Spatial patterns of above-ground biomass in tropical alpine páramo ecosystems using allometric models and LiDAR data

Context: Páramos, high-elevation alpine ecosystems found in the northern Andes, are a biodiversity hotspot and play a crucial role in climate change mitigation due to their carbon storage capacity. Above-ground biomass (AGB) serves as a key indicator of ecosystem health and carbon sequestration potential. Accurate estimates of above-ground biomass are essential for understanding the variability of carbon storage across different páramo vegetation types, successional stages and degradation impacts supporting the design of effective conservation and management strategies. Objectives: We analyzed the main patterns of AGB across different vegetation types and plant growth forms combining methods of direct field measurements and UAV-LiDAR. This study was conducted into conserved area named El Cocuy National Natural Park, within Páramos ecosystems in the northeast of the Colombian Andes. Methods: We measured the AGB of the different plant growth forms and related that to relevant allometric traits by using simple linear models. Using the allometric equations we estimated the AGB of 30 plots in areas dominated by different páramo vegetation types. Airborne LiDAR data was collected from these plots and canopy height and density metrics were processed to determine landscape-level above-ground biomass calibrated with the ground measurements. Results: We found that plant height, basal diameter, and leaf area explained AGB variation for the different plant growth forms. We selected models with canopy height model (CHM) as predictor, to explain above-ground biomass at the landscape level. Allometric and LiDAR derived models showed páramo values ranging from 3 to 11 Mg C ha⁻¹. Conclusions: Our results demonstrated that it is possible to understand above ground carbon accumulation patterns at the landscape level by combining direct and indirect methods, such as allometric equations and LiDAR data, in areas representing the heterogeneity of páramo vegetation. This study is pioneering in providing information for non-forest carbon reservoirs and the impacts of human actions on the dynamics of the AGB, which are crucial to reach national greenhouse gases emission targets.