Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Fish and Wildlife Technical Report”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

117 records · Page 7Linked to original sources
USGS2021

Habitat suitability index model improvement recommendations

As part of the model improvement effort for the 2023 Coastal Master Plan, the Habitat Suitability Index (HSI) models used during previous master plans were reevaluated to assess how the model relationships could be improved, and to determine what species should be included in the master plan analyses. This process considered the technical reviews, comments, and suggested improvements provided by model developers, advisory groups, and other experts during previous master plans. Reviews were then conducted to determine the availability of data and information that could be used to make model improvements. As a result of this effort, a recommended list of relevant species to model is provided, and HSI model improvements are recommended that are categorized by whether the suitability index (SI) relationship to be improved is statistical-based or literature-based. The species recommended to be included in the 2023 Coastal Master Plan analyses are: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. These species were selected because they represent a range of taxonomies, life histories, trophic levels, and habitats, and most are commercially- or recreationally-important in coastal Louisiana. Most of these species were also included in the 2017 Coastal Master Plan analyses, and the models used during that effort should be further improved. Seaside sparrow and bald eagle are new for the master plan, and new models should be developed for the analyses. The 2017 fish, shrimp, and blue crab HSI models included a water quality SI that was based on statistical analyses of species catch and environmental data collected by the Louisiana Department of Wildlife and Fisheries. As suggested during the 2017 Coastal Master Plan, the modeling approach used to develop the water quality SI was revisited and alternate modeling approaches were explored. Using literature and an evaluation of the general steps of model development, three components for HSI model improvement were identified, including 1) selecting alternative modeling approach(es); 2) detecting and resolving statistical issues; and 3) improving model fit and evaluation. Multiple options for each component were explored, which resulted in a proposed multi-step phased approach for model improvement. This proposed approach entails improving the generalized linear models used for the 2017 water quality SIs and then, if desired, comparing them to alternative model approaches (e.g., generalized additive models) to explore model performance and select the best approach to use for the 2023 Coastal Master Plan HSI models. All of the existing master plan HSI models include literature-based SIs, which use information from published studies of species-habitat associations to derive suitability relationships. Similar to previous master plans, these literature-based SIs should be updated and improved for the 2023 Coastal Master Plan using recent literature and new ecological knowledge. Preliminary reviews were conducted and recent information was found that could be used to improve the eastern oyster, crayfish, and potentially brown pelican HSI models; but no appropriate recent literature was located for improvement of the American alligator, gadwall, and mottled duck HSI models. However, it is recommended that the literature reviews and information searches be continued. In addition to the statistical-based water quality SI, the 2017 fish, shrimp, and blue crab HSI models also included a structural habitat SI that was based on literature showing high densities of these species in fragmented marsh. The relationship used for this SI, however, did not account for the effects of other estuarine habitats, such as submerged aquatic vegetation and oyster reefs, which are also important to these species. Therefore, a meta-analysis approach is proposed that would estimate the relative importance of these habitats for each species, and the results of this analysis could be used to calculate a new structural habitat SI for the 2023 Coastal Master Plan.

Report↗
USGS2013

Seventy-five years of science—The U.S. Geological Survey’s Western Fisheries Research Center

