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Maximum carrying capacity of Malian grasslands

H. BREMAN *

(*) H. Breman, Associate Expert, UNESCO.


1. Introduction
2. Method
3. Results
Conclusion
Bibliography


SUMMARY

The catastrophic loss of cattle in the Sahel during the last few years has accentuated the importance of quantifying the assertion that there are too many cattle there. This study is an attempt to estimate the carrying capacity of the Malian grasslands, taking into account variations in rainfall, on the basis of partial data on their primary productivity.

1. Introduction

The catastrophic loss of cattle as a result of the drought has seriously affected human life in the Sahel. Even more serious are the losses suffered by the most important natural resource for cattle: vegetation. Already, under less severe conditions, the vegetation in countries south of the Sahara is threatened (Boudet, 1972).

Agrostological studies conducted prior to the prodigious mortality in 1973 show a certain degree of over-grazing of the largest stock-breeding regions in Mali, which are Mopti and Gao (I.E.M.V.T., 1972 b, 1971). A specification of the degree of over-grazing is inevitable if measures are to be taken to avert future catastrophes.

This study is therefore an attempt to estimate the carrying capacity of Malian grasslands, taking into account variations in rainfall, on the basis of partial data on their primary productivity. The results obtained seem fairly valid, since it was possible to make a more or less accurate forecast of cattle mortality in 1973 and to specify the regions that would be most seriously affected.

2. Method

As source of data on the primary productivity of grasslands, the four existing agrostological reports were used: i.e., those on Mopti and Gourma (Gag) already referred to, the agrostological survey of the Niono region (I.E.M.V.T. 1970) and the report on the Yanfolila district (I.E.M.V.T., 1972 a). The sites of these studies are shown on Fig. 1. This figure shows clearly that the area studied covers only part of the country. The zones studied cover nearly 140,000 km²; in other words, ± 20 percent of the country, excluding the Sahara.

The reports gave direct information about the various vegetation groups, their primary productivity (= total biomass of the herbaceous stratum at the end of the growth season), the nature of their soils, and most often, their scope; in other words, the areas covered. Where the reports used did not give the necessary specifications, the areas were assessed with the aid of the vegetation maps in reports. Climatological maps on each of the vegetation groups were used to determine the mean annual precipitation.

The reports distinguished between total and palatable primary productivity; and the lowest value was used to assess the stocking rate, based on extrapolations of the productivity of zones studied throughout the country. First of all, we established the variable environmental factors that must be taken into account in making the forecasts.

3. Results

3.1. Ecological factors

The volume of vegetational matter produced over any given period depends on climatic and edaphic factors. It is not possible to express the influence of all the ecological factors without using a data-processing machine, but the most important factors cannot be overlooked.

Rainfall seems to be only climatic factor of great importance, considering the enormous difference of an annual rainfall of 1,550 to 0 mm (Fig. 1) between the south and north of the country. The average and the potential evapotranspiration (PET), between around 1,550 and 1,950 mm annually (Mali 1973). Two edaphic factors should probably be taken into account, i. e. pedology and floods.

Figure 1 - Region of the Republic of Mali with a mean annual precipitation of over 100 mm

3.1.1. Edaphic factors

The extent of edaphic variations is assessed by calculating the average primary productivity of vegetation types in relation to their substratum. The result is shown in Table 1 which illustrates the total and the palatable primary productivity separately.

For the purposes of this study, floods appear to be the important edaphic factor, because of their enormous impact on productivity. It is true that the productivity of species on socle and cuirass is lower than that of other plant groups, but the latter occupy only 7.5 percent of the total surface of the zones studied.

Table 1 - The primary productivity of the herbaceous stratum of the various plant groups in relation to their substratum

Substratum

Primary productivity

Total t/ha/year

Area

Palatable t/ha/year

Area

Socle or cuirass

0.6

7.5 %

0.6

7.5 %

Sandy soil

34.1%

1.3

38.1%


Concretion

1.5

6.8 %

1.6

13.7 %

Alluvium

1.7

10.9 %

1.3

15.9 %

Flood lands

5.2

9.8 %

35

17.6 %

(The productivity is expressed in tons of dry matter: the areas are given as percentage of the zones studied. All the areas do not total 100 percent because of lands without specifications)

3.1.2. Rainfall

The mean annual rainfall is assessed for each vegetation group on the basis of climatic maps. This has made it possible to assess the correlation between average primary productivity per year and the mean precipitation of the different zones of the country, taking into account areas covered by the various vegetation types. The results are shown in Fig. 2.

