## 4 Eddy Covariance Research  
One the best examples of successful efforts to apply new technologies to tropical forest research came two decades ago with the installation of eddy flux towers within the Large-scale Biosphere-Atmosphere Experiment (LBA) in Amazonia, an international research program involving collaborations between hundreds of scientists from Brazil, the United States, and other countries. Patterned after a previous successful program of flux studies on boreal ecosystems in Canada, the LBA was motivated by the need for improved observations of carbon, evapotranspiration, and sensible heat fluxes in the tropics to understand how changes in land use and climate might affect the sustainability of the biological and physical functions of Amazonia, as well as their subsequent influence on the global climate system. The eddy covariance method provides a means to directly and non-intrusively estimate the vertical transport of CO\({}_{2}\) and other greenhouse gases through and out of the forest canopy. These data, coupled with the appropriate sensors, can provide invaluable data to improve our understanding of carbon cycles, energy fluxes, and other atmospheric controls. The measurements of the net CO\({}_{2}\) flux between terrestrial ecosystems and the atmosphere using eddy covariance techniques have been fundamental to the development and application of global and regional carbon source-sink patterns and predictions of the future terrestrial carbon balance [11; 13; 20; 21]. The LBA studies suggest that Amazonia has been, on average, nearly neutral with respect to carbon over the last decade, albeit a small net source during ENSO events. Despite several decades of eddy flux measurements at multiple sites across the Amazon Basin, regional biogeophysical models have had difficulties in reproducing the seasonal pattern of the net ecosystem exchange of carbon dioxide. The eddy covariance measurements of NEE were taken in an old-growth forest. The global network of eddy covariance towers (FLUXNET) currently consists of more than 500 active sites, but humid tropical forests are underrepresented [11]. La Selva has been a flux site since 1998, and past research has identified a large sensitivity of nighttime temperature fluxes. The daytime net ecosystem fluxes were largely controlled by solar radiation rather than by evaporative demand. The dry season vapor pressure deficit was identified as a main control for forest growth on interannual timescales [22; 23; 24; 25]. The eddy covariance research over the last two decades at La Selva has had challenges in maintaining continuous measurements across the seasons and has further highlighted the challenges of extrapolating data to broader forest areas. The eddy covariance analyses carried out from 1984-2000 at La Selva found that the canopy tree growth in the old-growth forest varied \(>\)two-fold among years. The trees' annual diameter increments in this 16-yr period were negatively correlated with the annual means of the daily minimum temperatures [22]. The tree growth variations were also negatively covaried with the net carbon exchange, as inferred by an inverse tracer-transport model. The measurements during the 1997-1998 El Nino year found significant reductions in tree growth, and large inferred tropical releases of CO2 to the atmosphere occurred. These and other recent findings are consistent with the decreased net primary production in tropical forests in warm years. Previously, the walk-up towers at La Selva were similar in height to the scattered emergent tree crowns. With a new 60-m tower, the eddy covariance system will be located sufficiently above the mean canopy height to minimize any potential interference of the tallest trees with the eddy covariance measurements [21]. The canopy profile system will soon be monitoring light (PAR) and CO2-H2O concentrations at 5-m height intervals from 0 m to 50 m. The data from the profile system will be used to calculate the canopy storage of CO2, which is an important component of the ecosystem carbon flux budget.