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Phosphate fertilizers used in planted forests mainly come from scarce and non-renewable sources, and there is a need for new sources of phosphorus (P). An alternative is the use of sewage sludge (SS), rich in organic matter, nitrogen, and P. The objectives were to evaluate the soil P availability and its effect on wood production in 22-month-old Eucalyptus urograndis plantation treated with SS. A field experiment was set up in a randomized complete block design, four replicates, with the following treatments: control without fertilization; mineral fertilization (MF); 14.5 Mg ha–1 of SS + 22 kg ha–1 of P (S1P1); 29 Mg ha–1 of SS (S2); 29 Mg ha–1 of SS + 17.5 kg ha–1 of P (S2P2); and 43.5 Mg ha–1 of SS (S3), dry base. Of the total P in SS, 65% was in organic form and 42% was in labile + moderately labile forms. S2P2 and S3 positively altered the pattern of soil P distribution, with more P in the labile and moderately labile fractions than in the non-labile fraction, along 0–20 cm depths, than MF and control. There were higher microbial and available P as a function of SS dose. Wood volume and biomass were highly related to soil P availability as a function of SS dose. Within the SS treatments, S2P2 resulted in higher gains of volume and biomass of wood. The SS application at the recommend rate, supplemented with 66% of recommended P fertilizer dose in Eucalyptus plantations, can reduce the use of P fertilizer by 33% and N fertilizer by 100% and maintain comparable soil P availability and wood production.

This study aimed to map the stem biomass of an even-aged eucalyptus plantation in southeastern Brazil based on canopy height profile (CHPs) statistics using wall-to-wall discrete return airborne laser scanning (ALS), and compare the results with alternative maps generated by ordinary kriging interpolation from field-derived measurements. The assessment of stem biomass with ALS data was carried out using regression analysis methods. Initially, CHPs were determined to express the distribution of laser point heights in the ALS cloud for each sample plot. The probability density function (pdf) used was the Weibull distribution, with two parameters that in a secondary task, were used as explanatory variables to model stem biomass. ALS metrics such as height percentiles, dispersion of heights, and proportion of points were also investigated. A simple linear regression model of stem biomass as a function of the Weibull scale parameter showed high correlation (adj.R2 = 0.89). The alternative model considering the 30th percentile and the Weibull shape parameter slightly improved the quality of the estimation (adj.R2 = 0.93). Stem biomass maps based on the Weibull scale parameter doubled the accuracy of the ordinary kriging approach (relative root mean square error = 6 % and 13 %, respectively).

O objetivo desse trabalho foi caracterizar a madeira serrada de clones de Eucalyptus com 7 a 13 anos, plantados comercialmente na região de Entre Rios e Esplanada, BA. Para efeito de comparação e como referência, foram utilizadas amostras de Eucalyptus cloeziana com 22 anos, em função da ótima aptidão dessa espécie para serraria. As amostras foram retiradas em duas posições verticais e três posições radiais ao longo do tronco das árvores. Foram observadas diferenças entre clones e posição radial para o índice de rachaduras de extremidade de tábuas secas, flecha de encurvamento, flecha de arqueamento e quantidade de nós, enquanto não houve diferenças em relação à posição da tora ao longo do fuste. Todos os materiais apresentaram alta incidência de nós. As rachaduras de tábua seca, arqueamento e quantidade de nós diminuem no sentido medula-casca, enquanto que o encurvamento tende a aumentar.

