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Herbaceous forage variability in an arid pastoral region of Kenya: importance of topographic and rainfall gradients
Journalof Arid Environments (1990) 19, 147-159
Herbaceous forage variability in an arid pastoral region of Kenya: importance of topographic and rainfall gradients M. B. Coughenour,*t D. L. Coppock* & J. E. Ellis* Accepted 12 September 1989 Temporal and spatial variabilities in rainfall, herbaceous production and biomass were studied over a 4-year period in a topographically diverse, arid pastoral region of northwest Kenya. A significant relation between rainfall and primary production was found, and this was applied in a manner that considered topographic variation and its influence on rainfall variation over the region. Primary production responses to rainfall occurred as pulses that were rapidly attenuated as the dry seasons progressed. The combination of spatial and temporal variability of herbaceous forage is significant for nomadic pastoralists who move along rainfall gradients between wet and dry seasons. Dry areas at low elevations produce forage that is available for only a short period of time, which explains pastoral use of drier areas early in the wet season. Quantitative analyses of relationships between topography, rainfall and forage are needed to determine appropriate pastoral densities in topographically diverse arid regions.
Introduction
Spatial and temporal forage availability is particularly important for migratory or nomadic herbivores or pastoralists in arid regions. These foragers try to buffer unpredictability and use spatial variance advantageously through movement. For example, nomadic pastoralists of the southern part of Turkana District in northwest Kenya exploit over 8000 km 2 of mostly arid ecosystem by moving autonomous households up to 15 times per year (McCabe, 1983; McCabe & Ellis, 1987). Livestock (cattle, camels, goats and sheep) are herded over large areas on an opportunistic basis and movement decisions are largely based on seasonal and spatial distributions of available forage (Coppock, Ellis etal. 1986, 1988). Approximately 36% of human food originates from herbaceous plants, primarily through a herbaceous-eattle-milk energy flow pathway (Galvin, 1985; Coughenour, Ellis et al., 1985). Satellite imagery of the Turkana District suggested a wide range of vegetation production potentials at different locations (Ellis & Dick, 1985) as a result of spatial variation in rainfall, soils and previous use. Mean annual rainfall in the region varies threeto fourfold over tens of kilometers, soils vary from sand to lava, and grazing intensity and burning frequency are unevenly distributed. Quantitative measures of forage production are needed to determine appropriate or adaptive human and livestock population densities in such areas (e.g., Coe, Cumming et al., 1976; Kalff, Downing etal., 1985). However, the most directand reliable methods for estimating primary production demand large investments of time and resources which • Natural Resource Ecology Laboratory, Colorado StateUniversity, Fort Collins, Colorado 80523, U.S.A. tCurrent address: International Livestock Centerfor Africa, P.O. Box 5689, AddisAbaba, Ethiopia.
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M. B. COUGHENOUR ET AL.
makes them difficult to implement over large areas. While the most common method requires sampling large numbers of small quadrats on relatively restricted sampling areas, these site level studies can often be extrapolated to larger areas (e.g., Sala, Parton et aI., 1988). It is advantageous for pastoralists to know when and where growth is occurring, because temporal variability of forage in arid environments can be extreme. Herbaceous biomass and nutrients often become available in a short temporal pulse of a brief rainy season (NoyMeir, 1973). Annual plants may be short lived and nutritious green tissues may senesce rapidly. Pulses of rainfall and herbaceous production are not necessarily uniformly distributed over the region. Our goal here is to predict spatial-temporal patterns of herbaceous productivity in the southern Turkana region of Kenya (8400 knr'), and discuss the significance of this variability for the pastoralists. We will generate a regional distribution of herbaceous production from knowledge of plant responses, rainfall and rainfall distributions. We propose that regional predictions can be enhanced by combining elevation and digitized regional topography data.
Study area Study sites were located in the area of the Ngisonyoka subsection of the Turkana tribe (Fig. 1). The Ngisonyoka area is approximately 70 km south west of Lake Turkana and is entirely within the low-lying Rift Valley (500-2000 m altitude). Rift highlands rise only tens of kilometers from the south and west boundaries. A Pre-Cambrian basementcomplex mountain range bisects the area. Sandy piedmont alluvial fans and plains are dissected by numerous ephemeral streams and washes that flow after large storms. These streams are typically lined with large Acacia tortilis trees. Much of the eastern half of the area is covered with weathered Miocene lava, as gravelly plains and hills that have a thin mantle of gravelly-loam soil (Sombroek, Braun et at., 1982; Hemming & Trapnell, 1957). The area encompasses both arid (300-550 mm rainfall) and very arid (150-350 mm) ecoclimate zones (Sombroek, Braun etal., 1982). Mean annual rainfall at weather stations in the area varies from 201 to 394 mm/year, while annual potential Penman evapotranspiration is 2200-2700 mm1year. A period of 'long' rains usually occurs in March-May, while 'short' rains occur around November. However, seasonal patterns are relatively weak. Often 9-11 months pass without significant rainfall. Mean daily temperature is about 30°C and mean maximum is about 35°Cwith little seasonal variation (Little & Johnson, 1984). The characteristic vegetation of the arid zone is dry thorn-bushland, while dwarf-shrub grassland is the most widespread vegetation of the very arid zone (Pratt & Gwynne, 1977). Annual herbaceous species are predominant in areas receiving less than 300 mm annual rainfall, while perennial species are increasingly important in less arid areas. Several physiognomic vegetation types are found in this region, including sparse bush grassland, dwarf shrub grassland, bushed grassland, wooded grassland, bush, woodland, and riparian forest (Ellis & Coppock, 1984; Ellis & Dick, 1985). Woody canopy cover ranges from 2 to 100%, but most area is 10 to 40% covered (Coughenour, Ellis et al., 1985; Ecosystems Ltd., 1983/84). Aristida mutabilis and Eragrostis spp., annual grasses are dominant on unshaded sites. In shaded habitats, the annual grasses Brachiaria Ieersiodies, Dactyloctenium aegyptium and Digitaria oelutina predominate. Numerous annual forb species are present, particularly in unshaded habitats. The perennials Cenchrus ciliaris and Kyllingia welwitschii occur in certain areas, but the most important perennial grasses where rainfall is less than 450 mm are A. adscensionis and Leptothrium senegalense. Perennial Cyperus spp. and S porobolus spp. are very important where rainfall exceeds 450 mm at lower elevations. A more complete list of South Turkana plant species was compiled by Morgan (1981).
HERBACEOUS PRODUCTION IN NORTHWEST KENYA
149
36°E
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t-----4
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Figure 1. The South Turkana study area showing locations of study sites and rainfall recording (squares), other temporary rainfall recording sites (triangles) and villages with permanent rainfall recording (stars). Elevation contours are shown in metres above sea level.