As of January 2010, 75 years have elapsed since Dr. Frederic Fish initiated the pioneering research program that would evolve into today’s Western Fisheries Research Center (WFRC). Fish began his research working alone in the basement of the recently opened Fisheries Biological Laboratory on Lake Union in Seattle, Washington. WFRC’s research began under the aegis of the U.S. Fish and Wildlife Service and ends its first 75 years as part of the U.S. Geological Survey with a staff of more than 150 biologists and support personnel and a heritage of fundamental research that has made important contributions to our understanding of the biology and ecology of the economically important fish and fish populations of the Nation. Although the current staff may rarely stop to think about it, WFRC’s antecedents extend many years into the past and are intimately involved with the history of fisheries conservation in the Western United States. Thus, WFRC Director Lyman Thorsteinson asked me to write the story of this laboratory “while there are still a few of you around who were here for some of the earlier years” to document the rich history and culture of WFRC by recognizing its many famous scientists and their achievements. This historyalso would help document WFRC’s research ‘footprint’ in the Western United States and its strategic directions. Center Director Thorsteinson concluded that WFRC’s heritage told by an emeritus scientist also would add a texture of legitimacy based on personal knowledge that will all-to-soon be lost to the WFRC and to the USGS. The WFRC story is important for the future as well as for historical reasons. It describes how we got to the place we are today by documenting the origin, original mission, and our evolving role in response to the constantly changing technical information requirements of new environmental legislation and organizational decision-making. The WFRC research program owes its existence to the policy requirements of Federal conservation legislation originating with the construction of Grand Coulee Dam in 1933. The research program was shaped by laws enacted in subsequent years such as the Federal Water Pollution Control Act (1972), National Environmental Policy Act (1973), Endangered Species Act (1974), and Northwest Power Planning Act (1980), to name only a few. The WFRC has not been constrained by direct management or regulatory responsibility for a particular fishery (such as providing sustainable catch limits data to a resource management structure). Thus, WFRC has been able to concentrate on scientific pursuits and information needs required by contemporary environmental legislation. Over the years, we have pioneered in several important areas of fisheries research including the diagnoses and control of diseases in economically important fish, effects of environmental alterations on the physiological quality and survival of Pacific salmon released from federal mitigation hatcheries, applications in biotelemetry, and the bioenergetics of predator-prey interactions in the Columbia River. The WFRC of today is a widely distributed organization in the Western United States. Knowledge of the historical connections and accomplishments of our predecessors is important beyond the sense of pride and unity it instills in the WFRC family of today. For example, a discerning reader will note the evolution of WFRC’s research from a single disciplinary focus (early era—hatchery disease problems), to multiple disciplines (middle to late era—species, populations, habitats; threatened and endangered species), to the present era (multidisciplinary and with increasing process focus). For the benefit of the current WFRC staff, more emphasis has been placed on the early years rather than on the present day because people are quite naturally more familiar with the recent past than with the research done during the first decades of WFRC’s existence. By every rational measure, the WFRC has evolved into a fisheries research organization well positioned to provide the biological information needed to support the continued conservation and management of our Nation’s living aquatic natural resources. The high standard of excellence that connects WFRC’s past to our present research program provides a firm foundation on which to base the work yet to be done. In another 75 years, WFRC will undoubtedly be a very different place than it is today, but its evolution will be forever rooted in the story of the research and of the people related here. More about the diverse fisheries research projects WFRC scientists are conducting today is available at WFRC’s website: http://wfrc.usgs.gov/.

Washington↗
USGS2021

Habitat suitability index model improvements

Habitat suitability index (HSI) models were developed for the 2023 Coastal Master Plan to evaluate the potential effects of coastal restoration and protection projects on habitat for key coastal fish, shellfish, and wildlife species. These species included: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. Most of these species were included in the 2017 Coastal Master Plan analyses, and the HSI models from that effort were refined and improved following the recommendations described in the technical memorandum: 2023 Coastal Master Plan Habitat Suitability Index Model Improvement Recommendations (Sable et al., 2019). In addition to model improvements, HSI models were created for seaside sparrow and bald eagle, both of which are new species for the master plan analyses. For the HSI models that are primarily literature-based, literature reviews were conducted for recent studies that could be used to improve the suitability index (SI) relationships that compose the models. As a result of this review, modifications were made to the salinity-related SIs of the oyster model including: expanding the time period used for salinity effects to spawning; adjusting the range of suitable annual average salinity to be more representative of Louisiana populations; and making oyster’s minimum salinity tolerance temperature dependent. In addition, a new SI was incorporated in the oyster HSI model that accounts for the effects of sediment deposition on oysters. The crayfish HSI model was improved by adjusting the time periods used for the SIs that describe the hydrology required for the crayfish life cycle, and the soil characteristics SI that was part of the 2017 crayfish model was removed because soil conditions do not appear to be limiting for crayfish burrow construction in coastal Louisiana. The other literature-based HSI models from the 2017 Coastal Master Plan, i.e., American alligator, gadwall, mottled duck, and brown pelican, were unchanged, with the exception of a small adjustment made to the suitability of forested wetlands for gadwall. Lastly, a literature-based HSI model was created for seaside sparrow that consists of SIs related to vegetated habitat type, marsh vegetation coverage, and marsh elevation. Statistical-based HSI models were developed for brown shrimp (both small and large juvenile stages), white shrimp (small and large juvenile stages), blue crab (juvenile stage), gulf menhaden (juvenile and adult stages), spotted seatrout (juvenile and adult stages), largemouth bass, and bald eagle. The bald eagle HSI model was developed from a bald eagle nest probability of occurrence model that related nest occurrence from survey data with land cover type. The resulting model showed that combinations of forested wetlands, flotant marsh, and open water habitats were most suitable for nesting bald eagles. The 2023 fish, shrimp, and blue crab HSI models were developed using new approaches for the formulation of the water quality and structural habitat SIs that compose the models. For the 2017 models, the water quality SI was derived using only generalized linear mixed models (GLMMs) to estimate the relationship between salinity, water temperature, and species’ catch. For the 2023 models, however, multiple GLMMs and generalized additive models (GAMMs) were created for each species or life stage. These alternative models were compared and a single model that performed well statistically and was ecologically reasonable was selected for the species’ water quality SI. The structural habitat SI was developed using a meta-analysis of published literature to estimate the relative importance of various estuarine habitats to the fish and shellfish species. The results of this analysis were then used to modify the 2017 structural habitat SI relationship to account for the added habitat value of submerged aquatic vegetation and oyster reefs, which are also important habitats for juvenile fish and shellfish. Similar to the 2017 fish, shrimp, and blue crab models, the water quality and structural habitat SIs were then combined to create the 2023 HSI models. The 2023 Coastal Master Plan HSI models were integrated with the Integrated Compartment Model (and are referred to as ICM-HSIs) and tested using environmental output from the 2017 Coastal Master Plan Future Without Action scenario. The tests showed that, in general, the models produced reasonable representations of species’ habitat distribution. Furthermore, the improvements made to the oyster, crayfish, fish, shrimp, and blue crab HSI models generally yielded more realistic results compared to the 2017 HSI models.

