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USGS2000

Sampling for mercury at subnanogram per litre concentrations for load estimation in rivers

Estimation of constituent loads in streams requires collection of stream samples that are representative of constituent concentrations, that is, composites of isokinetic multiple verticals collected along a stream transect. An all-Teflon isokinetic sampler (DH-81) cleaned in 75??C, 4 N HCl was tested using blank, split, and replicate samples to assess systematic and random sample contamination by mercury species. Mean mercury concentrations in field-equipment blanks were low: 0.135 ng??L-1 for total mercury (??Hg) and 0.0086 ng??L-1 for monomethyl mercury (MeHg). Mean square errors (MSE) for ??Hg and MeHg duplicate samples collected at eight sampling stations were not statistically different from MSE of samples split in the laboratory, which represent the analytical and splitting error. Low fieldblank concentrations and statistically equal duplicate- and split-sample MSE values indicate that no measurable contamination was occurring during sampling. Standard deviations associated with example mercury load estimations were four to five times larger, on a relative basis, than standard deviations calculated from duplicate samples, indicating that error of the load determination was primarily a function of the loading model used, not of sampling or analytical methods.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2020

Moving from decision to action in conservation science

Biodiversity loss is a major threat to the integrity of ecosystems and is projected to worsen, yet the path to successful conservation remains elusive. Decision support frameworks (DSFs) are increasingly applied by resource managers to navigate the complexity, uncertainty, and differing socio-ecological objectives inherent to conservation problems. Most published conservation research that uses DSFs focuses on analytical stages (e.g., identifying an optimal decision), making it difficult to assess and learn from previous examples in a conservation practice context. Here, we (1) evaluate the relationship between the application of decision science and the resulting conservation outcomes, and (2) identify and address existing barriers to the application of DSFs to conservation practice. To do this, we develop a framework for evaluating conservation initiatives using decision science that emphasizes setting attainable goals, building momentum, and obtaining partner buy-in. We apply this framework to a systematic review of amphibian conservation decision support projects, including a follow-up survey of the pertinent conservation practitioners, stakeholders, and scientists. We found that all projects identified optimal solutions to reach stated objectives, but positive conservation outcomes were limited when implementation challenges arose. Further, we identified multiple barriers (e.g., dynamic and hierarchical leadership, scale complexity, limited resource availability) that can inhibit the progression from decision identification to action implementation (i.e., ‘decision-implementation gap’), and to successful conservation outcomes. Based on these results, we provide potential actionable steps and avenues for future development of DSFs to facilitate the transition from decision to action and the realization of conservation successes.

Biological Conservation↗

USGS2012

The Stanford-U.S. Geological Survey SHRIMP ion microprobe--a tool for micro-scale chemical and isotopic analysis

Answers to many questions in Earth science require chemical analysis of minute volumes of minerals, volcanic glass, or biological materials. Secondary Ion Mass Spectrometry (SIMS) is an extremely sensitive analytical method in which a 5–30 micrometer diameter "primary" beam of charged particles (ions) is focused on a region of a solid specimen to sputter secondary ions from 1–5 nanograms of the sample under high vacuum. The elemental abundances and isotopic ratios of these secondary ions are determined with a mass spectrometer. These results can be used for geochronology to determine the age of a region within a crystal thousands to billions of years old or to precisely measure trace abundances of chemical elements at concentrations as low as parts per billion. A partnership of the U.S. Geological Survey and the Stanford University School of Earth Sciences operates a large SIMS instrument, the Sensitive High-Resolution Ion Microprobe with Reverse Geometry (SHRIMP–RG) on the Stanford campus.

