MSCAGR (Plant Production) / Department of Plant Production / Agricultural production under rain-fed conditions is largely dependent on the availability of water stored in the soil during rainfall events. The production of cassava (Manihot esculenta Crantz) under rain-fed conditions in the north-eastern part of South Africa is constrained by low and erratic rainfall events. Improving cassava production in the area requires the use of cassava varieties which are efficient in the use of limited soil moisture. The current climate change and increasing population growth on the planet will place more pressure on agriculture to produce more food using less water. Therefore, previously under-researched and underutilised crop like cassava could be used to bridge the food gap in the future. Although the crop currently occupies low levels of utilisation in South Africa and it is cultivated by smallscale farmers in the Low-veld of Mpumalanga, Limpopo and Kwazulu-Natal provinces using landraces with no improved varieties available in the country. Information on the actual pattern of water extraction, water use and water use efficiency of cassava landraces grown in the dry environments of South Africa is limited. Therefore, the objective of the study was to determine the differences in water use efficiency, gaseous exchange and yield among four cassava landraces grown under rain-fed conditions. Two field experiments were conducted during the wetter (2016/2017) and drier (2017/2018) cropping season at the University of Venda's experimental farm. The trials were laid in a Randomized Complete Block Design (RCBD) consisting of four cassava landraces (ACC#1, ACC#2, ACC#3, and ACC#4) replicated three times. Mature cassava stem cuttings of 30 cm long, were planted manually at a spacing of 1 m x 1 m in both seasons. Each experimental unit consisted of six plant rows of 6 m length (36 m2) and 8 rows of 8 m length (64 m2) in the 2016/17 and 2017/2018 cropping season, respectively. The experiments were under rain-fed conditions without fertilizer additions and the plots were kept weed-free throughout the experimental period. Data collected in the field included soil moisture content, gaseous exchange parameters (net leaf ܥܱଶ uptake, stomatal conductance, and intracellular carbon dioxide concentration), chlorophyll content index (CCI), maximum photochemical quantum yield of PSII (Fv/Fm), effective quantum yield of PSII (ФPSII) and photosynthetic active radiation (PAR). Yield and yield components (root length (cm), root girth (cm), number of storage roots and mean root weight (g plant-1), root yield and aboveground biomass), as well as water use efficiency (WUE), were determined at harvest. Soil moisture content was measured at seven-day interval from sowing until harvest using a neutron probe. Soil moisture data were used to determine crop water use using the water balance approach. There was no variation in the root yield and yield components amongst the landraces in 2017/2018 cropping season but, genotypes affected aboveground biomass, root girth, number of roots per plant and root yield in 2016/2017 cropping season. There was a significant difference (P<0.01) in number of roots (per plant) 81% and 62% greater in ACC#3 and ACC#2 (6.7 & 6.0, respectively) compared with ACC#1 and ACC#4, which both recorded 4 roots per plant. Similarly, root girth was greater in ACC#3 (17.8 cm) and ACC#2 (18.2 cm) compared to ACC#1 (14.1 cm) and ACC#4 (12.9 cm), which were statistically the same. In contrast, total biomass (P<0.01) and root yield (P<0.05) were greater in ACC#3 (20.7 and 11.9 t ha-1, respectively) and ACC#1 (22.0 and 11.3 t ha-1, respectively) compared to ACC#2 and ACC#4 with root yields of 10.2 and 9.5 t ha-1, biomass of 17.1 and 16.3 t ha-1, respectively. Although the genotype x cropping season interaction did not affect root yield and yield components, root yield (by 33.8%; 2.7 t ha-1) and yield components were greater in the wetter compared to the drier season as expected. Water use efficiency of root yield (WUErt) and water use efficiency of biomass production (WUEb) varied with landraces in season I from 37.0 kg ha-1 mm-1 (ACC#4) to 46.60 kg ha-1 mm-1 (ACC#3), and between 71.30 kg ha-1 mm-1 (ACC#2) and 86.0 kg ha-1 mm-1 (ACC#1), respectively. Landraces did not differ in their water use and soil moisture extraction in both seasons but differed in season. However, there was a significant positive correlation between water