| dc.description.abstracteng | Transpiration is a central flux in the terrestrial water cycle and is considered an important ecosystem service for atmosphere and hydrosphere regulation. Transpiration is strongly affected by land cover and land-use changes, which are currently very pronounced in tropical regions. It is thus important to better understand transpiration in near-natural and in human-modified ecosystems. This includes aspects of spatio-temporal variation and scaling. The main objectives of this study were (1) to test scaling approaches from individual plants to stand transpiration by using crown metrics, (2) to analyze spatial variation in plant transpiration, and (3) to assess multi-level temporal dynamics of water circulation in a given plant. The study was implemented in the lowlands of Sumatra, where natural rainforests have been converted to oil palm and rubber plantations on a large scale. The actual study sites were a tropical rainforest, an oil palm agroforest and oil palm monocultures. We used drones for assessing crown and stand structures and sap flux measurements for measuring transpiration.
In study 1, we tested scaling approaches from individual plant to stand-level transpiration. At the stand level transpiration 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 a Red Green Blue camera. We used the structure from motion approach to compute several crown variables such as crown length, width, and volume. Crown volumes explained much of the observed spatial variability in water use for both palms (69%) and trees (81%); however, the specific crown volume model differed between palms and trees and there was no single linear model fitting for both. For trees, crown volume explained more of the observed variability than the conventional scaling variable stem diameter; consequently, uncertainties in stand-level estimates that result 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, probably due to the small‐statured trees and the reduced oil palm stand density. In conclusion, we consider drone‐derived crown metrics very useful for the scaling from single plant water use to stand‐level transpiration.
In study 2, we extended the testing of scaling approaches and analyzed predicted spatial variability in transpiration in a rainforest. Tropical rainforests comprise complex 3D structures and encompass heterogeneous site conditions. The objectives of our study were to further test the relationship between tree water use and crown metrics and to predict spatial variability of canopy transpiration across sites. In a lowland rainforest of Sumatra, we measured tree water use with sap flux techniques and simultaneously assessed crown metrics with drone-based photogrammetry. We observed a close linear relationship between individual tree water use and crown surface area (R2 = 0.76, n = 42 trees). Uncertainties in predicting stand-level canopy transpiration were much lower using tree crown metrics than the more conventionally used stem diameter. 3D canopy segmentation analyses in combination with the crown surface area–water use relationship predict substantial spatial heterogeneity in canopy transpiration. Among our eight study plots, there was a more than two-fold difference, with lower transpiration at riparian than at upland sites. In conclusion, we regard drone-based canopy segmentation and crown metrics to be very useful tools for the scaling of transpiration from tree- to stand-level. Our results indicate substantial spatial variation in crown packing and thus canopy transpiration of tropical rainforests.
In study 3, we assessed multi-level temporal dynamics of water circulation in a given plant. For oil palm, a potentially significant contribution of stem water storage to transpiration has been discussed in previous studies. We assessed water use characteristics of oil palms at different horizontal and vertical positions in the plant by using three sap flux techniques. In a radial profile of the stem, sap flux densities were low at the outer margin, increased to 2.5 cm under the bark and remained high to the innermost measured depth at 7.5 cm. In a vertical profile of the stem and with further sensors in leaf petioles, we found only small time lags of sap flux densities. Time lags along the flow path are often used for analyzing the contribution of water storage to transpiration. Thus, the small observed time differences in our study would leave only little room for a contribution of water storage to transpiration. However, water storage might still contribute to transpiration in ways that are not detected by time lag analysis. Such mechanisms may be explored in future studies.
In conclusion, the temporal analyses of oil palm water use suggest that the contribution of stem water storage to transpiration is not yet fully understood. The spatial analyses of transpiration indicate considerable variation of canopy transpiration in oil palm agroforests and particularly in rainforest. Drone-based crown and canopy assessments offer suitable opportunities for predicting such spatial variation. | de |