Yam Production Practices And Climate Change In Cross Rivers State, Nigeria

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 Dr. Ikechi Agbugba | Contributor on Agribusiness Topics

Dr. AgIkechi Agbugba  And Elijah, S. T., Department of Agricultural & Applied Economics, Rivers State University, Port Harcourt, Nigeria, Department of Agricultural Economics, University of Nigeria, Nsukka, Nigeria.

Abstract

There is a unidirectional relationship existing between agricultural productivity, climate change as well as food security in developed and developing economies of the world. Developing countries like Nigeria often depend on rainwater for the production of yam, among other crops.

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However, unpredictable changes in the onset of rains in the last 10 years have led to situations where yam planted with the arrival of early rains get smothered in the soil by an unexpected dry spell; resulting in harvest failures in Nigeria and other ecosystems that rely on rain-fed agriculture.

Specifically, the study determined the effect of the socio-economic characteristics on yam production in Cross River S, Nigeria; and further identified the activities of the farmers that exacerbate the effect of climate change in the study area.

The study employed a survey design. A multi-stage sampling technique was adopted to select 150 respondents for the study. The yam output was proxied by farmers’ income and was regressed against the independent variables. Ordinary Least Square analysis, Likert rating scale and descriptive statistics were employed to achieve the objectives. The results show that the socio-economic effect on yam production is statistically significant at P of 0.05.

The prevalent farm practices in the area according to the order of intensity were; burning of firewood – 16%, burning of crop residues and household waste as well as burning of fossil fuel by automobile – 11%, deforestation and the use of fertilizer – 10%, bush burning, use of herbicide/insecticide and burning of fossil fuel by industries – 9%, continuous cropping – 8% and use of insecticide/pesticide – 7%.

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It was recommended that policies should be put in place to regulate anthropogenic practices that foster climate change and variability. The government is advised to deploy more extension agents who are knowledgeable on climate change issues as this will result in minimization of the losses incurred to climate change.

Keywords: Yam, production, productivity, farmers, climate, climate change, Nigeria. 

Introduction

Climate change is a subject that has attracted considerable attention in recent years due to its deleterious effects on ecosystem (National Academy of Sciences, 2009). Until recently, the effects of man’s activities on climate variations were perceived as negligible and so climate change was generally taken for granted (Iheke & Oliver-Abali, 2011).

However, it is palpably established that climate change is no longer a trivial issue; it is a reality that is seriously affecting the earth already, especially challenging agricultural productivity and food security in both developed and developing economies of the world and thus requires urgent attention.

Although, the impacts of climate change on agricultural productivity may be positive or negative; however, empirical studies show that the latter outweighs the former (Enete, Madu, Mojekwu, Onyekuru, Onwubuya & Eze, 2011; Nzeh & Eboh, 2011).

In the view of the International Panel on Climate Change (IPCC, 2007), climate change is a change in the state of the climate that can be identified (e.g. using statistical tests) by changes in the mean and/or the variability of its properties and that persist for an extended period typically decades or longer. On the other hand, the United Nations Framework Convention on Climate Change

(UNFCCC, 1992) views climate change as a change of climate (air temperature, windfall, wind speed), which is attributable directly or indirectly to human activity that alters the composition of the global atmosphere, and which is in addition to natural climate variability observed over a comparative time periods.

Climate change may be due to natural internal processes or external forces such as persistent anthropogenic changes in the composition of the atmosphere or in land use. In recent times, various countries have been threatened by changes in climatic conditions ranging from draught, delayed rainfall, continuous melting of the polar region causing severe flood in some countries and speculation about the acid rain (Food, Agriculture and Natural Resources Policy Analysis Network [FANRPAN], 2010). 

In Africa as a whole and Nigeria in particular, the pattern of rainfall has already been altered, thereby affecting the commencement of the planting season and resulting in poor harvest yields. Although IPCC projections suggest that rainfall in southern Nigeria will increase (IPCC, 2001), the simultaneous increase in temperature may increase evaporation and potential evapo-transpiration, leading to a tendency towards droughts.

