Terrestrial ecosystems provide a substantial carbon sink that helps mitigate climate change, sequestering roughly 30% of anthropogenic carbon emissions annually. However, the long-term future of this sink is not well understood. In this dissertation, I use satellite remote sensing, in-situ measurements, and models to improve understanding of the nature and magnitude of spatial and temporal variation in the primary productivity of Eastern Deciduous Forests of the United States. In my first research chapter, I use remote sensing to model to the phenology of two key variables that control forest productivity: leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (fAPAR). Results show that the relationship between remotely sensed vegetation indices and both LAI and fAPAR is strongly influenced by systematic variation in near infrared reflectance arising from seasonal changes in canopy shadow fraction that are independent of physical changes in forest canopy properties. In my second research chapter, I use estimates of gross primary production (GPP) derived from eddy covariance measurements at four temperate deciduous sites to model the phenology and controls on light use efficiency (LUE) within and across sites. Results show that multiple modes of variation in incoming radiation dominate daily and seasonal variation in LUE, and provide a refined basis for understanding how variability in environmental controls affect LUE and how the strength of these drivers change throughout the growing season. In my third research chapter, I use the long-term record of Landsat imagery, in-situ phenological observations, and estimates of GPP derived from eddy covariance measurements at two temperate deciduous forest sites to investigate how phenology controls interannual variability in GPP at these sites. Results demonstrate that phenology metrics derived from remote sensing are consistent with in-situ measurements, and that interaction between the timing of growing season anomalies and incoming radiation explains a significant proportion of interannual variation in GPP. Taken together, results from this dissertation demonstrate how variation in phenology and LUE control variation in deciduous forest productivity, which is essential for reducing uncertainty in how future climate changes will impact the carbon budget of deciduous forest ecosystems.

Leaf traits have long been used to classify and characterise species in natural ecosystems. In addition, leaf traits provide important information about plants’ strategies for the use of resources and can be used to improve our understanding of ecosystem level processes such as nutrient cycling and carbon allocation. To explore the linkages between leaf traits and productivity, we worked in two resource-limited ecosystems (a grassland and a forest), and used leaf traits to understand how species respond to changes in available resources and their relationship to ecosystem processes. We worked in a species rich limestone-grassland located in central England, which has been subjected to long-term climatic manipulation (winter warming, summer drought and extra summer rainfall). We characterised species composition in terms of their identity, abundance and leaf structural properties (nitrogen content and leaf mass per area (LMA)) in the main treatments and the control. We found that change in species abundance was the most important factor to understand the differences in productivity (above ground biomass and total foliar nitrogen). We then measured CO2 exchange at ecosystem level, using a chamber technique, and assessed the treatments’ effect on the gross primary productivity (GPP) and ecosystem respiration (Reco). GPP and Reco were controlled by soil moisture and above ground biomass but also influenced by the conditions experienced during the growing season prior to the measuring period. Our second location was a post-disturbance chronosequence in a seasonally dry tropical forest in Costa Rica and we used leaf level gas exchange measurements to explore the role of nitrogen (N) and phosphorus (P) on the temporal-spatial variation of photosynthesis of dominant species. We found that photosynthetic efficiency was strongly linked to leaf N and P content, but that there was an important seasonal pattern on this relationship likely associated to P remobilization. Additionally we found seasonal changes in resources (water, nutrients) had a larger impact on the photosynthetic parameters than changes along the chronosequence. The two ecosystems studied for this thesis are contrasting in their physiognomy, species composition and climate, but are also characterised by species whose structural traits (high LMA and high C:N ratio) are likely to have a significant impact on the nutrient cycling processes. We learned that leaf traits provide important information about species strategies and their usage of resources and they can also aid to address questions at ecosystem level in time and space, either through simple aggregation or as emergent properties. Additionally, the traits explored are important input information to up-scale processes from leaf to the ecosystem level, a step needed to address the effect changes in resources will have on the seasonally dry tropical forest and grasslands, which represent a significant fraction of the total global carbon storage.

Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating R-n but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.

