Livestock Research for Rural Development 16 (11) 2004

Citation of this paper

Is it worth to recuperate degraded pasturelands?
An evaluation of profits and costs from the perspective of livestock producers and extension agents in Honduras

F Holmann, P Argel*, L Rivas**, D White***, R D Estrada**** C Burgos*****, E Perez******, G Ramirez******* and A Medina********

Centro International de Agriculture Tropical (CIAT), and International Research Institute in Livestock (ILRI). Cali, Colombia: F.Holmann@cgiar.org
*CIAT. San José, Costa Rica P.Argel@cgiar.org
**CIAT. Cali, Colombia:  L.Rivas@cgiar.org
***CIAT. Cali, Colombia: D.White@cgiar.org
****CIP-CIAT. Cali, Colombia: R.Estrada@cgiar.org
*****Dirección de Ciencia y Tecnología Agropecuaria (DICTA). Tegucigalpa, Honduras: Conrado_Burgos@msn.com
******ILRI. Managua, Nicaragua:  Edwin.ilri@cablenet.com.ni
*******CIAT. Cali, Colombia: G.Ramirez@cgiar.org
********CIAT. Cali, Colombia:  A.Medina@cgiar.org


Abstract

The objectives of this study were to: (a) estimate milk and beef yields obtained from cows grazing pastures in different stages of degradation; (b) estimate income losses as a result of the degradation process; (c) estimate the proportion of pasture areas found in each stage of degradation within the six administrative regions of Honduras; and (d) identify different strategies and costs to recuperate degraded pastures. Data came from two surveys executed during a workshop carried out in March 2004. The subjective perceptions of 25 livestock producers and 8 extension agents of the 6 administrative regions of Honduras were obtained to estimate the losses of animal productivity within the farm, region, and country. A 4-level scoring of pasture degradation was defined - where 1 was for the best condition (i.e., non-apparent degradation) and 4 was for the worst (i.e., severe degradation). Regressions, explaining the animal productivity losses at each level of pasture degradation, were generated according to the subjective and descriptive information.

Comparing the perception of degraded areas, producers considered that in Honduras the extent of pasture degradation is lower compared with extension agents. According to producers, 29% of the pasture area in the country is at Level 1 (i.e., no degradation) compared with only 19% of extension agents. Moreover, producers perceived a lower proportion of pastures in severe degradation (i.e., Level 4, 27%) in comparison with almost 31% perceived by extension agents. In the intermediate degradation levels (i.e., Levels 2 and 3), both groups were similar.

The country is forgoing milk and beef production due to the process of pasture degradation. According to estimations from producers, Honduras is loosing 284,106 tonnes of fluid milk and 48,271 tonnes of beef (live weight) annually for having pasture areas in Level 4 (i.e., severe degradation), equivalent to 48% of the annual production of milk and to 37% of beef. In economic terms, these losses in milk and beef yields are worth US$63 and US$48 million annually, respectively. The perception of extension agents is even more alarming. Honduras could produce 66% more milk and 50% more beef annually if livestock producers renovated their pastures before they reached level 4, equivalent to US$94 million in less revenues from milk sales and US$66 million from less beef sales.

Both groups perceive that pastures, in an early stage of degradation (i.e., Level 2), are more economical, practical and rapid to recuperate. Also, as the process of degradation advances (i.e., to Levels 3 and 4), both cost and time of recuperating such pastures increase significantly. According to producers, the recuperation of a pasture from Level 4 to Level 1 costs $140/ha and takes almost a half year (i.e., 5.6 months). Extension agents estimate this cost of recuperation 27% higher ($178/ha) with 5% more time (i.e., 5.9 months).

Producers perceive that grasses spend proportionately less time in going from Level 1 to 2 (i.e., 2.9 years) and as the process of degradation continues, pastures remain longer at advanced degraded levels (i.e., 3.1 years in going from level 2 to 3, and around 4.0 years in going from level 3 to 4). Moreover, producers think that the average productive life of improved grasses is about 10 years, while extension agents think that grasses degrade faster, with an average productive life of 8.4 years, 16% less than producers.

According to producers and extension agents, pastures degrade at an annual rate of 10% and 12%, respectively. With these rates, Honduras would maintain its current level of degradation between levels 2.48 and 2.65. However, the renovation of pastures at an annual rate of 10-12% does not solve the problem, but maintains it. Producers argued that the current financial situation does not allow the necessary cash flow to renovate their plots, and the option of credit is not viable since real interest rates are high (ie., 10%). After simulating this scenario, it was demonstrated that farmers are able to generate the additional income necessary to pay a credit, but only if this credit is taken with interest rates similar to those found in the international market (ie., 3%).

In order to eliminate the degraded areas found in Level 4 at the country level, it is necessary a one-time investment of $57 million according to producers and $84 million according to extension agents. The benefit obtained from this investment would result in a daily increase of 156,000 liters of milk and 26,500 kilograms of beef, equivalent to $22 millions/yr. Therefore, there are significant economic and productive incentives for the private and public sectors to develop and execute a plan of action to recuperate pasturelands in advanced stages of degradation.

Key words: Cost benefit, degraded pstures, extension agents, producers


Introduction

The progressive displacement of cattle raising toward marginal areas of lower productive capacity is a generalized phenomenon in Tropical Latin America. The low availability of adapted forage materials of high productivity together with the inadequate management of pastures has led to a fast decrease of productivity and low revenues to livestock farmers. This circumstance has been documented in Brazil, where cattle raising moved from the south states to the Midwest (Serrão and Toledo 1989), in Colombia from the Northern Coast and the Inter-andean Valleys to the Orinoco and Amazon region (Vera and Rivas 1997), and in Central America from the fertile Pacific region to the Atlantic (Kaimowitz 1995).

In selected livestock watersheds in Central America, it was estimated that between 50% and 80% of pasture areas are in advanced stages of degradation with a stocking rate lower than 40% with regard to pastures receiving an appropriate management (CATIE 2002). Biophysical analyses show that improved grasses usually degrade after 5-7 years. In Central America, the annual rate of pasture renovation is estimated at 5% while the degradation rate is 12%, this explains the progressive increase of degraded areas in Central America (CATIE 2002).

