- The study examined the effect of climate change on maize production in Nigeria from 1980-2010.
- The results showed average annual rainfall and temperature were 1288.311mm and 31.7173°C respectively over this period. Average annual maize output was 4.84 metric tons.
- Maize area cultivated and productivity increased with rising temperature and rainfall over time. However, maize output and area cultivated decelerated later in the period, likely due to increasing temperature and rainfall. Productivity accelerated.
2. Effect of climate change on maize production in Nigeria
Obasi and Uwanekwu 022
There is a growing consensus in scientific literature that
over the coming decades, higher temperature and
changing precipitation levels caused by climate change
will be unfavourable for crop growth and yield in many
regions and countries including Nigeria (Yusuf et al,
2008).
It is therefore projected that crop yield in Africa may fall
by 10-20% by 2050 or even up to 50% due to climate
change, particularly because African agriculture is
predominantly rained and hence fundamentally
dependent on the vagaries of weather (Jones and
Thornton, 2003).
Most of the crop production in Nigeria are low-
technology based and are therefore heavily susceptible
to environmental factors and climate change, which are
problems to farmers (Obioha, 2008). Farmers face
challenges of tragic crop failures, reduced agricultural
productivity, increased hunger, malnutrition and
diseases due to adverse effect of climate change
(Zoellick, 2009). These problems hamper agricultural
output and contribution of the agricultural sector to the
Nigeria’s Gross Domestic Product (GDP).
The specific objectives were to:
i. estimate the average maize output, hectarage,
productivity and climatic parameters from (1980-2010).
ii. estimate the trend of climatic parameters
(rainfall and temperature) from 1980 – 2010.
iii. Confirm acceleration, deceleration and
stagnation of the climatic trend variables from 1980 –
2010.
iv. estimate the significant effect of climate change
on maize crop output.
MATERIALS AND METHOD
This study was carried out in Nigeria. Nigeria's latitude
and longitude are 10° 00' N and 8° 00' E. Nigeria is the
most populous black nation in the world and agriculture
is a major activity especially in the rural areas. The data
(1980- 2010) for the study was obtained from
secondary sources. The sources include reports of
National Bureau of Statistics (NBS), FAOSTAT (The
Food and Agriculture Organization Online Agricultural
Database), production yearbook of Central Bank of
Nigeria (CBN), Ministry of Agriculture and Rural
Development (FMARD), several issues and
publications of Central Bank of Nigeria, as well as
Annual Reports and Statement of Accounts. Other
complimentary sources include published and
unpublished materials like proceedings, thesis,
textbooks, bulletin and academic journals. Information
from these sources covers variables of interest,
literature and other findings.
The analytical tools employed include descriptive tools
and Ordinary Least Square regression models.
Objectives I was achieved using descriptive statistics.
For objective 2, the trend was computed by fitting an
exponential function in time to data following the
procedure described by Onyenweaku and Ezeh (1987)
and Onyenweaku and Okoye (2005).
Y = boe
bt
……………………………………… (i)
When linearized in logarithm, equation (i) becomes (Y =
bo + bt )
Where: Y - Rainfall, temperature
t - Time and variables
bo,b1 - Regression
parameters to estimated.
For objective 3, in order to confirm the existence of
acceleration, deceleration or stagnation in rainfall and
temperature variable in Nigeria, quadratic equation in
time variable was fitted to the data as follows:
Log Q = a + bt + Ct2
…………………………..
(ii)
In the above specification, the linear and quadratic time
terms gives the secular path in the dependent variable
(Q). The quadratic time t
2
allows for the possibility of
acceleration, deceleration or stagnation during the
period of the study (Onyenweaku and Okoye, 2005;
Onyenweaku, 1993 and 2004; Sewat, 1981). Significant
positive value of the coefficient of t
2
confirms significant
acceleration; significant negative value of t
2
confirms
significant deceleration while non-significance of the
coefficient of t
2
implies stagnation or absence of either
acceleration or deceleration in the climate variables.
Objective 4 was analyzed by the use of ordinary least
square regression method specified thus;
Q = b
o
+ b1 x1 + b2 x2 + e ……………………… (iii)
Where Q= maize output, x1 = rainfall, x2 = temperature.
The four functional of forms of linear, exponential, semi-
log and Cob Douglas was analyzed and the lead
equation selected based on certain econometric (high
R2
value, F- ratio, number of significant factors) criteria.
RESULTS AND DISCUSSION
Maize output, hectarage, productivity and climatic
parameters.
The average maize output, hectarage productivity and
climatic parameters from 1980-2010 are presented in
Table 1.
The result shows that the average rainfall and
temperature statistics were 1288.311mm and
31.7173o
C in Nigeria. The average maize output within
the period was 4.84mt while hectarage and yield were
3.36mha and 1.44t/ha respectively.
3. Effect of climate change on maize production in Nigeria
J Agric. Econ. Rural Devel. 023
Table 1. Average maize output, hectarage productivity and climatic parameters from 1980-2010
Item Mean STD. DER. Mini Max
Rainfall 1288.311 97.6199 985.31 1468.33
Temperature 31.7173 0.5656 308083 33.2667
Output 4,838,1.09 2128530 612,000 7,525,000
Hectarage 3,3618.10 1461,745 438,000 5,472,000
Yield 1.4419 03275 0.9700 2.2
Source: FAOSTAT and NIMET. (units: output in metric tonnes, rainfall in millimeter, temperature in Degree Centigrades, yield in
metric tonnes ).