Methods
Herbaceous vegetation Herbaceous biomass was determined in 1981-82 (Coppock, 1985) by clipping 0'25-m 2 rectangular (0' 25 m x 1 m) quadrats located in a stratified random manner along a series of parallel transects at five sites. On each date and site 20 quadrats were clipped in each of two replicate areas. At three sites four quadrats were clipped beneath each of five randomly selected large trees growing along dry streambeds. On average, quadrats at a site were located within 7 ha. Stream terrace quadrats were typically spread over 4 ha. Clipped samples were taken on four dates, from the late wet season in 1981through two dry season samples and a late wet season sample in 1982. Green versus non-green cover and species cover were ocularly estimated within 30 Q'1-m2 quadrats located in a stratified random manner over 0·5 ha at each of three sites. In 1983 we constructed 22 thorn-fence grazing exclosures (10 m diameter) to prevent herbivory by pastoral livestock or other large herbivores. These exclosures were placed non-randomly due to their small number and area. Exclosures were located on relatively uniform stands of herbaceous vegetation which sometimes had less than the average amount of ground covered with patches of bare soil. At three sites two exclosures were
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M. B. COUGHENOUR ET AL.
placed on a sunlit interdrainage and two were placed in the shade of large trees on the stream terrace. At two sites one exclosure was placed on the interdrainage and one in the shade. At three sites there were only two exclosures, both in non-shaded areas. At one remote site in the mountains exclosures were unnecessary. On each date four 0'25-m 2 quadrats were clipped inside, and four outside of each exclosure. At the Mountain site eight quadrats were clipped. Larger quadrats (l m x 1 m) were used at three sites (Kalimnarok, Kadangoiy, Mountain) where perennial bunch grasses prevailed. Live and dead shoots were separated in the field. Poor rainfall and grass growth in 1984 warranted only a minor sampling effort. Graminoids were clipped from eight 0'25-m 2 quadrats within each of five exclosures (two sites) in late April at or near the time of peak standing crop. At two additional exclosures biomass was clipped directly on patches of perennial bunchgrass to estimate maximal biomass concentration in small areas. In late August standing-dead biomas was sampled at four sites (six exclosures) where a grazing exclosure effect was visibly apparent. Four quadrats were clipped inside and four outside each exclosure. There was zero green biomass on those sites at that time. Cover was estimated at these sites on 16quadrats inside and 20 outside of each exclosure to derive a relationship between standing-dead cover and biomass. Herbaceous aboveground net primary production (ANPP) was calculated from positive increments in live-plus-dead or live biomass since the beginning of a growth period. Cumulative ANPPs for the periods between March and May 1981, April and June 1982, Dates 1-2 1983, Dates 1-31983, and Dates 1-41983 were regressed on cumulative rainfall over the respective periods from the beginning of the wet season. Rainfall was recorded from mid to late May through November in 1983and 1984. Seven sites were monitored in 1983 and although 18 sites were established in 1984, only nine provided continuous data due to human interference. Gauges were read every 1-4 weeks. Additional monthly rainfall data for 1981-1987 were obtained from several permanent weather stations in the study area. A regression analysis of rainfall on elevation was performed for each year (Table 1). Terrain data for the region were encoded in a digital elevation model (OEM) with 40 m elevational resolution. The known weather station data for a particular year were entered into an algorithm that interpolated rainfall as follows. For each unknown point, elevation was computed from the OEM. Three estimates of rainfall were generated from observed rainfall at the three nearest weather stations, the rainfall-elevation relation and the elevation difference between the station and the unknown point. These estimates were weighted by the inverse cubic distance to each of the stations to arrive at a final estimate for the unknown point. The final set of points was then spatially interpolated by inverse distance weighting to give a regular grid and this regular grid was contoured to generate a rainfall map for the year. Yearly maps from 19821987 were averaged to derive a mean annual rainfall map. Results A relatively dry period that began in late 1979 was broken by rains in late March and early April 1981. From June 1980 through February 1981 an average of6 rom was recorded. In 1981 and 1982 the long rains were very favorable with 130 mm/month in March and April and 65 mm in May of 1981,80 mm/month in April and May ofl982 (mean rainfall over five permanent weather stations). In November 1982 110 mm fell, but field work ceased between June and April. Prior to the rains in 1981, live or dead herbaceous biomass or litter were virtually absent. The March-April rains provided a large pulse of herbaceous productivity by June (Fig. 2). Resultant standing biomass was greater in the shade of large trees growing along ephemeral streambeds than on sunlit interdrainages. Production was also greater at more south-western sites (Kadangoiy and Lobokot), Biomass at Lokosimaekori was low,
lSI
HERBACEOUS PRODUCTION IN NORTHWEST KENYA 400,------------------------------, N
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4
5
6
7
8
10
9
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12
2
3
4
5
6
82
81 Month/yeor
Figure 2. Dynamics of total standing biomass at sites sampled in 1981 and 1982. Each point based on
n = 40 O:25 m 2 plots except at Kadangoiy (n = 20) and Lobokot (n = 60) and shaded sites (n = 20).
Green cover constituted 100%,22%,32% and 100% of total cover in sunlit sites in the four respective dates. , Lokosimaekori; --t-, Katamanack; -0-, Katapadwell; ---B--, Kadangoi; ~,Lobokot; ···0..·, Lokos. shade; ....6· .. , Katam. shade; ·· ..x.... , Katap, shade.
