Comportamento e variação de procedências de Corymbia citriodora em diferentes tipos de solos

The aim of this study was the selection of Corymbia citriodora provenances for three different kinds of soils occurring in Luiz Antônio Experimental Station, São Paulo, Brazil (Latossolo Vermelho, Areia Quartzosa and Latossolo Roxo). The provenance test was established in 1983, with ten Corymbia citriodora provenances and one Eucalyptus grandis as control, original from a seed production area. The trials were established in a random block design with 11 treatments, three repetition and square plots with 25 trees. In 2008, there were evaluations of height, diameter at breast height (DBH, 1.3 m), stem form and survival. Significant differences among soils and provenances were detected for the growth traits, stem form and survival in all those studied soils. Significant provenance and soil interactions were not detected. All provenances showed higher growth in height and DBH in Purple Latosol. The control had a higher growth rate in relation to highness, DBH and stem form than Corymbia citriodora provenances in all the studied soils, but it presented, generally, a lower survival rate than Corymbia citriodora provenances. Pederneiras (11) Corymbia citriodora provenance presented a higher performance in relation to highness and DBH in all kinds of soils, and Gilgandra (4) provenance, original from Australia, had the worst development. Therefore, Pederneiras (11) provenance is, therefore, the best choose for reforestations in all those studied soils.

Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data

We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Variação e parâmetros genéticos em teste de progênies de polinização livre de Peltophorum dubium (Sprengel) taubert em Luiz Antonio -SP

Intensive deforestation and forest fragmentation of the Brazilian forest biomes has contributed to increase the number of trees species under the risk of extinction. Peltophorum dubium (Sprengel) Taubert is one of these species. Some of its populations are being conserved ex situ by the Instituto Florestal de São Paulo through provenance and progeny tests. The aim of this study was to investigate the genetic variation and to estimate genetic parameters at age 24 years in a progeny test of P. dubium established in Luiz Antônio, São Paulo State, Brazil. The trial was established in a random block design, with six replications, five plants per plot and 18 open-pollinated progenies. Measured were: diameter at breast height (DBH), height and stem form. The genetic parameters heritability, genetic variation and effective population size were estimated. Significant genetic differences were observed only for DBH. This trait also presented a high coefficient of genetic variation (CV g=4.8%) and heritability, especially among progeny means (h m 2=0.6607). This indicates that DBH is the most indicated trait for selection in the population. The effective population size conserved ex situ in the test was estimated to be 38.9. Concerning genetic conservation, although the effective population size in the test is small, the values of the genetic variation and of the heritability indicate that the ex situ population has sufficient genetic variation and potential to respond to changes promoted by natural and artificial selection.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

Functional Redundancy and Complementarities of Seed Dispersal by the Last Neotropical Megafrugivores

Background: Functional redundancy has been debated largely in ecology and conservation, yet we lack detailed empirical studies on the roles of functionally similar species in ecosystem function. Large bodied frugivores may disperse similar plant species and have strong impact on plant recruitment in tropical forests. The two largest frugivores in the neotropics, tapirs (Tapirus terrestris) and muriquis (Brachyteles arachnoides) are potential candidates for functional redundancy on seed dispersal effectiveness. Here we provide a comparison of the quantitative, qualitative and spatial effects on seed dispersal by these megafrugivores in a continuous Brazilian Atlantic forest. Methodology/Principal Findings: We found a low overlap of plant species dispersed by both muriquis and tapirs. A group of 35 muriquis occupied an area of 850 ha and dispersed 5 times more plant species, and 13 times more seeds than 22 tapirs living in the same area. Muriquis dispersed 2.4 times more seeds in any random position than tapirs. This can be explained mainly because seed deposition by muriquis leaves less empty space than tapirs. However, tapirs are able to disperse larger seeds than muriquis and move them into sites not reached by primates, such as large forest gaps, open areas and fragments nearby. Based on published information we found 302 plant species that are dispersed by at least one of these megafrugivores in the Brazilian Atlantic forest. Conclusions/Significance: Our study showed that both megafrugivores play complementary rather than redundant roles as seed dispersers. Although tapirs disperse fewer seeds and species than muriquis, they disperse larger-seeded species and in places not used by primates. The selective extinction of these megafrugivores will change the spatial seed rain they generate and may have negative effects on the recruitment of several plant species, particularly those with large seeds that have muriquis and tapirs as the last living seed dispersers. © 2013 Bueno et al.

Water availability determines the richness and density of fig trees within Brazilian semideciduous forest landscapes

The success of fig trees in tropical ecosystems is evidenced by the great diversity (+750 species) and wide geographic distribution of the genus. We assessed the contribution of environmental variables on the species richness and density of fig trees in fragments of seasonal semideciduous forest (SSF) in Brazil. We assessed 20 forest fragments in three regions in Sao Paulo State, Brazil. Fig tree richness and density was estimated in rectangular plots, comprising 31.4 ha sampled. Both richness and fig tree density were linearly modeled as function of variables representing (1) fragment metrics, (2) forest structure, and (3) landscape metrics expressing water drainage in the fragments. Model selection was performed by comparing the AIC values (Akaike Information Criterion) and the relative weight of each model (wAIC). Both species richness and fig tree density were better explained by the water availability in the fragment (meter of streams/ha): wAICrichness = 0.45, wAICdensity = 0.96. The remaining variables related to anthropic perturbation and forest structure were of little weight in the models. The rainfall seasonality in SSF seems to select for both establishment strategies and morphological adaptations in the hemiepiphytic fig tree species. In the studied SSF, hemiepiphytes established at lower heights in their host trees than reported for fig trees in evergreen rainforests. Some hemiepiphytic fig species evolved superficial roots extending up to 100 m from their trunks, resulting in hectare-scale root zones that allow them to efficiently forage water and soil nutrients. The community of fig trees was robust to variation in forest structure and conservation level of SSF fragments, making this group of plants an important element for the functioning of seasonal tropical forests. © 2013 Elsevier Masson SAS. All rights reserved.

