Monitoring Wildlife Interactions with Their Environment: an Interdisciplinary Approach
Objective: In a rapidly changing world, wildlife ecologists strive to correctly model and predict complex relationships between animals and their environment, which facilitates management decisions impacting public policy to conserve and protect delicate ecosystems. Recent advances in monitoring systems span scientific domains, including animal and weather monitoring devices and landscape classification mapping techniques. The current challenge is how to combine and use detailed output from various sources to address questions spanning multiple disciplines.
Methods: WolfScout wildlife and weather tracking system is a software tool capable of filling this niche. WolfScout automates the integration of the latest technological advances in wildlife GPS collars, weather stations, drought conditions, and severe weather reports, and animal demographic information. The database stores a variety of classified landscape maps including natural and manmade features. Additionally, WolfScout’s spatial database management system allows users to calculate distances between animals’ location and landscape characteristics, which are linked to the best approximation of environmental conditions at the animal’s location during the interaction.
Results: The WolfScout system is an exemplary utility that provides researchers with an interdisciplinary approach to monitor wildlife interactions with their environment. To standardize information used in research projects, high quality data from multiple scientific fields is integrated and formatted for direct analysis. The animal, weather, and spatial calculations with landscape metadata can be extracted in various combinations through the web-interface dependent on the proposed hypotheses and desired mathematical models. Successful deployment at Fort Bragg Military Reserve resulted in management implications for wildlife-longleaf pine ecosystems.
Conclusion: The WolfScout wildlife and weather tracking system promotes interoperability between data sources, software applications, and research projects, which facilitates our ability to tackle and model complex questions affecting wildlife interactions with their environment. The development of this novel data management tool is a solid step towards the future direction of interdisciplinary science.
Lauren E Charles-Smith, Ignacio X Domínguez, Robert J Fornaro, Christopher S DePerno, and Suzanne Kennedy-Stoskopf
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