Figure 2 - The total (--.--) and palatable (-.-) primary productivity expressed as tons of dry matter, in correlation with mean annual rainfall.

The exactness of the curves on Fig. 2 should be tested. Above all, it is the region falling within the 750 to 1,550 mm rainfall belt that should be studied thoroughly. However, there already exists an indication as to the validity of those curves drawn on the basis of extrapolation, in the 1972/73 assessment of the primary productivity of grasslands made by the Sotuba Institut des Recherches Zootechniques in Bamako. Averages of 2.6 and 2.8 tons/ha/year, respectively, were found for the total primary productivity.

According to the curve on Fig. 2, the average primary productivity under an annual precipitation of 1,100 mm, which is the average rainfall in Bamako, is 3.2 t/ha; in other words, higher than what was measured. But it should be noted that rainfall during the last two years was 730 and 870 mm in Bamako. We may thus expect a productivity of around 2.5 and 2.7 t/ha under those rains, according to Fig. 2. Besides, the results are not extremes, as shown in Fig. 3. This figure is a comparison between the total primary productivity of the herbaceous stratum in Mali and Algeria and that of a South African grassland (according to Claudin, 1973).

The origin of the two bends in the Mali curve is unknown, but they show the transition from the Sahel to the Soudanian savannah, and it is possible to picture a more or less sharp increase in the number of perennial graminaceae by the first bend and trees and shrubs in the second. It is not clear if the curve of the palatable primary productivity also has two bends. However, errors would be marginal if one were to use the following formulae in describing the curves:

P = 0.9 R + 720 (100 < R < 400)

P = 2.4 R + 150 (44 < R < 1,500); where P is productivity in kg/ha/year and R is the rainfall in mm/year.

3.2. Variability of rainfall

Special attention should be paid to the flaw in the curves on Fig. 2, which is, incidentally, the weak point of the reports used. It is based on the assessment of only one year's primary productivity. The primary productivity will, however, depend on rainfall, although rainfall is not an invariable factor in Mali: quite the contrary.

Fifteen rainfall stations recorded a variation described by a standard-deviation as being between 12.8 and 28.3 percent of the mean annual rainfall on the site (Mali, 1973). The standard deviation becomes greater as and when precipitation is low (Fig. 4).

Figure 3 - The correlation between the total primary productivity of the herbaceous stratum expressed in tons of dry matter and the mean annual rainfall for 3 African countries.

Figure 4 - The mean annual rainfall in correlation with its standard deviation expressed

The correlations that exist between rainfall and palatable productivity (the two formulae of 3.1.2) and between rainfall and its standard deviation make it possible to estimate productivity, taking into account the variation in rainfall.

Fig. 5 is a graphic representation of the results of these estimations. It shows the primary productivity of palatable species of the herbaceous stratum with a mean annual precipitation and ah average annual rainfall ± 1 and 2 times the standard deviation of that rainfall. The estimates in question are based on the hypothesis that variation of rainfall in a given area will influence the primary productivity of that area in the same way as variation of the mean annual rainfall influences the average primary productivity of the different regions of the country. This hypothesis is not challenged by studies made in the neighbourhood of Bamako (see 3.1.2).

Figure 5 - The primary productivity of palatable species expressed as tons of dry matter under a mean annual rainfall (M) and under mean annual rainfall 1 and 2 times above and below its standard deviation (M ±s and M ± 2 s)

3.3. Carrying capacity

Fig. 5 has made it possible to assess the carrying capacity of Malian grasslands under a mean precipitation and an average rainfall 1 or 2 times below the standard deviation. And what is most interesting for the ecological planning of grasslands, if an attempt to avoid the risk of destroying the grasslands beyond repair during relatively dry years is to be made, is not the primary productivity under average precipitation but productivity under an average rainfall 1 or 2 times less than the standard deviation.

