Dynamic of Fires in the Cerrado of Maranhão State, North-Eastern Brazil

Fires have a central role in carbon emissions in tropical regions, directly affecting the carbon cycle and the health of the population. In the Cerrado, fire occurs naturally and by human influence, used in the productive process of agriculture and livestock. In this context the aim of this paper was to characterize the spatiotemporal dynamics of fires in the Brazilian Savannas, also known as Cerrado, in the state of Maranhão (North-eastern Brazil). We used datasets from remote sensing and INMET weather stations. Data were processed and tabulated. Spatial and regression analyses were performed. Our results evidenced that the fires are modulated by the seasonality of the rainfall regime, being able to be influenced also by variations of temperature and moisture of the air. This region was affected in 2007 and 2012 by droughts that caused the expressive increase in the number of fires. In this region, deforestation is not directly linked to the occurrence of fires. The savanna formations were identified as the most susceptible to the occurrence of fires, since they account for a large part of the recurrences and occurrences of fires in this region.As queimadas têm um papel central nas emissões de carbono nas regiões tropicais, afetando diretamente o ciclo do carbono e a saúde da população. No Cerrado, o fogo ocorre naturalmente e por influência humana, utilizado no processo produtivo da agricultura e pecuária. Nesse contexto o objetivo deste trabalho foi caracterizar a dinâmica espaço-temporal das queimadas no Cerrado do estado do Maranhão. Para isso, foram utilizados dados derivados de produtos de sensoriamento remoto e de estações meteorológicas do INMET. Os dados foram processados e tabulados. Análises espaciais e de regressão foram realizadas. Os resultados evidenciaram que as queimadas são moduladas pela sazonalidade do regime de chuva, podendo ser influenciada também por variações de temperatura e umidade do ar. Essa região foi afetada nos anos de 2007 e 2012 por secas que ocasionaram o aumento expressivo no número de queimadas. Nessa região, o desmatamento não está ligado diretamente à ocorrência de queimadas. A vegetação de formações savânicas foram identificadas como as mais suscetíveis à ocorrência de queimadas, por totalizarem grande parte das recorrências e ocorrências de queimadas nessa região

Floristics and above-ground biomass (AGB) in Peatlands in Peruvian Lowland Amazonia, Loreto – Peru

Amazonian forests comprise almost 10% of stored carbon (C) in the world’s land ecosystems. This C is held both in above-ground biomass (AGB) and in the soil. AGB in an individual plant depends on plant size, often measured in trees as height (H) and diameter (D), and the density of plant tissues, often approximated in trees by wood density (WD). Soil C storage depends on the balance between inputs from AGB due to mortality and senescence and outputs due to decay and erosion. Peatlands, wetlands recently described in northern Peruvian Amazonia, show unusually high rates of soil C accumulation. For these habitats information on C budget contributions from peatland plants is unavailable. In this study I estimated AGB in various peatlands of northern Peruvian Amazonia, and asked why some of these peatlands store more AGB than others. I first set out to estimate the relative contribution of inter- and intra-specific variation to variation in AGB among individual peatland trees. I found that 80% of the variation in AGB among individual trees was due to inter-specific variation. Then I assessed the extent to which the three traits that determine AGB (i.e., D, H and WD) contribute to inter- and intra-specific variation in AGB among peatland trees. I found variation in D and the interaction between D and H contributed most to inter- and intra-specific variation in AGB among trees. Last, I estimated the extent to which variation in AGB among peatland locations was due to variation in species composition, stem density and intra-specific variation in AGB. I found that species composition and intra-specific variation, but not stem density, explained nearly equal amounts of variation in AGB among peatland locations. In summary, detailed knowledge of tree size can provide good estimates of species level biomass estimates in the peatlands of northern Peruvian Amazonia. Additionally, what species are present, as well as how their biomass varies (intra-specifically) from site to site drives AGB variation among peatland locations

