The environmental impacts of mining on Gishwati Protected Reserve in Rwanda

Muhire, Innocent; Manirakiza, Vincent; Nsanganwimana, Florien; Nyiratuza, Madeleine; Inzirayineza, Thierry Aimable; Uworwabayeho, Alphonse

doi:10.1007/s10661-021-09372-9

Cited by 10 publications

(9 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mining developments can have a wide range of impacts on socio-ecological systems 3 , 4 . For example, contamination of water and soil with toxic chemicals is a significant problem in mining regions 47 – 49 . Tailings dams which store toxic by-products of mineral extraction processes in large reservoirs are a particular risk as they can fail causing pollution of soils and waterways which impacts land at some distance from the mine itself 50 .…”

Section: Discussionmentioning

confidence: 99%

Quasi-experimental analysis of new mining developments as a driver of deforestation in Zambia

Morley

Buchanan

Mitchard

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Mining is a vital part of the global, and many national, economies. Mining also has the potential to drive extensive land cover change, including deforestation, with impacts reaching far from the mine itself. Understanding the amount of deforestation associated with mining is important for conservationists, governments, mining companies, and consumers, yet accurate quantification is rare. We applied statistical matching, a quasi-experimental methodology, along with Bayesian hierarchical generalized linear models to assess the impact on deforestation of new mining developments in Zambia from 2000 to present. Zambia is a globally significant producer of minerals and mining contributes ~ 10% of its gross domestic product and ~ 77% of its exports. Despite extensive deforestation in mining impacted land, we found no evidence that any of the 22 mines we analysed increased deforestation compared with matched control sites. The extent forest lost was therefore no different than would likely have happened without the mines being present due to other drivers of deforestation in Zambia. This suggests previous assessments based on correlative methodologies may overestimate the deforestation impact of mining. However, mining can have a range of impacts on society, biodiversity, and the local environment that are not captured by our analysis.

show abstract

Section: Discussionmentioning

confidence: 99%

Quasi-experimental analysis of new mining developments as a driver of deforestation in Zambia

Morley

Buchanan

Mitchard

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…These pressures led to an extensive conversion of forested land for settlement and agricultural expansion, to meet the growing demands for food and energy (Munanura et al, 2018;Rukundo et al, 2018). This period was de ned by the fragmentation of natural forest parks, with Gishwati-Mukura in the LKV catchment losing more than half of its original land during the period (Kanyamibwa, 1998;Muhire et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Land Use Land Cover Change in the African Great Lakes Region: A Spatial-Temporal Analysis and Future Predictions for the Lake Kivu catchment, Rwanda.

Kayitesi,

Guzha,

Tonini

et al. 2024

Preprint

View full text Add to dashboard Cite

The African Great Lakes Region has experienced substantial Land Use Land Cover Change (LULCC) over the last decades. The main drivers of LULCC include an interplay of political, demographic, and socio-economic factors. This study focused on the Lake Kivu catchment in Rwanda, a critical ecosystem in the African Great Lakes Regions, exploring historical LULCC, their major drivers, and predicting future LULC for different development scenarios. The methodology involved image classification using seasonal composites and integrating spectral indices with topographic features to enhance the discrimination and capturing seasonal variations. The classification results demonstrated an overall accuracy and kappa exceeding 83%. Historical LULCC analysis showed significant changes, particularly the 1990–2000 decade, marked by forest loss ranging from 26.6–18.7% and an increase in agricultural land (from 27.7–43%). These changes were attributed to political conflicts in the region and population movements. Subsequent decades (2000–2010 and 2010–2020) witnessed forest recovery (24.8% by 2020). Artificial neural networks were used to predict future LULC scenarios, considering natural and socio-economic explanatory variables and historical LULC transitions. The analysis of explanatory variables highlighted the significant role of proximity to urban centers, population density, and terrain, in LULCC. River proximity drove agricultural and grassland expansion. The predicted future LULC for 2030 and 2050 indicate distinct trajectories likely to be influenced by demographic and socio-economic development trends. The findings of this study contribute to identifying opportunities for land restoration and conservation efforts, thereby ensuring the preservation of Lake Kivu catchment’s ecological integrity.

show abstract

“…The Linux kernel layer is the system kernel layer. Android core system services depend on the Linux 2.6 kernel, mainly adding a virtual CPU named goldfish and specific driver code required by Android runtime [17].…”

Section: Design and Implementation Of Gis Systemmentioning

confidence: 99%

Design and Implementation of Coal Mine Safety Monitoring System Based on GIS

Zhang¹

2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In order to further improve the safety production management capacity of coal enterprises and minimize the rate of coal mine safety accidents, based on the purpose of improving safety production efficiency, this paper constructs a coal mine safety detection system based on GIS technology. At the same time, on the basis of fixed-point positioning and remote monitoring at the PC end, this paper implements the whole process detection and monitoring of coal mine safety production with the help of mobile terminal intelligent system. The system software uses Java language to code it. In the first round of test, one function omission, three serious system errors, 14 general errors, and 21 minor errors are found. The accident passing rate of the second test is greater than 99.88%, and all performance indexes of the system meet the performance requirements, which proves the feasibility of the system.

show abstract

The environmental impacts of mining on Gishwati Protected Reserve in Rwanda

Cited by 10 publications

References 6 publications

Quasi-experimental analysis of new mining developments as a driver of deforestation in Zambia

Quasi-experimental analysis of new mining developments as a driver of deforestation in Zambia

Land Use Land Cover Change in the African Great Lakes Region: A Spatial-Temporal Analysis and Future Predictions for the Lake Kivu catchment, Rwanda.

Design and Implementation of Coal Mine Safety Monitoring System Based on GIS

Contact Info

Product

Resources

About