The degradation process

Degradation is usually defined as the temporary or permanent decrease of the soil productive capacity in a given agricultural ecosystem (Stocking and Murnaghan 2001). Latin America is the region of the developing world having the largest degraded areas (Oldeman 1992). In the case of pastures, the process of degradation is linked to: (1) the establishment of pastures in fragile soils (i.e., slopes); (2) sowing of poorly adapted species; (3) overgrazing during the rainy season; (4) uncontrolled and frequent burning of pastures; and (5) nutrient depletion (Spain and Gualdrón 1991). The degradation of pastures brings serious consequences to the producer: first, it reduces milk and beef yields and second, it increases production costs.

Once the improved pasture is established, nitrogen deficiency is the first factor destabilizing the pasture, inducing the beginning of the degradation process. After nitrogen deficiency takes place, the quality and the vigor of the pasture begin to decline and an acute reduction of the biological activity is induced; then, other nutrients, such as phosphorus and sulfur, can appear as deficient. When the pasture begins to lose vigor, the invasion of weeds appears, increasing the problem even more (Spain and Gualdrón 1991).

After a prolonged period of grazing, it may be possible that important changes in the physical structure of the soil appear, such as compaction, which increases water runoff, diminishes root development, and the extraction of nutrients deeper in the soil. In addition, soil compaction, through water runoff, initiates the process of erosion and the pasture enters in a process of severe degradation (Hoyos et al 1995).

Subjective perceptions can be the most viable and unique source of information to estimate revenues or economic losses of complex processes, especially in tropical environments (Grisley and Kellogg 1983). Producers make decisions based on their experiences, knowledge, and available literature. Therefore, knowing about the perceptions of producers, and the extension agents who assist them, about the degradation process and its relationship to animal productivity, is very important in order to determine actions and formulate strategies for recuperating degraded pastures.

There are three advantages in adopting the perspective of producers to estimate the degree of degradation and its effect on animal productivity (Stocking and Murnaghan 2001): (1) measures are more realistic regarding the actual processes of degradation in the field; (2) evaluations make use of an integrated vision of the final user, the producer; and (3) results provide a more practical point of view in comparison with the type of interventions accepted by academics or advisers.

Objective

The general objective was to estimate the economic impact, at the farm and regional level, of losses in animal productivity and reduced incomes from the utilization of pastures under different stages of degradation, previously defined by selected groups of small livestock holders and extension agents in Honduras.

The specific objectives were to: (a) estimate milk and beef yields from cows grazing pastures at different stages of degradation; (b) estimate the income losses as a result of the degradation process; (c) estimate the proportion of pasture areas found in each stage of degradation within the six administrative regions of Honduras; and (d) identify different strategies and costs to recuperate degraded pastures.


Materials and Methods

The Workshop

The subjective perception of producers and extension agents was elicited in order to obtain the information to estimate losses of animal productivity within the farm, region, and country. For this purpose, a two-day workshop was carried out on March 16-17, 2004 where 25 producers of the 6 administrative regions of Honduras (South, Central Western, Atlantic, North-Eastern, Central Eastern, and North-Western) and 8 livestock extension agents of the Dirección de Ciencia y Tecnología Agropecuaria (DICTA) participated. This way, the exercise allowed the extrapolation of results not only within the farm but also regional in order to estimate the impact of pasture degradation on the entire Honduran livestock sector. The workshop took place in the city of Juticalpa, state of Olancho, in the North-Eastern region of Honduras.

Participating producers were chosen under the following criteria: (a) be a small livestock holder producing milk and/or beef for the market; (b) income should come mainly from the livestock activity; (c) live preferably in the farm; (d) have adopted and established improved grasses in the farm; and (e) have at least 10 years of experience producing milk and/or beef.

During the morning of the first day of the workshop, informal lectures were given in order to explain the concept of pasture degradation and methodology to be used. A scoring of 4 levels of pasture degradation was defined: Level 1 being the best (i.e., non-apparent degradation) and 4 the worst (i.e., severe degradation) using the methodology developed by Barcellos (1986) described in Table 1. The five descriptive factors for estimating the quality of the pasture included color, dead matter, uncovered soil, presence of weeds and age of pasture since establishment.

Table 1. Qualitative and quantitative description of each of the four pasture degradation levels

 

Symptom

Level of Degradation

 

1
Non- apparent

2
Low

3
Moderate

4
Severe

Color

Dark Green

Light Green

Green-Yellow

Yellow

 

Dead matter

<10 %

11-20 %

21-30 %

>30 %

 

Uncovered soil

<10 %

11-20 %

21-30 %

>30 %

 

Weeds

<10 %

11-20 %
weeds appears with narrow leaves

21-30 %
weeds appears with wide leaves

>30 %
more pasture colonization using native grasses

 

Age, years established

1-3

4-6

7-9

> 10

 

Source: Barcellos 1986

 

Then, two surveys were explained in detail, which each participant had to complete. The first one consisted in estimating the expected milk and beef yields and the stocking rate of animals grazing pastures under each of the 4 levels of degradation, in both rainy and dry seasons. A copy of both surveys can be found in Holmann et al (2004).

The second survey consisted in estimating: (a) the proportion of total pasture area found in each of the 4 levels of degradation in the region where each producer came from (the livestock extension agents were requested to answer this question at national level, not regional); (b) identification of the strategy to recuperate pastures under each of the 4 levels of degradation, adding the corresponding costs and estimated time; and (c) the critical level of degradation in which to start investing resources to recuperate it.

Participants were divided in four groups. Each group was a mixture of producers from each of the 6 regions and two extension agents. Each group received a set of information containing: (a) a copy of Table 1; and (b) color photos with samples of each level of degradation to facilitate the completion of both surveys. These photos were shown during the lecture where the concept of pasture degradation was explained. Thus, participants were already familiar with these pictures. The distributed photos can be found in Holmann et al (2004).

