Derlayne Dias Roque, Marie-Paule Bonnet, Jérémie Garnier, Cleber Kraus Nunes, Patrick Seyler, David Motta Marques
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引用次数: 0
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.
Geoscience Data JournalGEOSCIENCES, 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.