Köppen's climate classification remains the most widely used system by geographical and climatological societies across the world, with well recognized simple rules and climate symbol letters. In Brazil, climatology has been studied for more than 140 years, and among the many proposed methods Köppen's system remains as the most utilized. Considering Köppen's climate classification importance for Brazil (geography, biology, ecology, meteorology, hydrology, agronomy, forestry and environmental sciences), we developed a geographical information system to identify Köppen's climate types based on monthly temperature and rainfall data from 2,950 weather stations. Temperature maps were spatially described using multivariate equations that took into account the geographical coordinates and altitude; and the map resolution (100 m) was similar to the digital elevation model derived from Shuttle Radar Topography Mission. Patterns of rainfall were interpolated using kriging, with the same resolution of temperature maps. The final climate map obtained for Brazil (851,487,700 ha) has a high spatial resolution (1 ha) which allows to observe the climatic variations at the landscape level. The results are presented as maps, graphs, diagrams and tables, allowing users to interpret the occurrence of climate types in Brazil. The zones and climate types are referenced to the most important mountains, plateaus and depressions, geographical landmarks, rivers and watersheds and major cities across the country making the information accessible to all levels of users. The climate map not only showed that the A, B and C zones represent approximately 81%, 5% and 14% of the country but also allowed the identification of Köppen's climates types never reported before in Brazil.

O objetivo deste trabalho foi avaliar a fotossíntese, condutância estomática e produtividade de clones de Eucalyptus em duas áreas distintas: uma no Município de Eunápolis, Sul da Bahia, com precipitação bem distribuída ao longo do ano (área úmida); e outra em Salto da Divisa, Leste de Minas Gerais, com precipitação concentrada nos meses quentes do ano (área seca). Foram estudados quatro clones, avaliando-se o crescimento, através do inventário das árvores; e as variáveis fotossintéticas, medidas com o aparelho Infrared Gas Analyser (IRGA). Dentro de cada área só houve diferença significativa entre clones na área úmida quanto à variável volume de madeira. A produtividade dos clones na área úmida foi 3,3 vezes superior à produtividade da área seca. Na área úmida, todos os clones diminuíram a condutância estomática com o aumento do déficit de pressão de vapor, com queda de 0,16 mol m² s-1 para cada 1 kPa de aumento no DPV e taxa fotossintética máxima variando de 12,5 a 16,4 µmol m² s-1. A comparação entre os clones da área úmida resultou em diferença significativa do clone A, que apresentou fotossíntese máxima superior à dos demais. Na área seca não houve relação entre condutância estomática e DPV e não se observou diferença na fotossíntese entre os clones, que variou de 1,2 a 3,4 µmol m² s-1. Verificou-se relação linear entre a fotossíntese máxima e a produtividade dos clones, evidenciando que a taxa fotossintética foi um dos fatores responsáveis pela maior produtividade do Eucalyptus na área úmida.

No Brasil, diversos municípios estão construindo estações de tratamento de esgoto (ETEs), e futuramente serão produzidas anualmente milhares de toneladas de lodo para as quais deverá ser dada destinação adequada. O lodo de esgoto tratado (biossólido) é o resíduo resultante do tratamento do esgoto urbano, e sua disposição final precisa ser bem planejada devido às implicações sanitárias, ambientais, econômicas e sociais. Apresenta elevado teor de matéria orgânica e de nutrientes e poderia ser utilizado como fertilizante em plantios florestais. Esta pesquisa foi realizada na Estação de Ciências Florestais de Itatinga (Universidade de São Paulo), com o objetivo de avaliar o efeito da adição de três doses (10, 20 e 30 t ha-1) dos lodos de esgoto úmido (torta) e seco (granulado), complementados com K e B e aplicados ao solo nas linhas de plantio em parcelas experimentais de Eucalyptus grandis. Dezoito meses após a implantação das mudas no campo, o volume dos troncos demonstrou aumento significativo (ao redor de 130%) no tocante ao crescimento dos eucaliptos tratados com os biossólidos úmido e seco em relação à testemunha sem aplicação de fertilizante, bem como teve resultado semelhante ao do tratamento com adubo mineral. Entretanto, não houve diferença significativa entre os tratamentos com a aplicação dos biossólidos úmido e seco. Com relação à nutrição mineral, foi observado aumento da concentração dos elementos P, Ca e Zn nas folhas com as maiores doses dos biossólidos, e verificou-se efeito inverso de Mn. As concentrações foliares de todos os nutrientes nos eucaliptos tratados com os biossólidos mantiveram-se dentro dos limites observados usualmente nas plantações comerciais, não havendo sinais de desequilíbrio nutricional.In Brazil, several municipalities are building waste treatment plants and in the future thousands of tons of sewage sludge will be generated. Sewage sludge is the waste left over after wastewater treatment and its disposal needs to be well planned, considering sanitary, environmental, economic and social implications. Sewage sludge (biosolids) is high in organic content and plant nutrient and could be applied as fertilizer in forest plantations. The aim of this research, conducted at the Experimental Station of Itatinga (University of São Paulo) was to evaluate the effects of increasing doses (10, 20 and 30 tons ha-1) of wet and dry biosolids(pellets), complemented with K and B, and applied to planting rows in experimental Eucalyptus grandis plots 1.5 years after seedling plantation. Trunk volume increased significantly regarding the eucalypt trees that received wet and dry sewage sludge, compared to the control treatment (no fertilization), and a similar growth of eucalypt trees that received full mineral fertilization. Regarding mineral nutrition, a positive correlation was observed between doses of biosolids and P, Ca, and Zn concentrations in the leaves, but a negative effect for Mn and biosolid dose. The foliar concentration of all the nutrients in the biosolid-treated eucalypt trees remained within the limits observed in commercial plantations, with no signs of nutritional imbalance.

