Department of Environment, Land, Water and Planning, Arthur Rylah Institute for Environmental Research, Heidelberg, VIC, 3084, Australia.
School of BioSciences, The University of Melbourne, Parkville, VIC, 3010, Australia.
Environ Monit Assess. 2022 Feb 14;194(3):185. doi: 10.1007/s10661-021-09727-2.
Understanding the impact of management interventions on the environment over decadal and longer timeframes is urgently required. Longitudinal or large-scale studies with consistent methods are best practice, but more commonly, small datasets with differing methods are used to achieve larger coverage. Changes in methods and interpretation affect our ability to understand data trends through time or across space, so an ability to understand and adjust for such discrepancies between datasets is important for applied ecologists. Calibration or double sampling is the key to unlocking the value from disparate datasets, allowing us to account for the differences between datasets while acknowledging the uncertainties. We use a case study of livestock grazing impacts on riparian vegetation in southeastern Australia to develop a flexible and powerful approach to this problem. Using double sampling, we estimated changes in vegetation attributes over a 12-year period using a pseudo-quantitative visual method as the starting point, and the same technique plus point-intercept survey for the second round. The disparate nature of the datasets produced uncertain estimates of change over time, but accounting for this uncertainty explicitly is precisely the objective and highlights the need to look more closely at this very common problem in environmental management, as well as the potential benefits of the double sampling approach.
需要迫切了解管理干预对环境的影响在数十年及更长时间内的影响。最好采用具有一致方法的纵向或大规模研究，但更常见的是，使用具有不同方法的小数据集来实现更大的覆盖范围。方法和解释的变化会影响我们随着时间或跨越空间理解数据趋势的能力，因此，理解和调整数据集之间的这种差异对于应用生态学家来说非常重要。校准或双重采样是从不同数据集中挖掘价值的关键，使我们能够在承认不确定性的同时，考虑到数据集之间的差异。我们使用澳大利亚东南部牲畜放牧对河岸植被影响的案例研究来开发解决此问题的灵活而强大的方法。我们使用双重采样，以伪定量视觉方法作为起点，在 12 年内估计植被属性的变化，第二轮则使用相同的技术和点截距调查。数据集的不相似性产生了不确定的随时间变化的估计值，但明确考虑到这种不确定性正是目标所在，这突出了需要更仔细地研究环境管理中这一非常普遍的问题，以及双重采样方法的潜在好处。
