Guerric Le Maire

Production and carbon allocation in monocultures and mixed-species plantations of Eucalyptus grandis and Acacia mangium in Brazil

Introducing nitrogen-fixing tree species in fast-growing eucalypt plantations has the potential to improve soil nitrogen availability compared with eucalypt monocultures. Whether or not the changes in soil nutrient status and stand structure will lead to mixtures that out-yield monocultures depends on the balance between positive interactions and the negative effects of interspecific competition, and on their effect on carbon (C) uptake and partitioning. We used a C budget approach to quantify growth, C uptake and C partitioning in monocultures of Eucalyptus grandis (W. Hill ex Maiden) and Acacia mangium (Willd.) (treatments E100 and A100, respectively), and in a mixture at the same stocking density with the two species at a proportion of 1 : 1 (treatment MS). Allometric relationships established over the whole rotation, and measurements of soil CO(2) efflux and aboveground litterfall for ages 4-6 years after planting were used to estimate aboveground net primary production (ANPP), total belowground carbon flux (TBCF) and gross primary production (GPP). We tested the hypotheses that (i) species differences for wood production between E. grandis and A. mangium monocultures were partly explained by different C partitioning strategies, and (ii) the observed lower wood production in the mixture compared with eucalypt monoculture was mostly explained by a lower partitioning aboveground. At the end of the rotation, total aboveground biomass was lowest in A100 (10.5 kg DM m(-2)), intermediate in MS (12.2 kg DM m(-2)) and highest in E100 (13.9 kg DM m(-2)). The results did not support our first hypothesis of contrasting C partitioning strategies between E. grandis and A. mangium monocultures: the 21% lower growth (ΔB(w)) in A100 compared with E100 was almost entirely explained by a 23% lower GPP, with little or no species difference in ratios such as TBCF/GPP, ANPP/TBCF, ΔB(w)/ANPP and ΔB(w)/GPP. In contrast, the 28% lower ΔB(w) in MS than in E100 was explained both by a 15% lower GPP and by a 15% lower fraction of GPP allocated to wood growth, thus partially supporting our second hypothesis: mixing the two species led to shifts in C allocations from above- to belowground, and from growth to litter production, for both species.

Dynamics of soil exploration by fine roots down to a depth of 10 m throughout the entire rotation in Eucalyptus grandis plantations

Although highly weathered soils cover considerable areas in tropical regions, little is known about exploration by roots in deep soil layers. Intensively managed Eucalyptus plantations are simple forest ecosystems that can provide an insight into the belowground growth strategy of fast-growing tropical trees. Fast exploration of deep soil layers by eucalypt fine roots may contribute to achieving a gross primary production that is among the highest in the world for forests. Soil exploration by fine roots down to a depth of 10 m was studied throughout the complete cycle in Eucalyptus grandis plantations managed in short rotation. Intersects of fine roots, less than 1 mm in diameter, and medium-sized roots, 1–3 mm in diameter, were counted on trench walls in a chronosequence of 1-, 2-, 3.5-, and 6-year-old plantations on a sandy soil, as well as in an adjacent 6-year-old stand growing in a clayey soil. Two soil profiles were studied down to a depth of 10 m in each stand (down to 6 m at ages 1 and 2 years) and 4 soil profiles down to 1.5–3.0 m deep. The root intersects were counted on 224 m2 of trench walls in 15 pits. Monitoring the soil water content showed that, after clear-cutting, almost all the available water stored down to a depth of 7 m was taken up by tree roots within 1.1 year of planting. The soil space was explored intensively by fine roots down to a depth of 3 m from 1 year after planting, with an increase in anisotropy in the upper layers throughout the rotation. About 60% of fine root intersects were found at a depth of more than 1 m, irrespective of stand age. The root distribution was isotropic in deep soil layers and kriged maps showed fine root clumping. A considerable volume of soil was explored by fine roots in eucalypt plantations on deep tropical soils, which might prevent water and nutrient losses by deep drainage after canopy closure and contribute to maximizing resource uses.

Testing Different Methods of Forest Height and Aboveground Biomass Estimations From ICESat/GLAS Data in Eucalyptus Plantations in Brazil

The Geoscience Laser Altimeter System (GLAS) has provided a useful dataset for estimating forest heights in many areas of the globe. Most of the studies on GLAS waveforms have focused on natural forests and only a few were conducted over forest plantations. This work set out to estimate the stand-scale dominant height and aboveground biomass of intensively managed Eucalyptus plantations in Brazil using the most commonly used models developed for natural forests. These forest plantations are valuable case studies, with large and numerous stands that are very uniform, in which field measurements are precise compared to natural forests. The height of planted Eucalyptus forest stands estimated from waveforms acquired by GLAS were compared with in situ measurements in order to determine the model that produced the best forest height estimates. For our slightly sloping study site , the direct method defined as the difference between the signal begin and the ground peak provided forest height estimates with an accuracy of 2.2 m. The use of statistical models based on waveform metrics and digital elevation models provided slightly better results (1.89 m accuracy) in comparison with the direct method and the most relevant metrics proved to be the trailing edge extent and the waveform extent. Moreover, a power law model was used to fit in situ aboveground biomass to in situ forest height. The results using this model with GLAS-derived heights showed an accuracy for biomass of 16.1 Mg/ha.

Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity

ABSTRACT Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red and near-infrared channels). Different strategies were devised to assess the accuracy of the classification methods: confusion matrices and derived accuracy indicators with and without equalizing class proportions, assessing the pairwise difference error rates and accounting for the spatial resolution bias. The robustness of the accuracy with respect to a reduction of the quantity of calibration data available was also assessed by a bootstrap approach in which the amount of training data was systematically reduced. Methods reached overall accuracies ranging from 85% to 95%, which demonstrates the ability of 250 m imagery to resolve fields down to 20 ha. Despite significantly different error rates, the site effect was found to persistently dominate the method effect. This was confirmed even after removing the share of the classification due to the spatial resolution of the satellite data (from 10% to 30%). This underlines the effect of other agrosystems characteristics such as cloudiness, crop diversity, and calendar on the ability to perform accurately. All methods have potential for large area cropland mapping as they provided accurate results with 20% of the calibration data, e.g. 2% of the study area in Ukraine. To better address the global cropland diversity, results advocate movement towards a set of cropland classification methods that could be applied regionally according to their respective performance in specific landscapes.

Measured and modeled interactive effects of potassium deficiency and water deficit on gross primary productivity and light-use efficiency in Eucalyptus grandis plantations

Global climate change is expected to increase the length of drought periods in many tropical regions. Although large amounts of potassium (K) are applied in tropical crops and planted forests, little is known about the interaction between K nutrition and water deficit on the physiological mechanisms governing plant growth. A process-based model (MAESPA) parameterized in a split-plot experiment in Brazil was used to gain insight into the combined effects of K deficiency and water deficit on absorbed radiation (aPAR), gross primary productivity (GPP), and light-use efficiency for carbon assimilation and stem biomass production (LUEC and LUEs ) in Eucalyptus grandis plantations. The main-plot factor was the water supply (undisturbed rainfall vs. 37% of throughfall excluded) and the subplot factor was the K supply (with or without 0.45 mol K m(-2 ) K addition). Mean GPP was 28% lower without K addition over the first 3 years after planting whether throughfall was partly excluded or not. K deficiency reduced aPAR by 20% and LUEC by 10% over the whole period of growth. With K addition, throughfall exclusion decreased GPP by 25%, resulting from a 21% decrease in LUEC at the end of the study period. The effect of the combination of K deficiency and water deficit was less severe than the sum of the effects of K deficiency and water deficit individually, leading to a reduction in stem biomass production, gross primary productivity and LUE similar to K deficiency on its own. The modeling approach showed that K nutrition and water deficit influenced absorbed radiation essentially through changes in leaf area index and tree height. The changes in gross primary productivity and light-use efficiency were, however, driven by a more complex set of tree parameters, especially those controlling water uptake by roots and leaf photosynthetic capacities.

Evaluation of ALOS/PALSAR L-Band Data for the Estimation of Eucalyptus Plantations Aboveground Biomass in Brazil

The Phased Array L-band Synthetic Aperture Radar (PALSAR-1) has provided very useful images dataset for several applications such as forestry. L-Band radar measurements have been widely used but with somewhat contradictory conclusions on the potential of this radar wavelength to estimate the aboveground biomass (AGB). The first objective of this study was to analyze the L-band SAR backscatter sensitivity to forest biomass for Eucalyptus plantations. The results showed that the radar signal is highly dependent on biomass only for values lower than 50 t/ha, which corresponds to plantations of approximately 3 years of age. Next, random forest (RF) regressions were performed to evaluate the potential of PALSAR data to predict the Eucalyptus biomass. Regressions were constructed to link the biomass to both radar signal and age of plantations. Results showed that the age was the variable that best explained the biomass followed by the PALSAR HV polarized signal. For biomasses lower than 50 t/ha, HV signal and plantation age were found to have the same level of importance in predicting biomass. For biomasses higher than 50 t/ha, plantation age was the main variable in the RF models. The use of PALSAR signal alone did not correctly predict the biomass of Eucalyptus plantations [ℝ2 lower than 0.5 and root-mean-squared error (RMSE) higher than 46.7 t/ha]. The use of plantation age in addition to the PALSAR signal improved slightly the prediction results (ℝ2 increased from 0.88 to 0.92 and RMSE decreased from 22.7 to 18.9 t/ha). PALSAR imagery does not allow a direct estimation of planting date of Eucalyptus stands but can follow efficiently the occurrence of clear-cuts if images are acquired sequentially, therefore allowing a rough estimate of the following plantation date because a stand of Eucalyptus is generally replanted 2-4 months after cutting. With a time series of radar images, it could be, therefore, possible to estimate the plantation age, and therefore improving the estimates of plantation biomass.

