mammals Management; the Bureau of Land Management; and the North Slope Borough, Department of Wildlife Management. This report is comprehensive, describing results for achieving the overlap

Beaufort Sea, Chukchi Sea↗

Strategic Plan for the North American Breeding Bird Survey: 2006-2010

Executive Summary The mission of the North American Breeding Bird Survey (BBS) is to provide scientifically credible measures of the status and trends of North American bird populations at continental and regional scales to inform biologically sound conservation and management actions. Determining population trends, relative abundance, and distributions of North American avifauna is critical for identifying conservation priorities, determining appropriate conservation actions, and evaluating those actions. The BBS program, jointly coordinated by the U.S. Geological Survey and Environment Canada’s Canadian Wildlife Service, provides the U.S. and Canadian Federal governments, state and provincial agencies, other conservation practitioners, and the general public with science-based avian population trend estimates and other information for regional and national species’ population assessments. Despite the demonstrated value of the BBS for furthering avian conservation across North America, its importance is often underappreciated, and it is underfunded compared with many other government-supported programs that report on status of the environment. Today, BBS resources, adjusted for inflation, are below the amount allocated in the 1970s and are still only sufficient to support two biologists. Yet the number of routes, participants, data, and data requests has quadrupled. Data and information management and delivery requirements and security concerns, non-existent in 1966, impose further demands on BBS resources. In addition, the Mexican expansion of the BBS offers new hope for a truly continental approach to avian conservation, but also brings additional challenges. Meeting the goals of this plan will take cooperation among myriad stakeholders; yet, even with collaboration, most objectives of this plan will be unattainable if BBS program support is not increased. The BBS developed this strategic plan to help set priorities and identify resources required for the program to continue to meet the evolving needs of the conservation community for information on bird population change. By setting clear goals, strategies, and measures of success, this plan provides a cohesive framework and vision for maintenance and development of the BBS. The plan identifies two major goals for the BBS, with a number of strategies and objectives to achieve these goals. Over the next 5 years, progress made in addressing each long-term goal and its associated 5-year strategies and objectives will gage the plan’s success. Specific actions, projected outcomes, and measures of success related to accomplishing these are outlined in Table 1, with a timeline in Table 2. The two main goals for the program, with a summary of the strategies to achieve them, are: Goal 1: Collect scientifically credible measures of the status and trends of North American bird populations at continental and regional scales. The North American Breeding Bird Survey will continue to support North American natural resource conservation through the collection of scientifically credible measures of the status and trends of continental bird populations. While doing this, the BBS will work to improve the science behind the program to better meet its mission and the changing needs of the avian conservation community. In partnership with collaborators, the BBS will address detection probability bias and habitat bias, improve analytical methods, and more fully assess and account for observer quality. Moreover, the BBS will improve the quality and breadth of avian population data through strategic increases in route density and the establishment of a Mexican BBS program. Goal 2: Ensure BBS data and analytical results are widely available and easily accessible for use by the avian conservation and management communities. At the heart of the BBS lies a four-million-record database containing more than 40 years of data on more than 600 bird species. These data are of no value if not well maintained, appropriately analyzed, and widely and easily accessible. The USGS has greatly improved data management and accessibility in recent years. Trend estimates were first made available via the Internet in the mid-1990s, followed closely by the raw data with baseline metadata and standard operating procedures. Nevertheless, numerous enhancements to data management and the usability of BBS results will greatly improve the ability of the BBS to serve avian conservation goals. The BBS needs to ensure that BBS data and results presented on the web site use the best data-management practices and statistical methods, with adequate documentation for users to understand them and any differences between different trend estimates. Moreover, the BBS needs to increase communication with BBS partners and stakeholders to ensure that it continues to meet the avian population status and trends needs of the conservation community and to encourage the development of new products. Working with collaborators, the BBS will develop tools for integrating environmental parameters like habitat change into the analyses, and for integrating BBS data with other avian survey results. In addition, the BBS will continue to improve data and database management through the incorporation of additional data and data fields, such as georeferenced stop locations and more complete metadata for the raw data and results, thus enhancing the uses that can be made of the data.

