Soil moisture regime and palm height influence embolism resistance in oil palm

Plasticity of wood and leaf traits related to hydraulic efficiency and safety is linked to evaporative demand and not soil moisture in rubber (Hevea brasiliensis)

The predicted increase of drought intensity in South-East Asia has raised concern about the sustainability of rubber (Hevea brasiliensis Müll. Arg.) cultivation. In order to quantify the degree of phenotypic plasticity in this important tree crop species, we analysed a set of wood and leaf traits related to the hydraulic safety and efficiency in PB260 clones from eight small-holder plantations in Jambi province, Indonesia, representing a gradient in local microclimatic and edaphic conditions. Across plots, branch embolism resistance (P50) ranged from -2.14 to -2.58 MPa. The P50 and P88 values declined, and the hydraulic safety margin increased, with an increase in the mean annual vapour pressure deficit (VPD). Among leaf traits, only the changes in specific leaf area were related to the differences in evaporative demand. These variations of hydraulic trait values were not related to soil moisture levels. We did not find a trade-off between hydraulic safety and efficiency, but vessel density (VD) emerged as a major trait associated with both safety and efficiency. The VD, and not vessel diameter, was closely related to P50 and P88 as well as to specific hydraulic conductivity, the lumen-to-sapwood area ratio and the vessel grouping index. In conclusion, our results demonstrate some degree of phenotypic plasticity in wood traits related to hydraulic safety in this tropical tree species, but this is only in response to the local changes in evaporative demand and not soil moisture. Given that VPD may increasingly limit plant growth in a warmer world, our results provide evidence of hydraulic trait changes in response to a rising evaporative demand.

Oil palm (Elaeis guineensis) plantation on tropical peatland in South East Asia: Photosynthetic response to soil drainage level for mitigation of soil carbon emissions

While existing moratoria in Indonesia and Malaysia should preclude continued large-scale expansion of palm oil production into new areas of South-East Asian tropical peatland, existing plantations in the region remain a globally significant source of atmospheric carbon due to drainage driven decomposition of peatland soils. Previous studies have made clear the direct link between drainage depth and peat carbon decomposition and significant reductions in the emission rate of CO₂ can be made by raising water tables nearer to the soil surface. However, the impact of such changes on palm fruit yield is not well understood and will be a critical consideration for plantation managers. Here we take advantage of very high frequency, long-term monitoring of canopy-scale carbon exchange at a mature oil palm plantation in Malaysian Borneo to investigate the relationship between drainage level and photosynthetic uptake and consider the confounding effects of light quality and atmospheric vapour pressure deficit. Canopy modelling from our dataset demonstrated that palms were exerting significantly greater stomatal control at deeper water table depths (WTD) and the optimum WTD for photosynthesis was found to be between 0.3 and 0.4 m below the soil surface. Raising WTD to this level, from the industry typical drainage level of 0.6 m, could increase photosynthetic uptake by 3.6 % and reduce soil surface emission of CO₂ by 11 %. Our study site further showed that despite being poorly drained compared to other planting blocks at the same plantation, monthly fruit bunch yield was, on average, 14 % greater. While these results are encouraging, and at least suggest that raising WTD closer to the soil surface to reduce emissions is unlikely to produce significant yield penalties, our results are limited to a single study site and more work is urgently needed to confirm these results at other plantations.

Soil water availability and branch age explain variability in xylem safety of European beech in Central Europe

Xylem embolism resistance has been identified as a key trait with a causal relation to drought-induced tree mortality, but not much is known about its intra-specific trait variability (ITV) in dependence on environmental variation. We measured xylem safety and efficiency in 300 European beech (Fagus sylvatica L.) trees across 30 sites in Central Europe, covering a precipitation reduction from 886 to 522 mm year⁻¹. A broad range of variables that might affect embolism resistance in mature trees, including climatic and soil water availability, competition, and branch age, were examined. The average P₅₀ value varied by up to 1 MPa between sites. Neither climatic aridity nor structural variables had a significant influence on P₅₀. However, P₅₀ was less negative for trees with a higher soil water storage capacity, and positively related to branch age, while specific conductivity (K_s) was not significantly associated with either of these variables. The greatest part of the ITV for xylem safety and efficiency was attributed to random variability within populations. We conclude that the influence of site water availability on P₅₀ and K_s is low in European beech, and that the high degree of within-population variability for P₅₀, partly due to variation in branch age, hampers the identification of a clear environmental signal.

