**2. Methodology**

*Forest Degradation Around the World*

from 5000 to 65,000 hectares [3].

periods of welding.

community conflicts.

they produce.

real growth rate of the GDP was about 5.4%. On the other hand between 2016 and 2017, the rate of inflation passed from −1.8 to 1.8%, that is to say, a clear increase of 2% [1]. The rate of inflation which results in the impact that the rise in the price of goods has on the purchasing power of the consumers is relatively low. It indicates that apart from the agricultural sector, few economic alternatives are offered to the

Mali Sahelian country knew a long cycle of dryness between 1968 and 1985. For this period, the rains were done rare. It had as consequences the degradation of the grounds, the recurring dryness, a reduction in vegetable cover with a considerable reduction of spaces of grazing ground and a deceleration of the growth of the livestock. During years 1970 and 1980, the Sahelian countries made considerable great strides of the demographic growth which resulted thereafter in an expansion of the cultivated grounds, less grounds put in fallow and the exhaustion of the grounds. During nearly one century, the essence of the marketing policy of the colonizers rested on the cultures of revenue. The imposition of the cultures of revenue by the colonial capacities more contributed to deforestation with as a corollary the degradation of the not very fertile grounds. Thus, 60–93% of the energy needs of the Sahelians come from wood [2]. Between 1990 and 2005, deforestation passed from 84,000 to 144,000 hectares. It results primarily from the human intervention. During this interval of period, the total surface of artificial afforestation passed

The economic activities of the rural populations of Mali are mainly dependent on the agriculture which constitutes their principal source of income. With that the exploitation of the forest resources is added (nonwoody forest products, woodcut, pharmacopeia, etc.) which come to them in complement from incomes for the

With the accentuated effects of the climatic change, these populations are more and more confronted with falls of their mean level of productivity, which impacts negatively on their level of incomes. Consequently, to compensate for the fall of their agricultural incomes and the abuse of the local forest resources, they are increasingly inclined with the expansion of cultivable surfaces with an aim of increasing the agricultural output per hectare. It has as a corollary the excessive firewood cut for the charcoal (domestic consumption and sale on the urban markets), with less afforestation with regard to the local trees. The excessive anthropic pressures on these resources limit their productivities and exacerbate local and

Indeed, in front of these factors impacting the standard of living of these populations, they find as alternative the migration, the rural migration, nonagricultural gold washing and other activities (small trade and seasonal work in the large cities). These various factors thus make it possible to compensate for those which would have positive and significant impacts on deforestation. For this study, except the above-mentioned factors, it is also a question of determining the socio-economic and anthropic effects which impact positively and negatively deforestation. It will make it possible to pose a real not very used econometric diagnosis by the engineering departments which primarily focus on the descriptive analysis of the data that

Considering these various factors, one would be brought to analyse and interpret the bond of dependence between the deforestation and the variation of the economic (macroeconomic indicator determined by the GDP per capita and the poverty line) and demographic (evolution of the size of the population and manpower of the pupils having the level of the second cycle) factors. And a thorough comprehension of the anthropic actions (pasture of the cattle, consumption of the firewood and charcoal, the breeding, the expansion of surfaces of food crops

rural medium in order to easily integrate the nonagricultural market.

**120**

### **2.1 Medium of study and data acquisition**

From its surface, Mali is the 23<sup>e</sup> vastest country in the world. It is located between the 10e and 25e degrees of northern latitude and between the 4<sup>e</sup> degree of east longitude and the 12e degree of western longitude. The climate is at the same time very dry and very heat for the 3/4 of the country, except in the extreme South, being in part of the area of Sikasso. In the Far North, the Sahara, precipitations' ring average is lower than 250 mm and exceeds 100–150 mm with difficulty. On the other hand, in the extreme North, the rains are quasi non-existent. The Sahel sheltering the semi-desert central areas receives on average less than 500 mm of rain per annum. The South is subhumid with average precipitations lower than 750 mm per annum. The lowest value of the average annual temperature is of 28°C and highest is of 32°C3 .