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Indeed, recent studies indicate a 10-25% decrease in precipitation in southern Nigeria since the beginning of the century. If this trend persists, rainfall in the humid regions of southern Nigeria may be about 50% to 80% of the 1900 values by 2100 (Adejuwon, 2004). Such periods of drought will have a drastic impact upon agricultural output in the region, particularly if there is no forest remaining to act as a buffer during times of food crisis.

Yam production in Nigeria seems to be the most vulnerable by the deleterious effects of climate change (Oluwasusi and Tijani, 2013). Yam is an annual tuber and monocot plant. It belongs to the genus “Dioscorea” and the family “Dioscoreacea”. The food plant comprises of 600 species out of which ten species produces edible tubers and only six are cultivated in Africa (Musa, Onu, Vosanka & Anonguku, 2011).

As a root crop, the place of yam in the diet of the people in West Africa and in Nigeria in particular cannot be overemphasized. Babaleye (2003) observes that yam contributes more than 200 dietary calories per capita daily for more than 150 million people in West Africa while serving as an important source of income to the people. 

In Nigeria, yam is becoming more expensive and relatively unaffordable in urban areas as production growth has not kept pace with population growth leading to demand exceeding supply (Kushwaha & Polycarp, 2000). Yam production in Nigeria is entirely dominated by smallscale farmers (Baimey, 2006).

Furthermore, the production of this crop like every other crop is affected by factors varying from physical, economic to cultural. Climate, one of the physical factors, is the most crucial factor, which determines the nature of the natural vegetation, the characteristics of the soils, the crops that can be grown, and the type of farming that can be practiced in any region (Obiokoro, 2005).

The most important climatic elements for crop growth and yield are radiant energy, or solar radiation, temperature and water or rainfall (Ekaputa, 2004). Solar radiation in turn determines the thermal characteristics of the environment, namely net radiation, day-length or photoperiod, the air and soil temperatures

(Danjuma, 2004). Soil and air temperatures affect the developmental stages more than any other factor (Ayoade, 2004). 

Climate change can seriously affect agricultural production. Climate change brings about changes in weather patterns which in turn give rise to imbalances in seasonal cycles, harm to ecosystems and water supply affecting agriculture and food production, causing sea levels to rise.

Extreme weather events such as floods, landslides and drought are caused by climate change. Climate change, including global warming and increased climate variability result in a variety of impacts on agriculture (Ejiogu & Ejiogu, 2010). Nzeh and Eboh (2011) noted that unpredictable changes in the onset of rains in the last 10 years have led to situations where crops planted with the arrival of early rains get smothered in the soil by an unexpected dry spell that can follow early planting.

The crop smothering, and the late arrival of rains due to climate variability, results in harvest failures in ecosystems that rely on rain-fed agriculture. Climate change impacts the four key dimensions of food security – availability, stability, access, and utilization.

Availability of agricultural products is affected by climate change directly through its impacts on crop yields, crop pests and diseases, and soil fertility and water-holding properties. It is also affected by climate change indirectly through its impacts on economic growth, income i. distribution, and agricultural demand. In addition, stability of crop yields and food supplies is negatively affected by variable ii. weather conditions (Edame, Anam, Fonta & Duru, 2011). 

There have been numerous studies of climate change, the bulk of these were conducted in temperate and highly industrialized countries (Mendelsohn, 2000). Most of the empirical work to date on the effect of climate change on crop production has focused on Europe, the United States, Canada and Australia (Molua & Lambi, 2007).

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Worldwide little research has focused on developing regions such as those in the tropical rainforest where the poor who may be most vulnerable to adverse changes live. Scientists fear that the most adverse effects are likely to occur in this region (Molua & Lambi, 2007).       