Circular↗

Vascular Plant and Vertebrate Inventory of Tumacacori National Historical Park

Executive Summary This report summarizes the results of the first comprehensive biological inventory of Tumacacori National Historical Park (NHP) in southern Arizona. These surveys were part of a larger effort to inventory vascular plants and vertebrates in eight National Park Service units in Arizona and New Mexico. From 2000 to 2003 we surveyed for vascular plants and vertebrates (fish, amphibians, reptiles, birds, and mammals) at Tumacacori NHP to document presence of species within the administrative boundaries of the park's three units. Because we used repeatable study designs and standardized field techniques, these inventories can serve as the first step in a long-term monitoring program. We recorded 591 species at Tumacacori NHP, significantly increasing the number of known species for the park (Table 1). Species of note in each taxonomic group include: * Plants: second record in Arizona of muster John Henry, a non-native species that is ranked a 'Class A noxious weed' in California; * Amphibian: Great Plains narrow-mouthed toad; * Reptiles: eastern fence lizard and Sonoran mud turtle; * Birds: yellow-billed cuckoo, green kingfisher, and one observation of the endangered southwestern willow flycatcher; * Fishes: four native species including an important population of the endangered Gila topminnow in the Tumacacori Channel; * Mammals: black bear and all four species of skunk known to occur in Arizona. We recorded 79 non-native species (Table E.S.1), many of which are of management concern, including: Bermudagrass, tamarisk, western mosquitofish, largemouth bass, bluegill, sunfish, American bullfrog, feral cats and dogs, and cattle. We also noted an abundance of crayfish (a non-native invertebrate). We review some of the important non-native species and make recommendations to remove them or to minimize their impacts on the native biota of the park. Based on the observed species richness, Tumacacori NHP possesses high biological diversity of plants, fish, and birds for a park of its size. This richness is due in part to the ecotone between ecological provinces (Madrean and Sonoran), the geographic distribution of the three units (23 km separates the most distant units), and their close proximity to the Santa Cruz River. The mesic life zone along the river, including rare cottonwood/willow forests and adjacent mesquite bosque at the Tumacacori unit, is representative of areas that have been destroyed or degraded in many other locations in the region. Additional elements such as the semi-desert grassland vegetation community are also related to high species richness for some taxonomic groups. This report includes lists of species recorded by us (or likely to be recorded with additional effort) and maps of study sites. We also suggest management implications and ways to maintain or enhance the unique biological resources of Tumacacori NHP: limit development adjacent to the park, exclude cattle and off-road vehicles, develop an eradication plan for non-native species, and hire a natural resource specialist. These recommendations are intended to assist park staff with addressing many of the goals set out in their most recent natural resources management plan. This study is the first step in a long-term process of compiling information on the biological resources of Tumacacori NHP and its surrounding areas, and our findings should not be viewed as the final authority on the plants and animals of the park. Therefore, we also recommend additional inventory and monitoring studies and identify components of our effort that could be improved upon, either through the application of new techniques (e.g., use of genetic markers) or by extending the temporal and/or spatial scope of our research.

Open-File Report↗

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↗

Vascular Plant and Vertebrate Inventory of Gila Cliff Dwellings National Monument

Executive Summary This report summarizes the results of the first comprehensive biological inventory of Gila Cliff Dwellings National Monument (NM) in western New Mexico. This project was part of a larger effort to inventory plants and vertebrates in eight National Park Service units in Arizona and New Mexico. Our surveys address many of the objectives that were set forth in the monument's natural resource management plan almost 20 years ago, but until this effort, those goals were never accomplished. From 2001 to 2003 we surveyed for vascular plants and vertebrates (amphibians, reptiles, birds, and mammals) at Gila Cliff Dwellings NM to document presence of species within the boundaries of the monument. For all taxonomic groups that we studied, we collected 'incidental' sightings on U.S. Forest Service lands adjacent to the monument, and in a few cases we did formal surveys on those lands. Because we used repeatable study designs and standardized field techniques, these inventories can serve as the first step in a biological monitoring program for Gila Cliff Dwellings NM and surrounding lands. We recorded 552 species at Gila Cliff Dwellings NM and the surrounding lands (Table 1). We found no non-native species of reptiles, birds, or mammals, one non-native amphibian (American bullfrog), and 33 non-native plants. Particularly on lands adjacent to the monument we found that the American bullfrog was very abundant, which is a cause for significant management concern. Species of non-native plants that are of management concern include red brome, bufflegrass, and cheatgrass. For a park unit of its size and geographic location, we found the plant and vertebrate communities to be fairly diverse; for each taxonomic group we found representative species from a wide range of taxonomic orders and/or families. The monument's geographic location, with influences from the Rocky Mountain, Chihuahuan Desert, and Madrean ecological provinces, plays an important role in determining the species richness at the monument. Also important is the wide range of conditions at the site. The diversity of plants results from a wide variety of soil types and aspects (from the cool, moist Cliff Dweller Canyon to dry mesa slopes) and an abundance of water from the West Fork of the Gila River. In turn, the vertebrate communities respond to this diversity of vegetation, topography, and microsites. For example, for each taxonomic group we found species that were only associated with a single community type, most often the riparian areas along the West and Middle forks of the Gila River. We found cause for significant concern with regard to loss of species in the last few decades. One species of amphibian (Chiricahua leopard frog) is certainly extirpated from the area. Three other species of amphibians (Mexican spadefoot, Woodhouse's toad, and red-spotted toad), reported as being 'common' in the area in 1971, were not found during our surveys. In addition, we did not find three species of rodents that were found in 1965: silky pocket mouse, Ord's kangaroo rat, and southern grasshopper mouse. The monument's aquatic vertebrate component, in particular, may be at a critical juncture whereby other species, such as gartersnakes, may be poised for extirpation. Declining abundance of native fish species has been demonstrated from long-term monitoring of these communities along the Middle Fork of the Gila River. This report includes lists of species recorded by us or species likely to be recorded with additional survey effort. It also includes management implications from our work - how the monument staff might better maintain or enhance the unique biological resources of the monument. This study is the first step in a long-term process of compiling information on the biological resources of the monument and its surrounding areas. We recommend additional inventory and monitoring studies and identify components of our effort that could be improved upon

