Watershed and riparian areas of Mau Forest Complex in Kenya are experiencing increased threats due to unsustainable land use activities geared towards economic growth amidst growing population. This study was carried ...Watershed and riparian areas of Mau Forest Complex in Kenya are experiencing increased threats due to unsustainable land use activities geared towards economic growth amidst growing population. This study was carried out to examine effects of land use activities on riparian vegetation, soil and water quality along two major rivers (Chemosit and Kipsonoi) of South West Mau Forest (SWMF). Land use activities adjacent to these rivers and biodiversity disturbance on the riparian zone were identified and underpinned to changes on Total Nitrogen, Total Phosphorous, Potassium, Sulphur, Cadmium, Copper, Lead, Total Suspended Solids and soil Organic Carbon. Three sampling sites designated(upstream, midstream and downstream) were identified and established along each river as guided by existing land use activities represented by forest, tea plantation and mixed agricultural farming respectively. At each sampling site, a 200 m × 50 m section was systematically marked on each side of the river bank;the longest side being parallel to the river flow and divided into three belts transects each 20 m × 50 m, spaced 70 m apart. Six distinct land use activities (indigenous forest, food crop, tree and tea farming, livestock keeping and urban settlement) were identified as the major land use activities in SWMF. Plant species richness decreased and overall riparian disturbance increased from upstream (intact canopy with native vegetation) to mid-stream and downstream as epitomized by the structure, biodiversity disturbance resulting from extensive and intensive farming, intrusion of exotic species to livestock grazing and urban settlement. Variation among sampling sites in Total Suspended Solids, pH, Total Nitrogen, Phosphorus and Potassium were associated to different land use activities along the riparian zone. Total Nitrogen and water pH showed significant sensitivity to land use changes (p < 0.05). Put together these results indicate loss of biodiversity, riparian disturbance hence a need to adopt environmental-friendly land use planning and sustainable farming systems in SWMF.展开更多
The Mau Forest has in the recent past elicited serious political and environmental debates regarding its conservation status, as the forest is fast dwindling and the repercussions felt widely across the country. The f...The Mau Forest has in the recent past elicited serious political and environmental debates regarding its conservation status, as the forest is fast dwindling and the repercussions felt widely across the country. The forest, regarded as the largest indigenous montane forest in east Africa, has been hard hit by land-use changes mainly extensive and ill-planned human settlements. To save the forest, the government has resorted to forced evictions of the settlers. We sought to understand the drivers and causes for the observed illegal settlements in the Mau Forest. To collect data, we conducted focus group discussions and administered household questionnaires on evictees in the South-West and Eastern Mau. Data were analyzed using descriptive and inferential statistics. The results of the binary logistic regression model indicate that Poverty (p = 0.000), Agricultural production (p = 0.000) and Land Given by Government (p = 0.018) contributed significantly to the prediction of people’s motivation of settling in the Mau Forest. In conclusion, population pressure, laxity in forest law enforcement and insecure land tenure and politics were identified as some of the factors that motivated the observed rise in illegal settlements in Mau Forest. Such information on the factors that led to the illegal settlements in Mau Forest would be useful for forest conservation policy makers and managers. It will be a basis upon which interventions can be undertaken to enhance sustainable forest management in Kenya and beyond.展开更多
Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remot...Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remote sensing satellite of Vietnam with resolution of 2.5 m (Panchromatic) and 10 m (Multispectral). The objective of this research is to compare two classification approaches using VNREDSat-1 image for mapping mangrove forest in Vien An Dong commune, Ngoc Hien district, Ca Mau province. ISODATA algorithm (in PBC method) and membership function classifier (in OBC method) were chosen to classify the same image. The results show that the overall accuracies of OBC and PBC are 73% and 62.16% respectively, and OBC solved the “salt and pepper” which is the main issue of PBC as well. Therefore, OBC is supposed to be the better approach to classify VNREDSat-1 for mapping mangrove forest in Ngoc Hien commune.展开更多