Report↗
USGS1987

Results of a workshop concerning assessment of the functions of bottomland hardwoods

The U.S. Environmental Protection Agency (EPA) is authorized under Section 404 of the Clean Water Act (33 U.S.C. 1344) to participate in the regulation of the discharge of dredged or fill material into waters of the United States. This regulatory authority is exercised in partnership with the U.S. Army Corps of Engineers, which has responsibility for permit issuance, and in consultation with the U.S. Fish and Wildlife Service and the National Marine Fisheries Service. Through amendments to the original statute, a series of legal actions and court decisions, and the development of operating guidance among the responsible agencies, Section 404 has evolved into the primary mechanism afforded Federal authorities for the protection of wetlands. EPA recognizes the importance of wetlands in achieving the goals of the Clean Water Act, which are to protect and maintain the chemical, physical, and biological integrity of the Nation’s waters. EPA Administrator Lee Thomas has identified wetlands protection as among the highest of Agency priorities. EPA recognizes that bottomland hardwood (BLH) wetlands have vital and unique attributes that, if lost, would severely impact the physical, chemical, and biological integrity of the Nation's waters. As part of a broad program to better protect the Nation's wetlands, EPA has therefore identified bottomland hardwood wetlands as a priority resource requiring special attention on a national basis. Recognizing the importance of implementing an effective, nationally consistent, and scientifically defensible regulatory program, EPA, in October 1984, issued Interim Operating Guidance to its field personnel for implementing the Section 404 regulatory program in bottomland hardwood wetlands. With the goal of improving and finalizing that guidance, EPA is sponsoring a series of workshops designed to answer key questions concerning BLH wetlands, based on the best scientific and technical information currently available. The first two workshops were directed toward summarizing existing scientific and technical knowledge concerning the functions of BLH ecosystems, the characteristics that are important to each function, and the impact of various development activities on those characteristics. The first workshop, which was held in St. Francisville, Louisiana, in December, 1984, examined a wetland zonation concept as a framework for gaining a greater understanding of BLH structure and function. The workshop set out to determine whether characterization of BLH resources as a series of relatively distinct zones, defined by concomitant variation in hydrologic regime, soils, and vegetation, might provide the basis for a useful and scientifically sound regulatory framework. For examp1e, if certain zones are of particular importance to one or more wetland functions that the Clean Water Act was intended to protect, then the zonation concept might be useful from the perspective of how various activities should be regulated. Discussions during the first workshop, however, indicated that the zonation concept provides, at best, only an incomplete picture of the structure and function of BLH ecosystems. In many cases, BLH functions are not limited to or closely correlated with particular zones and, furthermore, many factors other than zone are important determinants of BLH functions. With these responses in mind, the second workshop, held at Lake Lanier, Georgia, in July, 1985, was designed to elicit information on two questions. First, if zones are not an adequate framework for understanding the functions of BLH systems, what characteristics (predictors) can be used to assess the extent to which a particular site performs these functions? And second, what are the impacts of various development activities that often occur in BLH ecosystems on those characteristics and thus on the functions themselves? At the second workshop, individual workgroups dealing with particular subject areas (e.g., hydrology, water quality, fisheries, wildlife, ecosystem processes, and cultural/recreational/economic resources) were able to identify site characteristics that are important determinants of the performance of various functions. For example, the Hydrology Workgroup identified flood storage as one of three major hydrologic functions that BLH ecosystems perform. The workgroup then identified the most important characteristic (e.g., surface area of the site, soil saturation, and others) that determine flood storage and the likely impact of several common activities (e.g., conversion to soybean production and levee construction) on these characteristics. Some of the workgroups also provided estimates of the aggregate impact of activities, acting through all of the characteristics, on certain functions. The workgroups also identified key characteristics that could be used to identify high-value wetlands for various functions. In addition, the workgroups pointed out a number of topics needing further examination and discussion. First, all of the workgroups identified the need to develop the technical basis and information sources to address the problem of cumulative impacts in the regulatory process. Second, most of the workgroups noted the important of contextual variables in assessing the function of a particular site. For example, the location of a BLH site in relationship to other tracts of habitat is an important variable for many wildlife species. Similarly, the extent to which a site retains or transforms contaminants is depended not only on the characteristics of the site, but also on its position in a watershed relative to contaminant inputs. And finally, several of the workgroups pointed out that assessing the impact of an activity on a function is not as simple as "adding up" the impact on individual characteristics, but may depend instead on complex interactions among characteristics. Addressing these questions, as summarized in the objectives and discussions that follow, was the focus of the third workshop, the results of which are described in this report.