The whole of the data collected for this study is secondary data. They are time series and cover the periods going from 2003 to 2012. The data made up are carried mainly on deforestation and of the macroeconomic and sociodemographic variables. The collected data come from the sources of the National Institute of the Statistics—INSTAT of Mali, the World Bank, the reports/ratios of study and the sites: perspective.usherbrooke.ca and ps://donnees.banquemondiale.org.

#### **2.2 Specification of the model and processing of data**

Two models of regression will be used to analyse the direct and indirect bonds between deforestation and the variables from which it would result. The estimate of the first regression will relate to ordinary least squares (OLS) in order to identify the immediate causes of deforestation. The second stage will be specified with the model logarithmic curve in order to explain the relative variations (in %) of deforestation following the variations (in %) of the macroeconomic and sociodemographic variables. The data processing will be made by the Stata software.

*First stage of the specification of the model*

$$\text{Def} = \beta\_0 + \beta\_1 \,\text{ManLi} + \beta\_2 \,\text{FWC} + \beta\_3 \,\text{SFC} + \beta\_4 \,\text{PFC} + \varepsilon \tag{1}$$

Def: annual decline of forest cover (km<sup>2</sup> ). ManLi: manpower of the livestock (number). FWC: firewood overall consumption (tons).

<sup>3</sup> https://fr.m.wikipedia.org consulted the 14/02/2019 at 15. 32

SFC: surface of food crops (hectare). PFC: production of food crops (tons). β1, 2, 3, 4: coefficients. β0: constant. ε: term of the error. *Second specification of the model*

$$\text{LnDef} = \beta\_0 + \beta\_1 \,\text{LnPop} + \beta\_2 \,\text{LnTEEFII} + \beta\_3 \,\text{LnGDPC} + \text{U} \tag{2}$$

Ln: neperian logarithm. Def: annual decline of forest cover (km<sup>2</sup> ). Population: population of the inhabitants (number). ETPF II: total of the population having the level from Fundamental II (number). GDPC: gross domestic product per capita (\$). β1,2,3,4: coefficients. U: constant.

## **3. Econometric estimate, results and discussions**

#### **3.1 Anthropic actions**

The anthropic actions having impacts on deforestation are caused directly by human activities. Among those we have the pressures exerted by the animals on spaces of grazing ground, the woodcut for multiple uses, the extension of cultivable surfaces for cereals and the production of food crops.

In the model of estimate between the anthropic deforestation and actions, it arises that R2 = 0.8789, which would explain why 87.89% of the causes of deforestation are due to the explanatory variables of the model, that is, to the human activities. There is adequacy of the model. It arises that the model is overall significant since the value of Prob(F-statistic) is associated to be lower than 5%. As a whole, variables ManLi, FWC, SFC and PFC have overall a significant impact on the degradation of forest cover. More specifically, only variables ManLi and FWC have a significant impact on the degradation of forest cover (**Table 1**).

#### *3.1.1 The pasture*

The value of the coefficient associated with the variable ManLi is negative and significant to 10%. It indicates an opposite relation between the deforestation and the number of the cattle. It is obvious that the increase in the livestock in rural medium of Mali is one of the causes of the reduction of the level of deforestation. Therefore, the increase in livestock impacts negatively the degradation of vegetable cover (graminaceous grasses, fodder and Graminaceae). It allows a rapid restoration of the forest cover made up of woody species. It appears thus that it is the overgrazing which leads to the abuse of the forest resources.

Space pastorales in rural medium of Mali are sufficiently available, and their rational use allows the reduction of the deforestation which induces an increase in forest cover. The breeding thus appears as an essential factor which impacts deforestation negatively. The elasticity of reduction of the degradation of the forest surface being of 6.66%, which implies that the increase of 1% of animals constitutes the livestock, would reduce the deforestation by 6.66%. It implies that the increase of the livestock through the production of the organic manure enriching the ground improves the agricultural productivity and contributes to the increase of the forest cover of 6.66%.

**123**

woody species [5].

