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The Brazilian Atlantic Rainforest presents great diversity of flora and stand structures, making it difficult for traditional forest inventories to collect reliable and recurrent information to classify forest succession stages. In recent years, remote sensing data have been explored to save time and effort in classifying successional forest stages. However, there is a need to understand if any of these sensors stand out for this purpose. Here, we evaluate the use of multispectral satellite data from four different platforms (CBERS-4A, Landsat-8/OLI, PlanetScope, and Sentinel-2) and airborne light detection and ranging (LiDAR) to classify three forest succession stages in a subtropical ombrophilous mixed forest located in southern Brazil. Different features extracted from multispectral and LiDAR data, such as spectral bands, vegetation indices, texture features, and the canopy height model (CHM) and LiDAR intensity, were explored using two conventional machine learning methods such as random trees (RT) and support vector machine (SVM). The statistically based maximum likelihood (MLC) algorithm was also compared. The classification accuracy was evaluated by generating a confusion matrix and calculating the kappa index and standard deviation based on field measurements and unmanned aerial vehicle (UAV) data. Our results show that the kappa index ranged from 0.48 to 0.95, depending on the chosen dataset and method. The best result was obtained using the SVM algorithm associated with spectral bands, CHM, LiDAR intensity, and vegetation indices, regardless of the sensor. Datasets with Landsat-8 or Sentinel-2 information performed better results than other optical sensors, which may be due to the higher intraclass variability and less spectral bands in CBERS-4A and PlanetScope data. We found that the height information derived from airborne LiDAR and its intensity combined with the multispectral data increased the classification accuracy. However, the results were also satisfactory when using only multispectral data. These results highlight the potential of using freely available satellite information and open-source software to optimize forest inventories and monitoring, enabling a better understanding of forest structure and potentially supporting forest management initiatives and environmental licensing programs. [ABSTRACT FROM AUTHOR]

Double-entry volume equations require measurement of diameter and height variables, making forest inventory more expensive. This can be limiting for small farms. Then the single-entry volume equations, where diameter at breast height (DBH) is the independent variable, are a cost-effective option for these landowners because they optimize data collection due to the use of one readily available variable (the DBH) and require few resources. The objective of this study was to evaluate the effective contribution of the height in the estimation of eucalypt trees volume for small-scale silvopastoral systems. For this, four single-entry and five double-entry volumetric models were fitted to the data for six different silvopastoral systems in Coronel Pacheco, Minas Gerais State, Brazil. The six strata consisted of combinations of three different Eucalyptus genetic material and three silvopastoral systems, and the models were compared aiming the selection of the best of each type in each system. Double-entry models, specifically logarithmic Spurr and logarithmic Schumacher–Hall, fitted better than single-entry ones for all but one of the strata, where they were overcome by the Husch's model. Although the superiority of the formers can have been easily verified by different and complementary statistics, we found that the volume estimates provided by the best double-entry and the best single-entry model of each stratum differed by a quantity that can be considered irrisory, from both practical and monetary points of view. On a per tree basis, the sum of the differences for each stratum, in absolute value, did not surpass 0.051 m3, or only US$ 0.25, considering a market value of US$ 4.90/m3. And when simulating a real scenario of batch sales for each stratum, by simple extrapolation of the mean volume and considering their effective tree stand, such differences did not exceed ± 0.25 m3/ha, or ± US$ 1.20/ha. Following the same logic, even when comparing the best double-entry model to the worst single-entry one for each stratum, we still observed only negligible differences. Considering the sampled trees, these differences amounted to a balance per stratum of only − 0.015 to + 0.032 m3 (or between − US$ 0.07 and + US$ 0.16). When extrapolated to the total trees in each stratum, the overall balance did not exceed an absolute value of 0.283 m3 (or US$1.39). These results suggest that the contribution of height may be negligible in estimating the volume of eucalyptus trees for small silvopastoral systems. Consequently, smallholders may not benefit from measuring tree heights. Rather, they may save money by foregoing a comprehensive forest inventory and instead using single-entry models, such as the Husch model, to estimate the wood volume of their forest stands. Another highlight or reinforcement of this work is that the use of the Furnival index was crucial for a reliable selection of the best models, once it allows for comparisons among models both with and without a log transformation of the volume. [ABSTRACT FROM AUTHOR]

In this study, we provide a checklist of the species of Odonata (Insecta) from the state of Santa Catarina (southern Brazil), along with their location records in the municipalities across the state (whenever possible). We compiled 147 species from 60 genera and nine families, making Santa Catarina the second state with the most Odonata species recorded in southern Brazil. The families with the highest number of species were Libellulidae (54 species from 18 genera), followed by Coenagrionidae (36 species from 17 genera), Gomphidae (20 species from ten genera) and Aeshnidae (15 species from eight genera). Several regions of Santa Catarina are unexplored (mostly the westernmost and central regions of the state), whereas the knowledge in the southern coast and the subtropical highland grasslands remains restricted to sparse occurrence records. Moreover, the distribution records in the state show an enormous historical track associated with the establishment of late entomologists in the region. Our study highlights the role of Atlantic Forest biome in maintaining high levels of diversity of Odonata species richness in Brazil and also shows that many areas in subtropical forests in Brazil are not adequately sampled. [ABSTRACT FROM AUTHOR]

The research proposes a model to estimate the carbon stock in mangrove forests from multispectral images from Landsat 8 and Sentinel 2B satellites. The Gramame River mangrove, located on the southern coast of Paraíba State, Brazil, was adopted as the study area. Carbon stocks in biomass, below and above ground, were measured from a forest inventory, and vegetation indices were processed on the Google Earth Engine (GEE) platform. To define the fit curves, linear and non-linear regressions were used. The choice of the model considered the highest coefficients of determination (R2), the biomass and carbon stock were estimated from the equations. The biomass carbon stock, calculated from field data, corresponded to 22.27 Gg C, equivalent to 81.75 Gg CO2, with 13.85 Gg C (50.84 Gg CO2) and 8.42 Gg C (30.91 Gg CO2) stored in biomass above and below ground, respectively. Among the models fitted to the indices calculated from Landsat 8 images, NDVI was the one that best explained the spatial distribution of biomass and carbon, with 90.26%. For Sentinel 2B, SAVI was able to explain 80.76%. The total estimated plant carbon stocks corresponded to 26.66 Gg (16.20 Gg C above and 10.36 Gg C below ground) for Landsat 8 and 27.76 Gg C (16.93 Gg C above and 10.83 Gg C below ground) for Sentinel 2B. The proposed work methodology and the suggested mathematical models can be replicated to analyze carbon stocks in other locations, especially in the Americas, because they share the same species. [ABSTRACT FROM AUTHOR]

Countries have pledged to different national and international environmental agreements, most prominently the climate change mitigation targets of the Paris Agreement. Accounting for carbon stocks and flows (fluxes) is essential for countries that have recently adopted the United Nations System of Environmental-Economic Accounting - ecosystem accounting framework (UNSEEA) as a global statistical standard. In this paper, we analyze how spatial carbon fluxes can be used in support of the UNSEEA carbon accounts in five case countries with available in-situ data. Using global multi-date biomass map products and other remotely sensed data, we mapped the 2010–2018 carbon fluxes in Brazil, the Netherlands, the Philippines, Sweden and the USA using National Forest Inventory (NFI) and local biomass maps from airborne LiDAR as reference data. We identified areas that are unsupported by the reference data within environmental feature space (6–47% of vegetated country area); cross-validated an ensemble machine learning (RMSE=9–39 Mg C ha - 1 and R 2 =0.16–0.71) used to map carbon fluxes with prediction intervals; and assessed spatially correlated residuals (<5 km) before aggregating carbon fluxes from 1-ha pixels to UNSEEA forest classes. The resulting carbon accounting tables revealed the net carbon sequestration in natural broadleaved forests. Both in plantations and in other woody vegetation ecosystems, emissions exceeded sequestration. Overall, our estimates align with FAO-Forest Resource Assessment and national studies with the largest deviations in Brazil and USA. These two countries used highly clustered reference data, where clustering caused uncertainty given the need to extrapolate to under-sampled areas. We finally provide recommendations to mitigate the effect of under-sampling and to better account for the uncertainties once carbon stocks and flows need to be aggregated in relatively smaller countries. These actions are timely given the global initiatives that aim to upscale UNSEEA carbon accounting. [ABSTRACT FROM AUTHOR]

