Interpreting insect declines: seven challenges and a way forward
Interpreting insect declines: seven challenges and a way forward
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DOI：
10.1111/icad.12408
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发表时间：
2020-03-01
影响因子：
3.5
通讯作者：
Hassall, Christopher
中科院分区：
文献类型：
--
作者：
Didham, Raphael K.;Basset, Yves;Hassall, Christopher
许多昆虫物种受到全球变化的人为驱动因素的威胁。在科学文献中有许多关于昆虫数量下降和灭绝的有据可查的例子，但最近一些较弱的研究提出了全球危机的极端主张，引起了媒体的广泛报道，并引起了前所未有的公众关注。如果危言耸听的昆虫数量减少的说法经不起仔细审查，这种关注可能是一把双刃剑。我们确定了在得出关于昆虫数量减少的可靠推断方面的七个关键挑战：历史基线的建立、研究中心选择的代表性、时间序列趋势估计的稳健性、检测偏差效应的缓解以及解释密度依赖性潜在人为因素的能力，从样本丰度推断种群水平的推断中的物候变化和尺度依赖性。在评价人口趋势的证据和确定这些趋势的驱动因素时，需要更加谨慎。我们提出的最佳实践方法，避免方法错误，减少潜在的偏见，并产生更强大的分析时间序列trends.Despite许多现有的挑战和陷阱，我们提出了一个前瞻性的招股说明书昆虫种群监测的未来，突出机会，更有创造性地利用现有的基线数据，采样和新的计算方法的技术进步。昆虫学家无法独自应对这些挑战，只有通过与公民科学家、许多学科的其他研究科学家和数据分析师的合作，下一代研究人员才能弥合小昆虫和大数据之间的差距。
Many insect species are under threat from the anthropogenic drivers of global change. There have been numerous well-documented examples of insect population declines and extinctions in the scientific literature, but recent weaker studies making extreme claims of a global crisis have drawn widespread media coverage and brought unprecedented public attention. This spotlight might be a double-edged sword if the veracity of alarmist insect decline statements do not stand up to close scrutiny.We identify seven key challenges in drawing robust inference about insect population declines: establishment of the historical baseline, representativeness of site selection, robustness of time series trend estimation, mitigation of detection bias effects, and ability to account for potential artefacts of density dependence, phenological shifts and scale-dependence in extrapolation from sample abundance to population-level inference.Insect population fluctuations are complex. Greater care is needed when evaluating evidence for population trends and in identifying drivers of those trends. We present guidelines for best-practise approaches that avoid methodological errors, mitigate potential biases and produce more robust analyses of time series trends.Despite many existing challenges and pitfalls, we present a forward-looking prospectus for the future of insect population monitoring, highlighting opportunities for more creative exploitation of existing baseline data, technological advances in sampling and novel computational approaches. Entomologists cannot tackle these challenges alone, and it is only through collaboration with citizen scientists, other research scientists in many disciplines, and data analysts that the next generation of researchers will bridge the gap between little bugs and big data.