Precision and accuracy of sampling methods in thinned Pinus taeda L. stands

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 fixed-area, 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.

VOLUMETRIC MODELING OF Pinus taeda L. FROM ORBITAL IMAGES

This work aimed to investigate the potential of image-derived indices derived from Sentinel-2/MSI images in the volumetric modeling of a stand of Pinus taeda L. located in Bom Retiro, State of Santa Catarina. For this purpose, field data derived from a forest inventory were used, by the fixed area method and simple random sampling with an allocation of 18 circular plots of 400 m². The remotely located data comprised an orbital image from the Sentinel-2/MSI sensor. From this image, 14 average vegetation indices per plot were calculated. These indices were correlated with the volume by plot (m³ 0.04 ha-1) derived from the inventory. The indices with the best correlation for volume by plot (m³ 0.04 ha-1) were the Generalized Difference Vegetation Index (GDVI) and Adjusted Soil Vegetation Index (SAVI) with 0.39 and 0.36, respectively. The best regression model completed using these VIs estimated the volume by plot with R² controls of 0.9402 and Syx of 1.44%. The use of spectral indices generated from Sentinel-2/MSI sensor data enabled the volumetric estimate of the Pinus taeda L. stand, not revealing differences between the volume accumulated by forest inventory and by orbital images. However, it is worth pointing out that new tests be carried out on other forest species and with medium to high spatial resolution sensors.

EFEITO DA IDADE SOBRE O POLINÔMIO DO QUINTO GRAU PARA AFILAMENTO DE Pinus taeda L.

A forma dos troncos das árvores é um importante parâmetro de qualidade e necessária para calcular e estimar o volume dos troncos das árvores, contudo varia conforme uma série de fatores, entre eles a idade das árvores. O objetivo deste estudo é demonstrar o efeito da idade sobre os parâmetros do polinômio do quinto grau e, consequentemente, sobre a forma do tronco de árvores de Pinus taeda L., visando a formulação de funções de afilamento, que podem representar troncos de diferentes formas. Os dados são provenientes de 631 árvores, com idades variando de 4 a 31 anos, de diversos povoamentos florestais na região Meio Oeste do estado de Santa Catarina, Brasil. Foi ajustado e testado o polinômio do quinto grau sem qualquer alteração, e com seus coeficientes expressos como função linear da idade, por meio do procedimento PROC NLIN do aplicativo computacional SAS® OnDemand for Academics. O polinômio do quinto grau, com os coeficientes e ajustados como função linear da idade, apresentou o melhor desempenho estatístico, realismo biológico e conformidade com o conhecimento teórico sobre a forma dos troncos das árvores de Pinus taeda. Dessa forma, apenas uma equação de afilamento foi capaz de estimar diâmetros ao longo do tronco de árvores de diferentes formas, com precisão e exatidão.

Single-Step Genomic Analysis Increases the Accuracy of Within-Family Selection in a Clonally Replicated Population of Pinus taeda L.

The use of genomic markers in forest tree breeding is expected to improve the response to selection, especially within family. To evaluate the potential improvements from genotyping, we analyzed a large Pinus taeda L. clonal population (1,831 cloned individuals) tested in multiple environments. Of the total, 723 clones from five full-sib families were genotyped using 10,337 single-nucleotide polymorphism markers. Single-step models with genomic and pedigree-based relationships produced similar heritability estimates. Breeding value predictions were greatly improved with inclusion of genomic relationships, even when clonal replication was abundant. The improvement was limited to genotyped individuals and attributable to accounting for the Mendelian sampling effect. Reducing clonal replication by omitting data indicated that genotyping improved breeding values similar to clonal replication. Genomic selection predictive ability (masking phenotypes) was greater for stem straightness (0.68) than for growth traits (0.41 to 0.44). Predictive ability for a new full-sibling family was poorer than when full-sibling relationships were present between model training and validation sets. Species that are difficult to propagate clonally can use genotyping to improve within-family selection. Clonal testing combined with genotyping can produce breeding value accuracies adequate to graft selections directly into deployment orchards without progeny testing. Study Implications Genomic markers can improve the reliability of breeding values, resulting in a more confident ranking of individuals within families. For genotyped individuals, the improvements were comparable to clonal testing. Breeding programs for species that are difficult to propagate clonally should consider genotyping to replace or supplement clonal testing as a means to improve within-family selection. For genomic prediction of breeding values without phenotypes (genomic selection), a robust genetic relationship between model training and validation sets is required. The single-step model allows genotyping a subset of the population and is a straightforward extension of well-established methods.

Litterfall and Accumulated Nutrients in Pinus taeda Plantation and Native Forest in Southern Brazil

The dynamics of the production, chemical composition, and accumulated nutrients in litterfall are essential to understand the availability of nutrients and, consequently, possible gains in productivity in different forest types. Thus, the objective of the present study was to evaluate the litterfall and the accumulated nutrients in litterfall in a Pinus taeda plantation and native forest from southern Brazil. Two forest types: (i) an eight-year-old Pinus taeda L. plantation; and (ii) a native forest fragment, located in southern Brazil, were studied for four years. The monthly and annual litterfall production, chemical composition, accumulated nutrients, and nutrient use efficiency of the litterfall were evaluated. The Pinus taeda plantation showed higher values of leaves/needles litterfall and N, P, K, Ca and Mg use efficiency. This demonstrates that Pinus taeda plantations have a high production of needle biomass, which, in turn, has increased cell division, favoring the entry of these nutrients into the soil via decomposition. Our results show that total litterfall production did not significantly influence the accumulated nutrient and nutrient efficiency of litterfall, demonstrating that evaluating litterfall fractionation, such as leaves/needles, twigs and miscellaneous, is essential to understand the quantity and quality of litterfall and, thus, the nutrient cycling, which can contribute to possible silvicultural practices to be implemented, which can provide growth gains in forest types.

Prediction ability of genome-wide markers in Pinus taeda L. within and between population is affected by relatedness to the training population and trait genetic architecture

Genomic prediction has the potential to significantly increase the rate of genetic gain in tree breeding programs. In this study, a clonally replicated population (n = 2063) was used to train a genomic prediction model. The model was validated both within the training population and in a separate population (n = 451). The prediction abilities from random (20% vs. 80%) cross validation within the training population were 0.56 and 0.78 for height and stem form, respectively. Removal of all full-sib relatives within the training population resulted in ∼50% reduction in their genomic prediction ability for both traits. The average prediction ability for all 451 individual trees was 0.29 for height and 0.57 for stem form. The degree of genetic linkage (full sib family, half sib family, unrelated) between the training and validation sets had a strong impact on prediction ability for stem form but not for height. A dominant dwarfing allele, the first to be reported in a conifer species, was discovered via GWAS on linkage group 5 that conferred a 0.33 m mean height reduction. However, the QTL was family specific. The rapid decay of LD, large genome size, and inconsistencies in marker-QTL linkage phase suggest that large, diverse training populations are needed for genomic selection in Pinus taeda L.