Temporal turnover in species' ranks can explain variation in Taylor's slope for ecological timeseries

IF 4.4 2区 环境科学与生态学 Q1 ECOLOGY Ecology Pub Date : 2024-07-24 DOI:10.1002/ecy.4381
Shyamolina Ghosh, Blake Matthews
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Abstract

The scaling exponent relating the mean and variance of the density of individual organisms in space (i.e., Taylor's slope: zspace) is well studied in ecology, but the analogous scaling exponent for temporal datasets (ztime) is underdeveloped. Previous theory suggests the narrow distribution of ztime (e.g., typically 1–2) could be due to interspecific competition. Here, using 1694 communities time series, we show that ztime can exceed 2, and reaffirm how this can affect our inference about the stabilizing effect of biodiversity. We also develop a new theory, based on temporal change in the ranks of species abundances, to help account for the observed ztime distribution. Specifically, we find that communities with minimal turnover in species' rank abundances are more likely to have higher ztime. Our analysis shows how species-level variability affects our inference about the stability of ecological communities.

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物种等级的时间更替可以解释生态时间序列中泰勒斜率的变化。
生态学对空间中生物个体密度的平均值和方差的比例指数(即泰勒斜率:zspace)进行了深入的研究,但对时间数据集(ztime)的类似比例指数的研究还很不够。以前的理论认为,ztime 的狭窄分布(如通常为 1-2)可能是由于种间竞争造成的。在此,我们利用 1694 个群落的时间序列表明,ztime 可以超过 2,并重申了这如何影响我们对生物多样性稳定效应的推断。我们还根据物种丰度等级的时间变化提出了一个新理论,以帮助解释观察到的 ztime 分布。具体来说,我们发现物种等级丰度变化最小的群落更有可能具有较高的 ztime。我们的分析表明了物种水平的变化如何影响我们对生态群落稳定性的推断。
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来源期刊
Ecology
Ecology 环境科学-生态学
CiteScore
8.30
自引率
2.10%
发文量
332
审稿时长
3 months
期刊介绍: Ecology publishes articles that report on the basic elements of ecological research. Emphasis is placed on concise, clear articles documenting important ecological phenomena. The journal publishes a broad array of research that includes a rapidly expanding envelope of subject matter, techniques, approaches, and concepts: paleoecology through present-day phenomena; evolutionary, population, physiological, community, and ecosystem ecology, as well as biogeochemistry; inclusive of descriptive, comparative, experimental, mathematical, statistical, and interdisciplinary approaches.
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