With these defined levels of degradation, three farms (close to Juticalpa) were chosen in a previous visit one month before the workshop which had pasture plots at different levels of degradation. After selecting the plots that would be visited during the workshop, the producer was requested not to allow grazing in those pastures, so that, at the time of the visit, the plots would be in the best possible condition to reduce the bias from grazing.

Participants visited these farms together in the afternoon of the first day of the workshop. Seven 1/3-ha plots representing the four levels of degradation were visited. After a 30-minute walk in each plot the survey was completed. The color photographs of each of the seven visited plots can be found in Holmann et al (2004).

At the end of the afternoon, participants completed the second survey, and both surveys were delivered to the first author of the study. During the second day, results from both surveys were presented using as example the North-Eastern region in order to provoke discussion.

Statistical analysis

Data from both surveys were entered into an Excel database for analysis using the statistical software SAS (Statistical Analysis System, version 8.2). For the analysis of the first survey containing 227 items, descriptive statistics were obtained, and regressions were generated which best explained animal yield losses at each level of pasture degradation.

For the analysis of the second survey containing 33 items, the SPSS statistical software was used (Statistical Package for Social Sciences, version 10) to generate simple and crossed descriptive statistics and frequency tables.

Estimation of milk and beef yields in areas of permanent pastures

In order to estimate the production of milk and beef for each degradation level, the following formulae were used:

The milk yield was estimated through the application of the following equation:

(1) Y = (An * {[(MYRain-Level n * (M/12) ] + [(MYDry-Level n * (1-M/12)]} * 0.25 * 365) /1000

where

Y = milk yield, in metric tonnes of fluid milk per year
An = area of the n region with permanent pastures, in hectares
MYRain-Level n = milk yield, in kg/ha/day, during the rainy season, according to the regressions of Table 2 for each level of degradation
M = months of duration of the rainy season
MYDry-Level n = milk yield, in kg/ha/day, during the dry season, estimated according to the regressions of Table 2 for each level of degradation
0.25 = factor representing the national average of cows in permanent milking (i.e., 25%) as a percentage of the national herd
365 = number of days in one year
1000 = factor to convert kilograms to metric tonnes

The beef yield was estimated through the application of the following equation:

(2) Y = (An * {[ (BYRain-Level n * (M/12) ] + [ (BYDry-Level n * (1-M/12)]} * 0.49 * 365)/ 1000

where

Y = yield of beef of growing females and males, in metric tonnes of live weight gains per year
An = area of the n region with permanent pastures, in hectares
BYRain-Level n = beef yield, in kg/ha/day of livestock, during the rainy season, estimated according to the regressions of Table 2 for each level of degradation
M = months of duration of the rainy season
BYDry-Level n = beef yield, in kg/ha/day of livestock, during the dry season estimated according to the regressions of Table 2 for each level of degradation
0.49 = factor representing the national average of growing females and males (i.e., 49%) as a percentage of the national herd
365 = number of days in one year
1000 = factor to convert kilograms to metric tonnes

The estimation of the annual milk yield by producers in each region and by extension agents at national level, was then compared with the official data in order to determine the degree of certainty of the subjective perceptions. The annual estimate of the beef yield was not possible to compare with the official data. This was due to the fact that official data only reports animals slaughtered annually and not the weight gain increases of all growing females and males, which was the goal of this study.

Estimation of productivity and income losses

In order to estimate the loss in milk yield due to the degradation process, Equation 1 (described previously) was applied. For example, in order to estimate the loss in milk yield within areas with pastures at Level 4 by not being at Level 1, Equation 1 is applied twice. The first time is to estimate the quantity of milk that could be produced in Level 4 areas if they were at Level 1. The second time is for estimating the actual quantity of milk produced at Level 4. Subtracting the result of the first application from the second give us the quantity of milk forgone due to having pastures at Level 4.

Y = (Alevel 4 * {[ (MYRain-Level 1 * (D/12) ] + [ (MYDry-Level 1 * (1-D/12)]} * 0.25 * 365)/1000 - (Alevel 4 * {[ (MYRain-Level 4 * (D/12) ] + [ (MYDry-Level 4 * (1-D/12)]} * 0.25 * 365)/ 1000

This exercise was repeated three times. The first one for estimating the quantity of milk forgone in pastures having a Level 2 degradation. The second exercise was for estimating the milk yield forgone in pasture areas with Level 3, and the third exercise was for estimating the milk yield forgone in pasture areas with Level 4. This same process was repeated for estimating beef yield losses using Equation 2.

In order to estimate the income losses, as a result of the reduction of milk and beef yields due to the degradation process, the losses in milk and beef production at each level of degradation were multiplied by the prices of milk and beef reported in Table 9.

Estimation of recuperating degraded pasture areas

In order to estimate the cost of recuperating regional and national areas at different levels of degradation, the weighted average costs/ha were multiplied by the pasture areas at each degradation level.


Results and Discussion

Perception of milk and beef yield reductions in the degradation process

Table 2 contains the regressions generated from the survey information which best explained the productivity loss of milk and beef according to season of the year. With these regressions, estimated losses in production of milk and beef for each degradation level and region of the country were generated, in terms of volumes (i.e., tonnes of beef and milk annually) and revenues (i.e., million dollars per year). These regressions were linear in the Southern, Atlantic, Central Eastern and North-Western regions, and for livestock extension agents; and exponential in the Central Western and North-Eastern regions (Table 2).

