<?xml version="1.0" encoding="UTF-8"?><doi_batch xmlns="http://www.crossref.org/grant_id/0.2.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/grant_id/0.2.0 https://gitlab.com/crossref/schema/-/raw/master/schemas/grant_id0.2.0.xsd" version="0.2.0">  <head>    <doi_batch_id>batch_auto_20260713</doi_batch_id>    <timestamp>202607131256465730</timestamp>    <depositor>      <depositor_name>BOEM ESP geoESPIS</depositor_name>      <email_address>ESPIS@boem.gov</email_address>    </depositor>    <registrant>Bureau of Ocean Energy Management</registrant>  </head>  <body>    <grant>      <project>        <project-title xml:lang="en">Data Synthesis and Advanced Predictive Modeling of Deep Coral and Hardbottom Habitats in the Southeast Atlantic: Guiding Efficient Discovery and Protection of Sensitive Benthic Areas</project-title>          <investigators>          <person role="investigator">            <alternateName>Biogeography Branch</alternateName>            <affiliation>              <institution country="US">NOAA National Centers for Coastal Ocean Science</institution>            </affiliation>          </person>          </investigators>        <description xml:lang="en">This study compiled records of the observed occurrence and developed models and maps of the predicted occurrence of deep-sea corals and hardbottom habitats offshore of the Southeastern United States. A database of presence-absence observations of deep-sea corals with associated measures of sampling effort and bottom type was compiled from 20 datasets containing data collected during underwater visual surveys conducted between 2001 and 2018. These observations were integrated with spatial environmental predictors depicting depth and seafloor topography, substrate, oceanography, and geography in statistical models (occupancy models) to predict and map the occurrence of 24 taxa of deep-sea corals and hardbottom habitats across the study area. The maps identify areas where these organisms and habitats are more likely and less likely to occur. In addition, a map of predicted genus richness was produced for the 23 genera of deep-sea corals included in the study. Information from the presence-absence database and maps of predicted occurrence and genus richness can inform and support environmental risk assessments, environmental impact statements, and other decision documents related to the review of proposed offshore energy development in the region.</description>        <award_amount currency="USD">550000</award_amount>        <funding amount="550000" currency="USD" funding-percentage="100" funding-type="award">          <funder-name>U.S. Department of the Interior, Bureau of Ocean Energy Management, Environmental Studies Program</funder-name>          <funder-id>https://doi.org/10.13039/100012475</funder-id>        </funding>        <award-dates start-date="2015-10-01" end-date="2020-09-25"/>      </project>      <award-number>M16PG00010</award-number>      <doi_data>        <doi>10.67297/9A1DB8</doi>        <resource>https://boem.gov/awardpages/100152</resource>      </doi_data>    </grant>  </body></doi_batch>