Report↗
USGS2007

Applying radar technology to migratory bird conservation and management: Strengthening and expanding a collaborative

Executive Summary Understanding the factors affecting migratory bird and bat populations during all three phases of their life cycle—breeding, nonbreeding, and migration—is critical to species conservation planning. This includes the need for information about these species’ responses to natural challenges, as well as information about the effects of human activities and structures. Habitats and other resources critical to migrants during passage and stopover are being destroyed, degraded, and threatened by human activities. Birds and bats are also uniquely susceptible to human use of the airspace. Wind turbines, communication and power transmission towers, and other tall structures, known to cause bird and bat mortality, are being erected or proposed in increasing numbers across the country. In addition, the potential for bird/aircraft collisions poses human safety threats. Management and regulatory agencies, conservation organizations, and industry currently lack the information they need to meet their missions and statutory responsibilities. The biological data available from various radar technologies offer a unique opportunity to learn more about the spatiotemporal distribution patterns, flight characteristics, and habitat use of “aero-fauna.” Recognizing the opportunities presented by radar technologies, the U.S. Geological Survey (USGS), the U.S. Fish and Wildlife Service (USFWS), and university partners collaborated first on individual projects and then in a broader, informal “collaborative” to coordinate their radar-related research and work together to develop the suite of products needed for conservation of birds and bats. Having produced two summary documents (Sojda and others, 2005; Ruth and others, 2005), the next objective was to convene a workshop for researchers, management and regulatory agencies, and other interested parties. The focus of this initial workshop was on strengthening the existing USGS-USFWS-university partnership and expanding the “collaborative” to include new Federal agency partners. The subject matter was centered on discussing available technologies, appropriate applications, management-related needs, and ways to strengthen collaborative research and conservation efforts. The workshop opened with presentations about the history of the “radar collaborative,” a description of the workshop objectives and focuses, and a summary of resource management and regulatory needs. Scientific presentations describing current research projects or subjects followed, given by USGS scientists, as well as scientists from other Federal agencies, academia, conservation and ornithological organizations, and a private contracting firm. Presenters addressed a wide variety of management issues including siting of wind-power facilities, bird/aircraft collisions, effects of hurricanes Katrina and Rita on bird migration, bird use of Conservation Reserve Program land, defining bird migration patterns at a broad regional scale, and associating migrant birds with their stopover habitats. Presentations described a variety of radar technologies including NEXRAD weather surveillance radar, modified mobile marine radar, military tracking radar, pencil beam radar, and dual polarization radar, as well as complementary techniques and analysis methods such as acoustic monitoring, thermal imaging, artificial intelligence, and individual-based modeling. Key issues, themes, and questions identified during the open discussions that followed fell into five main categories: (1) agency needs and challenges; (2) radar technology and applications—technical questions and issues; (3) tools and resources for managers and researchers; (4) standardization of protocols; and (5) collaborative opportunities. Participants identified the following management, regulatory, or business issues facing them which may be addressed with radar technologies: tall structures; wind turbines; identification and protection of key habitats; assessment of management activities; and bird/aircraft strikes. Participants frequently expressed the need for specific information about which radar technologies are best used for answering particular questions. User groups emphasized the importance of clear, defensible scientific information on which they can base their activities. In turn, researchers emphasized their need for clearly defined, specific questions from managers so that they can design and conduct the required research. Discussions about technical issues requiring further research and collaboration included target identity, ground-truthing, linking migrants to habitat, and standardized protocols for applied research. Workshop participants identified and endorsed a series of seven action items that would promote collaboration and begin to address key issues identified at the workshop: Action Item #1 : Establish a working subgroup to address large-scale surveillance radar standardization issues. Action Item #2 : Establish a working subgroup to address small-scale radar standardization issues. Action Item #3 : Bring management and regulatory agencies together to identify the three most important information needs for each key management issue relating to radar technologies. Action Item #4 : Develop Fact Sheet(s) to provide information about radar technology applications to migratory bird and bat conservation issues. Action Item #5 : Create a “radar collaborative” Website to provide information about radar biology applications, contacts, publications, and so forth. Action Item #6 : Formalize and expand the USGS-USFWS “radar collaborative.” Action Item #7 : Advance basic research, such as target identity and validation, which will support and improve our abilities to apply radar technologies to conservation objectives. There was considerable interest in expanding the “radar collaborative” to include those agencies, organizations, and industries represented at the workshop. It was felt that the publication of the workshop proceedings, implementation of action items, and additional future meetings or workshops will be crucial in strengthening the “radar collaborative” effort and promoting the use of these valuable technologies for conserving migratory species.

