Implications of scale dependence for cross‐study syntheses of biodiversity differences,Ecology Letters

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Implications of scale dependence for cross‐study syntheses of biodiversity differences
Ecology Letters ( IF 7.6 ) Pub Date : 2020-11-20 , DOI: 10.1111/ele.13641
Rebecca Spake _{1,

2} , Akira S. Mori ₃ , Michael Beckmann ₄ , Philip A. Martin _{5,

6} , Alec P. Christie ₆ , Marlyse C. Duguid ₇ , C. Patrick Doncaster ₂

Affiliation

Biodiversity studies are sensitive to well‐recognised temporal and spatial scale dependencies. Cross‐study syntheses may inflate these influences by collating studies that vary widely in the numbers and sizes of sampling plots. Here we evaluate sources of inaccuracy and imprecision in study‐level and cross‐study estimates of biodiversity differences, caused by within‐study grain and sample sizes, biodiversity measure, and choice of effect‐size metric. Samples from simulated communities of old‐growth and secondary forests demonstrated influences of all these parameters on the accuracy and precision of cross‐study effect sizes. In cross‐study synthesis by formal meta‐analysis, the metric of log response ratio applied to measures of species richness yielded better accuracy than the commonly used Hedges' g metric on species density, which dangerously combined higher precision with persistent bias. Full‐data analyses of the raw plot‐scale data using multilevel models were also susceptible to scale‐dependent bias. We demonstrate the challenge of detecting scale dependence in cross‐study synthesis, due to ubiquitous covariation between replication, variance and plot size. We propose solutions for diagnosing and minimising bias. We urge that empirical studies publish raw data to allow evaluation of covariation in cross‐study syntheses, and we recommend against using Hedges' g in biodiversity meta‐analyses.

中文翻译：

尺度依赖性对生物多样性差异跨研究综合的影响

生物多样性研究对公认的时空尺度依赖性很敏感。跨研究综合可以通过整理样本数量和大小差异很大的研究来扩大这些影响。在这里，我们评估研究水平和跨研究的生物多样性差异的不精确性和不精确性，这些差异是由研究范围内的谷物和样本量，生物多样性测度以及效应量度指标的选择引起的。来自老龄和次生林的模拟群落的样本证明了所有这些参数对交叉研究效应量的准确性和精确度的影响。在通过正式的荟萃分析进行跨研究的综合中，将对数响应比的度量应用于物种丰富度的度量比常用的Hedges's g产生了更好的准确性。衡量物种密度的方法，危险地将更高的精度与持续的偏差结合在一起。使用多级模型对原始地块比例数据进行全数据分析也容易受到比例依赖偏差的影响。由于复制，方差和样地大小之间普遍存在协变量，我们证明了在跨研究综合中检测规模依赖性的挑战。我们提出了用于诊断和最小化偏差的解决方案。我们敦促实证研究发布的原始数据，以允许交叉研究合成共变的评估，我们建议不要使用套期摹生物多样性荟萃分析。

更新日期：2021-01-11

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