Márcio Rocha Francelino

ORCID: 0000-0001-8837-1372
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About
Contact & Profiles
Research Areas
  • Polar Research and Ecology
  • Soil Geostatistics and Mapping
  • Geology and Paleoclimatology Research
  • Geography and Environmental Studies
  • Climate change and permafrost
  • Geochemistry and Geologic Mapping
  • Cryospheric studies and observations
  • Soil erosion and sediment transport
  • Soil Management and Crop Yield
  • Agricultural and Food Sciences
  • Soil Carbon and Nitrogen Dynamics
  • Environmental and biological studies
  • Remote Sensing and LiDAR Applications
  • Soil and Land Suitability Analysis
  • Soil and Unsaturated Flow
  • Amazonian Archaeology and Ethnohistory
  • Microbial Community Ecology and Physiology
  • Land Use and Ecosystem Services
  • Conservation, Biodiversity, and Resource Management
  • Marine and coastal plant biology
  • Rural Development and Agriculture
  • Soil Moisture and Remote Sensing
  • Mineral Processing and Grinding
  • Ecology and Vegetation Dynamics Studies
  • Biocrusts and Microbial Ecology

Universidade Federal de Viçosa
2016-2025

Instituto Federal de Educação, Ciência e Tecnologia de Minas Gerais
2024

Universidade Federal de Ouro Preto
2023

Universidade Federal Rural do Rio de Janeiro
2011-2020

Instituto Federal Goiano
2010

Fundação de Apoio à Pesquisa do Estado da Paraíba
2009

Instituto Florestal
2009

Universidade Federal de Alagoas
2006-2007

José Alexandre Melo Demattê André Carnieletto Dotto Ariane F.S. Paiva Marcus Vinicius Sato Ricardo Simão Diniz Dalmolin and 60 more Maria do Socorro Bezerra de Araújo Elisângela B. da Silva Marcos Rafael Nanni Alexandre ten Caten Norberto Cornejo Noronha Marilusa Pinto Coelho Lacerda José Coelho de Araújo Filho Rodnei Rizzo Henrique Bellinaso Márcio Rocha Francelino Carlos Ernesto Gonçalves Reynaud Schaefer L. E. Vicente Uemeson José dos Santos Everardo Valadares de Sá Barretto Sampaio Rômulo Simões Cézar Menezes José João Lelis Leal de Souza Walter Antônio Pereira Abrahão Ricardo Marques Coelho C. R. Grego João Luiz Lani Antônio Rodrigues Fernandes Deyvison Andrey Medrado Gonçalves Sérgio Henrique Godinho Silva Michele Duarte de Menezes Nilton Curi Eduardo Guimarães Couto Lúcia Helena Cunha dos Anjos Marcos Bacis Ceddia Érika Flávia Machado Pinheiro Sabine Grunwald Gustavo M. Vasques José Marques Júnior Airon J. da Silva Marcos C. de Vasconcelos Barreto Gabriel Nuto Nóbrega Marcelo Z. da Silva Sara F. de Souza Gustavo Souza Valladares J. H. M. Viana Fabrício da Silva Terra Ingrid Horák‐Terra Peterson Ricardo Fiorio Rafael Carlos da Silva Elizio F. Frade Júnior Raimundo Humberto Cavalcante Lima J. M. Filippini Alba Valdomiro Severino de Souza Júnior Maria De Lourdes Mendonça Santos Brefin Maria de Lourdes Pinheiro Ruivo Tiago Osório Ferreira Marny A. Brait Norton R. Caetano Idone Bringhenti Wanderson de Sousa Mendes José Lucas Safanelli Clécia Cristina Barbosa Guimarães Raúl Roberto Poppiel Arnaldo Barros e Souza Carlos A. Quesada Hilton Thadeu Zarate do Couto

10.1016/j.geoderma.2019.05.043 article EN Geoderma 2019-08-05

Soil texture is one of the most important soil properties as it drives several physical, chemical, biological, hydrological, and mechanical properties, processes. In Antarctica controls different ecological processes, such carbon stocks, nutrient leaching, toxic metals retention. Thus, there a pressing need for accurate data Antarctic ice-free areas, especially under pressures imposed by climate changes human disturbances on continent. this work, we predicted distribution sand, silt, clay...

10.1016/j.geoderma.2023.116405 article EN cc-by-nc-nd Geoderma 2023-03-09

Global soil carbon maps are essential to understanding the global cycle and supporting policy decisions, but their uncertainty in remote areas with limited data remains a significant challenge. Assessing quantifying at regional level can shed light on existing uncertainties maps, providing more dependable information for stakeholders. Therefore, this study aimed model map organic (SOC) stock western Amazon, Rondônia state, which witnessed loss of 30% its native coverage last 35 years. We...