Fact Sheet↗

USGS2019

Analytical framework to estimate water use associated with continuous oil and gas development

An analytical framework was designed to estimate water use associated with continuous oil and gas (COG) development in support of the U.S. Geological Survey Water Availability and Use Science Program. This framework was developed to better understand the relation between the production of COG resources for energy and the amount of water needed to sustain this type of energy development in the United States. The total mean undiscovered, technically recoverable volume of COG has increased, highlighting the continued need to develop approaches to better characterize water use associated with COG development. The analytical framework can be used to estimate water use associated with COG development for three water-use components—direct, indirect, and ancillary water use—that are related to the life cycle of COG development. Direct water use is defined as water used in a wellbore to complete a well, including the water used for drilling, cementing, stimulating, and maintaining the well during production. Indirect water use is the water used at or near the well site, including water used for dust abatement, for cleaning equipment, and for crew and staff use. Ancillary water use is all other water used during the life cycle of COG development that is not categorized as direct or indirect, such as additional local or regional water use resulting from a change (for example, population) related to COG development. The analytical framework includes the data inputs, the processes involved in estimating the water-use coefficients and analyzing their uncertainties, and the outputs. The analytical framework was developed as an R script, which contains the statistical models used to estimate water-use components. The availability of data across COG reservoirs in the United States is variable and presents challenges for estimating water use for extracting COG from their reservoirs; thus, the R script can be modified for the types of data available within a COG reservoir, the extent and resolution of data available for each water-use component, and the desired output of the water-use assessment. The script was written so that the units of the data in the script were standardized. Water-use estimates were simulated for the mean and 10th, 50th, and 90th percentiles of the data distributions. Uncertainties were quantified with confidence intervals for the estimated coefficients. Uncertainty for estimated or simulated data can be calculated with the R script by providing a range of representative values that are within the appropriate confidence intervals of the mean of the data.

Lower 48 states↗

USGS2021

Cyprosulfamide: Analysis of the herbicide safener and two of its degradates in surface water and groundwater from the Midwestern United States

Herbicide safeners are commonly included in herbicide formulations to selectively protect crops from herbicide toxicity but are poorly understood in terms of their environmental occurrence and fate. This study established an analytical method for a newer safener, cyprosulfamide, and two of its degradates, cyprosulfamide desmethyl and N -cyclopropyl-4-sulfamoylbenzamide, in water via solid-phase extraction and liquid chromatography with tandem mass spectroscopy. To evaluate the potential for off-field transport and transformation of cyprosulfamide, the method was used to analyze groundwater and surface water samples collected near cornfields in the midwestern United States where cyprosulfamide had been applied. All three compounds were detected in surface water samples ( N = 34); N -cyclopropyl-4-sulfamoylbenzamide was most frequently detected (56%), followed by cyprosulfamide (25%) and cyprosulfamide desmethyl (19%). Maximum concentrations ranged from 22.0 to 5185.9 ng/L, with the highest concentrations and detection rates during the growing season. None of our target analytes were detected in groundwater.

ACS Agricultural Science and Technology↗

USGS2022

A framework to integrate innovations in invasion science for proactive management

Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.

Biological Reviews↗

USGS1989

40Ar-39Ar dating of the Manson impact structure: A Cretaceous-Tertiary boundary crater candidate

The mineralogy of shocked mineral and lithic grains in the Cretaceous-Tertiary (K-T) boundary claystone worldwide is most consistent with a bolide impact on a continent. Both the concentrations and sizes of these shocked grains are greatest in the western interior of North America. These data suggest that the Manson impact structure in north-central Iowa is a viable candidate for the K-T boundary impact event. Argon-40–argon-39 age spectrum dating of shocked microcline from the crystalline central uplift of the Manson impact structure indicates that there was severe argon-40 loss at 65.7 ± 1.0 million years ago, an age that is indistinguishable from that of the K-T boundary, within the limits of analytical precision.