Open-File Report↗

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗

Groundwater/surface-water interactions in the Bad River Watershed, Wisconsin

A groundwater-flow model was developed for the Bad River Watershed and surrounding area by using the U.S. Geological Survey (USGS) finite-difference code MODFLOW-NWT. The model simulates steady-state groundwater-flow and base flow in streams by using the streamflow routing (SFR) package. The objectives of this study were to: (1) develop an improved understanding of the groundwater-flow system in the Bad River Watershed at the regional scale, including the sources of water to the Bad River Band of Lake Superior Chippewa Reservation (Reservation) and groundwater/surface-water interactions; (2) provide a quantitative platform for evaluating future impacts to the watershed, which can be used as a starting point for more detailed investigations at the local scale; and (3) identify areas where more data are needed. This report describes the construction and calibration of the groundwater-flow model that was subsequently used for analyzing potential locations for the collection of additional field data, including new observations of water-table elevation for refining the conceptualization and corresponding numerical model of the hydrogeologic system. The study area can be conceptually divided into three primary hydrogeologic environments. The first encompasses the southern uplands with relatively low topographic relief, where groundwater-flow is unconfined and occurs primarily in sandy till and glacial outwash overlying Archean-aged crystalline bedrock. The second includes a transitional area of higher topographic relief and shallow depth to bedrock, in the vicinity of ridges formed by steeply dipping, early-Proterozoic aged metasedimentary units of the Marquette Range Supergroup (including the Ironwood Formation), and late-Proterozoic igneous units associated with the Midcontinent Rift System (MRS). Groundwater-flow in this area likely occurs primarily through connected networks of bedrock fractures that are not well characterized, and also in isolated pockets of Quaternary deposits. The third and last hydrogeologic environment includes lowlands along Lake Superior where a deep sandstone aquifer is confined by thick deposits of clay-rich till. Model input was compiled by using both published and unpublished data. Constant flux boundary conditions for the model perimeter were developed from a regional analytic element model described in appendix 1 of this report. Pumping from 26 high-capacity wells within the model area was included. The SFR stream network was developed from the National Hydrography Dataset (NHDPlus Version 2) and hydrography from the Wisconsin Department of Natural Resources (WDNR). Hydraulic conductivity values were determined for each model cell by interpolation from a network of pilot points, within zones representing major hydrogeologic units. Recharge to the groundwater system was estimated on a cell-by-cell basis by using the Soil Water Balance code (SWB), with gridded daily temperature and precipitation data for the period 1980&ndash;2011, and GIS coverages of soil and land-surface conditions. Estimated recharge varies considerably, following spatial patterns in the precipitation and soil hydrologic group inputs. The lowest recharge values occur in the Superior lowlands, whereas the highest values occur in the upland areas, especially those underlain by sandy soils, and in the vicinity of bedrock hills. The model was calibrated to groundwater-levels and base flows obtained from the USGS National Water Information System (NWIS) database, and groundwater-levels obtained from the WDNR and Band River Band well-construction databases. Calibration was performed via nonlinear regression by using the parameter-estimation software suite PEST. Groundwater levels and base-flow observations in the calibration dataset were well simulated by the calibrated model, with reasonable values of hydraulic conductivity. The pilot-point parameters that were most constrained by observations during model calibration coincided with the locations containing the most wells (head observations)&mdash;especially the population centers of Ashland, Mellen, and other communities along the major highway corridors. Results from the calibrated model illustrate differences in the nature of groundwater-flow within the watershed. In the southern part of the watershed, where bedrock is shallow, groundwater flow paths are relatively short, extending from local recharge areas to adjacent first and second-order streams. In contrast, laterally continuous deposits of clay-rich till covering the Superior Lowlands isolate most smaller streams from the sandstone aquifer, allowing for longer flow paths toward larger streams such as the Bad, Marengo, and White Rivers. Approximately three-quarters of all first-order stream cells were dry in the Superior Lowlands, compared to only half of first-order stream cells in the southern bedrock uplands. The model was used to delineate the groundwatershed for the Bad and Kakagon Rivers. &ldquo;Groundwatershed&rdquo; is defined as the area contributing groundwater discharge to one of these streams and their tributaries. The groundwatershed was found to align closely with the surface-watershed, with the most notable exception occurring along the southwestern half of Birch Hill, where surface water drains southwest towards the Potato River, and groundwater flows north and east towards Lake Superior. Similarly, the contributing area of groundwater-flow to the Reservation was delineated. Results indicate the off-Reservation groundwater contributing area to be limited in comparison to the extent of the watershed, extending southward into the highlands underlain by MRS igneous rock units, but not further into the area underlain by the Marquette Range Supergroup. Stable isotope samples were collected from 54 wells within the watershed, to investigate sources of groundwater. Oxygen-18 (&delta; 18 O) values lower than -13.0 per mil were documented in the sampling, and likely indicate the presence of recharge water from the last glacial period (>9,500 years old) beneath the northern portion of the Reservation, in the vicinity of Odanah, Wisconsin. Finally, a new data-worth analysis of potential new monitoring-well locations was performed by using the model. The relative worth of new measurements was evaluated based on their ability to increase confidence in model predictions of groundwater levels and base flows at 35 locations, under the condition of a proposed open-pit iron mine. Results of the new data-worth analysis, and other inputs and outputs from the Bad River model, are available through an online dynamic web mapping service at ( http://wim.usgs.gov/badriver/ ).