Fire Responses to the 2010 and 2015/2016 Amazonian Droughts

Extreme droughts in Amazonia cause anomalous increase in fire occurrence, disrupting the stability of environmental, social, and economic systems. Thus, understanding how droughts affect fire patterns in this region is essential for anticipating and planning actions for remediation of possible impacts. Focused on the Brazilian Amazon biome, we investigated fire responses to the 2010 and 2015/2016 Amazonian droughts using remote sensing data. Our results revealed that the 2015/2016 drought surpassed the 2010 drought in intensity and extent. During the 2010 drought, we found a maximum area of 846,800 km2 (24% of the Brazilian Amazon biome) with significant (p ≤ 0.05) rainfall decrease in the first trimester, while during the 2015/2016 the maximum area reached 1,702,800 km2 (47% of the Brazilian Amazon biome) in the last trimester of 2015. On the other hand, the 2010 drought had a maximum area of 840,400 km2 (23% of the Brazilian Amazon biome) with significant (p ≤ 0.05) land surface temperature increase in the first trimester, while during the 2015/2016 drought the maximum area was 2,188,800 km2 (61% of the Brazilian Amazon biome) in the last trimester of 2015. Unlike the 2010 drought, during the 2015/2016 drought, significant positive anomalies of active fire and CO2 emissions occurred mainly during the wet season, between October 2015 and March 2016. During the 2010 drought, positive active fire anomalies resulted from the simultaneous increase of burned forest, non-forest vegetation and productive lands. During the 2015/2016 drought, however, this increase was dominated by burned forests. The two analyzed droughts emitted together 0.47 Pg CO2, with 0.23 Pg CO2 in 2010, 0.15 Pg CO2 in 2015 and 0.09 Pg CO2 in 2016, which represented, respectively, 209%, 136%, 82% of annual Brazil’s national target for reducing carbon emissions from deforestation by 2017 (approximately 0.11 Pg CO2 year-1 from 2006 to 2017). Finally, we anticipate that the increase of fires during the droughts showed here may intensify and can become more frequent in Amazonia due to changes in climatic variability if no regulations on fire use are implemented

Dinâmica de incêndios florestais e alterações biofísicas na Amazônia e Cerrado brasileiros a partir de séries temporais de sensoriamento remoto

Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós-Graduação em Geografia, 2019.Os biomas brasileiros se adaptaram a diferentes padrões de presença ou ausência do fogo. Dados derivados de sensoriamento remoto têm sido uma das principais bases para a detecção de incêndios florestais e os danos na estrutura da vegetação, especialmente com o desenvolvimento de sensores com alta resolução temporal e espectral, e o estabelecimento de longas séries contínuas. Nesse sentido, esta tese buscou aprofundamento em três pontos: (1) Qual a potencialidade de produtos de sensoriamento remoto para a descrição da dinâmica do fogo no Brasil? (2) Como detectar cicatrizes de queimadas a partir de séries temporais em ambientes amazônicos?; e por fim (3) Quais os danos na vegetação resultantes da alteração do regime histórico do fogo e como podem ser quantificados por sensoriamento remoto? Para ampliar o conhecimento sobre essas questões foram utilizados diversos produtos derivados dos sensores Moderate Resolution Imaging Spectroradiometer (MODIS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) e Operational Land Imager (OLI), além de diversos dados espaciais, em três escalas: uma para todo o território nacional, uma área específica do Cerrado e duas áreas específicas da Amazônia. A metodologia básica consistiu na análise de séries temporais MODIS para detecção e quantificação dos efeitos do fogo. Os resultados permitiram concluir que: (1) Os produtos globais MODIS de detecção de cicatrizes de queimadas apresentaram altas taxas de erros de omissão no Brasil, superiores a 78% em média no território nacional, sendo seu uso recomendado apenas para análises regionais ou globais. Os produtos de queimadas apresentaram as menores acurácias nos biomas dos Pampas, Amazônia e Mata Atlântica e as maiores acurácias nos biomas do Cerrado e da Caatinga. Apesar desta limitação, o produto MCD64 permitiu descrever o regime do fogo no país, as principais regiões de ocorrência e a influência da umidade e classe de vegetação neste padrão. Foram estabelecidas como limite para a ação do fogo, as zonas sem estiagem, como o Oeste da Amazônia e litoral leste do Brasil, assim como as áreas do semiárido nordestino. (2) Dentre os métodos analisados de diferença sazonal e normalização temporal, a normalização pela média da banda espectral do Infravermelho Próximo foi responsável pela maior acurácia na detecção de cicatrizes de queimadas na Amazônia, retificando a utilização de alguns índices especializados originalmente para vegetações temperadas, como o Normalized Burn Ratio (NBR). Outros métodos analisados, como a diferença sazonal e normalização por z-score, apresentaram melhor acurácia que imagens originais, mas inferior em comparação com a normalização pela média. (3) A alteração da recorrência do fogo teve influência direta no padrão biofísico e fenológico da vegetação nas áreas de estudo na Amazônia e no Cerrado. As variáveis de produtividade primária bruta e albedo apresentaram baixa representatividade espacial. As mudanças com maior inclinação da tendência, do Enhanced Vegetation Index (EVI) e temperatura superficial, foram tanto relacionadas com a recorrência do fogo, quanto com a classe de uso da vegetação, como nas terras indígenas. A inclinação da tendência, no EVI e temperatura superficial, foi maior na área do Cerrado, reforçando a necessidade urgente de conservação deste bioma. A pesquisa atestou a importância de dados de sensoriamento remoto para avaliação da dinâmica do fogo e dos seus efeitos na vegetação. A utilização de séries temporais do sensor MODIS permitiu tanto identificar as áreas queimadas com maior acurácia que outros produtos disponíveis, quanto quantificar as fragilidades da vegetação relacionadas ao padrão de fogo atual.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).Brazilian biomes have adapted to different patterns of presence or absence of fire. Data derived from remote sensing have been one of the main techniques for the detection of forest fires and damage to vegetation structure, especially with the development of high temporal and spectral resolution sensors and the establishment of long continuous series. Thus, we intend to focus on three points in this thesis: (1) What is the potential of remote sensing products for the description of fire dynamics in Brazil? (2) How to detect burn scars from remote sensing time series in Amazonian environments? And finally (3) What damages in the vegetation resulting from the alteration of the historical fire regime and how can they be quantified by remote sensing? In order to increase the knowledge about these issues, several products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors were used, in addition to diverse spatial data, in three scales: one for the whole national territory, one specific area of the Cerrado and two specific areas of the Amazon. The basic methodology consisted of the analysis of MODIS time series for the detection and quantification of fire effects. The results allowed to conclude that: (1) MODIS global burned area products presented high omission errors rates in Brazil, higher than 78% on average in the national territory, and their use is recommended only for regional or global analyzes. The burned area products showed the lowest value in the biomes of the Pampas, Amazon Forest and Atlantic Forest, and the highest values in the biomes of the Cerrado and Caatinga. In spite of this limitation, the product MCD64 allowed to describe the fire regime in the country, the main regions of occurrence and the influence of moisture and vegetation class in this pattern. Were established as a limit for the action of the fire the areas without drought, such as the Western Amazon and the east coast of Brazil, as well as areas with low availability of rainfall and fuel, such as the semi-arid in the Northeast. (2) Among the analyzed methods of seasonal difference and temporal normalization, the normalization of the Near Infrared spectral band by the zero-mean, was responsible for the greater accuracy in the detection of burn scars in the Amazon region, rectifying the use of some indices originally specialized for temperate vegetation, such as the Normalized Burn Ratio (NBR). Other methods analyzed, such as the seasonal difference and z-score normalization, showed better accuracy than original images, but lower than normalization by the zero-mean. (3) The alteration of fire recurrence had a direct influence on the biophysical and phenological pattern of vegetation the study areas of Amazon and Cerrado. The variables of gross primary productivity and albedo showed low spatial representativeness. The changes with higher trend slope, of Enhanced Vegetation Index (EVI) and surface temperature, were related both to fire recurrence and to the vegetation use class, as in indigenous lands. The slope of the trend in EVI and surface temperature was higher in the Cerrado area, reinforcing the urgent need for conservation of this biome. The research attested the importance of remote sensing data for the evaluation of fire dynamics and its effects on vegetation. The use of MODIS time series allowed both identifying the burned areas with greater accuracy than other available products, and quantifying the fragilities of the vegetation related to the current fire pattern