Decisões tomadas no planejamento da implantação florestal, como a densidade do plantio e o material genético, alteram a disponibilidade de recursos naturais tais como nutrientes, água e luz e consequentemente afetam a assimilação do carbono, que está diretamente relacionada ao crescimento da planta. Ainda são escassas as informações de como e quanto a densidade de plantio e o material genético afetam a fixação de carbono pelas ávores. O objetivo desse trabalho foi avaliar os padrões de fixação e alocação de carbono em plantações clonais de Eucalyptus sp. em duas densidades de plantio (3x2 m e 3x4 m), em um Latossolo Vermelho Distrófico T ípico A moderado. O estudo foi desenvolvido na Estação Experimental de Ciências Florestais de Itatinga-SP - ESALQ/USP, com três materiais clonais de Eucalyptus urophylla: AEC 0144, AEC 224 e COP 1404. O delineamento experimental utilizado foi em blocos casualizados, com esquema fatorial 3 x 2, sendo composto por três clones de eucalipto em dois espaçamentos, com 6 repetições para cada tratamento. Durante o intervalo de um ano (dos 40 aos 52 meses de idade) foram determinados a Produtividade Primária Líquida da Parte Aérea (ANPP: incremento da biomassa aérea somada ao folhedo), a Respiração Autotrófica da Parte Aérea (Rp: respiração das folhas e do tronco com base com base na ANPP, assumindo um valor constante de eficiência de uso do carbono (CUE) de 0,53 (GIARDINA et al., 2003)), o Fluxo de Carbono Abaixo do Solo (TBCF: produção e respiração das raízes grossas e finas, exsudatos das raízes e produção de substratos usados por micorrizas) e a Produtividade Primária Bruta (GPP: somatório dos fluxos de carbono) para os seis tratamentos avaliados. A maior produtividade encontrada para o clone AEC 0144 no espaçamento 3x2 m foi resultado de uma maior GPP (5997,45 g C m-2 ano-1), maior partição de carbono para incremento de tronco (30%) e menor partição da GPP para TBCF (34%). A ANPP variou de 1453,99 g C m-2 ano-1 (Clone COP 1404 no espaçamento 3x2 m) a 2288,78 g C m-2 ano-1 (Clone AEC 0144 no espaçamento 3x2 m), sendo os maiores fluxos encontrados para os clones AEC 0144 em ambos espaçamentos e para o clone COP 1404 no espaçamento 3x4 m. A variação encontrada nos valores de respiração da parte aérea seguiram o mesmo padrão dos resultados da ANPP. O TBCF foi significadamente superior para os clones AEC 0144 e AEC 224 no espaçamento 3x2 m com 2056,36 g C m-2 ano-1 e 1903,83 g C m-2 ano-1, respectivamente; e para o clone COP 1404 no espaçamento 3x4 m (1927,43 g C m-2 ano-1). Houve correlação positiva do TBCF com a GPP, mas não com a ANPP. / Decisions not planned for forest deployment, such as planting density and genetic material, alter the availability of natural resources such as nutrients, water and light and consequently affect the assimilation of carbon, which is directed to plant growth. They are still scarce as information on how and how much planting density and genetic material for a fixation of carbon by trees. The objective of this work was to evaluate the carbon allocation patterns in clonal plantations of Eucalyptus sp. in two planting densities (3x2 m and 3x4 m), in a typical Typic A moderate Dystrophic Red Latosol. The study was developed at the Experimental Station of Forest Sciences of Itatinga-SP - ESALQ / USP, with three clonal materials of Eucalyptus urophylla: AEC 0144, AEC 224 and COP 1404. The experimental design was a randomized complete block design with a factorial scheme 3 x 2, being composed of three clones of eucalyptus in two spacings, with 6 replicates for each treatment. During the one-year interval (from 40 to 52 months of age) was determined Aboveground Net Primary Productivity (ANPP: increase of the aerial biomass added to the litterfall), Aboveground Autotrophic Respiration (Rp: leaf respiration and (CUE) of 0.53 (GIARDINA et al., 2003)), Total Belowground Carbon Flux (TBCF: production and respiration of the roots) and Gross Primary Productivity (GPP: sum of the carbon fluxes) for the six treatments evaluated. The higher productivity found for the clone AEC 0144 in the 3x2 m spacing resulted from a higher GPP (5997.45 g C m-2 year-1), larger carbon partition for trunk increment (30%) and smaller partition from GPP for TBCF (34%). The ANPP ranged from 1453.99 g C m-2 year-1 (Clone COP 1404 in spacing 3x2 m) to 2288.78 g C m-2 year-1 (Clone AEC 0144 in 3x2 m spacing) Found for clones AEC 0144 in both spacings and COP 1404 in 3x4 m spacing. The variation found in aboveground autotrophic respiration values followed the same pattern of ANPP results. The TBCF was significantly higher for clones AEC 0144 and AEC 224 at 3x2 m spacing with 2056.36 m-2 year-1 and 1903.83 m-2 year-1, respectively; and for clone COP 1404 in 3x4 m spacing (1927.43 m-2 year-1). There was a positive correlation between TBCF and GPP, but not with ANPP.