In Brazil, forest inventory variation is calculated independently, and model-related uncertainty is systematically ignored. Although methods of estimation evaluation and sampling uncertainty together are unknown in the country, they are indispensable for improving the results of forest inventories since obtaining high quality estimates is extremely important for the country, due to its large forest areas and distinguished for being a world leader in the supply of timber and non-timber forest products, and a reference as a provider of environmental services. In view of the above, this paper presents the following study hypothesis: "Considering the uncertainty associated with inventory components: i - sampling and ii - regression model combined in the total variance of the forest inventory results in more accurate volume and biomass estimates" Thus, the aim of this study was to evaluate the uncertainties associated with sampling and the linear regression model in volume and biomass estimates in Acacia mearnsii stands in Brazil. To jointly evaluate these two sources of uncertainty, the hybrid variance estimator was used, with an analytical approach. The results showed that if model uncertainty is not considered, the total uncertainty is underestimated by 6.51%. In biomass estimates, the total uncertainty is underestimated by 18.74%. Ignoring uncertainty in total estimates can lead to uninformed decisions in forest management, with economic implications, particularly in biomass estimates, where the associated variation is even greater than in volume due to the nature of this variable. [ABSTRACT FROM AUTHOR]

Local inventories provide primary key information on diversity and distribution of species for conservation purposes. Here we describe the composition and conservation status of anuran fauna in flooded habitats eastern Amazon and evaluate to preference and the level of association of species with the flooded habitats in a poorly known area of the flooded forest present in the Ariri district, state of Amapá, North Brazil. Four nocturnal sampling events were carried out during the rainy season: beginning of the rainy season (March-May 2014 and December 2014-February 2015), mid rainy season (June-August 2014), and end of rainy season (September-November 2014), using visual encounter survey. We identified 29 anuran species. According to flooded habitat preference, the highest richness of species was found in high várzea (22 species, 75.9%, H' = 3.091), and 16 species (55.2%) was recorded with high association with flooded habitats. Including all flooded habitats, a greater number of constant species were found, followed by accessory and accidental species. Species accumulation curve showed a tendency toward stabilization of species richness only in the end of rainy season. Our study provides important data on the local anuran fauna and the presence of species typical of flooded and non-flooded habitats demonstrates a certain degree of similarity between species composition, reinforcing the importance of flooded habitats for the preservation of anurans of the Amazonia Forest in north Brazil. [ABSTRACT FROM AUTHOR]

This study used four surveys to capture perceptions of the current scenario of the forest sector and on the trends of the sector regarding human resources. The aim was to investigate the skills entailed by the profession from the viewpoint of professionals, taking into account job offers and the opinion of new college graduates. All surveys were analyzed using proportions and mean estimates. The first survey on forest organizations indicated a shortage of qualified professionals for the job market as well as a lack of training in behavioral skills (soft skills), pointed out by 100% of the organizations surveyed. We identified a gap between the importance given to certain skills and the performance of new college graduates in their academic training. Behavioral skills, such as communication, problem solving, leadership, and proactivity were considered of high importance; nevertheless, new graduates usually lacked these soft skills. In addition, a gap was identified in areas of knowledge not traditionally addressed in forest-engineering programs, such as REDD+ mechanisms, carbon market, and landscape management. The third and fourth surveys point to a convergence between job requirements from candidates and the responses of new graduates about the skills they consider important for their professional career. A three-line discussion is suggested, encompassing extension activities and professional experience in the academic world, bringing academia closer to job-market requirements, and including curriculum changes to follow current trends. [ABSTRACT FROM AUTHOR]

There is a great need to identify interactions among silvopastoral systems and microclimatic indicators that describe the effect of trees compared to conventional pasture systems without trees. The objective of this study was to evaluate thermal conditions in a silvopastoral system and a pasture area exposed to full sunlight in the eastern Amazon, Brazil. The silvopastoral system was composed of the forest tree species Bertholletia excelsa H.B.K., Dipteryx odorata (Aubl.) Willd, and Khaya grandifoliola C.DC.. During the monitoring period, a forest inventory was carried out that included 30 trees from each species for which thermal profiles were created using a high-precision thermographic camera. Near-infrared thermography showed a positive and direct correlation with dendrometric variables. Silvopastoral systems with K. grandifoliola reduced the heat profile the most compared to conditions in a pasture fully exposed to sunlight, which demonstrates the ecosystem service provided by trees for thermal regulation in these systems. The microclimatic conditions explain the greater presence of bovines in the silvopastoral system as they were most likely in search of the thermal comfort provided by the trees during the period of the highest daytime temperatures. The silvopastoral system benefits the caloric balance and thermal comfort of pasture animals. [ABSTRACT FROM AUTHOR]

Brazil is one of the world's wood short-fiber producers, cultivating 7.5 million hectares of eucalypt trees. Foresters and resource managers often face difficulties in surveying reliable Eucalyptus productivity levels for the purpose of purchasing and prospecting lands. Spatial data science (DS) and machine learning (ML) provide powerful approaches to make the best use of the large datasets available today. Agriculture has made great use of these approaches, and in this paper, we explore how forestry can benefit as well. We hypothesized that both DS and ML techniques can be used to improve Eucalyptus productivity zoning based on multiple operational datasets of tree growth and environment. Based on more than 12,000 permanent forest inventory plots of commercial Eucalyptus plantations and the climate, soil, and altitude variables associated with them, a supervised ML approach was adjusted to model the forest plantation productivity. A multi-tuning of the decision-tree (DT) algorithm hyperparameters was prepared to yield 450 DT models, with a better one delivering an RMSE of 53.5 m3 ha−1, split in 35 terminal nodes, here interpreted as Eucalyptus productivity zones. The DT model showed an optimum performance index of 0.83, a coefficient of determination of 0.91, a root mean squared error of 12.3 m3 ha−1, and a mean absolute percentage error only of 3.1% in predicting the testing dataset throughout the study area. The DT rule set was interpreted in a user-friendly table and was prepared to classify any location within the study area in each one of the 35 productivity zones based on the required environment variables of the DT algorithm. The high quality of the model obtained made it possible to spatialize the DT rules, providing a reliable cartographic visualization of the probability levels of true Eucalyptus productivity for a huge region of forest-based industries in Brazil. These data-science techniques also provided a yield gap analysis using a very down-to-earth approach. We estimated a yield gap by an amount of 4.2 × 107 m3, representing a few more than 113,000 ha, or 15% of the current forest base. This is the amount of avoided area expansion to accumulate the same wood stock in case the productivity is raised to the attainable level in each zone. This present study provided deeper analysis and reproducible tools to manage forest assets sustainably. [ABSTRACT FROM AUTHOR]

Araucaria angustifolia (Bertol.) Kuntze, commonly known as Brazilian pine, is a significant tree species in the Brazilian flora that once covered an area of 200,000 km2 in the Southern region. During the 1970s, high-quality timber logs from this conifer became the primary export product of the country. However, the species is endangered due to uncontrolled exploitation and is subject to a harvesting ban. It is crucial, therefore, to explore sustainable cultivation methods for this species, which necessitates urgent research and scientific insights. In this study, we present a simulation of a management strategy for in situ conservation by manipulating growth space and crown size dynamics. Forest inventory data and mixed forest regression equations were employed to describe the horizontal dimensions of average and maximum potential crown growth, resulting in two management scenarios. The results presented in management diagrams show that both approaches required logging numerous trees to ensure adequate space for healthy tree growth and provide soil coverage and forest protection. Therefore, the absence of effective forest management initiatives for Araucaria forests may have further implications for the structure, production, conservation, and overall development. To address these challenges, we propose two hypotheses: firstly, that tree diameter depends on crown dimensions, which are in turn influenced by tree growth space, and, secondly, that crown dimensions serve as a reliable indicator of existing competition and can be utilized to simulate forest management practices. We urge that implementing sustainable forest management initiatives for Araucaria angustifolia at selected locations can contribute to expanding natural forest areas, mitigate deterioration caused by high competition, discourage illegal logging, and prevent overexploitation of their edible seeds, which hinders regeneration. Our results underscore the significant implications of the lack of forest management initiatives in rural properties, potentially resulting in irreversible deterioration. The exact consequences of this deterioration remain unclear, emphasizing the need for further studies to understand its eventual effects on the growth reaction of trees of different diameters, ages, and crown conditions after the liberation of their crowns. [ABSTRACT FROM AUTHOR]

