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Jason Osenkowski

Publications and source records attributed to Jason Osenkowski.

3 recordsLinked to original sources

Evaluating conservation units using network analysis: A sea duck case study

Conserving migratory wildlife requires understanding how groups of individuals interact across seasons and landscapes. Telemetry reveals individual movements at large spatiotemporal scales; however, using movement data to define conservation units requires scaling up from individual movements to species- and community-level patterns. We developed a framework to define flyways and identify important sites from telemetry data and applied it to long-term, range-wide tracking data from three species (640 individuals) of sea ducks: namely, North American scoters ( Melanitta spp). Our network of 88 nodes included both multispecies hotspots and areas uniquely important to individual species. We found limited spatial overlap between scoters wintering on the Atlantic and Pacific coasts of North America, with differing connectivity patterns between coasts. Finally, we identified four multispecies conservation units that did not correspond to traditional management flyways. From this approach, we show how individual movements can be used to quantify range-wide connectivity of migratory species and reveal gaps in conservation strategies.

Frontiers in Ecology and the Environment

Visualizing populations of North American sea ducks: Maps to guide research and management planning

North American sea ducks generally breed in mid- to northern-latitude regions and nearly all rely upon marine habitats for much of their annual cycle. Most sea duck species remained poorly studied until the 1990s when declines were noted in several species and populations. Subsequent research, much of which was funded by the Sea Duck Joint Venture, began in the late 1990s with an emphasis on defining use areas throughout the annual cycle, migration patterns, and determining if there were distinct populations, within species, across North America. These studies relied largely upon satellite telemetry information to identify winter, breeding, and molting areas of sea ducks. New information from band recovery and genetic markers was added, contributing to hypotheses and initial conclusions about population delineation. Information on population units across North America is critical for identifying appropriate scales for evaluating population status and trends through annual monitoring surveys, harvest assessments, habitat protection and measuring effectiveness of management applications. Previous descriptions of population segments were for single species or smaller groups of similar species. Here, we summarize current knowledge on the general distribution and population segments of 13 species of sea ducks in North America by comparing range maps to long-term band recovery, genetic, and satellite telemetry data to inform population delineation assessments and future research. These comparisons show a high degree of consistency in population patterns for most species across the independent data types. These maps provide a foundation for developing new hypothesis-driven research to address remaining knowledge gaps and questions about population differentiation, annual cycle distribution, habitat use, and harvest assessment.

North America

Incorporating temporal variation in seabird telemetry data: time variant kernel density models

A key component of the Mid-Atlantic Baseline Studies project was tracking the individual movements of focal marine bird species (Red-throated Loon [Gavia stellata], Northern Gannet [Morus bassanus], and Surf Scoter [Melanitta perspicillata]) through the use of satellite telemetry. This element of the project was a collaborative effort with the Department of Energy (DOE), Bureau of Ocean Energy Management (BOEM), the U.S. Fish and Wildlife Service (USFWS), and Sea Duck Joint Venture (SDJV), among other organizations. Satellite telemetry is an effective and informative tool for understanding individual animal movement patterns, allowing researchers to mark an individual once, and thereafter follow the movements of the animal in space and time. Aggregating telemetry data from multiple individuals can provide information about the spatial use and temporal movements of populations. Tracking data is three dimensional, with the first two dimensions, X and Y, ordered along the third dimension, time. GIS software has many capabilities to store, analyze and visualize the location information, but little or no support for visualizing the temporal data, and tools for processing temporal data are lacking. We explored several ways of analyzing the movement patterns using the spatiotemporal data provided by satellite tags. Here, we present the results of one promising method: time-variant kernel density analysis (Keating and Cherry, 2009). The goal of this chapter is to demonstrate new methods in spatial analysis to visualize and interpret tracking data for a large number of individual birds across time in the mid-Atlantic study area and beyond. In this chapter, we placed greater emphasis on analytical methods than on the behavior and ecology of the animals tracked. For more detailed examinations of the ecology and wintering habitat use of the focal species in the midAtlantic, see Chapters 20-22.

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