Estimation of the aboveground biomass in the trans-boundary River Sio Sub-catchment in Uganda

The enormous land cover in Uganda is rapidly being depleted or encroached. To examine this, the study aimed at estimating the above-ground biomass in River Sio sub-catchment in Uganda. The study utilized an ortho-rectified Landsat TM/ETM image of 2004 which was classified using NDVI classification system for the aboveground biomass assessment in ILWIS 3.3 software. A total of 42 homogenous sampling sites were identified for biomass estimation along six laid transects measuring 500m long. The seven randomly selected sampling plots measured 50m X 50 m. The classification showed that Bushlands (0.17), wetlands (0.03) and small scale farming (- 0.29-0.03) had relatively more medium and low biomass ranges compared to grasslands (-0.41/-0.29) which mainly comprised of bare land. The above ground biomass was relatively higher in bushlands (4.9 tons) and wetlands (4.7 tons) compared to non-uniform small scale farming (farmlands) with 3.9 tons and grasslands with 1.6 tons. The variation in biomass shows that the sub-catchment requires an urgent need for land use/cover planning and management to prevent further degradation of land cover

Correlation between sunshine hours and climatic parameters at four locations in Uganda

One of the most important factors in solar energy production is related to the predictability of sunshine hours. The objective of this study is to assess the correlation between sunshine hours and relative humidity, cloud cover, maximum and minimum temperature, for the purpose of identifying the most appropriate parameter(s) for the prediction of sunshine hours in Uganda. Climatic data for the meteorological stations of Entebbe, Mbarara, Tororo and Makerere, extending over a period of 15 years (1990-2005) was collected from the Department of Meteorology, Kampala. The data set included maximum temperature, minimum temperature, relative humidity at 6 am and at 12 noon, Cloud cover at 6 am and at 12 noon and Sunshine hours. A multiple regression technique was used to assess the correlation between sunshine hours and maximum and minimum temperatures, cloud cover at 6 am and at 12 noon and relative humidity at 6 am and at 12 noon. Results have shown that the availability of sunshine hours can be predicted by the use of maximum and minimum temperatures, relative humidity at 6 am and 12 noon and cloud cover at 6 am and at 12 noon in Uganda, but, principal components and factoraAnalysis have indicated that two parameters, especially relative humidity at noon or 6 am and Maximum temperature are enough to capture the variability of sunshine hours in Uganda

Sediment and nutrient loads into river Lwiro, in the Lake Kivu basin, Democratic Republic of Congo

This study assessed sediment and nutrient loads in Lwiro river, Lake Kivu basin in the Democratic Republic of Congo. Water discharge was measured and water samples were collected twice a month from 6 sites in Lwiro river system and analyzed for total suspended sediment (SS), temperature, pH, dissolved oxygen (DO), chemical oxygen demand (COD), five-day biological oxygen demand (BOD5), alkalinity and nutrients (P, N, PO43-, NO3- and NH4+) using standard methods. Results show that the concentration of BOD5 was low (1.08 ± 0.83 mg/L); but COD (13.13 ± 6.26 mg/L) and SS (1.15 ± 0.36 mg/L) were high in the industrial effluent than in agricultural effluent (2.7 ± 0.77 mg/L for BOD5; 9.05 ± 3.55 mg/L for COD and 0.81 ± 0.36 mg/L for TSS). It was observed that all these values were low compared to the standard limit proposed by UNECE and Uganda standard. TSS, nutrient and other chemicals parameters load analyzed were high in agriculture effluent than in industrial effluent except for NH4+ load. Temporal variation and site difference between TSS and nutrient load were significantly different (F=5.54, p< 0.005 for SS; F= 8.59, p< 0.005 for TP and F=7.63, p< 0.005 for TN). Techniques for reducing nutrient and TSS loads should be initiated in the microcatchment to protect the Lake Kivu.Keywords: Sediment; nutrient load; industrial; agriculture effluent; Lwiro river; Lake Kivu

Dynamics of forest cover conversion in and around Bwindi impenetrable forest, Southwestern Uganda

Forest cover has been converted to agricultural land use in and around the protected areas of Uganda. The objectives of this study were; to examine the dynamics of forest cover change in and around Bwindi impenetrable forest between 1973 and 2010 and to identify the drivers of forest cover change. The trend in forest cover change was assessed by analyzing a series of orthorectified landsat imageries of 1973, 1987 and 2001 using unsupervised and supervised classification. Land use/cover map for 2010 was reconstructed by analyzing 2001 image, validated and/or reconstructed by ground truthing, use of secondary data and key informant interviews. A series of focused group discussions and key informant interviews were also used to identify drivers of land use/cover change. Policies and institutional arrangements that could have affected forest cover change for the studied time period were also identified. Results showed that protected forest and woodlot in unprotected area had declined by 7.8% and 70.7% respectively as small scale farming and tea plantations had increased by 13.9% and 78.3% respectively between 1973 and 2010. The conversions were attributed to land use pressure due to population growth, change in socio-economic conditions and institutional arrangements. The severe loss of woodlot outside the protected area not only poses a potential threat to the protected forest but also calls for intervention measures if efforts to mitigate climate change impacts are to be realized

