Leveraging collaborative infrastructure for movement ecology to scale insights and preserve biodiversity data

The field of movement ecology offers unique, expanding approaches to document and understand biodiversity on Earth. Widespread changes are occurring in the distribution and abundance of many animal populations, including population declines and changing phenology, migrations and behavior. Data from animal-borne sensors—known as bio-logging or animal tracking—collected by ecologists and wildlife managers offer novel opportunities to investigate animals’ responses to environmental change, mitigate negative impacts on biodiversity and preserve a record of species and behaviors that will be altered or lost in coming decades. In this thesis, I argue that despite considerable investment in collaborative data infrastructures, these data remain underutilized for scaling research insights and conservation impacts, with most datasets at risk of loss within a generation. To address this, I propose innovations that build on existing successes to drive their preservation and beneficial use. In Chapter 2, I convene an international group of movement ecologists, database managers, hardware and software developers and experts in data standards. We report on the results of a community consultation on the collection, sharing and archiving of bio-logging data. We provide evidence that despite the growth of shared data platforms, a large majority of bio-logging datasets remain undiscoverable and on track to become inaccessible. We then present a vision for standards to describe, transfer and aggregate bio-logging data, along with tools to ensure long-term access through curated data collections. These proposals offer a roadmap for data integration to foster cross-disciplinary use, enable time-sensitive applications and expand digital natural history archives. Finally, we call for the launch of a community-led body to coordinate these efforts and provide an inventory of specific recommendations for relevant stakeholders, including funding agencies, publishers and museums. In Chapter 3, co-authors and I present the Arctic Animal Movement Archive, a collection of over 200 curated datasets that document animal movements and behavior in the Arctic and subarctic. The archive represents over three decades of harmonized information about 86 species in terrestrial and marine environments. This archive demonstrates the kind of living data collection proposed in Chapter 2, supporting real-time data collection, public discovery of both public and controlled-access data, and networking to initiate new projects. Through analysis of participating datasets, we offer insights into the influence of climate on animal behavior across decades, continents and species. First, we find that following warmer winters, golden eagles arrive at their Arctic summering grounds earlier, with evidence for age-specific impacts of climate variability on phenology. Second, we find that more northern caribou populations are calving earlier than at the turn of the century, possibly indicating an adaptive response to climate change. Third, we show that movement rates of terrestrial mammals are affected by weather in ways that vary among species, potentially altering predator-prey relationships. We finally invite future participation and collaborative analyses using the archive. In Chapter 4, I introduce a collection of empirical and synthesis research studies that investigate Arctic animal migrations. I place this work in the context of our current knowledge of amplified warming in the Arctic and limits on how vertebrate animals can respond to this change through natural selection and phenotypic plasticity. I then survey the studies in the collection from multiple perspectives. First, the studies present newly documented migrations or possible range expansions of twelve species. Second, they offer novel demonstrations of among-individual variation and within-individual plasticity. Third, they provide insights into how populations are being affected by changes within and across trophic levels. Fourth, they demonstrate a wide range of research methods, including established and novel approaches. I synthesize shared calls for future work and data needs, including gaps in baseline information needed to understand patterns in population size and distribution. Further, I provide evidence that these data gaps are due in part to a lack of integration of existing sensor-based biodiversity data. The piece concludes with an outlook on future approaches to research and management in the region, and to defining conservation goals, in the context of Arctic climate change. In Chapter 5, co-authors and I introduce ECODATA, a set of open-source, graphical user interface software applications for movement ecologists and wildlife managers. These programs are developed with a network of experts practicing wildlife conservation and management in the Yellowstone-to-Yukon migration corridor, with the goal to meet shared analysis needs to improve the use of wildlife tracking data for communication and decision making. ECODATA-Prepare offers tools to assess and process large environmental geospatial datasets, and ECODATA-Animate supports the creation of custom, dynamic geospatial data animations. Both tools support access and visual analysis of animal tracking data along with remote sensing, weather reanalysis and physical feature datasets that influence animal behavior. We demonstrate use of the software to process big data and build animations visualizing movements of predator and prey species near transportation infrastructure, as well as movements of female caribou with associated calving events, both in the context of seasonal vegetation changes. We further publish the two case study animations along with reproducible steps to prepare inputs and settings. The software builds on existing collaborative infrastructure for movement ecology to offer interoperability, shared data protocols and joint analysis across jurisdictions. Together, this work reveals knowledge that can be gained through the use of bio-logging technology and the potential for collaborative infrastructure to advance movement ecology and biodiversity conservation. Further, it provides new evidence for the volume of data and expertise that are missing from existing platforms and initiatives. In this context, I offer social and technical paths forward to improve the volume, quality and accessibility of these data. Looking forward, I discuss current efforts to reimagine movement ecology, shifting from a tradition of isolated, project-specific data collection to coordinated global research and resources for biodiversity monitoring. I further detail opportunities to improve collaborative infrastructure through data stewardship. Finally, I outline emerging challenges and approaches that movement ecologists can take to address them. While ecological studies can and should continue to be driven by local needs and questions, coordination through shared research guidelines, standards and software can offer improved access to data, insights and expertise, now and for future generations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.