use efficiency of root yield (WUErt) (0.963***) and water use efficiency of biomass production (WUEb) (0.847***). WUE of biomass production was greater in the drier than the wetter season partly because of dry matter accumulation per evapotranspiration within the landraces. Photosynthesis did not vary with landraces, however, stomatal conductance varied with landraces from 0.08 mmol m-2 s-1 (ACC#4) to 0.2 mmol m-2 s-1 (ACC#2). In contrast, ACC#1 and ACC#3 recorded the same value of stomatal conductance, which is 0.1 mmol m-2 s-1. The effective quantum yield of PSII photochemistry (ΦPSII) did not vary with landraces but the maximum photochemical quantum yield of PSII (Fv/Fm) varied with landraces from 0.652 (ACC#4) to 0.792 (ACC#3) in season II. The proportion of intercepted radiation was affected by landraces in 2017/2018 cropping season. Highest proportion of intercepted radiation was observed in ACC#3 and the lowest in ACC#2. Proportion of intercepted radiation varied with landraces from 22.62% (ACC#2) to 86.45% (#ACC#3). There were significant genotypic variations in chlorophyll content recorded in both season. Chlorophyll content varied with landraces from 33.1 CCI (ACC4) to 55.4 CCI (#ACC3) in the 2016/2017, and in 2017/2018 cropping season chlorophyll content varied with landraces from 36.9 CCI (ACC4) to 78.7 CCI (#ACC3). The highest genotypic variation in chlorophyll content was observed in ACC#3, whilst the lowest chlorophyll content was recorded in ACC#4 in both seasons. / NRF

京都大学 / 0048 / 新制・課程博士 / 博士(地域研究) / 甲第19833号 / 地博第189号 / 新制||地||66(附属図書館) / 32869 / 京都大学大学院アジア・アフリカ地域研究研究科東南アジア地域研究専攻 / (主査)教授 竹田 晋也, 教授 岩田 明久, 准教授 古澤 拓郎, 教授 神﨑 護 / 学位規則第4条第1項該当 / Doctor of Area Studies / Kyoto University / DGAM

Monitoring carbon stock has emerged as a critical environmental problem among several worldwide organizations and collaborations in the context of global warming and climate change. This study seeks to provide a remote sensing solution based on three types of data, to explore the feasibility and reliability of estimating aboveground biomass (AGB) in order to improve the efficiency of monitoring carbon stock. The study attempted to investigate the potential of using Google Earth Engine (GEE), and the combinations of different datasets from Sentinel-1 (SAR), Sentinel-2 multispectral imagery, and LiDAR data to estimate AGB, by using the random forest algorithm (RF). Two models were proposed: the first one (Model 1) detected the AGB temporal changes from 2016 to 2021 in Southern Sweden; while the second one (Model 2) focused on Hultsfred municipality and studied the influence of different variables including the canopy height. Besides, six experimental groups of variables were tested to determine the performance of using different types of remote sensing data. We validated these two models with the observed AGB, and the findings showed that the combination of SAR polarization, multisprectral bands, vegetation indices able to estimate AGB for Model 1. In addition, Model 2 showed that further using the canopy height data can further improve the estimation.  We also found out that the spectral bands from Sentinel-2 contributed the most to AGB estimation for Model 1 in terms of: bands B3 (Green), B4 (Red), B5 (Red edge), B11 (SWIR), B12 (SWIR); and, vegetation indices of RVI, DVI, and EVI. On the other hand, for Model 2, B1(Ultra blue), B4 (Red), EVI, SAVI, and the canopy height are the most crucial variables for estimating AGB. Besides, the radar backscatter values using VV and VH modes from Sentienl-1 were both important for Models 1 and 2. For Model 1, the experimental group with the best accuracy was the group that used all variable combinations from Sentinel-1 and 2, and its   was 0.33~0.74. For Model 2, the group that used all the variables, in addition to the canopy height performed the best, where its   is 0.91. These therefore showed the benefit of integrating different remote sensing data sources.  In conclusion, this study showed the potential of using RF and GEE to estimate AGB in Southern Sweden. Furthermore, this study also shows the possibility of handling large dataset for a large scale area, at the resolution of 10 m, and producing time series AGB maps from 2016 to 2021. This can help enhance our understanding of AGB temporal changes and carbon stock detection in Southern Sweden, that can provide valuable insights for forest management and carbon monitoring.

No description available.

