Chironomidae from Eastern Amazon: Understanding the differences of land-use on functional feeding groups

Deforestation for agricultural purposes is the most dangerous human action against the conservation of the Brazilian Amazon Forest; its rates reached almost 20% of the original forested area. Many studies have been conducted on Chironomidae systematics and ecology over the Amazon biome, but most concerned the Central Amazon, while little is known about Chironomidae diversity and the effects of land development and agriculture intensification on the aquatic biota from Eastern Brazilian Amazon. The present study analyzed the effects of different land-use and land-cover on Chironomidae assemblages. Land-Use and Land-Cover (LULC) at the riparian zone were assessed from satellite imagery and three categories were defined: Forest, Secondary (Capoeira) and Agriculture. Ten catchments were selected: two for Forest, five for Agriculture and three for Secondary. For each catchment we characterized habitat and sampled insects. We hypothesized that i) the assemblage taxonomic richness will change across different land uses on riparian zones and ii) feeding functionality is a better information than taxonomic resolution to show the importance of LULC upon stream. A total of 20,884 individuals were sampled from the streams, abundance was higher in Agriculture streams. Corynoneura (18.4%), Pentaneura (14.6%) and Rheotanytarus (14.0%) were the most abundant genera in Agriculture streams; Corynoneura (17.8%), Caladomyia (13.6%), Paratanytarsus (13.1%) and Beardius (10.9%) dominated Forest streams; Goeldichironomus (25.9%), Rheotanytarus (17.6%) and Polypedilum (13.2%) dominated Capoeira streams. Regarding FFG, gatherers were the most numeric abundant in Forest (50.3%), followed by filterers (38.7%), predators (6.6%) and shredders (4.2%). In Capoeira, filterers were the main FFG (61.1%), gatherers (27.9%), predators (7.7%) and shredders (3.3%). In Agriculture streams, predators, filterers and gatherers had close numeric participation, 34.9%, 32.4% and 32.2%, respectively. Shredders performed a smaller fraction (0.4%). In Forest and Agriculture, scrapers participation was under 0.2%, while it was absent at Capoeira. Permutation tests showed significant differences among assemblages, based on numerical abundance of genera and on functional feeding group data. Even though, shredders showed a discrete participation in all three LULC, it was statistically significant higher at Forest streams when compared to Agriculture ones. Our study was able to demonstrate taxonomic differences of all LULC analyzed and it also showed the importance in considering the feeding behavior to understand the effects of land-use and land-covers changes.

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Ecosystem Structure throughout the Brazilian Amazon from Landsat Observations and Automated Spectral Unmixing

Earth Interactions ◽

10.1175/ei134.1 ◽

2005 ◽

Vol 9 (7) ◽

pp. 1-31 ◽

Cited By ~ 35

Author(s):

Gregory P. Asner ◽

David E. Knapp ◽

Amanda N. Cooper ◽

Mercedes M. C. Bustamante ◽

Lydia P. Olander

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Brazilian Amazon ◽

Canopy Gap ◽

Amazon Forest ◽

Ecosystem Structure ◽

Gap Fraction ◽

Cerrado Savanna ◽

Spectral Mixture

Abstract The Brazilian Amazon forest and cerrado savanna encompasses a region of enormous ecological, climatic, and land-use variation. Satellite remote sensing is the only tractable means to measure the biophysical attributes of vegetation throughout this region, but coarse-resolution sensors cannot resolve the details of forest structure and land-cover change deemed critical to many land-use, ecological, and conservation-oriented studies. The Carnegie Landsat Analysis System (CLAS) was developed for studies of forest and savanna structural attributes using widely available Landsat Enhanced Thematic Mapper Plus (ETM+) satellite data and advanced methods in automated spectral mixture analysis. The methodology of the CLAS approach is presented along with a study of its sensitivity to atmospheric correction errors. CLAS is then applied to a mosaic of Landsat images spanning the years 1999–2001 as a proof of concept and capability for large-scale, very high resolution mapping of the Amazon and bordering cerrado savanna. A total of 197 images were analyzed for fractional photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and bare substrate covers using a probabilistic spectral mixture model. Results from areas without significant land use, clouds, cloud shadows, and water bodies were compiled by the Brazilian state and vegetation class to understand the baseline structural typology of forests and savannas using this new system. Conversion of the satellite-derived PV data to woody canopy gap fraction was made to highlight major differences by vegetation and ecosystem classes. The results indicate important differences in fractional photosynthetic cover and canopy gap fraction that can now be accounted for in future studies of land-cover change, ecological variability, and biogeochemical processes across the Amazon and bordering cerrado regions of Brazil.

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Hydrological regime, water availability and land use/land cover change impact on the water balance in a large agriculture basin in the Southern Brazilian Amazon

Journal of South American Earth Sciences ◽

10.1016/j.jsames.2021.103224 ◽

2021 ◽

Vol 108 ◽

pp. 103224

Author(s):

Tárcio Rocha Lopes ◽

Cornélio Alberto Zolin ◽

Rafael Mingoti ◽

Laurimar Gonçalves Vendrusculo ◽

Frederico Terra de Almeida ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Water Balance ◽

Land Cover Change ◽

Water Availability ◽

Hydrological Regime ◽

Brazilian Amazon ◽

Land Use Land Cover ◽

Change Impact

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Assessment of land cover on soil erosion in Lam Phra Phloeng watershed by USLE model

MATEC Web of Conferences ◽

10.1051/matecconf/201819202017 ◽

2018 ◽

Vol 192 ◽

pp. 02017 ◽

Cited By ~ 1

Author(s):

