Environmental Sciences, Informatics and Statistic Department, University of Venice, Venice, Italy.
Division of Oceanography, ECHO Group Ecology and Computational Hydrodynamics in Oceanography, Istituto Nazionale di Oceanografia e di Geofisica Sperimentale - OGS, Trieste, Italy.
Glob Chang Biol. 2020 Feb;26(2):786-797. doi: 10.1111/gcb.14827. Epub 2019 Oct 1.
Implementing the Ecosystem Approach in marine ecosystems is moving from preliminary steps-dedicated to defining the optimal features for indicators and developing efficient indicator frameworks-towards an operational phase where multisector marine management decisions are executed using this information. Within this operational context, emergent ecosystem properties are becoming quite promising as they have been demonstrated to be globally widespread and repeatable, and to be quite effective in detecting significant state variations of complex systems. Biomass accumulation across TLs (CumB-TL) combines two important emergent properties of an ecosystem (energy flow, in terms of transfer efficiency, and storage, expressed as biomass), both amenable to detecting rapid ecosystem change. However, for further application, it is crucial to understand which types of drivers an indicator is sensitive to and how robust it is in relation to modifications of the external conditions and/or the system state. Here we address some outstanding questions of these CumB-TL curves related to their sensitivity to various drivers by carrying out a global scale assessment (using data from 62 LMEs) over six decades (1950-2010). We confirm the consistency of the S-pattern across all the LMEs, independent from latitude, ecosystem, environmental conditions, and stress level. The dynamics of the curve shape showed a tendency to stretch (i.e. decrease of steepness), in the presence of external disturbance and conversely to increase in steepness and shift towards higher TL in the case of recovery from stressed conditions. Our results suggest the presence of three main types of ecosystem dynamics, those showing an almost continuous increase in ecological state over time, those showing a continuous decrease in ecological state over time, and finally those showing a mixed behaviour flipping between recovering and degrading phases. These robust patterns suggest that the CumB-TL curve approach has some useful properties for use in further advancing the implementation of the Ecosystem Approach, allowing us to detect the state of a given marine ecosystem based on the dynamics of its curve shape, by using readily available time series data. The value of being able to identify conditions that might require management actions is quite high and, in many respects, represents the main objective in the context of an Ecosystem Approach, with large applications for detecting and responding to global changes in marine ecosystems.
在海洋生态系统中实施生态系统方法正从初步步骤(专门用于定义指标的最佳特征并开发有效的指标框架)向操作阶段转变,在该阶段,使用这些信息执行多部门海洋管理决策。在这种操作环境中,新兴生态系统特性变得非常有前景,因为它们已被证明在全球范围内广泛存在且可重复,并且在检测复杂系统的显著状态变化方面非常有效。TL 上的生物量积累(CumB-TL)结合了生态系统的两个重要的新兴特性(以传递效率表示的能量流和以生物量表示的存储),这两者都适合检测生态系统的快速变化。然而,为了进一步应用,了解一个指标对哪些类型的驱动因素敏感以及它在外部条件和/或系统状态的变化方面的稳健性至关重要。在这里,我们通过在六个十年(1950-2010 年)内对 62 个 LME 进行全球范围的评估(使用来自这些 LME 的数据),解决了与这些 CumB-TL 曲线的敏感性相关的一些悬而未决的问题。我们确认了所有 LME 中 S 型模式的一致性,独立于纬度、生态系统、环境条件和压力水平。曲线形状的动态显示出在存在外部干扰时拉伸(即陡峭度降低)的趋势,而在从压力条件恢复时则增加陡峭度并向更高 TL 转移的趋势。我们的结果表明,存在三种主要的生态系统动态类型,那些随着时间的推移生态状态几乎连续增加的,那些随着时间的推移生态状态连续减少的,最后那些显示出在恢复和退化阶段之间翻转的混合行为的。这些稳健的模式表明,CumB-TL 曲线方法具有一些有用的特性,可用于进一步推进生态系统方法的实施,使我们能够根据其曲线形状的动态来检测特定海洋生态系统的状态,使用现成的时间序列数据。能够识别可能需要管理措施的条件的价值非常高,并且在许多方面代表了生态系统方法背景下的主要目标,在检测和应对海洋生态系统的全球变化方面具有广泛的应用。