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

Revisiting application of statistics in Agricultural Research in sub-Saharan Africa: Entry points for improvement

The importance of statistics in empowering the agricultural research process and sharpening interventions cannot be over-emphasized. Undocumented evidence points to misconceptions, misuse or underuse of statistics among agricultural researchers in sub-Saharan Africa (SSA); pointing to the possibility that the subject has been part of the causes the unfulfilled targets in the agricultural sector in the region. The objective of this study was to analyse and document weaknesses in statistical practice in agricultural research, with a view to identifying entry points for strengthening the performance of the sector for SSA to be able to achieve its set goals. A desk study involving 165 research articles published in the African Crop Science Journal over the period of 17 years (2000 to 2017) was conducted through a rigorous SWOT analysis for issues related to the use of statistics in the implementation of agricultural research in SSA. A checklist consisting of key elements related to study design; data collection, analysis and exploitation; and presentation, was used to guide the interrogation. Findings indicated that researchers generally made explicit description of treatment structures that fairly matched the study objectives and hypotheses (in the few cases where they were stated), with a few weaknesses in the description of factorial treatment structure. The Randomised Complete Block Design was most commonly used among the designs, with 3-4 replicates. However, there was hardly any justification for its use, as the blocking factors were never mentioned and thus their role in determining the precision of the results was difficult to determine. Analysis of Variance was the main method for data analysis, followed by correlations. The F-test and the associated P-values were the basis for decisions on treatment differences. Most researchers had problems with presentation and interpretation of P-values and significance level. Post adhoc tests mostly used the Least Significant Difference (LSD) for pairwise mean comparisons, with little consideration for the treatment structure, the number of treatments and the nature (qualitative or quantitative). Generally, estimates of treatment means were presented together with various measures of precision, in both tables and graphical forms. In several cases, LSD was used or misused interchangeably with standard error (SE) or standard error of difference (SED). Several statistical software were used for data analysis and presentation, with the main ones being SAS, Genstat and MSTAT-C. Key entry points for improvement heavily lie in human and infrastructural resource capacity improvement, most specifically in (i) periodic review of university and other tertiary institutions\u2019 curricula to provide sufficient time allocation, physical space and relevant infrastructure for true hands on practice; (ii) more effective utilisation of the few statisticians available in the region, (iii) short term staff in-service retooling courses, (iv) sustained statistical service units wherever necessary, and (v) provision for periodic interactive statistician-researcher platforms (such as conferences and workshops) for sharing notes on challenges and achievements during implementation of their research programmes.L\u2019importance des statistiques pour renforcer le processus de recherche agricole et affiner les interventions ne saurait \ueatre trop soulign\ue9e. Des preuves non document\ue9es font ressortir des id\ue9es fausses, un usage abusif ou un usage insuffisant des statistiques parmi les chercheurs en agriculture en Afrique subsaharienne (ASS); soulignant la possibilit\ue9 que le sujet ait fait partie des causes des objectifs non atteints dans le secteur