Table 2. Regressions for estimating the response in milk and beef yield per hectare by season of the year and region in Honduras

Region

Milk yield, kg/ha/day

Beef yield, gr/ha/day

Rainy season

Dry season

Rainy season

Dry season

South

y = 14.37 – 3.59x

y = 8.97 – 2.36x

y = 988 – 237x

y = 475 – 124x

Central Western

y = 31.18e-0.88x

y = 31.01e-1.56x

y = 3135e-1.21x

y =  2122e-1.75x

Atlantic

y = 13.51 – 2.89x

y = 13.68 – 3.21x

y = 703 – 133x

y = 1555 – 408x

North-Eastern

y = 24.09e-0.56x

y = 11.28e-0.63x

y = 2319e-0.61x

y =  901e-0.66x

Central Eastern

y = 10.00 – 2.11x

y = 4.22 – 1.04x

y = 1782 – 439x

y = 661 – 176x

North Western

y = 16.43 – 3.86x

y = 4.96 – 1.30x

y = 1232 – 308x

y = 164 – 47x

Extension agents

y = 20.30 – 4.67x

y = 7.76 – 1.97x

y = 1644 – 389x

y = 454 – 131x

y = milk or beef yield (i.e., in kg/ha/day);  x = degradation level (i.e., 1, 2, 3 or 4)

Figures 1 and 2 show the production of milk and beef for each degradation level generated from these regressions. As observed, there was the general trend to associate low milk and beef yields and low stocking rates as the degradation process increased, which was expected.

Figure 1. Perceived milk yield by level of degradation.

 

 

 

Figure 2. Perceived beef yield by level of degradation

Pasture areas in each level of degradation

Table 3 contains the national livestock inventory and the areas under permanent pastures for each of the 6 administrative regions of Honduras.

Table 3. Livestock inventory, permanent pasture areas, and animal stocking rate by administrative region in Honduras, according to the 1997 agricultural and livestock census

Region

Livestock Inventory

Pasture area, ha

Total heads

Adult cows

Males and growing females

Milking1

Dry

South

258,344

44,394

46,206

167,744

173,174

Central Western

130,020

23,932

24,908

81,180

112,502

Atlantic

237,316

44,345

46,155

146,816

145,859

North-Eastern

404,976

68,941

71,755

264,280

387,220

Central Eastern

257,385

40,847

42,514

174,024

208,501

North-Western

772,742

120,260

125,169

527,313

508,407

TOTAL

2,060,783

342,720

356,706

1,361,357

1,535,663

1According to IICA (2003), 49% of the inventory of adult cows are in permanent milking
Source: Dirección General de Estadística y Censo (1998); FAO (2004)

Table 4 shows the production of milk and beef by region during the year 2003. As observed, there are a little over 1.5 million hectares under permanent pastures with more than 2 million head of cattle distributed among more than 100,000 livestock farms that produced some 597,000 tonnes  of fluid milk and 57,000 tonnes of beef.

Table 4. Number of farms, milk and beef production, and average farm size for each of the six administrative regions of Honduras in 2003

Region

Number of Farms

Annual milk yield, tonnes fluid milk

Annual beef yield, tonnes

Average Farm Size

cows/farm

ha/farm

South

15,335

77,329

7,022

5.9

11.3

Central Western

15,520

41,686

3,398

3.1

7.2

Atlantic

6,305

77,244

6,147

14.3

23.1

North-Eastern

18,722

120,087

11,065

7.5

20.7

Central Eastern

15,487

71,151

7,286

5.4

13.5

North-Western

30,177

209,4780

22,077

8.1

16.8

TOTAL

101,276

597,000 a

57,000

6.9

15.2

a The average yield by milking cows during 2003 was of 4.8 kg/day
Source: Dirección General de Estadística y Censo (1998); IICA (2003); FAO (2004)

When participants were asked to estimate the proportion of pasture area within their regions found in each level of degradation, the answer was variable (Table 5). The North-Eastern region showed the highest proportion (and quantity) of area with degradation problems, since it has the greater proportion with moderate (i.e., Level 3, 32%) and severe degradation (i.e., Level 4, 38%). The Southern region has less degradation problems, since more than 66% of the pasture area is between Levels 1 (43%) and 2 (23%). The other regions were in between these two extremes.

Table 5. Estimated proportion of pastures for each level of degradation by region in Honduras

Region

Level of degradation1

Level 1
(Non-apparent)

Level 2
(Low)

Level 3
(Moderated)

Level 4
(Severe)

Proportion, %

Area, ha

Proportion, %

Area, ha

Proportion, %

Area, ha

Proportion, %

Area, ha

South

43.3

74,984

23.3

40,349

13.3

23,032

20.0

34,635

Central Western

30.0

33,751

16.7

18,788

23.3

26,212

30.0

33,751

Atlantic

26.7

38,944

16.7

24,358

28.3

41,278

28.3

41,278

North-Eastern

15.6

60,400

13.8

53,436

32.5

125,847

38.1

147,531

Central Eastern

23.3

48,581

23.3

48,580

25.0

52,125

28.4

59,214

North Western

34.0

172,858

28.0

142,354

20.0

101,681

18.0

91,513

Average Producers

28.8

429,518

20.3

327,865

23.7

370,175

27.1

407,922

Extension agents

18.8

288,705

28.1

431,521

22.5

345,524

30.6

469,913

1 Mean degradation level for the country is 2.48 and 2.65, according to producers and extension agents, respectively

Comparing the perception of degraded areas between livestock producers and extension agents, the latter perceive a lower problem of degradation. According to producers, in Honduras 29% of the area under pastures is in Level 1 (i.e., no degradation) in comparison with 19% perceived by extension agents. In addition, producers perceive a smaller proportion of pastures in conditions of severe degradation (i.e., Level 4, 27%) compared with almost 31% perceived by extension agents. At the intermediate degradation levels (i.e., Levels 2 and 3) both groups were similar.

Production of milk and beef perceived at each degradation level

Table 6 shows the production of milk and beef that livestock producers and extension agents perceive based on the pasture areas found in each degradation level. These data were obtained through the application of the regressions in Table 2 based on the methodology described earlier.

