Modelling the sustainability and productivity of pastoral systems in the communal areas of Namaqualand

ARTICLE IN PRESS

Journal of Arid Environments 70 (2007) 701–717

Journal of Arid Environments www.elsevier.com/locate/jaridenv

Modelling the sustainability and productivity of pastoral systems in the communal areas of Namaqualand F.D. Richardsona, B.D. Hahna,{, M.T. Hoffmanb, a

Department of Mathematics and Applied Mathematics, University of Cape Town, Private Bag X3, Rondebosch. 7701, South Africa b Botany Department, Leslie Hill Institute for Plant Conservation, University of Cape Town, Private Bag X3, Rondebosch, Cape Town 7701, South Africa Received 30 August 2005; received in revised form 20 July 2006; accepted 21 July 2006 Available online 23 January 2007

Abstract We investigated the effects of rainfall and the number of animals on changes in vegetation and on the output of milk and meat from the communal areas of Namaqualand. Previously published shortand long-term models link processes that range from the levels of tissue (in, for example, the mammary gland), to the milk yields of individual animals, to the growth and survival of their young and to long-term changes in plant species populations at the ecosystem level. These models have been used to study how different factors and management strategies affect livestock productivity and vegetation composition on a 20,000 ha rangeland in Namaqualand. First, the inter-relations between rainfall, stocking rate and productivity were studied using the short-term model. This model shows that in addition to total rainfall and stocking rate, the timing of rainfall within a year also influences doe live weight and survival to the end of the year. When the long-term model is run, using recorded rainfall, predictions of small stock numbers agree closely with livestock data recorded over the same 30-year period. One thousand replicates of 100-year runs of the long-term model were then used to study the probable impact of different upper limits to stock numbers on animal performance. Off take (sales and slaughterings) are maximal when stock numbers are limited to 2000 adults. Animal numbers increase marginally as the limit is increased above this level, but the variability between years in numbers increases. Secondly, the long-term model was used to study the long-term effects of the stocking rate strategies on rangeland condition. The model predicts that although these effects are variable, when moderately degraded range is stocked with an upper limit at the recommended Corresponding author. Tel.: +27 21 650 2440; fax: +27 21 650 4046.

E-mail address: [email protected] (M.T. Hoffman). Deceased author.

{

0140-1963/$ - see front matter r 2006 Published by Elsevier Ltd. doi:10.1016/j.jaridenv.2006.07.013

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

702

level it is unable to recover to less degraded states over 100 years. Thirdly, the model was used to examine the effects of reduction in stock numbers and slaughtering of kids in a drought year on goat numbers during the subsequent 5 years. Finally, the model predicts that a 10% reduction in mean annual rainfall will lead to a 35% reduction in animal numbers over 200 years. r 2006 Published by Elsevier Ltd. Keywords: Climate change; Degradation; Desert; Karoo; Livestock production; Disequilibrium

1. Introduction Overgrazing by domestic livestock is considered to be one of the most important threats to the biodiversity of Namaqualand (Cowling and Pierce, 1999). Effective planning and management to ensure the livelihoods of pastoralists in the short-term and to sustain the long-term productivity of the range require that the behaviour of the system is understood. Mathematical models enable integration of all the individual processes and their interactions within a rangeland system (Thornley, 1998). Biot (1993) suggested that modelling the behaviour of rangeland is preferable to an approach based solely on monitoring for the prediction of long-term responses to different management strategies. Dynamic simulation models have been developed for a communal rangeland at Paulshoek in central Namaqualand (Hahn et al., 2005; Richardson et al., 2005). This area was chosen as a large amount of data on the abundance and biomass productivity of different plant species has been collected over nearly a decade of research. In addition long-term data sets of animal numbers and daily rainfall are available as well as some data on the growth of individual animals. There are three further reasons for modelling this area:



 

Firstly, although there are reports that perennial palatable shrublands have been replaced by annual-dominated vegetation associated with unpalatable or poisonous plants (Hoffman et al., 1999; Todd and Hoffman, 1999), the factors or combinations of factors that cause such degradation are not well understood. Secondly, the predicted adverse effects of climate change on vegetation may be most severe in Namaqualand (Midgely et al., 2001). Thirdly, as a result of the land redistribution programme, a larger proportion of land in Namaqualand will in future be held under communal tenure than at present (Wyn-Jones et al., 1998).

