Anarah Samuel Emeka1, Okoye Chukwuemeka Uzoma2, Ositanwosu Chukwunonso.O3, Umeukeje Adaeze Peace4 and Joseph Oluwaseun Komolafe5
1Department of Agricultural Economics and Animal Science, Nnamdi Azikiwe University, Awka; 2Department of Agricultural Economics, University of Nigeria, Nsukka
*Corresponding author: samuelanarah@gmail.com; se.anarah@unizik.edu.ng
This investigation quantifies the influence of inter-annual climate variability alongside long-term climate trends on agricultural output across Nigeria for the period 1991-2022. Attention is centred on dominant meteorological drivers specifically precipitation, air temperature, solar radiation, atmospheric CO2 concentrations, and relative humidity with yield responses of principal crops being the dependent variable of interest. Using rigorously sourced secondary data, the empirical analysis adopts the Autoregressive Distributed Lag (ARDL) model complemented by preliminary stationarity assessment via both Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests to confer confidence in the estimation procedures. The statistical outputs indicate that, within a lag structure, rainfall, thermal energy, and photon flux exert an overall positive but heterogeneously tempered influence on yields, with the crop-to-climatic response exhibiting significant temporal lags. Conversely, atmospheric CO2 and humidity albeit with delayed feedback pathways exhibit negative damping effects, thereby underscoring the intricate and delayed nexus between plant physiology and altered atmospheric regimes. Collectively, the evidence substantiates a pronounced and polycentric attenuation of agricultural productivity traceable to long-term climate change within the observed cohort. The analysis thereby advocates the prompt execution of geographically tailored adaptive measures, comprising (i) the dissemination of climate-resilient cultivars, (ii) systematic enlargement of irrigation networks to mitigate rainfall variability, and (iii) consolidation of agricultural extension systems to elevate farm-level adaptive capacity.