Increased light-use efficiency sustains net primary productivity of shaded coffee plants in agroforestry system

In agroforestry systems, shade trees strongly affect the physiology of the undergrown crop. However, a major paradigm is that the reduction in absorbed photosynthetically active radiation is, to a certain extent, compensated by an increase in light-use efficiency, thereby reducing the difference in net primary productivity between shaded and non-shaded plants. Due to the large spatial heterogeneity in agroforestry systems and the lack of appropriate tools, the combined effects of such variables have seldom been analysed, even though they may help understand physiological processes underlying yield dynamics. In this study, we monitored net primary productivity, during two years, on scales ranging from individual coffee plants to the entire plot. Absorbed radiation was mapped with a 3D model (MAESPA). Light-use efficiency and net assimilation rate were derived for each coffee plant individually. We found that although irradiance was reduced by 60% below crowns of shade trees, coffee light-use efficiency increased by 50%, leaving net primary productivity fairly stable across all shade levels. Variability of aboveground net primary productivity of coffee plants was caused primarily by the age of the plants and by intraspecific competition among them (drivers usually overlooked in the agroforestry literature) rather than by the presence of shade trees.

Tree crown detection in high resolution optical images during the early growth stages of Eucalyptus plantations in Brazil

Individual tree detection methods are more and more present, and improve, in forestry and silviculture domains with the increasing availability of satellite metric imagery [2–7]. Automatic detection on these very high spatial resolution images aims to determine the tree positions and crown sizes. In this paper, we use a mathematical model based on marked point processes, which showed advantages w.r.t. several individual tree detection algorithms for plantations [2], to analyze an Eucalyptus plantation in Brazil, with 2 optical images acquired by the WorldView-2 satellite. A tentative detection simultaneously with 2 images of different dates (multi-date) has been tested for the first time, which estimates individual tree crown variation during these dates. While, for most current detection methods, only the static state of tree crowns at the moment of one images acquisition is estimated. The relevance of detection is discussed considering the detection performance in tree localizations and crown sizes. Then, tree crown growth are deduced from detection results and compared with the expected dynamics of corresponding populations.

Very high resolution satellite images for parameterization of tree-scale forest process-based model

Very high spatial resolution (VHSR) satellite images provide interesting information for parameterizing tree-scale forest process-based models, and in particular their light absorption submodels, which is at the basis of photosynthesis calculation. Such tree-scale models require a large amount of field measurements to describe the forest ecosystems, i.e. all tree positions, their sizes and shapes, their leaf areas, etc. These data are generally measured directly in the field [1], which can be tedious for large areas like a forest stand. In this study, we explore the possibility to parameterize such tree-scale models directly or indirectly from panchromatic and multispectral very high resolution images.

Simulating the Canopy Reflectance of Different Eucalypt Genotypes With the DART 3-D Model

Finding suitable models of canopy reflectance in forward simulation mode is a prerequisite for their use in inverse mode to characterize canopy variables of interest, such as leaf area index (LAI) or chlorophyll content. In this study, the accuracy of the three-dimensional reflectance model DART (Discrete Anisotropic Radiative Transfer) was assessed for canopies of different genotypes of Eucalyptus, having distinct biophysical and biochemical characteristics, to improve the knowledge on how these characteristics are influencing the reflectance signal as measured by passive orbital sensors. The first step was to test the model suitability to simulate reflectance images in the visible and near infrared. We parameterized DART model using extensive measurements from Eucalyptus plantations including 16 contrasted genotypes. Forest inventories were conducted and leaf, bark, and forest floor optical properties were measured. Simulation accuracy was evaluated by comparing the mean top of canopy (TOC) bidirectional reflectance of DART with TOC reflectance extracted from a Pleiades very high resolution satellite image. Results showed a good performance of DART with mean reflectance absolute error lower than 2%. Intergenotype reflectance variability was correctly simulated, but the model did not succeed at catching the slight spatial variation for a given genotype, excepted when large gaps appeared due to tree mortality. The second step consisted of sensitivity analysis to explore which biochemical or biophysical characteristics influenced more the canopy reflectance between genotypes. Perspectives for using DART model in inversion mode in these ecosystems were discussed.