Amazonian biodiversity has been used for generations by human populations, especially by Indigenous peoples and traditional communities in their cultural, social and economic practices. However, forest degradation, driven by forest fires, has threatened the maintenance of these resources. This study examined the effects of recent forest fires on species with timber, non-timber and multiple-use potential in Brazil's state of Acre. Forest inventories in five forest types were analyzed, identifying species with timber, non-timber and multiple-use potential based on a review of existing scientific articles, books and studies in the technical literature. The indicators of the effect of forest fires on species density were based on the mean and standard deviation of tree density and absolute abundance. We found that 25% of the tree individuals have potential for use by humans, 12.6% for timber, 10.7% non-timber and 1.4% have multiple-use potential. With the negative impact of fire, the reduction in timber, non-timber and multiple-use potential can range from 2 to 100%, depending on the vegetation type and especially on the recurrence of fire. However, even in forests that are degraded by fire, species that are useful to humans can be maintained to a certain degree and contribute to other environmental services, thus they must be preserved. [ABSTRACT FROM AUTHOR]

Statement of problem. Brazilian guidelines establish a set of parameters to classify forest regeneration stages, but there are no criteria or evidence for prioritizing key indicators. Purpose. This study performed a comparative analysis between phytosociological parameters to verify the hypothesis that there is a difference in their explanatory power of the forest regeneration stages. Consequently, it shows the need to prioritize key indicators for classifying forest regeneration stages. Material and methods. The analyzes were carried out using a database of the Floristic Forest Inventory of Santa Catarina, Southern Brazil, composed of 177 sampling units of subtropical Atlantic forest (Mixed Ombrophilous Forest) characterized according to 12 quantitative and qualitative phytosociological parameters. Several statistical tests were performed to analyze the explanatory ability of the phytosociological parameters. Such process includes tests for multivariate ordering, principal component analysis (PCA), discriminant analysis (FDA and QDA), exploratory factor analysis (EFA), and multiple correspondence analysis (MCA). Afterward, is provided a ranking regarding the analyzed indicators based on their usefulness to separate forest regeneration stages, measured in terms of classification accuracy according to the QUEST (Quick Unbiased Efficient Statistical) algorithm. The hypothesis was verified with two-way tests at a significance level (α) equal to 0.05, for a test power (1-β) of 0.8 and a minimum detectable effect of medium size (ρ = 0.3). Results. Statistical significance tests confirmed the research hypothesis. Regarding both the qualitative and quantitative variables, the ranking resulting from the discriminant analysis provided the best accuracy (85.3%). In decreasing priority order, was defined the following parameter order: basal area, number of individuals and species, Shannon diversity index, diameter at breast height, total height, stem height, leaf litter, canopy structure, canopy cover, the density of lianas and epiphytes. Conclusions. The phytosociological parameters have statistically different explanatory power (p < 0.0001), which should be considered when classifying forest regeneration stages. Practical implications. The presented results and conclusions should substantially impact the guidelines and decision-making process for cutting down the forest/native vegetation and applicable compensation measures, which are currently only based on the forest regeneration stages. [ABSTRACT FROM AUTHOR]

The Eucalyptus genus is extensively planted in Brazil for industrial use, and with the expansion of forest frontiers and climate changes, studies are needed on how these changes affect wood density (WD). The aim of this study was to evaluate the effect of some climate variables on WD of an Eucalyptus urophylla clone for a 4–5 year period. WD from trees collected in 12 sites were evaluated. Five growth rings were identified using a magnifying glass, X-ray densitometry, and forest inventory. WD was correlated with temperature (T), precipitation (P), soil water deficit, ring width, and current annual increment. There was no variation in WD in the first 20 months among sites. From that age on, WD was mainly correlated with T (r > 0.6). The 1 °C increase in T resulted in a WD reduction of 0.014 g cm−1, and increases of 10 m³ ha−1 in the final volume were related to an increase of 0.004 g cm−1 in WD. Researchers and managers should continue to put efforts into broad experimental networks to assess the effects of climate change on the adaptation and wood quality of Eucalyptus clones. Highlights The influence of climate on E. urophylla wood density was greater after the third year of growth. The mean air temperature was the best correlated climatic variable with E. urophylla wood density. The cross-site climatic gradient was more important in wood density variation of E. urophylla than the variability among the years. [ABSTRACT FROM AUTHOR]

Euterpe edulis is an endangered palm species that provides the most important non-timber forest product exploited in its natural habitat, the Brazilian Atlantic Forest hotspot1,4. From 1991 to 2017, pasturelands, agriculture, and monoculture of tree plantations were responsible for 97% of Atlantic Forest deforested areas in Brazil and Santa Catarina was one of the Brazilian states with the greatest loss of forest area14. In the last decade, E. edulis fruits reached their highest commercial value, producing the southeastern equivalent of Amazonian "açai" (Euterpe oleracea)5,7,8. As a shade-tolerant species, E. edulis adapts very well to agroforestry systems8,10. To evaluate potential areas for cultivation of E. edulis through agroforestry systems, we developed and applied a spatial model for mapping suitable areas. To accomplish this, we analyzed multisource biophysical data and E. edulis distribution data from the Forest Inventory of Santa Catarina. We identified two areas with potential occurrence of the species, one in the domains of coastal Dense Ombrophilous Forest where the species is more common and another in the domains of inland Deciduous Seasonal Forest where its occurrence was suspected, but not proven, until 2021. Today, Deciduous Seasonal Forest is the most fragmented and impacted by agriculture. Our model, together with confirmed areas of occurrence, indicates that deciduous seasonal forest region should be prioritized for production and recovery of E. edulis through agroforestry systems. [ABSTRACT FROM AUTHOR]

This study aimed to indicate the ideal sample size for continuous forest inventories in the tropical forest in Amapá. Data were obtained from a monitoring inventory started in 2010 and completed in 2016, in five permanent sampling units of 100m x 100m with an inclusion level of DBH = 10cm. Randomly allocated sample subunits with five different dimensions ranging from 400 m2 to 1600 m2 were simulated within these units. The measurement times of each sampling unit, from the first to the last three, were timed. Dimensions were analyzed for their accuracy and relative efficiency. Given the above and depending on the purpose of the inventory, the standard sampling unit of 1 ha (100 m x 100 m) is recommended for the inventory variables. The 20 m x 20 m (400 m2) square sampling unit was the most suitable for monitoring growth variables (annual increment in diameter, basal area, and volume), indicating that these sampling units for continuous inventories can become an essential alternative for use in monitoring inventory in the region. [ABSTRACT FROM AUTHOR]

African mahogany plantations are increasing in Brazil, especially those planted with the species Khaya grandifoliola C. DC. Despite the interest in establishing plantations, there is a lack of studies in management practices for the genus. This makes it difficult to improve methodologies that optimise forest inventory activities, which are essential to support forest management decisions. Therefore, this study aimed to evaluate the effect of the number of trees selected to determine the mean dominant height, and to verify its impact on site classification of African mahogany stands. This will then optimise height sampling and ensure correct site index estimation. To determine the dominant height, 11 treatments were tested, with the selection of 1st to 11th thickest trees per plot, representing between 9 and 102 dominant trees per hectare. The effect of the treatments was evaluated using the values of the mean dominant height and metrics regarding site index classification (stability, stratification capacity and relationship with stand growth). Treatments with inclusion of more dominant trees resulted in a more stable site classification at the expense of a lower correlation with stand growth. Treatments using fewer dominant trees resulted in a greater allocation of plots in the upper site classes, showing that the number of trees used to calculate the dominant height influences the distribution of plots in different site classes. We concluded that Treatments 3 (27 trees ha−1) to 6 (55 trees ha−1) had the best performance, guaranteeing adequate site index estimation. The selection of at least 27 and a maximum of 55 dominant trees per hectare is recommended for African mahogany plantations with low planting densities. [ABSTRACT FROM AUTHOR]