As florestas tropicais exibem elevada biodiversidade e desempenham um importante papel no ciclo global do carbono. Porém, essas florestas têm sido impactadas aceleradamente nos últimos anos. No Brasil, a floresta tropical Atlântica está restrita a aproximadamente 7 % de sua extensão original e seus remanescentes ainda sofrem ameaças. Com isso, informações sobre a dinâmica da vegetação desse bioma são importantes para entender o funcionamento desse ecossistema e servem de subsídio para auxiliar em sua conservação e restauração. No presente estudo, os principais processos que regem a dinâmica de uma floresta (mortalidade, recrutamento e crescimento) foram estimados em duas fisionomias distintas da floresta tropical Atlântica. Além disso, a variação líquida da biomassa acima do solo (BAS) também foi estimada. Para o presente estudo foram utilizadas cinco (5) parcelas permanentes de um (1) hectare inseridas no projeto temático Gradiente Funcional, sendo: quatro (4) na floresta de Terras Baixas e uma (1) na floresta de Restinga. Os inventários foram realizados no momento da implantação das parcelas permanentes (2006) e após dois (2) anos. Os resultados obtidos demonstraram que a Restinga (1635 ind.ha-1) possui maior densidade total de indivíduos vivos com o DAP \'>OU=\'4,8 cm que a Terras Baixas (1221 ind.ha-1). O estoque de biomassa acima do solo (BAS) foi maior na Terras Baixas (212,3 Mg.ha-1) que na Restinga (166,3 Mg.ha-1) (DAP \'>OU=\'4,8 cm). A distribuição dos indivíduos nas classes de diâmetro influenciou essas diferenças estruturais: a Restinga possui maior densidade total de indivíduos na menor classe de diâmetro e a floresta de Terras Baixas possui maior densidade de indivíduos na maior classe. Tal fato também impactou a distribuição do estoque de BAS nas classes de diâmetro: a floresta de Restinga estoca mais biomassa na classe de 10-30 cm e a floresta de Terras Baixas na maior classe de DAP, \'>OU=\'50 cm. A mediana da taxa de incremento diamétrico da comunidade arbórea não diferiu entre os dois tipos de floresta, sendo igual a 1,0 mm.ano-1 na Restinga e 0,8 mm.ano-1 na Terras Baixas (DAP \'>OU=\'4,8 cm). Diferenças na taxa de incremento diamétrico com relação às formas de vida (árvores e palmeiras) foram observadas. A taxa de incremento diamétrico das árvores apresentou relação positiva com o aumento das classes de DAP e o índice de iluminação de copa. O mesmo padrão não foi observado para as palmeiras. A taxa de mortalidade da comunidade arbórea foi semelhante entre os dois tipos de floresta, sendo igual a 2,46 % na Restinga e 2,00 % na Terras Baixas (DAP \'>OU=\'4,8 cm). A taxa de recrutamento também foi semelhante entre as florestas, sendo igual a 1,42 % na Restinga e 1,36 % na floresta de Terras Baixas. A variação líquida da BAS foi maior nas Terras baixas (0,64 Mg.ha-1.ano-1) que na Restinga (0,32 Mg.ha-1.ano-1). Por fim, a floresta tropical Atlântica apresenta maior densidade de indivíduos vivos, menor estoque de BAS, menor taxa de incremento e reposição quando comparada com outras florestas tropicais, possivelmente devido à distribuição da precipitação ao longo do ano / Tropical forests display a biodiversity unmatched by any other vegetation type and play an important role in the global terrestrial carbon cycle. However, tropical forests have been severely impacted in the last years. In Brazil, the tropical Atlantic forest is restricted to approximately 7 % of its original extension and its fragments still remain threatened. Hence, information regarding the vegetation dynamic of this important biome is important to understand the functioning of this ecosystem and support conservation and restoration actions. Here, the principal processes that drive forest dynamics (mortality, recruitment and growth) were estimated for two tropical Atlantic forest types. Additionally, the net aboveground biomass change (AGB) also was estimated. In this study, five one-hectare permanent plots established by the Gradiente Funcional project were adopted: four (4) plots in lowland and one (1) in seasonally flooded Atlantic forest. The forestry inventories were performed in the same time of permanent plot establishment (2006) and after two (2) years (2008). The results showed that the seasonally flooded Atlantic forest has greater total stem density (DBH \'>OU=\'4.8 cm) than lowland Atlantic forest, equal to 1635 ind.ha-1 in seasonally flooded and 1221 ind.ha-1 in lowland forest. The aboveground biomass (AGB) was greater in lowland than in seasonally flooded forest, equal to 166.3 Mg.ha-1 in seasonally flooded and 212.3 Mg.ha-1 in lowland forest (4,8 cm DBH). The distribution of trees among DBH classes influenced these structural differences: the seasonally flooded forest