COS 39-1 - Coupling remote sensing data with ground surveys of grassland communities following experimental nutrient deposition and disturbance

Abstract: Anthropogenic induced nutrient deposition and large-scale disturbances are two prominent and pervasive drivers of global change in grassland ecosystems. Unintended changes in grassland community dynamics and functional group diversity threaten to alter grassland ecosystem functions (e.g., nutrient cycling and primary production) and services (e.g., carbon sequestration and food production). The emergence of Unmanned Aerial Vehicles (UAVs; i.e., drones) and advancements in remote sensing (RS) technology to assess changes in grassland community composition is of increasing interest to ecologists and restoration practitioners alike. Here, we used UAV RS imagery to quantify functional group changes of a tallgrass prairie in central Texas, USA (31.044611, -97.349240) following experimental nutrient deposition and disturbance. We compared our results with ground survey data to assess the accuracy of our RS data. The field site consisted of 25, 5 m x 5 m plots, arranged in a 5 x 5 Latin Square design. Treatments included: (1) Control (C), (2) nitrogen (N), phosphorus (P), potassium (P), and micronutrients addition (NPK), (3) soil disturbance (D), (4) NPK+D, and (5) NPK cessation (not used in this analysis). The soil disturbance treatment was carried out in January 2022 by rototilling the soil surface to a depth of 15 cm, while nutrient addition was administered in April 2022 as 10 g m^-2 of granular N, P, K, and micronutrients. UAV RS data were collected monthly in all plots between March – September 2022. Corresponding surveys of species percent cover were taken within seven days of each UAV RS survey. Nonparametric multidimensional scaling of ground cover data indicated community composition strongly varied among treatments. Nutrient addition alone resulted in increased cover in C₄ grasses - primarily invasive Sorghum halepense. Paired nutrient addition and disturbance caused total species turnover and significant reduction in C₃ and C₄ grasses and legume cover, but significantly increased the cover of forbs, specifically noxious Ambrosia trifida. Functional group cover estimates from UAV RS data mirrored ground survey results, but the accuracy of results varied across sample dates. UAV RS was most accurate at estimating functional group cover during May, June, and July, coinciding with peak plant activity. Our results indicate nutrient deposition and disturbance changed plant functional group cover and these changes can be detected using UAV-remote sensing techniques.