Geology Reports⌕ Search

Geology topics

Richard S. Sojda

Publications and source records attributed to Richard S. Sojda.

16 recordsLinked to original sources

Observation of sandhill cranes' ( Grus canadensis ) flight behavior in heavy fog

The behaviors of birds flying in low visibility conditions remain poorly understood. We had the opportunity to monitor Sandhill Cranes (Grus canadensis) flying in heavy fog with very low visibility during a comprehensive landscape use study of refuging cranes in the Horicon Marsh in southeastern Wisconsin. As part of the study, we recorded flight patterns of cranes with a portable marine radar at various locations and times of day, and visually counted cranes as they departed the roost in the morning. We compared flight patterns during a fog event with those recorded during clear conditions. In good visibility, cranes usually departed the night roost shortly after sunrise and flew in relatively straight paths toward foraging areas. In fog, cranes departed the roost later in the day, did not venture far from the roost, engaged in significantly more circling flight, and returned to the roost site rather than proceeding to foraging areas. We also noted that compared to mornings with good visibility, cranes flying in fog called more frequently than usual. The only time in this 2-year study that observers heard young of the year calling was during the fog event. The observed behavior of cranes circling and lingering in an area while flying in poor visibility conditions suggests that such situations may increase chances of colliding with natural or anthropogenic obstacles in the vicinity.

Wisconsin↗

Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework

[1] Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very “sharp”). Synthetic forecasts show that a modest “sharpening” can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement.

Montana↗

A risk-based approach to evaluating wildlife demographics for management in a changing climate: A case study of the Lewis's Woodpecker

Given the projected threat that climate change poses to biodiversity, the need for proactive response efforts is clear. However, integrating uncertain climate change information into conservation planning is challenging, and more explicit guidance is needed. To this end, this article provides a specific example of how a risk-based approach can be used to incorporate a species' response to climate into conservation decisions. This is shown by taking advantage of species' response (i.e., impact) models that have been developed for a well-studied bird species of conservation concern. Specifically, we examine the current and potential impact of climate on nest survival of the Lewis's Woodpecker ( Melanerpes lewis ) in two different habitats. To address climate uncertainty, climate scenarios are developed by manipulating historical weather observations to create ensembles (i.e., multiple sequences of daily weather) that reflect historical variability and potential climate change. These ensembles allow for a probabilistic evaluation of the risk posed to Lewis's Woodpecker nest survival and are used in two demographic analyses. First, the relative value of each habitat is compared in terms of nest survival, and second, the likelihood of exceeding a critical population threshold is examined. By embedding the analyses in a risk framework, we show how management choices can be made to be commensurate with a defined level of acceptable risk. The results can be used to inform habitat prioritization and are discussed in the context of an economic framework for evaluating trade-offs between management alternatives.

Idaho↗

Identifying the decision to be supported: a review of papers from environmental modelling and software

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for consideration by journal editors to aid them in filtering papers that use the term, “decision support”.

Leipzig↗

Multi-scale clustering of functional data with application to hydraulic gradients in wetlands

A new set of methods are developed to perform cluster analysis of functions, motivated by a data set consisting of hydraulic gradients at several locations distributed across a wetland complex. The methods build on previous work on clustering of functions, such as Tarpey and Kinateder (2003) and Hitchcock et al. (2007), but explore functions generated from an additive model decomposition (Wood, 2006) of the original time se- ries. Our decomposition targets two aspects of the series, using an adaptive smoother for the trend and circular spline for the diurnal variation in the series. Different measures for comparing locations are discussed, including a method for efficiently clustering time series that are of different lengths using a functional data approach. The complicated nature of these wetlands are highlighted by the shifting group memberships depending on which scale of variation and year of the study are considered.

Journal of Data Science↗

New software methods in radar ornithology using WSR-88D weather data and potential application to monitoring effects of climate change on bird migration

Radar ornithology has provided tools for studying the movement of birds, especially related to migration. Researchers have presented qualitative evidence suggesting that birds, or at least migration events, can be identified using large broad scale radars such as the WSR-88D used in the NEXRAD weather surveillance system. This is potentially a boon for ornithologists because such data cover a large portion of the United States, are constantly being produced, are freely available, and have been archived since the early 1990s. A major obstacle to this research, however, has been that identifying birds in NEXRAD data has required a trained technician to manually inspect a graphically rendered radar sweep. A single site completes one volume scan every five to ten minutes, producing over 52,000 volume scans in one year. This is an immense amount of data, and manual classification is infeasible. We have developed a system that identifies biological echoes using machine learning techniques. This approach begins with training data using scans that have been classified by experts, or uses bird data collected in the field. The data are preprocessed to ensure quality and to emphasize relevant features. A classifier is then trained using this data and cross validation is used to measure performance. We compared neural networks, naive Bayes, and k-nearest neighbor classifiers. Empirical evidence is provided showing that this system can achieve classification accuracies in the 80th to 90th percentile. We propose to apply these methods to studying bird migration phenology and how it is affected by climate variability and change over multiple temporal scales.

