Surface water quality in Amazonian Floodplain Lakes, data set of the Lago Grande de Curuai Floodplain Lake, Pará-Brazil

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Geoscience Data Journal Pub Date : 2023-06-23 DOI:10.1002/gdj3.207
Derlayne Dias Roque, Marie-Paule Bonnet, Jérémie Garnier, Cleber Kraus Nunes, Patrick Seyler, David Motta Marques
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Abstract

Between 2013 and 2017, we carried out nine field missions in the Lago Grande de Curuai floodplain, located in Pará state – North of Brazil – to collect samples for monitoring surface water quality. This site separated from the river by a narrow bank is composed of a network of channels and shallow lakes, a morphology shared by the floodplains of the lower Amazon. A multiparameter probe was used in situ to measure electrical conductivity, temperature, pH, dissolved oxygen, chlorophyll, turbidity, depth and a Secchi disk to estimate transparency. Water grab samples were analysed for suspended material, alkalinity, humic acid, phosphorus, nitrogen, carbon and chlorophyll. Sampling stations were distributed over the seven larger lakes in the floodplain and sampled at different periods of the hydrological cycle. The number of samples varied with the floodplain water level, with a minimum of 25 samples for each field visit. This data set is a collection of water quality data to assist in the limnological or biogeochemical studies of surface waters in Amazonian floodplain lakes, and the product of successive French-Brazilian projects: (1) the Clim-FABIAM ‘Climate changes and Floodplain lake biodiversity in the Amazon Basin: how to cope and help the ecological and economic sustainability’ funded by the French Foundation for biodiversity research (FRB), (2) the project Bloom-ALERT –‘Environmental sensitivity and population health vulnerability to cyanobacteria in the Amazon: towards shared indicators’ funded by the French-Brazilian research program GUYAMAZON 2014, and the project (3) ‘Ecossistemas das várzeas e biodiversidade: Impactos das mudanças ambientais e climáticas considerando cenários de desenvolvimento sustentáveis’ (Project number 490634/2013-3) funded by the Brazilian National scientific Research Council CNPq.

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亚马逊洪泛平原湖泊的地表水质量,巴西帕拉艾湖的数据集
2013 年至 2017 年间,我们在位于巴西北部帕拉州的库鲁艾格兰德湖洪泛平原进行了九次实地考察,采集样本以监测地表水水质。该地点与河流之间隔着一条狭窄的河岸,由河道和浅湖组成,其形态与亚马逊河下游的洪泛平原相同。现场使用多参数探头测量电导率、温度、pH 值、溶解氧、叶绿素、浊度、深度,并使用 Secchi 盘估算透明度。对抓取的水样进行了悬浮物、碱度、腐殖酸、磷、氮、碳和叶绿素分析。采样站分布在洪泛区七个较大的湖泊中,在水文周期的不同时期采样。样本数量随洪泛区水位的变化而变化,每次实地考察至少采集 25 个样本。这组数据收集了水质数据,有助于对亚马逊洪泛平原湖泊地表水进行湖泊学或生物地球化学研究,是法国-巴西连续开展的项目的成果:(1) Clim-FABIAM "气候变化与亚马逊河流域洪泛平原湖泊生物多样性 "项目:如何应对气候变化并促进生态和经济的可持续发展",该项目由法国生物多样性研究基金会(FRB)资助;(2) Bloom-ALERT 项目--"亚马逊蓝藻对环境的敏感性和人口健康的脆弱性:实现共享指标",该项目由 2014 年法国-巴西研究计划 GUYAMAZON 资助;(3) "Ecossistemas das várzeas e biodiversidade:Impactos das mudanças ambientais e climáticas considerando cenários de desenvolvimento sustentáveis"(项目编号 490634/2013-3),由巴西国家科学研究委员会 CNPq 资助。
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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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