Table 6.  Estimated production* of milk and beef for each level of degradation

Region

Degradation level

Total

Difference with official data %

Level 1
(non-apparent)

Level 2
(low)

Level 3
(Moderate)

Level 4
(Severe)

Fluid milk production (tonnes/yr

Weight gains, tonnes/yr

Fluid milk production tonnes/yr

Weight gains tonnes/yr

Fluid milk production tonnes/yr

Weight gains tonnes/yr

Fluid milk production tonnes/yr

Weight gains tonnes/yr

Fluid milk yield tonnes/yr

Live cattle yield tonnes/yr

South

57,065

6,947

20,177

2,497

5,464

721

0

31

82,706

10,196

+ 7.0

Central Western

28,303

3,652

5,195

514

2,631

197

1,294

66

37,423

4,429

- 10.2

Atlantic

37,633

4,639

17,003

2,152

17,703

2,274

6,629

1,144

78,968

10,209

+ 2.2

North Eastern

54,459

9,324

26,964

4,425

35,484

5,582

23,290

3,509

140,196

22,840

+ 16.8

Central Eastern

24,515

7,941

17,554

5,265

11,320

2,787

4,377

- 85

57,766

15,908

- 18.8

North Western

128,079

16,076

71,964

8,733

27,464

3,001

3,173

- 196

230,680

27,614

+ 10.1

Total Producers

330,054

48,579

158,857

23,586

100,066

14,562

38,763

4,469

627,739

91,196

+ 5.2

Extension agents

281,884

40,688

290,991

40,827

128,008

16,562

32,160

756

733,043

98,833

+ 22.8

Estimates obtained from the regressions in Table 2 and pasture areas for each level of degradation reported in Table 5

Comparing milk and beef yields between producers and extension agents, the latter perceive a higher production of both milk and beef at the extreme degradation levels (i.e., Levels 1 and 4) and a lower production in the intermediate levels (i.e., Levels 2 and 3). However, once the total production is consolidated, extension agents perceive that Honduras produces 17% more milk and 8% more beef than the volumes perceived by producers. Comparing the milk yield estimates against the official data reported by the Government of Honduras, producers overestimated milk production by 5% while extension agents overestimated it by 23%.

Forgone milk and beef production as a result of the degradation process

Table 7 shows the annual milk yield that each region forgoes for having pasture areas at various degradation levels different to Level 1. In other words, it is the quantity of additional milk that each region could produce if all areas under permanent pastures were at Level 1.

Table 7.  Estimates of milk production forgone due to the process of pasture degradation with respect to level 1

Region

Milk production forgone, tonnes/year

Total

Level 2 (Low)

Level 3 (Moderate)

Level 4 (Severe)

South

10,530

12,064

23,984

46,578

Central Western

10,560

19,350

27,009

56,919

Atlantic

6,535

22,185

33,259

61,979

North-Eastern

21,211

77,973

109,717

208,901

Central Eastern

6,959

14,983

25,503

47,445

North-Western

56,115

47,877

64,634

168,626

Total producers

111,910

194,432

284,106

590,448

Extension agents

105,528

189,490

399,637

694,655

Table 8 shows the same information for beef production.

Table 8. Estimates of beef production forgone due to the process of pasture degradation with respect to level 1

Region

Beef weight gain forgone, tonnes/year

Total

Level 2
(Low)

Level 3
 (Moderate)

Level 4
(Severe)

South

1,241

1,413

3,178

5,832

Central Western

1,519

2,639

3,586

7,744

Atlantic

749

2,642

3,773

7,164

North-Eastern

3,822

13,842

19,262

36,926

Central Eastern

2,676

5,734

9,765

18,175

North-Western

4,506

6,456

8,707

19,669

Total producers

14,513

32,726

48,271

95,510

Extension agents

20,128

32,134

65,471

117,733

Table 9 reports producer farm gate prices per tonne of milk and beef in 2004, US$/tonne during dry and rainy seasons

Table 9.  Producer farmgate prices per ton of milk and beef in 2004, US$/tonne a

Region

Length of rainy season, months

Milk price

Beef price

Rainy

Dry

Mean Price1

Rainy

Dry

Mean price1

South

5

146

315

245

1020

1070

1050

Central Western

5

236

309

279

990

990

990

Atlantic

10

266

266

266

990

990

990

North-Eastern

6

112

281

197

990

990

990

Central Eastern

6

185

253

219

990

1010

1000

North-Western

6

169

253

211

990

990

990

Mean

6.3

186

280

236

1000

1010

1000

a Based on an exchange rate of Lps 17.80 per US$1
1 Price per tonne of fluid milk and beef

Milk

The milk yield that the country forgoes due to the process of pasture degradation is significant. According to the subjective perception of producers, Honduras is not producing 284,106 tonnes of fluid milk per year because it has pasture areas at Level 4 (i.e., severe degradation), equivalent to 48% of the national production of milk (Table 7).

That is, if both public and private sectors carry out a strategy for producers to maintain their grazing areas between Levels 1 and 3 (i.e., not allowing pasture areas to reach Level 4), Honduras, according to producers, could produce today 48% more milk with the same cows in the same pasture areas. In economic terms, this forgone milk is worth $63 million annually (Table 10). The perception of extension agents is that Honduras could produce 66% more milk if producers renovate their pastures before they reach Level 4, which represents $94 million annually in revenue.

Table 10. Estimates of forgone revenues as a result of reduced milk yields due to the process of pasture degradation with respect to level 1, million US$/year

Region

Forgone revenue as a result of reduced milk yields

Total

Level 2
(Low)

Level 3
 (Moderate)

Level 4
(Severe)

South

2.58

2.95

5.88

11.41

Central Western

2.95

5.40

7.53

15.88

Atlantic

1.74

5.90

8.85

16.49

North-Eastern

4.18

15.36

21.61

41.15

Central Eastern

1.52

3.28

5.59

10.39

North-Western

11.84

10.10

13.64

35.58

Total producers

24.81

42.99

63.10

130.90

Extension agents

24.90

44.72

94.31

163.93

Beef

According to the subjective perception of producers, the country forgoes weight gains equivalent to 48,271 tonnes of beef annually by having grazing areas in Level 4 (Table 8). Honduras slaughters around 345,000 animals per year producing about 130,000 tonnes of beef. Thus, producers perceive that the country could produce 37% more beef if pasture areas currently under Level 4 were in Level 1, equivalent to $48 millions (Table 11). Likewise, extension agents consider that the weight gains forgone by having pasture areas in Level 4 is higher (i.e., 65,471 tonnes of beef, equivalent to 50% of the annual beef production of Honduras), equivalent to $65 millions.

