Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain.
Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain.
J Environ Manage. 2023 Nov 1;345:118676. doi: 10.1016/j.jenvman.2023.118676. Epub 2023 Aug 8.
We developed an application model based on the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework, endorsed by the United Nations Statistical Commission in 2021. This model enables mapping condition accounts for forest ecosystems using automated computation. We applied the model nationally in Spain between 2000 and 2015 to test its effectiveness. Our model follows five methodological steps to generate forest condition accounts: (i) definition and spatial delimitation of forest ecosystem types; (ii) selection of variables using the ecosystem condition typology encompassing physical, chemical, compositional, structural, functional, and landscape characteristics; (iii) establishment of reference levels, including lower (collapse) and upper (high ecosystem integrity) thresholds; (iv) aggregation of variables into condition index; and (v) calculation of a single condition index by rescaling the aggregated indicators between 0 and 1. The results obtained from the model provide valuable insights into the status and trends of individual condition indicators, as well as aggregated condition index values for forest ecosystems, in a spatially explicit manner. Overall, the condition of the forest ecosystems in Spain showed a slight increase, from 0.56 in 2000 to 0.58 in 2015. However, distinct trends were observed for each ecosystem type. For example, mixed Alpine and Macaronesia forests exhibited a significant improvement, while the continental Mediterranean coniferous forests did not show any change. This innovative approach to monitoring forest condition accounts has important potential applications in policy and decision-making processes. It can contribute to effective evidence-based nature conservation, ecosystem service management, and identifying restoration areas.
我们开发了一个基于联合国统计委员会 2021 年认可的环境经济核算-生态系统核算(SEEA-EA)框架的应用模型。该模型可以使用自动化计算为森林生态系统映射条件账户。我们在西班牙全国范围内于 2000 年至 2015 年应用该模型,以检验其有效性。我们的模型遵循五个方法步骤来生成森林条件账户:(i)定义和空间划定森林生态系统类型;(ii)使用包含物理、化学、组成、结构、功能和景观特征的生态系统条件分类法选择变量;(iii)建立参考水平,包括下限(崩溃)和上限(高生态完整性)阈值;(iv)将变量聚合到条件指数中;以及(v)通过将聚合指标在 0 和 1 之间重新缩放来计算单个条件指数。模型得出的结果以空间显式的方式提供了有关个别条件指标和森林生态系统聚合条件指数值的状态和趋势的有价值的见解。总体而言,西班牙森林生态系统的状况略有增加,从 2000 年的 0.56 增加到 2015 年的 0.58。然而,每个生态系统类型都表现出不同的趋势。例如,混合高山和马卡罗尼西亚森林表现出显著改善,而大陆地中海针叶林则没有任何变化。这种监测森林条件账户的创新方法在政策和决策制定过程中具有重要的潜在应用。它可以为有效的基于证据的自然保护、生态系统服务管理和确定恢复区域做出贡献。