Validation of Farmer Perceived Soil Fertility Improving Tree Species in Agropastoral Communities of Bushenyi District

In sub-Saharan Africa, including Uganda, there is declining soil fertility and limited on-farm use of inorganic fertilizers due to poverty and limited subsidies for inorganic fertilizer use. Thus, integration of soil fertility improving tree species (SFITs) in farming systems remains a plausible option to sustaining soil productivity. However, knowledge of the effects of many of the locally growing farmer perceived soil fertility enhancing tree species on to soil chemical and nutrient contents are thus still lacking, and this has constrained decisions on their adoption and scaling up. The objectives of this paper were to identify farmers' preferred soil fertility improving tree species in agropastoral communities of Kyeizooba subcounty Bushenyi district, and characterize their litter content and assess their effect on selected soil chemical properties. Semistructured questionnaires were administered to 333 randomly selected agropastoral farmers. Litter and soils under canopy soils were sampled from three different environments: Under canopy radius (A), canopy edge (B), open pasture land up to thrice the canopy radius (C). Results revealed Eucalyptus as the most common tree species on livestock farms, followed by Erythrina abyssinica. The highest litter content was recorded for Markhamia lutea (240 g/cm2 under its canopy) followed by Croton macrostachyus (90 g/cm2), and 19 g/cm2 Erythrina abyssinica. Nitrogen was higher (P=.02) in Erythrina abyssinica litter, K and carbon in Croton macrostachyus litter (P=.03). These results give evidence that of soil improvers Erythrina abyssinica, Croton macrostachyus, and Markhamia lutea may positively affect soil fertility. Farmers' indigenous knowledge and or valuation of important tree species can be relied on, and thus, their indigenous knowledge need to be incorporated during identification of tree species for promotion in farming systems

Elaboration of Additional Modules on Climate Smart Agriculture and Climate Information System for Staff, Students, and other Stakeholders in Universities in Africa

The Accelerating Impacts of CGIAR Climate Research for Africa project (AICCRA) working through CCAFS, intends to make CGIAR-led cutting-edge science practices/technologies/tools available throughout Africa; especially in Sub-regions extremely vulnerable to climate change. The Regional Universities Forum for Capacity Building in Agriculture (RUFORUM), a network of 150 universities in 38 countries spanning the whole African continent is a partner in the AICCRA project. RUFORUM’s contribution in the AICCRA project is focused on mobilising African universities, create awareness and enhance the use of Climate Smart Agriculture (CSA) and Climate information services (CIS) knowledge and products developed by the CGIAR Centres and other research institutions engaged in CSA and CIS. Enhancing the use of CSA and CIS involves capacity, knowledge and technology audits at national and institutional level, mobilise CGIAR and other research centres to provide CSA and CIS knowledge, technology and skills and training of faculty to deploy the CSA and CIS products in training, research and outreach. Knowledge transfer and capacity building activities therefore form the central part of RUFORUM’s participation in the AICCRA project

Enhancing animal movement analyses: spatiotemporal matching of animal positions with remotely sensed data using Google Earth Engine and R

Movement ecologists have witnessed a rapid increase in the amount of animal position data collected over the past few decades, as well as a concomitant increase in the availability of ecologically relevant remotely sensed data. Many researchers, however, lack the computing resources necessary to incorporate the vast spatiotemporal aspects of datasets available, especially in countries with less economic resources, limiting the scope of ecological inquiry. We developed an R coding workflow that bridges the gap between R and the multi-petabyte catalogue of remotely sensed data available in Google Earth Engine (GEE) to efficiently extract raster pixel values that best match the spatiotemporal aspects (i.e., spatial location and time) of each animal’s GPS position. We tested our approach using movement data freely available on Movebank (movebank.org). In a first case study, we extracted Normalized Difference Vegetation Index information from the MOD13Q1 data product for 12,344 GPS animal locations by matching the closest MODIS image in the time series to each GPS fix. Data extractions were completed in approximately 3 min. In a second case study, we extracted hourly air temperature from the ERA5-Land dataset for 33,074 GPS fixes from 12 different wildebeest (Connochaetes taurinus) in approximately 34 min. We then investigated the relationship between step length (i.e., the net distance between sequential GPS locations) and temperature and found that animals move less as temperature increases. These case studies illustrate the potential to explore novel questions in animal movement research using high-temporal-resolution, remotely sensed data products. The workflow we present is efficient and customizable, with data extractions occurring over relatively short time periods. While computing times to extract remotely sensed data from GEE will vary depending on internet speed, the approach described has the potential to facilitate access to computationally demanding processes for a greater variety of researchers and may lead to increased use of remotely sensed data in the field of movement ecology. We present a step-by-step tutorial on how to use the code and adapt it to other data products that are available in GEE

