DocumentCode :
1365666
Title :
BirdVis: Visualizing and Understanding Bird Populations
Author :
Ferreira, Nivan ; Lins, Lauro ; Fink, Daniel ; Kelling, Steve ; Wood, Chris ; Freire, Juliana ; Silva, Cláudio
Volume :
17
Issue :
12
fYear :
2011
Firstpage :
2374
Lastpage :
2383
Abstract :
Birds are unrivaled windows into biotic processes at all levels and are proven indicators of ecological well-being. Understanding the determinants of species distributions and their dynamics is an important aspect of ecology and is critical for conservation and management. Through crowdsourcing, since 2002, the eBird project has been collecting bird observation records. These observations, together with local-scale environmental covariates such as climate, habitat, and vegetation phenology have been a valuable resource for a global community of educators, land managers, ornithologists, and conservation biologists. By associating environmental inputs with observed patterns of bird occurrence, predictive models have been developed that provide a statistical framework to harness available data for predicting species distributions and making inferences about species-habitat associations. Understanding these models, however, is challenging because they require scientists to quantify and compare multiscale spatialtemporal patterns. A large series of coordinated or sequential plots must be generated, individually programmed, and manually composed for analysis. This hampers the exploration and is a barrier to making the cross-species comparisons that are essential for coordinating conservation and extracting important ecological information. To address these limitations, as part of a collaboration among computer scientists, statisticians, biologists and ornithologists, we have developed BirdVis, an interactive visualization system that supports the analysis of spatio-temporal bird distribution models. BirdVis leverages visualization techniques and uses them in a novel way to better assist users in the exploration of interdependencies among model parameters. Furthermore, the system allows for comparative visualization through coordinated views, providing an intuitive interface to identify relevant correlations and patterns. We justify our design decisions and present case s- udies that show how BirdVis has helped scientists obtain new evidence for existing hypotheses, as well as formulate new hypotheses in their domain.
Keywords :
data visualisation; ecology; environmental science computing; statistical analysis; zoology; BirdVis; biotic processes; bird observation records; bird population understanding; bird population visualization; climate; conservation biologists; crowdsourcing; eBird project; ecological well being; ecology; habitat; interactive visualization system; land managers; local scale environmental covariates; multiscale spatial temporal patterns; ornithologists; spatio temporal bird distribution models; species-habitat associations; statistical framework; vegetation phenology; Biological system modeling; Data visualization; Ornithology; Predictive models; Spatial databases; Tag clouds; Ornithology; multiscale analysis; spatial data; species distribution models; temporal data.; Animals; Artificial Intelligence; Birds; Computer Graphics; Computer Simulation; Databases, Factual; Ecosystem; Flight, Animal; Models, Biological; Population Dynamics; Software; Songbirds; Species Specificity; User-Computer Interface;
fLanguage :
English
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
Publisher :
ieee
ISSN :
1077-2626
Type :
jour
DOI :
10.1109/TVCG.2011.176
Filename :
6065004
Link To Document :
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