Table 1. Regressions ofprecipitation (mm) on elevation (m) byyear. The periods 4/83-11/83 and 4/84-11/84 included datafrom temporary raingauges Period
N
r
p
Intercept mm
Slopemm/m
4/83-11/83 4/84-11/84
12 14
0'33 0'33
0'05 0·03
-347 -16
0·85 0'15
1979 1980 1981 1982 1983 1984 1985 1986 1987
6 5 6 7 6 6 7 10 10
0'81 0'46 0'84 0'40 0'31 0·32 0'77 0'87 0'66
0'01 0'20 0·01 0'12 0'25 0·24 0'01 <0'001 0'004
-246 -202 -538 -276 -279 -39 -352 -113 -148
0'98 0'63 1·35 1'00 0'80 0'27 0·99 0·58 0'72
probably due to livestock grazing as considerable numbers of pastoralists were in the area at that time. At Lobokot, standing crop was higher in the open area than in heavy bush. Over the subsequent 5 months most of the standing biomass was either grazed, transferred to litter or lost to weathering. Litter biomass increased from 0 in March to 2-12 g1m2 in June; 3,20,25, and 60 g/m2 were recorded at Lokosimaekori, Lobokot, Katamanock, and Katapadwell in November, which were only small proportions of total productivities. The rains of April-May 1982 yielded less. Again, biomass was greater in shade and in the south-west, and Lokosimaekori had abnormally low values. Litter biomass decreased from 40, 20, 2 and 2 g1m2 in March to 25, 0, 0 and 0 g1m2 in June at KatapadweU, Katamanak, Lobokot, and Lokosimaekori, respectively. Most or all of this litter biomass was produced in 1981 and most of the April-May 1982 production was still alive in June. The rains of 1983 were unusual in that an average of 30 mm/month occurred over the entire interval of May-October with significant falling in the typical dry season of JuneAugust; but there was no 'good' rainy season. On all dates, there was no significant differences in biomass (p > 0'05) inside versus outside exclosures except in September at Katamanak (Table 2). Human and livestock occupancy in these areas was extremely low in
sun shade
sun shade
sun shade
0 0 2 2 2
1 1
1 1
2 2
2 2
2 2
Exclosures
56 ± 17 157 ± 96 87 ± 39
51 ± 28 32 ± 13
90 ± 31* 41 ± 23
50 ± 13* 20 ± 15
43 ± 21* 0
(g/rrr')
15 0 24
1 22
7 38
1 98
0 0
(% Live) )
57 ± 26 48 ± 16 64 ± 22 82 ± 43 126 ± 33
59 ± 17 54 ± 18
35 ± 16 133 ± 67
79 ± 30 79 ± 27
70 ± 24* 83 ± 28
8 ± 6' 0
(g/m
2
79 75 31 60 89
35 74
46 46
59 98
100 0
(% Live)
May-June
90 ± 35 158 ± 48
39 ± 16 79 ± 48
16 ± 8 15 ± 6
17 ± 11 34 ± 19
0 0
(g/m")
t Significant grazing exclosure effect; exclosure x =
69 70
100 100
100 100
100 100
0 0
(% Live)
July
*Significant difference between sun and shade (p 5 0·05). 46 ± 17, unprotected x = 78 ± 26 g/nr'.
sun shade Katamanak lava sun Kalimnarok sun Kadangoiy sun
Open Subcanopy
Mountainsite
Interdrainage Stream terrace
Ngatagoi footslope
Interdrainage Stream terrace
sun shade
sun shade
Kanaiiki footslope
Interdrainage Stream terrace
Katapaduiell
Interdrainage Stream terrace
Lokosimaekori
Interdrainage Stream terrace
Northern site
Site
April-May
48 ± 183 ± 62 ± 214 ± 173 ±
44* 169 21+ 87 43
134 ± 52 99 ± 28
78 ± 40 65 ± 41
147 ± 113 91 ± 37
117 ± 52 101 ± 35
68 ± 25 48 ± 23
(g/m")
70
71
92 97 100
100 100
100 63
100 100
100 100
100 99
(% Live)
September-October
--
Table 2. Herbaceous aboveground biomass (mean ± standard deviation g/m2 ) andpercent of biomass alivein 1983. n = 8 quadrats/exclosure
r-
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o 0 c:::
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HERBACEOUS PRODUCTION IN NORTHWEST KENYA
153
Table 3. Biomass (g/m2 ) and cover (%) in 1984. April-May biomass was from within exclosures only. All biomass in August-September was dead. An additional nine exclosures had essentially zero standing live or dead biomass then. Each number representsn = 8 O'25 m 2 quadrats
August-September
April-May Enclosures Site
n
Katapadwell Kadangoiy Lokosimaekori Ngatatoi Katamanak E. Katamanak W.
2 3 1 1
1
1
Live biomass
Cover
Biomass Dead biomass
In
0·9 ± 0·8 1-6 ± 1·2 5·7 ± 2,5* 5'5 ± 16'4 2·4 ± 5·5 10'6 ± 13-3t 15·6 ± 15,6* 13'4 ± 9'0* 5'6 ± Nt
Out
In
Out
3·7 ± 3·4 5·0 ± 3,7* 2·2 ± 3·7 1-3 ± 1'3 3·2 ± 3'1 4'0 ± 2'7 3'7 ± z-z
5-4 ± 6'8t 7·7 ± 5,8* 7'4 ± 4'3* 2'3 ± 2'4
0'7 ± 0'7 1'4 ± 1·7 1'4 ± 1'7 1'1 ± 0'8
* Significant exclosure effect p < 0'05. [ Significant exclosure effect p < 0'01.
1983. Total biomass in shaded habitats was not consistently greater than in unshaded habitats, but there was usually more green biomass in shade. Sites farther south and west were more productive, though this gradient was much less pronounced than in 1981-82. Total biomass remained constant but green biomass declined through May and June, and grasses were much greener in shade during that period. There was considerable decline in both live and standing dead through July, though rains at some sites promoted additional growth. Late August rains produced a large growth pulse at all sites. Litter biomass of 1983 was collected only in April-May. There was 0 g/m2 at N. site, 35 at Lokosimaekori, 63 at Katapadwell, 33 at Ngatagoi, 13 at Katamanock, 133 at Kalimnarok, and 28 g/m 2 at Kadangoiy. This litter probably represented part of the production response to the rains of November 1982. The rains of 1984 failed and this year was considered by the Turkana to be one of the 'bad' years that occurs every 4-5 years. Sampling in early May 1983 yielded very little biomass (Table 3). Biomass concentrations on patches of perennial bunchgrass (Leptathrium senegalense) at Katapadwell were 25 g/m 2 (mean) ± 17g/m 2 (stand. dev.) live and 78 ± 48 g/m 2 dead. By early September there was no green biomass and very little dead biomass remaining either inside or outside the grazing exclosures, indicating significant losses due to weathering rather than to grazing. However, standing dead was significantly greater inside all of the samples exclosures. No standing dead was visible in or around nine of the exclosures that were not sampled. At the remaining four unsampled exclosures there were no visible grazing effects and biomasses were visibly similar to those observed at the other sites. A regression analysis showed that dry weight of standing dead in late 1984 was significantly correlated with percent cover as: g/m2 = 14·8 + 2.7 x cover%,';' = 0'77 at Katapadwell, and g/m 2 = 0·8 + 0·033 x cover%,';' = 0·78 at the other sites. There was a significant positive relationship between herbaceous production and rainfall over the 4-year period (Fig. 3). Points representing shaded habitats appeared to lie above the regression line, however there was no significant difference between the means of shaded and unshaded habitats (z-test). At low rainfall (below 200 mm), it appeared that shaded habitats produced more than sunlit, however this difference was also nonsignificant. Rainfall data from 1979-87 were subjected to rainfall-elevation analysis (Fig. 4). In 5 of the 8 years there were significant rainfall-elevation relations (Table 1). These relations varied from year to year. Realistic rainfall maps could be produced only for the years 198287 because of the absence of data from Lokichar station in 1979-81. The Lokichar data
154
M. B. COUGHENOUR ET AL. 400 ,..---------------~-------___,
o
0
300
N
0
E
+
<,
2:
c: 0
+o
200
0
+
:>
-e
e
0 + +
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+ +
100
+
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·0 300
200
100
400
Rainfall (rnm)
Figure 3. Cumulative aboveground net primary production versus cumulative rainfall at sites sampled in the wet seasons of 1981 and 1982, and April-September 1983 (see Table 3). The line indicates y = -20 + 0'71x, ,;. = 0'74, n = 55, P « 0·001. Each point represents a cumulation of current production since onset of rains.•, annual sun; +, annual shade; D, perennial; - - y = -20,0 + 0'7x;';' = 0·74. were critical because this site typically deviates below the rainfall-elevation relationship and because it was the only site in the north-eentral part of the study area. Individual maps from 1982-87 were averaged together to produce a 6-year average rainfall map (Fig. 5). The resultant rainfall map was used in conjunction with the production versus rainfall regression equation to calculate a map of mean annual herbaceous aboveground production for the 6-year period (Fig. 6). Annual herbaceous ANPP derived by this method was 214 ± 124 g/m 2 averaged over the region.
