Geology topics

Michael G. Brasher

Publications and source records attributed to Michael G. Brasher.

10 recordsLinked to original sources

USGS2023

Spatiotemporal dynamics of duck harvest distributions in the Central and Mississippi flyways, 1960–2019

Geographical distributions of waterfowl exhibit annual variation in response to spatiotemporal variation in weather conditions, habitat availability, and other factors. Continuing changes in climate and land use could lead to persistent shifts of waterfowl distributions, potentially causing a mismatch with habitat conservation planning, wetland restoration efforts, and harvest management decisions informed by historical distributions. We used band recoveries and harvest records (i.e., hunter-harvested wings) from the United States Fish and Wildlife Service Waterfowl Parts Collection Survey as indices of duck distribution in autumn and winter, and quantified intra-annual, interannual, and interspecific variation in their geographic distributions across 6 decades (1960–2019) for 15 duck species in the Central and Mississippi flyways in North America. Specifically, we tested for annual and decadal shifts in mean latitude and longitude of recoveries for each month (Oct–Jan) by species and taxonomic guild (i.e., dabbling, diving ducks). Overall, species varied in the extent, timing, and sometimes direction, of distributional change in recoveries. From 1960–2019, mean recovery locations for dabbling ducks shifted south 105–296 km in October and 27 km in November (wings only), whereas mean latitudes shifted north 144–234 km in December and 186–301 km in January. Mean recovery locations for diving ducks shifted north 162 km in October (wings only), 84–173 km in December, and 66–120 km in January, but shifted 99–512 km south in November. Shifts in longitude were less consistent between guilds and data types. Finally, distributional change rarely accelerated during recent decades, except for southward shifts of band recoveries of diving ducks in November and northward shifts of band and wing recoveries of dabbling ducks in January. Although anecdotal accounts of large-scale northward shifts in duck distributions are prolific in the land management and hunting communities, our data demonstrate more subtle shifts that vary considerably by species and month. Observed changes in recovery distributions could necessitate changes in timing of habitat management practices throughout the Central and Mississippi flyways and may result in fewer hunting and recreational opportunities for some species in southern states. Quantifying patterns of historical change is a necessary first step to understanding temporal and interspecific variation in waterfowl distributions, which will help with landscape-scale conservation and management efforts in the future and enable effective communication to core constituencies regarding ongoing changes and their implications for recreational engagement.

The Journal of Wildlife Management↗

USGS2022

Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions

The North American Wetlands Conservation Act (16 U.S.C. 4401-4412) provided funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JVs) (i.e., partnerships for cooperative planning and coordinated management of the continent’s waterfowl populations and habitats). The JVs evaluate funding proposals submitted with their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs, however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six NAWCA proposals submitted to the Upper Mississippi / Great Lakes Joint Venture in 2016 and seven proposals submitted to the Gulf Coast Joint Venture in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV’s management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi / Great Lakes Joint Venture, but not for the Gulf Coast Joint Venture. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.

Journal of Fish and Wildlife Management↗

USGS2022

The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts

Methods are being developed to capitalize on citizen science data for research and monitoring, but these data are rarely used within established decision-making frameworks of wildlife agencies. Citizen science data are often collected at higher resolution and extent than targeted monitoring programs, and may provide complementary information. Here, we demonstrate that carefully filtered semi-structured citizen science observations, when paired with targeted survey data, can produce ecological predictions at higher resolution and extent than targeted surveys alone, and both datasets can represent complementary aspects of species' ecology. We present case studies demonstrating how citizen science data can enhance or supplement decision-making of government and conservation organizations. First, we show how the continuous spatial coverage of citizen science projects, when coupled with targeted surveys, can improve estimates of metrics used by the U.S. Fish and Wildlife Service in regulatory processes to estimate population size, and inform take limits of federally managed species nationwide. Second, we show that the spatial coverage of citizen science accommodates dynamic avian space use patterns during key times of the year, relative to standardized monitoring protocols carried out by the Illinois Natural History Survey. Lastly, we demonstrate that citizen science information can replicate estimates of migratory chronologies for the Illinois Natural History Survey and the U.S. Fish and Wildlife Service for some waterfowl species, and in some contexts can supplement missing data on abundance. These findings illustrate the value of integrating validated information from semi-structured citizen science into the current evidence base used to justify, inform, and evaluate conservation decision-making.