Open-File Report↗
USGS2020

Gear comparison study for sampling nekton in Barataria Basin marshes

This project was funded by the Louisiana Trustee Implementation Group (LA TIG) to support decisions related to investments in long-term monitoring. The LA TIG seeks to ensure long-term monitoring informs coastal restoration activities with the goal of sustaining and improving fisheries impacted by the Deepwater Horizon (DWH) Oil Spill. The project objective was to compare nekton catch across an estuarine gradient using different sampling gear with the goal of identifying trade-offs among nekton sampling approaches. To accomplish this objective, Louisiana Department of Wildlife and Fisheries (LDWF), The Water Institute of the Gulf (the Institute), Dynamic Solutions, LLC, Louisiana State University Agricultural Center (LSU AgCenter), and the U.S. Geological Survey (USGS) completed a field gear comparison study from 2018 to 2019. This work compared electrofisher and seine sampling at 12 fixed stations in Barataria Basin using data collected by LDWF. In addition, and in conjunction with LDWF monthly sampling, the same 12 fixed stations were sampled in May 2019 using a throw trap to compare nekton catch and assemblages collected with the throw trap, seine and electrofisher. LDWF has been conducting seine sampling since 1986, and seine data are used by the State of Louisiana to assess juvenile shrimp, crab and fish abundances, sizes and overall assemblages. In 2018, LDWF began conducting electrofisher sampling at 12 Barataria Basin seine stations in order to determine if the two gear types sample similar species and assemblages for potential future replacement of long-term seine sampling with electrofishing. Throw traps were included as they provide density estimates, which are ultimately the desired statistic used in modeling trophic webs, and are used in assessing habitat restoration outcomes. The project compared the nekton catch and assemblages collected using seine, electrofisher, and throw trap data from marsh edge habitats located across the estuarine gradient in Barataria Basin. Specifically, catch per unit effort (CPUE), species richness, species-specific total length (mm) distribution and nekton assemblages were compared between gear types. The first dataset was collected in May 2019 with throw trap (Appendix A), seine (LDWF data), and electrofisher (LDWF data) gear, and the second dataset (collected by LDWF) spanned 14 months of seine and electrofisher monthly sampling occurring from May 2018 through June 2019 at 12 stations in Barataria Basin. Key findings include that gear bias was not evident across the range of water quality conditions (salinity, temperature, o C, dissolved oxygen, mg L-1 , turbidity, NTU; Appendix B: scatter plots) captured during this pilot study, but differences in nekton catch per unit effort (CPUE) and assemblages were evident between gear types. However, those differences largely depended on the parameter examined. For example, the overall CPUE was highest for electrofishing, followed by seine, and then throw trap. When grass shrimp (the most abundant taxon collected) were removed from CPUE, the electrofisher and seine results were similar in CPUE. When CPUE was corrected for gear efficiency and total area sampled, the throw trap had the highest reported density of nekton sampled, followed by electrofisher and seine results. Electrofishing captured the highest number of species, which included more unique species compared to seine or throw trap catches, though all gear types captured at least one unique species. These highlight a need for caution in interpreting assemblage and density data when comparing datasets derived from different sampling methodologies. These key findings can help inform implementation and interpretation of long-term monitoring data in Louisiana as management decisions are made about coastal restoration projects to sustain and improve fisheries. There are trade-offs in selecting gear types for estuarine nekton monitoring of density, abundance, species richness, and assemblages. The table below (Table 1) summarizes some considerations when selecting gear types for long-term monitoring of estuarine nekton. In addition to biological and ecological considerations, other important considerations include cost, the labor required to conduct sampling, logistics, and potential uncertainties related to how effective each gear type is for sampling the wide variety of conditions found across Louisiana’s coastal habitats. For example, although electrofishing may capture higher CPUE, the equipment is more expensive to obtain and maintain compared to the other gear types. Most importantly, this table highlights differences in the nekton assemblages sampled by each gear type; this consideration is critical when designing the goals of a long-term monitoring program as it will inform how the data can be used and interpreted in the future. This report provides caveats, assumptions, and recommendations that can help support the Louisiana Coastal Protection and Restoration Authority (CPRA), LDWF and the LA TIG in comparing data from different gear types, and in making decisions for future monitoring. Findings from this study are limited to the range of water quality conditions occurring during these data collection events; these data and analyses could benefit from sampling across a wider range of water quality conditions, and collection of habitat structure and bottom type data which are not routinely collected but critically influence nekton. Further investigation examining how relative differences detected in key species abundances between gear types might impact ecosystem indicators and energetics in a modeled food web would provide valuable input to understand outputs of the Comprehensive Aquatic System Model for Barataria Basin, including the potential impacts of nekton monitoring decisions on food web models.

Louisiana↗
USGS2011

Population estimates and monitoring guidelines for endangered Laysan Teal, Anas Laysanensis, at Midway Atoll: Pilot study results 2008-2010.