Wisconsin↗

Using advanced population genomics to better understand the relationship between offshore and spawning habitat use for Atlantic Sturgeon

Atlantic Sturgeon ( Acipenser oxyrinchus oxyrinchus ) are a large-bodied anadromous fish that historically supported important fisheries along the east coast of the United States. Following years of overharvest and habitat degradation, populations experienced severe declines. In 2012, the National Marine Fisheries Service listed Atlantic Sturgeon under the Endangered Species Act (ESA; 61 FR 4722). Their listing named five Distinct Population Segments (DPSs), predicated on genetic groups composed of geographically proximate populations. Federal management of Atlantic Sturgeon presents challenges, as sturgeon from each of the five DPSs mix extensively in coastal and marine habitats yet take and recovery progress must be evaluated separately for each unit. Genetic assignment testing based on mitochondrial and microsatellite markers allows individuals to be assigned back to their natal river and DPS. However, this approach is not perfect and some individuals may be incorrectly assigned. Recent advances in genomics offer the potential of a higher resolution approach to genetic assignment testing, and thus may reduce uncertainty associated with assignment testing. In addition, genomics allows a greater number of markers to be examined from across a broader portion of the sturgeon genome, thus may provide an enhanced perspective of population structure for the species, and potentially allow other previously intractable questions to be addressed (Bernatchez et al. 2017, Supple and Shapiro 2018). We used next-generation sequencing to develop a draft genome for Atlantic Sturgeon and identify single nucleotide polymorphisms (SNPs) that could be used to resolve the natal river and DPS of individual Atlantic Sturgeon. We identified 1,210 candidate SNPs within the nuclear genome as well as 49 SNPs within the mitochondrial genome. After filtering and review, we selected 161 nuclear SNPs and 39 mitochondrial SNPs for further testing and evaluation. We used genotyping-in-thousands by sequencing (GT-seq) to simultaneously sequence nuclear SNP loci, mitochondrial SNP loci, and the existing panel of twelve microsatellite loci. This effort required a pilot sequencing run on a single sturgeon sample to test marker amplification and refine primer strengths, followed by a series of sequencing runs to generate baseline data for 288 individuals representing nine populations of Atlantic Sturgeon in four DPSs. Using baseline data from the nine populations, we ran a series of genomic analyses to characterize diversity within and among populations, providing a benchmark for this species using the new SNP markers. Allelic richness was similar for all populations, although there was a general trend of more northern population containing greater levels of allelic richness. Interestingly, we observed linkage disequilibrium among many pairs of loci within many populations. This might be the result of physical linkage but could also suggest these populations are recovering from genetic bottlenecks and/or are effectively small, leading to specific haplotypes to be favored by chance. Pairwise differentiation among populations varied among the populations ( F ST range: 0.010-0.098) and was significantly correlated ( r = 0.771; P < 0.001) to pairwise F ST observed using microsatellite markers). Population clustering and ordination techniques using the new genomic data both support an overall population structure that is similar to the current DPS management units (which were developed primarily based on microsatellite genetic data). Overall, this suggests that existing microsatellite markers and the panel of SNP markers developed in this study provide similar information about the populations structure and ecology of Atlantic Sturgeon. Given the observed differences in allele frequencies among populations, our genomic baseline supports previous assertations that Atlantic Sturgeon show natal homing, despite mixing extensively in marine waters during non-breeding periods. Lower levels of differentiation between populations in the South Atlantic DPS suggest that populations in this region may have greater levels of gene flow relative to their more northerly conspecifics, which has also previously been suggested based on microsatellite data. The observed differentiation among populations provides the necessary foundation for determining the natal river and DPS of Atlantic Sturgeon using assignment testing. We tested the utility of our new genomic baseline for resolving the population and DPS of Atlantic Sturgeon. Our nuclear SNP markers showed utility for identifying the origin of unknown Atlantic Sturgeon samples, as 86.5% were assigned to the correct DPS and 66.3% were assigned to the correct natal river. However, since this study was funded the Conservation Genetics and Genomics Laboratory at Leetown Science Center has made significant improvements to their microsatellite genetic baseline, which now performs more effectively than our new genomic approach (the genetic baseline includes 12 populations and 5 DPSs, and correctly assigns 95.8% of individuals to DPS and 84.9% of individuals to their natal population using 12 microsatellite loci). We conducted an ad hoc exploration of how additional microsatellite or nuclear SNP loci may further improve the accuracy of assignment testing. We found that additional microsatellite markers are likely to result in greater improvements in assignment efficiency than additional nuclear SNPs. However, a much larger number of SNP loci (which if identified could be sequenced using other methods that are now available; e.g., the RAD-capture approach published by Ali et al. 2016) could produce assignment efficiencies that are greater than what is currently feasible using microsatellites. In the absence of further research and development of additional SNP markers for Atlantic Sturgeon (possibly using an approach other than GT-seq), the existing microsatellite loci are the most effective means available to determine the natal river and DPS of Atlantic Sturgeon encountered in offshore waters. Because our new genomic markers were less effective than the existing panel of 12 microsatellite markers, we chose to use the existing microsatellite markers to assign Atlantic Sturgeon captured in another BOEM-funded study (cooperative agreement M16AC00003; Monitoring endangered Atlantic Sturgeon and commercial finfish habitat use offshore New York) following consultation with our project officer. Using this approach, we genotyped and assigned 186 Atlantic Sturgeon captured in coastal waters off the Rockaway Peninsula, New York. The vast majority of these sturgeon were assigned to the New York Bight DPS (94.62%), and most appear to belong to the Hudson River population (87.10%) with smaller contributions from the Delaware River population (7.53%). Smaller contributions (2.15%) were observed from six other populations, including those from the James, York, Kennebec, Ogeechee, and Edisto rivers. Although most of the fish we assigned were assigned to the nearest spawning rivers (Hudson and Delaware), the contributions from distant rivers is consistent with the propensity of this species to move long distances and form mixed stock aggregations along the continental shelf. This finding indicates that spawning populations (and their corresponding DPS) from distant locations may potentially be impacted by offshore activities. In fact, activities in this region of the New York Bight could negatively impact Atlantic Sturgeon population from at least four different DPSs. Genetic or genomic assignment testing remains an essential tool to characterize potential impacts to Atlantic Sturgeon populations and should be applied more broadly to better characterize potential impacts of activities in other locations.