California, Illinois, Iowa, Missouri↗

USGS2021

Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives

Resource allocation for land acquisition is a common multi-objective problem that involves complex trade-offs. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service currently uses the Targeted Resource Acquisition Comparison Tool (TRACT) to allocate funds from the Migratory Bird Conservation Fund (MBCF; established through the Migratory Bird Hunting and Conservation Act of 1934) for land acquisition based on cost-benefit analysis, regional priority rankings of candidate land parcels available for acquisition, and the overall biological contribution to duck population objectives. However, current policy encourages decision makers to consider societal and economic benefits of lands acquired, in addition to their biological benefits to waterfowl. These decisions about portfolio elements (i.e. individual land parcels) require an analysis of the difficult trade-offs among multiple objectives. In the last decade the application of multi-criteria decision analysis (MCDA) methods has been instrumental in aiding decision makers with complex multi-objective decisions. In this study, we present an alternative approach to developing land acquisition portfolios using MCDA and Modern Portfolio Theory (MPT). We describe the development of a portfolio decision analysis tool using constrained optimization for land acquisition decisions by the NWRS. We outline the decision framework, describe development of the prototype tool in Microsoft Excel, and test the results of the tool using land parcels submitted as candidates for MBCF funding in 2019. Our results indicate that the constrained optimization outperformed the traditional TRACT method and ad hoc portfolios developed using current NWRS criteria.

Ecological Applications↗

USGS2019

Spatial integration of biological and social objectives to identify priority landscapes for waterfowl habitat conservation

Waterfowl population management and habitat conservation compose one of the oldest and most successful adaptive management frameworks in the world. Since its inception, the North American Waterfowl Management Plan (NAWMP) has emphasized strategically targeted conservation investments in regions that most affect waterfowl population dynamics. By 2012, regional conservation had progressively become more science-based and strategic: many migratory bird partnerships had initiated or completed projects on mapping and modeling waterfowl distribution and abundances using geospatial techniques. However, when developing a map depicting and titled “Areas of Greatest Continental Significance to North American Ducks, Geese, and Swans” for the 2012 NAWMP Revision, waterfowl professionals articulated the need for improved decision frameworks and use of consistent datasets for refining large-scale spatial products depicting priority areas for waterfowl and people. This report describes a framework for developing a spatial value model to support the identification of North American geographies of importance to waterfowl during the breeding and non-breeding periods and to resource users who could potentially support (financially and (or) politically) waterfowl habitat conservation. Objectives used to identify priority geographies were determined through a collaborative process of the NAWMP Science Support Team, Priority Landscapes Committee (PLC), and other experts in the fields of waterfowl biology and ecology, environmental science, and human dimensions. ArcGIS Desktop was used as the platform for managing, analyzing, combining and displaying the spatial data as well as producing new data through spatial analysis functions. Thirty-eight spatial layers were developed, and several composite spatially explicit products (maps of North America) were produced based on PLC recommendations. The composite products have extensive similarities to the 2012 NAWMP map depicting areas of greatest continental significance to North American waterfowl. There are also some differences, especially in regions of the high Arctic and in Mexico. These differences between spatial value model maps and the 2012 NAWMP output likely arose from inclusion of social objectives, reduced dependence on expert opinion to generate abundance estimates, lack of population surveys in some regions and availability of expanded survey data in other regions, and use of model-based waterfowl population estimates for some unsurveyed areas. The structured decision-making framework application in this study is discussed, and the appropriate use of the products and their limitations are outlined. Additionally, options for future improvements are presented by identifying gaps in data collection, waterfowl-habitat association assumptions, and uncertainties related to social objectives. These spatial products are intended for use by national, regional, and province/state level wildlife professionals to aid their decisions in targeting waterfowl habitat conservation.

Open-File Report↗

USGS2017

Implementing the 2012 North American Waterfowl Management Plan revision: Populations, habitat, and people

The North American Waterfowl Management Plan (NAWMP) has established a model for wildlife conservation planning over the last 3 decades. Management at a continental scale, leveraged funding, regional partnerships, and a strong science basis have been notable features. Periodic updates to the NAWMP occurred since implementation in 1986; however, a fundamental revision was accomplished in 2012 after extensive stakeholder engagement. An explicit fundamental goal for waterfowl conservation supporters was added in 2012, complementing existing goals for sustainable populations and sufficient habitat found in previous updates. We present a synopsis of progress toward implementation of the 2012 NAWMP and challenge the waterfowl management community to continue with meaningful steps toward achieving NAWMP goals. Adding goals and objectives for supporters increases potential relevance of NAWMP; however, it also presents a level of complexity that was not entirely anticipated. Additionally, the 2012 NAWMP recognized that traditional support from waterfowl hunters alone will not be sufficient to support waterfowl conservation in the future. Simultaneous consideration of multiple objectives, although implicit before, now is a specific focus for habitat and harvest management affecting hunters and other users of the waterfowl resource. The waterfowl management community is faced with revisiting objectives and management actions related to harvest regulations, landscape priorities, habitat conservation, and public engagement to garner broader support. These persistent management challenges are tangible and relevant candidates for greater integration. Ultimately, the structures and processes supporting waterfowl management also will need to be reconsidered.

