A forward model for data assimilation of forest ecology from remote sensing [electronic resource]
Keywords: Biology.

The abstracts for each of the four chapters is as follows: Chapter 1. A number of global land surface models simulate photosynthesis, respiration, and disturbance, important flows in the carbon cycle that are widely tested against flux towers and CO2 concentration gradients. The resulting forest biomass is examined in this paper for its resemblance to realistic stands, which are characterized using allometric theory. The simulated biomass pools largely do not conform to widely observed allometry, particularly for young stands. The discrepancy between the pool distribution between models and data suggests estimates of NEE have biases when integrated over the long term, as compared to observed biomass data, and could therefore compromise long-term predictions of land carbon sources and sinks. We think that this presents a practical obstacle for improving models by informing them better with data. The approach taken in this paper, examining biomass pools allometrically, offers a simple approach to improving the characteristic behaviors of global models with the relatively sparse data that is available globally by forest inventory. Chapter 2. Bidirectional reflectance signatures of vegetation are strongly shaped by the shadows cast between objects in a scene, such as tree crowns or leaves. Differences in the shape and spatial density of these objects result in distinct bidirectional reflectance distribution functions (BRDFs) in different biomes. We examined how allometry may constrain the variability of canopy architectural parameters in BRDF models, and consequently alter the attribution of variation in the simulated bidirectional reflectance factor (BRF). Allometry is the covariation between the size or number of organisms and their component parts. To test the importance of realistic variation and covariation of canopy architecture on BRDF, we incorporated the 3-D radiative transfer model DISORD (which uses the geometric optics (GO) model of Li and Strahler) into a Monte Carlo (MC) algorithm. The MC algorithm generated an ensemble of tree canopies whose parameters fulfilled the allometry of a set of measured forest plots from Russian forest inventory. The role of view geometry was directly considered using perturbations of the parameters to evaluate the sensitivity of the BRF itself, evaluated at different view angles, and the difference in BRF ([delta]BRF) as measured at two view angles representing paired satellite observations. The allometrically constrained forest plots had reduced variation in [delta]BRF compared to the uncorrelated plots, but the variation of the BRF itself is dramatically increased by allometry. The variation of the BRF is relatively constant among the view angles examined, whereas the variation in [delta]BRF increases dramatically with larger phase angles. The BRF was most sensitive to canopy attributes that were important in radiative transfer, such as LAI and stem area index (SAI), but there were also large (~40% of variance) contributions of geometric components such as tree number, crown size, and ground cover. By contrast, sensitivity of [delta]BRF was dominated by ground cover, crown size and tree number, which all play a role in the GO calculations. Together these results indicate that forest structure and leaf area could be usefully inverted together using paired observations with different viewing geometries. Ideal pairs of observations are those with large difference in phase angle, and along the gradient of the BRF peak, which most commonly occur with sequential MODIS/Terra overpasses. Chapter 3. The reflectance of the terrestrial ecosystems varies considerably when viewed from different angles, and this variation imposes a substantial limitation to the extraction of information, such as vegetation indices, from satellite reflectance data. However, the change of reflectance with different viewing and illumination directions is potentially informative of the sizes and shapes of objects within the scene, because the geometric optic effects of the shadows cast by these objects imposes the largest variation in the bidirectional reflectance. The classic model for simulating the geometric optics of tree crowns, the Li and Strahler (1992) geometric optics model (LS-GO), has been a valuable tool to constrain the hemispheric albedo in shrublands, savannas, and other open canopies, but has had limited success with closed canopies, in part because the model's central assumption is that forests are composed of uniformly sized spheroids that are randomly distributed in horizontal space. This paper describes the comparison of LS-GO with an alternative conception of the forest canopy using the "perfect plasticity assumption" (PPA). The PPA formalism posits that a forest population has a stem size distribution emerging from demographic processes and competition for space, and that in the face of this competition, stems lean such that tree crowns minimally overlap and maximally cover the ground. A set of Monte Carlo simulations was performed to create 3-D representations of forest canopies of different ages. Subsequently light-transport was simulated using a ray-tracing platform adapted to calculate fractional visibility of sunlit and shaded crown and ground over the upper hemisphere. The effects of both the size distribution and the spatial arrangement of crowns on fractional visibility over the viewing hemisphere are independently compared for significant differences between LS and PPA conceptions of forest cover. The experiment found that the traditional assumption made in remote sensing science that canopies are composed of a mean crown size, randomly distributed in horizontal space has significant consequences on the BRDF. The assumption that crowns are all equally sized affects primarily kc, and results in a shallower BRDF that is considerably brighter at large view zenith angles. The assumption that crowns are randomly placed affects primarily kg, and results in a broad peak in the hotspot. The minimum-overlap assumption, by contrast, has only a small peak around the retro-solar angle where sunlit ground is visible. Together, these results suggest that using traditional geometric optics models to invert satellite-measured BRDF for stand attributes such as tree density and mean crown size would contain significant biases. The experiment showed that under the assumption that the crown size distribution follows a Weibull function, the BRDF of young stands composed of many small trees is not significantly distinguishable from old stands composed of fewer, larger trees. This appears to be due to the disproportionate effect that large trees in young stands have in creating shadows, and pushing the BRDF to be more similar to older-stands. Future research is suggested to clarify tree size distributions of different ages and species compositions for improved BRDF inversion capabilities. Chapter 4. To develop a partitioning scheme that is consistent with metabolic scaling theory, a database on component mass and growth, collected from Fluxnet sites (Luyssaert et al., 2008), was examined to determine allometric patterns of component growth. We found that growth of foliage (Gfol), stem and branches (Gstem), coarse roots (Gcroot) and fine roots (Gfroot) in individual trees is largely explained (r2= 67-91%) by the magnitude of growth (G) itself. Gfol scales with G isometrically, meaning it is a fixed fraction of G (~25%). Root-shoot tradeoffs were manifest as a slow decline in Gfroot, as a fraction of G, from 50% to 25% as stands matured, with Gstem and Gcroot increasing as a consequence. Climatic and edaphic factors did not explain the residual variation in partitioning. These results indicate that a functional tradeoff between aboveground and belowground allocation, as driven by site-specific resource availability, is not strongly expressed in forests. Instead, forests are characterized by a strong competition for light, observed as a race for individual trees to ascend by increasing allocation toward wood, rather than by growing more leaves. These findings leverage short-term process studies of the terrestrial carbon cycle to improve decade-scale predictions of biomass accumulation in forests.