Submitted by Sandra Pereira (srpereira@ufrrj.br) on 2016-10-18T10:23:51Z No. of bitstreams: 1 2016 - Catherine Torres de Almeida.pdf: 4011870 bytes, checksum: 95ec0ec572d24a8a7285ec3bb17fac37 (MD5) / Made available in DSpace on 2016-10-18T10:23:51Z (GMT). No. of bitstreams: 1 2016 - Catherine Torres de Almeida.pdf: 4011870 bytes, checksum: 95ec0ec572d24a8a7285ec3bb17fac37 (MD5) Previous issue date: 2016-02-17 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / The Gross Primary Productivity (GPP) is the rate at the atmospheric CO2 is converted by photosynthetic activity in organic substances and is a measure of the total carbon fixed by the ecosystem. In the context of climate change, the focus for the fixation of carbon by forest ecosystems is the basis to mitigate emissions of anthropogenic CO2. There are several methods for the quantification of carbon stored in the vegetation, using data obtained by micrometeorological towers or by remote sensing. Among these methods, stands out the eddy covariance technique, that is much used to quantify the CO2 flux in many forest ecosystems. However, this technique has a high cost, limited operation and covers a small extent. Accordingly, the methods that employ remote sensing have the advantage of providing terrestrial primary productivity estimates for large areas where the methods at the field level are not feasible. This work has as main objective to evaluate the dynamics of the GPP in the Brazilian Legal Amazon over land use and land cover and weather variables. For understanding the relationship of the eddy covariance GPP with meteorological data, rainfall data from TRMM 3B43 product and environmental variables of flux towers were used. Data from TRMM satellite were validated with data from seven conventional weather stations of Amazonas state. The comparison was based on the Average Error (AE), Root Mean Square Error (RMSE), linear correlation coefficient (r) and Wilmott agreement index (d). We also used the Spearman correlation coefficient and a regression tree model to assess the relationship between flux tower GPP and environmental variables. To evaluate GPP estimates from two versions of the MOD17A2 product, derived from MODIS sensor data, these have been validated with surface data from seven LBA flux towers, of which four are in forest cover, one in transition forest and two in disturbed areas. The statistical analyzes were performed with R software, version 3.1.0. The results of the validation of TRMM 3B43 were positive, with high linear correlation (r = 0.83), high level of agreement (d = 0.85) and an adequate RMSE (59.77 mm), showing that this product can be used as an alternative source of quality data. Regarding the influence of the land use and land cover in GPP, it was found that the disturbed areas had lower productivity compared to the conserved areas and had their water balance affected, presenting higher values of the Bowen ratio. The GPP seasonality was predominantly related to radiation at the top of the atmosphere in forest areas of the equatorial Amazon. In areas more distant of the Ecuador, the GPP was influenced by radiation at the top of the atmosphere and also by rainfall and VPD, indicating limitation both by radiation and by water availability. MOD17A2 had no satisfactory agreement between in estimating GPP compared to the method of eddy covariance, underestimating productivity for most locations studied. The seasonality derived from the MODIS algorithm was only similar to the seasonality of GPP by eddy covariance method for non-equatorial locations. The areas in Equatorial Amazon exhibit distinct MOD17A2 GPP seasonal pattern of that verified by data from the micrometeorological towers. Given this, it is necessary to improve the MOD17A2 algorithm to enable it to estimate GPP depending on the different vegetation responses to drought and radiation. This improved understanding may help to produce better estimates of GPP in Amazon and the use of remote sensing in conjunction with the surface data