Journal of Wildlife Management↗

USGS2016

Brackish marsh zones as a waterfowl habitat resource in submerged aquatic vegetation beds in the northern Gulf of Mexico

Submerged aquatic vegetation (SAV) beds are shallow coastal habitats that are increasingly exposed to the effects of sea-level rise (SLR). In the northern Gulf of Mexico (nGoM), an area especially vulnerable to SLR, the abundance and distribution of SAV food resources (seeds, rhizomes, and tissue) can influence the carrying capacity of coastal marshes to support wintering waterfowl. Despite the known importance of SAV little is known about their distribution across coastal landscapes and salinity zones or how they may be impacted by SLR. We estimated SAV cover and seed biomass in coastal marshes from Texas to Alabama from 1 June – 15 September 2013 to assess variation in SAV and seed resource distribution and abundance across the salinity gradient. Percent cover of SAV was similar among salinity zones (10%–20%) although patterns of distribution differed. Specifically, SAV occurred less frequently in saline zones, but when present the percent coverage was greater than in fresh, intermediate and brackish. Mean seed biomass varied greatly and did not differ significantly among salinity zones. However, when considering only seed species identified as waterfowl foods, the mean seed biomass was lower in saline zones (1.2 g m–2). Alteration of nGoM marshes due to SLR will likely shift the distribution and abundance of SAV resources, and these shifts may affect carrying capacity of coastal marshes for waterfowl and other associated species.

Gulf of Mexico↗

USGS2015

Delineation of marsh types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama, in 2010

Coastal zone managers and researchers often require detailed information regarding emergent marsh vegetation types (that is, fresh, intermediate, brackish, and saline) for modeling habitat capacities and needs of marsh dependent taxa (such as waterfowl and alligator). Detailed information on the extent and distribution of emergent marsh vegetation types throughout the northern Gulf of Mexico coast has been historically unavailable. In response, the U.S. Geological Survey, in collaboration with the Gulf Coast Joint Venture, the University of Louisiana at Lafayette, Ducks Unlimited, Inc., and the Texas A&M University-Kingsville, produced a classification of emergent marsh vegetation types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama. This study incorporates about 9,800 ground reference locations collected via helicopter surveys in coastal wetland areas. Decision-tree analyses were used to classify emergent marsh vegetation types by using ground reference data from helicopter vegetation surveys and independent variables such as multitemporal satellite-based multispectral imagery from 2009 to 2011, bare-earth digital elevation models based on airborne light detection and ranging (lidar), alternative contemporary land cover classifications, and other spatially explicit variables. Image objects were created from 2010 National Agriculture Imagery Program color-infrared aerial photography. The final classification is a 10-meter raster dataset that was produced by using a majority filter to classify image objects according to the marsh vegetation type covering the majority of each image object. The classification is dated 2010 because the year is both the midpoint of the classified multitemporal satellite-based imagery (2009–11) and the date of the high-resolution airborne imagery that was used to develop image objects. The seamless classification produced through this work can be used to help develop and refine conservation efforts for priority natural resources.

Alabama, Louisiana, Mississippi, Texas↗

USGS2014

Delineation of marsh types of the Texas coast from Corpus Christi Bay to the Sabine River in 2010