has high stem density at smaller DBH size class while the lowland forest has high stem density at larger DBH size class. In addition, that variation in size structure also impacted the AGB distribution among DBH classes: the seasonally flooded Atlantic forest has more AGB in the 10-30 cm DBH class and the lowland Atlantic forest has more AGB in the large size class ( \'>OU=\'50 cm). The median growth rate of tree community did not differ between the two forest types, equal to 1.0 mm.yr-1 in seasonally flooded and 0.8 mm.yr-1 in lowland forest ( \'>OU=\'4.8 cm DBH). Differences in growth rates regarding the life forms (tree and palm) were observed. Tree growth rates showed positive relationship with crown illumination index and DBH classes. The same tendency was not observed for palm life form. The mortality rate of tree community did not differ between the two forest types, equal to 2.46 % in seasonally flooded and 2.00 % in lowland forest ( \'>OU=\'4.8 cm DBH). The recruitment rate also did not differ between the two forest types, equal to 1.42 % in seasonally flooded and 1.36 % in lowland forest (\'>OU=\'4.8 cm DBH). The lowland Atlantic forest AGB net change (0.64 Mg.ha-1.yr-1) was higher than seasonally flooded Atlantic forest (0.64 Mg.ha-1.yr-1). Finally, the tropical Atlantic forest has higher stem density, lower AGB, lower growth and turnover rates than other tropical forests probably due to rainfall distribution among year

As florestas tropicais exibem elevada biodiversidade e desempenham um importante papel no ciclo global do carbono. Porém, essas florestas têm sido impactadas aceleradamente nos últimos anos. No Brasil, a floresta tropical Atlântica está restrita a aproximadamente 7 % de sua extensão original e seus remanescentes ainda sofrem ameaças. Com isso, informações sobre a dinâmica da vegetação desse bioma são importantes para entender o funcionamento desse ecossistema e servem de subsídio para auxiliar em sua conservação e restauração. No presente estudo, os principais processos que regem a dinâmica de uma floresta (mortalidade, recrutamento e crescimento) foram estimados em duas fisionomias distintas da floresta tropical Atlântica. Além disso, a variação líquida da biomassa acima do solo (BAS) também foi estimada. Para o presente estudo foram utilizadas cinco (5) parcelas permanentes de um (1) hectare inseridas no projeto temático Gradiente Funcional, sendo: quatro (4) na floresta de Terras Baixas e uma (1) na floresta de Restinga. Os inventários foram realizados no momento da implantação das parcelas permanentes (2006) e após dois (2) anos. Os resultados obtidos demonstraram que a Restinga (1635 ind.ha-1) possui maior densidade total de indivíduos vivos com o DAP \'>OU=\'4,8 cm que a Terras Baixas (1221 ind.ha-1). O estoque de biomassa acima do solo (BAS) foi maior na Terras Baixas (212,3 Mg.ha-1) que na Restinga (166,3 Mg.ha-1) (DAP \'>OU=\'4,8 cm). A distribuição dos indivíduos nas classes de diâmetro influenciou essas diferenças estruturais: a Restinga possui maior densidade total de indivíduos na menor classe de diâmetro e a floresta de Terras Baixas possui maior densidade de indivíduos na maior classe. Tal fato também impactou a distribuição do estoque de BAS nas classes de diâmetro: a floresta de Restinga estoca mais biomassa na classe de 10-30 cm e a floresta de Terras Baixas na maior classe de DAP, \'>OU=\'50 cm. A mediana da taxa de incremento diamétrico da comunidade arbórea não diferiu entre os dois tipos de floresta, sendo igual a 1,0 mm.ano-1 na Restinga e 0,8 mm.ano-1 na Terras Baixas (DAP \'>OU=\'4,8 cm). Diferenças na taxa de incremento diamétrico com relação às formas de vida (árvores e palmeiras) foram observadas. A taxa de incremento diamétrico das árvores apresentou relação positiva com o aumento das classes de DAP e o índice de iluminação de copa. O mesmo padrão não foi observado para as palmeiras. A taxa de mortalidade da comunidade arbórea foi semelhante entre os dois tipos de floresta, sendo igual a 2,46 % na Restinga e 2,00 % na Terras Baixas (DAP \'>OU=\'4,8 cm). A taxa de recrutamento também foi semelhante entre as florestas, sendo igual a 1,42 % na Restinga e 1,36 % na floresta de Terras Baixas. A variação líquida da BAS foi maior nas Terras baixas (0,64 Mg.ha-1.ano-1) que na Restinga (0,32 Mg.ha-1.ano-1). Por fim, a floresta tropical Atlântica apresenta maior densidade de indivíduos vivos, menor estoque de BAS, menor taxa de incremento e reposição quando comparada com outras florestas tropicais, possivelmente devido à distribuição da precipitação ao longo do ano / Tropical forests display a biodiversity unmatched by any other vegetation type and play an important role in the global terrestrial carbon cycle. However, tropical