Fire occurrence on Mount Kenya and patterns of burning

Downing, Timothy; Imo, Moses; Kimanzi, Johnstone K.

doi:10.1016/j.grj.2016.12.003

Cited by 13 publications

(32 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While there are two wet and two dry seasons, the short dry season (July to September (16% of MPFs) is less severe because it still has some chance of precipitation and temperatures are also cooler than the January to March dry season (69% of MFPs) [47]. Our findings mostly coincide with those of [32], although they found no fires occurring during the July-August-September dry season as we did. The majority of fires (77%) were detected between 2500 m and 3750 m elevation (see Figure 3a), which roughly corresponds to upper montane forest and ericaceous bushland.…”

Section: Fire Locations and Timingsupporting

confidence: 74%

See 1 more Smart Citation

Fire on the Water Towers: Mapping Burn Scars on Mount Kenya Using Satellite Data to Reconstruct Recent Fire History

2019

View full text Add to dashboard Cite

Mount Kenya is one of Kenya’s ‘water towers’, the headwaters for the country’s major rivers including the Tana River and Ewaso Nyiro River, which provide water and hydroelectric power to the semiarid region. Fires affect water downstream, but are difficult to monitor given limited resources of local land management agencies. Satellite-based remote sensing has the potential to provide long term coverage of large remote areas on Mount Kenya, especially using the free Landsat data archive and moderate resolution imaging spectroradiometer (MODIS) fire products. In this study, we mapped burn scars on Mount Kenya using 30 m Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) derived dNBR (change in normalized burn ratio) and MODIS active fire detection and burned area data for fires occurring from 2004 to 2015. We also analyzed topographic position (elevation, slope, aspect) of these fires using an ASTER global digital elevation model (GDEM v2) satellite-derived 30 m digital elevation model (DEM). Results indicate that dNBR images calculated from data acquired about one year apart were able to identify large fires on Mount Kenya that match locations (and timing) of MODIS active fire points and burned areas from the same time period, but we were unable to detect smaller and/or older fires.

show abstract

Section: Fire Locations and Timingsupporting

confidence: 74%

“…Much work has focused on using remote sensing to map burn scars in Africa's savanna ecosystems [30,31], but little research has been conducted on fire mapping techniques on the East African montane ecosystems studied here [32]. Many tropical environments have a heterogeneous mix of vegetation types that vary along a topographic gradient.…”

Section: Introductionmentioning

confidence: 99%

Fire on the Water Towers: Mapping Burn Scars on Mount Kenya Using Satellite Data to Reconstruct Recent Fire History

2019

View full text Add to dashboard Cite

show abstract

“…Questionnaires were designed and a pilot test was conducted to refine the questions. The questionnaire included: Yes or No responses, with some questions that allowed responses on a Likert type of scale ranging from a very great extent (5) to no extent at all (1) and no response (0); and others where participants were required to express their personal opinions verbally. The questionnaires were used to interview 16 respondents from Gathiuru Forest Station (one KFS manager, one ranger, two CFA leaders, and 12 CFA members) between October 2015 and December 2016.…”

Section: Questionnairesmentioning

confidence: 99%

“…Farmers in Kenya use fire to prepare farmlands, break impenetrable bushlands; control weeds, pests and parasites and try to keep wildlife away from homes. Bushland and forest fires are common in Kenya because some community members use fire to burn charcoal, harvest wild honey, and hunt and roast game meat in forests and national parks [5].…”

Section: Introductionmentioning

confidence: 99%

Fire Management in Mount Kenya: A Case Study of Gathiuru Forest Station

Nyongesa

Vacik

2018

Forests

View full text Add to dashboard Cite

This paper proposes an Integrated Fire Management (IFM) framework that can be used to support communities and resource managers in finding effective and efficient approaches to prevent damaging fires, as well as to maintain desirable fire regimes in Kenya. Designing and implementing an IFM approach in Kenya calls for a systematic understanding of the various uses of fire and the underlying perceptions and traditional ecological knowledge of the local people. The proposed IFM framework allows different stakeholders to evaluate the risks posed by fires and balance them with their beneficial ecological and economic effects making it easier for them to develop effective fire management approaches. A case study of the proposed IFM framework was conducted in Gathiuru Forest, which that is part of the larger Mt. Kenya Forest Ecosystem. Focus group discussions were held with key resource persons, primary and secondary data on socio-economic activities was studied, fire and weather records were analysed and the current fire management plans were consulted. Questionnaires were used to assess how the IFM is implemented in the Gathiuru Forest Station. The results show that the proposed IFM framework is scalable and can be applied in places with fire-dependent ecosystems as well as in places with fire-sensitive ecosystems in Kenya. The effectiveness of the proposed IFM framework depends on the active participation, formulation and implementation of the IFM activities by the main stakeholder groups (Kenya Forest Service (KFS), Kenya Wildlife Service (KWS), and the Community Forest Associations (CFA). The proposed IFM framework helps in implementing cost-effective approaches to prevent damaging fires and maintain desirable fire regimes in Kenya.

show abstract

“…To characterize the fire regime, we estimated the number of fire events, fire frequency, total burned area, fire rotation (amount of time the whole study area takes to be burned), mean burned area, and mean annual burned area (Downing et al 2017) for the whole period (1984-2015) and for the 2 subperiods (1984-1999 and 2000-2015). The monthly occurrence of fires during the 32 years and in the different vegetation types was also analyzed.…”

Section: Fire Recordsmentioning

confidence: 99%