Accurate estimates of population size are often crucial to determining status and planning recovery of endangered species. The ability to detect trends in survival and population size over time enables conservation managers to make effective decisions for species and refuge management. During 2004–2007, the translocated population of endangered Laysan Teal (Anas laysanensis; also Laysan Duck) was fitted with radio transmitters providing known (―gold standard‖) measures of survival and reproduction. However, as the population grew, statistically rigorous monitoring protocols were needed that were less labor intensive than radio telemetry. A population die-off and alarmingly high number of carcasses (181) were recorded during a botulism epizootic in August–October 2008, which further reinforced the need for effective monitoring protocols since this endangered species is vulnerable to catastrophic population declines. In fall 2008, we initiated a pilot study using standardized surveys with uniquely marked birds to monitor abundance and estimate the population growth rate of the reintroduced Laysan Teal. Since few birds carried marks (leg bands) after the 2008 botulism die-off (only about 15% of the population), and standardized surveys were not yet implemented, the magnitude of the die-off on the population size was unknown. To learn more about this endangered species' status and develop monitoring protocols useful to refuge managers and recovery planners in the U.S. Fish and Wildlife Service (USFWS), we marked (banded) 252 new Laysan Teal for this pilot project. With skilled refuge staff and trained volunteers, we conducted counts of marked, unmarked, and unknown birds during bimonthly surveys from Oct 2008 to Jan 2010. We recorded the identities of marked birds observed, recovered carcasses, and then used the last date a bird was detected alive and the median resight frequency to conclude if a bird was likely to be alive on a given survey date. Using mark-resight data and individual resight frequencies, we produced a series of abundance estimates from surveys that met accuracy criteria and approached ―closed population‖ assumptions. Since only one year of standardized, atoll-wide surveys were conducted, we analyzed data selected from multiple surveys using Lincoln-Petersen (LP) estimates instead of multi-year likelihood estimators. We adjusted surveys to account for unknown birds (e.g., swimming birds), temporary band loss, and described the frequency of double counting. Double counting is an important consideration in the population estimate because we found a maximum of 13% of marked birds were counted multiple times during a survey. These survey protocols allowed us to estimate the species' post-fledging population (combined adults and juveniles), and the methods are comparable to those used on Laysan Island. The Laysan Teal population increased 91% from 247 (95% CI, 233–260) in 2007 to 439–508 in early 2010. There was no change from 2009 to 2010 indicating that there was no population growth, however, our 2010 estimate should be considered preliminary since only one month of 2010 resight data was used. We compared a series of direct counts to their corresponding population estimates during 2008–2009 to evaluate if counts could serve as an unbiased ―index‖ of population abundance. There was a moderate correlation between abundance estimates and total birds counted (r 2 = 0.51) during resight surveys but a low correlation with all-wetland counts (r 2 = 0.02). This indicated that using direct all-wetland counts to predict abundance would result in confidence intervals on the order of ± 200 birds, which is equal to 50% of the estimate. With such large confidence intervals, it would be unlikely to detect annual changes in abundance or determine the magnitude of a catastrophic decline. To improve the Laysan Teal population estimates, we recommend changes to the monitoring protocol. Additional years of data are needed to quantify inter-annual seasonal detection probabilities, which may allow the use of standardized direct counts as an unbiased index of population size. Survey protocols should be enhanced through frequent resights, regular survey intervals, and determining reliable standards to detect catastrophic declines and annual changes in adult abundance. In late 2009 to early 2010, 68% of the population was marked with unique color band combinations. This allowed for potentially accurate adult population estimates and survival estimates without the need to mark new birds in 2010, 2011, and possibly 2012. However, efforts should be made to replace worn or illegible bands so birds can be identified in future surveys. It would be valuable to develop more sophisticated population size and survival models using Program MARK, a state-of-the-art software package which uses likelihood models to analyze mark-recapture data. This would allow for more reliable adult population and survival estimates to compare with the ―source‖ Laysan Teal population on Laysan Island. These models will require additional years of resight data (> 1 year) and, in some cases, an intensive annual effort of marking and recapture. Because data indicate standardized all-wetland counts are a poor index of abundance, monitoring efforts could be improved by expanding resight surveys to include all wetlands, discontinuing the all-wetland counts, and reallocating some of the wetland count effort to collect additional opportunistic resights. Approximately two years of additional bimonthly surveys are needed to validate the direct count as an appropriate index of population abundance. Additional years of individual resight data will allow estimates of adult population size, as specified in recovery criteria, and to track species population dynamics at Midway Atoll.