forests have been severely impacted in the last years. In Brazil, the tropical Atlantic forest is restricted to approximately 7 % of its original extension and its fragments still remain threatened. Hence, information regarding the vegetation dynamic of this important biome is important to understand the functioning of this ecosystem and support conservation and restoration actions. Here, the principal processes that drive forest dynamics (mortality, recruitment and growth) were estimated for two tropical Atlantic forest types. Additionally, the net aboveground biomass change (AGB) also was estimated. In this study, five one-hectare permanent plots established by the Gradiente Funcional project were adopted: four (4) plots in lowland and one (1) in seasonally flooded Atlantic forest. The forestry inventories were performed in the same time of permanent plot establishment (2006) and after two (2) years (2008). The results showed that the seasonally flooded Atlantic forest has greater total stem density (DBH \'>OU=\'4.8 cm) than lowland Atlantic forest, equal to 1635 ind.ha-1 in seasonally flooded and 1221 ind.ha-1 in lowland forest. The aboveground biomass (AGB) was greater in lowland than in seasonally flooded forest, equal to 166.3 Mg.ha-1 in seasonally flooded and 212.3 Mg.ha-1 in lowland forest (4,8 cm DBH). The distribution of trees among DBH classes influenced these structural differences: the seasonally flooded forest has high stem density at smaller DBH size class while the lowland forest has high stem density at larger DBH size class. In addition, that variation in size structure also impacted the AGB distribution among DBH classes: the seasonally flooded Atlantic forest has more AGB in the 10-30 cm DBH class and the lowland Atlantic forest has more AGB in the large size class ( \'>OU=\'50 cm). The median growth rate of tree community did not differ between the two forest types, equal to 1.0 mm.yr-1 in seasonally flooded and 0.8 mm.yr-1 in lowland forest ( \'>OU=\'4.8 cm DBH). Differences in growth rates regarding the life forms (tree and palm) were observed. Tree growth rates showed positive relationship with crown illumination index and DBH classes. The same tendency was not observed for palm life form. The mortality rate of tree community did not differ between the two forest types, equal to 2.46 % in seasonally flooded and 2.00 % in lowland forest ( \'>OU=\'4.8 cm DBH). The recruitment rate also did not differ between the two forest types, equal to 1.42 % in seasonally flooded and 1.36 % in lowland forest (\'>OU=\'4.8 cm DBH). The lowland Atlantic forest AGB net change (0.64 Mg.ha-1.yr-1) was higher than seasonally flooded Atlantic forest (0.64 Mg.ha-1.yr-1). Finally, the tropical Atlantic forest has higher stem density, lower AGB, lower growth and turnover rates than other tropical forests probably due to rainfall distribution among year

O mapeamento da estrutura florestal em escala de paisagem nos permite avaliar como as florestas respondem aos impactos da ação humana e a mudanças nas condições ambientais. Neste contexto, a tese tem como objetivo elaborar modelos de estimativa de biomassa acima do solo e fechamento de dossel utilizando imagens de satélite, em diferentes estágios de sucessão de Mata Atlântica localizada em área com complexidade topográfica. Para alcançar este objetivo geral, temos dois objetivos específicos: (1) avaliar o efeito da geomorfologia na modelagem da biomassa florestal e fechamento do dossel; (2) analisar os resultados das estimativas considerando diferentes estágios de sucessão florestal e testar o efeito da radiação solar direta sobre o fechamento do dossel. Primeiro, sumarizamos os mais frequentes temas ecológicos e métodos utilizados na literatura ligados a modelagem de estrutura florestal por meio do sensoriamento remoto. Subsequentemente, utilizamos dados de campo e imagens de satélite (LANDSAT TM e ALOS AVNIR-2) para estimar biomassa e fechamento do dossel. Utilizamos modelo digital de elevação como fonte de informação geomorfológica. Foram encontradas melhores estimativas de biomassa e fechamento do dossel quando integramos as imagens de satélite com uma variável geomorfométrica secundária do relevo (Fator de iluminação), que é baseada no ângulo de incidência da radiação solar sobre faces de morros. O índice \"solo/vegetação\", elaborado no presente estudo, apresentou melhores estimativas de fechamento do dossel quando comparado com a performance de diferentes índices de vegetação. A biomassa estimada pelas imagens possibilitou a diferenciação entre diferentes estágios de sucessão florestal / Mapping forest structure in landscape scale enables the evaluation of how forested areas respond to human impact and