agricole de la r\ue9gion. L\u2019objectif de cette \ue9tude \ue9tait d\u2019analyser et de documenter les faiblesses de la pratique d\u2018 utilization de la statistique en mati\ue8re de recherche agricole, en vue d\u2019identifier les points d\u2019entr\ue9e permettant de renforcer les performances du secteur afin que l\u2019ASS puisse atteindre ses objectifs fix\ue9s. Une \ue9tude th\ue9orique comprenant 165 articles de recherche publi\ue9s dans le journal African Crop Science Journal dans une p\ue9riode de 17 ans (2000 \ue0 2017) qui ont \ue9t\ue9 r\ue9alis\ue9es au moyen d\u2019une analyse SWOT rigoureuse des probl\ue8mes li\ue9s \ue0 l\u2019utilisation des statistiques dans la mise en \u153uvre de la recherche agricole en ASS. Une liste de contr\uf4le comprenant des \ue9l\ue9ments cl\ue9s li\ue9s \ue0 la conception de l\u2019\ue9tude; collection, analyse et exploitation de donn\ue9es; et pr\ue9sentation, a \ue9t\ue9 utilis\ue9 pour guider l\u2019interrogatoire. Les r\ue9sultats ont indiqu\ue9 que les chercheurs avaient g\ue9n\ue9ralement d\ue9crit de mani\ue8re explicite les structures de traitement correspondant assez bien aux objectifs et hypoth\ue8ses de l\u2019\ue9tude (dans les cas rares o\uf9 elles avaient \ue9t\ue9 \ue9nonc\ue9es), avec quelques faiblesses dans la description de la structure de traitement factoriel. Le dispositif en bloc (fisher) randomis\ue9 \ue9tait le plus couramment utilis\ue9 parmi les dispositifs, avec 3 \ue0 4 r\ue9plicats. Cependant, son utilisation n\u2019\ue9tait gu\ue8re justifi\ue9e, car les facteurs de blocage n\u2019\ue9taient jamais mentionn\ue9s et leur r\uf4le dans la d\ue9termination de la pr\ue9cision des r\ue9sultats \ue9tait donc difficile \ue0 d\ue9terminer. L\u2019analyse de la variance \ue9tait la principale m\ue9thode d\u2019analyse des donn\ue9es, suivie par les corr\ue9lations. Le test F et les valeurs P associ\ue9es constituaient la base des d\ue9cisions sur les diff\ue9rences de traitements. La plupart des chercheurs ont eu des probl\ue8mes de pr\ue9sentation et d\u2019interpr\ue9tation des valeurs de p et du niveau de signification. Les tests post adhoc ont principalement utilis\ue9 la diff\ue9rence la moins significative (DMS) pour les comparaisons moyennes par paires, en prenant peu en compte la structure du traitement, le nombre de traitements et la nature (qualitative ou quantitative). En g\ue9n\ue9ral, les estimations des moyennes de traitement \ue9taient pr\ue9sent\ue9es avec diverses mesures de pr\ue9cision, sous forme de tableaux et de graphiques. Dans plusieurs cas, le DMS a \ue9t\ue9 utilis\ue9 ou utilis\ue9 de mani\ue8re interchangeable avec l\u2019erreur standard (ES) ou l\u2019erreur standard de diff\ue9rence (ESD). Plusieurs logiciels statistiques ont \ue9t\ue9 utilis\ue9s pour l\u2019analyse et la pr\ue9sentation des donn\ue9es, les principaux \ue9tant SAS, Genstat et MSTAT-C. Les points principaux d\u2019am\ue9lioration d\ue9pendent essentiellement de l\u2019am\ue9lioration de la capacit\ue9 des ressources humaines et infrastructurelles, plus particuli\ue8rement de (i) la r\ue9vision p\ue9riodique des programmes d\u2019\ue9tudes des universit\ue9s et autres \ue9tablissements d\u2019enseignement sup\ue9rieur afin de pr\ue9voir suffisamment de temps, un espace physique et une infrastructure appropri\ue9e pour une v\ue9ritable mise en pratique; (ii) une utilisation plus efficace des quelques statisticiens disponibles dans la r\ue9gion, (iii) des cours de r\ue9outillage en cours \ue0 court terme pour le personnel, (iv) des unit\ue9s de services statistiques durables, le cas \ue9ch\ue9ant, et (v) la mise en place de plates-formes interactives interactives de statisticiens et de chercheurs ( conf\ue9rences et d\u2019ateliers d\u2019\ue9criture) pour partager des notes sur les d\ue9fis et les r\ue9alisations au cours de la mise en \u153uvre de leurs programmes de recherche