o
0·2
0,3 004 0·5
0·6 0·7 0·8 0·9
1·0
1·1
1·2
OL---'-..L..L--'----'---,---'-----'--
0·3 0'4 05 0·6 07 0·8 0'9
1·0
1'1
1'2
Elevation (1000 m)
Figure 4. Analysis of rainfall versus elevation for the years 1979-1987 employing data from permanent stationsonly. Only significant regressions(P < 0'05) are shownaslines. (a) , 1979; + 1980;-+-.1981; D, 1982;0,1983. (b)., 1984;-+-, 1985;--e-, 1986; "'<)"',1987.
HERBACEOUS PRODUCTION IN NORTHWEST KENYA
155
Annual Rainfall mm (mean 1982-1987)
Figure 5. The distribution of mean annual rainfall (mm) over the study area, obtained as the average of individual distributions for each year 1982-1987.
Discussion
Effects on productivity The linear relationship of accumulated NPP on rainfall (Fig. 3) was very similar in terms of both slope and intercept to analogous relations observed over East Africa as a whole y = -19·6 + 0·85x (Deshmukh, 1984), and the Mediterranean basin y = -41 + 0·87 (Lel-louerou & Hoste, 1977). The regression line fell above a relation for the Sahel-Sudan y = 10·5 + 0·26x (Lel-louerou & Hoste, 1977) due to larger slope and smaller intercept, and above a line for the Serengeti y = -102 + 0·69x (McNaughton, 1985) due to larger slope and intercept. A positive x-intercept is usually observed in such relations and interpreted as the threshold amount of annual rainfall necessary to initiate growth (NoyMeir, 1973; Sala, Parton et al., 1988). The threshold effect was observed in the Turkana regression at about 28 mm. Growth after a dry season has indeed been observed with as little as 20-30 mm rainfall (personal observation, M. B. Coughenour). The slope, or the efficiency with which rainfall is converted to production (RUE) fell well within a range of observations made elsewhere (Lerlouerou, 1984). The slope of the Turkana relation indicates a RUE of 7 kg/mm/ha. The nearest comparable data, for Marsabit District in north-central Kenya (Herlocker & Dolan, 1980; Lamprey & Yusuf, 1981; Lusigi, 1981), indicated a RUE of2·2 to 9·2 for herbaceous vegetation. RUEs of 8-9 occurred in South African (Rutherford, 1978) as well as East African (Deshmukh, 1984) and Mediterranean grasslands (Lel-louerou & Hoste, 1977). A range of 3 to 6 is generally applicable for reasonably managed grasslands (Lelfouerou, 1984).
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M. B. COUGHENOUR ET AL.
Aboveground NPP g/m2 (mean 1982-1987)
Figure 6. The distribution of mean annual aboveground production (g/rrr') over the study area for the years 1982-1987.
Below 300-500 mm rainfall sandy soils such as those covering much of South Turkana have shown a greater potential for primary production than finer-textured soils (NoyMeir, 1973). Very low productivities have been observed on silt and loam soils below 300 mm rainfall in the Sahel, but higher productivities occurred on sandy soils (Bremen, Cisse et aI., 1979/80). In general, sandy soils hold water less tightly so it may be easier for plants to extract water when little is available. At higher availability, finer soils will store more water. The principle of this inverse texture hypothesis could promote higher production on Turkana sandy soils, although the exact thresholds between converse effects of fine and coarse soils will depend upon local evaporation and soil fertility. Nutrient concentrations in sandy soils of Turkana are very low (about 0·04% Nand 6 /J-g extractable PIg soil), but increasing nutrient levels may have little effect on herbaceous RUE because of low rainfall, and small nutrient requirements of C4 annual grasses (Breman, Cisse et al., 1979/80). Thus, while water was more limiting than nutrients below 300 mm rainfall, above 300 mm production was increased five-fold by fertilization (Breman & DeWit, 1983).
Improving spatial predictions These principles suggest that regional predictions from rainfall alone could be enhanced by development of separate NPP-rainfall relations for fine and coarse textured soils (e.g., Sala, Parton et al., 1988) and by development of different curves for rainfalls above and
HERBACEOUS PRODUCTION IN NORTHWEST KENYA
157
below the nutrient limitation threshold. Furthermore, it would be beneficial to document spatial distributions of nutrient limited soils over areas where rainfall is above the threshold. The variance among yearly relationships between elevation and rainfall (Table 1) demonstrates that a single relationship cannot be assumed over all time periods. In general, relations were poorer, and slopes were lower in drier years. We have applied this methodology to generate monthly rainfall maps for the area (Coughenour, unpublished), and have found that regressions must be developed on a monthly basis as well. In general, a regression should be developed from data covering the time period of attempted prediction and spatial interpolation. Prins and Loth (1988) found that relations between elevation and rainfall in Tanzania were generally poorer in the short rainy season and dry season than in the long rainy season. Short rains and dry season rains seemed to be produced by individual convective cells within a larger system, while long rains were generated by large monsoonal systems. Rainfall in dry years and months in Turkana also result from smaller convective systems, so the same lack of elevation effect on convective rainfall may be operating here. Consideration of additional variables would improve predictions of forage response to rainfall. Rain use efficiency is decreased by runoff and infiltration, and throughflow out of thin rocky soils. Distributions of woody canopy cover and explicit consideration of effects on shading and rainfall interception would be profitable. More accurate understanding is needed of elevational effects on rainfall where high elevation areas are small in relation to surrounding lowlands. Consideration of these effects would be facilitated by storing and utilizing topography, soils, woody canopy cover and other data in a geographic information system along with parameters describing forage responses under these differing conditions.
