scholarly journals Relationship between Genetic Variability and Land Use and Land Cover in Populations of Campomanesia adamantium (Myrtaceae)

Diversity ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 106 ◽  
Author(s):  
Bruno Crispim ◽  
Miklos Bajay ◽  
Adrielle de Vasconcelos ◽  
Thamiris Deo ◽  
Ramilla Braga ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Land Use ◽  
Genetic Variability ◽  
Land Cover ◽  
Aerial Images ◽  
Endemic Plant ◽  
Medicinal Uses ◽  
Mato Grosso ◽  
Diversity Studies ◽  
The Relationship

Campomanesia adamantium is an endemic plant of Cerrado biome that has potential for cultivation because its fruits have culinary and medicinal uses. However, genetic diversity studies using molecular markers with Cerrado species are scarce, and the inadequate extractive exploitation of fruits and the expansion of agricultural frontiers may also affect genetic variability. Therefore, studies in this field are of interest as they can provide sources for conservation and breeding programs. In this context, we investigated the genetic diversity of native populations of C. adamantium from different sites and the relationship between genetic variability and the land use and land cover of each site. A total of 207 plants were sampled in seven sites and characterized with seven polymorphic microsatellite markers. The use and coverage of land were mapped based on aerial images, and the land was classified into different categories. The genetic diversity was high in all populations, with low levels of differentiation due to allele sharing, mainly in Mato Grosso do Sul and Paraguay populations. The geographically closest populations were more genetically similar. The use and coverage of land indicated that intense agriculture promotes a significant decrease in genetic variability.

scholarly journals The Impact of Land Cover Change on Surface Energy and Water Balance in Mato Grosso, Brazil

2006 ◽  
Vol 10 (19) ◽  
pp. 1-17 ◽  
Author(s):  
Julia Pongratz ◽  
Lahouari Bounoua ◽  
Ruth S. DeFries ◽  
Douglas C. Morton ◽  
Liana O. Anderson ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Energy ◽  
Land Cover ◽  
Morphological Changes ◽  
Canopy Temperature ◽  
Surface Fluxes ◽  
Evergreen Forest ◽  
Wet Season ◽  
Mato Grosso ◽  
The Impact

Abstract The sensitivity of surface energy and water fluxes to recent land cover changes is simulated for a small region in northern Mato Grosso, Brazil. The Simple Biosphere Model (SiB2) is used, driven by biophysical parameters derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution, to compare the effects of different land conversion types. The mechanisms through which changes in vegetation alter surface fluxes of energy, momentum, water, and carbon are analyzed for both wet and dry seasons. It is found that morphological changes contribute to warming and drying of the atmosphere while physiological changes, particularly those associated with a plant’s photosynthetic pathway, counterbalance or exacerbate the warming depending on the type of conversion and the season. Furthermore, this study’s results indicate that initial clearing of evergreen and transition forest to bare ground increases canopy temperature by up to 1.7°C. For subsequent land use such as pasture or cropland, the largest effect is seen for the conversion of evergreen forest to C3 cropland during the wet season, with a 21% decrease of the latent heat flux and 0.4°C increase in canopy temperature. The secondary conversion of pasture to cropland resulted in slight warming and drying during the wet season driven mostly by the change in carbon pathway from C4 to C3. For all conversions types, the daily temperature range is amplified, suggesting that plants replacing forest clearing require more temperature tolerance than the trees they replace. The results illustrate that the effect of deforestation on climate depends not only on the overall extent of clearing but also on the subsequent land use type.

scholarly journals ALTERAÇÃO NA COBERTURA FLORESTAL DA REGIÃO NOROESTE DA AMAZÔNIA MATOGROSSENSE

Nativa ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 520
Author(s):  
Luani Rosa de Oliveira Piva ◽  
Rorai Pereira Martins Neto
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Forest Conversion ◽  
Landsat 8 ◽  
Amazon Forest ◽  
Landsat 8 Oli ◽  
Mato Grosso ◽  
The Past ◽  
Landsat 5 Tm

Nos últimos anos, a intensificação das atividades antrópicas modificadoras da cobertura vegetal do solo em território brasileiro vem ocorrendo em larga escala. Para fins de monitoramento das alterações da cobertura florestal, as técnicas de Sensoriamento Remoto da vegetação são ferramentas imprescindíveis, principalmente em áreas extensas e de difícil acesso, como é o caso da Amazônia brasileira. Neste sentido, objetivou-se com este trabalho identificar as mudanças no uso e cobertura do solo no período de 20 anos nos municípios de Aripuanã e Rondolândia, Noroeste do Mato Grosso, visando quantificar as áreas efetivas que sofreram alterações. Para tal, foram utilizadas técnicas de classificação digital de imagens Landsat 5 TM e Landsat 8 OLI em três diferentes datas (1995, 2005 e 2015) e, posteriormente, realizada a detecção de mudanças para o uso e cobertura do solo. A classificação digital apresentou resultados excelentes, com índice Kappa acima de 0,80 para os mapas gerados, indicando ser uma ferramenta potencial para o uso e cobertura do solo. Os resultados denotaram uma conversão de áreas florestais principalmente para atividades antrópicas agrícolas, na ordem de 472 km², o que representa uma perda de 1,3% de superfície de floresta amazônica na região de estudo.Palavras-chave: conversão de áreas florestais; uso e cobertura do solo; classificação digital; análise multitemporal. CHANGE IN FOREST COVER OF THE NORTHWEST REGION OF AMAZON IN MATO GROSSO STATE ABSTRACT: In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil’s land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuanã and Rondolândia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km², representing a loss of 1.3% of Amazon forest surface in the study region.Keywords: forest conversion; land use and land cover; digital classification; multitemporal analysis.

