Oil palm monocultures are highly productive, but there are widespread negative impacts on biodiversity and ecosystem functions. Some of these negative impacts might be mitigated by mixed-species tree interplanting to create agroforestry systems, but there is little experience with the performance of trees planted in oil palm plantations. We studied a biodiversity enrichment experiment in the lowlands of Sumatra that was established in a 6-to 12-year-old oil palm plantation by planting six tree species in different mixtures on 48 plots. Three years after tree planting, canopy cover was assessed by drone-based photogrammetry using the structure-from-motion technique. Drone-derived canopy cover estimates were highly correlated with traditional ground-based hemispherical photography along the equality line, indicating the usefulness and comparability of the approach. Canopy cover was further partitioned between oil palm and tree canopies. Thinning of oil palms before tree planting created a more open and heterogeneous canopy cover. Oil palm canopy cover was then extracted at the level of oil palms and individual trees and combined with ground-based mortality assessment for all 3,819 planted trees. For three tree species (Archidendron pauciflorum, Durio zibethinus, and Shorea leprosula), the probability of mortality during the year of the study was dependent on the amount of oil palm canopy cover. We regard the drone-based method for deriving and partitioning spatially explicit information as a promising way for many questions addressing canopy cover in ecological applications and the management of agroforestry systems.

Transpiration at the stand level is often estimated from water use measurements on a limited number of plants and then scaled up by predicting the remaining plants of a stand by plant size-related variables. Today, drone-based methods offer new opportunities for plant size assessments. We tested crown variables derived from drone-based photogrammetry for predicting and scaling plant water use. In an oil palm agroforest and an oil palm monoculture plantation in lowland Sumatra, Indonesia, tree and oil palm water use rates were measured by sap flux techniques.Simultaneously, aerial images were taken from an octocopter equipped with an Red Green Blue (RGB) camera. We used the structure from motion approach to compute several crown variables such as crown length, width, and volume. Crown volumes for both palms (69%) and trees (81%) explained much of the observed spatial variability in water use; however, the specific crown volume model differed between palms and trees and there was no single linear model fitting for both. Among the trees, crown volume explained more of the observed variability than stem diameter, and in consequence, uncertainties in stand level estimates resulting from scaling were largely reduced. For oil palms, an appropriate whole-plant size-related predictor variable was thus far not available. Stand level transpiration estimates in the studied oil palm agroforest were lower than those in the oil palm monoculture, which is probably due to the small-statured trees. In conclusion, we consider drone-derived crown metrics very useful for the scaling from single plant water use to stand-level transpiration.

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