*Economic Impacts of the Anthropic Effects of the Deforestation on the Rural Populations of Mali*

**Variable Coefficient Std. error t-Statistic Elasticity** C −17802.08 6641.227 −2.680541 −277.5293 ManLi −0.000171 6.67E-05 −2.558930 \* −6.661940 FWC 0.004886 0.001659 2.945847 \*\* 26.29780 SFC 0.000105 0.000185 0.566668 NS 0.255692 PFC −0.000200 0.000217 −0.922393 NS −0.676106

The large stockbreeders in rural medium being mainly wandering have a good perception of the traditional management of the natural resources. Most of the share of the livestock occupies spaces of grazing ground according to the variation of the seasons and the availability of fodder. It allows thus fast reconstitution of the vegetation after one period when space pastorales are almost unexploited [2].

*Note: \*\*\* = significant 1%, \*\* = significant 5%, \* = significant 10%, NS = not significant.*

The firewood overall consumption is positively correlated with deforestation. Its coefficient is positive and has a threshold of significativity of 5%. The firewood consumption by the households is thus one of the principal reasons of the deforestation in rural medium of Mali. That is means that as the consumption of the firewood increases, the decline of forest cover also increases. Thus, the elasticity of the variation of the firewood consumption with regard to the increase in deforestation is 26.30%. Any increase in the firewood consumption of 1% implies an increase

Indeed, that who corroborate with the idea according to which more the share of the countries of Africa Subsaharian use like principal energy wood. Nigeria does not make exception since the increase in its forest decline results mainly from the wood consumption due to a demand in increasing. This request results from an increasing population of need for sources of energy and building machineries for the houses [4]. In the Sahel and in Africa, the local wood energy consumption would be one of the principal causes of deforestation. With that the fall of the pluviometry characterized by dryness is added to the Sahel which decimates the population of the

In Mali, the proportion of the households which use the firewood or coal

environment of Mali, the use of wood thus constitutes the first source of energy. It is thus used as charcoal for cooking and in the manufacture of boxes and is

Consumption, Poverty and Welfare of Households of the National Institute of Statistics—INSTAT of Mali.

<sup>4</sup> Data resulting from the investigation of the periods active from April 2017 to March 2018, into

. Also in rural medium as in urban

*DOI: http://dx.doi.org/10.5772/intechopen.87252*

R-squared 0.878947 Adjusted R-squared 0.757894 Akaike information criterion 12.71521 Schwarz criterion 12.82478 Hannan-Quinn criter. 12.47876 Durbin-Watson stat 1.879230 Prob(F-statistic) 0.040414

*3.1.2 The firewood consumption*

*Anthropic factors determining deforestation.*

**Table 1.**

of 26.30% of the forest degradation.

passed from 77% in 2001 to 77.6% in 2016<sup>4</sup>

**Variable Coefficient Std. error t-Statistic Elasticity** C −17802.08 6641.227 −2.680541 −277.5293 ManLi −0.000171 6.67E-05 −2.558930 \* −6.661940 FWC 0.004886 0.001659 2.945847 \*\* 26.29780 SFC 0.000105 0.000185 0.566668 NS 0.255692 PFC −0.000200 0.000217 −0.922393 NS −0.676106 R-squared 0.878947 Adjusted R-squared 0.757894 Akaike information criterion 12.71521 Schwarz criterion 12.82478 Hannan-Quinn criter. 12.47876 Durbin-Watson stat 1.879230 Prob(F-statistic) 0.040414 *Note: \*\*\* = significant 1%, \*\* = significant 5%, \* = significant 10%, NS = not significant.*

*Economic Impacts of the Anthropic Effects of the Deforestation on the Rural Populations of Mali DOI: http://dx.doi.org/10.5772/intechopen.87252*

#### **Table 1.**

*Forest Degradation Around the World*

β1, 2, 3, 4: coefficients.

Ln: neperian logarithm.

β1,2,3,4: coefficients. U: constant.

**3.1 Anthropic actions**

arises that R2

*3.1.1 The pasture*

β0: constant. ε: term of the error.

SFC: surface of food crops (hectare). PFC: production of food crops (tons).

Def: annual decline of forest cover (km<sup>2</sup>

Population: population of the inhabitants (number).

GDPC: gross domestic product per capita (\$).