Table 11. Estimates of forgone revenues as a result of reduced beef yields due to the process of pasture degradation with respect to level 1

Region

Forgone revenues as a result of reduced beef yield, million US$/year

Total

Level 2
(Low)

Level 3
 (Moderate)

Level 4
(Severe)

South

1.30

1.48

3.34

6.12

Central Western

1.50

2.61

3.55

7.66

Atlantic

0.74

2.62

3.74

7.10

North-Eastern

3.78

13.70

19.07

36.56

Central Eastern

2.68

5.73

9.77

18.18

North-Western

4.46

6.39

8.62

19.47

Total producers

14.46

32.53

48.09

95.08

Extension agents

20.13

32.13

65.47

117.73

Strategies to recuperate degraded pasturelands

Table 12 shows the strategies and costs to recuperate pastures which are in different stages of degradation according to the perception of producers.

Table 12.  Strategies utilized by producers to recuperate pastures in different levels of degradation. Figures in parenthesis represent the proportion of people that would use the particular strategy

Strategy (n=25)

Cost and time to recuperate degraded pastures

From Level 2 to Level 1

From Level 3 to Level 1

From Level 4 to Level 1

Time, months

Cost, $/ha

Time, months

Cost, $/ha

Time, months

Cost, $/ha

a) Let pasture rest

2.4 (40 %)

0

2.0, (8 %)

0

 

 

b) Let pasture rest until seeding occurs

3.8 (12 %)

0

6.0 (4 %)

0

12.0 (4 %)

0

c) Planting a legume associated with a grass

2.5 (4 %)

111

2.5 (4 %)

33

 

 

d) Intensive grazing until biomass is low, then plow with tractor and let pasture rest

 

 

 

 

4.0 (20 %)

161

e) Fertilize, then let pasture rest

2.2 (44 %)

55

2.5 (44 %)

63

2.0 (4 %)

39

f) Re-plant areas infested with weeds, then let pasture rest

 

 

4.0 (32 %)

88

4.5 (8 %)

97

g) Establish pasture again

 

 

5.0 (8 %)

115

6.0 (64 %)

154

Weighted average

2.5

29

3.4

66

5.6

140

Table 13 shows the same information from extension agents. Both groups perceive that it is more economical, practical and faster to recuperate degraded pastures in their early stages (i.e., Level 2) and, as the process of degradation advances (i.e., to Levels 3 and 4), the cost of recuperating these pastures increases significantly as well as the time to recover them.

Table 13.  Strategies recommended by extension agents to recuperate pastures in different levels of degradation. Figures in parenthesis represent the proportion of people that would use the particular strategy

Strategy (n=8)

Cost and time to recuperate degraded pastures

From Level  2 to  Level 1

From Level 3 to Level 1

From Level  4 to Level  1

Time, months

Cost, $/ha

Time, months

Cost, $/ha

Time, months

Cost, $/ha

a) Let pasture rest

3.0 (25 %)

0

 

 

 

 

b) Let pasture rest until seeding occurs

3.0 (12.5 %)

0

4.5 (25 %)

0

 

 

c) Planting a legume associated with a grass

 

 

 

 

 

 

d) Intensive grazing until biomass is low, then plow with tractor and let pasture rest

 

 

 

 

 

 

e) Fertilize, then let pasture rest

2.2 (62.5 %)

46

2.5 (25 %)

83

 

 

f) Re-plant areas infested with weeds, then let pasture rest

 

 

4 (50 %)

115

5.0 (12.5 %)

139

g) Establish pasture again

 

 

 

 

6.0 (87.5 %)

184

Weighted average

2.5

29

3.7

78

5.9

178

Going from Level 2 to 1

Both groups perceived that the recuperation of a pasture from Level 2 to Level 1 is worth around $29/ha and takes about 2.5 months resting time. A group of producers (44%) chose the strategy of pasture fertilization (with an average cost of $55/ha) then a rest period of 2.2 months. This option was also the most frequent recommendation by extension agents (63%). A second group of producers (40%) considered that a resting period of 2.4 months would be sufficient for full recovering (i.e., no cash expenses). About 25% of extension agents recommended this strategy but the resting period was longer (i.e., 3 months). A smaller group of producers (12%) would let the pasture rest longer until seed bearing (i.e., 3.8 months). Extension agents advising this strategy (12%) recommended a shorter period of resting time (i.e., 3 months).

The estimated cost, at the national level, to recuperate pasture areas in Level 2 is about $9.5 million according to producers and $12.5 million according extension agents (Table 14). This amount represents, in the opinion of producers, 24% of the forgone revenues from milk and beef (i.e., $39 million, Tables 10 and 11). In the opinion of extension agents, this cost for pasture recuperation represents 28% of the $45 million in forgone revenues.

Table 14.  Cost of recuperating degraded pastures to Level 1 for each region of Honduras, million US$

Region

Level 2

Level 3

Level 4

Area, ha

Recovering cost

Area, ha

Recovering cost

Area, ha

Recovering cost

South

40,349

1.17

23,032

1.52

34,635

4.85

Central Western

18,788

0.54

26,212

1.73

33,751

4.73

Atlantic

24,358

0.71

41,278

2.72

41,278

5.78

North-Eastern

53,436

1.55

125,847

8.31

147,531

20.65

Central Eastern

48,80

1.1

52,25

3.4

59,14

8.9

North Western

142,354

4.13

101,681

6.71

91,513

12.81

Total  Producers

327,865

9.51

370,175

24.43

407,922

57.11

Extension agents

431,521

12.51

345,524

26.95

469,913

83.64

Going from Level 3 to 1

According to producers, to recuperate a pasture from Level 3 to Level 1 costs $66/ha and takes about 3.4 months of resting time. Extension agents perceive that the recuperation cost would be 18% higher ($78/ha) and would take 9% longer time (i.e., 3.7 months) than the one reported by producers. Most producers (76%) would try to recuperate this level of degradation by either fertilizing the pasture (44%) or replanting the areas infested with weeds (32%) and then let the pasture rest. About 75% of extension agents answered similarly. On the other hand, when the costs of recovering degraded pastures are compared between Levels 2 and 3, producers estimate that recuperating a pasture from Level 3 is 128% more expensive than recovering it from Level 2 (i.e., $66/ha vs. $29/ha, Table 12) and takes 36% more time (i.e. 3.4 months vs. 2.5 months). The perception of extension agents is more pessimist: they consider that recovering a pasture from Level 3 is 170% more expensive than recovering it from Level 2 (i.e., $78/ha vs. $29/ha, Table 13) and takes 48% more time.