The definition of strategies for forest restoration projects depends on information of the successional stage of the area to be restored. Usually, classification of the successional stage is carried out in the field using forest inventory campaigns. However, these campaigns are costly, time-consuming, and limited in terms of spatial coverage. Currently, forest inventories are being improved using 3D data obtained from remote sensing. The objective of this work was to estimate several parameters of interest for the classification of the successional stages of secondary vegetation areas using 3D digital aerial photogrammetry (DAP) data obtained from unmanned aerial vehicles (UAVs). A cost analysis was also carried out considering the costs of equipment and data collection, processing, and analysis. The study was carried out in southeastern Brazil in areas covered by secondary Atlantic Forest. Regression models were fit to estimate total height (h), diameter at breast height (dbh), and basal area (ba) of trees in 40 field inventory plots (0.09 ha each). The models were fit using traditional metrics based on heights derived from DAP and a portable laser scanner (PLS). The prediction models based on DAP data yielded a performance similar to models fit with LiDAR, with values of R² ranging from 88.3% to 94.0% and RMSE between 11.1% and 28.5%. Successional stage maps produced by DAP were compatible with the successional classes estimated in the 40 field plots. The results show that UAV photogrammetry metrics can be used to estimate h, dbh, and ba of secondary vegetation with an accuracy similar to that obtained from LiDAR. In addition to presenting the lowest cost, the estimates derived from DAP allowed for the classification of successional stages in the analyzed secondary forest areas. [ABSTRACT FROM AUTHOR]

Mammal richness, occurrence, diversity and uniformity were assessed in the northwest region of the Serra dos Toledos Biological Reserve, in the municipality of Itajubá, Minas Gerais State, Brazil. Richness was estimated via direct and indirect methods, and calculated using first- and second-order Jackknife. Shannon-Wiener and Simpson's diversity indices, as well as Pielou's evenness index, revealed a diverse environment, with values of 2.539, 0.8806 and 0.799, respectively. Interpretation of data on such diversity aspects indicated ecological heterogeneity in the mammals within the evaluated area. This survey identified 24 mammal species: 21 wild and three domestic; it allowed to draw an initial picture of the mammal diversity in this forest reserve, given the lack of published data on this fauna group in the region. To perform a survey of mammals in such environments, a larger sample effort and in larger area is more effective than in a representative area. Moreover, surveys on the geographic distribution of mammals in tropical forests are crucial when assessing conservation priorities in South America. The presence of humans and domestic mammal species recorded throughout the study reveals the fragility of this protected area; thus, monitoring and surveillance should be improved to prevent free movement of these individuals within this forest reserve. [ABSTRACT FROM AUTHOR]

This study aims to investigate the diametric structure of a seasonally dry tropical forest in Bahia and to select the best functions for the stand and species of greater importance. Two subsets were selected for fitting and validation from pre- and post-selective harvest inventories. Normal, Log-normal functions were tested; Gamma, Weibull 2P, and Weibull 3P. The best fits were selected using the Kolmogorov-Smirnov test for Akaike information criterion. Negative exponential curves and positive skewness best described the diameter distribution. This behavior was observed for the species with the highest IV and the stand. The Log-normal function best describes the diametric structure of Commiphora leptophioeeos, Manihot catingae, and Pataggonula bahiensis. It is recommended to individually describe the diameter structures of Aspidosperma pyrifolium, Pseudobombax simplicifolium, and population by the Weibull 3P function. The Normal, Gamma, and Weibull 2P functions did not present feasible predictions for frequencies of the diameter classes in all analyzed cases. [ABSTRACT FROM AUTHOR]

The Atlantic Forest of South America supports a rich terrestrial biodiversity but has been reduced to only a small extent of its original forest cover. It hosts a large number of endemic mammalian species but our knowledge of arboreal mammal ecology and conservation has been limited because of the challenges of observing arboreal species from ground level. Camera trapping has proven to be an effective tool in terrestrial mammal monitoring but the technique has rarely been used for arboreal species. For the first time in the Atlantic Forest, we obtained data on the arboreal mammal community using arboreal camera trapping, focusing on Caparaó National Park, Brazil. We placed 24 infrared camera traps in the forest canopy in seven areas within the Park, operating them continuously during January 2017–June 2019. During this period the camera traps accumulated 4,736 camera-days of footage and generated a total of 2,256 photographs and 30-s videos of vertebrates. The arboreal camera traps were able to detect arboreal mammals of a range of body sizes. The mammal assemblage comprised 15 identifiable species, including the Critically Endangered northern muriqui Brachyteles hypoxanthus and buffy-headed marmoset Callithrix flaviceps as well as other rare, nocturnal and inconspicuous species. We confirmed for the first time the occurrence of the thin-spined porcupine Chaetomys subspinosus in the Park. Species richness varied across survey areas and forest types. Our findings demonstrate the potential of arboreal camera trapping to inform conservation strategies. [ABSTRACT FROM AUTHOR]

In Brazil, most forest inventories by sampling use the fixed-area method, even though there are other alternatives methods developed since the 1940s. Research demonstrating the effectiveness of variable-area sampling methods is scarce, especially in forest plantations that advocate thinning throughout the production cycle. This study aimed to test different sampling methods of fixed (400 m² circular) and variable (Bitterlich and Strand) areas in a forest inventory in 9-year-old Pinus taeda L. plantations with 9 years without thinning and 14 years with thinning, comparing with the total enumeration of areas. The results obtained from the variables Number of Trees per hectare (N ha-1), Basal Area per hectare (G ha-1) and Volume per hectare (V ha-1) were submitted to a test of average comparison following a completely randomized design for each plantation and the differences observed were detected with the Scott-Knott test at 95% probability. It was evidenced that the Strand method presented greater accuracy for estimating all analyzed variables, especially in the area with thinning, however, it is necessary to increase the sampling intensity to guarantee precision in all cases. The fixed area method showed results consistent with the census for N ha-1 and presented overestimates in the area without thinning and underestimations in the area with thinning for Gha-1 and Vha-1. [ABSTRACT FROM AUTHOR]

Subject to overexploitation in the past centuries, the Atlantic Forest is subject to very rigorous protection rules. However, the law is a controversial issue since landowners are not compensated for the limited choice of land use possibilities. We believe that, alternatively to a general timber harvest ban, sustainable forest management of the Atlantic Forest has the potential to generate income for the landowners while sustaining important ecological functions of the forest. Such choice would require better understanding of the potential effects of timber harvesting on the forest ecosystem and on species composition and succession over time. In this context, we assessed the harvesting impact of a conventional harvesting method (CM) and compared it to an alternative harvesting method (AM) in three different stands (stands A, B and C) of a secondary forest fragment in southern Brazil. Results from three comprehensive forest inventories over a period of two years were used to assess the timber harvesting impact. Measurements of species composition (i.e., number of species, life form, ecological group), forest structure (i.e., density, basal area, DBH, volume) and saplings density formed the basis of the impact assessment. The inventories were carried out before, immediately after and two years after harvesting. Intensities of damage on remnant trees immediately after harvesting and two years after harvesting were also measured. Before harvesting, a total of 114 tree species (trees, tree fern and palm tree) belonging to 49 families were identified in the study site's three research stands. Palm trees and secondary species, such as Euterpe edulis, represented the majority of recruited individuals (DBH ≥ 5 cm) two years after harvesting. However, new saplings (DBH ≤ 5 cm) after two years were mainly pioneer woody tree species, such as Cecropia glaziovii and Schizolobium parahyba. On average, AM reduced damage to saplings by 5%. Most of the damages caused by CM were moderate to severe, while AM caused light to moderate damages. Binary logistic regression indicated dependency of the mortality rates on the independent variables "stand, stem and leaning damages." On the other hand, the recovery rates of damaged trees were dependent on crown, stem and leaning damages. Therefore, two years after harvesting a higher mortality rate of low-dimensional trees was observed in stands with high density of smaller trees and high density of improvement felling. Although crown damages were not related to mortality rates, high intensity of crown damages reduced recovery rates over time. [ABSTRACT FROM AUTHOR]

The helminth Echinococcus vogeli Rausch & Bernstein, 1972 is a causative agent of Neotropical Echinococcosis, a chronic zoonotic disease which is endemic to the Neotropical region. This parasite is transmitted from bush dogs (Speothos venaticus) to their prey, which include lowland pacas (Cuniculus paca) and agoutis (Dasyprocta spp.). In Brazil, most human cases of Neotropical Echinococcosis have been recorded in the Amazonian states of Acre and Pará, although few data are available on the occurrence of the potential definitive or intermediate hosts of E. vogeli in the Amazon region. In the present study, we surveyed the forests surrounding 46 human communities located within and around of outside six sustainable-use protected areas in the southwestern Amazon basin of Brazil. The forests were surveyed using camera traps to determine the local presence of potential wild hosts of E. vogeli, and the exploitation of these hosts for game meat was evaluated through interviews with 136 subsistence hunters resident in the local communities. We recorded pacas, agoutis, and bush dogs, as well as domestic dogs (Canis familiaris), all potential reservoirs of Neotropical Echinococcosis, using the same habitats. We also confirmed the frequent consumption of paca and agouti meat by subsistence hunters and their families in the study communities. Our data contribute to the understanding of the occurrence of E. vogeli in Brazilian ecosystems. [ABSTRACT FROM AUTHOR]