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach

Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. © 2013 Mokry et al.; licensee BioMed Central Ltd.

Mixing Eucalyptus and Acacia trees leads to fine root over-yielding and vertical segregation between species

The consequences of diversity on belowground processes are still poorly known in tropical forests. The distributions of very fine roots (diameter <1 mm) and fine roots (diameter <3 mm) were studied in a randomized block design close to the harvest age of fast-growing plantations. A replacement series was set up in Brazil with mono-specific Eucalyptus grandis (100E) and Acacia mangium (100A) stands and a mixture with the same stocking density and 50 % of each species (50A:50E). The total fine root (FR) biomass down to a depth of 2 m was about 27 % higher in 50A:50E than in 100A and 100E. Fine root over-yielding in 50A:50E resulted from a 72 % rise in E. grandis fine root biomass per tree relative to 100E, whereas A. mangium FR biomass per tree was 17 % lower than in 100A. Mixing A. mangium with E. grandis trees led to a drop in A. mangium FR biomass in the upper 50 cm of soil relative to 100A, partially balanced by a rise in deep soil layers. Our results highlight similarities in the effects of directional resources on leaf and FR distributions in the mixture, with A. mangium leaves below the E. grandis canopy and a low density of A. mangium fine roots in the resource-rich soil layers relative to monospecific stands. The vertical segregation of resource-absorbing organs did not lead to niche complementarity expected to increase the total biomass production. © 2012 Springer-Verlag Berlin Heidelberg.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Seasonal variation in leaf traits between congeneric savanna and forest trees in Central Brazil: Implications for forest expansion into savanna

The ecology of forest and savanna trees species will largely determine the structure and dynamics of the forest-savanna boundaries, but little is known about the constraints to leaf trait variation imposed by selective forces and evolutionary history during the process of savanna invasion by forest species. We compared seasonal patterns in leaf traits related to leaf structure, carbon assimilation, water, and nutrient relations in 10 congeneric species pairs, each containing one savanna species and one forest species. All individuals were growing in dystrophic oxisols in a fire-protected savanna of Central Brazil. We tested the hypothesis that forest species would be more constrained by seasonal drought and nutrient-poor soils than their savanna congeners. We also hypothesized that habitat, rather than phylogeny, would explain more of the interspecific variance in leaf traits of the studied species. We found that throughout the year forest trees had higher specific leaf area (SLA) but lower integrated water use efficiency than savanna trees. Forest and savanna species maintained similar values of predawn and midday leaf water potential along the year. Lower values were measured in the dry season. However, this was achieved by a stronger regulation of stomatal conductance and of CO2 assimilation on an area basis (A area) in forest trees, particularly toward the end of the dry season. Relative to savanna trees, forest trees maintained similar (P, K, Ca, and Mg) or slightly higher (N) leaf nutrient concentrations. For the majority of traits, more variance was explained by phylogeny, than by habitat of origin, with the exception of SLA, leaf N concentration, and A area, which were apparently subjected to different selective pressures in the savanna and forest environments. In conclusion, water shortage during extended droughts would be more limiting for forest trees than nutrient-poor soils. © 2013 Springer-Verlag Berlin Heidelberg.

Growth and carbon isotopes of Mediterranean trees reveal contrasting responses to increased carbon dioxide and drought

Forest dynamics will depend upon the physiological performance of individual tree species under more stressful conditions caused by climate change. In order to compare the idiosyncratic responses of Mediterranean tree species (Quercus faginea, Pinus nigra, Juniperus thurifera) coexisting in forests of central Spain, we evaluated the temporal changes in secondary growth (basal area increment; BAI) and intrinsic water-use efficiency (iWUE) during the last four decades, determined how coexisting species are responding to increases in atmospheric CO2 concentrations (Ca) and drought stress, and assessed the relationship among iWUE and growth during climatically contrasting years. All species increased their iWUE (ca. +15 to +21 %) between the 1970s and the 2000s. This increase was positively related to Ca for J. thurifera and to higher Ca and drought for Q. faginea and P. nigra. During climatically favourable years the study species either increased or maintained their growth at rising iWUE, suggesting a higher CO2 uptake. However, during unfavourable climatic years Q. faginea and especially P. nigra showed sharp declines in growth at enhanced iWUE, likely caused by a reduced stomatal conductance to save water under stressful dry conditions. In contrast, J. thurifera showed enhanced growth also during unfavourable years at increased iWUE, denoting a beneficial effect of Ca even under climatically harsh conditions. Our results reveal significant inter-specific differences in growth driven by alternative physiological responses to increasing drought stress. Thus, forest composition in the Mediterranean region might be altered due to contrasting capacities of coexisting tree species to withstand increasingly stressful conditions. © 2013 Springer-Verlag Berlin Heidelberg.