environmental conditions. In this context, the thesis aims to evaluate modeling approaches to estimate forest aboveground biomass and canopy closure with satellite images in different successional forest stands located at a rugged terrain region. Towards that goal, the specific objectives are: (1) to evaluate the effect of topographic features in the remotely sensed biomass and canopy closures estimations; (2) to analyze the modeled data over different successional stands of Atlantic Rainforest and test the effect of the annual direct sunlight in the forest canopy closure. First, we summarize the most frequent ecological inferences discussed in the literature and the methods used about forest structure modeling by using remote sensing data. Afterward, ground biophysical forest data and satellite images (LANDSAT TM and ALOS AVNIR-2) were used to estimate biomass and canopy closure. The modeling approach includes topographic features derived from digital elevation model. Our results show improved biomass and canopy closure estimates when the modeling includes satellite data interacting with a secondary geomorphometric variable (the Illumination Factor), that is based on direct solar beam angle. The soil/vegetation index, suggested in the present study, showed a better performance when compared with other vegetation index to estimate canopy closure. The modeled biomass shows evident biophysical distinction among different forest succession stages

O mapeamento da estrutura florestal em escala de paisagem nos permite avaliar como as florestas respondem aos impactos da ação humana e a mudanças nas condições ambientais. Neste contexto, a tese tem como objetivo elaborar modelos de estimativa de biomassa acima do solo e fechamento de dossel utilizando imagens de satélite, em diferentes estágios de sucessão de Mata Atlântica localizada em área com complexidade topográfica. Para alcançar este objetivo geral, temos dois objetivos específicos: (1) avaliar o efeito da geomorfologia na modelagem da biomassa florestal e fechamento do dossel; (2) analisar os resultados das estimativas considerando diferentes estágios de sucessão florestal e testar o efeito da radiação solar direta sobre o fechamento do dossel. Primeiro, sumarizamos os mais frequentes temas ecológicos e métodos utilizados na literatura ligados a modelagem de estrutura florestal por meio do sensoriamento remoto. Subsequentemente, utilizamos dados de campo e imagens de satélite (LANDSAT TM e ALOS AVNIR-2) para estimar biomassa e fechamento do dossel. Utilizamos modelo digital de elevação como fonte de informação geomorfológica. Foram encontradas melhores estimativas de biomassa e fechamento do dossel quando integramos as imagens de satélite com uma variável geomorfométrica secundária do relevo (Fator de iluminação), que é baseada no ângulo de incidência da radiação solar sobre faces de morros. O índice \"solo/vegetação\", elaborado no presente estudo, apresentou melhores estimativas de fechamento do dossel quando comparado com a performance de diferentes índices de vegetação. A biomassa estimada pelas imagens possibilitou a diferenciação entre diferentes estágios de sucessão florestal / Mapping forest structure in landscape scale enables the evaluation of how forested areas respond to human impact and environmental conditions. In this context, the thesis aims to evaluate modeling approaches to estimate forest aboveground biomass and canopy closure with satellite images in different successional forest stands located at a rugged terrain region. Towards that goal, the specific objectives are: (1) to evaluate the effect of topographic features in the remotely sensed biomass and canopy closures estimations; (2) to analyze the modeled data over different successional stands of Atlantic Rainforest and test the effect of the annual direct sunlight in the forest canopy closure. First, we summarize the most frequent ecological inferences discussed in the literature and the methods used about forest structure modeling by using remote sensing data. Afterward, ground biophysical forest data and satellite images (LANDSAT TM and ALOS AVNIR-2) were used to estimate biomass and canopy closure. The modeling approach includes topographic features derived from digital elevation model. Our results show improved biomass and canopy closure estimates when the modeling includes satellite data interacting with a secondary geomorphometric variable (the Illumination Factor), that is based on direct solar beam angle. The soil/vegetation index, suggested in the present study, showed a better performance when compared with other vegetation index to estimate canopy closure. The modeled biomass shows evident biophysical distinction among different forest succession stages