Forest plantations play an important role ecologically, contribute to carbon sequestration and support billions of dollars of economic activity each year through sustainable forest management and forest sector value chains. As the global demand for forest products and services increases, the marketplace is seeking more reliable data on forest plantations. Remote sensing technologies allied with machine learning, and most recently deep learning techniques, provide valuable data for inventorying forest plantations and related valuation products. In this work, deep semantic segmentation with U-net architecture was used to detect forest plantation areas using Sentinel-2 and CBERS-4A images of different areas of Brazil. First, the U-net models were built from an area of the Centre-East of Paraná State, and then the best models were tested in 3 new areas that present different characteristics. The U-net models built with Sentinel-2 images achieved promising results for areas similar to the ones used in the training set, with F1-score ranging from 0.9171 to 0.9499 and with Kappa values between 0.8712 to 0.9272, demonstrating the feasibility of deep semantic segmentation to detect forest plantations. [ABSTRACT FROM AUTHOR]

Southern Brazil's highland Araucaria Forest-Campos grassland mosaic is an ancient and iconic landscape in the globally important Atlantic Forest biodiversity hotspot. Human land use has inflicted significant losses on the region's natural vegetation since the late 19th Century, but these have not been effectively quantified. This study uses land cover maps and forest survey data to assess how much of the mosaic's natural vegetation remains, the quality of this remnant vegetation, how it has changed since 1985, and the extent to which it is protected. Natural vegetation covers 13.9–37.3 % of the Araucaria Forest-Campos mosaic's core regions and 13.0–38.0 % of the whole area, depending on the dataset. Most remnant areas are degraded and remaining forests have low average integrity. In only minorities of forest plots are the landscape's characteristic Araucaria angustifolia trees still present (23.5 % in the Araucaria Forest region), moderately abundant (11.4 %), or >50 % of the canopy (0.5 %). Major expansions in cropland and forest plantations between 1985 and 2018 drove net/absolute losses of 12.7 %/24.1 % in the mosaic's natural forest and 38.1 %/43.2 % in its natural grasslands. Protected Areas and Indigenous Territories cover 4.6 % of the core mosaic and 6.5 % of the whole region. These conserve important remnant vegetation, though grasslands are under-protected. By analysing and integrating diverse and complementary data sources, we significantly improve on and add nuance to previous estimates of the quantity and quality of Araucaria Forest remnants. This study also provides the first robust, quantitative estimate of remaining highland grassland across southern Brazil. [Display omitted] • Brazil's highland Araucaria Forest-Campos grassland mosaic is highly threatened. • Combining datasets gives key insights into both vegetation coverage and quality. • Natural vegetation covers 13–38 % of the whole mosaic and 14–37 % of its core regions. • Most remnant areas are degraded and remaining forests have low average integrity. • Campos grasslands are less protected and declining even more steeply than forests. [ABSTRACT FROM AUTHOR]

One of the most widely used tools for assessing the productive potential of planted Pinus taeda L. forests is to generate site index curves. Site index is a measure of the productive potential of forests and is influenced by various factors such as soil, water, light, among others, representing the relationship between the dominant height of trees and age at a specific location. This relationship produces a curve and can be used for site classification, consequently estimating the productivity of the forest stand. The objective of this study was to evaluate the performance of dynamic equations, the Algebraic Difference Approach (ADA), and its generalization (GADA). The data were obtained from permanent plots of Continuous Forest Inventory (CFI), collected in forest stands, through a sequence of annual remeasurements from 5 to 17 years of age. Dominant height was estimated as a function of age using nonlinear equations, and subsequently, the ADA and GADA methods were applied using the Chapman-Richards basic equation. The results of the GADA method provided a substantial reduction in the root mean square error (RMSE), less than half when compared to the traditional guide curve method, and an increase from 0.95 to 0.99 in R2 adj. Therefore, the GADA methodology proved to be suitable and efficient for site index classification, with noticeable flexibility and reliability on its estimates. • ADA and GADA were compared with the guide curve method for modeling site index curves. • The GADA method showed to be slightly better than ADA for modeling site index curves. • The GADA is a good method to evaluate site quality of planted forests of Pinus taeda L. • GADA and ADA provided more reliable estimates when compared to the guide curve method. • GADA is an effective and promising method for site index classification in Southern Brazil. [ABSTRACT FROM AUTHOR]

The Atlantic Forest is the most fragmented and threatened domain in Brazil. The main remnants are in the coastal regions. This paper describes a study performed at a protected federal reserve in Brazil located in western of São Paulo state, which is a transition with the Savannah. A forestry survey was made for understanding the forest structure, diversity, and floristic composition of an inland Atlantic Forest area. A total of 3,181 individuals with a Diameter at Breast Height over 3.5 cm were sampled. The data sample was composed of 29 families and 64 species from 15 plots. Forty-seven percent of the species were classified as a pioneer, 42% as secondary, and 11% as climax. The species Eugenia uniflora presented the highest importance value index. The values of Shannon-Weaver diversity and Pielou equitability index indicate the area has less diversity than others in the same phytophysiognomy and was dominated by a few species with many individuals. Several anthropogenic disturbances altered the forest cover of the Ponte Branca Forest remnant, which is in the process of secondary succession. [ABSTRACT FROM AUTHOR]

The large amount of degraded areas and productive potential of the legal reserves in Brazil make restoration an environmental demand and a commercial opportunity. We modelled the diameter growth as a function of age of eight tree species in restoration plantations in the Brazilian Amazon. From 14 years of annual forest inventory data, for each species, we tested variations of logistic function: simple logistic, logistic with covariant (plant area at the time of planting), logistic with random effect, logistic with random effect and covariant. Amongst the studied species, Schizolobium parahyba var. amazonicum, Tectona grandis and Simarouba amara showed the highest growth rates while Cordia alliodora, Cedrela odorata and three species of the genus Handroanthus showed slower growth. The gains from using the covariant in modeling were small for both fixed and mixed-effect models. Gains from the inclusion of the random effect were substantial. Mixed-effect models had the best performance in modeling the growth of the species. Our results provide basis for a critical view of the criteria and possibilities for degraded areas restoration and management practices in legal reserves of the Amazon. An economic analysis is required to ensure the viability of these areas' sustainable exploitation. [ABSTRACT FROM AUTHOR]

Different sampling methods can be used in forest surveys. It is important to know the precision and accuracy of these sampling methods, and which one is the most appropriate in specific conditions of the forest population. The aim of this study was to compare estimates of a forest inventory performed by different sampling methods with forest census results. The sampling methods evaluated were the fixed-area method and the variable-area methods of Bitterlich, Prodan, and Strand. The data were obtained in a 15-year-old thinned stand of Pinus taeda L., located in the municipality of Teixeira Soares, southern Brazil, with a total area of 12.80 ha. Initially, the forest census was carried out, and subsequently, the sample units for each sampling method were distributed in the stand, with a common starting point. The variables used to compare the sample results with the census means were quadratic diameter, number of trees, basal area, and volume, per hectare. Precision and accuracy were evaluated by sampling error and whether the confidence intervals covered the population means, respectively. The fixed-area and Bitterlich methods stood out in precision for all variables analysed. The fixedarea, Bitterlich and Strand methods with proportion to height provided more accurate estimates. The Prodan method provided inaccurate and imprecise estimates for the variables under analysis, except for the quadratic diameter. [ABSTRACT FROM AUTHOR]

Among amphibian species from high elevation areas in the Brazilian Atlantic Forest there is a high percentage of threatened and endemic species, but there is still a relative scarcity of local inventories for these organisms. Here, we present data on anuran composition, relative abundance and estimated densities for leaf-litter frogs from an Atlantic Forest area within the APA Serra da Mantiqueira, in Rio de Janeiro state, Brazil, based on results of a short-term survey carried out at altitudes of 1,350-1,750 m, in November 2005 (with additional records from surveys made in 2010 and 2011). Three sampling methods were used during the 2005 survey: plot sampling, visual encounter surveys (VES; performed during the day, at the dusk, and at night), and pitfall traps with drift fences; only non-standardized visual searches were employed during the 2010 and 2011 surveys. We recorded 24 species, with the direct-developer Ischnocnema sp. (gr. lactea) being the most abundant. Most anurans (90% of all individuals) sampled by VES were captured during the crepuscular and nocturnal periods. The estimated density of the local leaf-litter frog assemblage based on plot sampling was 18.4 ind/100 m2, which is one of the highest values currently reported for Atlantic Rainforest areas. This is the first study analyzing the anuran fauna composition of an Atlantic Forest area within the APA Serra da Mantiqueira and adds to the body of knowledge on the fauna of the southern region of Rio de Janeiro state. [ABSTRACT FROM AUTHOR]