The method used, the hypothesis and estimations made, will be discusssed briefly. The requirements of a UTL (Unit of Tropical Livestock = hypothetical animal weighing 250 kg) are calculated on the basis of 7 kg of dry matter per day of sufficient nutritive value. To maintain one UTL per hectare, the productivity of a rangeland should be 7,500 kg of dry matter on a grassland used throughout the year, since that production is necessary to meet the requirements of the rainy season, while at the same time preserving the production of straw to ensure the preservation of the rangeland and possibilities of regrowth during the dry season. Half of the primary productivity may be consumed in the course of any given season when the grassland is being grazed, during either the rainy season or the dry season.

Three pasture zones must be distinguished. First, we have the zone with more than 1,100 mm mean annual rainfall. It should be noted that the value of the figures estimated for this zone remains only theoretical until such time as epizootics such as trypanosomiasis can be successfully controlled. The exploitation of grasslands with an annual rainfall below 1,100 mm is, to a great extent, assessed in the light of movements of transhumance. Thus the zone with a mean annual rainfall of between 700 and 1,100 mm was taken as a rough approximation and as exclusive grassland during the dry season, whereas the zone with a mean annual rainfall below 700 mm was taken as exclusive rangeland during the rainy season, except for flood zones, which were also considered as dry season grasslands.

The 100 mm isohyet was taken as the northern limit for the study. Each zone was subdivided into bands corresponding to 100 mm rainfall differences. Corrections have been made to the flood zones - which were always dealt with separately - and also to the space used for agriculture. (5.5, 4.5, and 3.5 p. 100 respectively for the 3 zones from the south to the north. The 300 mm isohyet was taken as the limit for agriculture. The same applies to the exception made for the flood zone).

The durations of the rainy season and the dry season are determined on the basis of the curve in Fig. 6, which was drawn in the light of figures contained in the report of Balfour and Sons (Mali,. 1973). It is estimated that the average potential evapotranspiration (PET) is around 5 mm per day (1970 mm/year). The lines linking the points of the same potential evapotranspiration are more or less parallel to the Niger and cross the isohyets perpendicularly, and the number of days of mean rainfall above 5 mm assessed for 15 meteorological stations.

Figure 6 - The correlation between the duration of the rainy season, in days, and the mean annual rainfall.

It is on the basis of the foregoing data that the theoretical maximum carrying capacity of the country was assessed according to belts corresponding to the 100 mm annual rainfall differences during the grazing season on the belts. The results are summed up in Table 2.

It is necessary to explain how the stocking rate for vegetation types on the flood zones was assessed. For an average rainfall, the value shown in Table 1 was used, i.e. a primary productivity of 3.5 t/ha/year. Flood will however be negligible if rainfall during a given year is on the average twice below the standard deviation. The average productivity of the vegetation in question will not be higher in that case than that of other vegetation not on flood zones but with the same amount of rainfall. That is why, in this case, the primary productivity used was what was given in Fig. 5 for the rainfall in question. Part of the flood zones will be flooded by a mean precipitation 1 X below the standard deviation, in which case the average taken is the average for the primary productivity of flood zones and for the primary productivity of the non-flood zones with a mean rainfall 1 X below the standard deviation.

The figures in Table 2 are perhaps not clear at first glance, because they show the maximum stocking rate per rain belt during a given period of the year. The maximum stocking rate of the country as a whole should however be determined on the basis of the period of the year with the lowest stocking rate. The results of the assessments become clearer if, for the 3 groups of grasslands identified, we calculate the total number of " UTL-days " and, subsequently, divide this number by the average number of grazing days in the zones in question (equate " UTL-days " with " hours of work ") as is done in Table 3. This table shows that grasslands during the dry season are the limiting factor for stock breeding. The maximum stocking rate of the most important part of the country for stock breeding has an average 12.6, 106 UTL because of the absence of trypanosomiasis. However, this figure represents too high a stocking rate during years of below-average rainfall, given the hypothesis that herds can use the entire grazing land fully, which is not possible without water sources at various places. This is why it is much better to use 7 to 10,106 UTL as the maximum stocking rate of this zone.