Technical Report↗
USGS2016

Accuracy assessment/validation methodology and results of 2010–11 land-cover/land-use data for Pools 13, 26, La Grange, and Open River South, Upper Mississippi River System

Introduction/Background The U.S. Geological Survey (USGS)-Upper Midwest Environmental Sciences Center (UMESC) was responsible for development of several land cover/land use (LCU) systemic datasets of the Upper Mississippi River System (UMRS). These efforts (1989 and 2000) were funded by the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program (UMRR) Long Term Resource Monitoring (LTRM) element. Development of systemic datasets includes the acquisition, processing, and serving of high-resolution aerial photography and land cover/land use spatial datasets ( http://www.umesc.usgs.gov/data_library/land_cover_use/land_cover_use_data.html ). In 2008, the UMRR reached a collaborative agreement with the U.S. Fish and Wildlife Service-Region 3 to collect high-resolution digital imagery of the entire UMRS floodplain during 2010–11 for LTRM. The UMESC helped acquire, process, and serve this imagery, as well as produce and serve the 2010–11 LCU systemic dataset of the UMRS floodplain. Digital imagery for Pools 13, 26, La Grange, and Open River South was collected using an Applanix DSS 439 digital sensor system with a 40 millimeter lens and Color Infrared (CIR) filter. The imagery was collected at a resolution of 20 centimeters/pixel (8 inches/pixel) for Pool 13 and 40 centimeters/pixel (16 inches/pixel) for Pools 26, Open River South, and La Grange. All imagery was projected to Universal Transverse Mercator (UTM) Zone 15, North American Datum of 1983 (NAD 83). The General Wetland Vegetation Classification (GWVC) system used for mapping is hierarchical, and its 31 classes can be collapsed into broader categories using either a 15- or 7-class level. While the 1989 and 2000 LCU systemic datasets have not gone through a traditional thematic accuracy assessment (AA) in the past, nor have they undergone a validation analysis, the end products are of high quality. For each systemic dataset produced (1989, 2000, 2010–11), extensive field reconnaissance is performed before photointerpretation. The intent of this field reconnaissance is to learn, test, and verify image signatures as they relate to vegetation types. Questionable areas on the imagery are visited, and the plants or land features observed in the area are recorded for reference. This procedure verifies vegetation signatures on the imagery with those on the ground. In addition, once the photointerpretation is complete, the final LCU dataset undergoes extensive quality assurance/quality control to ensure the imagery is mapped correctly. Since the 2000 LCU systemic dataset was developed, there has been a growing interest in completing thematic AAs for the LTRM LCU spatial datasets. The objective of an AA is to measure the probability that a particular location has been assigned its correct vegetation class. An AA estimates thematic (map class) errors in the data, giving users information needed to determine data suitability for a particular application. At the same time, data producers are able to learn more about the nature of errors in the data. Thus, the two attributes of an AA are “producers’ accuracy,” which is the probability that an AA point has been mapped correctly (also referred to as an error of omission); and “users’ accuracy,” which is the probability that the map actually represents what was found on the ground (also referred to as error of commission). Producers’ and users’ accuracies can be obtained from the same set of data by using different analyses. Accuracy assessment is an extensive effort that requires seasonal field personnel and equipment, data entry, analyses, and post processing—tasks that are costly and time consuming. The geospatial team at the UMESC has suggested a validation process for understanding the accuracy of the spatial datasets, which will be tested on at least some areas of the UMRS. Validation is not a true verification of map-class type in the field; however, it can provide the user of the map with useful information that is similar to a field AA. Similar to an AA, validation involves generating random points based on the total area for each map class. However, instead of collecting field data, two or three individuals not involved with the photo-interpretative mapping separately review each of the points onscreen and record a best-fit vegetation type(s) for each site. Once the individual analyses are complete, results are joined together and a comparative analysis is performed. The objective of this initial analysis is to identify areas where the validation results were in agreement (matches) and areas where validation results were in disagreement (mismatches). The two or three individuals then perform an analysis, looking at each mismatched site, and agree upon a final validation class. (If two vegetation types at a specific site appear to be equally prevalent, the validation team is permitted to assign the site two best-fit vegetation types.) Following the validation team’s comparative analysis of vegetation assignments, the data are entered into a database and compared to the mappers’ vegetation assignments. Agreements and disagreements between the map and validation classes are identified, and a contingency table is produced. This document presents the AA processes/results for Pools 13 and La Grange, as well as the validation process/results for Pools 13 and 26 and Open River South.