Prediction of aboveground wood volume is one of most important stages when conducting a forest inventory and making forest management decisions. This is more difficult for native forest than for plantations given the high variability of the former (trees of different species and age groups). The objective of this work was to evaluate different strategies to estimate aboveground standing tree wood volume (v) using its diameter at breast height (DBH) and total height (h), comparing the use of form factors, volume equations fitted by ordinary least squares and mixed modelling, as well as the options from the literature. To achieve this, 351 trees were scaled during field campaigns, with 158 felled trees and 193 measured using Criterion equipment. The data collected from each scaled tree was: h, DBH, v and identification of the botanical species. We found that the best application of form factors occurred when the trees were divided by diameter classes. However, regression models, regardless of the fitting technique, presented better volume estimates than form factors. Mixed models, with either the species or diameter class as the random variable, provided the lowest errors when estimating tree volume. Thus, we recommend the use of mixed models as the best strategy to estimate volume of standing trees. The following equation can be used to estimate aboveground wood volume for trees from vegetation types similar to the ones of this study: ln(v) = −9.06013 + 1.91756 ln(DBH) + 0.69846 ln(h). [ABSTRACT FROM AUTHOR]

The severe deforestation of Brazil's Atlantic Forest and the increasing effects of climate change underscore the need to understand how tree species respond to climate and edaphic factors. To identify the most important environmental drivers of coastal Atlantic Forest diversity and functional composition, we studied 42 plots of coastal Atlantic Forest (restinga), which has a high diversity of plant communities and spans strong environmental gradients. We examined how forest physiognomy and functional composition respond to changes in the environment, hydraulic, and soil properties. We tested different hypotheses relating the roles of nutrients and soil water availability in driving shifts in tropical forest diversity and functioning. We collected wood samples and leaves from ˜85% of the plant species identified in the forest inventory and estimated the community‐weighted tree height, aboveground biomass, basal area of individual plants, specific leaf area, wood density, and the total tree biomass per community by the sum of all trees' aboveground biomass per plot. We measured water table depth and 24 physicochemical soil parameters. Hypotheses relating to these factors were formalized via both generalized additive models and piecewise structural equation models and null models of community assembly. Increasing drought, as reflected by increasing water table depth, coarse sand, and soil concentration of aluminum (>6 cmol/kg), was found to be a primary driver of shifts in all measured functional traits. Water table depth was found to be the main environmental driver of restinga species diversity, but shifts in species richness were largely decoupled from functional richness and functional dispersion. Our results suggest that decreases in soil water availability are a central driver of local phenotype–environment matching and that increasing water limitation increases the role of environmental filtering on multiple traits. Our results show that drought leads to a strong convergence (standardized effect size < −1.95) in forest function and leads to shifts to smaller statured forest in particular. These findings reveal important differences in the drivers of forest structure and functioning, suggesting that changes in local spatial variation in soil and moisture variables will be a central issue in restinga management and conservation. [ABSTRACT FROM AUTHOR]

The recent episodes of forest fires in Brazil and Australia of 2019 are tragic reminders of the hazards of forest fire. Globally incidents of forest fire events are on the rise due to human encroachment into the wilderness and climate change. Sikkim with a forest cover of more than 47%, suffers seasonal instances of frequent forest fire during the dry winter months. To address this issue, a GIS-aided and MaxEnt machine learning-based forest fire prediction map has been prepared using a forest fire inventory database and maps of environmental features. The study indicates that amongst the environmental features, climatic conditions and proximity to roads are the major determinants of forest fire. Model validation criteria like ROC curve, correlation coefficient, and Cohen's Kappa show a good predictive ability (AUC = 0.95, COR = 0.81, κ = 0.78). The outcomes of this study in the form of a forest fire prediction map can aid the stakeholders of the forest in taking informed mitigation measures. [ABSTRACT FROM AUTHOR]

The recovery of tree species composition after disturbance depends on dispersal either from nearby forests or from surviving individuals within the disturbed area. Understanding the influence of proximity to mature forests on species composition of regenerating secondary forests can help in predicting the trajectory of recovery from anthropogenic disturbances. Using forest inventory data from a chronosequence of regenerating secondary forests in the Atlantic Forest of southern Bahia, whereby transects were arranged from the edge of mature forest 100 m into the regenerating area, we calculated community weighted means (CWMs) for traits and the natural distribution ranges of species. We used Generalized Linear Mixed Models to investigate whether site characteristics such as forest age, distance from mature forest edge, soil chemical and physical properties, and canopy openness influence traits and natural distribution of regenerating secondary forest tree species. Results show that species traits were associated with regenerating forest age while the proportion of endemic and widespread species was associated with distance from mature forest and regenerating forest age. Irrespective of distance from mature forest, regenerating secondary forests recruit species with heavy and recalcitrant seeds, but this increased with regenerating forest age. Our results contribute to understanding the effects of forest fragmentation and in restoring forests after deforestation. [ABSTRACT FROM AUTHOR]

The Agroecological Zone Model-FAO (AZM) makes use of a physiological basis to estimate the potential productivity (Yp) and an empirical approach to simulate the effect of water deficit on attainable productivity (Ya). The Eucalyptus genus is the most planted in Brazil, with approximately six million hectares, commanding immense economic relevance for the country. Considering the importance of this forest species and the influence that weather conditions have on its growth, the aim of this study was to adapt, calibrate and evaluate the AZM to estimate Eucalyptus productivity for eight Brazilian clones. To accomplish this, forest inventory data from 23 trials and eight Eucalyptus clones (classified as plastic, tropical and subtropical) were obtained from different growing regions in Brazil, from 2011 to 2017. The calibration and adaptation of the model resulted in a significant improvement of its performance. The root-mean-square error was approximately 110 m3 ha−1 when not calibrated and 39 m3 ha−1 after calibration. The calibration also improved precision, with R2 going from 0.73 to 0.82, accuracy, with d index increasing from 0.70 to 0.93, and confidence, with c index going from weak (c = 0.59) to very good (c = 0.84). During the evaluation of the model with independent data, its performance was classified as great (c = 0.87). The AZM, adapted to the Eucalyptus forest, presented satisfactory performance for estimating Eucalyptus wood volume per hectare, representing a useful tool for all players in the forest sector. [ABSTRACT FROM AUTHOR]

We performed a process called SAR Interferometry (InSAR) to generate Digital Elevation Models (DEMs) from data pairs of the PALSAR-2 Synthetic Aperture Radar, from the ALOS-2 satellite. The pair of images used is a permutation between all acquired acquisitions of SAR data from ALOS-2, more precisely, we used data from two satellite passages (temporally spaced) in which the sensor was imaging the same area on the ground. There were PALSAR-2 L-Band Ultrafine images with an interval of 14 days between acquisitions (which is precisely the revisit time of the satellite) from two forest regions in the Paran´a state, Brazil. After the generation of the DEM, we observed a systematic error that generated a kind of very sharp ramp in the azimuthal direction. In this paper we present the followed steps and the investigation carried out to discover the causes of the error. We could observe that the satellite paths on the two dates suffer a relative displacement between them. In other words, this error occurs due to a non-constant baseline. This work was part of the R&D project of FAPESP (São Paulo State Research Support Foundation) entitled "Geração de inventários florestais a partir de um portfólio de soluções de sensoriamento remoto brasileiras de papel e celulose" (Generation of forest inventories from a portfolio of Brazilian remote sensing solutions for paper and cellulose) number "2017 / 25639- 5 - NRC - PIPE – Fase 2 Direta". [ABSTRACT FROM AUTHOR]