Os delineamentos sistemáticos se destacam pela sua compacidade e abrangência e por permitir testar maior número de espaçamentos possíveis. No entanto, não é utilizado devido ao arranjo sistemático (não casualizado) das plantas e à alta sensibilidade para valores perdidos. O objetivo deste trabalho foi descrever o modelo geoestatístico e métodos associados de inferência no contexto de análise de experimentos não aleatorizados, reportando resultados aplicados para identificar a dependência espacial em um particular experimento em delineamento sistemático tipo leque de Eucalyptus dunnii. Também foram propostas, analisadas e comparadas diferentes alternativas para tratar dados faltantes que pudessem advir de falhas e, ou, mortalidade de plantas. Os dados foram analisados seguindo-se três modelos que diferiram, com co-variáveis, na forma de tratar os dados faltantes. Para cada um destes foi construído um semivariograma, com o ajuste de três modelos de função de correlação, sendo os parâmetros estimados pelo método de máxima verossimilhança e selecionados pelo critério de Akaike. Esses modelos, com e sem o componente espacial, foram comparados pelo teste da razão de verossimilhança. De acordo com os resultados, verificou-se que: (1) as co-variáveis interagiram positivamente com a variável de resposta, evitando que dados coletados sejam desperdiçados; (2) a comparação dos modelos, com e sem o componente espacial, não confirmou a existência de dependência; (3) a incorporação da estrutura de dependência espacial aos modelos observacionais recuperou a capacidade de fazer inferências válidas na ausência de aleatorização, permitindo contornar problemas operacionais e, assim, garantindo que os dados possam ser submetidos a uma análise clássica.The systematic design stands out for its compactness, broadness and for allowing the testing of a larger number of spacings. However, it is not used due to the systematic arrangement (non-randomized) of the plants and the high sensibility for missing values. The aim of this work was to describe the geostatistic model and associated methods of inference in the analysis context of non-randomized experiment, reporting applied results to identify the spatial dependence in a fan systematic design of Eucalyptus dunnii. Furthermore, different alternatives for treating missing values that can occur from flaws and/or mortality of plants were proposed, analyzed and compared. Data were analyzed by three models that differed, with covariates, in the form of modeling missing data values. A semivariogram was built for each model, adjusting three correlation function models, being the parameters estimated through the maximum likelihood method and selected by the Akaike's criterion. These models, with and without the spatial component, were compared by the likelihood ratio test. The results showed that: (1) the covariates interacted positively with the response variable, avoiding data to be discarded; (2) the model comparison, with and without the spatial component, did not confirm the existence of dependence; (3) the incorporation of the spatial dependence structure into the observational models recovered the capacity to make valid inferences in the absence of randomization, overcoming operational problems and guaranteeing that the data can be subjected to classic analysis.