10.1016/j.geodrs.2024.e00773 article EN cc-by Geoderma Regional 2024-02-03

RESUMO Este trabalho apresenta um modelo para determinar a fragilidade ambiental em bacias hidrográficas. O estudo foi realizado na Bacia do Rio Aldeia Velha, RJ, localizada zona de contato e transição entre baixada litorânea o relevo montanhoso da Serra Mar. Fatores que influenciam ocorrência processos erosivos foram integrados por algoritmos SIG construção classes fragilidade. A análise multicriterial considerou numérico terreno, dados oficiais sobre variáveis ambientais, imagem orbital...

10.1590/2179-8087.107714 article PT cc-by Floresta e Ambiente 2016-03-31

Increasingly, applications of machine learning techniques for digital soil mapping (DSM) are being used different purposes. Considering the variety models available, it is important to know their performance in relation data and environmental variables involved mapping. This paper investigated eight algorithms a tropical mountainous area an official rural settlement Zona da Mata region Brazil. Morphometric maps generated from elevation model, together with Landsat-8 satellite imagery,...

10.1590/18069657rbcs20170421 article EN cc-by Revista Brasileira de Ciência do Solo 2018-11-14

The Juçara palm (Euterpe edulis Mart.) is a native species of the Atlantic Forest biome, with high commercial value due to, among other uses, extraction heart and pulp. This has essential ecological interaction fauna, providing food for many frugivorous species. However, it on list endangered species, mainly to disorderly exploration tree heart, but also climate change, habitat fragmentation, defaunation. In this context, understanding which areas are suitable grow important planning...

10.4136/ambi-agua.3033 article EN cc-by Ambiente e Agua - An Interdisciplinary Journal of Applied Science 2025-02-28

Background and Methods: We assessed the prokaryotic eukaryotic diversity present in non-vegetated vegetated soils on King George Island, Maritime Antarctic, combination with measurements of carbon dioxide fluxes. Results: For prokaryotes, 381 amplicon sequence variants (ASVs) were assigned, dominated by phyla Actinobacteriota, Acidobacteriota, Pseudomonadota, Chloroflexota, Verrucomicrobiota. A total 432 ASVs including representatives from seven kingdoms 21 phyla. Fungi communities, followed...

10.3390/dna5010015 article EN cc-by DNA 2025-03-10

Abstract This study aimed to test two hypotheses: (i) on the Brazilian semiarid territory, climate has greater weight as a driver of vegetation than soil and; (ii) arboreal Caatinga is whose environmental attributes are similar Dry Forest, in terms and attributes. We analyzed superficial horizon 156 standardized profiles distributed throughout region. Bioclimatic variables were obtained from WorldClim platform extracted location. The main types region considered: Caatinga, Forest Cerrado....

10.1088/1748-9326/ab3d7b article EN cc-by Environmental Research Letters 2019-08-21

ABSTRACT Two reports of Antarctic region potential new record high temperature observations (18.3°C, 6 February 2020 at Esperanza station and 20.8°C, 9 a Brazilian automated permafrost monitoring on Seymour Island) were evaluated by World Meteorological Organization (WMO) panel atmospheric scientists. The latter figure was reported as 20.75°C in the media. considered synoptic situation instrumental setups. It determined that large pressure system over area created föhn conditions resulted...

10.1175/bams-d-21-0040.1 article EN Bulletin of the American Meteorological Society 2021-07-06

Digital soil mapping (DSM) has been increasingly used to provide quick and accurate spatial information support decision-makers in agricultural environmental planning programs. In this study, we a DSM approach map soils western Haiti compare the performance of Multinomial Logistic Regression (MLR) with Random Forest (RF) classify soils. The study area 4,300 km2 is mostly composed diverse limestone rocks, alluvial deposits, and, lesser extent, basalt. A survey was conducted whereby were...

10.1590/18069657rbcs20170133 article EN cc-by Revista Brasileira de Ciência do Solo 2018-07-02

Abstract The detailed geomorphology of ice‐free landscapes Antarctica is key to understanding how their highly fragile environments respond climate change, at different temporal and spatial scales. Despite the recent advances in geomorphological studies areas, machine learning applications produce landform maps are still scarce on Antarctic continent. In this study, we evaluated predictive performance supervised algorithms digital Vega Island—Antarctic Peninsula region. We tested six models:...

10.1002/esp.5253 article EN Earth Surface Processes and Landforms 2021-09-27
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