Past human societies have left persistent marks on forests worldwide. However, the degree to which pre-colonial Amerindian societies have affected forest structure is still not fully understood, especially in southern Brazil. This study investigated the influence of two distinct Amerindian groups (Southern-Jê and Guarani) over tree composition of forest fragments in the State of Santa Catarina. Vegetation data was obtained from the Santa Catarina Forest and Floristic Inventory (SCFFI): a statewide systematic vegetation sampling project. Archaeological data was collated from literature reviews as well as existing databases for archaeological sites occupied by Guarani and Southern-Jê groups. Using these sites of known Amerindian occupation, and corresponding environmental variables, ecological niche models were developed for each Amerindian group, predicting potential archaeological sites occupied by these groups across southern Brazil. Maps of these potential occupation sites of pre-colonial Amerindian groups were compared with 417 corresponding floristic inventory plots. Redundancy analysis (RDA) was used to identify floristic composition patterns linked to areas with a high probability of Southern-Jê or Guarani presence. Southern-Jê and Guarani pre-colonial occupations overlapped near main rivers; however, Southern-Jê groups generally occupied elevated areas whereas Guarani occupied mostly coastal areas. We observed differences in forest composition associated with the predicted occurrence of these pre-colonial Amerindian groups. Based on these results, we argue there is a relationship between tree species distribution and pre-colonial human occupation by these two Amerindian groups. [ABSTRACT FROM AUTHOR]

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Aims Natural vegetation plays an important role in global carbon cycling and storage. Thus, the Cerrado (Brazilian savannah) is considered a carbon sink because of its intrinsic characteristics. Our aim was to evaluate how the aboveground biomass and biodiversity relationship change between three Cerrado remnants with different protection status: a 'control area' (Legal Reserve area), a protected area (PA) and a non-protected area (Non-PA). Methods All three studied fragments are situated in northern Minas Gerais state, Brazil. We estimated the aboveground carbon stocks based on the forest inventory. We also measured three dimensions of biodiversity metrics for each plot: functional trait dominance, taxonomic diversity and functional diversity. The following functional traits were evaluated for the species: wood density, maximum diameter and seed size. We carried out generalized linear models seeking to evaluate how carbon stocks, community-weighted mean (CWM) trait values, species richness and diversity, and functional diversity indices differ among the remnants. Important Findings The Cerrado areas without protection status had lower carbon stocks, species richness, species diversity, functional richness and functional dispersion, whereas both PA and Non-PA had lower CWM maximum diameter and seed size compared with the Legal Reserve control area. Generalized linear models showed that carbon stocks, species and functional richness metrics were correlated within and across sites, and thus, species richness could serve as a good proxy for functional richness and carbon stocks. The carbon stocks were positively driven by species richness and CWM maximum diameter, while they were negatively driven by functional dispersion. Functional richness, species diversity and CWM seed size appeared in the set of best models, but with no significant direct effect on carbon stocks. Thus, we concluded that absence of protection in the Cerrado areas decreases both species richness and carbon stocks. [ABSTRACT FROM AUTHOR]

The development of forest science had a great impulse after the transference of the Faculty of Forest, in 1964, from Viçosa to Curitiba. Maack was a pioneer and relevant character for knowledge about the forests of Parana, especially about Araucaria angustifolia. The forest inventory of Parana-Pine was a decisive milestone to make Parana and Brazilian authorities aware of the need to improve public policies to boost and conserve forest remnants in the south of the country. The creation of the Forest Research Center - FRC in 1968 signaled to the professors of the Forest College about the importance of doing good research. From this frame of reference, the scientific contributions produced by all areas of knowledge began, specifically in Silviculture, Forest Management, Wood and Forest Products Technology, Nature Conservation, and Economy, Administration and Forest Policy. In 1971, the Parana Forest Research Foundation - FUPEF was created. The interaction of UFPR's forestry courses, undergraduate and graduate, with the productive sectors resulted from the awareness of working together, as they understood that scientific and technological research must contribute to the qualitative development of Brazilian forest production. In the last 45 years, 475 projects and agreements have been developed as a result of this interaction. The major milestone for the consolidation of forestry research in the country was the signing of the Technical Cooperation Agreement between UFPR and the Albert-Ludwig University of Freiburg, Germany in 1970. During this period, there was an effective development in forest teaching, research and extension, including the creation of the first Master's Program in Forest Engineering in 1972 and the first Doctor's Program in 1982 in Brazil. As a result of this important cooperation, in the last 47 years, 806 masters and 494 doctors have completed their dissertations and thesis, totaling 1300 graduates, the most significant graduate education in the field of Agrarian Sciences in the country. The Journal Floresta, created with the objective of disseminating the scientific production of our professors and other researchers in the country, has published, in the last 50 years, 1606 papers produced by 1024 authors. The extraordinary advances that have been made in the country's forest base over the last 50 years have caused us joy. We can not know how much of us are in these results, but we are aware that our work and our scientific contributions have helped to build this reality. [ABSTRACT FROM AUTHOR]

Legislation governing strict-protection nature reserves in Brazil in principle precludes human habitation, but virtually all Amazon reserves are nonetheless inhabited. Historical ecology research reported herein assesses the impacts of occupation and resource use by beiradeiros (forest peasants) on the forests of a strictly designated nature reserve in the Iriri River basin (Brazilian Amazon). The hypothesis is that traditional beiradeiros activities are congruent with the aims of conservation of the reserve because their impacts are either neutral or enhance diversity of forest landscapes and biota. We designed the methodology underlying data collection to integrate forest inventory with archaeological techniques in two contrasting forest types (terra firme and seasonally inundated forest), faunal surveys, freelisting of tree terms by beiradeiros, and participant observation, in order to determine biological diversity indices, forest age and the parameters of traditional knowledge that encode such diversity in local vocabulary. Our research results lead us to reject the premise that traditional peasant activities lead to ecological degradation or impoverishment, and suggest that the rationale underpinning strictly protected nature reserves should be re-examined. [ABSTRACT FROM AUTHOR]

Question: How do biotic forest conditions, in terms of plant functional traits and tree basal area, and soil variables influence old‐growth forest dynamics? Location: A subtropical old‐growth forest in Southern Brazil. Methods: Forest inventories were conducted in 1999 and 2017, in 24 permanent plots of 500 m2. All trees with a circumference at breast height of ≥ 30 cm were measured, identified to the species level, and tagged. We fitted linear models to evaluate the effect of the biotic variables of initial forest communities (tree basal area, trait community‐weighted mean [CWM] and both species and functional diversity metrics) and of soil variables on forest dynamics. These models included biomass dynamics (annual rate of biomass increment and mortality) and demographic rates (recruitment and mortality rates). Furthermore, linear models were used to evaluate the effect of tree survival, recruitment and mortality and biomass increment on the net biomass change. Results: We observed a positive effect of species diversity and a negative effect of CWM leaf phosphorus content on the biomass increment. Biomass loss was positively related to basal area and negatively related to the CWM of leaf nitrogen content. Overall, net biomass change was negatively influenced by biomass loss due to mortality. Recruitment rates were negatively affected by soil potassium content and were positively affected by soil pH and functional evenness of the community. Mortality rates were positively predicted by soil clay content and negatively predicted by species diversity. Conclusions: Community functional traits, basal area and soil variables predicted growth, mortality and recruitment dynamics of this subtropical old‐growth forest. This work provides important information about the biomass and demographic dynamics of subtropical forests, showing that initial community characteristics influence the gain and loss of biomass and individuals over a period of almost two decades. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore methods to: (1) enhance coarse-scale estimates of wood volume from National Forest Inventories (NFIs) data and (2) map them at finer scales. The 'standard' coarse-scale estimation extrapolates wood volume from clusters to the grid cell they represent, using the cluster's represented forested area (RFA) to predict the cell's forested area. Data from a subset of Brazil's NFI clusters were combined with Landsat-8 imagery to explore a new coarse-scale method, where forested area derived from image classification (FADIC) is used instead of RFA. The RFA- and FADIC-derived estimates of total volume were, respectively, 197.4 million m3 and 116.3 million m3. For fine-scale methods, volume was estimated and mapped at pixel level using: (i) surface reflectance-based models (SRMs), and (ii) regression-kriging (RK) and a RK model (RKM) whose inputs were latitude and longitude of pixels. The SRM-based method captured the mean and the general spatial trend of the volume well. The RK-based method also estimated the mean well, but it failed to predict higher and lower volumes. The SRM- and RK-based estimates of total volume were 211.7 million m3 and 203.3 million m3, an overestimate of 7 per cent and 3 per cent, respectively, of the 'standard' NFI estimate (197.4 million m3), though both estimates were within the 95 per cent confidence interval, meaning that both fine-scale methods yield total volume statistically similar to the 'standard' coarse-scale method. [ABSTRACT FROM AUTHOR]