The range at Paulshoek is approximately 20,000 ha in extent and is situated at about 1000 m above sea level. Although the mean annual rainfall is 200 mm, it is very variable with a coefficient of variation (CV) of 0.39. This is greater than the CV (0.33) above which rangelands are thought to exhibit disequilibrium dynamics (Ellis, 1995). Most of the rainfalls during winter from April to September. Temperatures rarely exceed 37 1C in the summer months and sub-zero temperatures can be experienced in winter. The terrain is mountainous and rocky, although well-drained deep soils derived from gneiss boulders and bed-rock material occupy the river valleys. The texture of these soils is mainly sandyclay loam. In the lower-lying areas of Paulshoek the vegetation is dominated by a mixture

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

703

of perennial, low-growing (less than 1 m) leaf succulent shrubs and deciduous and evergreen shrubs. When heavily utilized, perennial plants are replaced by annuals, geophytes and the perennial toxic shrub, Galenia africana (GA). Higher-lying areas are dominated by Elytropappus rhinocerotis (renosterbos), a 1.5 m shrub unpalatable to livestock. Although more than 400 plant species have been recorded at Paulshoek, to simplify modelling, they were aggregated into four guilds (ecologically meaningful groups of species) which are described in general terms by Todd and Hoffman (1999) as woody perennial shrubs palatable to livestock (WP) (e.g. Tripteris sinuatum, Pentzia incana), succulent shrubs, primarily in the family Mesembryanthemaceae (ME—Mesembs) (e.g. Ruschia robusta, Leipoldtia schulzii), an unpalatable shrub guild which is dominated by GA (kraalbos) and annuals and geophytes (AG) (e.g. Leysera tenella, Homeria bifida). There are about 28 permanent flocks in Paulshoek comprising goats and sheep in a ratio of about 2:1. Individual herds amalgamate and separate from time to time depending on the personal circumstances of individual livestock owners (Baker and Hoffman, 2006). Individual herd size ranges fromo10 to4300 animals and since 1971 the total number of livestock on the Paulshoek rangeland has varied from 1007 to 6269 animals. This variation is influenced largely by rainfall and the needs and circumstances of the owners. Over the past 34 years (1971–2004) an average of 3458 animals have been kept on the Paulshoek range. Stocking rates are usually estimated in terms of small stock units (SSU) where different classes of animals are assigned a relative value according to the amount of forage that they would eat under optimum conditions. In this paper, adult female goats are one SSU, un-weaned kids and yearlings are equivalent to 0.5 and 0.8 SSU, respectively. Model output predicted that when the average total number of goats was 3424 the average SSU were 2170 (Richardson et al., 2005). If the conservative estimate of 200 donkeys (equivalent to 780 SSU) present in the area are included, then Paulshoek rangelands have supported substantially more animals than the long-term average stocking rate of 2000 SSU (0.1 SSU/ha) recommended by the National Department of Agriculture (Hoffman et al., 1999). 2. The models The productivity of rangelands is influenced by many factors including rainfall and its variability between and within years and soil characteristics such as infiltration rates and water storage capacity. Present attributes of the vegetation including standing biomass, species composition and water-use efficiency of different species are also important. The vegetation is influenced by the number and characteristics of herbivores which in turn vary over time with the amount and composition of the forage that they are able to eat and the decisions of their herders concerning where and for how long they should feed. Modelling such a system presents several problems. In addition to the large number of variables involved, an important characteristic of the system is that different processes operate on widely different spatial and temporal scales. For example, changes in plant composition in response to herbivory may not be apparent even after 20 years (Wiegand et al., 1998). However, the response in terms of milk yield to changes in frequency of milking or suckling occurs within hours (Wilde and Peaker, 1990). This may be an important factor affecting the performance of animals that are hand milked in addition to

ARTICLE IN PRESS 704

F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

suckling their young. Because variation in rainfall both between and within years is stochastic and changes in plant species depend on coincidences between many factors, model runs must be replicated before the probability of such changes may be predicted with confidence. For the analyses presented here, two separate but linked models have been developed to simulate processes that operate on two levels and on two widely different time-scales. At the lower level of individual plants and animals, the time step is 0.01 days while at the upper population/ecosystem level the time step is 1 year. A short-term mechanistic model is used to evaluate within-year management decisions in relation to the production of meat and milk and to develop sets of equations and rules for long-term models. The latter are designed to study the effects of different strategies on the sustainability of the ecosystem over years or even decades. The long-term model is also an essential step in identifying factors that operate on the lower level such as the amount and distribution of rainfall within the year, range condition and time of birth or death of animals on the behaviour of the system as a whole. The short-term mechanistic model comprises four sub-models: (1) soil moisture and plant growth; (2) diet selection, intake and digestion; (3) animal energy balance and production; and (4) reproduction and survival. The short-term mechanistic model partitions daily rainfall between runoff, infiltration and deep drainage and also simulates the loss of soil moisture by evaporation and transpiration. Forage production by different plant guilds is modelled in relation to soil moisture and the present potential for growth. Three factors are assumed to influence the animal’s preference for a specific type of plant or part of a plant: relative abundance, ease of harvesting and digestibility. The model combines three mechanisms of food intake regulation: the rate at which the animal is able to eat forage, physical capacity of the digestive system, and, in young animals, their growth potential. The model partitions predicted metabolizable energy intake between maintenance, accretion/depletion of body protein and fat, conceptus growth and milk production. Foetal growth and mammary gland development during pregnancy are represented in some detail as live weight at birth and milk production during the first 2 weeks after birth have a major effect on survival of the newborn. As reproductive and survival rates have a major influence on the long-term productivity of the system, these are modelled in relation to predicted live weight and live weight changes for the different age classes of livestock. Although both goats and sheep are kept in Paulshoek, our model assumes that flocks are comprised of only goats. The short-term mechanistic model is described in detail by Richardson and Hahn (2007a). The long-term model that consists of a set of equations, tables and rules is described by Hahn et al. (2005) and used in Richardson et al. (2005). One advantage of the short-term model when compared with another model of a semiarid shrubland production system (IMAGES, Hacker et al., 1991) is that it can simulate complex vegetation consisting of different guilds of shrubs and annuals having different patterns of growth, responses to soil moisture and preference by grazing animals. In addition, IMAGES uses a time step of 4 months and is not able to simulate the adverse effect of an 8-week delay in the onset of the rainy season on forage growth and the consequent effect on the survival of newborn kids. The Paulshoek model is also much simpler to use and run than the SPUR model described by Foy et al. (1999). SPUR uses a large number or parameters that have to be estimated for each specific ecosystem and the information required for such estimations is not available for Namaqualand.