Table 2 - The theoretical maximum stocking rate per belt corresponds to 100 mm rainfall differences during the grazing season on these belts

Rainfall in mm/year

Season

No. of days

Area in 1,000 km2

M

M-s

M-2s

150

RS

30

124.1

204

194

184

250

RS

50

68.8

136

126

117

350

RS

70

53.7

107

97

89

450

RS

86

47.7

99

85

77

550

RS

100

51.5

103

84

71

650

RS

114

56.4

111

86

67

750

DS

240

36.3

58

47

37

850

DS

229

32.0

69

57

45

950

DS

219

30.6

80

66

57

1,050

DS

210

27.3

92

76

61

1,150

TY

365

27.4

39

33

27

1,250

TY

365

23.9

42

36

29

1,350

TY

365

18.5

45

38

31

1,450

TY

365

18.8

49

41

34

1,550

TY

365

1.7

52

43

37

Flood

DS

229

36.3

109

72

42

(We have given the annual average for rainfall and have distinguished the seasons as " rainy season", RS; " dry season ", DS; and TY, " throughout the year ". The sizes of the areas used for agriculture and those of the flood zones have been corrected.)

Table 3 - The theoretical maximum stocking rate of the country per grazing zones

Rainfall in mm/year

Grazing period in days

Maximum stocking rate in 106 UTL per rainfall

No. of UTL-days x 106 per rainfall

M

M-s

M-2s

M

M-s

M-2s

A. Rainy season

150

30

25.30

23.80

22.80

759

714

684

250

50

9.35

8.65

8.05

467

432

402

350

70

5.75

5.20

4.80

492

364

336

450

86

4.70

4.05

3.70

404

348

318

550

100

5.30

4.30

3.65

530

430

365

650

114

6.25

4.85

3.80

713

553

433

Total

450

Maximum stocking rate of grasslands in the rainy season.

3,275

2,841

2,538

Average

75




43.7

37.9

33.8 UTL

B. Dry season

750

240

2.10

1.70

1.35

503

408

324

850

229

2.20

1.80

1.45

504

412

332

950

219

2.45

2.00

1.75

537

438

383

1,050

210

2.50

2.10

1.65

525

442

347

Flood

264

3.24

2.10

0.89

862

554

235

Total

1,162

Maximum stocking rate of grasslands in the dry season.

2,931

2,254

1,621

Average

232




12.6

97

7.0 UTL

C. Throughout the year

1,150

365

1.05

0.90

0.75




1,250

365

1.00

0.85

0.70




1,350

365

0.85

0.70

0.55


x 365


1,450

365

0.90

0.75

0.65




1,550

365

0.10

0.10

0.05




Total

1,825

Maximum stocking rate of grasslands throughout the year.

1,423

1,204

985

Average

365


3.9

3.3

2.7 UTL

TOTAL (Maximum stocking rate of grasslands during the dry season and throughout the year)

16.5

13.0

9.7 UTL

3.4. Present stocking rate

The present stocking rate is not well known because of the mortality of the last few years. This is why the estimated maximum stocking rate has been compared with that of 1969 (Mali 1970). This latter stocking rate has been summed up in Table 4, which gives 6.0.106 UTL (1 cattle= 1 UTL for 60 percent of livestock and 1/2 UTL for the remaining 40 percent; 1 sheep = 1 goat = 1/10 UTL. 1 horse = 1 cameline = 1 UTL) as total stocking rate prior to the 1972 drought.

Again, the 1969 stocking rate is, at first sight, lower by some millions of UTL than the theoretical maximum stocking rate. The total area of grasslands cannot, however, be utilized because of lack of water and it is probable that the acceptable maximum had already been exceeded during the past years for a homogenous distribution of herds over the 6 regions of the country.

3.5. Carrying capacity per region

The distribution of cattle is far from being homogenous, as is shown in Table 4. The biggest concentration is in the 5th and 6th regions. This is why the maximum stocking rate is also assessed per region according to the model given in Table 3. Thus, we took the fifth and sixth regions (Mopti and Gao) as one, in correlation with transhumance; those parts of the first, second, third, and fourth regions with a mean annual rainfall below 1,100 mm; and the parts of these regions with a mean annual rainfall of over 1,100 mm. The maximum stocking rate assessed and the 1969 stocking rate of these three regions of the country are summarized in Table S. This table shows clearly that it is the grasslands of the fifth and sixth regions that are most likely to be destroyed by overgrazing, even under average rainfall. There is no question of ecological planning of the grasslands.

