Impact of land cover change on aboveground carbon stocks in Afromontane landscape in Kenya

Pellikka, Petri; Heikinheimo, Vuokko; Hietanen, Jesse; Schäfer, E.; Siljander, Mika; Heiskanen, Janne

doi:10.1016/j.apgeog.2018.03.017

Cited by 107 publications

(88 citation statements)

References 54 publications

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“…The variables are in line with the previous studies in Africa, which have used, for example, mean canopy height, height percentiles and canopy density for modelling [6,[10][11][12]. Both modelling accuracy and explanatory variables are similar to the model used for the hills in the study by [15], who developed separate models for hills and lowlands using different ALS data.…”

Section: Als-based Aboveground Biomass Mapsupporting

confidence: 63%

“…Although the general patterns of AGB are very similar, the current map is an improvement over an earlier aboveground carbon map for the Taita Hills [15]. The authors in [15] generated their map for analyzing the effect of the land cover change on carbon stocks using a satellite image-based land cover map and land cover type-specific mean carbon density values.…”

Section: Als-based Aboveground Biomass Mapmentioning

confidence: 99%

“…The authors in [15] generated their map for analyzing the effect of the land cover change on carbon stocks using a satellite image-based land cover map and land cover type-specific mean carbon density values. However, the continuous AGB estimates are important as AGB depends on many variables, also within land cover classes (see Section 4.2).…”

Section: Als-based Aboveground Biomass Mapmentioning

confidence: 99%

“…Land use classes (extent of croplands and plantation forest) were extracted from the most recent land use and land cover classification for the area [15,56]. A SPOT 4 HRVIR satellite image from October 2011 with a pixel size of 20 m × 20 m has been used for the classification with ten classes.…”

Section: Explanatory Variables For Modelling Distribution Of Abovegromentioning

confidence: 99%

“…The landscape is a highly fragmented mosaic of montane forest patches, exotic plantations and agriculture with agroforestry and horticulture being common [25]. According to [15], the main land use and land cover types in 2011 were cropland (40.5%), thicket (28.9%), shrubland (12.8%), woodland and agroforestry (10.7%), plantation forest (4.6%), indigenous montane forest (1.4%) and bare rock, soil and built-up areas (1.1%). Agricultural expansion has been taking place in the area for decades.…”

Section: Introductionmentioning

confidence: 99%

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Determinants of Aboveground Biomass across an Afromontane Landscape Mosaic in Kenya

et al. 2017

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Afromontane tropical forests maintain high biodiversity and provide valuable ecosystem services, such as carbon sequestration. The spatial distribution of aboveground biomass (AGB) in forest-agriculture landscape mosaics is highly variable and controlled both by physical and human factors. In this study, the objectives were (1) to generate a map of AGB for the Taita Hills, in Kenya, based on field measurements and airborne laser scanning (ALS), and (2) to examine determinants of AGB using geospatial data and statistical modelling. The study area is located in the northernmost part of the Eastern Arc Mountains, with an elevation range of approximately 600-2200 m. The field measurements were carried out in 215 plots in 2013-2015 and ALS flights conducted in 2014-2015. Multiple linear regression was used for predicting AGB at a 30 m × 30 m resolution based on canopy cover and the 25th percentile height derived from ALS returns (R 2 = 0.88, RMSE = 52.9 Mg ha −1 ). Boosted regression trees (BRT) were used for examining the relationship between AGB and explanatory variables at a 250 m × 250 m resolution. According to the results, AGB patterns were controlled mainly by mean annual precipitation (MAP), the distribution of croplands and slope, which explained together 69.8% of the AGB variation. The highest AGB densities have been retained in the semi-natural vegetation in the higher elevations receiving more rainfall and in the steep slope, which is less suitable for agriculture. AGB was also relatively high in the eastern slopes as indicated by the strong interaction between slope and aspect. Furthermore, plantation forests, topographic position and the density of buildings had a minor influence on AGB. The findings demonstrate the utility of ALS-based AGB maps and BRT for describing AGB distributions across Afromontane landscapes, which is important for making sustainable land management decisions in the region.

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Section: Als-based Aboveground Biomass Mapsupporting

confidence: 63%

Section: Als-based Aboveground Biomass Mapmentioning

confidence: 99%

Section: Als-based Aboveground Biomass Mapmentioning

confidence: 99%

Section: Explanatory Variables For Modelling Distribution Of Abovegromentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determinants of Aboveground Biomass across an Afromontane Landscape Mosaic in Kenya

et al. 2017

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You eat what you find – Local patterns in vegetation structure control diets of African fungus‐growing termites

Vesala

Rikkinen

et al. 2022

Ecology and Evolution

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Fungus‐growing termites and their symbiotic Termitomyces fungi are critically important carbon and nutrient recyclers in arid and semiarid environments of sub‐Saharan Africa. A major proportion of plant litter produced in these ecosystems is decomposed within nest chambers of termite mounds, where temperature and humidity are kept optimal for the fungal symbionts. While fungus‐growing termites are generally believed to exploit a wide range of different plant substrates, the actual diets of most species remain elusive. We studied dietary niches of two Macrotermes species across the semiarid savanna landscape in the Tsavo Ecosystem, southern Kenya, based on carbon (C) and nitrogen (N) stable isotopes in Termitomyces fungus combs. We applied Bayesian mixing models to determine the proportion of grass and woody plant matter in the combs, these being the two major food sources available for Macrotermes species in the region. Our results showed that both termite species, and colonies cultivating different Termitomyces fungi, occupied broad and largely overlapping isotopic niches, indicating no dietary specialization. Including laser scanning derived vegetation cover estimates to the dietary mixing model revealed that the proportion of woody plant matter in fungus combs increased with increasing woody plant cover in the nest surroundings. Nitrogen content of fungus combs was positively correlated with woody plant cover around the mounds and negatively correlated with the proportion of grass matter in the comb. Considering the high N demand of large Macrotermes colonies, woody plant matter seems to thus represent a more profitable food source than grass. As grass is also utilized by grazing mammals, and the availability of grass matter typically fluctuates over the year, mixed woodland‐grasslands and bushlands seem to represent more favorable habitats for large Macrotermes colonies than open grasslands.

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Landsat time series reveal forest loss and woody encroachment in the Ngorongoro Conservation Area, Tanzania

Borges

Higginbottom

Cain

et al. 2022

Remote Sens Ecol Conserv

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Impact of land cover change on aboveground carbon stocks in Afromontane landscape in Kenya

Cited by 107 publications

References 54 publications

Determinants of Aboveground Biomass across an Afromontane Landscape Mosaic in Kenya

Determinants of Aboveground Biomass across an Afromontane Landscape Mosaic in Kenya

You eat what you find – Local patterns in vegetation structure control diets of African fungus‐growing termites

Landsat time series reveal forest loss and woody encroachment in the Ngorongoro Conservation Area, Tanzania

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