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

705

3. Application of the short-term model 3.1. Stocking rate, rainfall and productivity relations For runs of the short-term mechanistic model and a single run of the long-term model, the initial conditions for vegetation were 20% cover of woody palatable shrubs (WP), 12% cover of leaf succulent shrubs (Mesembs, ME) and 10% cover of the toxic perennial shrub GA. These plant guild proportions reflect vegetation subjectively judged from our experience in the region to be in a ‘‘standard’’ range condition somewhere between pristine and degraded states of transformation. As the mechanistic model uses plant numbers per hectare instead of percentage cover, the equivalent values used were: WP 5631; ME 1575 and GA 100 plants/ha. Model predictions of live weight up to 200 days of age for single and twin kids born in July 2000 to dams of different sizes agreed well with recorded observations when the stocking rate was set at 0.14 SSU/ha, the recorded stocking rate for that year (Richardson and Hahn, 2007b). These authors also reported that model predictions of reproductive and mortality rates for 2002 and 2003 were close to those of a flock for which data were available provided that realistic assumptions were made for stocking rate and that deaths due to predation are excluded. The mechanistic model shows how the amount and distribution of rainfall within a year and stocking rate affect the productivity of livestock and their survival rate (Fig. 1). For example, both the live weight of breeding females at the end of the year and their survival rate decreases as stocking rates increase. This relation varies between years and is influenced by both the total amount of rainfall and its distribution within the year (Fig. 1). In years of similar total rainfall (e.g. 106.0 vs. 115.6 mm), late rains lead to a substantial

96

96

96

50 Doe liveweight, kg

96

147.6 mm Early rain

95

95

96

96 95 40

115.6 mm Early rain

87

84

85 61

30

106.0 mm Late rain

0

0

0 0

20 0.05

0.10

0.15 0.20 Stocking rate, SSU/ha

0.25

Fig. 1. Three examples of the mechanistic model output showing the effect of rainfall amount and timing and stocking rate on suckling doe live weight and survival to the end of the year. The values immediately above the points are the % survival rates of does. Early rain (440% of the annual total falling between February and May) occurs about 12% of the time in Paulshoek while late rain (440% of the annual total falling between August and November) occurs 16% of the time.

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

706

reduction in live weight and survival of suckling females kidding before the onset of the main rains. At present Paulshoek farmers implement a strategy (variable stocking rate) whereby stocking rates vary between years as a result of reproductive and mortality rates. Most male progeny are sold or slaughtered before 1 year of age and on average about 12.5% of adult females are sold. Livestock numbers predicted by the long-term model when using recorded rainfall data and a variable stocking rate strategy closely track the stock numbers recorded for Paulshoek over the last three decades (Fig. 2). There are, however, discrepancies between years 12 and 25. The observed large increase in stock in year 12 was probably due to the purchase of additional animals following the severe decline in the population between years 8 and 10. The model realistically simulates the timing and magnitude of the observed ‘‘crashes’’ in the livestock population in years 8 and 28. When the model was run using 200 years of rainfall and seasonality data generated randomly from a probability table based on rainfall records from Springbok, it predicts that livestock numbers vary widely between years in a manner similar to the recorded data (Fig. 3). The percentage cover of each plant guild also varies between years. The model showed an abrupt and persistent increase in the percentage cover of GA and a decrease in WP and ME shrubs from year 90. This change reflects a deterioration in range condition (Table 1). All guilds decrease rapidly between years 136 and 154 as a result of several years of low annual rainfall that was accompanied by a severe reduction in the animal population. Subsequently, with the resumption of higher rainfall while stock numbers were relatively low, the vegetation recovered and WP becomes more plentiful than GA with a consequent improvement in range condition. This improvement in range condition would not occur if the rate of increase in animal numbers during recovery had been enhanced by purchase of additional stock. A realistic management strategy is to allow goat numbers to vary between years but to limit them to a maximum number of 1500 adult females and yearlings (hereafter referred to 7000

400

6000

350

Total Goats

250 4000 200 3000 150 Model prediction (L) Recorded Stock (L) Rainfall (R)

2000 1000

1978 106 mm

0 0

Annual Rainfall, mm

300

5000

100 50 0

10

20

30

Years Fig. 2. Recorded rainfall and small stock numbers for Paulshoek, compared with long-term model predictions over 30 years.

