Spatial Representativeness of MexFlux as a Regional FLUXNET Network
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Fecha
2025-12-09Autor
Perez Ruiz, Eli Rafael
Vargas, Rodrigo
Le, Huong
Villareal, Samuel
Alvarado-Barrientos, Susana
Cueva, Alejandro
Delgado-Balbuena, Josue
Flores-Renteria, Dulce
Hinojo-Hinojo, Cesar
Cervantes-Jiméne, Monica
Sánchez-Mejía, Zulia
Tarin, Tonantzin
Bullock, Stephen
Castellanos, Alejandro
Figueroa-Espinoza, Bernardo
Garatuza-Payán, Jaime
Holwerda, Friso
Rodriguez, Julio Cesar
Rojas-Robles, Nidia
Uuh-Sonda, Jorge
Velasco, Erik
Yépez, Enrico
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Environmental observatory networks are fundamental in advancing scientific understanding of biogeochemical processes. FLUXNET is a global network of regional eddy covariance networks that measure ecosystem-scale exchanges of greenhouse gases (e.g., CO2, CH4, H2O) and energy between the biosphere and the atmosphere. MexFlux is the eddy covariance network of Mexico, a megadiverse country with many underrepresented ecosystems within FLUXNET. This study evaluates the spatial representativeness of MexFlux by assessing its ability to capture the statistical and spatial heterogeneity of annual gross primary productivity (GPP) and evapotranspiration (ET) within Mexico. We tested four network configurations: the historical distribution of MexFlux sites (MexFlux-H, n = 33), an expanded network with 20 additional sites (MexFlux + 20, 53 sites), MexFlux sites with publicly available data (MexFlux-P, n = 20), and a hypothetical optimized design with only 25 sites (MexFlux25, n = 25). Results show that MexFlux-H and MexFlux-P overrepresent regions with GPP values between 250 and 600 gC m−2 yr−1 and ET of 200–1,200 mm yr−1. MexFlux + 20 demonstrates that adding 20 strategically located sites improves the representativeness of MexFlux while preserving the historical distribution of the network. The configuration of MexFlux25 highlights that a few but strategically distributed sites are an alternative way to enhance the representativeness of the network. Mountain regions, tropical forests, and urban sites may remain underrepresented in any network configuration, highlighting the challenges of monitoring efforts in this country. Our framework integrates distributions, copulas, semivariograms, and upscaling to highlight the value of a multidimensional assessment of spatial representativeness, which applies to other regional FLUXNET networks.
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