Abstract
AbstractIncreasing public engagement in volunteer science1, either through data collection2 or processing3, is both raising public awareness of science and gathering useful information for scientists. While the payoffs of citizen science4 are potentially large, achieving them requires new approaches to data management and analysis that can only result from strong cross-disciplinary collaborations. This is especially true in ecology and conservation biology, where historically the understanding of species’ responses to environmental change has been constrained by the limited spatial5 or temporal scale6 of available data. Here we describe collaborative research in ecology, computer science, and statistics to generate essential information for conservation management of North American birds: accurate dynamic bird distributions models based on habitat associations across much of North America. Unique is our ability to describe the broad-scale dynamics of seasonal bird distributions and the associated seasonal patterns of habitat use. Our source of bird distribution data is eBird7, an online bird checklist program that currently gathers more than 74,000 checklists monthly from a large network of contributors. Our results were made possible through a data intensive scientific workflow8 that includes analytical methods merged from the fields of machine learning and statistics. We believe that this novel approach of data collection, synthesis, analysis, and visualization will serve as a hallmark for future research initiatives, with broad applicability across many scientific domains.
Highlights
Increasing public engagement in volunteer science, either through data collection or processing, is both raising public awareness of science and gathering useful information for scientists
While the payoffs of citizen science are potentially large, achieving them requires new approaches to data management and analysis that can only result from strong cross-disciplinary collaborations
This is especially true in ecology and conservation biology, where historically the understanding of species’ responses to environmental change has been constrained by the limited spatial or temporal scale of available data
Summary
Increasing public engagement in volunteer science, either through data collection or processing, is both raising public awareness of science and gathering useful information for scientists. Essential information for conservation management of North American birds: accurate dynamic bird distributions models based on habitat associations across much of North America. Unique is our ability to describe the broad-scale dynamics of seasonal bird distributions and the associated seasonal patterns of habitat use.
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