<p dir="ltr">Forest ecosystems play a pivotal role in climate change mitigation. Sustainable forest management practices necessitate accurate quantification of forest aboveground carbon stocks (FACS). In the first part of this study, I compared the 13-year changes in FACS across three silvicultural systems, including even-aged management (EA), uneven-aged management (UEA), and non-harvested controls (NH), in Indiana's hardwood forests. Forest stands within each silvicultural system were assigned with one of the six treatment types, including clearcutting, shelterwood, or prescribed burning for EA, single-tree selection or patch cutting for UEA, or untreated controls. From 2008 to 2021, the FACS of the study area exhibited an increase from 91.5 ± 9.0 Mg/ha to 115.3 ± 2.1 Mg/ha. Single-tree selection, shelterwood, and prescribed burning were found to have minimal impacts on FACS. However, clearcutting and patch cutting resulted in a significant reduction in FACS, with subsequent recovery reaching only 30-37% of their pre-treatment levels after 13 years. Further investigations may use long-term inventory data to analyze the chronic recovery patterns on these sites.</p><p dir="ltr">In the second part of this study, I evaluated the feasibility of using 3DEP LiDAR in conjunction with the random forest algorithm for multiscale FACS prediction. It was found that the stand-scale model outperformed the plot-scale model, primarily due to a stand’s higher positioning accuracy and reduced boundary effects than the plot-scale model. This led to a reduction in RMSE from 25.43 Mg/ha (26%) to 16.74 Mg/ha (20%). Moreover, the stand-scale model exhibited robust landscape-level prediction performance even in scenarios where point density decreased from 7.7 points/m² to 2.0 points/m². However, the partitioned model including solely clearcut and patch sites produced a higher RMSE of 59% (17.82 Mg/ha) due to inaccurate LiDAR return classification and biased canopy height metrics extraction. Future research should delve into the mechanisms of point cloud classification to improve the FACS prediction accuracy for clearcut forest monitoring.</p><p dir="ltr">Overall, this thesis contributed to a deeper understanding of carbon dynamics in managed hardwood forests, highlighted the potential of using LiDAR technology for improved landscape-level carbon monitoring, and informed the decision-making processes in the context of climate change mitigation.</p><p><br></p>

En Europe, la prairie occupe près de 40% de la surface agricole utile et fournit un ensemble de services environnementaux et agricoles, tout en constituant un réservoir de diversité végétale et animale. Cet écosystème herbacé, plurispécifique et multifonctionnel est un système biologique complexe qui fait interagir l’atmosphère, la végétation et le sol, via les cycles biogéochimiques, notamment ceux du carbone et de l’azote. Motivées par le maintien des biens et services des prairies face aux changements climatiques et atmosphériques, les recherches actuelles sur l’écosystème prairial s’attachent à étudier l’évolution des processus clés du système prairial (i .e. production, échanges gazeux, changements d’espèce) sous changement climatique complexe. Ce projet de thèse a pour objectif d’étudier in situ les impacts des principales composantes du changement climatique (température de l’air, précipitations, concentration atmosphérique en gaz carbonique) sur des prairies extensives de moyenne montagne. Nous cherchons à mettre en évidence les changements de structure et de fonctionnement de l’écosystème prairial sous l’influence d’un scénario de changement climatique prévu à l’horizon 2080 pour le centre de la France. Ce scénario (ACCACIA A2) prévoit une augmentation de 3.5°C des températures de l’air, une augmentation des concentrations atmosphériques en CO2 de 200 ppm et une réduction des précipitations estivales de 20 %. Nos résultats indiquent qu’à moyen terme (trois ans de traitements expérimentaux) le réchauffement a des effets néfastes sur la production annuelle du couvert végétal. L’effet bénéfique d’une élévation des teneurs en CO2 sur la production aérienne n’apparaît qu’à partir de la troisième année. La richesse spécifique (nombre d’espèces) et les indices de diversité taxonomique n’ont pas montré de variations significatives sous changement climatique. Cependant après trois années de réchauffement, l’abondance des graminées semble être altérée. Contrairement à la production, les traits sont plus affectés par la concentration en CO2 élevée que par le réchauffement. Après trois ans de traitements, des mesures d’échanges gazeux (CO2) à l’échelle du couvert végétal pendant la saison de croissance ont montré un effet