Coefficients in Taylor's law increase with the time scale of water clarity measurements in a global suite of lakes

IF 7.6 1区 环境科学与生态学 Q1 ECOLOGY
Ecology Letters Pub Date : 2024-12-31 DOI:10.1111/ele.14451
Max R. Glines, Renata C. H. Amancio, Mikkel René Andersen, Helen Baulch, Ludmila S. Brighenti, Hannah E. Chmiel, Joel E. Cohen, Elvira de Eyto, Oxana Erina, Heidrun Feuchtmayr, Giovanna Flaim, Andrea Giudici, David P. Hamilton, Yannick Huot, Michael R. Kelly, Seán Kelly, Alo Laas, Christopher McBride, Camille Minaudo, Jose Fernandes Bezerra Neto, Katy Nugent, César Ordóñez, Marie-Elodie Perga, Brian Reid, Caren Scott, Peter A. U. Staehr, Denise Tonetta, Danielle Wain, Nicole K. Ward, Kevin C. Rose
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引用次数: 0

Abstract

Identifying the scaling rules describing ecological patterns across time and space is a central challenge in ecology. Taylor's law of fluctuation scaling, which states that the variance of a population's size or density is proportional to a positive power of the mean size or density, has been widely observed in population dynamics and characterizes variability in multiple scientific domains. However, it is unclear if this phenomenon accurately describes ecological patterns across many orders of magnitude in time, and therefore links otherwise disparate observations. Here, we use water clarity observations from 10,531 days of high-frequency measurements in 35 globally distributed lakes, and lower-frequency measurements over multiple decades from 6342 lakes to test this unknown. We focus on water clarity as an integrative ecological characteristic that responds to both biotic and abiotic drivers. We provide the first documentation that variations in ecological measurements across diverse sites and temporal scales exhibit variance patterns consistent with Taylor's law, and that model coefficients increase in a predictable yet non-linear manner with decreasing observation frequency. This discovery effectively links high-frequency sensor network observations with long-term historical monitoring records, thereby affording new opportunities to understand and predict ecological dynamics on time scales from days to decades.

Abstract Image

泰勒定律的系数随着全球湖泊水体清晰度测量的时间尺度而增加
识别描述跨越时间和空间的生态模式的尺度规则是生态学的核心挑战。泰勒波动缩放定律指出,人口规模或密度的方差与平均规模或密度的正幂成正比,这一定律在人口动力学中得到了广泛观察,并表征了多个科学领域的可变性。然而,尚不清楚这一现象是否准确地描述了时间上多个数量级的生态模式,从而将其他不同的观察联系起来。在这里,我们使用了来自35个全球分布的湖泊的10,531天的高频测量的水清晰度观测,以及来自6342个湖泊的数十年的低频测量来测试这一未知因素。我们专注于水的清晰度作为一个综合的生态特征,响应生物和非生物驱动。我们首次证明了不同地点和时间尺度的生态测量值的变化符合泰勒定律,模型系数随观测频率的降低以可预测的非线性方式增加。这一发现有效地将高频传感器网络观测与长期历史监测记录联系起来,从而为了解和预测从几天到几十年的时间尺度上的生态动态提供了新的机会。
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来源期刊
Ecology Letters
Ecology Letters 环境科学-生态学
CiteScore
17.60
自引率
3.40%
发文量
201
审稿时长
1.8 months
期刊介绍: Ecology Letters serves as a platform for the rapid publication of innovative research in ecology. It considers manuscripts across all taxa, biomes, and geographic regions, prioritizing papers that investigate clearly stated hypotheses. The journal publishes concise papers of high originality and general interest, contributing to new developments in ecology. Purely descriptive papers and those that only confirm or extend previous results are discouraged.
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