Significance to pastoralists The spatial pattern of NPP in Turkana predicted from rainfall maps displayed an overall south-west to north-east regional gradient. Part of this gradient was due to generally greater elevations in the south-west, however part was unrelated to elevation and appeared to be a result of regional weather patterns. Within the regional gradient, pronounced peaks of production were predicted from local increases in elevation. Both the regional and subregional rainfall gradients are actively exploited by the nomadic pastoralists. During and shortly after rainy seasons the drier areas are exploited for their herbaceous production (McCabe, 1983; Coppock, Ellis et al., 1986, 1988). The greater ephemerality of production and biomass there dictates that forage be utilized when it is available. Otherwise, forage nutrient contents will decline with senescence, and even the standing dead material will increasingly be lost. The ephemerality of standing forage in this environment was demonstrated by rates of decrease in standing crops in 1981 and 1982 (Fig. 2) and by nearly equal disappearance of tissues inside and outside exclosures in 1983 and 1984. By late 1984 only a few ofthe exclosures had significantly more standing dead within, and these levels were extremely low (5-15 g/nr'), Scarcity of standing dead is likely to be due in part to simple abiotic weathering from hot desiccating winds and possibly wind-borne sand (Pratt & Gwynne, 1977). Significant quantities of dead tissues may also be eaten by termites, small mammals or insects. It is more likely that areas on the wetter part of the gradient will experience a more sustained pulse of production because more water will be stored in the soil. Perennial species with coarser leaves become more common where temperatures are lower and greater abundance of woody vegetation may reduce wind, so abiotic weathering may be reduced. Therefore, it would be more urgent to utilize areas on the dry end of the gradient early in the wet season. As the low elevation areas on the wetter part of the gradient become exhausted, higher elevation areas with more difficult terrain and greater distances to water are increasingly utilized by cattle (McCabe,
158
M. B. COUGHENOUR ET AL.
1983; Coppock, Ellis et aZ., 1988). Since rainfall at higher elevations results in more growth, it is more likely that a reservoir of unused forage will be found there at the time of most critical need. Patterns of migratory movement into lower rainfall areas in the wet season are observed among wild ungulates elsewhere in Africa (Pennycuick, 1975; Fryxell & Sinclair, 1988). One reason suggested for exploitation of drier areas of the Serengeti in the wet season is that forage there may be more nutritious (Kruelen, 1975; McNaughton, 1985). Much of this effect may be related to more nutrient-rich soils in the drier areas. Where water is more abundant, grasses tend to be taller, more stemmy, and more lignified (Boutton, Tieszen et aZ., 1988). A more parsimonious explanation for use of drier areas in the wet season is that herbivores should simply exploit all available resources; thus failure to move into the drier areas in a timely manner would represent a significant lost opportunity. As Fryxell, Greever et al. (1988) argue, migrants may be more numerous than residents because they use a larger area and they make more efficient use of resources. Regional rainfall gradients are probably a significant aspect of many pastoral ecosystems. Where topography is pronounced rainfall gradients are likely to be sharper and of greater significance. It is important to quantify these gradients, determine their dependence on regional topography and their significance for spatio-temporal forage distributions. This work was supported by grants BSR-8612109, BSR-8206864 and DEB-8004182 from the National Science Foundation. Christy Proctor-Gregg, Paul Bovitz, and Robert Popp provided excellent technical support. The field expertise of Mohammed Bashir and Lopayone were invaluable. Jay Hart encoded the DEM. We thank the Kenyan Government for research permission and rainfall data, and the people of South Turkana for their cooperation.
References Boutton, T. W., Tieszen, L. L. & Imbamba, S. K. (1988). Seasonalchanges in the nutrient content of East African grassland vegetation. AfricanJournalofEcology, 26: 103-115. Breman, H. & DeWit, C. T. (1983). Rangeland productivity and exploitation in the Sahel. Science, 221: 1341-1347. Bremen, H., Cisse, A. M., Djiteye, M. A. & Elberse, W. TH. (1979/80). Pasture dynamics and forage availabilityin the Sahel. Israel Journalof Botany, 28: 227-25I. Coe, M. J., Cumming, D. H. & Phillipson, J. (1976). Biomass and primary production of large African herbivores in relation to rainfall and primary production. Oecologia, 22: 341-354. Coppock, D. L. (1985). Feeding ecology,nutrition, and energeticsoflivestockin a nomadic pastoral ecosystem. Ph.D. dissertation. Colorado State University, Fort Collins. Coppock, D. L., Ellis, J. E. & Swift, D. M. (1986) Livestock feeding ecology and resource utilization in a nomadic pastoral ecosystem. Journalof AppliedEcology, 23: 573-583. Coppock, D. L., Ellis, J. E. & Swift, D. M. (1988). Seasonalpatterns of activity, travel and water intake for livestock in South Turkana, Kenya. JournalofArid Environments, 14: 319-331. Coughenour, M. B., Ellis,J. E., Swift, D. M.,Coppock, D. L.,Galvin, K.,McCabe,J. T. & Hart, T. C. (1985). Energy extraction and use in a nomadic pastoral ecosystem. Science, 230: 619-625. Deshmukh, I. K. (1984). A common relationship between precipitation and grassland peak biomass for East and southern Africa. AfricanJournalof Ecology, 22: 181-186. Ecosystems, Ltd. (1983/1984). Turkana District Resource Survey. Turkana Rehabilitation Program, Draft Final Report. Ministry of Energy and Regional Development, Government of Kenya, Nairobi. Ellis, J. E. & Coppock, D. L. (1984).Vegetationpatterns in NgisonyokaTurkana. Appendix II. In: Dyson-Hudson, R. & McCabe, J. T. (Eds), Turkana Nomadism: Adaptation to an Unpredictable Varying Environment. pp. 315-330. Haven, Conn: Human Relations Area Files. 378 pp. Ellis, J. E. & Dick, O. (1985). The Vegetation of Turkana District: A LandsatAnalysis. Norwegian Agencyfor International Development, Oslo. Fryxell, J. M. & Sinclair, A. R. E. (1988). Seasonal migration by white-eared kob in relation to resources. AfricanJournalof Ecology, 26: 17-31.