Jatuwat Wattanasetpong ◽

Uma Seeboonruang ◽

Uba Sirikaew ◽

Walter Chen

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Cover ◽

Soil Loss ◽

Land Development ◽

Developed Countries ◽

Surface Erosion ◽

Agricultural Field ◽

Land Cover Data

Soil loss due to surface erosion has been a global problem not just for developing countries but also for developed countries. One of the factors that have greatest impact on soil erosion is land cover. The purpose of this study is to estimate the long-term average annual soil erosion in the Lam Phra Phloeng watershed, Nakhon Ratchasima, Thailand with different source of land cover by using the Universal Soil Loss Equation (USLE) and GIS (30 m grid cells) to calculate the six erosion factors (R, K, L, S, C, and P) of USLE. Land use data are from Land Development Department (LDD) and ESA Climate Change Initiative (ESA/CCI) in 2015. The result of this study show that mean soil erosion by using land cover from ESA/CCI is less than LDD (29.16 and 64.29 ton/ha/year respectively) because soil erosion mostly occurred in the agricultural field and LDD is a local department that survey land use in Thailand thus land cover data from this department have more details than ESA/CCI.

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PALSAR-2/ALOS-2 AND OLI/LANDSAT-8 DATA INTEGRATION FOR LAND USE AND LAND COVER MAPPING IN NORTHERN BRAZILIAN AMAZON

Boletim de Ciências Geodésicas ◽

10.1590/s1982-21702018000200017 ◽

2018 ◽

Vol 24 (2) ◽

pp. 250-269 ◽

Cited By ~ 5

Author(s):

João Arthur Pompeu Pavanelli ◽

João Roberto dos Santos ◽

Lênio Soares Galvão ◽

Maristela Xaud ◽

Haron Abrahim Magalhães Xaud

Keyword(s):

Land Use ◽

Land Cover ◽

Brazilian Amazon ◽

Landsat 8 ◽

Array Type ◽

Complex Landscape ◽

Hybrid Classification ◽

L Band ◽

Thematic Accuracy ◽

Better Than

Abstract: In northern Brazilian Amazon, the crops, savannahs and rainforests form a complex landscape where land use and land cover (LULC) mapping is difficult. Here, data from the Operational Land Imager (OLI)/Landsat-8 and Phased Array type L-band Synthetic Aperture Radar (PALSAR-2)/ALOS-2 were combined for mapping 17 LULC classes using Random Forest (RF) during the dry season. The potential thematic accuracy of each dataset was assessed and compared with results of the hybrid classification from both datasets. The results showed that the combination of PALSAR-2 HH/HV amplitudes with the reflectance of the six OLI bands produced an overall accuracy of 83% and a Kappa of 0.81, which represented an improvement of 6% in relation to the RF classification derived solely from OLI data. The RF models using OLI multispectral metrics performed better than RF models using PALSAR-2 L-band dual polarization attributes. However, the major contribution of PALSAR-2 in the savannahs was to discriminate low biomass classes such as savannah grassland and wooded savannah.

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Land Use and Land Cover Mapping in the Brazilian Amazon Using Polarimetric Airborne P-Band SAR Data

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2008.2000630 ◽

2008 ◽

Vol 46 (10) ◽

pp. 2956-2970 ◽

Cited By ~ 39

Author(s):

Corina da Costa Freitas ◽

Luciana de Souza Soler ◽

Sidnei JoÃo Siqueira Sant'Anna ◽

Luciano Vieira Dutra ◽

JoÃo Roberto dos Santos ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Brazilian Amazon ◽

Land Cover Mapping ◽

Sar Data

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ALTERAÇÃO NA COBERTURA FLORESTAL DA REGIÃO NOROESTE DA AMAZÔNIA MATOGROSSENSE

Nativa ◽

10.31413/nativa.v7i5.7248 ◽

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.

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Impacts of Rapid Changes of Land Cover and Intensive Human Activities on Avarga Toson Lake Area, Mongolia

Sustainability ◽

10.3390/su12156070 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6070

Author(s):

Urtnasan Mandakh ◽

Danzanchadav Ganbat ◽

Bayartungalag Batsaikhan ◽

Sainbayar Dalantai ◽

Zolzaya Adiya ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Surface Area ◽

Human Activities ◽

Water Surface ◽

Land Development ◽

Water Area ◽

Lake Area ◽

Surrounding Area ◽

Water Surface Area

Avarga Toson Lake and its surrounding area are very important for people, wildlife, and animals in Delgerkhaan Soum of Khentii Province in Eastern Mongolia. Some research has been conducted so as to explore the medical nature and characteristics of the lake and its surrounding area. However, the adverse effects of land use have neither been studied nor reported. The fact that the water catchment area is shrinking evidences clearly that findings of various real-time studies must be used effectively in the long-term by the local government and relevant authorities in order to take immediate remedial measures. Our study focused on land cover changes occurring as a result of human activities in the area, using a Landsat imageries and water indices approach to estimate the changes of land use and land cover. The aims of this study were to assess the land use and cover change that occurred between 1989 and 2018 and to define the impacting factors on the changes of water surface area in Avarga Toson Lake area, Mongolia. Findings revealed that the water surface area has decreased by 34.1% in the past 30 years. The lake water area had the weakest, positive correlation with temperature and precipitation. We did not find any indicators suggesting a relationship between lake area and climate variables. In contrast, the area was slightly correlated with socio-economic variables, such as Toson Lake area with the number of visitors (R2 = 0.89) and Burd Lake area the with number of livestocks (R2 = 0.75), respectively. Therefore, the main conclusion of this paper is that socioeconomic factors driven by land use change, policy, and institutional failure together with the existing pressure on the lake may amplify their effect of the water surface area decreasing. Additionally, even if policy adoption is relatively sufficient in the country, the public institutional capacity to implement a successful sustainable land management model regarding land access, land development, land resources protection, land market, and investments in infrastructure remains very limited.

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