Neglect of ecosystems services by mining, and the worst environmental disaster in Brazil

Neves, Ana Carolina de Oliveira; Nunes, Flávia Peres; Carvalho, F. A.; Fernandes, Geraldo Wilson

doi:10.1016/j.ncon.2016.03.002

Cited by 59 publications

(15 citation statements)

References 4 publications

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“…In addition to funding needed for rehabilitation and reclamation activities, the compensation process should account for the loss of key environmental services (Neves et al. ), including the loss of provisioning services like fishing. Mining disasters have stimulated proposals of compensation frameworks and mechanisms that account for environmental services and restoration time lags (Laurance , Bai et al.…”

Section: Introductionmentioning

confidence: 99%

Brazil's worst mining disaster: Corporations must be compelled to pay the actual environmental costs

Garcia

Ribeiro

Roque

et al. 2017

Ecological Applications

158

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Abstract. In November 2015, a large mine-tailing dam owned by Samarco Corporation collapsed in Brazil, generating a massive wave of toxic mud that spread down the Doce River, killing 20 people and affecting biodiversity across hundreds of kilometers of river, riparian lands, and Atlantic coast. Besides the disaster's serious human and socioeconomic tolls, we estimate the regional loss of environmental services to be ~US$521 million per year. Although our estimate is conservative, it is still six times higher than the fine imposed on Samarco by Brazilian environmental authorities. To reduce such disparities between estimated damages and levied fines, we advocate for an environmental bond policy that considers potential risks and environmental services that could possibly be impacted by irresponsible mining activity. Environmental bonds and insurance are commonly used policy instruments in many countries, but there are no clear environmental bond policies in Brazil. Environmental bonds are likely to be more effective at securing environmental restitution than post-disaster fines, which generally are inadequate and often unpaid. We estimate that at least 126 mining dams in Brazil are vulnerable to failure in the forthcoming years. Any such event could have severe socialenvironmental consequences, underscoring the need for effective disaster-management strategies for large-scale mining operations.

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Section: Introductionmentioning

confidence: 99%

Brazil's worst mining disaster: Corporations must be compelled to pay the actual environmental costs

Garcia

Ribeiro

Roque

et al. 2017

Ecological Applications

158

View full text Add to dashboard Cite

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“…Mining increased substantially the fish mortality in South America (Rodríguez-Lozano et al, 2016;Wenger et al, 2017). In freshwaters, it resulted in the worst environmental disaster in Brazilian history when the Bento Rodrigues dam collapsed in the Doce River basin, killing 19 persons and tons of fish, in 2015 (Neves, Nunes, de Carvalho, & Fernandes, 2016). A tragedy in 2019 followed the Bento Rodrigues disaster when another dam collapsed nearby the Brumadinho city, Brazil, and the "mud wave" spread downstream (please, see "Dam collapse at Brazilian mine exposes grave safety problems", in <theconversation.com>), killing at least 186 people.…”

Section: Environmental Alterationmentioning

confidence: 99%

A network meta‐analysis of threats to South American fish biodiversity

et al. 2019

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While environmental alterations have made Homo sapiens the hyperkeystone species of the globe, biotic homogenization initiated a new era, the “Homogenocene.” Still, some terrestrial and aquatic ecosystems in South America are considered pristine and wild, which can lead to a general faith that economic progress is consistent with conservation strategies, even without scientific support. We compiled anthropogenic threats to fish biodiversity in a hierarchical meta‐analysis, along with an evidence synthesis of threats related to biological invasions, based on peer‐reviewed research with the aim to represent the actual conservation status of the South American ichthyofauna. We highlighted human‐related threats and synergistic effects of biological invasions, climate change, environmental alterations (e.g., pollution, aquaculture and damming) and fisheries. Considering measures that reinforce novel alien fish (e.g., artificial hybrids or genetically modified) introductions, it became clear why an eventual increase in local or regional species richness is not always beneficial to aquaculture, biodiversity, human well‐being or nature. In fact, citizens in all societal roles, including scientists, should revise their concepts about threats to fish biodiversity. Environmental policies require more than taxonomic diagnostics to achieve conservation goals under an incompatible scenario of a multiplying number of fish species and biotic homogenization. We advocate for countries in South America using science‐based strategies useful to maintain their social and economic growth along with their “remaining nature.” We live a crucial moment when the government overlooks threats to biodiversity and uses agribusiness as the most acceptable manner of fuelling the economy.

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“…We conducted our study at Bento Rodrigues dam disaster area located west of the municipality of Marianna, Minas Gerais state (Brazil), the latitudes and the longitudes are −20.23 • and −43.42 • (Figure 1). The broken tailing dam released about 55-62 million m 3 of red mud into the Doce river and destroyed more than 900 hectares of agricultural area [35,36]. The study area includes the cities of Mariana, Ouro Preto, and Pte.…”

Section: Study Areamentioning

confidence: 99%

Spatial–Temporal Analysis of Land Cover Change at the Bento Rodrigues Dam Disaster Area Using Machine Learning Techniques

2019

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Disasters are an unpredictable way to change land use and land cover. Improving the accuracy of mapping a disaster area at different time is an essential step to analyze the relationship between human activity and environment. The goals of this study were to test the performance of different processing procedures and examine the effect of adding normalized difference vegetation index (NDVI) as an additional classification feature for mapping land cover changes due to a disaster. Using Landsat ETM+ and OLI images of the Bento Rodrigues mine tailing disaster area, we created two datasets, one with six bands, and the other one with six bands plus the NDVI. We used support vector machine (SVM) and decision tree (DT) algorithms to build classifier models and validated models performance using 10-fold cross-validation, resulting in accuracies higher than 90%. The processed results indicated that the accuracy could reach or exceed 80%, and the support vector machine had a better performance than the decision tree. We also calculated each land cover type’s sensitivity (true positive rate) and found that Agriculture, Forest and Mine sites had higher values but Bareland and Water had lower values. Then, we visualized land cover maps in 2000 and 2017 and found out the Mine sites areas have been expanded about twice of the size, but Forest decreased 12.43%. Our findings showed that it is feasible to create a training data pool and use machine learning algorithms to classify a different year’s Landsat products and NDVI can improve the vegetation covered land classification. Furthermore, this approach can provide a venue to analyze land pattern change in a disaster area over time.

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Neglect of ecosystems services by mining, and the worst environmental disaster in Brazil

Cited by 59 publications

References 4 publications

Brazil's worst mining disaster: Corporations must be compelled to pay the actual environmental costs

Brazil's worst mining disaster: Corporations must be compelled to pay the actual environmental costs

A network meta‐analysis of threats to South American fish biodiversity

Spatial–Temporal Analysis of Land Cover Change at the Bento Rodrigues Dam Disaster Area Using Machine Learning Techniques

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