<?xml version="1.0" encoding="UTF-8"?><metadata xml:lang="en">
<Esri>
<CreaDate>20231101</CreaDate>
<CreaTime>12464700</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>Biodiversity Conservation Network </resTitle>
</idCitation>
<searchKeys/>
<idPurp>The Biodiversity Conservation Network (or BioNet) of Maryland layer systematically identifies and prioritizes ecologically important lands to conserve Marylands biodiversity (i.e., plants, animals, habitats, and landscapes). This dataset aggregates numerous separate data layers hierarchically according to the BioNet Criteria Matrix. </idPurp>
<idAbs>&lt;DIV STYLE="text-align:Left;font-size:12pt"&gt;&lt;P&gt;&lt;SPAN&gt;These data were needed to maximize the influence and effectiveness of public and private conservation investments; promote shared responsibilities for land conservation between public and private sectors; and guide and encourage compatible land uses and land management practices.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;</idAbs>
<idCredit>IMAP.gov</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">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</Data>
</Thumbnail>
</Binary>
</metadata>
