Developing Allometric Equations for Exotic Annual Grasses using Extremely Close-Range Structure-from-Motion (SfM) in a Semi-Arid Ecosystem

Abstract:

The native vegetation communities in the sagebrush steppe, a semi-arid ecosystem type, are under threat from exotic annual grasses. These grasses, such as cheatgrass (Broumus Tectorum) and medusahead (Taeniatherum caput-medusae), increase fire severity and frequency, decrease biodiversity, and reduce soil carbon storage amongst other ecosystem services. The invasion of exotic annual grasses is causing detrimental impacts to land use by eliminating forage for livestock and creating a huge economic cost from fire control and post-fire restoration. Above ground biomass (AGB) is an important metric to estimate forage quantity, fuel loads, and in quantifying the effects of grazing regimens on these threatened rangelands. Current methods for collecting AGB rely exclusively on destructively harvested plots because there are limited allometric equations, to our knowledge, relating remotely sensed data to biomass of exotic annual grasses in the sagebrush steppe. We ask, can Structure-from-Motion (SfM) imagery capture the structure of exotic grasses in low-elevation semi-arid ecosystems? If so, what relationship exists between SfM-derived volume and destructively harvested biomass measurements?

SfM is a photogrammetry technique that uses digital images to develop 3-D point clouds that can be transformed into volumetric measurements of biomass. The SfM technique has the potential to quantify biomass estimates across multiple plots, increasing the spatial coverage compared to traditional field work. In southeast Oregon we developed allometric equations relating SfM-derived volume (m³) to biomass (g/m²). The resulting equation showed a positive relationship (R² = 0.51) between the log transformed SfM-derived volume and log transformed AGB when litter mass was removed. This relationship shows promise in being upscaled to larger surveys using aerial platforms such as Unmanned Aerial Systems (UAS). Ultimately, using allometric equations and remote sensing will increase the spatial coverage for biomass estimates of exotic annual grasses and improve the accuracy in estimates of forage availability for livestock producers.