Some of the studies in developing regions (Deressa et al., 2008a; 2008b; Akpalu, Hassan and Ringler, 2008) considered the effects of one or two aspects of climate change on maize and other crops. 

None within the knowledge of the researcher has focused on yam production in the agro-ecological zones of many developing countries especially that of the rainforest zone of Nigeria where the most vulnerable group live; hence, the necessity for this study. 

Purpose of the Study

The broad objective of the study is to examine yam production practices and climate change in Cross River State, Nigeria. 

Specifically, the purpose of the study is to: determine the effect of socio-economic characteristics on yam production in the

study area; identify yam farmers’ activities that exacerbate the effect on climate change in the study area. 

Materials And Methods

This study was carried out in Cross River State.  Cross River State, lies between latitudes 5032′ and 4027′ North and longitudes 7050′ and 9028′ East, bounded in the North by Benue State, in the Southwest by Akwa Ibom State, in the West by Ebonyi and Abia States.

The State shares an internal frontier to the East with the United Republic of Cameroon, and its Atlantic coastline is to the south, where the Calabar River meets the sea (Cross River State Government of Nigeria [CRSG], 2004). Cross River State has a land area of about 21,787 km2 and a population of about 2,892,988 people (NPC, 2006).

It has the largest rainforest covering about 7,290 square kilometers described as one of Africa’s largest remaining virgin forest harbouring as many as five million species of animals, insects and plants (MOFINEWS, 2004).

The climate of the area is controlled by two tropical air masses namely the equatorial maritime (MT) air mass, which originates from the South-West and the tropical continent (CT) air mass, which originates from North East (Alobi, 1992), with average temperatures ranging between 15°C – 30°C, and the annual rainfall between 1300 – 3000mm.

The high plateau of Obudu experience climatic conditions which are markedly different from the generalized dry and wet period in the rest of Cross River State. Temperatures are 4°C – 10°C lower due to high altitude than in the surrounding areas. Similarly, the annual rainfall figures are higher than in areas around them, particularly on the windward side (CRSG, 2011). 

Multi-stage sampling technique was used to select the respondents. This procedure considered the delineation of the study area into zones. The Cross River Agricultural Development Project

(CRADP) divided these agricultural zones into Ogoja Zone, Ikom Zone and Calabar Zone of the state (Adinya, Ibom, Ayuk, Agiopu, Umoh & Umeh, 2008). Each of the agricultural zones comprises six (6) Local Government Areas.

At the first stage one (1) Local Government Area was selected randomly from each of the zones. Five (5) farming communities was randomly selected from each of the Local Government Areas (making a total of fifteen (15) farming communities). Ten (10) respondents (farming households) was finally selected from each of the farming communities making a total of 150 farmers (respondents). 

Primary data was used for the analysis. The primary data were collected with the aid of detailed and well-structured questionnaire administered to the selected yam crop farmers and was complemented by scheduled interview. The questionnaire was designed to capture information on socio-economic data like age, gender, household size, size of land holding, etc.

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In this study, Objective (i) was realized using Ordinary Least Squares (OLS) analysis, while objective (ii) employed Likert rating scale as well as descriptive statistics such as: means, graphs, percentages, frequencies, tables, bar charts and pie charts. 

Regression Model

Multiple Regression model is specified, explicitly as follows:  

 Y= b0+X1+X2+X3+X4 + X5 + X6 + X7……..X14 + e

                                                   (1)

Where 𝑌𝑖 = yam yield (income) bo = Intercept

            X1 = sex (male =1, 0 otherwise) X2 = years of education

X3 = experience in yam production

(years)

X4 = belonging to an association

X5 = household size (number of persons)

X6 = age (years)  X7 = losses from diseases due to climate change (₦)

 X8 = excess preservation cost due to excessive rainfall/sunlight (₦)

            X9           =          excess            cost     on        disease

prevention

 X10 = market access (yes =1, 0 otherwise)

            X11 = cost of additional supply of yam

            X12 = hired labour (man days)

