2021
DOI: 10.1029/2020jg006090
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Representativeness of FLUXNET Sites Across Latin America

Abstract: Environmental monitoring, especially long-term monitoring programs are a backbone component for environmental science and policy (Chabbi et al., 2017; Lovett et al., 2007). Environmental monitoring is fundamental to foster knowledge as it promotes creativity for scientific methodologies, generates invaluable data products, and provides baselines and information to address socio-environmental grand challenges (Lovett et al., 2007; Scholes et al., 2017; Vargas et al., 2012). It is assumed that developing environ… Show more

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Cited by 41 publications
(28 citation statements)
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“…Grand challenges in the field of biogeosciences are global and require international collaborations to address them. Integrated and coordinated efforts are needed for success, but organizational and cultural challenges for global collaborations present barriers to interoperability (Villarreal & Vargas, 2021 ). Organizational barriers relate to challenges regarding institutional responsibility and authority, as well as the inequality of resources (Mirtl et al., 2018 ; Vargas et al., 2017 ).…”
Section: Global Collaboration Technology Transfer and Applicationmentioning
confidence: 99%
See 1 more Smart Citation
“…Grand challenges in the field of biogeosciences are global and require international collaborations to address them. Integrated and coordinated efforts are needed for success, but organizational and cultural challenges for global collaborations present barriers to interoperability (Villarreal & Vargas, 2021 ). Organizational barriers relate to challenges regarding institutional responsibility and authority, as well as the inequality of resources (Mirtl et al., 2018 ; Vargas et al., 2017 ).…”
Section: Global Collaboration Technology Transfer and Applicationmentioning
confidence: 99%
“…For example, challenges exist in balancing geographic representativeness and the need for environmental–ecological stratification (Guerin et al., 2020 ). Geographic gaps are common in data networks, especially for emerging nations, which directly impact data integration and openness (Villarreal & Vargas, 2021 ). While satellite imagery and open‐access platforms for data acquisition and processing can partially mitigate these geographic biases, inequity in resources, training, and access due to political restrictions and low funding in emerging nations greatly limit seamless integration.…”
Section: Field Experimental Remote Sensing and Real‐time Data For Bio...mentioning
confidence: 99%
“…To overcome the issue of regional biases when performing a local scale model calibration/validation, we built a network of flux towers from regional initiatives to represent the wide-ranging climate and ecosystem diversity of South America [34]. In addition to the most used flux tower network data compilation [35] from the large-scale biosphereatmosphere experiment in the Amazon (LBA-ECO) [36], we also included data from the SULFLUX (South Brazilian network of surface fluxes and climate change), ONDACBC (National Observatory of Water and Carbon Dynamics in the Caatinga Biome) [37], and the PELD Pantanal (long-term ecological research in Pantanal) [38], in conjunction with flux measurements supported by Brazilian universities, including the UFMT (Federal University of Mato Grosso) [39] and the USP (University of Sao Paulo) [40], funded by national and regional research agencies.…”
Section: Introductionmentioning
confidence: 99%
“…In fact, previous applications of ANNs for G prediction at the local scale [46,47] have yielded promising results. Considering the availability of the long time series of measured G, representative of the South American landscape [34,41], and the readily available remote sensing data, the usage of the ANN approach for large-scale applications is encouraged as a next step to assess its efficiency in predicting G.…”
Section: Introductionmentioning
confidence: 99%
“…For example, Villarreal et al [6] analyzed the representativeness of the eddy covariance sites of AmeriFlux based on the ecosystem functional types categories represented by each network. Villarreal and Vargas [7] assessed the representativeness of registered FLUXNET sites across Latin America using GPP and evapotranspiration. Pallandt et al [8] compared the environmental conditions observed at the tower locations and those within the larger Arctic domain, and mapped the representativeness of these eddy covariance network.…”
Section: Introductionmentioning
confidence: 99%