The Effect of Climate Change on Milk Production in Smallholder Farms; a Case of Nandi County, Kenya

Abstract

Climate variability changes ultimately impact agriculture and food productivity, and security. In Kenya, milk production is predominantly smallholder and dependent on rain-fed agriculture. To ensure that dairy farmers are empowered to prepare effectively, adapt and mitigate the effect of extreme climate changes, this study aimed to investigate the effect of climate change on milk production in smallholder farms; the case of Nandi county, Kenya. Primary data was sourced through structured questionnaires, focus group discussions (FGD), and key informant interviews. Secondary data sources data included observed and climate model outputs (precipitation, maximum and minimum temperature), fodder availability (Normalized Difference Vegetation Index –NDVI and Soil Moisture), and milk production (milk marketed). The study used a concurrent triangulation research design to allow mixed-methods research methodologies. Trend analysis and spatial plots were used to analyse spatiotemporal variability of past and future climate (2021-2050) based on RCP45 and RCP85. The relationship between climate and milk production was based on correlation and multi-regression analysis. Graphical and pie chart analyses were also used to present the results. Past and projected precipitation showed bimodal patterns with high spatial and temporal variability with remarkable differences between baseline and projected precipitation under RCP45 (-19.5% to 11.0%) and RCP85 (-9.5% and 26.3%) scenarios. Past and projected maximum and minimum temperatures showed increasing trends. Monthly NDVI and soil moisture values were higher in April and November, while seasonal values were high/low in JJA/DJF, indicating high/low fodder availability. Milk production showed a positive change from 2007 to 2016, with the highest/lowest values in April/December. Computed percentage change in seasonal milk production showed increases of up to 186% (MAM), 183% (JJA), 202% (SON), and 214% (DJF), whereas annual milk production showed increases of up to 204%. Correlation analysis found low coefficients in precipitation and higher coefficients in minimum temperature at lag 0, 1 and 2. The selected

models were based on different climate and fodder availability predictors and showed a positive relationship with milk production. Over 79% of households involved in milk production in Nandi County are male. Although the drought was the leading climate hazard affecting their grazing practices, other factors such as rainfall variability, unpredictability and extreme temperatures also affected grazing practices. The survey results indicated that observed changes in milk production, the amount of water available for the animal, body condition of the animal, heat detected, and growth of calves and heifers were negative in most of the wards in the County. The most important source of animal feed were natural pastures, mainly from own farms (86.9%), crop residue (62.6%), planted fodder such as Nappier grass (39.4%), and communal land (19.2%). The majority of farmers planted fodder in less than 0.5 acres of land for Napier (79.7%), Sorghum (54.3%), Rhodes grass (57.3%), Kikuyu Grass (49.4%), Lucerne (71.9%) and fodder Tree (82.1%) and conserved/preserved crop residue (88.2%), hay (39.9%) and silage (35.4%). Communal lands were overgrazed, and very little fodder was available, with the grass growth not beyond one foot. Methods used to address negative experiences of climate change include the use of conserved hay/silage (44.2%), buying of commercial feeds (40.9%), use of crop residue (74.6%), moving of animals to other farms (8.8%) and selling of animals (17.4%). Other measures adopted by households to help them avert negative climate change included the use of new fodder types/varieties, new planning methods, intercropping of different fodder, and conservation and preservation practices. Smallholder farms had also adopted Climate Smart Agricultural (CSA) technologies such as compost making (18.6%), use of biogas (2.5%), water conservation (56.6%), disease control (95.4%), planting of fodder trees (30.1%), reducing the number of animals (36.6%) and breeding using AI (63.4%). The study findings indicate that dairy productivity is highly sensitive to climate. Moreover, fodder availability which is also vulnerable to changes in climate, significantly influences milk production. Given the high spatial and temporal variability in these environmental factors, it is

expected that the projected change will significantly challenge future dairy productivity, especially in Nandi County of Kenya. The study recommends the need to improve on monitoring of weather and climate by increasing observation stations and developing weather and climate products targeting milk production. There is also a need to develop climate-smart fodder varieties/production methods and adopt climate-smart fodder varieties/production methods. Moreover, policy makers need not only to promote the use of climate-smart fodder varieties/production methods but also mainstream climate change information into development planning, budgeting and implementation at national and county levels