négatif du réchauffement sur l’activité photosynthétique du couvert et une acclimatation de la photosynthèse au cours de la saison de croissance sous CO2 élevé. Ces tendances ont aussi été trouvées sur la photosynthèse foliaire d’une des espèces dominantes du couvert (Festuca arundinacea). L’effet négatif direct du réchauffement à l’échelle foliaire semble être associé à une diminution des sucres dans les limbes. L’acclimatation à l’enrichissement enCO2 à l’échelle foliaire, quant à elle, semble être indirectement dépendante du statu hydrique du sol. Notre étude a aussi porté sur l’analyse des échanges gazeux sol-atmosphère d’un des principaux gaz à effet de serre trace des prairies, l’oxyde nitreux (N2O). Malgré une forte variabilité inter- et intra- annuelle, les flux de N2O semblent être favorisés sous réchauffement. L’augmentation de la température affecte aussi positivement les taux de nitrification et leur pool microbien associé (AOB), et les rejets de N2O via dénitrification. De plus, les flux de N2O mesurés aux champs ont montré une corrélation plus forte à la taille des populations microbiennes (nitrifiantes et dénitrifiantes) en traitement réchauffé qu’en traitement témoin. En conclusion, la température semble être le facteur principal dans les réponses de cette prairie aux changements climatiques futurs. De plus, nos résultats suggèrent que le fonctionnement (production, émissions de N2O) des prairies extensives de moyenne montagne est plus vulnérable aux changements climatiques que la structure de la communauté végétale. / In France, the grassland ecosystem represents an important part of the total of agricultural landscape and provides important economic and ecological services. This multifunctional ecosystem is a complex biological system where atmosphere, plants and soil interact together,via the biogeochemical cycles (particularly carbon and nitrogen cycles). In order to maintain goods and services from grasslands in changing environmental conditions, current research on the grassland ecosystem focus on the evolution of key grassland processes (i.e. production,gaseous exchanges, biodiversity) under multiple and simultaneous climate change.This thesis addresses the impacts of the three main climate change drivers (air temperature, precipitation and atmospheric carbon dioxide concentrations) on an extensively-managed upland grassland in situ. We investigated changes in ecosystem function and structure under the influence of a projected climate scenario for 2080 for central France. This scenario (ACCACIA A2) comprises : air warming of 3.5°C, 20 % reduction of the summer precipitation and an increase of 200 ppm in atmospheric carbon dioxide (CO2).Our results indicate that in the medium term (after three years of experimental treatments), warming had negative effects on the annual aboveground production. Elevated CO2 had no significant effects on aboveground production initially, but positive effects on biomass from the third year onwards. Species richness and the indices of species diversity did not show significant differences in response to climate change, but warming was associated with a decline in grass abundance after three years. Contrary to biomass production, plant traits showed a stronger response to elevated CO2 than to warming. After three years of study, canopy-level photosynthesis showed a negative effect of warming but an acclimation to elevated CO2 during the growing season. This pattern was also found for leaf-level photosynthetic rates measured on a dominant grass species (Festuca arundinacea). For Festuca, the direct negative effect of warming was associated with a decrease in leaf fructan metabolism. In contrast, the photosynthetic acclimation under elevated CO2 observed in Festuca seemed closely linked to the indirect effect of soil water content. Our study also examined effects of climate change on one of the main trace greenhouse gases in grasslands, nitrous oxide (N2O). During our study, N2O fluxes showed significant inter-and intra-annual variability. Nevertheless, mean annual N2O fluxes increased in response to warming. Warming had a positive effect on nitrification rates, denitrification rates and the population size of nitrifying bacteria (AOB). Furthermore, field N2O fluxes showed a stronger correlation with the microbial population size in the warmed compared with the control treatment. Overall, warming seems to be the main factor driving ecosystem responses to projected climate change conditions for this cool, upland grassland. In addition, our results suggest that grassland function (aboveground production, N2O emissions) are more vulnerable to complex climate change than grassland community structure for our study system.