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| Content Provider | Springer Nature Link |
|---|---|
| Author | Chapron, Guillaume |
| Copyright Year | 2015 |
| Abstract | Research in wildlife management increasingly relies on quantitative population models. However, a remaining challenge is to have end-users, who are often alienated by mathematics, benefiting from this research. I propose a new approach, ‘wildlife in the cloud,’ to enable active learning by practitioners from cloud-based ecological models whose complexity remains invisible to the user. I argue that this concept carries the potential to overcome limitations of desktop-based software and allows new understandings of human-wildlife systems. This concept is illustrated by presenting an online decision-support tool for moose management in areas with predators in Sweden. The tool takes the form of a user-friendly cloud-app through which users can compare the effects of alternative management decisions, and may feed into adjustment of their hunting strategy. I explain how the dynamic nature of cloud-apps opens the door to different ways of learning, informed by ecological models that can benefit both users and researchers. |
| Starting Page | 550 |
| Ending Page | 556 |
| Page Count | 7 |
| File Format | |
| ISSN | 00447447 |
| Journal | AMBIO |
| Volume Number | 44 |
| Issue Number | 4 |
| e-ISSN | 16547209 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2015-10-27 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Population models Cloud-computing Wildlife management Moose Wolf Bear Environment Ecology Atmospheric Sciences Physical Geography Environmental Management Environmental Engineering/Biotechnology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Geography, Planning and Development Ecology Environmental Chemistry Medicine |
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