Conference Paper↗

Functional linear models to test for differences in prairie wetland hydraulic gradients

Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.

Conference Paper↗

Management and research applications of long-range surveillance radar data for birds, bats, and flying insects

There is renewed interest in using long-range surveillance radar as a biological research tool due to substantial improvements in the network of radars within the United States. Technical improvements, the digital nature of the radar data, and the availability of computing power and geographic information systems, enable a broad range of biological applications. This publication provides a summary of long-range surveillance radar technology and applications of these data to questions about movement patterns of birds and other flying wildlife. The intended audience is potential radar-data end users, including natural-resource management and regulatory agencies, conservation organizations, and industry. This summary includes a definition of long-range surveillance radar, descriptions of its strengths and weaknesses, information on applications of the data, cost, methods of calibration, and what end users need to do, and some key references and resources.

Texas↗

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↗

Advancing migratory bird conservation and management by using radar: An interagency collaboration

Migratory birds face many changes to the landscapes they traverse and the habitats they use. Wind turbines and communications towers, which pose hazards to birds and bats in flight, are being erected or proposed across the United States and offshore. Human activities can also destroy or threaten habitats critical to birds during migratory passage, and climate change appears to be altering migratory patterns. The U.S. Fish and Wildlife Service (USFWS) and other agencies are under increasing pressure to identify and evaluate movement patterns and habitats used during migration and other times. Few tools for deciphering migratory travels exist, but radar-based studies of movements and habitat use patterns in songbirds, waterfowl, and bats hold promise. The U.S. system of over 150 Doppler weather radars provides continental coverage, similar to the scale of bird migration. Although data stored from weather radar represent perhaps the second largest biological data archive in the world, use of those data is currently limited to technically savvy biologists who can handle the obscure data formats. Complementary mobile radar units and thermal and acoustic monitoring are also used in site-specific studies. Efforts to advance bird conservation and management through the use of radar arose independently in several USFWS/USGS collaborations. Recently, this coalition of scientists and resource managers identified the need to work together more closely to foster radar-related research and software development. U.S. Geological Survey (USGS) scientists at Fort Collins Science Center, National Wetlands Research Center, Northern Rocky Mountain Science Center, and Patuxent Wildlife Research Center, as well as USFWS Migratory Bird biologists across the country, are collaborating with university partners to develop a suite of products for managers. The goals are to identify migratory pathways and stopover sites for conservation, mitigation, and landscape planning; convey the importance of functional landscapes and unobstructed airspaces for migrating wildlife; enable use of radar by the wider biological, wind power, and related communities; and simplify the analysis of radar data. The long term focus is to use radar technologies to better understand movement patterns and habitat associations of migratory birds and other wildlife. Land managers and industry may use the knowledge and tools developed to optimize the siting of energy projects, other facilities, and migratory bird habitat projects. The complementary endeavors, not all of which are funded, concentrate on four fundamentals: (1) develop software, in collaboration with National Oceanic and Atmospheric Administration (NOAA) scientists, that enables biologists to access unfiltered weather data and integrate it into standard geographic information systems; (2) develop artificial intelligence-based filters that separate bird from nonbird radar echoes; (3) determine characteristics of bird migration in terms of altitude, speed and direction, daily movements, seasonality, and associations with habitats and landforms; and (4) examine specific movement patterns in relation to towers, wind generation facilities, and tall obstructions. Many technical issues make this work difficult, including complex data structures, massive data sets, digital recognition of birds, large areas not covered by weather radar, and model validation; however, progress will only be furthered by tackling the challenge. The new coalition will meets its goals by: (1) facilitating a productive collaboration with NOAA, Department of the Interior bureaus, state wildlife agencies, universities, power companies, and other potential partners; (2) building and strengthening scientific capabilities within USGS; (3) addressing key migratory bird management issues; and (4) ensuring full funding for the collaborative effort.

