<?xml version="1.0" encoding="UTF-8" standalone="no"?><metadata xml:lang="en">
<Esri>
<CreaDate>20161005</CreaDate>
<CreaTime>07091500</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idAbs>The Fire Learning Network (FLN) engages dozens of multi-agency, community-based projects to accelerate the restoration of landscapes that depend on fire to sustain native plant and animal communities. By restoring this balance, the ecological, economic and social values of the landscapes can be maintained, and the threat of catastrophic wildfire can be reduced. Collaborative planning, implementation, adaptive management and the sharing of lessons learned are at the core of the FLN. Workshops, peer learning and innovative fire training through Prescribed Fire Training Exchanges​ (TREX) are just a few of the mechanisms the network uses.</idAbs>
<searchKeys>
<keyword>Fire Learning Network</keyword>
<keyword>  Nature Conservancy</keyword>
</searchKeys>
<idPurp>A map service of the Nature Conservancy's Fire Learning Network landscapes - October 4, 2016.</idPurp>
<idCredit>The Nature Conservancy</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>