Biome-Scale Forest Properties in Amazonia Based on Field and Satellite Observations

Amazonian forests are extremely heterogeneous at different spatial scales. This review intends to present the large-scale patterns of the ecosystem properties of Amazonia, and focuses on two parts of the main components of the net primary production: the long-lived carbon pools (wood) and short-lived pools (leaves). First, the focus is on forest biophysical properties, and secondly, on the macro-scale leaf phenological patterns of these forests, looking at field measurements and bringing into discussion the recent findings derived from remote sensing dataset. Finally, I discuss the results of the three major droughts that hit Amazonia in the last 15 years. The panorama that emerges from this review suggests that slow growing forests in central and eastern Amazonia, where soils are poorer, have significantly higher above ground biomass and higher wood density, trees are higher and present lower proportions of large-leaved species than stands in northwest and southwest Amazonia. However, the opposite pattern is observed in relation to forest productivity and dynamism, which is higher in western Amazonia than in central and eastern forests. The spatial patterns on leaf phenology across Amazonia are less marked. Field data from different forest formations showed that new leaf production can be unrelated to climate seasonality, timed with radiation, timed with rainfall and/or river levels. Oppositely, satellite images exhibited a large-scale synchronized peak in new leaf production during the dry season. Satellite data and field measurements bring contrasting results for the 2005 drought. Discussions on data processing and filtering, aerosols effects and a combined analysis with field and satellite images are presented. It is suggested that to improve the understanding of the large-scale patterns on Amazonian forests, integrative analyses that combine new technologies in remote sensing and long-term field ecological data are imperative

From models to data: understanding biodiversity patterns from environmental DNA data

