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São Paulo, Brazil

de Melo E.A.S.C.,Forestry Science and Research Institute IPEF | Bazani J.H.,4tree Agroflorestal | Arthur J.C.,Forestry Science and Research Institute IPEF | Borges J.S.,Duratex | And 2 more authors.
Forests | Year: 2016

Eucalypt plantations in Brazil have the highest mean productivity when compared to other producing countries, and fertilizer application is one of the main factors responsible for these productivities. Our aim was to identify appropriate rates of N, P and K in eucalypt plantations and their interactions with edaphoclimatic factors. Four trials with four rates and three nutrients (N, P and K) were set up. Each nutrient was studied separately, and the trees received sufficient rates of all of the other nutrients through fertilization, to avoid limitations not related to the desired nutrient. We assessed solid wood volume (SV), productivity gains (PG), leaf nutrient content and leaf area index (LAI) to determine the responses to fertilization. PG, regarding N, rates ranged from 104% to 127% at 60 months after planting. P fertilizer application led to gains in productivity in soils with levels of P-resin up to 5 mg· kg-1, but decreased with stand age. K fertilizer application responses increased within age in three sites. In Paulistania, responses to K application were close to zero. N and K responses were climate related. Leaf nutrient content and LAI were not able to predict the highest yields obtained. © 2016 by the authors. Source

Stape J.L.,North Carolina State University | Binkley D.,Colorado State University | Ryan M.G.,U.S. Department of Agriculture | Ryan M.G.,Colorado State University | And 14 more authors.
Forest Ecology and Management | Year: 2010

We examined the potential growth of clonal Eucalyptus plantations at eight locations across a 1000+ km gradient in Brazil by manipulating the supplies of nutrients and water, and altering the uniformity of tree sizes within plots. With no fertilization or irrigation, mean annual increments of stem wood were about 28% lower (16.2 Mg ha-1 yr-1, about 33 m3 ha-1 yr-1) than yields achieved with current operational rates of fertilization (22.6 Mg ha-1 yr-1, about 46 m3 ha-1 yr-1). Fertilization beyond current operational rates did not increase growth, whereas irrigation raised growth by about 30% (to 30.6 Mg ha-1 yr-1, about 62 m3 ha-1 yr-1). The potential biological productivity (current annual increment) of the plantations was about one-third greater than these values, if based only on the period after achieving full canopies. The biological potential productivity was even greater if based only on the full-canopy period during the wet season, indicating that the maximum biological productivity across the sites (with irrigation, during the wet season) would be about 42 Mg ha-1 yr-1 (83 m3 ha-1 yr-1). Stands with uniform structure (trees in plots planted in a single day) showed 13% greater growth than stands with higher heterogeneity of tree sizes (owing to a staggered planting time of up to 80 days). Higher water supply increased growth and also delayed by about 1 year the point where current annual increment and mean annual increment intersected, indicating opportunities for lengthening rotations for more productive treatments as well as the influence of year-to-year climate variations on optimal rotations periods. The growth response to treatments after canopy closure (mid-rotation) related well with full-rotation responses, offering an early opportunity for estimating whole-rotation yields. These results underscore the importance of resource supply, the efficiency of resource use, and stand uniformity in setting the bounds for productivity, and provide a baseline for evaluating the productivity achieved in operational plantations. The BEPP Project showed that water supply is the key resource determining levels of plantation productivity in Brazil. Future collaboration between scientists working on silviculture and genetics should lead to new insights on the mechanisms connecting water and growth, leading to improved matching of sites, clones, and silviculture. © 2010 Elsevier B.V. Source

le Maire G.,CIRAD - Agricultural Research for Development | Marsden C.,CIRAD - Agricultural Research for Development | Marsden C.,Montpellier SupAgro | Nouvellon Y.,CIRAD - Agricultural Research for Development | And 6 more authors.
Remote Sensing of Environment | Year: 2011

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25m3/ha for volume (15% of the volume average value) and about 1.6m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. © 2011 Elsevier Inc. Source

Baghdadi N.,IRSTEA | Le Maire G.,CIRAD - Agricultural Research for Development | Bailly J.-S.,Agro ParisTech | Ose K.,IRSTEA | And 4 more authors.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2015

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. © 2008-2012 IEEE. Source

Baghdadi N.,IRSTEA | Le Maire G.,CIRAD - Agricultural Research for Development | Fayad I.,IRSTEA | Bailly J.-S.,Agro ParisTech | And 3 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2014

The Geoscience Laser Altimeter System (GLAS) has provided a useful dataset for estimating forest height 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. The objective of this study was to test the best known models used for estimating canopy height and above ground biomass of intensively managed Eucalyptus plantations in Brazil using full waveform LiDAR data. Studies to estimate forest heights from LiDAR data have highlighted that the fitting coefficients of developed models are strongly dependent on environmental factors such as the region of the study site, terrain topography, and forest type. In this study, we evaluated the main models developed to predict canopy height using a combination of parameters extracted from GLAS waveforms and a digital elevation model, in order to explore which combination of parameters yields the best forest height estimates. In addition, a model to estimate above ground biomass from dominant height was calibrated. © 2014 IEEE. Source

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