X13 = quantity of fertilizer used (kg) 

X14 = quantity of pesticide applied

(ltrs)  ei   =  stochastic or error term 

Results And Discussion

Effect of Socio-Economic Characteristics on Yam Production 

The multiple regression was used to examine the effect of socio-economic characteristics on yam production, which is the first objective of this study. The study used the proceeds (income) from yam to proxy yam production at the end of a season, while it employs the core socio-economic variables are loss from disease due to climate change, quantity of fertilizer used, quantity of pesticides, excess cost on disease prevention, excess cost of additional supply of yam and cost of excess rainfall. The results are presented on Table 1.0.

Table 1.0: Results of the Soio-Economic Effect on Yam Production

            Table 1.0:Variable(s) OLS Results of the Effect of Climate Change on Yam   Coefficient             Standard    Incomet- p- Error           test      value

            Gender           17705.91       10954.99       1.62    0.109

             Years in school        3400.593       2221.65          1.53    0.128

            Experience    3614.757       1182.997        3.06    0.003

            Losses (disease) due to      -1.30626        1.209275       –           0.282

             climate change        1.08

            Market access          26465.73       12420.81       2.13    0.035

             Household size        13603.63       2938.993       4.63    0.000

             Belong to association         2023.423       7297.488       0.28    0.782

Hired labour (number of      106.4758       58.35159       1.82    0.070 days)

 Quantity of Fertilizer           298.423          79.78255       3.74    0.000 used

 Quantity of pesticide           3485.5            2426.643       1.44    0.153 used

Source

Excess cost on disease : Computed from Field Survey Data, 0.7826564     0.54415722013                     1.44    0.1153  prevention

The results above show proof of a highly Cost of additional -0.5182472 variab1.144351le  – income is explained by the – 0.642 significant estimation as the general supply of yam stated independent variables in the 0.45

            Cost of excess rainfall -0.3994985            0.8576652     –           0.642

significance testing indices, Prob of F is model. To further ascertain the predicting 0.47 not only less than 0.05 but is 0.0000. Also Constant -5422.12 strength of the independent variables in 19387.6 – 0.006 the results show that R-squared is 0.8918 the model, Figure 1.0 is used for the 2.81 that implies that 89.18% of the dependent R-squared 0.8918 illustration.    

            Prob of F        0.0000                                     

            0          200000           400000           600000           80000

Fitted values

Figure 1.0: Predicting Power of the Explanatory Variables of Income

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Figure 1.0 shows a strong predicting strength of the explanatory variables in the model as the scatter-diagram portrays a 45-degree pattern as expected. This therefore shows that the explanatory variables strongly determine the independent variable and therefore the omitted variables are not very significant in determining income. With this background therefore the study concentrates on the five independent variables that should reflect the socioeconomic variables.

On the general scope the results showed that farmer’s experience, market access, house hold size and the quantity of fertilizer used are significant and positive determinants of Income which is however, the expected a priori.

They are said to be significant due to the fact that their p-values are all less than 0.05 and their t-values greater than the absolute value of 2, to this respect, house hold size is the most determinant factor as its pvalue is zero.

While gender, years in school, association participation, hire labour practice, use of pesticides and excess cost on disease prevention are all positively related with income but not significant in determining income as their t-value all lie below the absolute value of 2 and the probabilities (p-value) are all greater than 0.05.

These results are also not very strange, given that if household size is significant in determining farmer’s income, we expect that the farmers should not bother hiring much labour since they make use of household labour. Also losses from disease due to climate change, cost of additional supply of yam and the cost of excess rainfall are all negatively insignificantly related with yam yield.

However, concentrating on the six socioeconomic variables that predict productivity of yam, we commence with the losses from disease due to climate change. A unit increase in the loss from the disease decreases the farmer’s income by 1.30626, thereby portraying a negative relationship with farmer’s income. More importantly we find that the losses are not really significant in determining farmer’s income.