Eucalyptus plantations cover extensive areas in tropical regions and require accurate growth monitoring for efficient management. Traditional in-situ measurements, while necessary, are labor-intensive and impractical for large-scale assessments. Very high-resolution satellite stereo imagery is playing an increasingly important role in the estimation of fine Digital Surface Models (DSMs) across landscapes. However, its ability to estimate canopy height models (CHMs) has not been widely investigated. This study investigates the integration of high-resolution satellite stereo imagery from the Pleiades sensor with airborne or satellite Lidar data to estimate canopy height over eucalyptus plantations. Two study sites were selected in Brazil, representing flat and semi-mountainous topographies, Mato Grosso do Sul (MS) and Sao Paulo (SP), respectively. Digital Surface Models generated from Pleiades images (DSMP) were combined with Digital Terrain Models extracted from airborne Lidar data (DTMALS) to create Canopy Height Models (CHMALS). The evaluation of the CHMALS was based on two in situ canopy height measurements (Hmax and Hmean). For the SP site, the CHMALSmax, which is the average height of top 10% pixel values within each plot, correlated well with in situ Hmean, which is the average height of 10 central trees (r = 0.98), showing a bias of 1.4 m, RMSE of 3.1 m, and rRMSE of 18.5%. At the MS site, CHMALSmax demonstrated a bias of 1.9 m, RMSE of 2.3 m, rRMSE of 17.3%, and r correlation of 0.92. Despite a tendency to underestimate heights below 20 m in young tree plantations with open canopy, the results indicate reliable canopy height estimation. The study also investigates the potential of Global Ecosystem Dynamics Investigation (GEDI) elevation data as an alternative to DTMALS in absence of airborne Lidar data. The resulting CHMGedi is promising but slightly less accurate than Lidar-based CHMs. The best GEDI-based CHM (CHMGedimax) showed a bias and rRMSE of 1.3 m and 20.5% for the SP site, and 2.2 m and 24.9% for the MS site. These findings highlight the potential for integrating Pleiades and Lidar data for efficient and accurate canopy height monitoring in eucalyptus plantations.

Over the past two decades spaceborne LiDAR systems have gained momentum in the remote sensing community with their ability to accurately estimate canopy heights and aboveground biomass. This article aims at using the most recent global ecosystem dynamics investigation (GEDI) LiDAR system data to estimate the stand-scale dominant heights (${{\boldsymbol{H}}_{{\rm{dom}}}}$), and stand volume (V) of Eucalyptus plantations in Brazil. These plantations provide a valuable case study due to the homogenous canopy cover and the availability of precise field measurements. Several linear and nonlinear regression models were used for the estimation of ${{\boldsymbol{H}}_{{\rm{dom}}}}$ and V based on several GEDI metrics. ${{\boldsymbol{H}}_{{\rm{dom}}}}$ and V estimation results showed that over low-slopped terrain the most accurate estimates of ${{\boldsymbol{H}}_{{\rm{dom}}}}$ and V were obtained using the stepwise regression, with an root-mean-square error (RMSE) of 1.33 m (R2 of 0.93) and 24.39 m3.ha−1 (R2 of 0.90) respectively. The principal metric explaining more than 87% and 84% of the variability (R2) of ${{\boldsymbol{H}}_{{\rm{dom}}}}$ and V was the metric representing the height above the ground at which 90% of the waveform energy occurs. Testing the postprocessed GEDI metric values issued from six available different processing algorithms showed that the accuracy on ${{\boldsymbol{H}}_{{\rm{dom}}}}$ and V estimates is algorithm dependent, with a 16% observed increase in RMSE on both variables using algorithm a5 vs. a1. Finally, the choice to select the ground return from the last detected mode or the stronger of the last two modes could also affect the ${H_{{\rm{dom}}}}$ estimation accuracy with 12 cm RMSE decrease using the latter.