Montane forest ecosystems support biodiversity and provide varied ecosystem services to adjacent and downstream human communities. However, human-induced disturbances are common in many of these ecosystems, threatenin...Montane forest ecosystems support biodiversity and provide varied ecosystem services to adjacent and downstream human communities. However, human-induced disturbances are common in many of these ecosystems, threatening their capacity to sustain their functions. This study assessed the status of woody vegetation and livestock use of a Kenyan montane forest 10 years after government-sanctioned cessation of human encroachment. The findings can inform suitable interventions that support recovery of abandoned forest settlements subjected to continuous anthropogenic disturbances. Selected woody vegetation attributes and livestock disturbance indicators were assessed across three human-driven disturbance regimes (light, moderate and heavy) using stratified-systematic sampling technique. Data on the extent of community dependence on forest grazing were collected from 381 randomly selected forest adjacent households using semi-structured questionnaires. Information on the palatability of plants to livestock was obtained from Focus Group Discussions. Vegetation data were analyzed using linear mixed models, while descriptive analysis was applied on household survey data. A total of 33 woody plant species belonging to 22 families were identified, out of which 55% were perceived to be unpalatable to livestock. Species richness, species diversity, stem density and basal areas declined significantly with increasing levels of disturbance. Specifically, these attributes were 59% - 98% lower in heavily disturbed sites than in moderately and lightly disturbed sites. A vast majority (88%) of the sampled households grazed their livestock in the forest throughout the year. Evidence from this study indicates that intense past and ongoing anthropogenic disturbances caused significant negative effects on the forest vegetation condition, and lowered its capacity to recover. Forest managers should prioritize minimizing recurrent anthropogenic disturbances as the forest recovers to ensure successful succession and sustainable provision of ecosystem services.展开更多
Soil organic carbon （SOC） pool has the potential to mitigate or enhance climate change by either acting as a sink, or a source of atmospheric carbon dioxide （CO2） and also plays a fundamental role in the health an...Soil organic carbon （SOC） pool has the potential to mitigate or enhance climate change by either acting as a sink, or a source of atmospheric carbon dioxide （CO2） and also plays a fundamental role in the health and proper functioning of soils to sustain life on Earth. As such, the objective of this study was to investigate the applicability of a novel evolutionary genetic optimization-based adaptive neuro-fuzzy inference system （ANFIS-EG） in predicting and mapping the spatial patterns of SOC stocks in the Eastern Mau Forest Reserve, Kenya. Field measurements and auxiliary data reflecting the soil-forming factors were used to design an ANFIS-EG model, which was then implemented to predict and map the areal differentiation of SOC stocks in the Eastern Mau Forest Reserve. This was achieved with a reasonable level of uncertainty （i.e., root mean square error of 15.07 Mg C ha-l）, hence demonstrating the applicability of the ANFIS-EG in SOC mapping studies. There is potential for improving the model performance, as indicated by the current ratio of performance to deviation （1.6）. The mapping also revealed marginally higher SOC stocks in the forested ecosystems （i.e., an average of 109.78 M C ha-1） than in the aro-ecosvstems （i.e., an average of 95.9 Mg C ha-l）.展开更多
文摘Watershed and riparian areas of Mau Forest Complex in Kenya are experiencing increased threats due to unsustainable land use activities geared towards economic growth amidst growing population. This study was carried out to examine effects of land use activities on riparian vegetation, soil and water quality along two major rivers (Chemosit and Kipsonoi) of South West Mau Forest (SWMF). Land use activities adjacent to these rivers and biodiversity disturbance on the riparian zone were identified and underpinned to changes on Total Nitrogen, Total Phosphorous, Potassium, Sulphur, Cadmium, Copper, Lead, Total Suspended Solids and soil Organic Carbon. Three sampling sites designated(upstream, midstream and downstream) were identified and established along each river as guided by existing land use activities represented by forest, tea plantation and mixed agricultural farming respectively. At each sampling site, a 200 m × 50 m section was systematically marked on each side of the river bank;the longest side being parallel to the river flow and divided into three belts transects each 20 m × 50 m, spaced 70 m apart. Six distinct land use activities (indigenous forest, food crop, tree and tea farming, livestock keeping and urban settlement) were identified as the major land use activities in SWMF. Plant species richness decreased and overall riparian disturbance increased from upstream (intact canopy with native vegetation) to mid-stream and downstream as epitomized by the structure, biodiversity disturbance resulting from extensive and intensive farming, intrusion of exotic species to livestock grazing and urban settlement. Variation among sampling sites in Total Suspended Solids, pH, Total Nitrogen, Phosphorus and Potassium were associated to different land use activities along the riparian zone. Total Nitrogen and water pH showed significant sensitivity to land use changes (p < 0.05). Put together these results indicate loss of biodiversity, riparian disturbance hence a need to adopt environmental-friendly land use planning and sustainable farming systems in SWMF.