The estimated cost, at the national level, to recover the areas which are in Level 3 is about $24 million according to producers and $27 million according to extension agents (Table 14). This amount represents, in the opinion of producers, 32% of the $75 million in forgone revenues from reduced milk and beef yields (Tables 10 and 11). According to extension agents, this amount represents 35% of the $77 million in forgone revenues from lower milk and beef production.

Going from Level 4 to 1

According to producers, the recuperation of a pasture from Level 4 to Level 1 costs about $140/ha and takes almost half year (i.e., 5.6 months). Extension agents perceive that the recuperation cost would be 27% higher ($178/ha) and would take 5% more time (i.e., 5.9 months) than the one reported by producers.

Most producers (64%) considered that the best strategy to recover a pasture in this level of degradation is to completely establish the pasture again at a cost of $154/ha and to wait 6 months. About 87% of extension agents would also recommend this strategy but at a higher cost, $184/ha. The establishment of a pasture implied in all cases soil preparation with machinery or animal traction, application of herbicides, seed planting, and application of fertilization (i.e., NPK)

A second group of producers (20%) would recuperate pastures in this level of degradation by grazing the plot intensively, then apply several passes of harrow with a tractor at a cost of $161/ha, plus a resting period of 4 months. The rest of extension agents (13%) would recommend the strategy of replanting the infested areas with weeds at a cost of $139/ha, plus a resting period of 4 months.

The estimated cost, at the national level, to recuperate areas under Level 4 of degradation is about $57 million according to producers, and $84 million perceived by extension agents (Table 14). This amount represents, in the opinion of producers, 51% of the $111 million in forgone revenues for milk and beef yield reductions (Tables 10 and 11). Additionally, in the opinion of extension agents, this amount represents 52% of the $160 million in forgone revenues from lower animal productivity.

Useful life of improved grasses throughout the degradation process

On average, producers perceive that grasses take proportionately less time in going from Level 1 to 2 (i.e., 2.9 years) and as the process of degradation advances, pastures remain longer at each degraded level (i.e., 3.1 years in going from Level 2 to 3 and around 4.0 years in going from level 3 to 4). Moreover, producers perceive that the mean productive life of improved grasses is approximately 10 years, ranging from 9 years for Brachiaria humidicola and Digitaria swazilandensis up to 12.3 years for "Star grass" (Cynodon nlemfuensis, Table 15).

Table 15.  Estimated life a pasture spends in each level of degradation until the process is completed, according to the perception of producers, years

Species

Level 1 to 2

Level 2 to 3

Level 3 to 4

Total Useful Life

Bracharia decumbens (n = 12)

3.21

3.13

3.58

9.92

Bracharia hybrid (Mulato) (n = 8)

2.25

3.25

4.31

9.81

Panicum maximum (Tanzania) (n = 3)

3.33

3.00

4.33

10.66

Cynodon nlemfuensis (Star) (n = 3)

4.67

2.33

5.33

12.33

Digitaria swazilandensis (n = 1)

2.00

3.00

4.00

9.00

Bracharia humidicola (n = 1)

1.00

4.00

4.00

9.00

Andropogon gayanus (n = 5)

2.30

3.30

4.00

9.60

Bracharia brizantha  (Marandú) (n = 8)

2.75

2.75

3.90

9.40

Panicum maximum (Guinea) (n = 2)

4.25

3.00

3.50

10.75

Panicum hybridum (King grass) (n = 1)

3.00

4.00

5.00

12.00

Bracharia brizantha (Toledo), (n = 3)

2.17

3.17

4.00

9.34

Average (n = 47)

2.87

3.07

4.03

9.97

On the other hand, extension agents perceive that grasses degrade faster, with a productive life of 8.4 years, 16% lower than producers, ranging from 6 years for Digitaria swazilandensis up to 12 years for Brachiaria Brizantha cv. Marandú (Table 16).

Table 16.  Estimated life a pasture spends in each level of degradation until the process is completed, according to the perception of extension agents, years

Species

Level 1 to 2

Level 2 to 3

Level 3 to 4

Total Useful Life

Bracharia decumbens (n = 2)

3.00

3.40

4.00

10.40

Bracharia hybrid (Mulato) (n = 3)

1.83

2.67

3.33

7.83

Cynodon nlemfuensis (Estrella) (n = 2)

2.50

2.50

2.50

7.50

Digitaria swazilandensis (n = 1)

1.00

2.00

3.00

6.00

Bracharia humidicola (n = 1)

1.00

3.00

4.00

8.00

Andropogon gayanus (n = 1)

4.00

2.00

1.00

7.00

Bracharia brizantha (Marandú) (n = 1)

5.00

4.00

3.00

12.00

Panicum maximum (Guinea) (n = 2)

3.50

1.50

2.00

7.00

Bracharia brizantha (Toledo) (n = 2)

2.00

4.00

5.00

11.00

Cynodon dactylon (Bermuda) (n = 1)

3.00

2.00

1.00

6.00

Average (n = 16)

2.60

2.73

3.06

8.39

When to start recuperating degraded pastures

When producers were asked for the critical level of degradation at which they would start investing resources to recuperate their pastures, the answer was Level 2.7. Extension agents would recommend to start investing resources when a pasture reaches Level 2.6. As a reference, the average level of pasture degradation in Honduras is, according to producers, 2.48, and for extension agents, 2.65 (Table 5).

Producers and extension agents perceive that pastures degrade at an annual rate of 10% and 11.9%, respectively (Tables 15 and 16). At these rates, Honduras would maintain the current degradation levels. That is, in order to maintain these levels, producers should renew annually between 10% and 12% of the total pasture area of each farm. However, the recuperation of pastures at a 10-12% annual rate does not solve the problem, only maintains it.