Open-File Report↗

Artificial intelligence based decision support for trumpeter swan management

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

Idaho, Montana, Utah, Wyoming↗

Development of an expert system for assessing trumpeter swan breeding habitat in the Northern Rocky Mountains.

A decision support system for the management of the Rocky Mountain Population of Trumpeter Swans (Cygnus buccinators) is being developed. As part of this, three expert systems are also in development: one for assessing the quality of Trumpeter Swan breeding habitat; one for making water level recommendations in montane, palustrine wetlands; and one for assessing the contribution a particular site can make towards meeting objectives from as flyway perspective. The focus of this paper is the development of the breeding habitat expert system, which currently consists of 157 rules. Out purpose is to provide decision support for issues that appear to be beyond the capability of a single persons to conceptualize and solve. We propose that by involving multiple experts in the development and use of the systems, management will be significantly improved. The knowledge base for the expert system has been developed using standard knowledge engineering techniques with a small team of ecological experts. Knowledge was then coded using production rules organized in decision trees using a commercial expert system development shell. The final system has been deployed on the world wide web.

Rocky Mountains↗

Bayesian time series analysis of segments of the Rocky Mountain trumpeter swan population

A Bayesian time series analysis technique, the dynamic linear model, was used to analyze counts of Trumpeter Swans (Cygnus buccinator) summering in Idaho, Montana, and Wyoming from 1931 to 2000. For the Yellowstone National Park segment of white birds (sub-adults and adults combined) the estimated probability of a positive growth rate is 0.01. The estimated probability of achieving the Subcommittee on Rocky Mountain Trumpeter Swans 2002 population goal of 40 white birds for the Yellowstone segment is less than 0.01. Outside of Yellowstone National Park, Wyoming white birds are estimated to have a 0.79 probability of a positive growth rate with a 0.05 probability of achieving the 2002 objective of 120 white birds. In the Centennial Valley in southwest Montana, results indicate a probability of 0.87 that the white bird population is growing at a positive rate with considerable uncertainty. The estimated probability of achieving the 2002 Centennial Valley objective of 160 white birds is 0.14 but under an alternative model falls to 0.04. The estimated probability that the Targhee National Forest segment of white birds has a positive growth rate is 0.03. In Idaho outside of the Targhee National Forest, white birds are estimated to have a 0.97 probability of a positive growth rate with a 0.18 probability of attaining the 2002 goal of 150 white birds.

Idaho, Montana, Wyoming↗

An application of queuing theory to waterfowl migration

There has always been great interest in the migration of waterfowl and other birds. We have applied queuing theory to modelling waterfowl migration, beginning with a prototype system for the Rocky Mountain Population of trumpeter swans (Cygnus buccinator) in Western North America. The queuing model can be classified as a D/BB/28 system, and we describe the input sources, service mechanism, and network configuration of queues and servers. The intrinsic nature of queuing theory is to represent the spatial and temporal characteristics of entities and how they move, are placed in queues, and are serviced. The service mechanism in our system is an algorithm representing how swans move through the flyway based on seasonal life cycle events. The system uses an observed number of swans at each of 27 areas for a breeding season as input and simulates their distribution through four seasonal steps. The result is a simulated distribution of birds for the subsequent year's breeding season. The model was built as a multiagent system with one agent handling movement algorithms, with one facilitating user interface, and with one to seven agents representing specific geographic areas for which swan management interventions can be implemented. The many parallels in queuing model servers and service mechanisms with waterfowl management areas and annual life cycle events made the transfer of the theory to practical application straightforward.

Rocky Mountains↗

A framework for ecological decision support systems: Building the right systems and building the systems right

Workshops in the late 1990's launched the commitment of the U.S. Geological Survey's Biological Resources Division (BRD) to develop and implement decision support systems (DSS) applications. One of the primary goals of this framework document is to provide sufficient background and information for Department of the Interior (DOI) bureau stakeholders and other clients to determine the potential for DSS development. Such an understanding can assist them in carrying out effective land planning and management practices. This document provides a definition of DSS and its characteristics and capabilities. It proceeds to describe issues related to meeting resource managers needs, such as the needs for specific applications, customer requirements, information and technology transfer, user support, and institutionalization. Using the decision process as a means to guide DSS development and determine users needs is also discussed. We conclude with information on method to evaluate DSS development efforts and recommended procedures for verification and validation.

Information and Technology Report↗