can contribute to generate an overview of GPP in this biome. / A Produtividade Prim?ria Bruta (PPB) ? a taxa na qual o CO2 atmosf?rico ? convertido pela atividade fotossint?tica em subst?ncias org?nicas e ? uma medida do total de carbono fixado pelo ecossistema. No contexto das mudan?as clim?ticas, o enfoque para a fixa??o de carbono pelos ecossistemas florestais ? a base para mitigar as emiss?es de CO2 antropog?nico. Existem diversos m?todos destinados ? quantifica??o do carbono estocado na vegeta??o, que utilizam dados obtidos por meio de torres micrometeorol?gicas de fluxo ou atrav?s de sensoriamento remoto. Dentre esses m?todos, se destaca a t?cnica de covari?ncia de v?rtices turbulentos, por ser muito empregada para quantificar o fluxo de CO2 em diversos ecossistemas florestais. Por?m, esta t?cnica possui um custo alto, operacionalidade restrita e abrange uma pequena extens?o. Nesse sentido, os m?todos que empregam o sensoriamento remoto t?m a vantagem de fornecer estimativas de produtividade prim?ria terrestre para grandes ?reas, onde os m?todos ao n?vel do terreno n?o s?o vi?veis. Este trabalho tem como objetivo geral avaliar a din?mica da PPB na Amaz?nia Legal brasileira em rela??o ao uso e cobertura do solo e ?s vari?veis meteorol?gicas. Para compreender a rela??o da PPB obtida pelo m?todo de covari?ncia de v?rtices turbulentos com dados meteorol?gicos, foram utilizados dados de chuva do produto 3B43 do sat?lite TRMM e vari?veis ambientais das torres de fluxo. Os dados do sat?lite TRMM foram validados com dados de sete esta??es meteorol?gicas convencionais do estado do Amazonas. A compara??o foi baseada no Erro M?dio (EM), Raiz do Erro M?dio Quadr?tico (REMQ), coeficiente de correla??o linear (r) e ?ndice de concord?ncia de Wilmott (d). Tamb?m utilizou-se o coeficiente de correla??o de Spearman e um modelo de ?rvore de regress?o para avaliar a rela??o entre a PPB da torre de fluxo e as vari?veis ambientais. Para avaliar as estimativas de PPB de duas vers?es do produto MOD17A2, derivadas de dados do sensor MODIS, estas foram validadas com dados de superf?cie de sete torres de fluxo do Projeto LBA, das quais quatro se encontram em cobertura florestal, uma em floresta de transi??o e duas em ?reas antropizadas. As an?lises estat?sticas foram realizadas no software R, vers?o 3.1.0. Os resultados da valida??o do produto 3B43 do TRMM foram positivos, com alta correla??o linear (r = 0,83), alto ?ndice de concord?ncia (d = 0,85) e REMQ satisfat?rio (59,77 mm), mostrando que este produto pode ser utilizado como uma fonte alternativa de dados de qualidade. Em rela??o ? influ?ncia do uso e da cobertura do solo na PPB, verificou-se que as ?reas antropizadas apresentaram menor produtividade em rela??o ?s ?reas conservadas e tiveram seu balan?o h?drico afetado, pois apresentaram altos valores da raz?o de Bowen. A sazonalidade da PPB foi predominantemente relacionada ? radia??o no topo da atmosfera nas ?reas de floresta da Amaz?nia equatorial. Nas ?reas mais distantes do Equador, a PPB foi influenciada pela radia??o no topo da atmosfera e tamb?m pela chuva e VPD, indicando limita??o tanto pela radia??o quanto pela disponibilidade de ?gua. O MOD17A2 n?o apresentou boa estimativa de PPB comparado ao m?todo de v?rtices turbulentos, subestimando a produtividade para a maioria das localidades estudadas. A sazonalidade da PPB deste algoritmo somente foi similar ? sazonalidade da PPB pelo m?todo de v?rtices turbulentos para as localidades n?o-equatoriais. As ?reas na Amaz?nia Equatorial apresentaram padr?o sazonal da PPB do MOD17A2 distinto do verificado pelos dados das torres micrometeorol?gicas. Diante disto, ? necess?rio melhorar o algoritmo MOD17A2 para que este possa estimar PPB em fun??o das diferentes respostas da vegeta??o ? seca e ? radia??o. Esse melhor entendimento poder? contribuir para produzir melhores estimativas da PPB para a Amaz?nia e o uso do sensoriamento remoto em conjunto com os dados de superf?cie pode contribuir para gerar uma vis?o geral da PPB nesse bioma.