Producers from the Atlantic, North-Eastern and North-Western regions would await up to Levels 3.3, 3.2 and 3.0 respectively, before starting investing resources to recuperate pastures, while producers from the Southern, Central Western, and Central Eastern regions would do it earlier (i.e., when the level of degradation reaches 2.3) (Table 17).

Table 17.  Level of pasture degradation perceived as critical to start investing resources to recuperate it.  Ranges of responses are in parenthesis

Region

Critical level of degradation

South (n=3)

2.3 (2 – 3)

Central Western (n=3)

2.3 (2 – 3)

Atlantic (n=3)

3.3 (2 – 4)

North Eastern (n=8)

3.2 (2 – 4)

Central Eastern (n=3)

2.3 (2 – 3)

North Western (n=5)

3.0 (2 – 4)

Total producers (n=25)

2.7 (2 – 3.5)

Extension agents (n=8)

2.6 (2 – 4)

Most producers argued that their current financial situation does not allow them to generate enough cash flow to invest resources to recuperate their pastures, and the option of credit is not viable because the current real interest rate is expensive (10%) and difficult to obtain. In order to verify this argument, we took as a case study the mean farm size from the last census of Honduras, which corresponds to a 15 ha-farm with a herd of 7 cows (Table 4). The season to recuperate pastures is during the rains, which coincides with a drop in the producer price of milk of about 34% due to excess supply from good weather conditions (i.e., $0.186/kg vs. $0.28/kg, Table 9). On the other hand, milk yield increases during the rains. Therefore, a cash flow was simulated based on the gross incomes from both seasons (Figure 3) and based on these resources Table 18 was constructed to simulate two scenarios: (1) the current situation of degraded pastures, represented by the national average (i.e., 30% of the pasture area at Level 1, 25% at Level 2, 25% at Level 3, and the remaining 25% at Level 4, Table 13) with the target of maintaining this current level [ie., renovating 10% of pasture area annually (i.e., 1.5 ha)]; and (2) the ideal situation, represented by the elimination of all grazing areas under Level 4 (ie., 3.75 ha).

Figure 3. Monthly gross income during dry and rainy seasons in a representative farm of Honduras

As observed in Table 18, with the current situation the gross income during the rainy season is about $861 (~$143/month) in comparison with $640 during the dry season (~$107/month). Assuming the producer uses this difference in revenue to renovate his pastures, there is barely enough resources for 1.5 ha ($221 @ $140/ha) equivalent to 10% of total grazing area. Thus, with the increase in gross income during the rainy season, the producer is able to maintain the current level of pasture degradation in the farm but unable to recuperate the remaining areas under Level 4 with existing farm resources. Under the ideal situation scenario (i.e., a farm without Level 4), if the producer could obtain a 18-month credit with a similar interest rate existing in the international market (i.e., 3%), then the producer is able to generate the additional income to pay the credit with the increase in milk yield the following year resulting from higher quality forage available.

Table 18.  Required resources for a representative farm of Honduras to renovated degraded pastures in two scenarios

Scenario

Degradation Level 1, %

Area to renovate, ha 2

Milk yield, kg milk/ha/day 3

Gross income4 by season of the year, US$/farm/season

Available resources5 during the rainy season to renovate degraded pastures

Rainy Season

Dry season

Rainy Season

Dry season

Resources, US$/Farm

Area6 that can be renovated

Current Situation

30-25-25-25

1.5

5.98

2.73

861

640

221

1.47

Ideal Situation

40-30-30-0

3.75

7.79

3.74

1072

817

609

4.06

1Proportion of grazing area at each degradation level (i.e., under the Current Situation, 30% of grazing area is with pastures in Level 1, 25% in Level 2, 25% in Level 3, and the remaining 25% in Level 4).
2 In the Current Situation scenario, this area is equivalent to 10%, which is the rate necessary to replace the pasture according to the useful life of 10 years perceived by producers. In the Ideal Situation scenario, it is necessary to renovate 25% of the grazing area (i.e., 3.75 has) in order to eliminate all pastures in Level 4.
3Yield based on the equations described in Table 2
4It includes the sale of 1 culled cow annually (300 kg @ $0.55/kg live weight) and 2 weaned male calves (90 kg each @ $0.90/kg live weight). The rainy season lasts 6 months and the dry season the remaining 6 months. It was assumed that 49% of adult cows are in permanent milking.
5For the Current Situation scenario, available resources for pasture renovation is the difference between the income obtained during the rainy season and the dry season. For the Ideal Situation scenario, available resources are the difference between the Ideal Situation and the Current one plus the difference between the income obtained during the rainy and the dry seasons.
6Assuming an establishment cost of US$150/ha.

In order to eliminate the degraded areas found in Level 4 at the country level, it is necessary a one-time investment of $57 million. The benefit obtained from this investment would result in a daily increase of 156,000 liters of milk and 26,500 kilograms of beef, equivalent to $22 millions/yr. Therefore, there are significant economic and productive incentives for the private and public sectors to develop and execute a plan of action to recuperate pasturelands in advanced stages of degradation.


Conclusions: Learned lessons

One specie of grass

It is recommended to visit plots with the same grass specie, preferably the most common in the country (ex., Bracharia decumbens), to reduce the bias involved in the evaluation of several species of grass as occurred in this study.

Length of the workshop

It is recommended to extend the duration of the workshop one more day (i.e., 3 days instead of 2) to have enough time to tabulate the survey data from all participants during the second day and to show the results on the third day to capture all the variability from the discussion. The second day could be used to have a field day.

Number of participating producers

In this workshop, 25 small livestock owners participated from 6 regions, averaging 4.2 persons/region. An increase to 5 producers per region is recommended to allow more discussion. This study was carried out with a budget of US$4,000 (excluding salaries). The extension of an additional workshop day with one additional producer per region would increase the cost to approximately US$5,000.


References

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Received 28 August 2004; Accepted 20 September 2004

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