Atlantic Coast↗

Data compilation and assessment for water resources in Pennsylvania state forest and park lands

As a result of a cooperative study between the U.S. Geological Survey and the Pennsylvania Department of Conservation and Natural Resources (PaDCNR), available electronic data were compiled for Pennsylvania state lands (state forests and parks) to allow PaDCNR to initially determine if data exist to make an objective evaluation of water resources for specific basins. The data compiled included water-quantity and water-quality data and sample locations for benthic macroinvertebrates within state-owned lands (including a 100-meter buffer around each land parcel) in Pennsylvania. In addition, internet links or contacts for geographic information system coverages pertinent to water-resources studies also were compiled. Water-quantity and water-quality data primarily available through January 2007 were compiled and summarized for site types that included streams, lakes, ground-water wells, springs, and precipitation. Data were categorized relative to 35 watershed boundaries defined by the Pennsylvania Department of Environmental Protection for resource-management purposes. The primary sources of continuous water-quantity data for Pennsylvania state lands were the U.S. Geological Survey (USGS) and the National Weather Service (NWS). The USGS has streamflow data for 93 surface-water sites located in state lands; 38 of these sites have continuous-recording data available. As of January 2007, 22 of these 38 streamflow-gaging stations were active; the majority of active gaging stations have over 40 years of continuous record. The USGS database also contains continuous ground-water elevation data for 32 wells in Pennsylvania state lands, 18 of which were active as of January 2007. Sixty-eight active precipitation stations (primarily from the NWS network) are located in state lands. The four sources of available water-quality data for Pennsylvania state lands were the USGS, U.S. Environmental Protection Agency, Pennsylvania Department of Environmental Protection (PaDEP), and the Susquehanna River Basin Commission. The water-quality data, which were primarily collected after 1970, were summarized by categorizing the analytical data for each site into major groups (for example, trace metals, pesticides, major ions, etc.) for each type (streams, lakes, ground-water wells, and springs) of data compiled. The number of samples and number of detections for each analyte within each group also were summarized. A total of 410 stream sites and 205 ground-water wells in state lands had water-quality data from the available data sets, and these sites were well-distributed across the state. A total of 107 lakes and 47 springs in state lands had water-quality data from the available data sets, but these data types were not well-distributed across the state; the majority of water-quality data for lakes was in the western or eastern sections of the state and water-quality data for springs was primarily located in the central part of the Lower Susquehanna River Valley. The most common types of water-quality data collected were major ions, trace elements, and nutrients. Physical parameters, such as water temperature, stream discharge, or water level, typically were collected for most water-quality samples. Given the large database available from PaDEP for benthic macroinvertebrates, along with some data from other agencies, there is very good distribution of benthic-macroinvertebrate data for state lands. Benthic macroinvertebrate samples were collected at 1,077 locations in state lands from 1973 to 2006. Most (980 samples) of the benthic-macroinvertebrate samples were collected by PaDEP as part of the state assessment of stream conditions required by the Clean Water Act. Data compiled in this report can be used for various water-resource issues, such as basin-wide water-budget analysis, studies of ecological or instream flow, or water-quality assessments. The determination of an annual water budget in selected basins is best supported by the availab

Pennsylvania↗

Occurrence of selected radionuclides in ground water used for drinking water in the United States: A reconnaissance survey, 1998

