GLOSSAQUA: A global dataset of size spectra across aquatic ecosystems

IF 4.4 2区 环境科学与生态学 Q1 ECOLOGY
Ecology Pub Date : 2025-03-18 DOI:10.1002/ecy.70050
Zeynep Ersoy, Charlotte Evangelista, Aitor Larrañaga, Daniel M. Perkins, Javier Sánchez-Hernández, Teofana Chonova, David Cunillera-Montcusí, Carmen García-Comas, Jorge García-Girón, Ioar de Guzman, Justin Pomeranz, Victor Saito, Matías Arim, Dirceu Baumgartner, Gilmar Baumgartner, Mauro Berazategui, Dani Boix, Giovanna Collyer, Jordi Compte, Almir Manoel Cunico, Renee M. van Dorst, Jon Harding, Ursula Gaedke, Stéphanie Gascón, Éder André Gubiani, Daniel Hernández, James R. Junker, Mercedes López-Vázquez, Anderson Luís Maciel, Thomas Mehner, Roger Paulo Mormul, Ramiro Pereira-Garbero, Danielle Petsch, Pitágoras Augusto Piana, Xavier D. Quintana, Julia Reiss, Lucía Rodríguez-Tricot, Jordi Sala, Wilson Sebastián Serra, Tadeu Siqueira, Helen J. Warburton, Matías Zarucki, Ignasi Arranz
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引用次数: 0

Abstract

Body size is a key trait in ecology due to its influence on metabolism and many other life-history traits that affect population and community responses to environmental variation as well as ecosystem properties. The size spectrum represents the relationship between abundance (or biomass) and body size, independent of species identity. Size spectrum parameters, such as the slope or intercept, have been applied extensively as indicators of ecological status across multiple ecosystem types. The GLOSSAQUA dataset includes data from mainly heterotrophic communities composed of single (e.g., zooplankton, macroinvertebrates, or fish) to multiple taxonomic groups (e.g., from primary consumers to apex predators, and phytoplankton to large zooplankton), across diverse spatial and temporal scales, from surveys in freshwater (43% studies), marine (52% studies) and brackish (5% studies) ecosystems. In total, we compiled a unique global dataset of 8459 size spectrum slopes or exponents, 5237 intercepts, and 4,497 linearity coefficients (i.e., defined by the R2 of the linear fit of the size spectrum) from 127 articles and gray literature (i.e., unpublished datasets). The current dataset aims to help identify the main drivers shaping aquatic size spectrum parameters at a global scale and contribute to cross-ecosystem comparisons. GLOSSAQUA can serve to explore questions such as factors influencing spatial and temporal dynamics of community size structure, comparing the response of community size structure between natural versus human-impacted sites, and comparing global patterns in different aquatic ecosystems. We encourage researchers, especially those from underrepresented geographical areas (e.g., South Hemisphere and Asia) to fuel this dataset in the future. The dataset is provided under a CC-BY-NC-S4 4.0 license, and users are encouraged to cite this data paper when using the data.

GLOSSAQUA:水生生态系统尺寸光谱的全球数据集
体型是生态学的一个关键特征,因为它影响着新陈代谢和许多其他生活史特征,这些特征影响着种群和群落对环境变化和生态系统特性的反应。大小谱表示丰度(或生物量)与体型之间的关系,与物种身份无关。尺寸谱参数,如坡度或截距,已广泛应用于多种生态系统类型的生态状况指标。GLOSSAQUA数据集包括主要由单一(如浮游动物、大型无脊椎动物或鱼类)到多个分类类群(如从初级消费者到顶级捕食者,从浮游植物到大型浮游动物)组成的异养群落的数据,跨越不同的时空尺度,包括淡水(43%的研究)、海洋(52%的研究)和咸水(5%的研究)生态系统的调查。总的来说,我们从127篇文章和灰色文献(即未发表的数据集)中编译了一个独特的全球数据集,包括8459个大小光谱斜率或指数,5237个截距和4497个线性系数(即由大小光谱线性拟合的R2定义)。目前的数据集旨在帮助确定在全球范围内形成水生尺寸谱参数的主要驱动因素,并有助于跨生态系统的比较。GLOSSAQUA可用于探索影响群落规模结构时空动态的因素,比较自然和人为影响地点对群落规模结构的响应,比较不同水生生态系统的全球格局等问题。我们鼓励研究人员,特别是那些来自代表性不足的地理区域(如南半球和亚洲)的研究人员,在未来为这个数据集提供燃料。本数据集在CC-BY-NC-S4 4.0许可协议下提供,鼓励用户在使用数据时引用本数据论文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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