Iowa, Illinois, Minnesota, Missouri, Wisconsin↗
USGS2014

Spatially explicit habitat models for 28 fishes from the Upper Mississippi River System (AHAG 2.0)

Environmental management actions in the Upper Mississippi River System (UMRS) typically require pre-project assessments of predicted benefits under a range of project scenarios. The U.S. Army Corps of Engineers (USACE) now requires certified and peer-reviewed models to conduct these assessments. Previously, habitat benefits were estimated for fish communities in the UMRS using the Aquatic Habitat Appraisal Guide (AHAG v.1.0; AHAG from hereon). This spreadsheet-based model used a habitat suitability index (HSI) approach that drew heavily upon Habitat Evaluation Procedures (HEP; U.S. Fish and Wildlife Service, 1980) by the U.S. Fish and Wildlife Service (USFWS). The HSI approach requires developing species response curves for different environmental variables that seek to broadly represent habitat. The AHAG model uses species-specific response curves assembled from literature values, data from other ecosystems, or best professional judgment. A recent scientific review of the AHAG indicated that the model’s effectiveness is reduced by its dated approach to large river ecosystems, uncertainty regarding its data inputs and rationale for habitat-species response relationships, and lack of field validation (Abt Associates Inc., 2011). The reviewers made two major recommendations: (1) incorporate empirical data from the UMRS into defining the empirical response curves, and (2) conduct post-project biological evaluations to test pre-project benefits estimated by AHAG. Our objective was to address the first recommendation and generate updated response curves for AHAG using data from the Upper Mississippi River Restoration-Environmental Management Program (UMRR-EMP) Long Term Resource Monitoring Program (LTRMP) element. Fish community data have been collected by LTRMP (Gutreuter and others, 1995; Ratcliff and others, in press) for 20 years from 6 study reaches representing 1,930 kilometers of river and >140 species of fish. We modeled a subset of these data (28 different species; occurrences at sampling sites as observed in day electrofishing samples) using multiple logistic regression with presence/absence responses. Each species’ probability of occurrence, at each sample site, was modeled as a function of 17 environmental variables observed at each sample site by LTRMP standardized protocols. The modeling methods used (1) a forward-selection process to identify the most important predictors and their relative contributions to predictions; (2) partial methods on the predictor set to control variance inflation; and (3) diagnostics for LTRMP design elements that may influence model fits. Models were fit for 28 species, representing 3 habitat guilds (Lentic, Lotic, and Generalist). We intended to develop “systemic models” using data from all six LTRMP study reaches simultaneously; however, this proved impossible. Thus, we “regionalized” the models, creating two models for each species: “Upper Reach” models, using data from Pools 4, 8, and 13; and “Lower Reach” models, using data from Pool 26, the Open River Reach of the Mississippi River, and the La Grange reach of the Illinois River. A total of 56 models were attempted. For any given site-scale prediction, each model used data from the three LTRMP study reaches comprising the regional model to make predictions. For example, a site-scale prediction in Pool 8 was made using data from Pools 4, 8, and 13. This is the fundamental nature and trade-off of regionalizing these models for broad management application. Model fits were deemed “certifiably good” using the Hosmer and Lemeshow Goodness-of-Fit statistic (Hosmer and Lemeshow, 2000). This test post-partitions model predictions into 10 groups and conducts inferential tests on correspondences between observed and expected probability of occurrence across all partitions, under Chi-square distributional assumptions. This permits an inferential test of how well the models fit and a tool for reporting when they did not (and perhaps why). Our goal was to develop regionalized models, and to assess and describe circumstances when a good fit was not possible. Seven fish species composed the Lentic guild. Good fits were achieved for six Upper Reach models. In the Lower Reach, no model produced good fits for the Lentic guild. This was due to (1) lentic species being much less prominent in the Lower Reach study areas, and (2) those that do express greater prominence principally do so only in the La Grange reach of the Illinois River. Thus, developing Lower Reach models for Lentic species will require parsing La Grange from the other two Lower Reach study areas and fitting separate models. We did not do that as part of this study, but it could be done at a later time. Nine species comprised the Lotic guild. Good fits were achieved for seven Upper Reach models and six Lower Reach models. Four species had good fits for both regions (flathead catfish, blue sucker, sauger, and shorthead redhorse). Three species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (blue catfish, rock bass, and skipjack herring). Twelve species comprised the Generalist guild. Good fits were achieved for five Upper Reach models and eight Lower Reach models. Six species had good fits for both regions (brook silverside, emerald shiner, freshwater drum, logperch, longnose gar, and white bass). Two species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (red shiner and blackstripe topminnow). Poorly fit models were almost always due to the diagnostic variable “field station,” a surrogate for river mile. In these circumstances, the residuals for “field station” were non-randomly distributed and often strongly ordered. This indicates either fitting “pool scale” models for these species and regions, or explicitly model covariances between “field station” and the other predictors within the existing modeling framework. Further efforts on these models should seek to resolve these issues using one of these two approaches. In total, nine species, representing two of the three guilds (Lotic and Generalist), produced well-fit models for both regions. These nine species should comprise the basis for AHAG 2.0. Additional work, likely requiring downscaling of the regional models to pool-scale models, will be needed to incorporate additional species. Alternately, a regionalized AHAG could be comprised of those species, per region, that achieved well-fit models. The number of species and the composition of the regional species pools will differ among regions as a consequence. Each of these alternatives has both pros and cons, and managers are encouraged to consider them fully before further advancing this approach to modeling multi-species habitat suitability.

Upper Mississippi River System↗