The U.S. Geological Survey, in collaboration with the U.S. Environmental Protection Agency, the American Water Works Association, and the American Water Works Service Company, completed a targeted national reconnaissance survey of selected radionuclides in public ground-water supplies. Radionuclides analyzed included radium-224 (Ra-224), radium-226 (Ra-226), radium-228 (Ra-228), polonium-210 (Po-210) and lead-210 (Pb-210).This U.S. Geological Survey reconnaissance survey focused intentionally on areas with known or suspected elevated concentrations of radium in ground water to determine if Ra-224 was also present in the areas where other isotopes of radium had previously been detected and to determine the co-occurrence characteristics of the three radium isotopes (Ra-224, Ra-226, and Ra-228) in those areas. Ninety-nine raw-water samples (before water treatment) were collected once over a 6-month period in 1998 and 1999 from wells (94 of which are used for public drinking water) in 27 States and 8 physiographic provinces. Twenty-one of the 99 samples exceeded the current U.S. Environmental Protection Agency drinking-water maximum contaminant level of 5 picocuries per liter (pCi/L) for combined radium (Ra-226 + Ra-228). Concentrations of Ra-224 were reported to exceed 1 pCi/L in 30 percent of the samples collected, with a maximum concentration of 73.6 pCi/L measured in water from a nontransient, noncommunity, public-supply well in Maryland. Radium-224 concentrations generally were higher than those of the other isotopes of radium. About 5 percent of the samples contained concentrations of Ra-224 greater than 10 pCi/L, whereas only 2 percent exceeded 10 pCi/L for either Ra-226 or Ra-228. Concentrations of Ra-226 greater than 1 pCi/L were reported in 33 percent of the samples, with a maximum concentration of 16.9 pCi/L measured in water from a public-supply well in Iowa. Concentrations of Ra-228 greater than 1 pCi/L were reported in 22 samples, with a maximum concentration of 72.3 pCi/L measured in water from a non-transient, noncommunity, public-supply well in Maryland.Radium-224, which is a decay product of Ra-228 in the Th-232 decay series, was significantly correlated with Ra-228 (Spearman?s rank correlation coefficient ?r? equals 0.82) and to a lesser degree with Ra-226 (r equals 0.69), which is an isotope in the U-238 decay series. The rank correlation coefficient between Ra-226 and Ra-228 was 0.63. The high correlation between Ra-224 and Ra-228 concentrations and the corresponding isotopic ratios of the two (about 1:1 in 90 percent of the samples) indicates that the two radionuclides occur in approximately equal concentrations in most ground water sampled. Thus, Ra-228 can be considered as a reasonable proxy indicator for the occurrence of Ra-224 in ground water.The maximum concentration of Po-210 was 4.85 pCi/L and exceeded 1 pCi/L in only two samples. The maximum concentration of Pb-210 was 4.14 pCi/L, and about 10 percent of the samples exceeded 1 pCi/L. Areas with known, or suspected, elevated concentrations of polonium and lead were not targeted in this survey.Three major implications are drawn for future radionuclide monitoring on the basis of this information: (1) grossalpha particle analyses of ground water should be done within about 48-72 hours after collection to determine the presence of the short-lived, alpha-particle emitting isotopes, such as Ra-224, which was detected in elevated concentrations in many of the samples collected for this survey; (2) the isotope ratios of Ra-224 to Ra-228 in ground water are variable on a national scale, but the two radioisotopes generally occur in ratios near 1:1, therefore, the more commonly measured Ra-228 can be used as an indicator of Ra-224 occurrence for some general purposes other than compliance; and (3) the isotopic ratios of Ra-226 to Ra-228 were less than 3:2 in many samples. These ratios corroborate results of previous studies that have shown the presence of Ra-228.

Water-Resources Investigations Report↗

Adaptive management framework and decision support tool for invasive annual bromes in seven Northern Great Plains National Park Service units

