Hughes Alice C
School of Biological Sciences, University of Hong Kong, Hong Kong, China.
Plants (Basel). 2023 Jun 12;12(12):2291. doi: 10.3390/plants12122291.
With the recent launch of the Kunming-Montreal global biodiversity framework (GBF), and the associated monitoring framework, understanding the framework and data needed to support it is crucial. Unfortunately, whilst the monitoring framework was meant to provide key data to monitor progress towards goals and targets, most indicators are too unclear for detection or marking progress. The most common datasets for this task, such as the IUCN redlist of species, have major spatial inaccuracies, and lack the temporal resolution to track progress, whilst point-based datasets lack data from many regions, in addition to species coverage. Utilising existing data will require the careful use of existing data, such as the use of inventories and projecting richness patterns, or filling data gaps before developing species-level models and assessments. As high-resolution data fall outside the scope of explicit indicators within the monitoring framework, using essential biodiversity variables within GEOBON (which are noted in the prelude of the monitoring framework) as a vehicle for data aggregation provides a mechanism for collating the necessary high-resolution data. Ultimately developing effective targets for conservation will require better species data, for which National Biodiversity Strategic Action Plans (NBSAPs) and novel mechanisms for data mobilisation will be necessary. Furthermore, capitalising on climate targets and climate biodiversity synergies within the GBF provides an additional means for developing meaningful targets, trying to develop urgently needed data to monitor biodiversity trends, prioritising meaningful tasks, and tracking our progress towards biodiversity targets.
随着最近《昆明-蒙特利尔全球生物多样性框架》(GBF)及其相关监测框架的推出,了解该框架以及支持它所需的数据至关重要。不幸的是,虽然监测框架旨在提供关键数据以监测朝着各项目标和具体目标取得的进展,但大多数指标过于模糊,无法用于检测或标记进展情况。用于此任务的最常见数据集,如世界自然保护联盟(IUCN)物种红色名录,存在重大空间误差,且缺乏跟踪进展的时间分辨率,而基于点的数据集除了物种覆盖范围外,还缺少许多地区的数据。利用现有数据需要谨慎使用现有数据,例如利用清单和预测丰富度模式,或在开发物种水平模型和评估之前填补数据空白。由于高分辨率数据不在监测框架内明确指标的范围内,将全球生物多样性观测网络(GEOBON)中的基本生物多样性变量(在监测框架的前言中有所提及)用作数据汇总的工具,提供了一种整理必要高分辨率数据的机制。最终,制定有效的保护目标将需要更好的物种数据,为此需要国家生物多样性战略行动计划(NBSAPs)和新的数据动员机制。此外,利用《全球生物多样性框架》中的气候目标和气候与生物多样性协同效应,为制定有意义的目标、努力开发监测生物多样性趋势所需的迫切需要的数据、确定有意义的任务优先级以及跟踪我们在生物多样性目标方面的进展提供了额外途径。