## 5 Soil Sensor Arrays
The efflux values measured at La Selva were in the range of 3 to 4 \(\mu\)mol m\({}^{-2}\) s\({}^{-1}\)[28] in our studies. However, previous studies at La Selva have reported low rates of soil CO\({}_{2}\) production of only 1 to 5 \(\mu\)mol m\({}^{-2}\) s\({}^{-1}\)[28]. In a seasonal dry tropical forest, we identified soil respiration (Rs) rates of 7 to 8 \(\mu\)mol m\({}^{-2}\) s\({}^{-1}\), and our tropical forest measurements found soil respiration rates as high as 13 \(\mu\)mol m\({}^{-2}\) s\({}^{-1}\)[29]. We used a gradient-flux method based on the concentrations of CO\({}_{2}\) in the soil profile to estimate soil respiration (Rs) (Figure 4). In a soil context, Rs includes both the CO\({}_{2}\) production through metabolism and the physical movement of the CO\({}_{2}\) molecule through soil to the atmosphere. The flux-gradient Rs technology has been demonstrated using several validation applications [30]. We identified the differences in the soil CO\({}_{2}\) concentrations after applying temperature and pressure corrections at multiple depths and computing the flux based on diffusion kinetics and a gas diffusivity model based on [PERSON]'s first law for calculating the soil CO\({}_{2}\) efflux. We compared the modeled fluxes to the manual measurements using above-ground chambers. This approach was complicated by the derived soil physical properties, which varied greatly across La Selva and impacted the model results. Other parameters were found to be helpful in describing the soil processes. We used CO\({}_{2}\) production (Ps) to represent the metabolic production of CO\({}_{2}\), and Rs for soil ecosystem respiration. Once the concentrations at the different soil layers were known, we calculated the Ps as the inverse of the differential between the Rs values of the two layers divided by the depth. Rs integrated both the Ps and diffusion. Biochemically derived CO\({}_{2}\) comes from three primary sources: (a) autotrophic root respiration (Rr) coming from fixed CO\({}_{2}\); (b) autotrophic, newly fixed CO\({}_{2}\) that is inspired from symbiotic microorganisms, in particular from mycorrhizal fungi (Rmf); and (c) heterotrophic CO\({}_{2}\) resulting from decomposing organisms (Rh) (Figure 5). To understand the  
Figure 5: Carbon cycling model showing the carbon inputs and outputs to the atmosphere and soil. differing components, and because soil temperature in the humid tropics varies minimally, we contrasted the overall CO\({}_{2}\) production with its components, Kr, Rmf, and Rh. A key variable for modeling the soil efflux is the amount of air-filled soil pore space (\(\theta\)), which is highly variable in time (wet and dry periods) and space (soil texture differences, canopy interception, microtopography), even at the experimental plot scale. The second is the tortuous particulate barriers blocking the pathway for gas molecules. The high clay content of the La Selva soils and high rainfall results in a water layer or extremely high surface water content, which restricts gas diffusion. We know little about the possible allocation of carbon to soil and its unavailability for allocation to root and microbe productivity. Is there a significant loss of carbon to CH\({}_{4}\)? Or is soil CO\({}_{2}\) lost by dissolving the soil in water [31] and moving it out of the system by another pathway? (Figure 5). These possibilities are intriguing but challenging to address directly. Automated minirhizotron systems (AMR) were installed adjacent to the soil sensor arrays and minirhizotrons were installed in order to image the growth of roots and mycorrhizale at rates set by the user (Figure 6). Our design utilized a Pro-Scope mounted on a sled, which moved the camera within a glass tube. The camera was connected to a computer and a 120-volt power source with a hot-wired connection for on-site image storage and wireless transfer.