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

707

600 RAINSE2

Annual Rainfall, mm

500 400 300 200 100 0 0

20

40

60

80

(a)

100 120 Years

140

160

180

200

8000

22

18

14 4000

10

6 2000

WP (L) ME (L) GA (L) Goats (R)

2 -2 0 (b)

Total Goats

Guild cover, %

6000

20

40

60

80

0 100 120 140 160 180 200 Years

Fig. 3. Long-term model showing: (a) the variation in annual rainfall and (b) variation in plant guild cover and goat numbers using randomly generated annual rainfall and seasonality data (WP ¼ woody palatable shrubs, ME ¼ leaf succulent shrubs (Mesembryanthemaceae); GA ¼ Galenia africana—a toxic perennial shrub). The mean number of goats (adults+kids) over this period is 3560 animals.

as adults) which is the strategy adopted by most commercial farmers on privately owned farms in the region and one in which the upper limit to stock numbers is kept within the stocking rates recommended by the Department of Agriculture (Hoffman et al., 1999). Model output showed that under these circumstances, the relative proportions of the three guilds remained largely unchanged over the period simulated. However, all perennial guilds decreased following a sequence of low rainfall years between years 38 and 45 (Fig. 4). Recovery of vegetation especially WP and ME follows from year 61 onwards. This is due to 470 mm of rain in year 61 combined with low stock numbers following only

ARTICLE IN PRESS 708

F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

Table 1 Rules for determining range condition state on a scale from 1 to 5 given total plant cover (TPC, rows) and the cover of GA as a percentage of total plant cover (GA/TPC %, columns) TPC

o20 20–30 30–40 40–50 450

GA/TPC (%) 0–10

10–25

25–40

40–65

465

3 2 1 1 1

3 3 2 1 1

4 3 2 2 1

4 4 3 3 2

4 4 4 3 3

The states are defined as: good (1), light degradation (2), moderate degradation (3), and severe degradation (4).

70 mm of rain in year 57. This strategy of limiting stock numbers substantially reduced their annual variation and resulted in only one major crash in the animal population during 100 years compared with the very wide fluctuation in animal numbers under the variable strategy (see Figs. 2 and 3). This run used the recorded rainfall data shown in Fig. 2 followed by 70 years of randomly generated rainfall. As a result of the stochastic variation in rainfall, the behaviour of the system varies between runs as well as within runs of the long-term model. Single runs have to be repeated many (usually 1000) times to estimate the averages of the different outputs. These repeated replicates are referred to as ‘‘bulk runs’’. The initial conditions for percentage cover of the different plant guilds for the bulk runs were 14.2, 6.9 and 12.1 for WP, ME and GA, respectively. The estimated averages may be used to examine the effect of different management strategies on both livestock production and rangeland condition. A series of bulk runs have been performed to examine probable effects on average flock size, variability in flock size if different limits (ranging from 500 to no upper limit) on the total number of adult animals allowed on the range are imposed (Fig. 5). The results show that as the limit exceeded 2000 adults, there is little increase in the annual average livestock population largely because of the frequent severe mortality and frequent low reproductive rates that occur as the limit exceeded 2000. The variation between years in the animal population (measured as the CV) increases substantially as the limit increases above about 1500 adults. However, the highest average annual off take (number of animals sold) is achieved when stock numbers are limited to 2000 adults, which is the stocking rate recommended by the Department of Agriculture (Hoffman et al., 1999). Thus, temporal variation in the size of the breeding flock and rate of off take would increase as the limit increases thereby increasing the difficulties of planning and management. 3.2. The long-term effect of stocking rate on rangeland condition The effects of stocking rate on rangeland condition were further investigated. Rules for the definition of range condition are proposed in Table 1 and relate to the amount of total plant cover (TPC) and the ratio of GA to TPC (GA/TPC). The long-term consequences of a stocking rate strategy on range condition may be estimated as the probability of the range being in a specific state at the end of 100 years. Initial conditions are important and a moderately degraded range (State 3) was used for

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

709

500 RAIN Annual Rainfall, mm

400

300

200

100

0 0

10

20

30

40

50

60

70

80

90

100

Years

(a) 26

3200

22

2800

2400 14 2000 10

Total goats

Guild cover (%)

18

1600 6 1200

WP (L) ME (L) GA (L) GOATS (R)

2 -2

800 0

(b)

10

20

30

40

50 60 Years

70

80

90

100

Fig. 4. Variation in (a) rainfall and (b) variation in plant guild cover and number of goats when they are allowed to vary between years but are limited to a maximum of 1500 adults (does and yearlings) (WP ¼ woody palatable shrubs, ME ¼ leaf succulent shrubs (Mesembryanthemaceae); GA ¼ Galenia africana—a toxic perennial shrub). Mean number of goats (adults+kids) over this period is 2644 animals.

the bulk runs simulated here. Under these conditions, the probability of the range being in State 1 (good) after 100 years is 61% when an upper limit of 500 adults is imposed and 24% and 4% when the limits are 1000 and 1500, respectively (Fig. 6). With a limit of 1000 adults the most probable final state is light degradation. As the limit on animal numbers increases the probable final condition of the vegetation deteriorates. If the limit is set at 2000 or more the probability of ending in a moderately degraded state (State 3) exceeds 60%. The range of probable final states reflects the changes, over time, in the cover of different guilds, particularly GA that are contingent on the interaction between rainfall and stock numbers in each year (see Fig. 3).