La distribution de l'abondance des espèces en un site, et la similarité de la composition taxonomique d'un site à l'autre, sont deux mesures de la biodiversité ayant servi de longue date de base empirique aux écologues pour tenter d'établir les règles générales gouvernant l'assemblage des communautés d'organismes. Pour ce type de mesures intégratives, le séquençage haut-débit d'ADN prélevé dans l'environnement (" ADN environnemental ") représente une alternative récente et prometteuse aux observations naturalistes traditionnelles. Cette approche présente l'avantage d'être rapide et standardisée, et donne accès à un large éventail de taxons microbiens jusqu'alors indétectables. Toutefois, ces jeux de données de grande taille à la structure complexe sont difficiles à analyser, et le caractère indirect des observations complique leur interprétation. Le premier objectif de cette thèse est d'identifier les modèles statistiques permettant d'exploiter ce nouveau type de données afin de mieux comprendre l'assemblage des communautés. Le deuxième objectif est de tester les approches retenues sur des données de biodiversité du sol en forêt amazonienne, collectées en Guyane française. Deux grands types de processus sont invoqués pour expliquer l'assemblage des communautés d'organismes : les processus "neutres", indépendants de l'espèce considérée, que sont la naissance, la mort et la dispersion des organismes, et les processus liés à la niche écologique occupée par les organismes, c'est-à-dire les interactions avec l'environnement et entre organismes. Démêler l'importance relative de ces deux types de processus dans l'assemblage des communautés est une question fondamentale en écologie ayant de nombreuses implications, notamment pour l'estimation de la biodiversité et la conservation. Le premier chapitre aborde cette question à travers la comparaison d'échantillons d'ADN environnemental prélevés dans le sol de diverses parcelles forestières en Guyane française, via les outils classiques d'analyse statistique en écologie des communautés. Le deuxième chapitre se concentre sur les processus neutres d'assemblages des communautés. S.P. Hubbell a proposé en 2001 un modèle décrivant ces processus de façon probabiliste, et pouvant être utilisé pour quantifier la capacité de dispersion des organismes ainsi que leur diversité à l'échelle régionale simplement à partir de la distribution d'abondance des espèces observée en un site. Dans ce chapitre, les biais liés à l'utilisation de l'ADN environnemental pour reconstituer la distribution d'abondance des espèces sont discutés, et sont quantifiés au regard de l'estimation des paramètres de dispersion et de diversité régionale. Le troisième chapitre se concentre sur la manière dont les différences non-aléatoires de composition taxonomique entre sites échantillonnés, résultant des divers processus d'assemblage des communautés, peuvent être détectées, représentées et interprétés. Un modèle statistique conçu à l'origine pour classifier les documents à partir des thèmes qu'ils abordent est ici appliqué à des échantillons de sol prélevés selon une grille régulière au sein d'une grande parcelle forestière. La structure spatiale de la composition taxonomique des microorganismes est caractérisée avec succès et reliée aux variations fines des conditions environnementales au sein de la parcelle. Les implications des résultats de la thèse sont enfin discutées. L'accent est mis en particulier sur le potentiel des modèles thématique (" topic models ") pour la modélisation des données de biodiversité issues de l'ADN environnemental.Integrative patterns of biodiversity, such as the distribution of taxa abundances and the spatial turnover of taxonomic composition, have been under scrutiny from ecologists for a long time, as they offer insight into the general rules governing the assembly of organisms into ecological communities. Thank to recent progress in high-throughput DNA sequencing, these patterns can now be measured in a fast and standardized fashion through the sequencing of DNA sampled from the environment (e.g. soil or water), instead of relying on tedious fieldwork and rare naturalist expertise. They can also be measured for the whole tree of life, including the vast and previously unexplored diversity of microorganisms. Taking full advantage of this new type of data is challenging however: DNA-based surveys are indirect, and suffer as such from many potential biases; they also produce large and complex datasets compared to classical censuses. The first goal of this thesis is to investigate how statistical tools and models classically used in ecology or coming from other fields can be adapted to DNA-based data so as to better understand the assembly of ecological communities. The second goal is to apply these approaches to soil DNA data from the Amazonian forest, the Earth's most diverse land ecosystem. Two broad types of mechanisms are classically invoked to explain the assembly of ecological communities: 'neutral' processes, i.e. the random birth, death and dispersal of organisms, and 'niche' processes, i.e. the interaction of the organisms with their environment and with each other according to their phenotype. Disentangling the relative importance of these two types of mechanisms in shaping taxonomic composition is a key ecological question, with many implications from estimating global diversity to conservation issues. In the first chapter, this question is addressed across the tree of life by applying the classical analytic tools of community ecology to soil DNA samples collected from various forest plots in French Guiana. The second chapter focuses on the neutral aspect of community assembly. A mathematical model incorporating the key elements of neutral community assembly has been proposed by S.P. Hubbell in 2001, making it possible to infer quantitative measures of dispersal and of regional diversity from the local distribution of taxa abundances. In this chapter, the biases introduced when reconstructing the taxa abundance distribution from environmental DNA data are discussed, and their impact on the estimation of the dispersal and regional diversity parameters is quantified. The third chapter focuses on how non-random differences in taxonomic composition across a group of samples, resulting from various community assembly processes, can be efficiently detected, represented and interpreted. A method originally designed to model the different topics emerging from a set of text documents is applied here to soil DNA data sampled along a grid over a large forest plot in French Guiana. Spatial patterns of soil microorganism diversity are successfully captured, and related to fine variations in environmental conditions across the plot. Finally, the implications of the thesis findings are discussed. In particular, the potential of topic modelling for the modelling of DNA-based biodiversity data is stressed