Carbon Sequestration by the Above Ground Biomass Pool in the South West Mau Forest of Kenya, 1985 - 2015

Forests are important for regulation of the global carbon balance. Increase in forest biomass enhances atmospheric carbon sequestration while decrease in forest biomass contributes to carbon dioxide emissions. World over, forest biomass has been declining due to forest loss and degradation. The South West Mau has experienced significant forest loss since 1964. The decline is posited to have significant impacts on carbon sequestration, carbon storage, carbon dioxide emissions and status of atmospheric carbon dioxide. This study assessed interannual trend and variability as well as change point detection in carbon sequestration in South West Mau Forest, Kenya between 1985 and 2015. Above ground biomass carbon sequestration was quantified based on the Carnegie-Ames-Stanford Approach (CASA) and carbon fraction for tropical climate domain. Carbon sequestration dynamics were characterized by increase-decrease cycles of approximately 3 years and low interannual variability (CV= 9.13). It emerged that South West Mau Forest was a net carbon emitter with a carbon sequestration balance of -588.40 Kg/ha between 1985 and 2015. Keywords: Forest, Carbon sequestration, Carnegie-Ames-Stanford Approach, Above ground net primary production DOI: 10.7176/JEES/10-8-05 Publication date:August 31st 202

Trend and Variability in Interannual Air Temperature Over South West Mau Forest, 1985 - 2015

The research is sponsored by Jomo Kenyatta University of Agriculture and Technology and National Commission for Science, Technology and Innovation Kenya. Abstract Globally high altitude forest regions are considered to be more prone to rapid warming. These regions have also shown great seasonal and inter annual temperatures variability. In Kenya mean annual temperatures increased by 1.00C since 1960. Going by global trends it is plausible to argue that high altitude forest areas in Kenya might have shown great seasonal and inter annual temperatures variability over time. This study assessed interannual trend and variability as well as change point detection in average annual air temperature in South West Mau Forest, Kenya between 1985 and 2015. South West Mau Forest is an indigenous montane ecosystem with a tropical montane climate. Annual average air temperature over the South West Mau forest pointed towards climate warming of 0.01880C per year (Kendall’s tau = 0.3677, p value = 0.0033) but with low interannual variability (CV= 0.11%). A shift in the annual average air temperature of 0.3680C at p= 0.0051 was detected between 1985-1998 and 1999- 2015. There was a weak positive anomaly in the annual average air temperature with a slope of 0.0192 and R2 = 0.3074. Overall the region experienced climate warming. Keywords: Climate warming, Trend, Variability, Average temperature DOI: 10.7176/JNSR/11-16-04 Publication date:August 31st 202

High aboveground carbon stock of African tropical montane forests

Tropical forests store 40-50 per cent of terrestrial vegetation carbon(1). However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests(2). Owing to climatic and soil changes with increasing elevation(3), AGC stocks are lower in tropical montane forests compared with lowland forests(2). Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network(4) and about 70 per cent and 32 per cent higher than averages from plot networks in montane(2,5,6) and lowland(7) forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa(8). We find that the low stem density and high abundance of large trees of African lowland forests(4) is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse(9,10) and carbon-rich ecosystems. The aboveground carbon stock of a montane African forest network is comparable to that of a lowland African forest network and two-thirds higher than default values for these montane forests.Peer reviewe

Estimation of Tree Height and Forest Biomass Using Airborne LiDAR Data: A Case Study of Londiani Forest Block in the Mau Complex, Kenya