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

Limiting nutrients for bean production on contrasting soil types of Lake Victoria Crescent of Uganda

Common bean (Phaseolus vulgaris L.) is one of the most important grain legumes in East Africa, but its yield has remained below the genetic potential. Declining soil fertility is among the primary constraints to bean production in most East African bean producing regions. Often existing recommendations are generic and inept to guide farm level decision making on nutrient replenishment. A greenhouse nutrient omission study was conducted to determine the limiting nutrients in three soils of Masaka District, commonly cropped to beans: “Liddugavu” a Phaeozem, “Limyufumyufu” a Cambisol and “Luyinjayinga” an Umbrisol soil. Nine treatments; (i) complete nutrient treatment, (ii) N omitted, (iii) P omitted, (iv) K omitted, (v) Mg omitted, (vi) S omitted, (vii) Ca omitted, (viii) Micronutrients omitted and (ix) control without nutrients. Each treatment was randomly assigned to the three soils and replicated three times using a completely randomised design. Nitrogen, phosphorus and potassium were limiting nutrients for bean production in Umbrisol (Luyinjayinja) while in Cambisol (‘Limyufumyufu), common bean production was most limited by soil acidity. The performance varied with soil types, with beans grown on the Phaeozem registering greater leaf number and growth, confirming both scientist’s and local farmer’s knowledge that this soil has greater potential than the other two soils

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

PARTNERSHIPS IN HIGHLANDS OF RWANDA UNDER INTEGRATED AGRICULTURAL RESEARCH FOR DEVELOPMENT (IAR4D) ARRANGEMENTS

The Integrated Agricultural Research for Development (IAR4D) concept was proposed to respond to the failures of Agriculture Research and Development (ARD) systems in Sub-Saharan Africa. The key element of implementation and success of IAR4D was action sites called agricultural Innovation Platform (IPs) and their counterfactual sites. Social Network Analysis (SNA) is used to explain social relationships and partnerships. This study explored the patterns of agricultural partnerships among stakeholders in the highlands of Rwanda under IAR4D. Data were collected in action sites that included Mudende, Gataraga, Remera and Rwerere; and in their counterpart counterfactual sites that comprised of Bigogwe, Nyange and Gacaca. Results showed that in action sites, stakeholders were linked to different and diversified partners. Furthermore, many stakeholders were connected to several partners through agricultural partnerships, hence creating complex social networks with high density and degree of distribution. In the counterfactual sites, however, stakeholders were exclusively linked to the same kind of partners, and one stakeholder was connected to one partner through probably non-agricultural partnerships. These facts demonstrated that IAR4D created dense interfaces, significantly improved the networking system, and delivered technologies and innovations.Le concept de Recherche Agricole Int\ue9gr\ue9e pour le D\ue9veloppement (IAR4D) a \ue9t\ue9 propos\ue9 comme solution aux \ue9checs des syst\ue8mes Recherches Agricoles et D\ue9veloppement (ARD) en Afrique Sub-Saharienne. L\u2019\ue9l\ue9ment principal de la r\ue9ussite et du succ\ue8s d\u2019IAR4D \ue9tait l\u2019\ue9tablissement des sites d\u2019action appel\ue9s Plateformes Agricoles d\u2019innovation (IPs) ainsi que leurs sites t\ue9moins. L\u2019analyse du R\ue9seau Sociale (SNA) est utilis\ue9e pour expliquer les rapports et les relations sociaux des acteurs et des partenaires. La pr\ue9sente \ue9tude avait pour objectif d\u2019explorer les structures des relations socio-agricoles parmi les acteurs et les partenaires dans les hautes altitudes du Rwanda soumises \ue0 l\u2019IAR4D. Les donn\ue9es ont \ue9t\ue9 r\ue9colt\ue9es dans les sites d\u2019action comprenant\ua0: Mudende, Gataraga, Remera et Rwerere ainsi que dans leurs contreparties sites t\ue9moins incluant Bigogwe, Nyange et Gacaca. Les r\ue9sultats ont montr\ue9 que dans les sites d\u2019action, les acteurs \ue9taient associ\ue9s aux partenaires de natures diff\ue9rentes et un acteur \ue9tait li\ue9 \ue0 plusieurs partenaires a la fois. Dans les sites t\ue9moins par contre, les acteurs \ue9taient li\ue9s aux partenaires de m\ueames natures que ceux-ci et un acteur \ue9tait rarement li\ue9 \ue0 plus de deux partenaires. Ces faits ont montr\ue9 que l\u2019IAR4D a cr\ue9e un r\ue9seau socio-agricole tr\ue8s dense et sophistiqu\ue9 et ainsi a consid\ue9rablement am\ue9lior\ue9 le r\ue9seau socio-agricole. Par cons\ue9quent, l\u2019IAR4D peut \ueatre recommand\ue9 pour le transfert the technologies and des innovations agricoles

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