| The research presented in this dissertation was driven by the hypothesis that the Luquillo Experimental Forest, PR would maximize its useful energy capture at mid-elevations where environmental conditions cause the ecosystem's rates of photosynthesis and respiration, as well as the efficiency of these processes, to be intermediate relative to those at lower and higher elevations. To test this 'maximum power' hypothesis quantitatively, I used an approach that combined novel field sampling techniques with computer simulation modeling. This approach allowed me to examine variations in primary productivity and climate at both small and large spatial scales and to test the validity of an existing process-based productivity model (FOREST-BGC, Running and Coughlan 1988) developed for the same region by Wang et al. (2003).; I measured area-based rates of CO2 uptake and release under different microclimatic conditions in canopy and understory leaves, woody stems, and soil plots located at various elevations ranging from near sea level to over 1000 m. I then scaled these measurements over space and time by developing an empirically-driven computer simulation model. Results indicate that there are significant differences among species with respect to both rates of carbon exchange and the physiological parameters that determine these rates (e.g., foliar nitrogen, leaf mass per area). Model results support the hypothesis that NPP is highest at mid-elevations where environmental conditions favor optimal ecosystem net production. My estimates of GPP are about 45% lower than those of Wang et al. (2003), possibly due to factors that increase the level of detail in my model such as a stratified canopy, foliar nitrogen variability and species distribution patterns. However, my estimates of NPP are roughly the same, suggesting that both GPP and autotrophic respiration in the Wang et al. (2003) model are overestimated. This implies that the FOREST-BGC simulation model may not be suitable for use in tropical forest locations. |
