Mapping and quantification of ferruginous outcrop savannas in the Brazilian Amazon: A challenge for biodiversity conservation

The eastern Brazilian Amazon contains many isolated ferruginous savanna ecosystem patches (locally known as ‘canga vegetation’) located on ironstone rocky outcrops on the top of plateaus and ridges, surrounded by tropical rainforests. In the Carajás Mineral Province (CMP), these outcrops contain large iron ore reserves that have been exploited by opencast mining since the 1980s. The canga vegetation is particularly impacted by mining, since the iron ores that occur are associated with this type of vegetation and currently, little is known regarding the extent of canga vegetation patches before mining activities began. This information is important for quantifying the impact of mining, in addition to helping plan conservation programmes. Here, land cover changes of the Canga area in the CMP are evaluated by estimating the pre-mining area of canga patches and comparing it to the actual extent of canga patches. We mapped canga vegetation using geographic object-based image analysis (GEOBIA) from 1973 Landsat-1 MSS, 1984 and 2001 Landsat-5 TM, and 2016 Landsat-8 OLI images, and found that canga vegetation originally occupied an area of 144.2 km2 before mining exploitation. By 2016, 19.6% of the canga area was lost in the CMP due to conversion to other land-use types (mining areas, pasturelands). In the Carajás National Forest (CNF), located within the CMP, the original canga vegetation covered 105.2 km2 (2.55% of the CNF total area), and in 2016, canga vegetation occupied an area of 77.2 km2 (1.87%). Therefore, after more than three decades of mineral exploitation, less than 20% of the total canga area was lost. Currently, 21% of the canga area in the CMP is protected by the Campos Ferruginosos National Park. By documenting the initial extent of canga vegetation in the eastern Amazon and the extent to which it has been lost due to mining operations, the results of this work are the first step towards conserving this ecosystem.

[1]  J. Dorr Supergene iron ores of Minas Gerais, Brazil , 1964 .

[2]  G. E. Tolbert,et al.  The Recently Discovered Serra dos Carajas Iron Deposits, Northern Brazil , 1971 .

[3]  J. D. Tarpley,et al.  Global vegetation indices from the NOAA-7 meteorological satellite , 1984 .

[4]  R. Congalton,et al.  Accuracy assessment: a user's perspective , 1986 .

[5]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[6]  Russell G. Congalton,et al.  Assessing the accuracy of remotely sensed data : principles and practices , 1998 .

[7]  M. Macambira,et al.  Geochronological provinces of the Amazonian Craton , 1999 .

[8]  M. Bidovec,et al.  Geochemical Atlas of Europe, Part 1, Background Information, Methodology and Maps , 2005 .

[9]  Patrick Bogaert,et al.  Forest change detection by statistical object-based method , 2006 .

[10]  C. Jacobi,et al.  Plant communities on ironstone outcrops: a diverse and endangered Brazilian ecosystem , 2007, Biodiversity and Conservation.

[11]  Gregory Duveiller,et al.  Deforestation in Central Africa: Estimates at regional, national and landscape levels by advanced processing of systematically-distributed Landsat extracts , 2008 .

[12]  D. Groves,et al.  Metallogenesis of the Carajás Mineral Province, Southern Amazon Craton, Brazil: Varying styles of Archean through Paleoproterozoic to Neoproterozoic base- and precious-metal mineralisation , 2008 .

[13]  R. Morris Anthropogenic impacts on tropical forest biodiversity: a network structure and ecosystem functioning perspective , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[14]  C. Yates,et al.  Plant communities of the ironstone ranges of South Western Australia: hotspots for plant diversity and mineral deposits , 2010, Biodiversity and Conservation.

[15]  Dirk Tiede,et al.  ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data , 2010, Int. J. Geogr. Inf. Sci..

[16]  Xulin Guo,et al.  Detecting an Optimal Scale Parameter in Object-Oriented Classification , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[17]  C. Jacobi,et al.  Soaring Extinction Threats to Endemic Plants in Brazilian Metal-Rich Regions , 2011, AMBIO.

[18]  Julien Radoux,et al.  Please Scroll down for Article International Journal of Geographical Information Science Thematic Accuracy Assessment of Geographic Object-based Image Classification Thematic Accuracy Assessment of Geographic Object-based Image Classification , 2022 .

[19]  Frédéric Achard,et al.  An automated approach for segmenting and classifying a large sample of multi-date Landsat imagery for pan-tropical forest monitoring , 2011 .