This shows that even though yam productivity resulted from some losses due to diseases induced by climate change, it is not yet significant in affecting farmer’s income negatively. Therefore, there is need for the government and other non-governmental organisations to control the spread of these diseases now that it’s not yet significant before it starts affecting farmer’s income severely. 

The quantity of fertiliser used is highly significant in determining income, and the fact that it is positively related is more enlightening as it contributes to the growth of the farmer’s income. A unit increase in fertiliser used increases farmer’s income by 298.423. This therefore means that even with the advent of climate change the use of fertiliser improves farmer’s income which is rather encouraging.

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This is a call for policy makers to make fertiliser available for farmers to use as a boast to yam production and proceed in Cross River state of Nigeria.

Considering the quantity of pesticides used the results show that it equally not significant in determining farmer’s income. A unit increase in the quantity of pesticides used increases the farmer’s income by 3485.5 which is expected as the pesticides prevent the Yam from harm and therefore permits it to grow and be ready for the market.

However it is not significant in determining the farmer’s income as the tvalue is less than the magnitude of 2 (that is 1.4).

Excess cost of disease prevention appears not to be significant as well, given the ttest that is 1.44 which is good for the farmers as this does not significantly affects yam yield, however this must not go out of hand even though the current situation is mild since a unit increase in the cost of disease prevention increases income by 0.7826564. Also excess cost of additional supply of yam and cost of excess rainfall are relatively insignificant in determining farmer’s yam yield with tvalues that are as low as 0.45 and 0.47 respectively.

They both have a negative and inverse relationship with farmer’s yam income that connote that an increase in any of these expenditures decrease the amount of income. Fortunately the results do not show that this effect is significant, but just as discussed with the other independent variables there is need to be on the watch out. 

To conclude our result of objective one we state that, on the six count charge – six core independent variables just one of them is significant in determining the effect on yam yield and five are not.

It therefore means that even though the effect of climate change has been significant in the production of many other crops in different areas, it is not yet significant in the production of yam yield in Cross River state of Nigeria.

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Effect             of        Framer’s       Activities      the form of frequencies, percentages, bar Exacerbating Climate Change  charts and pie charts. These analyses are To capture objective two this study illustrated below; suggests the use of descriptive statistics in   Table 2.0: Results of Farmers’ Activities Using Descriptive Statistics Variable(s)   Very  Great     Some  Little  No extent       great extent   extent  extent    (%) extent  (%)  (%)  (%)      (%) Bush burning                45               48       28        12        7                           (34.29)             (20.0) (8.57)  (5.0)               (32.14) Continuous       61               33       23        13      10                  cropping      (43.57)             (23.57)           (16.43)           (9.29) (7.14) Burning waste              22               50       21        40       7                     (15.71)             (35.71)           (15.0) (28.57)            (5.0) Burning          of             48   35       37           20       0                   fossil           fuel       (34.29)         (25.0) (26.43)             (14.29)           (0.0)       (industries) Use of fertiliser            74    3         9         18      36                    (52.86)      (2.14)             (6.43) (12.86)           (25.71) Use   of             96   14       11         11        8                   insecticides               (68.57)         (10.0) (7.86) (7.86)  (5.71) Burning        of             34          19       29        54       4                   fossil           fuel       (24.29)         (13.57)             (20.71)           (38.57)           (2.86) (automobile) Deforestation      16   35    72    17    0                     (11.43) (25.0) (51.43) (12.14)  (0.0) Burning of fire       1   11     9    72   47                  wood    (0.71) (7.86) (6.43) (51.43) (33.57) Use of       87    1    9    15   28                  herbicide   (62.14) (0.71) (6.43) (10.71) (20.0) Figures in parenthesis are percentages Source: Field Survey, 2013 The cross tabulation above indicates that practice of bush burning and its of the 140 respondents or farmers that devastating consequences on the were interviewed 45 of them making a environment. Farmers that practiced

total of 32.14% said the used bush burning to a very great extent and 34.29% accepted the practiced bush burning and only 5% of them did not practice bush burning at all.