Table 4 - Stocking rate of the grasslands before the 1972 drought in units of 1,000 head

Region

Cattle

Sheep and goats

Asses

Camelines

Horses

Total UTL

Kayes

520

755

89

15

34

584

Bamako

530

600

64

18

40

575

Sikasso

480

330

58

-

1

448

Ségou

620

690

42

19

26

630

Mopti

1,400

2,475

65

44

39

1,483

Gao

1,800

6,400

182

124

40

2,335

Total

5,350

11,250

500

220

180

6,056

UTL

4,280

1,125

250

220

180

6,056

Table 5 - Maximum and effective stocking rate of the grasslands specified, per region

Region

Theoretical maximum stocking rate in 106 UTL with rainfall of

Stocking rate in 1969, in 106 UTL

M

M-s

M-2s

South

3.9

3.3

2.7

0.4

North-West

10.4

8.2

6.2

1.9

North-East

2.8

1.8

0.7

3.7

Here, the entire primary production has been fully used, instead of using to the maximum only half of that production which is necessary for the preservation of resources. Even so, a consumption of the total 1972 primary production could only save 1.4, 106 UTL from death caused by hunger; in other words, it would have been possible to predict a death rate of 2.3, 106 UTL from lack of fodder on the basis of this model. (Rainfall during the year in question was a mean rainfall almost twice below the standard deviation.) In fact, the death rate was perhaps higher than 38 percent of the livestock, because of lack of water. Government sources have estimated that 40 percent of cattle perished during the 1972-1973 season. A solution to the water shortage problem, i.e. the drilling of wells in the fifth and sixth regions, can only be a false solution. The result will be an extension of zones in a state of deterioration - in other words, a thinning out of grasslands and a reduction of the primary production that is the prerequisite for stock breeding.

Conclusion

The conclusion can be brief. Cattle mortality, serious as it may be for the thousands of families affected and also for the country's economy, could be another starting point for stock breeding in Mali on an ecological basis. Efforts should be made to limit the maximum stocking rate of the fifth and sixth regions to 1-2 million UTL. The development of underground water resources of these regions will be justified only if this restriction is imposed. An increase in the number of livestock seems possible in the northwest of the country if the entire grazing land of the area can be used. This is where the development of underground water resources could be very useful. Efforts should, however, be made to avoid a high increase of stocking rate on limited surfaces, if we do not want to be engaged here, as in the northeast, in a war on two fronts against the encroachment of the desert. It should be recalled in this regard that it is not the zone directly south of the Sahara that is threatened by overgrazing, but grazing zones of the dry season; in other words, zones with an annual rainfall of 700 to 1,100 mm. The model given allows for an annual assessment of the stocking rates of grazing lands during the dry season (since they constitute the primary limiting factor for stock breeding - see Table 3), if data on precipitation during the year in question is available. It may also be possible to tell if there is need for clearing certain zones. Thus maximum benefit can be obtained from the enormous resources of the grasslands during the rainy season.

Bibliography

1. BELIME, E.L. - Les travaux du Niger. Paris, Martin-Mamy/Crouan et Roques, 1940.

2. BOUDET, G. - Désertification de l'Afrique tropicale sèche, Adamsonia (ser. 2: 505-524) 12: 1972.

3. CLAUDIN, J. - Etude Phytoécologique du Hodna. Algérie. M.A.R.A./F.A.O., 1973.

4. I.E.M.V.T. - Etude Agrostologique pour la création d'une Station d'embouche dans la région de Niono, no. 29, le Mali, 1970.

5. I.E.M.V.T. - Esquisse Pastorale et Esquisse de Transhumance de la région du Gourma, le Mali, 1971.

6. I.E.M.V.T. - Aménagement du berceau de la race N'Dama dans le cercle de Yanfolila, no. 36, le Mali, 1972.

7. I.E.M.V.T. - Projet de Développement de l'Elevage dans la Région de Mopti, no. 37, le Mali, 1972.

8. Mali. - Annuaire Statistique 1970, Service de la Statistique générale de la Comptabilité Nationale et de la Mécanographie, 1970.

9. Mali. - Rapport sur l'Etude Sectorielle concernant l'Approvisionnement en eau du pays. D. Balfour and Sons, 1973.

10. RATTRAY, J.M. - The Grass Cover of Africa, F.A.O., 1960.


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