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      <comment>Funding Agency and Grant Number: Naturschutzbund Deutschland e.V. (NABU); EU's Horizon Europe research and innovation programme; German Centre for Integrative Biodiversity Research (iDiv) - German Research Foundation [DFG-FZT 118, 202548816]; Digital Agriculture Knowledge and Information System (DAKIS) Project [031B0729A]; German Federal Ministry of Education and Research (BMBF);  [101060816]
            Funding text: An initial phase of this study was funded by Naturschutzbund Deutschland e.V. (NABU) (Space for Nature: 10% LF on agricultural area) and was continued thanks to funding from the EU's Horizon Europe research and innovation programme to project Agroecology-TRANSECT (Grant Agreement No. 101060816) . The views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them . LNS, EAF, AB and GP gratefully acknowledges the support of the German Centre for Integrative Biodiversity Research (iDiv) funded by the German Research Foundation (DFG-FZT 118, 202548816) . SDBK and ACW acknowledge the Digital Agriculture Knowledge and Information System (DAKIS) Project (031B0729A) , financed by the German Federal Ministry of Education and Research (BMBF) .</comment>
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      <abstractText>EU agricultural landscapes are vital for biodiversity. Intensive agricultural practices constitute, however, key drivers of biodiversity loss. The EU Biodiversity Strategy for 2030 aims to restore "at least 10 % of agricultural area under high-diversity landscape features", yet it lacks specific guidance for assessment and implementation. Here, we develop an approach to (a) map and assess agricultural landscape features (LF) cover at a landscape scale, (b) cluster agricultural landscapes by complexity using both compositional and configurational heterogeneity metrics, and (c) prioritise landscapes and sites for LF restoration by targeting areas of lower productivity and higher erosion risk, to enhance farmer acceptance and increase restoration benefits. Using Brandenburg, Germany, as a case study, we found that 94.4 % of landscapes fall short of the 10 % landscape features cover target. We categorised five agricultural landscape types ranging from simple to complex mosaics. At the local scale, in ten randomly selected landscapes, we identified an additional 11 % of agricultural areas on which LF could be restored. Our study helps advance methodologies to prioritise LF restoration. It can provide guidance for administrators and planners to assess the LF status and advance their adoption by farmers. We recommend prioritising landscapes and selecting restoration actions based on overall landscape complexity assessment. At the local scale, we recommend participatory processes involving local stakeholders. We believe our methodology is transferable to other EU regions, and highlights both the opportunities and challenges in developing a standardised, EU-wide approach for prioritising LF restoration to support agroecological transitions in Europe.</abstractText>
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&lt;div class=&quot;title&quot;&gt;&lt;a href=&quot;/gui2/?mode=browse&amp;params=publication;36120018&quot; target=&quot;_blank&quot;&gt;Mapping and prioritising landscape feature restoration in agricultural landscapes: A case study in Brandenburg, Germany&lt;/a&gt;&lt;/div&gt;    &lt;div&gt;		&lt;span class=&quot;journal-title&quot;&gt;LAND USE POLICY&lt;/span&gt;

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&lt;div class=&quot;lastModified&quot;&gt;Last Modified: 2025.12.30. 01:31 Admin Szuper (admin)
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	&lt;pre class=&quot;comment&quot; style=&quot;margin-top: 0; margin-bottom: 0;&quot;&gt;&lt;u&gt;Comments&lt;/u&gt;: Funding Agency and Grant Number: Naturschutzbund Deutschland e.V. (NABU); EU&apos;s Horizon Europe research and innovation programme; German Centre for Integrative Biodiversity Research (iDiv) - German Research Foundation [DFG-FZT 118, 202548816]; Digital Agriculture Knowledge and Information System (DAKIS) Project [031B0729A]; German Federal Ministry of Education and Research (BMBF);  [101060816]
 ...&lt;/pre&gt;

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