Loblolly pine is an important managed tree species within the southeastern United States, and better understanding spatial patterns in its productivity has potential to contribute to both modeling and management of the species. Using recently-created pine management maps specific to Virginia and empirical relationships predicting pine LAI from the Landsat satellite, we conducted a statewide analysis of temporal patterns in stand-level southern pine leaf area index (LAI) following clear-cut and planting. Here, using 28 years of Landsat time-series data for 13,140 stands that were clear-cut between 2014-2017, we examined 1) when LAI peaked over the rotation, and 2) how LAI in each stand compared to a recommended fertilization threshold of 3.5 LAI. We found that, on average, winter LAI reached a maximum of 2.02., which can be approximately doubled to give a summer LAI of 4.04, and within stand peak occurred between years 13 and 15. We also found that around 45.8% of stands achieved an LAI value higher than 3.5: a fertilization threshold recommended for managed stands in Virginia. The dataset produced by our analysis will bolster information required for modeling loblolly pines as a plant functional type in regional land simulations, and the finding that most stands are below the recommended LAI fertilization threshold will fuel further management-motivated research. / Master of Science / Management of pines in the southeastern U.S. contributes to the region's economy and carbon sequestration potential. In this study, we used Virginia forest harvest maps to identify individual patches (stands) of pine forest which had each gone through a full harvest life cycle (rotation). With unique managed pine stands identified, we used satellite imagery to estimate growth of canopy leaf area over time within each stand, using a metric called leaf area index (LAI). We identified 13,140 separate stands, each with up to 28 years of available data. We took the first full-state census of areas of managed pines in Virginia, and their leaf area development. We acquired one LAI measurement from February of each year, for each stand in Virginia. Using February LAI for each of our stands, we found that an average stand in VA has a maximum winter LAI of 2.02 (meaning an approximate maximum summer LAI of 4.04), and that stands generally reached their peak LAI after around 14 years of growth. It is recommended, in VA, that a landowner fertilize their stand in the middle of a harvest rotation if summer peak LAI is under 3.5, at stand closure. We found that at ten years of stand age, 45.8% of stands were estimated to reach above this threshold. Since this study's dataset is the most comprehensive LAI dataset for managed pines in VA, it may be used to improve management outcomes as well as understand pine productivity for land surface modeling purposes.

CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A produção de borracha natural de seringueira (Hevea brasiliensis) é uma atividade estratégica para a economia nacional. O principal fator redutor da produtividade dessa atividade é a ocorrência de doenças no seringal. O nematoide de galhas (Meloidogyne exigua) é a principal doença radicular dessa cultura no Brasil e sua identificação antecipada permite um melhor manejo desta epidemia no seringal e a redução de seus prejuízos. O objetivo desse estudo foi identificar áreas com a ocorrência de M. exigua em seringais através do uso dos índices espectrais de vegetação - Índice de Vegetação por Diferença Normalizada (NDVI) e Índice de Razão Simples (RS) - gerados a partir de imagens da constelação de satélites RapidEye® (resolução de 5 metros). Seringais produtivos, com pelo menos 7 anos de plantio, em Minas Gerais (irrigado) e em Goiás (não irrigado) foram amostrados e georreferenciados na segunda metade do período das chuvas e as densidades de nematoides no solo, nas raízes e total foram estimadas. O seringal em Minas Gerais foi amostrado inicialmente seguindo as anormalidades evidenciadas pelo índice NDVI gerado através de imagens do satélite Landsat 8 (resolução de 30 metros). O seringal em Goiás foi amostrado aleatoriamente com o intuito de validar os resultados observados no seringal em Minas Gerais. Apesar de serem identificadas regressões significativas com o uso de imagens de alta resolução (RapidEye®) entre as variáveis densidades de nematoides e os índices espectrais de vegetação, nenhuma apresentou coeficiente de determinação (R2) superior a 0,31. A estatística descritiva do conjunto de dados de ambos os seringais não identificou diferenças entre as áreas para as densidades de nematoides encontradas nas raízes ou a densidade total, no entanto, a densidade de nematoides no solo foi aproximadamente 236% superior no seringal em Goiás, enquanto que ambos os índices neste seringal foram inferiores aos índices estimados para o seringal em Minas Gerais. Está diferença foi consequência da irrigação na área em Minas Gerais. As correlações de Pearson, Spearman e Kendall foram calculadas para as densidades de nematoides e os índices espectrais. As correlações entre a densidade de nematoides do seringal e o índice NDVI foram as que apresentaram os maiores coeficientes significativos para qualquer das correlações avaliadas. Através do índice NDVI é possível diferenciar um seringal não infestado de um seringal infestado pelo nematoide de galhas M. exigua. / The production of natural rubber from rubber trees (Hevea brasiliensis) is a strategic activity for Brazilian economy. The main factor reducing productivity of this activity is the occurrence of diseases in the rubber plantation. The root-knot nematode (Meloidogyne exigua) is the main root disease of this culture in Brazil and its early identification enables better management of its outbreak in orchards and the reduction of their losses. This study identified areas with the occurrence of M. exigua in rubber plantations through the use of spectral vegetation indices - Normalized Difference Vegetation Index (NDVI) and Simple Ratio Index (SR) - generated from images of the constellation RapidEye® satellites (5 meters resolution). Productive rubber plantations, at least 7 years old, in Minas Gerais (irrigated) and Goiás (non-irrigated) states were sampled and georeferenced in the second half of the rainny season and the quantities of nematodes in soil, roots and total were estimated. The rubber plantation in Minas Gerais was sampled initially following the abnormalities detected by the NDVI index generated through the images of Landsat 8 satellite (30 meters resolution). The rubber plantation in Goiás was sampled randomly to validate the results observed in the first rubber plantation (Minas Gerais). In spite of the identification of significant regressions with the use of high resolution images (RapidEye®) between the variables quantities of nematodes and spectral vegetation indices, none showed a coefficient of determination (R2) greater than 0.31. The descriptive statistics of the data set from both surveys did not identify differences in the quantities of nematodes found in the roots or the total quantity between the areas, however, the amount of nematodes in the soil was approximately 236% greater in Goiás rubber plantation, while both spectral vegetation indices (NDVI and SR) in this rubber plantation were lower than the indices estimated for the rubber plantation in Minas Gerais. This difference was a result of irrigation in the area in Minas Gerais. The correlations of Pearson, Spearman and Kendall were calculated between the densities of nematodes and the spectral vegetation indexes. The correlations between the amount of nematodes in rubber trees plantation and NDVI index showed the best significant coefficients for any of the correlations evaluated. Through the NDVI index it is possible to differentiate an infested rubber tree plantation from a non-infested rubber tree plantation by M. exigua root-knot nematode. / Tese (Doutorado)