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          <titl xml:lang="en">Experts agreement on key elements of transformational adaptation to climate risks</titl>
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        <AuthEnty affiliation="Wageningen University" xml:lang="en">R. Biesbroek
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      <abstract xml:lang="en">&lt;P&gt;This data is collected in the context of a NWO_VIDI project and aims to collect expert views on the key elements that constitute transformational adaptation to climate risks.&lt;/P&gt;&lt;P&gt;  Experts on transformational adaptation to climate risks form a small but rapidly emerging group and the topic has gaine considerable interest in recent years. &lt;/P&gt;&lt;P&gt;  Data collection took place via three rounds of surveys using Qualtrics software. In round one, experts rated the relevance of 27 elements, provided qualitative justifications for their ratings, and suggested missing elements. In round two, experts re-evaluated the elements for which there was little agreement in round 1, considering the controlled opinion feedback. All responses from round 1 were anonymized and summarized where needed by the researchers. Experts rated the relevance of a few additional elements that were suggested by multiple experts in round one. In the third round experts evaluated two definitional statements derived from earlier responses. &lt;/P&gt;&lt;P&gt;  The Delphi panel comprised n=99 participants in Round1, n=64 in Round2, and n=52 in Round3. In Round1, participants included researchers (n=26), practitioners (n=27), mixed profiles (n=28), and those who preferred not to answer (n=18); the distribution was similar in subsequent rounds (Round2: n= 17, 17, 18, 12; Round3: n=15, 13, 15, 9). Regional foci were diverse, including Africa (Round2: n=10; Round3: n=7), the Americas (n=7; n=5), Asia/Middle East (n=5; n=4), Europe (n=12; n=10), and Oceania (n=4; n=3), while many reported no specific regional focus (n=24; n=21).  Participants worked across multiple administrative levels, most commonly national (n=38; n=31) and local (n=43; n=34), followed by province (n=28; n=24), community (n=29; n=22), global (n=27; n=21), and regional (n=20; n=17).&lt;/P&gt;</abstract>
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