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

65

Goat numbers and annual offtake

2000

55 1600 45 1200

Offtake (L) Goats (L) Goats CV (R)

800

35 25 15

400

CV (%) of Goat numbers

710

5 -5

0 500 1000 1500 2000 2500 3000 3500 Var Upper limit goat numbers (Does + Yearlings)

Fig. 5. The effect of limiting adult goat numbers on average annual flock size, annual variation (measured as coefficient of variation, %) in flock size and on annual off take over 100 years. Var on the X-axis means that there is no upper limit to stock numbers.

3.3. Management responses to drought Recorded data and model output (see Figs. 2 and 3) show that droughts in Namaqualand impact heavily on the livestock industry especially in the communal areas. Interventions aimed at limiting the impact of drought, both in the drought year and during the subsequent 5 years were investigated. First, the number of animals on the rangeland may be reduced. Second, newborns may be slaughtered to reduce the energy expenditure of lactating females and enhance their chances of survival and of re-conception in the following year. The mechanistic model was used to simulate the effects of stock reduction using the recorded rainfall for a year when the annual rainfall was 106 mm and only 36 mm had been recorded by July 1. The model predicts that the live weight of adult females at the end of the year and survival to that date both increased as the stocking rate after July 1 was reduced (Fig. 7). Stocking rate during the second half of the year also has an impact on the vegetation. The predicted density of edible material of WP at year end is 19.2; 14.3; 9.2 and 7.1 kg/ha when stocked at 0.025, 0.050, 0.075 and 0.1 SSU/ha, respectively. Slaughtering the young shortly after birth reduces the energy expenditure of their dams and the magnitude of their weight losses (Fig. 8). As a result the model predicts a substantial increase in the proportion of adult females that survived until the end of the year. If suckling females die then their kids would also almost certainly die. The does whose kids are slaughtered would be more likely to re-conceive in the following year as they will be almost 10 kg heavier than those that rear twins. One thousand replicates of the long-term model long term were used to examine the effect of flock size when the effects of drought become apparent on July 1 and slaughtering kids at that time (Fig. 9). Mean goat numbers over 5 years were predicted to reach a maximum if the stocking rate is reduced to 0.05 SSU/ha (1000 goats) at the beginning of the drought and no other measures are taken (Fig. 9). However, if the kids were slaughtered shortly after birth then the maximum mean population was achieved when the

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

711

70 Limit No. of Adult Goats

Probability of final state (%)

60

500 1000

50

1500 2000

40

Variable 30 20 10 0 1

2 3 Final range condition state

4

Fig. 6. The effect of limiting adult goat numbers on final rangeland state after 100 years of grazing. The states are defined as good (1), light degradation (2), moderate degradation (3), severe degradation (4), functionally irreversible degradation (5). Starting conditions are for moderately degraded rangeland (State 3). Variable means that there is no upper limit to the number of adults.

58 54

Doe liveweight (kg)

50 46

Doe survival rate

Stocking rate after July 1, SSU/ha

42 38

0.94 0.89

0.100

34

0.38

0.050 Parturition

0.025

30

0.00

0.075 26 0

4

8

12

16

20

24 28 32 36 Week in year

40

44

48

52

Fig. 7. The effect of a reduction in stocking rate on July 1 on doe live weight and survival until 31 December of the same year. The initial stocking rate was set at 0.1 adult goats/ha which is the value recommended by the Department of Agriculture for the area.

stocking rate was 0.075 SSU/ha (1500 goats) at the start of the drought. This is probably because conception rates in the year after the drought are high as adult females that do not rear kids are substantially heavier and more fertile at the start of the next breeding season

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

712

58 Rear twins 54

Kids Slaughtered

Doe liveweight, kg

50 Doe survival rate 46 42

O.96

38 Birth 34 0.37 30 2

4

6

8

10

12

14 16 18 20 Week in year

22

24

26

28

30

Fig. 8. The effect of rearing twins or slaughtering them on doe live weight and survival. The stocking rate was set at 0.1 adult goats/ha prior to July 1 and 0.075 adults/ha after that date. Annual rainfall for this simulation was 106 mm.