[20]  Gabriel Luís Bonora Vidrih Ferreira,et al.  Meio Ambiente e Mineração na Constituição Federal , 2012 .

[21]  N. Gibson,et al.  Patterns of plant diversity in ironstone ranges in arid south western Australia , 2012 .

[22]  P. Fearnside,et al.  Amazonian forest loss and the long reach of China’s influence , 2013, Environment, Development and Sustainability.

[23]  Dar A. Roberts,et al.  Ten-Year Landsat Classification of Deforestation and Forest Degradation in the Brazilian Amazon , 2013, Remote. Sens..

[24]  D. Lu,et al.  Spatiotemporal analysis of land-use and land-cover change in the Brazilian Amazon , 2013, International journal of remote sensing.

[25]  J. Stape,et al.  Köppen's climate classification map for Brazil , 2013 .

[26]  N. P. Barbosa,et al.  Challenges for the conservation of vanishing megadiverse rupestrian grasslands , 2014 .

[27]  B. Soares-Filho,et al.  Global demand for steel drives extensive land-use change in Brazil's Iron Quadrangle , 2014 .

[28]  Thomas Blaschke,et al.  Geographic Object-Based Image Analysis – Towards a new paradigm , 2014, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.

[29]  B. Soares-Filho,et al.  Offsetting the Impacts of Mining to Achieve No Net Loss of Native Vegetation , 2014, Conservation biology : the journal of the Society for Conservation Biology.

[30]  C. Schaefer,et al.  Ecology and evolution of plant diversity in the endangered campo rupestre: a neglected conservation priority , 2015, Plant and Soil.

[31]  A. Auler,et al.  Carajás National Forest: Iron Ore Plateaus and Caves in Southeastern Amazon , 2015 .

[32]  L. Santos,et al.  Landscapes and Landforms of Brazil , 2015 .

[33]  P. Souza‐Filho,et al.  Changes in the land cover and land use of the Itacaiunas River watershed, arc of deforestation, Carajas, southeastern Amazon , 2015 .

[34]  Marcelo,et al.  Flora of the cangas of the Serra dos Carajás , Pará , Brazil : history , study area and methodology , 2016 .

[35]  V. Imperatriz-Fonseca,et al.  Reconciling Mining with the Conservation of Cave Biodiversity: A Quantitative Baseline to Help Establish Conservation Priorities , 2016, PloS one.

[36]  Maycira Costa,et al.  Distribution of Artisanal and Small-Scale Gold Mining in the Tapajós River Basin (Brazilian Amazon) over the Past 40 Years and Relationship with Water Siltation , 2016, Remote. Sens..

[37]  P. Souza‐Filho,et al.  Influence of seasonal variation on the hydro-biogeochemical characteristics of two upland lakes in the Southeastern Amazon, Brazil. , 2016, Anais da Academia Brasileira de Ciencias.

[38]  Pedro Lage Viana,et al.  Flora das cangas da Serra dos Carajás, Pará, Brasil: história, área de estudos e metodologia , 2016 .

[39]  R. Dall’Agnol,et al.  Geochemical distribution and threshold values determination of heavy metals in stream water in the sub-basins of Vermelho and Sororó rivers, Itacaiúnas River watershed, Eastern Amazon, Brazil , 2018, Geochimica Brasiliensis.

[40]  Pedro Lage Viana,et al.  Cangas da Amazônia: a vegetação única de Carajás evidenciada pela lista de fanerógamas , 2018, Rodriguésia.

[41]  D. Zappi,et al.  Amazon canga : the unique vegetation of Carajás revealed by the list of seed plants , 2018 .

[42]  M. Gastauer,et al.  Conserving relics from ancient underground worlds: assessing the influence of cave and landscape features on obligate iron cave dwellers from the Eastern Amazon , 2018, PeerJ.

[43]  Vicente Pérez-Muñuzuri,et al.  Extreme Wave Height Events in NW Spain: A Combined Multi-Sensor and Model Approach , 2017, Remote. Sens..

[44]  V. Imperatriz-Fonseca,et al.  Landscape Genomic Conservation Assessment of a Narrow-Endemic and a Widespread Morning Glory From Amazonian Savannas , 2018, Front. Plant Sci..

[45]  Pedro Walfir M. Souza Filho,et al.  A GEOBIA Approach for Multitemporal Land-Cover and Land-Use Change Analysis in a Tropical Watershed in the Southeastern Amazon , 2018, Remote. Sens..

[46]  M. Gastauer,et al.  Mine land rehabilitation in Brazil: Goals and techniques in the context of legal requirements , 2018, Ambio.