The objective of this work was to evaluate the adjustment of taper models with and without bark for clone GG100 in a commercial plantation located in the southern state of Tocantins. Twenty-five trees were cubed in which data were fitted five taper models, three of which were the most used in Brazil and two representing the poorly tested models in the country. In the evaluation of the taper models, the following statistical criteria were adopted: standard error of the estimate, adjusted coefficient of determination, mean deviation, sum of squares of the relative residue, percentage residue, and analysis of the distribution of residues. It was concluded by an exponent-shape type model to describe the trunk profile with and without bark of individual clones of clone GG100. [ABSTRACT FROM AUTHOR]

Background Ecotone has been defined as "a multi-dimensional environmentally stochastic interaction zone between ecological systems with characteristics defined in space and time, and by the strength of the interaction" (Hufkens et al. 2009). This is a known concept to define transitional zones between two or more ecological communities, ecosystems or biotic regions. Ecotone forests, dispersed in northern Brazilian Amazonia, are natural formations which have been largely affected by anthropogenic impacts, such as deforestation and fire. Maracá Ecological Station, State of Roraima, Brazil, is a protected area with extensive representations of ecotone forests in this region of the Amazonia. Forest inventories and floristic surveys are important as they extend our knowledge (1) of forest structure and tree species composition and (2) of tree and palm species ecology in this region of the Amazonia. Both improve our ability to predict changes in plant diversity, considering the future scenarios of climate change in comparison with previous surveys performed in Maracá. New information We present a forest inventory carried out in 129 plots (10 m x 50 m; 6.45 ha in total) dispersed in a grid (5 km x 5 km) located in a forest zone ecotone in the eastern part of Maracá Ecological Station. All stems (tree + palm) with diameter at breast height = 10 cm were recorded, identified and measured. A total of 3040 stems were recorded (tree = 2815; palm = 225), corresponding to 42 botanic families and 140 identified species. Seven families and 20 genera contained unidentified taxa (12.2%). Sapotaceae (735 stems; 10 species), Leguminosae (409; 24) and Rubiaceae (289; 12) were the most abundant families. Peltogyne gracilipes Ducke (Leguminosae), Pradosia surinamensis (Eyma) T.D.Penn. (Sapotaceae) and Ecclinusa guianensis Eyma (Sapotaceae) were the species with the highest importance value index (~ 25%). The dominance (m ha) of these species corresponds to > 36% of the total value observed in the forest inventory. Our dataset provides complementary floristic and structure information on tree and palm in Maracá, improving our knowledge of this Amazonian ecotone forest. [ABSTRACT FROM AUTHOR]

Anthropogenic land expansion, particularly urbanization, is pervasive, dramatically modifies the environment and is a major threat to wildlife with its associated environmental stressors. Urban remnant vegetation can help mitigate these impacts and could be vital for species unable to survive in harsh urban environments. Although resembling nonurban habitats, urban vegetation remnants are subject to additional environmental stresses. Here, we evaluate the occurrence and density of the endemic ghost butterfly (Morpho epistrophus nikolajewna) that was once common, in the highly fragmented Atlantic forest of NE Brazil. We tested whether this butterfly would be found at lower densities in urban forest fragments of contrasting sizes as opposed to rural ones, given the number of environmental stressors found in urban areas. We surveyed 14 forest fragments (range 2.8 to over 3,000 ha) of semideciduous Atlantic forest in rural and urban locations using transect based distance sampling. The ghost butterflies showed strong seasonality; flying only from April to June. They were only identified in an urban fragment (515 ha), with an estimate of 720 individuals and a density 1.4 ind/ha. All forest fragments had experienced some level of logging in the past, which might have had an effect in the butterfly population. Nevertheless, rural forest fragments were subject to increased particulate matter concentrations, associated to biomass burning that we suggest might have had a more influential role driving the collapse of rural populations. Our findings show the importance of urban forest remnants to sustain population of this endangered species. [ABSTRACT FROM AUTHOR]

• Climatic water deficit included in basal area modeling is recommended for Brazil. • G & Y system that accounts for water availability displays reduced bias in volume estimation. • The new type of G & Y system enables the generation of site-specific curves. • The new type of G & Y system allows for testing environment × genotype interaction. • The new type of G & Y system is simple to use and implement. Growth and yield (G &Y) model systems aim at forecasting forest productivity. The lack of environmental variables to account for how water availability constrains eucalyptus production in Brazil, however, is argued to be a major drawback of these model systems. Thus, this study aimed to develop a stand-level G & Y model system that accounts for water availability (G & Y with SWD), highlighting its usefulness when applied for clonal eucalypt stands under drier climatic conditions. The dataset is composed of remeasurement information of sixteen research sites that span all climatic regions in Brazil. A total of eleven eucalypt clones were planted in single block plots at each site, and extra replications under the rainfall exclusion system were also installed for these eleven clones in fourteen sites. Linear algebra techniques were used to simultaneously fit a compatible set of prediction and projection basal area equations. A stand-level volume equation was also developed. These equations were validated through the use of an independent dataset composed of the rainfall exclusion plots. Finally, the accuracy and usefulness of a conventional G & Y model system applied to clonal eucalypt stands in Brazil was compared to the new proposed G & Y model system, which accounts for the impact of water availability in eucalyptus productivity. The prediction and projection basal area equations accounting for water availability displayed estimates in the order of 5% more accurate compared to the conventional basal area modeling. Stand-level volume estimates were 40% and 74% less biased through the use of the new G & Y model system. This result highlighted how useful and powerful the newly developed approach is, since the model system was capable to provide accurate estimates through the use of the rainfall exclusion plots. The new G & Y model system is a powerful alternative to estimate forest afforestation yield and is fully capable to accurately update forest inventories. The model system can also be used for projecting how forest growth may be impacted by short-term climate variation. [ABSTRACT FROM AUTHOR]

The present study aimed to verify if important biological data are being lost in a well-sampled region due to areas neglected by most biodiversity surveys. We performed a floristic and structural survey of an Atlantic Forest located at the bottom of an escarpment, in the southern region of the state of Minas Gerais, Brazil. A total of 19 plots of 400 m2 were allocated, totaling 0.76 ha of sampled area. All arboreal individuals with a diameter at breast height equal to or greater than 5 cm were sampled. We also collected surface soil samples for analysis. In order to evaluate the influence of edaphic factors and scarp on the tree community, a canonical correspondence analysis was performed. In order to analyze whether the studied forest is similar to or distinct from the rest of the region, a detrended correspondence analysis was carried out with 15 Atlantic Forest surveys located in the surroundings of the study area. The high floristic diversity and the structural variations found in the studied forest were attributed to the environmental heterogeneity due to the influences of the escarpment and the variations in the soil conditions, resulting in a forest with its own floristic composition and structure. The study suggested that important biological data are being lost in biodiversity surveys, even in well-sampled areas, due to neglected areas of difficult access. Thus, it is important the inclusion of these neglected sites in biodiversity inventories. [ABSTRACT FROM AUTHOR]

Abstract Southern Brazil's highland Araucaria forest is ancient, diverse and unique, but its future is under significant threat from 20th Century habitat loss and 21st Century climate change. Paleoecological studies have revealed that it expanded rapidly over highland grasslands around 1000 years ago, but whether this expansion was caused by human land use or climate change has been a topic of considerable debate. Discriminating between these potential drivers has so far not been possible with fossil pollen, however, as the palynological representation of floristic and structural differences in Araucaria forest remains poorly understood. Here, we address this shortcoming using modern pollen rain from moss polsters and vegetation surveys in forest areas with minimal current human disturbance. We show that forest plots with evident structural differences lack consistent differences in their floristic composition and cannot be reliably distinguished by their pollen spectra. We quantify pollen–vegetation relationships for 27 key tree genera of Araucaria forest, showing that, despite significant intra-taxon variability, 22 of these are under-represented or absent in the pollen record. These palynologically under-represented and silent taxa include many of the forest's most ecologically important tree species, with only Araucaria, Lamanonia , Podocarpus , Myrsine and Clethra being more abundant in the pollen rain than vegetation. Our results suggest that subtle structural changes in Araucaria forest, as well as moderate to significant floristic changes, may not be clearly distinguished in fossil pollen records – an important limitation when attempting to identify past human and climatic impacts on Araucaria forest via pollen analysis. Highlights • The first quantitative pollen–vegetation study in Brazil's Araucaria forest • Of the 27 key tree taxa examined, 22 are under-represented in modern pollen rain. • Structurally different Araucaria forest plots produce similar pollen spectra. • These findings have clear implications for the reconstruction of the forest's past. [ABSTRACT FROM AUTHOR]