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Fryxell, J. M., Greever, J. & Sinclair, A. R. E. (1988). Why are migratory ungulates so abundant? American Naturalist, 131: 781-798. Galvin, K. (1985). Food procurement, diet and nutrition of Turkana pastoralists in the ecological and social context. Ph.D. dissertation. State University of New York, Binghamton. Hemming, C. F. & Trapnell, C. G. (1957). A reconnaissance classification of the soils of the South Turkana desert. Journal of Soil Science, 8: 167-183. Herlocker, D. J. & Dolan, R. A. (1980). Primary Productivity of the Herb Layer and Its Relation to Rainfall. IPAL Tech. Rep. A-3. MAB, Nairobi. Ka1ff, J., Downing, J. A. & Smith, T. T. (1985). Rainfall, agriculture, livestock and human density in the dry regions of Kenya. Journal of Arid Environments, 9: 173-183. Krue1en, D. (1975). Wildebeest habitat selection on the Serengeti plains, Tanzania, in relation to calcium and lactation: a preliminary report. East African WildlifeJournal, 13: 297-304. Lamprey, H. F. & Yussuf, H. (1981). Pastoralism and desert encroachment in northern Kenya. Ambio, 10: 131-134. LelIouerou, H. N. (1984). Rain use efficiency: A unifying concept in arid-land ecology. Journal of Arid Environments, 7: 213-247. Lel-louerou, H. N. & Hoste, C. H. (1977). Rangeland production and annual rainfall relations in the Mediterranean Basin and the African Sahelo-Sudanian Zone. Journal of Range Management, 30: 181-189. Little, M. A. & Johnson, B. R. (1984). Weather conditions in South Turkana, Kenya. Appendix I, p. 298-314. In: Dyson-Hudson, R. & McCabe, J. T. (Eds), TurkanaNomadism: Adaptationtoan Unpredictably Varying Environment. pp. 298-314. New Haven, Conn: Human Relation Area Files. 378 pp. Lusigi, W. J. (1981). Combatting Desertification and Rehabilitating Degraded Production Systems in Northern Kenya. IPAL Tech. Rep. A-4. MAB, Nairobi. McCabe, J. T. (1983). Land use among the pastoral Turkana. Rural Africana, 15·16: 109-126. McCabe, J. T. & Ellis, J. E. (1987). Beating the odds in arid Africa. Natural History, 96: 32-41. McNaughton, S. J. (1985). Ecology of a grazing ecosystem: the Serengeti. Ecological Monographs, 55: 259-294. Morgan, W. T. W. (1981). Ethnobotany ofthe Turkana: Use of plants by a pastoral people and their livestock in Kenya. Economic Botany, 35: 96-130. Noy-Meir, I. (1973). Desert ecosystems: Environment and producers. Annual Review of Ecology andSystematics, 4: 25-51. Pennycuick, L. (1975). Movements of the migratory wildebeest population in the Serengeti area between 1960 and 1973. East African WildlifeJournal, 13: 65-87. Pratt, D. J. & Gwynne, M. D. (1977). Range Management and Ecology in East Africa. London: Hodder and Stoughton. 320 pp. Prins, H. H. T. & Loth, P. E. (1988). Rainfall patterns as background to plant phenology in northern Tanzania. Journal of Biogeography, 15: 451-463. Rutherford, M. C. (1978). Primary Production Ecology in Southern Africa. In: Werger, M. J. (Ed.), Biogeography and Ecology of Southern Africa. pp. 621-659. The Hague: Dr. Junk. 1439 pp. Sala, O. E., Parton, W. J., Joyce, L. A. & Lauenroth, W. K. (1988). Primary production of the central grassland region ofthe United States. Ecology, 69: 40-45. Sombroek, W. G., Braun, H. M. H. & Van Der Pouw, B. J. A. (1982). Exploratory soil map and agro-climatic zone map of Kenya, 1980. Kenya Soil Survey Report E1. Ministry of Agriculture, Republic of Kenya. Trapnell, C. G. & Griffiths, J. F. (1960). The rainfall-altitude relation and its ecological significance in Kenya. East African AgriculturalJournal, 25: 207-213.
Herbaceous forage variability in an arid pastoral region of Kenya: importance of topographic and rainfall gradients M. B. Coughenour,*t D. L. Coppock* & J. E. Ellis* Accepted 12 September 1989 Temporal and spatial variabilities in rainfall, herbaceous production and biomass were studied over a 4-year period in a topographically diverse, arid pastoral region of northwest Kenya. A significant relation between rainfall and primary production was found, and this was applied in a manner that considered topographic variation and its influence on rainfall variation over the region. Primary production responses to rainfall occurred as pulses that were rapidly attenuated as the dry seasons progressed. The combination of spatial and temporal variability of herbaceous forage is significant for nomadic pastoralists who move along rainfall gradients between wet and dry seasons. Dry areas at low elevations produce forage that is available for only a short period of time, which explains pastoral use of drier areas early in the wet season. Quantitative analyses of relationships between topography, rainfall and forage are needed to determine appropriate pastoral densities in topographically diverse arid regions.
Introduction
Spatial and temporal forage availability is particularly important for migratory or nomadic herbivores or pastoralists in arid regions. These foragers try to buffer unpredictability and use spatial variance advantageously through movement. For example, nomadic pastoralists of the southern part of Turkana District in northwest Kenya exploit over 8000 km 2 of mostly arid ecosystem by moving autonomous households up to 15 times per year (McCabe, 1983; McCabe & Ellis, 1987). Livestock (cattle, camels, goats and sheep) are herded over large areas on an opportunistic basis and movement decisions are largely based on seasonal and spatial distributions of available forage (Coppock, Ellis etal. 1986, 1988). Approximately 36% of human food originates from herbaceous plants, primarily through a herbaceous-eattle-milk energy flow pathway (Galvin, 1985; Coughenour, Ellis et al., 1985). Satellite imagery of the Turkana District suggested a wide range of vegetation production potentials at different locations (Ellis & Dick, 1985) as a result of spatial variation in rainfall, soils and previous use. Mean annual rainfall in the region varies threeto fourfold over tens of kilometers, soils vary from sand to lava, and grazing intensity and burning frequency are unevenly distributed. Quantitative measures of forage production are needed to determine appropriate or adaptive human and livestock population densities in such areas (e.g., Coe, Cumming et al., 1976; Kalff, Downing etal., 1985). However, the most directand reliable methods for estimating primary production demand large investments of time and resources which • Natural Resource Ecology Laboratory, Colorado StateUniversity, Fort Collins, Colorado 80523, U.S.A. tCurrent address: International Livestock Centerfor Africa, P.O. Box 5689, AddisAbaba, Ethiopia.
148
M. B. COUGHENOUR ET AL.
makes them difficult to implement over large areas. While the most common method requires sampling large numbers of small quadrats on relatively restricted sampling areas, these site level studies can often be extrapolated to larger areas (e.g., Sala, Parton et aI., 1988). It is advantageous for pastoralists to know when and where growth is occurring, because temporal variability of forage in arid environments can be extreme. Herbaceous biomass and nutrients often become available in a short temporal pulse of a brief rainy season (NoyMeir, 1973). Annual plants may be short lived and nutritious green tissues may senesce rapidly. Pulses of rainfall and herbaceous production are not necessarily uniformly distributed over the region. Our goal here is to predict spatial-temporal patterns of herbaceous productivity in the southern Turkana region of Kenya (8400 knr'), and discuss the significance of this variability for the pastoralists. We will generate a regional distribution of herbaceous production from knowledge of plant responses, rainfall and rainfall distributions. We propose that regional predictions can be enhanced by combining elevation and digitized regional topography data.