National Park Service (NPS) units in the northern Great Plains (NGP) were established to preserve and interpret the history of the United States, 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 northern mixed-grass prairie, which not only provides background scenery and habitat but is the 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. Cheatgrass ( Bromus tectorum ) and Japanese brome ( Bromus japonicus )—collectively referred to as “annual bromes”—are of particular concern because of their documented increase through time, and their association with lower native plant diversity, in NGP parks. A variety of grazing, herbicide-application, and prescribed-fire experiments have shown promising short-term results for controlling annual bromes in research-scale plots in the NGP, but it is unclear whether these management actions will be as effective at the larger spatial and longer temporal scales relevant to park management. When uncertainties about the effectiveness of different management actions cannot be answered with traditional research approaches in time to prevent resource degradation, yet recurrent management decisions must be made, an adaptive management approach may be appropriate. Thus, in 2017, we began to develop the ABAM—Annual Brome Adaptive Management—framework. The aim of this framework is to reduce uncertainties about methods for controlling annual bromes in seven NGP parks through a formal process of learning from the application of on-going management. A uniform framework across seven parks provides greater opportunities for reducing these uncertainties compared to a single park acting alone or to multiple parks using different adaptive management frameworks. This technical report details the development and expected implementation of the ABAM framework. After briefly introducing the issue (Section 1) and describing the context in which the framework was developed (Section 2), the report describes how a structured decision-making process was used to frame the problem, determine concrete objectives, and decide the alternative actions for achieving those objectives that the framework would be designed around (Section 3). Then the report describes the process used to develop the ABAM decision support system (Section 4). At the core of this system is the ABAM decision support tool, a Bayesian decision network built on nearly two decades of vegetation monitoring data from NGP parks, as well as current literature and ABAMspecific experiments. This tool, referred to as the ABAM model by its intended users, is built to work with the existing vegetation monitoring, prescribed fire, and invasive plant management programs that support the seven ABAM parks. In Section 5, the report describes how output from the ABAM model is produced and used in annual vegetation management decision making. It describes the ABAM R package (Baldwin et al. 2021) and an example R script that leads a user through an annual workflow using the model and the package. This workflow updates the model with information from new monitoring events following management actions of prescribed fire, herbicide application, or a combination thereof. With the updated model, data describing the current condition of vegetation in park management units, and current data for environmental factors included in the model (soil texture, slope, weather, and grazing), the user then runs the model to predict future vegetation conditions—and managers’ happiness with the outcome—in response to each of 10 management actions for each management unit in each park. These predictions inform managers’ decisions regarding locations and types of management actions to apply in the upcoming year. The ABAM framework is in its infancy, and the report concludes (Section 6) with a discussion of its longer-term viability. Successful adaptive management requires commitment for the long term, likely decades. Currently, the predictions of the decision support tool are not expected to be highly accurate, but they ideally will improve over time as more management actions are applied and their outcomes are captured by monitoring. We designed the ABAM decision support tool to work with the existing management and monitoring resources in ABAM parks to maximize the sustainability of the model’s use, but the ABAM framework requires more than the model. Because this application of an adaptive management framework supported by a quantitative decision support tool to guide vegetation management is unique within the NPS (to our knowledge), institutional knowledge and mechanisms for long-term implementation of the ABAM framework do not exist within the agency. Additionally, the ABAM model and the data that inform it could be improved in a variety of ways. Thus, this report concludes with a discussion of ways to both sustain and improve upon the work completed so far.