**3. Econometric estimate, results and discussions**

surfaces for cereals and the production of food crops.

ing which leads to the abuse of the forest resources.

a significant impact on the degradation of forest cover (**Table 1**).

LnDef = β<sup>0</sup> + β<sup>1</sup> LnPop + β<sup>2</sup> LnTEEFII + β<sup>3</sup> LnGDPC + U (2)

).

ETPF II: total of the population having the level from Fundamental II (number).

The anthropic actions having impacts on deforestation are caused directly by human activities. Among those we have the pressures exerted by the animals on spaces of grazing ground, the woodcut for multiple uses, the extension of cultivable

In the model of estimate between the anthropic deforestation and actions, it

tion are due to the explanatory variables of the model, that is, to the human activities. There is adequacy of the model. It arises that the model is overall significant since the value of Prob(F-statistic) is associated to be lower than 5%. As a whole, variables ManLi, FWC, SFC and PFC have overall a significant impact on the degradation of forest cover. More specifically, only variables ManLi and FWC have

The value of the coefficient associated with the variable ManLi is negative and significant to 10%. It indicates an opposite relation between the deforestation and the number of the cattle. It is obvious that the increase in the livestock in rural medium of Mali is one of the causes of the reduction of the level of deforestation. Therefore, the increase in livestock impacts negatively the degradation of vegetable cover (graminaceous grasses, fodder and Graminaceae). It allows a rapid restoration of the forest cover made up of woody species. It appears thus that it is the overgraz-

Space pastorales in rural medium of Mali are sufficiently available, and their rational use allows the reduction of the deforestation which induces an increase in forest cover. The breeding thus appears as an essential factor which impacts deforestation negatively. The elasticity of reduction of the degradation of the forest surface being of 6.66%, which implies that the increase of 1% of animals constitutes the livestock, would reduce the deforestation by 6.66%. It implies that the increase of the livestock through the production of the organic manure enriching the ground improves the agricultural productivity and contributes to the increase of the forest cover of 6.66%.

= 0.8789, which would explain why 87.89% of the causes of deforesta-

*Second specification of the model*

**122**

*Anthropic factors determining deforestation.*

The large stockbreeders in rural medium being mainly wandering have a good perception of the traditional management of the natural resources. Most of the share of the livestock occupies spaces of grazing ground according to the variation of the seasons and the availability of fodder. It allows thus fast reconstitution of the vegetation after one period when space pastorales are almost unexploited [2].

#### *3.1.2 The firewood consumption*

The firewood overall consumption is positively correlated with deforestation. Its coefficient is positive and has a threshold of significativity of 5%. The firewood consumption by the households is thus one of the principal reasons of the deforestation in rural medium of Mali. That is means that as the consumption of the firewood increases, the decline of forest cover also increases. Thus, the elasticity of the variation of the firewood consumption with regard to the increase in deforestation is 26.30%. Any increase in the firewood consumption of 1% implies an increase of 26.30% of the forest degradation.

Indeed, that who corroborate with the idea according to which more the share of the countries of Africa Subsaharian use like principal energy wood. Nigeria does not make exception since the increase in its forest decline results mainly from the wood consumption due to a demand in increasing. This request results from an increasing population of need for sources of energy and building machineries for the houses [4]. In the Sahel and in Africa, the local wood energy consumption would be one of the principal causes of deforestation. With that the fall of the pluviometry characterized by dryness is added to the Sahel which decimates the population of the woody species [5].

In Mali, the proportion of the households which use the firewood or coal passed from 77% in 2001 to 77.6% in 2016<sup>4</sup> . Also in rural medium as in urban environment of Mali, the use of wood thus constitutes the first source of energy. It is thus used as charcoal for cooking and in the manufacture of boxes and is

<sup>4</sup> Data resulting from the investigation of the periods active from April 2017 to March 2018, into Consumption, Poverty and Welfare of Households of the National Institute of Statistics—INSTAT of Mali.

used to cover the roofs of the concessions. In rural and urban medium, there are many electric posts which are made containing wood. The mortars, the rammers, the hoe, cart, etc. are also designed containing wood. That who confers on wood multiples uses.