than those that rear kids. The final mean numbers for both strategies were slightly higher than the averages over 5 years indicating that stock numbers continued to increase over the period. 3.4. Possible effects of climate change Since Namaqualand might be subject to a reduction in annual rainfall as a result of climate change (Midgely et al., 2001), a single run of the long-term model is used to examine the effect of a 10% decline in mean annual rainfall, but with the same pattern of variability. Goat numbers and the cover of all perennial guilds vary more widely than when the model is run using the recorded average and variability (compare Fig. 10 with Fig. 3). Both ME and GA are almost driven to extinction three times during the 200 years simulation, but they recover when stock numbers are very low. From year 100 onwards ME cover is always less than that of GA. The predicted average number of animals over 200 years (2329) is 35% less than the average number predicted for the recorded rainfall pattern (3560). 4. Discussion The models illustrate the ways in which the ecosystem and associated livestock may have adapted to this highly variable environment. Palatable guilds such as WP have apparently survived because periodical severe reduction in animal numbers during a drought is followed by slow recovery of the livestock population that enables WP cover to increase before herbivory again adversely affects it (Figs. 3 and 4). Model predictions may be used

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

713

1800 1600

Number of adults + yearlings

1400 1200 1000 800

Annual mean Kids reared Final mean Kids reared Annual mean Kids slaughtered Final mean kids slaughtered

600 400 200 0 500

750 900 1000 1200 1500 2000 Number of adults at the start of the drought

2500

3000

Fig. 9. The effect of adult goat numbers and the rearing of kids on July 1 at the start of a drought year (o75 mm of rain in total) on flock size over the subsequent 5 years.

in a decision support system to predict the probable consequences of different management strategies. The latter depend on the goals and objectives of the pastoralists and those concerned with land-use policy. The objectives of pastoralists in order of importance are avoidance of risk, maximising return per unit of scarce resources (livestock, labour forage and water) and conservation of resources (Perrier, 1995). There is a belief that small flocks may not survive during droughts and their owners may be forced out of livestock production. This is the motivation to maintain large flocks and herds. The model shows that in Namaqualand this belief is mistaken since there is virtually no increase in average livestock numbers if the limit to the number of adults in Paulshoek is increased above 2000 (0.1/ha). This is because the long-term average number of stock increases only marginally if the limit is increased beyond 2000 because the variation in numbers between years increases (Fig. 5). This increase in variability would increase the difficulties of planning and management. However, the model also shows that increasing the upper limit of adult goat numbers above 2000 adults has little effect on the probable final state of the vegetation. This behaviour of the system only occurs if no measures are taken to limit mortality due to drought (Richardson et al., 2005) or to purchase additional animals following a drought. The stocking rates recommended by the Department of Agriculture are apparently derived from a relation between estimates of long-term average carrying capacity and mean annual rainfall (van den Berg, 1983; Jonas, 2004). The recommended stocking rate can be interpreted in different ways. Firstly, it can be interpreted as a constant number of animals that can be kept on the range. This implies that if severe mortality occurs the range will be restocked to the recommended rate in the subsequent year. Secondly, the

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

20

7000

WP (L) ME (L)

Cover of each guild (%)

6000

GA (L)

16

Goats (R)

5000 4000

12

3000 8

2000

Total goats

714

1000 4 0 0 0

20

40

60

80

100 120 Years

140

160

180

-1000 200

Fig. 10. Long-term model showing the variation on plant guild cover and goat numbers using randomly generated annual rainfall and seasonality data but with a 10% reduction in mean annual rainfall compared with the standard rainfall pattern. (WP ¼ woody palatable shrubs, ME ¼ leaf succulent shrubs (Mesembryanthemaceae); GA ¼ Galenia africana—a toxic perennial shrub). The mean number of goats over this period is 2329 animals.

recommended stocking rate can be interpreted as an upper limit to animal numbers that are otherwise allowed to vary in response to the availability of forage. Model output shows that implementation of these different interpretations can have different effects on vegetation condition. Long-term productivity of the system, measured as average off take of animals over 100 years, is maximal if livestock numbers are variable but limited to 2000 adults. Furthermore, Richardson et al. (2005) showed that implementation of this strategy resulted in only one major crash in 100 years compared with the two in 30 years that were recorded when no limit to animal numbers was imposed (Fig. 1). Over 100 years the average number of goats is 3174 with this strategy which is equivalent to 2006 SSU which is the Department of Agriculture’s recommendation (Hoffman et al., 1999). However, there are two major disadvantages to this policy. Firstly, the CV in animal numbers is 27.4% which makes planning and management difficult to achieve. Secondly, there is a 62.5% probability that the state of the vegetation after 100 years will be moderately degraded and only a 28% probability of it being lightly degraded. Using single runs of the long-term model Richardson et al. (2005) also showed that if stock numbers are held constant at the recommended stocking rate (2000 SSU), range condition deteriorates with GA eventually becoming the dominant guild. Thus the model indicates that WP cannot survive continuous severe defoliation during droughts and the subsequent recovery period when the WP population is low even when the stocking rate is that recommended by the Department of Agriculture. Observations in an arid region of Namibia support these ideas, where plant cover and species diversity as well as grass availability on communal rangeland and commercial ranches are similar. Although commercial ranches impose lower stocking rates than communal areas they sustain