Decisões tomadas no planejamento da implantação florestal, como a densidade do plantio e o material genético, alteram a disponibilidade de recursos naturais tais como nutrientes, água e luz e consequentemente afetam a assimilação do carbono, que está diretamente relacionada ao crescimento da planta. Ainda são escassas as informações de como e quanto a densidade de plantio e o material genético afetam a fixação de carbono pelas ávores. O objetivo desse trabalho foi avaliar os padrões de fixação e alocação de carbono em plantações clonais de Eucalyptus sp. em duas densidades de plantio (3x2 m e 3x4 m), em um Latossolo Vermelho Distrófico T ípico A moderado. O estudo foi desenvolvido na Estação Experimental de Ciências Florestais de Itatinga-SP - ESALQ/USP, com três materiais clonais de Eucalyptus urophylla: AEC 0144, AEC 224 e COP 1404. O delineamento experimental utilizado foi em blocos casualizados, com esquema fatorial 3 x 2, sendo composto por três clones de eucalipto em dois espaçamentos, com 6 repetições para cada tratamento. Durante o intervalo de um ano (dos 40 aos 52 meses de idade) foram determinados a Produtividade Primária Líquida da Parte Aérea (ANPP: incremento da biomassa aérea somada ao folhedo), a Respiração Autotrófica da Parte Aérea (Rp: respiração das folhas e do tronco com base com base na ANPP, assumindo um valor constante de eficiência de uso do carbono (CUE) de 0,53 (GIARDINA et al., 2003)), o Fluxo de Carbono Abaixo do Solo (TBCF: produção e respiração das raízes grossas e finas, exsudatos das raízes e produção de substratos usados por micorrizas) e a Produtividade Primária Bruta (GPP: somatório dos fluxos de carbono) para os seis tratamentos avaliados. A maior produtividade encontrada para o clone AEC 0144 no espaçamento 3x2 m foi resultado de uma maior GPP (5997,45 g C m-2 ano-1), maior partição de carbono para incremento de tronco (30%) e menor partição da GPP para TBCF (34%). A ANPP variou de 1453,99 g C m-2 ano-1 (Clone COP 1404 no espaçamento 3x2 m) a 2288,78 g C m-2 ano-1 (Clone AEC 0144 no espaçamento 3x2 m), sendo os maiores fluxos encontrados para os clones AEC 0144 em ambos espaçamentos e para o clone COP 1404 no espaçamento 3x4 m. A variação encontrada nos valores de respiração da parte aérea seguiram o mesmo padrão dos resultados da ANPP. O TBCF foi significadamente superior para os clones AEC 0144 e AEC 224 no espaçamento 3x2 m com 2056,36 g C m-2 ano-1 e 1903,83 g C m-2 ano-1, respectivamente; e para o clone COP 1404 no espaçamento 3x4 m (1927,43 g C m-2 ano-1). Houve correlação positiva do TBCF com a GPP, mas não com a ANPP. / Decisions not planned for forest deployment, such as planting density and genetic material, alter the availability of natural resources such as nutrients, water and light and consequently affect the assimilation of carbon, which is directed to plant growth. They are still scarce as information on how and how much planting density and genetic material for a fixation of carbon by trees. The objective of this work was to evaluate the carbon allocation patterns in clonal plantations of Eucalyptus sp. in two planting densities (3x2 m and 3x4 m), in a typical Typic A moderate Dystrophic Red Latosol. The study was developed at the Experimental Station of Forest Sciences of Itatinga-SP - ESALQ / USP, with three clonal materials of Eucalyptus urophylla: AEC 0144, AEC 224 and COP 1404. The experimental design was a randomized complete block design with a factorial scheme 3 x 2, being composed of three clones of eucalyptus in two spacings, with 6 replicates for each treatment. During the one-year interval (from 40 to 52 months of age) was determined Aboveground Net Primary Productivity (ANPP: increase of the aerial biomass added to the litterfall), Aboveground Autotrophic Respiration (Rp: leaf respiration and (CUE) of 0.53 (GIARDINA et al., 2003)), Total Belowground Carbon Flux (TBCF: production and respiration of the roots) and Gross Primary Productivity (GPP: sum of the carbon fluxes) for the six treatments evaluated. The higher productivity found for the clone AEC 0144 in the 3x2 m spacing resulted from a higher GPP (5997.45 g C m-2 year-1), larger carbon partition for trunk increment (30%) and smaller partition from GPP for TBCF (34%). The ANPP ranged from 1453.99 g C m-2 year-1 (Clone COP 1404 in spacing 3x2 m) to 2288.78 g C m-2 year-1 (Clone AEC 0144 in 3x2 m spacing) Found for clones AEC 0144 in both spacings and COP 1404 in 3x4 m spacing. The variation found in aboveground autotrophic respiration values followed the same pattern of ANPP results. The TBCF was significantly higher for clones AEC 0144 and AEC 224 at 3x2 m spacing with 2056.36 m-2 year-1 and 1903.83 m-2 year-1, respectively; and for clone COP 1404 in 3x4 m spacing (1927.43 m-2 year-1). There was a positive correlation between TBCF and GPP, but not with ANPP.