Soil respiration is one of the largest annual fluxes of carbon dioxide to the atmosphere. But little is known how biotic and abiotic factors affect soil respiration. And a compounding issue is that soil respiration can naturally vary greatly on both spatial and temporal scales. Also, human disturbance can have dramatic effects on nutrient cycling and soil respiration. Low power wireless sensor networks could help address some of the problems by collecting high-resolution data over multiple scales and long time periods with little maintenance needs.
We deployed a wireless sensor network to monitor soil conditions in an upland tropical rainforest in the Ecuadorian Amazon. The network consisted of 12 soil CO2 sampling locations using the well method at four sites, two in an old forest and two in a young forest. The young forest was cleared 20 to 25 years ago for a helicopter pad. At each site we collected five-minute readings for soil CO2 concentrations, soil moisture, and soil and air temperatures. Next to each sampling location were ring used for daily chamber flux measurements. The sampling locations were arranged on two scales. The spacing at each site was 3 meters and between sites was 25 meters. We deployed the network for several weeks in both the wet and dry seasons. Soil samples were collected and analyzed for bulk density, porosity, texture, and other soil parameters.
Results/Conclusions
The chamber method demonstrated that soil respiration was 30 percent higher, on average in the old forest than the young forest, in both seasons. The well method’s estimated soil efflux did not match the measured values collected via the chamber method. Often the well method overestimated measured fluxes. This elucidates the need for refinement of well method models so that the predicated values are closer to actual fluxes. The average chamber fluxes measured in the tropical forest (3.07 umol m-2 s-1) were lower than the average flux that we have observed in a temperate forest under similar soil conditions (3.36). The cause of these differences may be litter inputs, fine root density, or hydrologic effects of denuding the forest.