Table 2. Estimated functions for production area and productivity of maize in Nigeria, 1980-2010.
Production:
Constant term (a) Coefficient (b) R
2
F
14.2075
(76.50***)
0.0623
(6.14***)
0.5656 37.75***
Area:
14.0979
(66.65***)
0.0475
(4.12***)
0.3687 16.94***
Productivity:
0.1029
(2.01***)
0.0148
(5.01***)
0.4635 25.05***
Figures in parenthesis are t-values, * and *** is significant at 10% and 1% level of probability respectively
Table 3. Estimated function
Constant term (a) Constant term (a) R
2
F
Rainfall 7.0731
(299.55***)
0.0054
(4.15***)
0.3730 17.25***
Temperature 3.4405
(606.70***)
0.0010
(3.22**)
0.2704 10.38***
Figures in parenthesis are t-values, ** and *** is significant at 5% and 1% level of
probabilities respectively.
Trends in maize production and climate variable in
Nigeria 1980-2010.
From Table 2, the coefficients of the trend variable
were all highly significantly at 1% level of probability
indicating that output, area and productivity of maize in
Nigeria increased with time within the period under
review. The means that area cultivated increased as
well as productivity irrespective of the climatic condition
within this period.
Trend in rainfall temperature variables in Nigeria:
1980-2010.
Table 3 shows the estimated log linear function in time
variable for rainfall and temperature within the period
and it showed positive trends. The coefficient of the
trend variables for rainfall was highly significant at 5%
level of probability. This implies that rainfall and
temperature increased with time within the period. The
coefficient in Table 3 also shows the relationships. The
implication is that there was increase in these climatic
variables and this has a possibility of affecting crop
performance.
Confirmation of Acceleration, Deceleration and
stagnation of maize production and climatic
variables in Nigeria: 1980-2010
From Table 4, the coefficients of the b2 for temperature
and rainfall were negatively signed but not significant.
The non-significance of the coefficient of b2 was a
confirmation of stagnation within the period following
Madu and Chinaka 2011. This implies a relative
stagnation of maize output within this period because
there was no significant increase or decrease. This
may be attributed to the variation on climatic conditions.
Confirmation of Acceleration, Deceleration and
stagnation of production, area and productivity of
maize in Nigeria. 1980-2010.
The coefficients of b2 for output and area were
negatively signed and highly significant at 1% level of
4. Effect of climate change on maize production in Nigeria
Obasi and Uwanekwu 024
Table 4. Estimated quadratic function in time variable for rainfall and
temperature in Nigeria. 1980-2010.
Defendants variable Estimated coefficients
bo b1 b2 R
2
F
Rainfall 7.0497
(189.85***)
0.0096
(1.79*)
-0.0013
(-0.82)
0.3877 8.86**
Temperature 3.4389
(380.07***)
0.0013
(0.99)
-0.0000088
(-0.22)
0.2717 5.04*
Figures in parentheses are t-values. *,*,*, and *** is significant at 10%, 5% and 1%
respectively.
Confirmation of Acceleration, Deceleration and stagnation of production, area and
productivity of maize in Nigeria. 1980-2010.
Table 5. Estimated quadratic functions in time variables for output, Area and
productivity of maize in Nigeria.
Defendants variable Estimated coefficients
Production bo b1 b2 R2
F
13.3066
(67.99***)
0.2261
(8.02***)
-0.0051
(-5.99**)
0.8095 59.49***
Area 12.9514
(70.39***)
0.2559
(9.66***)
-0.0065
(-3.11***)
0.8113 60.21***
Productivity 0.3540
(5.71***)
-0.0296
(-3.32**)
0.0014
(5.13***)
0.7236 36.66***
Figures in parentheses are f-values ** and *** is significant at 5% and 1% level of
probability respectively.
Table 6. Regression estimates of the effect of climatic variables
in maize output, hectarage and yield in Nigeria 1980-2010.
Variable Output
(semi-log)
+
Hectarage
(double log
+
)
Yield
(Semi-log
+
)
Constant
-284052574
(-5.42)
-60.1031
(-2.67*)
-27.3099
(-2.83**)
Rainfall 13913496
(4.09***)
3.1299
(2.14*)
1.6133
(2.58*)
Temperature 54769251
(3.53**)
15.2048
(2.28*)
4.9770
(1.75*)
R2
0.5988 0.3332 0.3283
F (20.14***) 6.75** (6.60**)
Figures in parentheses are f-values ** and *** is significant at 5% and
1% level of probability respectively.
probability as shown in Table 5. This implies a
confirmation of deceleration of output and area of
maize within the period, (Chi-Chung et al, (2004). The
coefficient of the b2 for productivity was positively
signed and highly significant at 1% level of probability.
This implies a confirmation of acceleration of yield
within the period under review. This may be related to
better management of the farm to increase output per
area cultivated.
Effect of climatic variables on maize output,
hectarage and yield of maize in Nigeria.
The results from Table 6 show that the semi-log
functional form was chosen as the lead equation
because of a high R2
value of 0.5988 which indicates
59.88% variability in maize output explained by the
climatic variables. The F- ratio was highly significant at
1% indicating a regression of best fit. The coefficients
of rainfall and temperature were positively signed and
significant, this implies that increase in rainfall and
temperature to corresponding increases in maize
output at a deceleration within the period.
For maize hectarage, the Cobb Douglas functional farm
was chosen as the lead equation because of a high R2
value of 0.3332 indicating 33.32% variability in
hectarage of maize explained by the climatic variables.
The result showed that increase in climatic variable led