Coastal zone managers and researchers often require detailed information regarding emergent marsh vegetation types for modeling habitat capacities and needs of marsh-reliant wildlife (such as waterfowl and alligator). Detailed information on the extent and distribution of marsh vegetation zones throughout the Texas coast has been historically unavailable. In response, the U.S. Geological Survey, in cooperation and collaboration with the U.S. Fish and Wildlife Service via the Gulf Coast Joint Venture, Texas A&M University-Kingsville, the University of Louisiana-Lafayette, and Ducks Unlimited, Inc., has produced a classification of marsh vegetation types along the middle and upper Texas coast from Corpus Christi Bay to the Sabine River. This study incorporates approximately 1,000 ground reference locations collected via helicopter surveys in coastal marsh areas and about 2,000 supplemental locations from fresh marsh, water, and “other” (that is, nonmarsh) areas. About two-thirds of these data were used for training, and about one-third were used for assessing accuracy. Decision-tree analyses using Rulequest See5 were used to classify emergent marsh vegetation types by using these data, multitemporal satellite-based multispectral imagery from 2009 to 2011, a bare-earth digital elevation model (DEM) based on airborne light detection and ranging (lidar), alternative contemporary land cover classifications, and other spatially explicit variables believed to be important for delineating the extent and distribution of marsh vegetation communities. Image objects were generated from segmentation of high-resolution airborne imagery acquired in 2010 and were used to refine the classification. The classification is dated 2010 because the year is both the midpoint of the multitemporal satellite-based imagery (2009–11) classified and the date of the high-resolution airborne imagery that was used to develop image objects. Overall accuracy corrected for bias (accuracy estimate incorporates true marginal proportions) was 91 percent (95 percent confidence interval [CI]: 89.2–92.8), with a kappa statistic of 0.79 (95 percent CI: 0.77–0.81). The classification performed best for saline marsh (user’s accuracy 81.5 percent; producer’s accuracy corrected for bias 62.9 percent) but showed a lesser ability to discriminate intermediate marsh (user’s accuracy 47.7 percent; producer’s accuracy corrected for bias 49.5 percent). Because of confusion in intermediate and brackish marsh classes, an alternative classification containing only three marsh types was created in which intermediate and brackish marshes were combined into a single class. Image objects were reattributed by using this alternative three-marsh-type classification. Overall accuracy, corrected for bias, of this more general classification was 92.4 percent (95 percent CI: 90.7–94.2), and the kappa statistic was 0.83 (95 percent CI: 0.81–0.85). Mean user’s accuracy for marshes within the four-marsh-type and three-marsh-type classifications was 65.4 percent and 75.6 percent, respectively, whereas mean producer’s accuracy was 56.7 percent and 65.1 percent, respectively. This study provides a more objective and repeatable method for classifying marsh types of the middle and upper Texas coast at an extent and greater level of detail than previously available for the study area. The seamless classification produced through this work is now available to help State agencies (such as the Texas Parks and Wildlife Department) and landscape-scale conservation partnerships (such as the Gulf Coast Prairie Landscape Conservation Cooperative and the Gulf Coast Joint Venture) to develop and (or) refine conservation plans targeting priority natural resources. Moreover, these data may improve projections of landscape change and serve as a baseline for monitoring future changes resulting from chronic and episodic stressors.

Texas↗

USGS2014

Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements

Population-based habitat conservation planning for migrating and wintering waterfowl in North America is carried out by habitat Joint Venture (JV) initiatives and is based on the premise that food can limit demography (i.e. food limitation hypothesis). Consequently, planners use bioenergetic models to estimate food (energy) availability and population-level energy demands at appropriate spatial and temporal scales, and translate these values into regional habitat objectives. While simple in principle, there are both empirical and theoretical challenges associated with calculating energy supply and demand including: 1) estimating food availability, 2) estimating the energy content of specific foods, 3) extrapolating site-specific estimates of food availability to landscapes for focal species, 4) applicability of estimates from a single species to other species, 5) estimating resting metabolic rate, 6) estimating cost of daily behaviours, and 7) estimating costs of thermoregulation or tissue synthesis. Most models being used are daily ration models (DRMs) whose set of simplifying assumptions are well established and whose use is widely accepted and feasible given the empirical data available to populate such models. However, DRMs do not link habitat objectives to metrics of ultimate ecological importance such as individual body condition or survival, and largely only consider food-producing habitats. Agent-based models (ABMs) provide a possible alternative for creating more biologically realistic models under some conditions; however, ABMs require different types of empirical inputs, many of which have yet to be estimated for key North American waterfowl. Decisions about how JVs can best proceed with habitat conservation would benefit from the use of sensitivity analyses that could identify the empirical and theoretical uncertainties that have the greatest influence on efforts to estimate habitat carrying capacity. Development of ABMs at restricted, yet biologically relevant spatial scales, followed by comparisons of their outputs to those generated from more simplistic, deterministic models can provide a means of assessing degrees of dissimilarity in how alternative models describe desired landscape conditions for migrating and wintering waterfowl.

Wildfowl↗