The choice of initial spacing (stocking or density) for plantations influences the amount of growth resources available for each tree, rates of growth and survival, and the stand-level wood production and profit. A given number of trees per hectare can be arranged in various geometric ways, with designs varying the spacing between planting rows, and the distance between trees within rows. Large distances between rows lower costs of site preparation, but tight packing of trees within rows may limit light interception, leading to rapid forest stratification (into dominant and suppressed classes) and increasing risks of weed competition and wind damage. We evaluated the effects of spacing (m2 tree−1) and geometric layout (distances between rows, and between trees within rows) on the productivity of two Eucalyptus grandis x E. urophylla clones. A complete 2 × 3 × 3 factorial design was applied to two clones, with three spacing levels (6.0, 10.5 and 15.0 m² tree−1) and 3 between-row distances (3, 6, and 9 m). After 6 years, Clone 1 was 11% more productive (MAI 33.8 m³ ha−1 yr−1) than Clone 2 (MAI 30.5 m³ ha−1 yr−1), largely owing to greater wind damage of Clone 2 (especially at wide between-row spacings). The highest growth for both clones occurred at the densest spacing (6.0 m² tree−1), with a yield of 212 m³ ha−1. Greater spacing lowered stand yield by 10% (10.5 m² tree−1) to 18% (15.0 m² tree−1). Increasing distances between rows (coupled with decreasing distances between trees within rows) also decreased yields, dropping by 16% as between-row distance increased from 3 to 9 m. High densities of trees planted in a square design gave the greatest yields.

The Global Ecosystem Dynamics Investigation LiDAR (GEDI) is a new full waveform (FW) based LiDAR system that presents a new opportunity for the observation of forest structures globally. The backscattered GEDI signals, as all FW systems, are distorted by topographic conditions within their footprint, leading to uncertainties on the measured forest variables. In this study, we explore how well several approaches based on waveform metrics and ancillary digital elevation model (DEM) data perform on the estimation of stand dominant heights (Hdom) and wood volume (V) across different sites of Eucalyptus plantations with varying terrain slopes. In total, five models were assessed on their ability to estimate Hdom and four models for V. Results showed that the models using the GEDI metrics, such as the height at different energy quantiles with terrain data from the shuttle radar topography mission’s (SRTM) digital elevation model (DEM) were still dependent on the topographic slope. For Hdom, an RMSE increase of 14% was observed for data acquired over slopes higher than 20% in comparison to slopes between 10 and 20%. For V, a 74% increase in RMSE was reported between GEDI data acquired over slopes between 0–10% and those acquired over slopes higher than 10%. Next, a model relying on the height at different energy quantiles of the entire waveform (HTn) and the height at different energy quartiles of the bare ground waveform (HGn) was assessed. Two sets of the HGn metrics were generated, the first one was obtained using a simulated waveform representing the echo from a bare ground, while the second one relied on the actual ground return from the waveform by means of Gaussian fitting. Results showed that both the simulated and fitted models provide the most accurate estimates of Hdom and V for all slope ranges. The simulation-based model showed an RMSE that ranged between 1.39 and 1.66 m (between 26.76 and 39.26 m3·ha−1 for V) while the fitting-based method showed an RMSE that ranged between 1.26 and 1.34 m (between 26.78 and 36.29 m3·ha−1 for V). Moreover, the dependency of the GEDI metrics on slopes was greatly reduced using the two sets of metrics. As a conclusion, the effect of slopes on the 25-m GEDI footprints is rather low as the estimation on canopy heights from uncorrected waveforms degraded by a maximum of 1 m for slopes between 20 and 45%. Concerning the wood volume estimation, the effect of slopes was more pronounced, and a degradation on the accuracy (increased RMSE) of a maximum of 20 m3·ha−1 was observed for slopes between 20 and 45%.

The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called “EucVI”) which gave similar LAI retrieval results but in a simpler way. The R2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.