Science↗

USGS2007

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Computers & Geosciences↗

USGS2018

Executive summary. In Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report

Central to life on Earth, carbon is essential to the molecular makeup of all living things and plays a key role in regulating global climate. To understand carbon’s role in these processes, researchers measure and evaluate carbon stocks and fluxes. A stock is the quantity of carbon contained in a pool or reservoir in the Earth system (e.g., carbon in forest trees), and a flux is the direction and rate of carbon’s transfer between pools (e.g., the movement of carbon from the atmosphere into forest trees during photosynthesis). This document, the Second State of the Carbon Cycle Report (SOCCR2), examines the patterns of carbon stocks and fluxes—collectively called the “carbon cycle.” Emphasis is given to these patterns in specific sectors (e.g., agriculture and energy) and ecosystems (e.g., forests and coastal waters) and to the response of the carbon cycle to human activity. The purpose of SOCCR2 is to assess the current state of the North American carbon cycle and to present recent advances in understanding the factors that influence it. Concentrating on North America—Canada, the United States, and Mexico—the report describes carbon cycling for air, land, inland waters (streams, rivers, lakes, and reservoirs), and coastal waters (see Figure ES.1, p. 23). The questions framing the publication A U.S. Carbon Cycle Science Plan (Michalak et al., 2011) inspired development of three slightly modified questions that guide SOCCR2’s content and focus on North America in a global context: How have natural processes and human actions affected the global carbon cycle on land, in the atmosphere, in the ocean and other aquatic systems, and at ecosystem interfaces (e.g., coastal, wetland, and urban-rural)? How have socioeconomic trends affected atmospheric levels of the primary carbon-containing gases, carbon dioxide (CO2) and methane (CH4)? How have species, ecosystems, natural resources, and human systems been impacted by increasing greenhouse gas (GHG) concentrations, associated changes in climate, and carbon management decisions and practices? SOCCR2 synthesizes the most recent understanding of carbon cycling in North America, assessing new carbon cycle findings and information, the state of knowledge regarding core methods used to study the carbon cycle, and future research needed to best inform carbon management and policy options. Focusing on scientific developments in the decade since the First State of the Carbon Cycle Report (SOCCR1; CCSP 2007), SOCCR2 summarizes the past, current, and projected state of carbon sources, sinks, and natural processes, as well as contributions by human activities. In addition to CO2 and CH4, the report sometimes discusses nitrous oxide (N2O), a GHG associated with activities and processes that affect fluxes of carbon gases.1 SOCCR2 also describes improvements in analysis tools; developments in decision support; and new insights into ecosystem carbon cycling, human causes of changes in the carbon cycle, and social science perspectives on carbon. Since publication of SOCCR1, coordinated research from agencies in the three North American countries has enabled innovative observational, analytical, and modeling capabilities to further advance understanding of the North American carbon cycle (see Appendix D: Carbon Measurement Approaches and Accounting Frameworks, p. 834). Some of the report’s main conclusions, based on the Key Findings of each chapter, are highlighted in Box ES.1, Main Findings of SOCCR2, p. 24.

Report↗

USGS2024

Integrated science for the study of microplastics in the environment—A strategic science vision for the U.S. Geological Survey

