Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, CB2 3QZ, UK; Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, TR10 9FE, UK.
School of Biological Sciences, University of Queensland, Brisbane, Australia; Centre for Biodiversity and Conservation Science, University of Queensland, Brisbane, Australia.
Trends Ecol Evol. 2021 Mar;36(3):196-205. doi: 10.1016/j.tree.2020.11.001. Epub 2020 Dec 10.
Humanity's impact on the environment is increasing, as are strategies to conserve biodiversity, but a lack of understanding about how interventions affect ecological and conservation outcomes hampers decision-making. Time series are often used to assess impacts, but ecologists tend to compare average values from before to after an impact; overlooking the potential for the intervention to elicit a change in trend. Without methods that allow for a range of responses, erroneous conclusions can be drawn, especially for large, multi-time-series datasets, which are increasingly available. Drawing on literature in other disciplines and pioneering work in ecology, we present a standardised framework to robustly assesses how interventions, like natural disasters or conservation policies, affect ecological time series.
人类对环境的影响正在增加,同时也在制定保护生物多样性的策略,但由于缺乏对干预措施如何影响生态和保护结果的理解,这阻碍了决策的制定。时间序列通常用于评估影响,但生态学家往往比较干预前后的平均值;忽略了干预可能引发趋势变化的可能性。如果没有允许各种反应的方法,就可能得出错误的结论,特别是对于越来越多的大型多时间序列数据集。借鉴其他学科的文献和生态学的开创性工作,我们提出了一个标准化框架,以稳健地评估干预措施(如自然灾害或保护政策)如何影响生态时间序列。