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

715

pressure on the vegetation during the post-drought recovery period by supplementary feeding and purchase of additional animals while numbers recover slowly on communal rangeland (Ward et al., 1998). Imposing a limit of 1500 adult goats reduces to 55% the probability that the final state of the rangeland at Paulshoek will be moderately degraded. This does not indicate a change in guild composition of the vegetation, but reflects a low value for total perennial cover. Inspection of Fig. 4 shows that at this stocking rate, the cover of all guilds varies widely but in a similar manner in response to the variability in rainfall between years, but there is no progressive decline. Compare this with the case when the variable stocking rate strategy was imposed and no upper limit was placed on stock numbers (Fig. 3). Under these conditions there were periods of several years when GA was the dominant guild, before WP once more became the most plentiful guild. This is consistent with the analyses of Hoffman and Cowling (1990) which showed that over many decades Karoo vegetation has become degraded and then recovered. A further advantage of stocking at 1500 adults is that while annual off take is only marginally reduced below the maximum achieved when the limit is 2000 adults, the CV in annual goat numbers declines to 10.2%. This would lead to a reduction in risk and an increase in household security. The average total number of animals of all ages is then 2644 and the average number of SSU is reduced to 1659. Hoffman (1988) analysed a large body of experimental data and historical records. He concluded that the then Karoo range management systems (continuous grazing, group camp system, non-selective grazing, and short duration grazing) were based on deterministic views of how the ecosystem functions and ignored the stochastic variation in soil moisture characteristic of the region. The rationale for these systems is based on the assumed effects of defoliation at different phases of the growth cycle, within years, on plant growth, seed production and seedling survival. They ignore the interactions between weather, livestock numbers and the state of the rangeland that vary widely between years and have a major impact on the productivity of livestock and vegetation. The model described by Hahn et al. (2005) that was used in the analyses reported in this paper provides a theory of long-term semi-arid rangeland dynamics that accounts for climatic variability and is able to predict population fluctuations of both plants and livestock. Hoffman (1988) suggested that such a theory would be required before appropriate grazing management systems can be developed for the Karoo. Output from this model indicates that a management system that allows for small stock numbers to vary between years in response to rainfall but with an upper limit of 1500 adults (0.075 adults/ha) would ensure sustainability of both livestock production and the vegetation. The survival of the livestock population depends on the survival of adult females. The models show that this may be enhanced during a drought by reducing the number of animals if the recorded rainfall by July 1 is less than 50 mm. More adult females may be retained if the kids or lambs are slaughtered shortly after birth. This indicates that Karakul pelt production would be a suitable production system if droughts as severe as that simulated in Figs. 1, 7 and 8 occur frequently. Karakul pelt production is recommended for regions where the mean annual rainfall is 200 mm or less, provided that genotypes capable of producing high quality pelts are used (Wilson, 1995). This production system would reduce the risk of pastoralism in this area. The model predicts that a 10% decrease in mean annual rainfall would lead to a substantial decrease in the long-term average in stock numbers but this assumes that the pattern of variation is unchanged. The model also assumes that a change in mean annual