Executive Summary Evidence of the widespread occurrence of microplastics throughout our environment and exposure to humans and other organisms over the past decade has led to questions about the possibility of health hazards and mitigation of exposures. This document discusses nanoplastics as well as microplastics (referred to solely as microplastics); the microplastics have a range from 1 micrometer to 5 millimeters (1 μm–5 mm) in length, whereas the nanoplastics are less than 1 μm in length (sidebar ES1). A myriad of environmental exposure pathways with microplastics to humans and wildlife, including ingestion, inhalation, and bodily absorption, are likely to exist. A growing body of evidence has documented bioaccumulation of microplastics in tissues and organs of humans and wildlife, benthic community effects, and potential nutritional and reproductive effects in some wildlife species. Understanding if or when environmental exposures pose a health risk is complicated by the diversity of microplastic sizes, morphologies, polymer types, and chemicals added during manufacturing or sorbed from the environment; ongoing challenges in analytical methods used to detect, quantify, and characterize microplastics and associated chemicals in our ecosystems; and the fact that ecotoxicological studies regarding microplastics are still in their infancy. Therefore, the study of environmental exposures and potential related health hazards of microplastics to the public and wildlife is a One Health (sidebar ES2) research topic that necessitates integrated science approaches. A better understanding of the sources, pathways, fate, and biological effects of microplastics has become a priority of the Federal Government, State governments, Tribes, stakeholders, and the public. Examples of Federal and State microplasticfocused legislation and programs to prioritize microplastic research and reduction include the Federal Microbead-Free Waters Act of 2015, California Senate Bills 1422 and 1263 (2018), the U.S. Environmental Protection Agency (EPA) Trash Free Waters Program, the National Institute of Standards and Technology’s Microplastic and Nanoplastic Metrology project, and Minnesota’s microplastic project. With its unique expertise and capabilities, the U.S. Geological Survey (USGS) is well positioned to help fill some of the most important microplastic science gaps. This strategic science vision document for microplastics identifies current (2023) microplastic science gaps and prioritizes research relevant to the mission, expertise, and capabilities of the USGS. It is intended for USGS scientists and stakeholders to use as a starting point for planning, prioritizing, and designing collaborative environmental microplastic science. Many of the microplastic science gaps and priorities are scalable, from local to national, and thus, can be made commensurate with available funding and evolving analytical and field tools, laboratory capacity, and stakeholder needs. Current (2023) or future research by academia and other Federal or State agencies, and Tribes may be aimed at some of the same microplastic science gaps identified in this document. Therefore, this document can be used as an information resource to maximize strengths and capabilities and minimize redundancy in communication and collaboration.

Circular↗

USGS2007

Potential for shoreline changes due to sea-level rise along the U.S. mid-Atlantic region

Sea-level rise over the next century is expected to contribute significantly to physical changes along open-ocean shorelines. Predicting the form and magnitude of coastal changes is important for understanding the impacts to humans and the environment. Presently, the ability to predict coastal changes is limited by the scientific understanding of the many variables and processes involved in coastal change, and the lack of consensus regarding the validity of existing conceptual, analytical, or numerical models. In order to assess potential future coastal changes in the mid-Atlantic U.S. for the U.S. Climate Change Science Program (CCSP), a workshop was convened by the U.S. Geological Survey. Assessments of future coastal change were made by a committee of coastal scientists with extensive professional experience in the mid-Atlantic region. Thirteen scientists convened for a two-day meeting to exchange information and develop a consensus opinion on potential future coastal changes for the mid-Atlantic coast in response to sea-level rise. Using criteria defined in past work, the mid-Atlantic coast was divided into four geomorphic compartments: spits, headlands, wave-dominated barriers, and mixed-energy barriers. A range of potential coastal responses was identified for each compartment based on four sea-level rise scenarios. The four scenarios were based on the assumptions that: a) the long-term sea-level rise rate observed over the 20th century would persist over the 21st century, b) the 20th century rate would increase by 2 mm/yr, c) the 20th century rate would increase by 7 mm/yr, or d) sea-level would rise by 2 m over the next few hundred years. Potential responses to these sea-level rise scenarios depend on the landforms that occur within a region and include increased likelihood for erosion and shoreline retreat for all coastal types, increased likelihood for erosion, overwash and inlet breaching for barrier islands, as well as the possibility of a threshold state (e.g., dramatic change in barrier evolution, such as segmentation or disintegration) for some barrier island systems. The likelihood of the potential coastal responses is expressed using standard terminology employed in climate change assessments (e.g., as used by the Intergovernmental Panel on Climate Change and CCSP). This assessment was based on the coastal geomorphology in its present condition and does not consider any coastal protection that might be undertaken in the future. The committee recognized that a variety of erosion mitigation measures have been implemented along developed portions of the coast and these are very likely to be applied in the future. It was also acknowledged that economics, political will, and other factors can drive decisions to implement these measures, and that such decisions cannot be predicted with confidence. The results of this assessment are depicted graphically on maps of the study area.

