Evaluating Management Strategies for Mount Kenya Forest Reserve and National Park to Reduce Fire Danger and Address Interests of Various Stakeholders

Nyongesa, Kevin W.; Vacik, Harald

doi:10.3390/f10050426

Cited by 16 publications

(19 citation statements)

References 26 publications

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“…The water tower provides fresh water to about 7 million people (EAC et al, 2016). The total population of the communities that live within the districts that border the water tower was estimated at 24.4 million in 2009 (Nyongesa and Vacik, 2019).…”

Section: Mt Kenyamentioning

confidence: 99%

Land use and climate change effects on water yield from East African forested water towers

Wamucii

Oel

Ligtenberg

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. East African forested mountain regions are vital in generating and supplying water resources to adjacent arid and semi-arid lowlands. However, these ecosystems are under pressure from both climate and land use changes. This study aimed to analyze the effects of climate and land use changes on water yield using the Budyko framework as a first-order conceptual framework assuming steady-state for pristine/protected forested areas. For nine selected forested water towers in East Africa, the amount and distribution of water resources and their decadal changes were analyzed. Results show that most areas inside and outside the water towers are under pressure from human influences. Water yield was more sensitive to climate changes compared to land use changes within the selected East African water towers themselves. However, for the surrounding lowlands, the effects of land use changes had greater impacts on water yield. We conclude that the East African water towers have seen a strong shift towards wetter conditions, especially in the period of 2011–2019, while, at the same time, the potential evapotranspiration is gradually increasing. Given that most of the water towers were identified as non-resilient to these changes, future water yield is likely to also experience more extreme variations.

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Section: Mt Kenyamentioning

confidence: 99%

Land use and climate change effects on water yield from East African forested water towers

Wamucii

Oel

Ligtenberg

et al. 2021

Hydrol. Earth Syst. Sci.

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show abstract

“…Nyongesa and Vacik [22] developed a methodological approach using the MCDA approach of the Analytical Hierarchy Process (AHP) with a set of objectives and criteria to address the complexity of the decision problem in a Forest reserve and National Park in Kenya. They evaluated seven management strategies focusing on climate change mitigation, protection of water catchments, education and research, stakeholder involvement, biodiversity conservation, timber production, and community interests, and selected the best management strategy to reduce fire danger and increase the social benefits based on the preferences of all stakeholder groups.…”

Section: Case Studies With Simulation and Scenario Analysismentioning

confidence: 99%

Management of Multiple Ecosystem Services under Climate Change, Bioeconomy and Participation

Başkent

Borges

Vacik

et al. 2021

Forests

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The Special Issue “Decision Support to Address Multiple Ecosystem Services in Forest Management Planning” includes nine research papers, two review papers, and a white paper presenting highlights of focused research initiatives. The papers provide a comprehensive framework for the analysis and review of advanced Decision Support Systems (DSS), which are multi-criteria decision approaches. Their emphasis is on how these methods and tools may contribute to address the multi-functionality of forests, to support scenario and trade-off analysis of ecosystem services, and to represent interests and behavior of various stakeholders. In the context of forest ecosystem management, a need has arisen to consider various dimensions in the design of the planning process. This calls for the development of appropriate mixes of decision making tools and methods and for its testing with the support of case studies. In this Special Issue, comments on, and implications of, the improvement of innovative decision methods and systems to address the provision of a wide range of ecosystem services and support scenario analysis with the active involvement of stakeholders are presented.

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“…MKFR's highly heterogeneous canopy consists of deciduous and evergreen tree species. Anthropogenic activities determine vegetation types and their distribution at the lower altitudes [21,29]. The montane forest zone lies between 1980 and 3000 m asl on the western, eastern, and southern sides of the mountain [30].…”

Section: Study Areamentioning

confidence: 99%

Machine Learning Classification of Endangered Tree Species in a Tropical Submontane Forest Using WorldView-2 Multispectral Satellite Imagery and Imbalanced Dataset

Jackson

Adam

2021

Remote Sensing

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Accurate maps of the spatial distribution of tropical tree species provide valuable insights for ecologists and forest management. The discrimination of tree species for economic, ecological, and technical reasons is usually necessary for achieving promising results in tree species mapping. Most of the data used in tree species mapping normally have some degree of imbalance. This study aimed to assess the effects of imbalanced data in identifying and mapping trees species under threat in a selectively logged sub-montane heterogeneous tropical forest using random forest (RF) and support vector machine with radial basis function (RBF-SVM) kernel classifiers and WorldView-2 multispectral imagery. For comparison purposes, the original imbalanced dataset was standardized using three data sampling techniques: oversampling, undersampling, and combined oversampling and undersampling techniques in R. The combined oversampling and undersampling technique produced the best results: F1-scores of 68.56 ± 2.6% for RF and 64.64 ± 3.4% for SVM. The balanced dataset recorded improved classification accuracy compared to the original imbalanced dataset. This research observed that more separable classes recorded higher F1-scores. Among the species, Syzygium guineense and Zanthoxylum gilletii were the most accurately mapped whereas Newtonia buchananii was the least accurately mapped. The most important spectral bands with the ability to detect and distinguish between tree species as measured by random forest classifier, were the Red, Red Edge, Near Infrared 1, and Near Infrared 2.

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Evaluating Management Strategies for Mount Kenya Forest Reserve and National Park to Reduce Fire Danger and Address Interests of Various Stakeholders

Cited by 16 publications

References 26 publications

Land use and climate change effects on water yield from East African forested water towers

Land use and climate change effects on water yield from East African forested water towers

Management of Multiple Ecosystem Services under Climate Change, Bioeconomy and Participation

Machine Learning Classification of Endangered Tree Species in a Tropical Submontane Forest Using WorldView-2 Multispectral Satellite Imagery and Imbalanced Dataset

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