Climate variability and impacts on maize (Zea mays) yield in Ghana, West Africa

Abstract

Rain-fed agriculture is predominantly the primary source of livelihood in sub-Saharan Africa. In Ghana, it employs over 60% of the population and contributes to about 30% of the Gross Domestic Product (GDP). Despite the relevance of rain-fed agriculture to the socioe-conomic development of the country, studies investigating the impacts of climate variability on crop yield in the region are limited. This prevents the growth of relevant policy frameworks to address the threats posed by climate variability on crop production. As a contribution to guide policy planning and food security in Ghana, the present study seeks to analyze the vulnerability of maize yield to rainfall, soil moisture, and minimum and maximum temperature variability in Ghana. Moreover, the study assesses the impact of below-normal and above-normal rainfall conditions on maize yield in the country. The results show a decreasing trend in rainfall and soil moisture and an increasing trend in the maize yield and minimum and maximum temperature in Ghana. The individual climate variables (rainfall, soil moisture, minimum and maximum temperature) account for approximately 4.2, 22.5, 39.2, and 23.1%, respectively, of the annual maize yield variations throughout the study period. Multivariate regression analysis revealed that soil moisture and minimum and maximum temperature account for approximately 75% of the variation of maize yield under wetter-than-normal conditions in Ghana. This implies that, under wetter-than-normal rainfall conditions, 25% of the variation in maize yield could be attributable to non-climatic conditions or practices. In like manner, climatic parameters account for 40.8% of maize yield under drier-than-normal rainfall conditions in the country. This study, therefore, recommends investment in climate-smart agronomic technologies such as access to improved seed, extension and mechanization services, and other farm management practices to maximize maize yield in the country.

Adoption of climate-smart agricultural practices by smallholder farmers in rural Ghana: An application of the theory of planned behavior

“…Increased rainfall variability and drought associated with climate change poses the greatest challenge to the food systems and sustainable agricultural development of sub-Saharan Africa (SSA) [1,2] and to the region's food and nutrition security [3]. SSA is regarded as the most vulnerable region to the negative impacts of climate change, because of structural and institutional weakness, high poverty levels and the low adoption of modern techniques that limits farmers' capacity to adapt [4][5][6].…”

“…Climate-Smart Agriculture aims to achieve three pillars: (1) sustainably increase agricultural productivity and incomes; (2) enhance farmers' adaptive capacity and build resilience; and (3) reduce the emission of greenhouse gases (GHGs) [12,13]. It has become imperative for farmers in developing countries to adopt and use CSA practices since they include numerous inexpensive farm-based sustainable agricultural land management techniques such as water management, zero/minimum tillage, residue management, and agroforestry among others.…”

Trends of Rainfall Onset, Cessation, and Length of Growing Season in Northern Ghana: Comparing the Rain Gauge, Satellite, and Farmer’s Perceptions

“…Global ecosystems are experiencing changes in rainfall amount, intensity, and temporal distributions [1] that poses a great challenge to agricultural production [2][3][4]. Trends of rainfall amount are widely documented [5,6] but shifts in rainfall seasonality (onset and cessation) have received less attention although it determines timing of cropping calendar activities.…”

Spatial and temporal distribution of optimal maize sowing dates in Nigeria

“…Consequently, maize yield variability has ranged from 42–78.3%, with maize yields varying from 44.5 kg/ha to 4830 kg/ha over the period 1979–2009 [ 7 ]. In Ghana climate variability explains maize yield variations of 4.2, 22.5, 39.2 and 23.1% through changes in rainfall, soil moisture, minimum and maximum temperature for the period, 1981–2015 [ 10 ].…”