Mid-Atlantic Coast↗

USGS1981

United States Geological Survey Yearbook, fiscal year 1980

It is not very often that a single event is so overwhelming that it changes public perceptions of natural hazards for generations. Perhaps for the U.S. Geological Survey, the explosive volcanic activity of Mount St. Helens began such a change. After 101 years of careful science of the Earth's past and meticulous observations and assessments of the present, predictive earth science was in full public view. However vague and faint the glimpse of the future made possible by earth science, it was enough. Warnings were issued, thousands of lives were saved, and the age of real-time geology began. The Survey's basic mission has not changed, but the power of our analytical tools has increased by several orders of magnitude. The Survey's efforts to understand Earth processes and hydrologic principles continued with the collection, during fiscal year 1980, of valuable new data on the geologic origin and framework, seismicity, and mineral and energy resources of the United States. The Survey is also responsible for classification of the leasable minerals on Federal lands and the regulation of mineral exploration and development activities on Federal and Indian lands. As the principal earth science fact-gathering agency, the Survey provides information for sound decisionmaking by government and private industry. Industry uses the Survey's information in exploring for energy and minerals and improving their efforts to make development of energy and minerals compatible with environmental protection standards. Government uses the Survey's information in conducting leasing operations on public lands, in regulating the safe design and siting of nuclear plants, and in establishing guidelines for determining and locating areas that are subject to geologic hazards such as landslides, earthquakes, and volcanic eruptions. The Yearbook reports a broad range of the Survey's accomplishments during the past fiscal year and provides an overview of future directions. Many of the topics covered will continue to be important natural resource and earth science issues of the 1980's.

Yearbook↗

USGS2022

A golden era for volcanic gas geochemistry?

The exsolution, rise, expansion, and separation of volatiles from magma provides the driving force behind both effusive and explosive volcanic eruptions. The field of volcanic gas geochemistry therefore plays a key role in understanding volcanism. In this article, we summarize the most important findings of the past few decades and how these shape today’s understanding of volcanic degassing. We argue that the recent advent of automated, continuous geochemical monitoring at volcanoes now allows us to track activity from unrest to eruption, thus providing valuable insights into the behavior of volatiles throughout the entire sequence. In the next 10 years, the research community stands to benefit from the expansion of geochemical monitoring networks to many more active volcanoes. This, along with technical advances in instrumentation, and in particular the increasing role that unoccupied aircraft systems (UAS) and satellite-based observations are likely to play in collecting volcanic gas measurements, will provide a rich dataset for testing hypotheses and developing diagnostic tools for eruption forecasts. The use of consistent, well-documented analytical methods and ensuring free, public access to the collected data with few restrictions will be most beneficial to the advancement of volcanic gas science.

Bulletin of Volcanology↗

USGS2000

Analytical group decision making in natural resources: Methodology and application

Group decision making is becoming increasingly important in natural resource management and associated scientific applications, because multiple values are treated coincidentally in time and space, multiple resource specialists are needed, and multiple stakeholders must be included in the decision process. Decades of social science research on decision making in groups have provided insights into the impediments to effective group processes and on techniques that can be applied in a group context. Nevertheless, little integration and few applications of these results have occurred in resource management decision processes, where formal groups are integral, either directly or indirectly. A group decision-making methodology is introduced as an effective approach for temporary, formal groups (e.g., workshops). It combines the following three components: (1) brainstorming to generate ideas; (2) the analytic hierarchy process to produce judgments, manage conflict, enable consensus, and plan for implementation; and (3) a discussion template (straw document). Resulting numerical assessments of alternative decision priorities can be analyzed statistically to indicate where group member agreement occurs and where priority values are significantly different. An application of this group process to fire research program development in a workshop setting indicates that the process helps focus group deliberations; mitigates groupthink, nondecision, and social loafing pitfalls; encourages individual interaction; identifies irrational judgments; and provides a large amount of useful quantitative information about group preferences. This approach can help facilitate scientific assessments and other decision-making processes in resource management.