Montana, Nebraska, South Dakota, Wyoming↗

Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state

Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.

Louisiana↗

Ecology of Greater Sage-Grouse in the Bi-State Planning Area Final Report, September 2007

Conservation efforts for greater sage-grouse (Centrocercus urophasianus), hereafter sage-grouse, are underway across the range of this species. Over 70 local working groups have been established and are implementing on-the-ground sage-grouse oriented conservation projects. Early on in this process, the California Department of Fish and Game (CDFG) recognized the need to join in these efforts and received funding from the U.S. Fish and Wildlife Service (USFWS) under the Candidate Species Conservation Program to help develop a species conservation plan for sage-grouse in the Mono County area. This conservation plan covers portions of Alpine, Mono, and Inyo counties in California and Douglas, Esmeralda, Lyon, and Mineral counties in Nevada. A concurrent effort underway through the Nevada Governor's Sage-grouse Conservation Team established Local Area Working Groups across Nevada and eastern California. The Mono County populations of sage-grouse were encompassed by the Bi-State Local Planning Area, which was comprised of six population management units (PMUs). The state agencies from California (CDFG) and Nevada (Nevada Department of Wildlife; NDOW) responsible for the management of sage-grouse agreed to utilize the process that had begun with the Nevada Governor's Team in order to develop local plans for conservation planning and implementation. Resources from the USFWS were applied to several objectives in support of the development of the Bi-State Local Area Sage-grouse Conservation Plan through a grant to the U.S. Geological Survey (USGS). Objectives included: (1) participate in the development of the Bi-State Conservation Plan, (2) compile and synthesize existing sage-grouse data, (3) document seasonal movements of sage-grouse, (4) identify habitats critical to sage-grouse, (5) determine survival rates and identify causal factors of mortality, (6) determine nest success and brood success of sage-grouse, and (7) identify sage-grouse lek sites. Progress reports completed in 2004 and 2005 addressed each of the specific objectives and this final report focuses on the biological information gathered in support of local conservation efforts. Participation in the development of the Bi-State Local Area Conservation Plan was accomplished on multiple scales. Beginning in the fall of 2002, USGS personnel began participating in meetings of local stakeholders involved in the development of a sage-grouse conservation plan for the Bi-State planning area. This included attendance at numerous local PMU group meetings and field trips as well as participating on the technical advisory committee (TAC) for the Bi-State group. Whenever appropriate, ongoing results and findings regarding sage-grouse ecology in the local area were incorporated into these working group meetings. In addition, the USGS partnered with CDFG to help reorganize one of the local PMU groups (South Mono) and edited that portion of the Bi-State plan. The USGS also worked closely with CDFG to draft a description of the state of knowledge for sage-grouse genetic information for inclusion in the Bi-State Conservation Plan. The first edition of the Bi-State Conservation Plan for Greater Sage-Grouse was completed in June 2004 (Bi-State Sage-grouse Conservation Team 2004). This report is organized primarily by PMU to facilitate the incorporation of these research findings into the individual PMU plans that compose the Bi-State plan. Information presented in this report was derived from over 7,000 radio-telemetry locations obtained on 145 individual sage-grouse during a three year period (2003-2005). In addition, we collected detailed vegetation measurements at over 590 habitat sampling plots within the study area including canopy cover, shrubs, forbs, and grasses diversity. Vegetation data collection focused on sage-grouse nests, and brood-use areas. Additionally we collected data at random sites to examine sage-grouse habitat relationships within the study area. The majori

Open-File Report↗

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