Fig 2.0: Farmers’ activities that exacerbate climate change issues with respect to their To have a clearer picture of the intensities little extent. Based on this therefore the of climate change the study illustrates the figure above illustrates that the most

This is rather high and calls for policy implementers to sensitize farmers on the continuous cropping to a very great extent amounted to about 43.57% which is expected however as most of them depend solely on farming and do not have enough land to practice crop rotation. Only 7.14% of the farmers did not practice continuous cropping, meaning up to 92.86% of them practiced continuous cropping at least to some extent.

About 95% of the farmers practiced waste burning as against 5% that did not, and out of the 95%, 15.71% of them practiced it to a very great extent, 35.71% to a great extent, 15% to some extent and 28.57% to a little extent. Therefore, suggesting a huge per cent of the farmer’s that practice waste burning rather than more “clean” methods of wage disposal. Most of the farmers are fully involve in these activities that worsen climate change.

The situation becomes even worse with activities such as burning of fossil fuel and deforestation as all the farmers testify to the presence of such activities that exacerbate the climate change incidences. However we note that the use of herbicides, use of fertilisers and the burning of firewood is not practiced by 20%, 25% and 33.57% respectively of the farmers.

While the most practiced to a very great extent is the use of insecticides that amount to about 68.57%. composite index of the intensities using bar charts. The composite index was gotten by summing up all the responses of the responses on farmer’s activities by assigning 5 to a very great extent, 4 to a intensively used is the practice of firewood burning with about 526 followed by the burning of fossil fuel by vehicles and then the burning of waste.

While the least intensively practiced are great extent, 3 to some extent and 2 to a the continuous cropping and the use of herbicides with a composite index of 288. 

            bushburn       contcrop         burncrop        burnfoss         usefert

            useinpert        burnfossveh  deforindis       burnfirewood useherbs

8%

9% 9%

16%

11%

            10%    9%

            11%    10%

7%

Fig 3.0: Pie chart of the Percentages Distribution of Farmer’s Activities 

This could be further buttressed with a pie chart showing the intensities of the farmer’s activities in percentages. The pie chart above suggest that based on the 10 farmer’s activities that worsen the effect of climate change considered in the study, the greatest contributor is the burning of firewood 16%, 11% for the burning of crop and household waste as well as the burning of fossil fuel by automobile.

Followed by deforestation and the use of fertiliser, burning of fossil fuel by industries and the least contributor is that of continuous cropping with only 8%. However, their contributions are more or less similar having only small margins among them. 

Conclusion 

The findings illustrate that the socioeconomic variables has no significant effect on the production of yam, among other production of root crops grown in the study area. However, the study does not suggest that the socio-economic variables with reference to climate change and variability has no effect on root crops generally, as the bulk of empirical review posits that the variables has critical effect on crop production.

Little research in the subject of climate change and its impact on agricultural productivity has been done in the area of study. Consequently, the rural farmers are to a large extent ignorant of the anticipated deleterious impact. It therefore calls for policy makers in the country to focus their research interests on the subject matter of climate change and its associated issues towards the study area.

Recommendations

Based on the findings of the study, the following recommendations and policy implications are advocated as alternatives to curb the deleterious effect influence between yam productivity and climate change in the study area, as well as the country at large. More should be invested in research on more efficient measures to combat the nascent turbulence peculiar with climate variability and change in the study area and the entire planet.

Although, the findings of the study established that the effect of socioeconomic variables with respect to climate change is insignificant on yam production; hence, there is need to be on the watch to avoid its untold devastating impediment on the agrarian economy.

In essence, policies should be put in place to regulate anthropogenic practices that foster climate change and its variability. Moreover, one of the predominant challenges in the study area is lack of access to extension services, to redress this, the government should deploy more extension agents to the area of study. 

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