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Dealing with Trade-Offs in Destructive Sampling Designs for Occupancy Surveys

机译：在占用性调查的破坏性采样设计中权衡取舍

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Occupancy surveys should be designed to minimise false absences. This is commonly achieved by increasing replication or increasing the efficiency of surveys. In the case of destructive sampling designs, in which searches of individual microhabitats represent the repeat surveys, minimising false absences leads to an inherent trade-off. Surveyors can sample more low quality microhabitats, bearing the resultant financial costs and producing wider-spread impacts, or they can target high quality microhabitats were the focal species is more likely to be found and risk more severe impacts on local habitat quality. We show how this trade-off can be solved with a decision-theoretic approach, using the Millewa Skink Hemiergis millewae from southern Australia as a case study. Hemiergis millewae is an endangered reptile that is best detected using destructive sampling of grass hummocks. Within sites that were known to be occupied by H. millewae, logistic regression modelling revealed that lizards were more frequently detected in large hummocks. If this model is an accurate representation of the detection process, searching large hummocks is more efficient and requires less replication, but this strategy also entails destruction of the best microhabitats for the species. We developed an optimisation tool to calculate the minimum combination of the number and size of hummocks to search to achieve a given cumulative probability of detecting the species at a site, incorporating weights to reflect the sensitivity of the results to a surveyor’s priorities. The optimisation showed that placing high weight on minimising volume necessitates impractical replication, whereas placing high weight on minimising replication requires searching very large hummocks which are less common and may be vital for H. millewae. While destructive sampling methods are sometimes necessary, surveyors must be conscious of the ecological impacts of these methods. This study provides a simple tool for identifying sampling strategies that minimise those impacts.
机译：占用调查应设计为最大程度地减少失误。通常可以通过增加重复性或提高调查效率来实现。在破坏性抽样设计的情况下，对单个微生境的搜索代表了重复调查，因此，将错误缺席最小化会导致固有的权衡。测量员可以对更多低质量的微生境取样，承担相应的财务成本并产生更广泛的影响，或者他们可以将高质量的微生境作为目标，前提是更可能发现重点物种并可能对当地生境质量造成更严重的影响。我们以来自澳大利亚南部的Millewa Skink Hemiergis millewae作为案例研究，展示了如何通过决策理论方法解决这种折衷方案。 Hemiergis millewae是一种濒临灭绝的爬行动物，最好使用破坏性取样的草山丘来检测。在已知被H. millewae占据的地点内，逻辑回归模型显示，在大型山雀中更频繁地发现蜥蜴。如果此模型可以准确地表示检测过程，则搜索大型山雀将更为有效，并且所需的重复次数较少，但是这种策略还需要破坏该物种的最佳微生境。我们开发了一种优化工具，可以计算出要搜索的最小数量的山雀数量和大小的组合，以实现在现场发现给定物种的给定累积概率，并结合权重以反映结果对测量员优先级的敏感性。优化表明，将重物放在最小的体积上是不切实际的复制，而将重物放在最小的复制上则需要搜索非常大的山雀，而这些山雀是不常见的，可能对H. millewae至关重要。尽管有时必须使用破坏性采样方法，但测量师必须意识到这些方法对生态的影响。这项研究提供了一种简单的工具，可用于确定将这些影响最小化的抽样策略。

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