Vegetation Effects on Soil Moisture Retrieval from Water Cloud Model Using PALSAR-2 for Oil Palm Trees

In oil palm crop, soil fertility is less important than the physical soil characteristics. It is important to have a balance and sufficient soil moisture to sustain high yields in oil palm plantations. However, conventional methods of soil moisture determination are laborious and time-consuming with limited coverage and accuracy. In this research, we evaluated synthetic aperture radar (SAR) and in-situ observations at an oil palm plantation to determine SAR signal sensitivity to oil palm crop by means of water cloud model (WCM) inversion for retrieving soil moisture from L-band HH and HV polarized data. The effects of vegetation on backscattering coefficients were evaluated by comparing Leaf Area Index (LAI), Leaf Water Area Index (LWAI) and Normalized Plant Water Content (NPWC). The results showed that HV polarization effectively simulated backscatter coefficient as compared to HH polarization where the best fit was obtained by taking the LAI as a vegetation descriptor. The HV polarization with the LAI indicator was able to retrieve soil moisture content with an accuracy of at least 80%.

Hydraulic variability of three temperate broadleaf tree species along a water availability gradient in central Europe

Plant hydraulic traits are key for understanding and predicting tree drought responses. Information about the degree of the traits' intra-specific variability may guide the selection of drought-resistant genotypes and is crucial for trait-based modelling approaches. For the three temperate minor broadleaf tree species Acer platanoides, Carpinus betulus and Tilia cordata, we measured xylem embolism resistance (P₅₀ ), leaf turgor loss point (P_TLP ), specific hydraulic conductivity (K_S ), Huber values (HVs), and hydraulic safety margins in adult trees across a precipitation gradient. We further quantified trait variability on different organizational levels (inter-specific to within-canopy variation), and analysed its relationship to climatic and soil water availability. Although we observed a certain intra-specific trait variability (ITV) in safety-related traits (P₅₀ , P_TLP ) with higher within-tree and between-tree than between populations variability, the magnitude was small compared to inter-specific differences, which explained 78.4% and 58.3% of the variance in P₅₀ and P_TLP , respectively. In contrast, efficiency-related traits (K_S , HV) showed a high ITV both within populations and within the crowns of single trees. Surprisingly, the observed ITV of all traits was neither driven by climatic nor soil water availability. In conclusion, the high degree of conservatism in safety-related traits highlights their potential for trait-based modelling approaches.

Predicting Tree Sap Flux and Stomatal Conductance from Drone-Recorded Surface Temperatures in a Mixed Agroforestry System—A Machine Learning Approach

Plant transpiration is a key element in the hydrological cycle. Widely used methods for its assessment comprise sap flux techniques for whole-plant transpiration and porometry for leaf stomatal conductance. Recently emerging approaches based on surface temperatures and a wide range of machine learning techniques offer new possibilities to quantify transpiration. The focus of this study was to predict sap flux and leaf stomatal conductance based on drone-recorded and meteorological data and compare these predictions with in-situ measured transpiration. To build the prediction models, we applied classical statistical approaches and machine learning algorithms. The field work was conducted in an oil palm agroforest in lowland Sumatra. Random forest predictions yielded the highest congruence with measured sap flux (r2 = 0.87 for trees and r2 = 0.58 for palms) and confidence intervals for intercept and slope of a Passing-Bablok regression suggest interchangeability of the methods. Differences in model performance are indicated when predicting different tree species. Predictions for stomatal conductance were less congruent for all prediction methods, likely due to spatial and temporal offsets of the measurements. Overall, the applied drone and modelling scheme predicts whole-plant transpiration with high accuracy. We conclude that there is large potential in machine learning approaches for ecological applications such as predicting transpiration.