<?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">A Demonstration Marine Biodiversity Observation Network (BON) for Ecosystem Monitoring</project-title>          <investigators>          <person role="investigator">            <alternateName>Marine Science Institute</alternateName>            <affiliation>              <institution country="US">University of California Santa Barbara</institution>            </affiliation>          </person>          </investigators>        <description xml:lang="en">A growing body of research demonstrates that the maintenance of marine biodiversity (including coastal biodiversity) is critical to sustained ecosystem and human health and resilience in a globally changing environment, and the condition of marine biodiversity offers a proxy for the status of ocean and coastal ecosystem health and ability to provide ecosystem services. Managing marine resources in a way that conserves existing marine biodiversity helps address other ocean management objectives, especially those related to cumulative effects. The objective of the Santa Barbara Channel Marine Biodiversity Observation Network (SBC MBON) was to develop a prototype ecosystem-based framework, across a range of habitats, looking at multiple trophic levels and species, and informed by historical data and past modeling efforts to the extent possible. Thirty-six distinct datasets spanning a full range of environmental resources were harmonized to enable integration across programs. Nineteen of these datasets were initiated, managed, and published by the SBC MBON. Integrated datasets enabled many new analyses across a regional scale, including (1) models to predict ecological outcomes from different options in decommissioning oil and gas platforms, and (2) identification of conditions necessary for an impact analysis to correctly identify consequences from a simulated oil spill to coastal ecosystems. To conduct monitoring of giant kelp, a foundational species in the Santa Barbara Channel and the West Coast, remote sensing data were combined with integrated datasets to identify spatial scales of variation over large areas. This approach was an effective method to obtain a predictive understanding of biodiversity patterns. Environmental DNA (eDNA) metabarcoding can outperform visual surveys to capture the spatial patterns in biodiversity at fine scales with less field effort and more power than traditional methods, supporting the notion that eDNA can be a critical scientific tool for detecting biodiversity changes in marine ecosystems. A broadly applicable framework which can be adapted to any region was proposed to assess and mitigate the impacts of offshore wind development to marine birds. A coordinated approach to biodiversity monitoring provides substantial benefit in characterizing marine regions, understanding potential impacts from offshore energy, understanding cumulative effects from multiple stressors, and identifying relevant indicators for monitoring outcomes of management decisions.</description>        <award_amount currency="USD">1250000</award_amount>        <funding amount="1250000" 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="2020-09-30"/>      </project>      <award-number>M15AC00006</award-number>      <doi_data>        <doi>10.67297/9A1D7F</doi>        <resource>https://boem.gov/awardpages/100095</resource>      </doi_data>    </grant>  </body></doi_batch>