Dynamics of forest cover conversion in and around Bwindi impenetrable forest, Southwestern Uganda

Forest cover has been converted to agricultural land use in and around the protected areas of Uganda. The objectives of this study were; to examine the dynamics of forest cover change in and around Bwindi impenetrable forest between 1973 and 2010 and to identify the drivers of forest cover change. The trend in forest cover change was assessed by analyzing a series of orthorectified landsat imageries of 1973, 1987 and 2001 using unsupervised and supervised classification. Land use/cover map for 2010 was reconstructed by analyzing 2001 image, validated and/or reconstructed by ground truthing, use of secondary data and key informant interviews. A series of focused group discussions and key informant interviews were also used to identify drivers of land use/cover change. Policies and institutional arrangements that could have affected forest cover change for the studied time period were also identified. Results showed that protected forest and woodlot in unprotected area had declined by 7.8% and 70.7% respectively as small scale farming and tea plantations had increased by 13.9% and 78.3% respectively between 1973 and 2010. The conversions were attributed to land use pressure due to population growth, change in socio-economic conditions and institutional arrangements. The severe loss of woodlot outside the protected area not only poses a potential threat to the protected forest but also calls for intervention measures if efforts to mitigate climate change impacts are to be realized

LAND USE/COVER CHANGE PATTERNS IN HIGHLAND ECOSYSTEMS OF LAKE BUNYONYI CATCHMENT IN WESTERN UGANDA

Land use and cover changes influence the livelihood and degradation of fragile ecosystems. The extents of these changes in pattern were investigated in Lake Bunyonyi Catchment which lies in the South Western Highlands of Uganda. The dynamics and magnitude of land use and cover changes were assessed using Landsat (TM/ETM+) satellite images and collection of socio-economic data through interviews. The images were processed and analysed using the mean-shift image segmentation algorithm to cluster and quantify the land use and cover features. The study noted that in the assessment period 1987-2014, the small-scale farmlands, open water and grasslands remained quasi constant; while the woodlots followed a quadratic trend, with the lowest acreage experienced in 2000. The tropical high forests and wetlands cover types experienced significant decline over the years (P<0.05). Patches of small-scale farmlands, woodlots, and wetland interchangeably lost or gained more land dependant on climate variability. Even though the tropical high forest lost more than it gained, it only gained and lost to small scale farmland and woodlots; while grassland mainly lost to small scale farmland and woodlots.L\u2019occupation du sol et les changements de couverture influencent la subsistance et la d\ue9gradation des \ue9cosyst\ue8mes fragiles. La tendance des niveaux de ces changements \ue9taient \ue9valu\ue9e dans le basin versant du lac Bunyonyi qui relie les r\ue9gions montagneuses du Sud-Ouest d\u2019Ouganda. Les dynamiques et l\u2019 envergure d\u2019utilisaton de la terre et les changements de couverture \ue9taient \ue9valu\ue9es en utilisant les images du satellite Landsat (TM/ETM+) et la collecte des donn\ue9es socio-\ue9conomiques \ue0 travers des interviews. Les images \ue9taient trait\ue9es et analy\ue9es en utilisant l\u2019algorithme de segmentation de passage-moyen-d\u2019image pour grouper et quantifier les occupations du sol et les caract\ue9ristiques de la couverture. L\u2019\ue9tude a montr\ue9 que dans la p\ue9riode d\u2019\ue9valuation de 1987-2014, la petite \ue9tendue de terres cultivables, l\u2019eau libre et les prairies sont demeur\ue9es quasi constantes; tandis que les terres bois\ue9es ont suivi une tendance quadratique, avec la plus petite superficie observ\ue9e en l\u2019an 2000. Les grandes for\ueats tropicales et les zones humides ont exp\ue9riment\ue9 un d\ue9clin significatif au cours des ann\ue9es (P<0.05). Les petites parcelles de terres agricoles, les terres bois\ue9es, et les zones humides indistinctement ont perdu et gagn\ue9 plus de terres d\ue9pendamment de la variabilit\ue9 climatique. Bien que la grande for\ueat tropicale aie perdu plus qu\u2019elle en a gagn\ue9e; elle a seulement perdu de tr\ue8s petites \ue9tendues de terres agricoles et bois\ue9es; alors que les prairies ont principalement perdu de tr\ue8s petites \ue9tendues de terres agricoles et bois\ue9es