文摘The Mau Forest has in the recent past elicited serious political and environmental debates regarding its conservation status, as the forest is fast dwindling and the repercussions felt widely across the country. The forest, regarded as the largest indigenous montane forest in east Africa, has been hard hit by land-use changes mainly extensive and ill-planned human settlements. To save the forest, the government has resorted to forced evictions of the settlers. We sought to understand the drivers and causes for the observed illegal settlements in the Mau Forest. To collect data, we conducted focus group discussions and administered household questionnaires on evictees in the South-West and Eastern Mau. Data were analyzed using descriptive and inferential statistics. The results of the binary logistic regression model indicate that Poverty (p = 0.000), Agricultural production (p = 0.000) and Land Given by Government (p = 0.018) contributed significantly to the prediction of people’s motivation of settling in the Mau Forest. In conclusion, population pressure, laxity in forest law enforcement and insecure land tenure and politics were identified as some of the factors that motivated the observed rise in illegal settlements in Mau Forest. Such information on the factors that led to the illegal settlements in Mau Forest would be useful for forest conservation policy makers and managers. It will be a basis upon which interventions can be undertaken to enhance sustainable forest management in Kenya and beyond.
文摘Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remote sensing satellite of Vietnam with resolution of 2.5 m (Panchromatic) and 10 m (Multispectral). The objective of this research is to compare two classification approaches using VNREDSat-1 image for mapping mangrove forest in Vien An Dong commune, Ngoc Hien district, Ca Mau province. ISODATA algorithm (in PBC method) and membership function classifier (in OBC method) were chosen to classify the same image. The results show that the overall accuracies of OBC and PBC are 73% and 62.16% respectively, and OBC solved the “salt and pepper” which is the main issue of PBC as well. Therefore, OBC is supposed to be the better approach to classify VNREDSat-1 for mapping mangrove forest in Ngoc Hien commune.
文摘Montane forest ecosystems support biodiversity and provide varied ecosystem services to adjacent and downstream human communities. However, human-induced disturbances are common in many of these ecosystems, threatening their capacity to sustain their functions. This study assessed the status of woody vegetation and livestock use of a Kenyan montane forest 10 years after government-sanctioned cessation of human encroachment. The findings can inform suitable interventions that support recovery of abandoned forest settlements subjected to continuous anthropogenic disturbances. Selected woody vegetation attributes and livestock disturbance indicators were assessed across three human-driven disturbance regimes (light, moderate and heavy) using stratified-systematic sampling technique. Data on the extent of community dependence on forest grazing were collected from 381 randomly selected forest adjacent households using semi-structured questionnaires. Information on the palatability of plants to livestock was obtained from Focus Group Discussions. Vegetation data were analyzed using linear mixed models, while descriptive analysis was applied on household survey data. A total of 33 woody plant species belonging to 22 families were identified, out of which 55% were perceived to be unpalatable to livestock. Species richness, species diversity, stem density and basal areas declined significantly with increasing levels of disturbance. Specifically, these attributes were 59% - 98% lower in heavily disturbed sites than in moderately and lightly disturbed sites. A vast majority (88%) of the sampled households grazed their livestock in the forest throughout the year. Evidence from this study indicates that intense past and ongoing anthropogenic disturbances caused significant negative effects on the forest vegetation condition, and lowered its capacity to recover. Forest managers should prioritize minimizing recurrent anthropogenic disturbances as the forest recovers to ensure successful succession and sustainable provision of ecosystem services.
文摘Soil organic carbon （SOC） pool has the potential to mitigate or enhance climate change by either acting as a sink, or a source of atmospheric carbon dioxide （CO2） and also plays a fundamental role in the health and proper functioning of soils to sustain life on Earth. As such, the objective of this study was to investigate the applicability of a novel evolutionary genetic optimization-based adaptive neuro-fuzzy inference system （ANFIS-EG） in predicting and mapping the spatial patterns of SOC stocks in the Eastern Mau Forest Reserve, Kenya. Field measurements and auxiliary data reflecting the soil-forming factors were used to design an ANFIS-EG model, which was then implemented to predict and map the areal differentiation of SOC stocks in the Eastern Mau Forest Reserve. This was achieved with a reasonable level of uncertainty （i.e., root mean square error of 15.07 Mg C ha-l）, hence demonstrating the applicability of the ANFIS-EG in SOC mapping studies. There is potential for improving the model performance, as indicated by the current ratio of performance to deviation （1.6）. The mapping also revealed marginally higher SOC stocks in the forested ecosystems （i.e., an average of 109.78 M C ha-1） than in the aro-ecosvstems （i.e., an average of 95.9 Mg C ha-l）.