Forest Science↗

USGS2013

Has the time come for big science in wildlife health?

The consequences of wildlife emerging diseases are global and profound with increased burden on the public health system, negative impacts on the global economy, declines and extinctions of wildlife species, and subsequent loss of ecological integrity. Examples of health threats to wildlife include Batrachochytrium dendrobatidis , which causes a cutaneous fungal infection of amphibians and is linked to declines of amphibians globally; and the recently discovered Pseudogymnoascus (Geomyces) destructans , the etiologic agent of white nose syndrome which has caused precipitous declines of North American bat species. Of particular concern are the novel pathogens that have emerged as they are particularly devastating and challenging to manage. A big science approach to wildlife health research is needed if we are to make significant and enduring progress in managing these diseases. The advent of new analytical models and bench assays will provide us with the mathematical and molecular tools to identify and anticipate threats to wildlife, and understand the ecology and epidemiology of these diseases. Specifically, new molecular diagnostic techniques have opened up avenues for pathogen discovery, and the application of spatially referenced databases allows for risk assessments that can assist in targeting surveillance. Long-term, systematic collection of data for wildlife health and integration with other datasets is also essential. Multidisciplinary research programs should be expanded to increase our understanding of the drivers of emerging diseases and allow for the development of better disease prevention and management tools, such as vaccines. Finally, we need to create a National Fish and Wildlife Health Network that provides the operational framework (governance, policies, procedures, etc.) by which entities with a stake in wildlife health cooperate and collaborate to achieve optimal outcomes for human, animal, and ecosystem health.

EcoHealth↗

USGS2013

A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?

Successful environmental/water quality-monitoring programs usually require a balance between analytical capabilities, the collection and preservation of representative samples, and available financial/personnel resources. Due to current economic conditions, monitoring programs are under increasing pressure to do more with less. Hence, a review of current sampling and analytical methodologies, and some of the underlying assumptions that form the bases for these programs seems appropriate, to see if they are achieving their intended objectives within acceptable error limits and/or measurement uncertainty, in a cost-effective manner. That evaluation appears to indicate that several common sampling/processing/analytical procedures (e.g., dip (point) samples/measurements, nitrogen determinations, total recoverable analytical procedures) are generating biased or nonrepresentative data, and that some of the underlying assumptions relative to current programs, such as calendar-based sampling and stationarity are no longer defensible. The extensive use of statistical models as well as surrogates (e.g., turbidity) also needs to be re-examined because the hydrologic interrelationships that support their use tend to be dynamic rather than static. As a result, a number of monitoring programs may need redesigning, some sampling and analytical procedures may need to be updated, and model/surrogate interrelationships may require recalibration.

Environmental Science & Technology↗

USGS2020

What processes must we understand to forecast regional-scale population dynamics?

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.

Proceedings of the Royal Society B: Biological Sci↗

USGS2012

Discovering shared segments on the migration route of the bar-headed goose by time-based plane-sweeping trajectory clustering

We propose a new method to help ornithologists and ecologists discover shared segments on the migratory pathway of the bar-headed geese by time-based plane-sweeping trajectory clustering. We present a density-based time parameterized line segment clustering algorithm, which extends traditional comparable clustering algorithms from temporal and spatial dimensions. We present a time-based plane-sweeping trajectory clustering algorithm to reveal the dynamic evolution of spatial-temporal object clusters and discover common motion patterns of bar-headed geese in the process of migration. Experiments are performed on GPS-based satellite telemetry data from bar-headed geese and results demonstrate our algorithms can correctly discover shared segments of the bar-headed geese migratory pathway. We also present findings on the migratory behavior of bar-headed geese determined from this new analytical approach.

Journal of Information and Computational Science↗