Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, Italy.
Facoltà di Scienze Agrarie, Ambientali e Alimentari, Libera Università di Bozen/Bolzano, Italy; Dipartimento di Agricoltura, Ambiente e Alimenti, Università degli Studi del Molise, Italy.
J Environ Manage. 2024 Sep;368:122002. doi: 10.1016/j.jenvman.2024.122002. Epub 2024 Aug 12.
In recent years, Climate-Smart Forestry (CSF) has emerged as an innovative approach to sustainable forest management, aiming to enhance forest resilience and to balance the provision of ecosystem services facing climate-related threats. This study introduces for the first time a new composite climate-smart index (I) to assess CSF. The methodological approach comprises the following steps: (i) the selection and evaluation of CSF indicators; (ii) the weighting of these indicators; and (iii) the assessment of CSF for Mediterranean forests in two distinct periods, specifically 2005 and 2015. Eight indicators were selected from a systematic literature review. The Analytic Hierarchy Process was applied to translate the preferences obtained through an online questionnaire from a network of CSF-expert stakeholders into weights, at both indicators and criteria levels (i.e., adaptation, mitigation, and the social dimension). Results reveals that indicators "tree species composition", "forest damage", and "regeneration" are of crucial importance for CSF assessment. The comparison of the CSF value between the years 2005 and 2015, shows a slight increase in CSF ratings. The I serves as a comprehensive index of CSF covering all aspects of that concept, i.e. adaptation, mitigation, and the social dimension (including production). The national-scale analysis provides an overview of the dynamics that involve forest management of Mediterranean forests against climate change. The study offers a practicable method for CSF evaluation with its allover set of indicators, representing a suitable tool for supporting forest managers to mitigate the negative impacts of climate change.
近年来，气候智能型林业（CSF）作为一种可持续森林管理的创新方法出现，旨在提高森林的弹性，并平衡面对与气候相关的威胁时提供生态系统服务的能力。本研究首次引入了一种新的综合气候智能指数（I）来评估 CSF。该方法包括以下步骤：（i）选择和评估 CSF 指标；（ii）对这些指标进行加权；（iii）在两个不同时期（即 2005 年和 2015 年）评估地中海森林的 CSF。从系统文献综述中选择了 8 个指标。通过在线问卷从 CSF 专家利益相关者网络中获得的偏好，应用层次分析法（AHP）转化为指标和标准（即适应、缓解和社会维度）的权重。结果表明，指标“树种组成”、“森林损害”和“更新”对 CSF 评估至关重要。2005 年和 2015 年 CSF 值的比较表明，CSF 评级略有增加。I 是 CSF 的综合指数，涵盖了适应、缓解和社会维度（包括生产）的所有方面。国家尺度的分析提供了对地中海森林森林管理应对气候变化的动态的概述。该研究提供了 CSF 评估的实用方法及其全面的指标集，是支持森林管理者减轻气候变化负面影响的合适工具。
