Integration of remote sensing in spatial ecology: assessing the interspecific interactions of two plant species in a semi-arid woodland using unmanned aerial vehicle (UAV) photogrammetric data.

The spatial structure of plant communities in semi-arid regions is mostly derived by plant-plant interactions and environmental heterogeneity. In this study, we investigated the intra- and interspecific interactions and their contribution to growth inhibition in the patches of Pistacia trees and Amygdalus shrubs in semi-arid woodland communities through the implementation of photogrammetric data provided by unmanned aerial vehicle (UAV). This study was conducted in a part of Wild Pistachio Natural Reserve covered by Pistacia-Amygdalus stands in Zagros Mountains, western Iran. We used univariate and bivariate forms of pair- and mark correlation functions and Analytical Global Envelopes under inhomogeneous Poisson process which allow detection of the interactions of the species within the 45-ha study area. Our results indicated that the UAV-derived photogrammetric data proved to be efficient in identification of the plant individuals (F-score ≈ 0.92 for both species). Additionally, strong coefficients of determination (R2 = 0.98 and 0.94 for Pistacia and Amygdalus, respectively) supported prediction of crown area. We observed the aggregation of the species individuals in clusters of conspecifics and heterospecifics at small spatial scales, most likely as a result of aggregation in favourable parts of the study area. The aggregation of the species within patches had a marked effect on their size (i.e., crown area, height) inferred as growth inhibition, probably due to intra- and interspecific competition. Our findings demonstrated that promising UAV photogrammetric data can be effectively utilized by ecologists for investigation of plant associations, hence increasing the potentiality of remote sensing in spatial ecology of vegetation patches in semi-arid environments.