Study area Study sites were located in the area of the Ngisonyoka subsection of the Turkana tribe (Fig. 1). The Ngisonyoka area is approximately 70 km south west of Lake Turkana and is entirely within the low-lying Rift Valley (500-2000 m altitude). Rift highlands rise only tens of kilometers from the south and west boundaries. A Pre-Cambrian basementcomplex mountain range bisects the area. Sandy piedmont alluvial fans and plains are dissected by numerous ephemeral streams and washes that flow after large storms. These streams are typically lined with large Acacia tortilis trees. Much of the eastern half of the area is covered with weathered Miocene lava, as gravelly plains and hills that have a thin mantle of gravelly-loam soil (Sombroek, Braun et at., 1982; Hemming & Trapnell, 1957). The area encompasses both arid (300-550 mm rainfall) and very arid (150-350 mm) ecoclimate zones (Sombroek, Braun etal., 1982). Mean annual rainfall at weather stations in the area varies from 201 to 394 mm/year, while annual potential Penman evapotranspiration is 2200-2700 mm1year. A period of 'long' rains usually occurs in March-May, while 'short' rains occur around November. However, seasonal patterns are relatively weak. Often 9-11 months pass without significant rainfall. Mean daily temperature is about 30°C and mean maximum is about 35°Cwith little seasonal variation (Little & Johnson, 1984). The characteristic vegetation of the arid zone is dry thorn-bushland, while dwarf-shrub grassland is the most widespread vegetation of the very arid zone (Pratt & Gwynne, 1977). Annual herbaceous species are predominant in areas receiving less than 300 mm annual rainfall, while perennial species are increasingly important in less arid areas. Several physiognomic vegetation types are found in this region, including sparse bush grassland, dwarf shrub grassland, bushed grassland, wooded grassland, bush, woodland, and riparian forest (Ellis & Coppock, 1984; Ellis & Dick, 1985). Woody canopy cover ranges from 2 to 100%, but most area is 10 to 40% covered (Coughenour, Ellis et al., 1985; Ecosystems Ltd., 1983/84). Aristida mutabilis and Eragrostis spp., annual grasses are dominant on unshaded sites. In shaded habitats, the annual grasses Brachiaria Ieersiodies, Dactyloctenium aegyptium and Digitaria oelutina predominate. Numerous annual forb species are present, particularly in unshaded habitats. The perennials Cenchrus ciliaris and Kyllingia welwitschii occur in certain areas, but the most important perennial grasses where rainfall is less than 450 mm are A. adscensionis and Leptothrium senegalense. Perennial Cyperus spp. and S porobolus spp. are very important where rainfall exceeds 450 mm at lower elevations. A more complete list of South Turkana plant species was compiled by Morgan (1981).
HERBACEOUS PRODUCTION IN NORTHWEST KENYA
149
36°E
Loichang,:' atak -..j
t-----4
IOkm
o
o
Lop~ot
Ka ilu
•
N.-
·te
a
(J
Figure 1. The South Turkana study area showing locations of study sites and rainfall recording (squares), other temporary rainfall recording sites (triangles) and villages with permanent rainfall recording (stars). Elevation contours are shown in metres above sea level.
Methods
Herbaceous vegetation Herbaceous biomass was determined in 1981-82 (Coppock, 1985) by clipping 0'25-m 2 rectangular (0' 25 m x 1 m) quadrats located in a stratified random manner along a series of parallel transects at five sites. On each date and site 20 quadrats were clipped in each of two replicate areas. At three sites four quadrats were clipped beneath each of five randomly selected large trees growing along dry streambeds. On average, quadrats at a site were located within 7 ha. Stream terrace quadrats were typically spread over 4 ha. Clipped samples were taken on four dates, from the late wet season in 1981through two dry season samples and a late wet season sample in 1982. Green versus non-green cover and species cover were ocularly estimated within 30 Q'1-m2 quadrats located in a stratified random manner over 0·5 ha at each of three sites. In 1983 we constructed 22 thorn-fence grazing exclosures (10 m diameter) to prevent herbivory by pastoral livestock or other large herbivores. These exclosures were placed non-randomly due to their small number and area. Exclosures were located on relatively uniform stands of herbaceous vegetation which sometimes had less than the average amount of ground covered with patches of bare soil. At three sites two exclosures were
150
M. B. COUGHENOUR ET AL.
placed on a sunlit interdrainage and two were placed in the shade of large trees on the stream terrace. At two sites one exclosure was placed on the interdrainage and one in the shade. At three sites there were only two exclosures, both in non-shaded areas. At one remote site in the mountains exclosures were unnecessary. On each date four 0'25-m 2 quadrats were clipped inside, and four outside of each exclosure. At the Mountain site eight quadrats were clipped. Larger quadrats (l m x 1 m) were used at three sites (Kalimnarok, Kadangoiy, Mountain) where perennial bunch grasses prevailed. Live and dead shoots were separated in the field. Poor rainfall and grass growth in 1984 warranted only a minor sampling effort. Graminoids were clipped from eight 0'25-m 2 quadrats within each of five exclosures (two sites) in late April at or near the time of peak standing crop. At two additional exclosures biomass was clipped directly on patches of perennial bunchgrass to estimate maximal biomass concentration in small areas. In late August standing-dead biomas was sampled at four sites (six exclosures) where a grazing exclosure effect was visibly apparent. Four quadrats were clipped inside and four outside each exclosure. There was zero green biomass on those sites at that time. Cover was estimated at these sites on 16quadrats inside and 20 outside of each exclosure to derive a relationship between standing-dead cover and biomass. Herbaceous aboveground net primary production (ANPP) was calculated from positive increments in live-plus-dead or live biomass since the beginning of a growth period. Cumulative ANPPs for the periods between March and May 1981, April and June 1982, Dates 1-2 1983, Dates 1-31983, and Dates 1-41983 were regressed on cumulative rainfall over the respective periods from the beginning of the wet season. Rainfall was recorded from mid to late May through November in 1983and 1984. Seven sites were monitored in 1983 and although 18 sites were established in 1984, only nine provided continuous data due to human interference. Gauges were read every 1-4 weeks. Additional monthly rainfall data for 1981-1987 were obtained from several permanent weather stations in the study area. A regression analysis of rainfall on elevation was performed for each year (Table 1). Terrain data for the region were encoded in a digital elevation model (OEM) with 40 m elevational resolution. The known weather station data for a particular year were entered into an algorithm that interpolated rainfall as follows. For each unknown point, elevation was computed from the OEM. Three estimates of rainfall were generated from observed rainfall at the three nearest weather stations, the rainfall-elevation relation and the elevation difference between the station and the unknown point. These estimates were weighted by the inverse cubic distance to each of the stations to arrive at a final estimate for the unknown point. The final set of points was then spatially interpolated by inverse distance weighting to give a regular grid and this regular grid was contoured to generate a rainfall map for the year. Yearly maps from 19821987 were averaged to derive a mean annual rainfall map. Results A relatively dry period that began in late 1979 was broken by rains in late March and early April 1981. From June 1980 through February 1981 an average of6 rom was recorded. In 1981 and 1982 the long rains were very favorable with 130 mm/month in March and April and 65 mm in May of 1981,80 mm/month in April and May ofl982 (mean rainfall over five permanent weather stations). In November 1982 110 mm fell, but field work ceased between June and April. Prior to the rains in 1981, live or dead herbaceous biomass or litter were virtually absent. The March-April rains provided a large pulse of herbaceous productivity by June (Fig. 2). Resultant standing biomass was greater in the shade of large trees growing along ephemeral streambeds than on sunlit interdrainages. Production was also greater at more south-western sites (Kadangoiy and Lobokot), Biomass at Lokosimaekori was low,
lSI
HERBACEOUS PRODUCTION IN NORTHWEST KENYA 400,------------------------------, N
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2a. e
30 0
~
200
u
~ .E V> "0
;§
100
4
5
6
7
8
10
9
II
12
2
3
4
5
6
82
81 Month/yeor
Figure 2. Dynamics of total standing biomass at sites sampled in 1981 and 1982. Each point based on
n = 40 O:25 m 2 plots except at Kadangoiy (n = 20) and Lobokot (n = 60) and shaded sites (n = 20).
