Weather information (WI) related reliability problems and constraints are commonly reported factors forfarmers’ adaptation decisions to climate-induced impacts in Ethiopia. However, the level of reliability of theWI, kinds of the WI constraints, and how these constraints impede farmers’ adaptation decisions have notsystematically been studied. The present study investigated the reliability and constraints of WI from farmers’perspective in East Gojjam Zone. Three hundred fifty-eight farm households were selected from three woredasthrough random sampling. Interview surveys, focus group discussions, and key informant interviews wereapplied to generate quantitative and qualitative datasets. Frequency, mean score, and correlation wereemployed to analyze the quantitative dataset, while descriptive-interpretative method was used to analyzethe qualitative ones. The findings disclosed that farmers in the study area have diverse WI sources thoughonly farmers’ own experiences and development agents were perceived to be reliable sources for them.The correlation coefficient results confirmed that the number of WI sources had significant positive relationswith family size, and farmland size, while it had a non-significant negative correlation with the farm experiencesof the household heads. The study also identified a range of socioeconomic, demographic and institutional factors, and programming mechanisms and information contents of which the four top that negatively affect farmers’ adaptation decisions were spatial ambiguity, lack of trust, lack of information about the seasonal onset, itsend, and its distribution within the season. To guide farmers’ effective adaptation decisions, these constraints inthe information contents of the WI have to be resolved.KeywordsWeather information, reliability, constraints, East Gojjam, Ethiopia

Dry evergreen Afromontane forests are severely threatened due to the expansion of agriculture and overgrazing by livestock. The objective of this study was to investigate the composition of woody species, structure, regeneration status and plant communities in Seqela forest, as well as the relationship between plant community types and environmental variables. Systematic sampling was used to collect vegetation and environmental data from 52 (20 m x 20 m) (400 m2) plots. Density, Diameter at Breast Height (DBH), basal area, frequency, and importance value index (IVI) of woody species were computed to characterize the vegetation structure of the forest. Agglomerative hierarchical cluster analysis and Canonical Correspondence Analysis (CCA) with R software were used to identify plant communities and analyse the relationship between plant community types and environmental variables, respectively. A total of 68 woody plant species belonging to 63 genera and 44 families were identified. The Shannon diversity index and evenness values of the study area were 2.12 and 0.92, respectively. The total basal area and density of woody species were 27.4 m2 ha-1 and 1079.3 individual ha-1, respectively. The most frequent woody species in the Seqela forest included Albizia gummifera (51.92%), Croton macrostachyus (44.23%), Olinia rochetiana and Teclea nobilis (36.54%). Additionally, the most dominant species, as indicated by their importance value index (IVI), were Erythrina brucei (IVI = 11.24), Prunus africana (IVI=8.68), and Croton macrostachyus (IVI=7.38). Four plant community types were identified: Albizia gummifera - Ekebergia capensis, Prunus africana - Croton macrostachyus, Vachellia abyssinica - Dombeya torrida and Schefflera abyssinica - Teclea nobilis. The CCA results showed that the variation of species distribution and plant community formation were significantly (P < 0.05) related to altitude, organic matter, aspect, slope and soil available phosphorus. The regeneration status assessment of the forest revealed a good regeneration status, which was linked to diverse and abundant seed bank in the soil can ensure a continuous supply of seeds for regeneration; therefore, it is recommended to implement periodic soil seed bank assessments to monitor seed diversity and abundance and inform targeted conservation actions.

Smallholders cultivated sugarcane for household consumption, immediate cash, and feedinglivestock in Ethiopia. However, its production and productivity are constrained by a lack ofimproved varieties. Sugarcane germplasm was collected from Districts of West Gojjam,Ethiopia, to evaluate yield and its contributing characters and quantify the phenotypic diversityat Mankusa, Jabitehnan, Ethiopia. The experiment was conducted using a randomised completeblock design with three replications for two crop cycles, from April 2020 to March 2023. Datawere recorded for the number of tillers, internode length, sellable stalks, plant height, stalkdiameter, cane yield and biomass yield from twelve genotypes collected. The data recorded weresubjected to analysis of variance, and means were separated using the Duncan Multiple RangeTest at a 5% significance level. Variance and multivariate analysis indicated the existence ofhigh phenotypic diversity between genotypes in all quantitative traits studied. Acc 7/20 and Acc5/20 genotypes produced the highest number of tillers and longest internodes, while Acc 6/20produced the highest number of sellable stalks. The genotype Acc 4/20 was the longest, and thethickest genotype, which could be elite donors for it respected quality traits through crossing.The highest cane yield was recorded from Acc 4/20 (178.04 t/ha), Acc 7/20 (151.41 t/ha), Acc8/20 (134.1 t/ha) and Acc 12/20 (132 t/ha), producing 58, 34, 19 and 17% advantageous fromthe overall genotypes mean, respectively. Cluster analysis grouped the twelve sugarcanegenotypes into four clusters, indicating the possibility of broadening the genetic basis bycrossing genotypes in the different clusters. It also indicated that a cross between cluster II andIII genotypes could create the thickest canes with many sellable stalks. Therefore, genotypes Acc04/20, Acc 07/20, Acc 8/20 and Acc 12/20 have been recommended and must be evaluated in other sugarcane growing areas to exploit their potential.Keywords: Cluster Analysis, PCA, Sugarcane, Variability, Yield