<?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">Transparent modeling of collision risk for three federally-listed bird species to offshore wind development</project-title>          <investigators>          <person role="investigator">            <alternateName>Northeast Regional Office, Division of Migratory Birds</alternateName>            <affiliation>              <institution country="US">U.S. Fish and Wildlife Service</institution>            </affiliation>          </person>          </investigators>        <description xml:lang="en">A stochastic collision risk model and online web application was released in 2022 to estimate risk of avian collisions with offshore wind energy turbines in the United States (US). This decision support tool, called the Stochastic Collision Risk Assessment for Movement (SCRAM; Adams et al. 2022), uses movement data from automated radio telemetry studies to characterize collision risk in three federally-protected bird species: the red knot (Calidris canutus), pping plover (Charadrius melodus), and roseate tern (Sterna dougallii). Phase 2 of the project (2023–2024) updates the SCRAM models and tool to incorporate new sources of data (e.g., satellite-based tracking technology), improve the models, and increase the functionality of the online platform.</description>        <award_amount currency="USD">273374</award_amount>        <funding amount="273374" 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="2021-08-12" end-date="2024-09-02"/>      </project>      <award-number>M19PG00023</award-number>      <doi_data>        <doi>10.67297/9A1EAA</doi>        <resource>https://boem.gov/awardpages/100394</resource>      </doi_data>    </grant>  </body></doi_batch>