Tactical decisions on natural resource management require accurate and up to date spatial information for sustainable forest management. Remote sensing devices by the use of multispectral data obtained from satellites or airborne sensors, allow substantial data acquisition that reduce cost of data collection and satisfy demands for continuous precise data. Forest height and Diameter at Breast Height (DBH) are crucial variables to predict volume and biomass. Traditional methods for estimation of tree heights and biomass are time consuming and labour intensive making it difficult for countries to carry out periodic National forest inventories to support forest management and REDD+ activities. This study assessed the applicability of LiDAR data in estimating tree height and biomass in a variety of forest conditions in Londiani Forest Block. The target forests were natural forest, plantation forests and other scattered forests analysed in a variety of topographic conditions. LiDAR data were collected by an aircraft flying at an elevation of 1550 m. The LIDAR pulses hitting the forest were used to estimate the forest height and the density of the vegetation, which implied biomass. LiDAR data were collected in 78 sampling plots of 15 m radius. The LiDAR data were ground truthed to compare its accuracy for above ground biomass (AGB) and height estimation. The correlation coefficients for heights between LiDAR and field data were 0.92 for the pooled data, 0.79 in natural forest, 0.95 in plantation forest and 0.92 in other scattered forest. AGB estimated from LiDAR and ground truthed data had a correlation coefficient of 0.86 for the pooled data, 0.78 in natural forest, 0.84 in plantation forest and 0.51 in other scattered forests. This implied 62%, 84%and 89% accuracy of AGB estimation in natural forests, other scattered forests and plantation forests respectively. The even aged conditions of plantation forests might have resulted to better estimates of height and AGB as compared to uneven aged natural forests and scattered forests. The results imply the reliability of using Airborne LIDAR scanning in forest biomass estimates in Kenya and are an option for supporting a National Forest Monitoring System for REDD+

Allometric Equations for Estimating Silk Oak (Grevillea robusta) Biomass in Agricultural Landscapes of Maragua Subcounty, Kenya

Grevillea robusta is widely interplanted with crops in Maragua subcounty, a practice that enhances biomass quantities in farmlands. However, quick tools for estimating biomass of such trees are lacking resulting in undervaluation of the farm product. This study sought to develop allometric equations for estimating tree biomass using diameter at breast height (DBH) and tree height as predictor variables. Tree biomass was computed using thirty-three (33) trees randomly selected from 12 one hectare plots established in each of the four agroecological zones (AEZs). DBH of all Grevillea robusta trees per plot was measured and three trees were selected for destructive sampling to cover the variety of tree sizes. Regression analysis was used to develop equations relating DBH/tree height to biomass based on linear, exponential, power, and polynomial functions. The polynomial and the power equations had the highest R2, lowest SEE, and MRE values, while DBH was the most suitable parameter for estimating tree biomass. The tree stem, branches, foliage, and roots biomass comprised 56.89%, 14.11%, 6.67%, and 22.32% of the total tree biomass, respectively. The mean tree biomass density (12.430±1.84 ton ha−1) showed no significant difference (p=0.09) across AEZs implying no difference in G. robusta agroforestry stocks across the AEZ. The allometric equations will support marketing of tree products by farmers and therefore better conservation and management of the tree resource

Field manual for tree volume and biomass modelling

Improving capacity in forest resources assessment in Kenya (IC-FRA)201

HIV infection, malnutrition, and invasive bacterial infection among children with severe malaria

Background. Human immunodeficiency virus (HIV) infection, malnutrition, and invasive bacterial infection (IBI) are reported among children with severe malaria. However, it is unclear whether their cooccurrence with falciparum parasitization and severe disease happens by chance or by association among children in areas where malaria is endemic. Methods. We examined 3068 consecutive children admitted to a Kenyan district hospital with clinical features of severe malaria and 592 control subjects from the community. We performed multivariable regression analysis, with each case weighted for its probability of being due to falciparum malaria, using estimates of the fraction of severe disease attributable to malaria at different parasite densities derived from cross-sectional parasitological surveys of healthy children from the same community. Results. HIV infection was present in 133 (12%) of 1071 consecutive parasitemic admitted children (95% confidence interval [CI], 11%–15%). Parasite densities were higher in HIV-infected children. The odds ratio for admission associated with HIV infection for admission with true severe falciparum malaria was 9.6 (95% CI, 4.9– 19); however, this effect was restricted to children aged ≥1 year. Malnutrition was present in 507 (25%) of 2048 consecutive parasitemic admitted children (95% CI, 23%–27%). The odd ratio associated with malnutrition for admission with true severe falciparum malaria was 4.0 (95% CI, 2.9–5.5). IBI was detected in 127 (6%) of 2048 consecutive parasitemic admitted children (95% CI, 5.2%–7.3%). All 3 comorbidities were associated with increased case fatality. Conclusions. HIV, malnutrition and IBI are biologically associated with severe disease due to falciparum malaria rather than being simply alternative diagnoses in co-incidentally parasitized children in an endemic area