![]() ![]() Over time, ecologists tried to develop alternative methods for AGB estimations (Catchpole and Wheeler 1992). 2009), and it is destructive, by precluding chances for multi-temporal replications of the measurements. Indeed, it is time- and energy-consuming (Loudermilk et al. Despite the overall reliability, this usual procedure shows some relevant shortcomings. 1996).įrom a methodological perspective, the most accurate way for estimating AGB requires cutting, drying, and weighting grass samples (Ohsowski et al. 2010) and fire management (Trollope et al. For such reasons, AGB estimation in grasslands is an effective tool for a wide range of ecological applications, including habitat monitoring (McNaughton 1985), pasture (Trotter et al. ![]() 1996) and (2) quantifying the effect of an array of biotic and abiotic factors on temporal and spatial productivity changes (Frank and McNaughton 1990, Augustine 2003, Knapp and Smith 2001). In highly responsive systems like grasslands, AGB estimations can help in (1) understanding the impact of biophysical and ecological processes on ecosystem productivity (Loreau and Hector 2001, Tilman et al. To this end, evaluating the AGB dry weight per unit surface is probably the most effective way to describe the primary productivity of an ecosystem. Aboveground biomass (AGB), the most visible of the five carbon pools in terrestrial ecosystems (Ravindranath and Ostwald 2008), is widely used in ecological studies as a proxy of primary productivity. Therefore, monitoring primary productivity is crucial to understand how environmental variations affect ecosystems. 2006) and increases of biomass production can affect species diversity (Li et al. Diachronic canopy variation model produced congruent patterns of inter-seasonal canopy variations proving to be a useful tool for analyzing local disturbance to vegetation canopy caused by grazing.īiodiversity and functioning of ecosystems are closely related to primary productivity: Biodiversity variations can result in a reduction of productivity (Tilman et al. Our study indicates that image-based photogrammetric techniques allow for reliable non-destructive measurements of surface biomass in diachronic analyses, offering a valuable tool for evaluating occurrence, magnitude, and spatial patterns of variations of community primary productivity over time. In one plot, we found an anomalous seasonal pattern, showing an AGB reduction in spring, which can be correlated with grazing, that promoted a subsequent increment in summer. Three plots revealed higher rates of AGB in the spring compared to summer season, as justified by the summer aridity constraints affecting vegetation productivity in Mediterranean areas. Adjusted volumes were fully correlated with the average point distance. Such options were then selected to measure the DCVM. The best fit was obtained selecting 1 mm grid cell size and minimum point height distance. ![]() The measurement setting for AGB volume estimations strongly influenced their correlation with traditional AGB scores. ![]() On the measured volume ( V d), the coefficient of density ( c ρ) was applied to adjust the volume values ( V adj) in relation to variation due to different DCVM point densities. Models relative to the same plot were aligned and their relative difference measured to produce a diachronic canopy variation model (DCVM). Furthermore, 3D models of four mountain pasture plots were reconstructed in May, July, and August. Volume-based AGB measures were regressed to AGB values resulting from destructive methods to identify the measurement settings that show the best fit. Three-dimensional (3D) models of fourteen 1 × 1 m 2 pasture plots were reconstructed and AGB volume measured under several measurement settings. Structure-from-motion (SfM) photogrammetry has been proved to be a reliable tool for rapid and not destructive AGB estimations in grass systems. Destructive AGB measurements, although accurate, are time-consuming and do not allow for repeated measurements as required by monitoring protocols. Aboveground biomass (AGB) is a parameter commonly used for assessing and monitoring primary productivity of grassland communities. ![]()
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