ARTICLE IN PRESS 716

F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

rainfall is not accompanied by changes in temperature and in wind. Long-term consistent changes in the weather may lead to changes in the species composition of vegetation in addition to any changes predicted by the model. A major weakness of the present models is that variation in vegetation over space is ignored. At high stocking rates during a year of low late rainfall (such as 106 mm in Fig. 1) more animals may survive than predicted by the model. This would occur if some of them have access to parts of the landscape (e.g. the rocky uplands) where the yield of edible plant material is higher than the average predicted for the area simulated (DeAngelis and Waterhouse, 1987; Illius and O’Connor, 1999). Acknowledgements This paper is dedicated to the memory of our colleague and friend Brian Hahn. We thank the National Research Foundation and the University of Cape Town for financial assistance. This paper uses data from the MAPOSDA research project funded by the European Commission under INCO-DC: International Cooperation with Development Countries (2000–2004), Contract no. ERBIC18CT970162 and by BIOTA Southern Africa, sponsored by the German Federal Ministry of Education and Research under promotion no. 01 LC 0024A. The support of the Paulshoek community is also gratefully acknowledged. The Mazda Wildlife Fund is thanked for the use of a courtesy vehicle during fieldwork for the collection of data. References Baker, L.E., Hoffman, M.T., 2006. Managing variability: Herding strategies in communal rangelands of semi-arid Namaqualand, South Africa. Human Ecology 34 (6), 765–784. Biot, Y., 1993. How long can high stocking densities be sustained? In: Behnke, R.H., Scoones, I., Kerven, C. (Eds.), Range Ecology at Disequilibrium. Overseas Development Institute, London. Cowling, R.M., Pierce, S.M., 1999. Namaqualand: A Succulent Desert. Fernwood Press, Cape Town. DeAngelis, D.L., Waterhouse, J.C., 1987. Equilibrium and nonequilibrium concepts in ecological models. Ecological Monographs 57, 1–21. Ellis, J.E., 1995. Climate variability and complex ecosystem dynamics: implications for pastoral development. In: Scoones, I. (Ed.), Living with Uncertainty. Intermediate Technology Publications, London, pp. 37–46. Foy, J.K., Teague, W.R., Hanson, J.D., 1999. Evaluation of the upgraded SPUR model (SPUR 2.4). Ecological Modelling 118, 149–165. Hacker, R.B., Wang, K.M., Richmond, G.S., Lindner, R.K., 1991. IMAGES: an integrated model of an arid grazing ecological system. Agricultural Systems 37, 119–163. Hahn, B.D., Richardson, F.D., Hoffman, M.T., Roberts, R., Todd, S.W., Carrick, P., 2005. A simulation model of long-term climate, livestock and vegetation interactions on communal rangelands in the semi-arid Succulent Karoo, Namaqualand, South Africa. Ecological Modelling 183, 211–230. Hoffman, M.T., 1988. Rationale for Karoo grazing systems: criticisms and research implications. South African Journal of Science 84, 556–559. Hoffman, M.T., Cowling, R.M., 1990. Vegetation change in the semi-arid eastern Karoo over the last 200 years: an expanding Karoo—fact or fiction. South African Journal of Science 86, 286–294. Hoffman, M.T., Cousins, B., Meyer, T., Petersen, A., Hendricks, H., 1999. Historical and contemporary land use and the desertification of the Karoo. In: Dean, W.R.J., Milton, S.J. (Eds.), The Karoo: Ecological Patterns and Processes. Cambridge University Press, Cambridge, pp. 257–273. Illius, A.W., O’Connor, T.G., 1999. On the relevance of nonequilibrium concepts to arid and semiarid grazing systems. Ecological Applications 9, 798–813. Jonas, Z., 2004. Land use and its impact on the Succulent Karoo. Unpublished M.Sc. Thesis, University of Cape Town, Cape Town.

ARTICLE IN PRESS F.D. Richardson et al. / Journal of Arid Environments 70 (2007) 701–717

717

Midgely, G.F., Rutherford, M., Bond, W., 2001. The Heat is on: Impacts of Climate Change on Plant Diversity in South Africa. National Botanical Institute, Claremont, South Africa. Perrier, G., 1995. New directions in range management planning. In: Scoones, I. (Ed.), Living with Uncertainty. Intermediate Technology Publications, London, pp. 47–57. Richardson, F.D., Hahn, B.D., 2007a. A mechanistic model to simulate within years the effects of rainfall, stocking rate and range condition on the productivity of forage and livestock in the semi-arid Succulent Karoo: 1. Description of the model and sensitivity analyses. Agricultural Systems, revised paper resubmitted for publication. Richardson, F.D., Hahn, B.D., 2007b. A mechanistic model to simulate within years the effects of rainfall, stocking rate and range condition on the productivity of forage and livestock in the semi-arid Succulent Karoo: 2. Evaluation and application. Agricultural Systems, revised paper resubmitted for publication. Richardson, F.D., Hahn, B.D., Hoffman, M.T., 2005. On the dynamics of grazing systems in the semi-arid succulent Karoo: the relevance of equilibrium and non-equilibrium concepts to the sustainability of semi-arid pastoral systems. Ecological Modelling 187, 491–512. Thornley, J.H.M., 1998. Grassland Dynamics: An Ecosystem Simulation Model. CAB International, Wallingford, Oxon. Todd, S.W., Hoffman, M.T., 1999. A fence line contrast reveals effects of heavy grazing on plant species diversity and community composition in Namaqualand, South Africa. Plant Ecology 142, 169–178. van den Berg, J.A., 1983. The relationship between long-term average rainfall and the grazing capacity of natural veld in the dry areas of South Africa. Proceedings of the Grassland Society of South Africa 18, 165–167. Ward, D., Ngairorue, B.T., Kathena, J., Samuels, R., Ofran, Y., 1998. Land degradation is not a necessary outcome of communal pastoralism in arid Namibia. Journal of Arid Environments 40, 357–371. Wiegand, T., Jeltsch, F., Bauer, S., Kellner, K., 1998. Simulation models for semi-arid rangelands of southern africa. African Journal of Range and Forage Science 15, 48–60. Wilde, C.J., Peaker, M., 1990. Autocrine control in milk production. Journal of Agricultural Science, Cambridge 114, 235–238. Wilson, R.T., 1995. Livestock Production Systems. The Tropical Agriculturalist Series. Macmillan Education Ltd, London and Basingstoke. Wyn-Jones, R.G., Young, E.M., Hoffman, M.T., Magole, L., Petersen, A., Arntzen, J., Majoro, M., 1998. Global change and subsistence rangelands in Southern Africa, an outline of a European Union funded project. In: de Bruyn, T.D., Scogings, P.F. (Eds.), Communal Rangelands in Southern Africa: A Synthesis of Knowledge. Department of Livestock and Pasture Science, University of Fort Hare.