scholarly journals Genetic structure and diversity among individuals of Copaifera langsdorffii Desf. from Mato Grosso, Brazilian Amazon, using ISSR markers

2021 ◽  
Vol 10 (16) ◽  
pp. e187101623025
Author(s):  
Daniele Paula Maltezo ◽  
Julliane Dutra Medeiros ◽  
Ana Aparecida Bandini Rossi
Keyword(s):  
Genetic Diversity ◽  
Genetic Structure ◽  
Genetic Variability ◽  
Polymorphic Information Content ◽  
Issr Markers ◽  
Group Method ◽  
Mato Grosso ◽  
Copaifera Langsdorffii ◽  
Genetic Structure And Diversity ◽  
Issr Primers

The Amazon is the largest tropical forest in the world and is home to around 20% of all the biodiversity on the planet, among the species present in the Amazon is Copaifera langsdorffii, exploited mainly for the extraction of oil-resin and wood, often in ways incorrect, which can cause the loss of genetic variability. The aim of this study was to evaluate the genetic structure and diversity among individuals of C. langsdorffii located in Mato Grosso, Brazil, using ISSR markers. We sampled leaves from 27 adult individuals of C. langsdorffii, whose total genomic DNA was extracted. A total of 12 ISSR primers were used for the molecular characterization of the individuals. A grouping analysis was performed using the unweighted pair group method, Bayesian analysis and characterized by the genetic diversity. The genetic diversity among and within the groups was demonstrated by the AMOVA. As a result, 106 fragments were amplified and 98.11% were polymorphic. The polymorphic information content of each primer ranged from 0.45 to 0.81.  The dendrogram showed the formation of 4 distinct groups. The greatest genetic variability is found within the groups and not between them. The percentage of polymorphism, genetic dissimilarity values and genetic diversity indexes indicate that there is high genetic variability among Copaifera langsdorffii individuals, suggesting that ISSR primers were efficient in detecting polymorphism in this species and that the individuals have potential for compose programs aimed at the preservation of the species and the ability to integrate germplasm banks.

scholarly journals AN ITERATIVE INFERENCE PROCEDURE APPLYING CONDITIONAL RANDOM FIELDS FOR SIMULTANEOUS CLASSIFICATION OF LAND COVER AND LAND USE

2015 ◽  
Vol II-3/W5 ◽  
pp. 369-376 ◽  
Author(s):  
L. Albert ◽  
F. Rottensteiner ◽  
C. Heipke
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Random Fields ◽  
Conditional Random Fields ◽  
Main Idea ◽  
Aerial Images ◽  
Land Use Classification ◽  
Inference Procedure ◽  
Cover Layer

Land cover and land use exhibit strong contextual dependencies. We propose a novel approach for the simultaneous classification of land cover and land use, where semantic and spatial context is considered. The image sites for land cover and land use classification form a hierarchy consisting of two layers: a <i>land cover layer</i> and a <i>land use layer</i>. We apply Conditional Random Fields (CRF) at both layers. The layers differ with respect to the image entities corresponding to the nodes, the employed features and the classes to be distinguished. In the land cover layer, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Both CRFs model spatial dependencies between neighbouring image sites. The complex semantic relations between land cover and land use are integrated in the classification process by using contextual features. We propose a new iterative inference procedure for the simultaneous classification of land cover and land use, in which the two classification tasks mutually influence each other. This helps to improve the classification accuracy for certain classes. The main idea of this approach is that semantic context helps to refine the class predictions, which, in turn, leads to more expressive context information. Thus, potentially wrong decisions can be reversed at later stages. The approach is designed for input data based on aerial images. Experiments are carried out on a test site to evaluate the performance of the proposed method. We show the effectiveness of the iterative inference procedure and demonstrate that a smaller size of the super-pixels has a positive influence on the classification result.

scholarly journals Influence of Land Use and Land Cover Change on Land surface temperature

2021 ◽  
Vol 283 ◽  
pp. 01038
Author(s):  
Jing Sun ◽  
Jing He
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Rapid Urbanization ◽  
Lulc Changes ◽  
The Mean ◽  
The Relationship

The rapid urbanization process has recently led to significant land use and land cover (LULC) changes, thereby affecting the climate and the environment. The purpose of this study is to analyze the LULC changes in Hefei City, Anhui Province, and their relationship with land surface temperature (LST). To achieve this goal, multitemporal Landsat data were used to monitor the LULC and LST between 2005 and 2015. The study also used correlation analysis to analyze the relationship between LST, LULC, and other spectral indices (NDVI, NDBI, and NDWI). The results show that the built-up land has expanded significantly, transforming from 488.26 km2 in 2005 to 575.64 km2 in 2015. It further shows that the mean LST in Hefei city has increased from 284.0 K in 2005 to 285.86 K in 2015. The results also indicate that there is a positive correlation between LST and NDVI and NDBI, while there is a negative correlation between LST and NDWI. This means that urban expansion and reduced water bodies will lead to an increase in LST.

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