Green cover constituted 100%,22%,32% and 100% of total cover in sunlit sites in the four respective dates. , Lokosimaekori; --t-, Katamanack; -0-, Katapadwell; ---B--, Kadangoi; ~,Lobokot; ···0..·, Lokos. shade; ....6· .. , Katam. shade; ·· ..x.... , Katap, shade.
Table 1. Regressions ofprecipitation (mm) on elevation (m) byyear. The periods 4/83-11/83 and 4/84-11/84 included datafrom temporary raingauges Period
N
r
p
Intercept mm
Slopemm/m
4/83-11/83 4/84-11/84
12 14
0'33 0'33
0'05 0·03
-347 -16
0·85 0'15
1979 1980 1981 1982 1983 1984 1985 1986 1987
6 5 6 7 6 6 7 10 10
0'81 0'46 0'84 0'40 0'31 0·32 0'77 0'87 0'66
0'01 0'20 0·01 0'12 0'25 0·24 0'01 <0'001 0'004
-246 -202 -538 -276 -279 -39 -352 -113 -148
0'98 0'63 1·35 1'00 0'80 0'27 0·99 0·58 0'72
probably due to livestock grazing as considerable numbers of pastoralists were in the area at that time. At Lobokot, standing crop was higher in the open area than in heavy bush. Over the subsequent 5 months most of the standing biomass was either grazed, transferred to litter or lost to weathering. Litter biomass increased from 0 in March to 2-12 g1m2 in June; 3,20,25, and 60 g/m2 were recorded at Lokosimaekori, Lobokot, Katamanock, and Katapadwell in November, which were only small proportions of total productivities. The rains of April-May 1982 yielded less. Again, biomass was greater in shade and in the south-west, and Lokosimaekori had abnormally low values. Litter biomass decreased from 40, 20, 2 and 2 g1m2 in March to 25, 0, 0 and 0 g1m2 in June at KatapadweU, Katamanak, Lobokot, and Lokosimaekori, respectively. Most or all of this litter biomass was produced in 1981 and most of the April-May 1982 production was still alive in June. The rains of 1983 were unusual in that an average of 30 mm/month occurred over the entire interval of May-October with significant falling in the typical dry season of JuneAugust; but there was no 'good' rainy season. On all dates, there was no significant differences in biomass (p > 0'05) inside versus outside exclosures except in September at Katamanak (Table 2). Human and livestock occupancy in these areas was extremely low in
sun shade
sun shade
sun shade
0 0 2 2 2
1 1
1 1
2 2
2 2
2 2
Exclosures
56 ± 17 157 ± 96 87 ± 39
51 ± 28 32 ± 13
90 ± 31* 41 ± 23
50 ± 13* 20 ± 15
43 ± 21* 0
(g/rrr')
15 0 24
1 22
7 38
1 98
0 0
(% Live) )
57 ± 26 48 ± 16 64 ± 22 82 ± 43 126 ± 33
59 ± 17 54 ± 18
35 ± 16 133 ± 67
79 ± 30 79 ± 27
70 ± 24* 83 ± 28
8 ± 6' 0
(g/m
2
79 75 31 60 89
35 74
46 46
59 98
100 0
(% Live)
May-June
90 ± 35 158 ± 48
39 ± 16 79 ± 48
16 ± 8 15 ± 6
17 ± 11 34 ± 19
0 0
(g/m")
t Significant grazing exclosure effect; exclosure x =
69 70
100 100
100 100
100 100
0 0
(% Live)
July
*Significant difference between sun and shade (p 5 0·05). 46 ± 17, unprotected x = 78 ± 26 g/nr'.
sun shade Katamanak lava sun Kalimnarok sun Kadangoiy sun
Open Subcanopy
Mountainsite
Interdrainage Stream terrace
Ngatagoi footslope
Interdrainage Stream terrace
sun shade
sun shade
Kanaiiki footslope
Interdrainage Stream terrace
Katapaduiell
Interdrainage Stream terrace
Lokosimaekori
Interdrainage Stream terrace
Northern site
Site
April-May
48 ± 183 ± 62 ± 214 ± 173 ±
44* 169 21+ 87 43
134 ± 52 99 ± 28
78 ± 40 65 ± 41
147 ± 113 91 ± 37
117 ± 52 101 ± 35
68 ± 25 48 ± 23
(g/m")
70
71
92 97 100
100 100
100 63
100 100
100 100
100 99
(% Live)
September-October
--
Table 2. Herbaceous aboveground biomass (mean ± standard deviation g/m2 ) andpercent of biomass alivein 1983. n = 8 quadrats/exclosure
r-
:>.
""l
::tI h1
c:::
Z 0
tIl
o ::r:
o 0 c:::
!'"
?=
N
::;;
HERBACEOUS PRODUCTION IN NORTHWEST KENYA
153
Table 3. Biomass (g/m2 ) and cover (%) in 1984. April-May biomass was from within exclosures only. All biomass in August-September was dead. An additional nine exclosures had essentially zero standing live or dead biomass then. Each number representsn = 8 O'25 m 2 quadrats
August-September
April-May Enclosures Site
n
Katapadwell Kadangoiy Lokosimaekori Ngatatoi Katamanak E. Katamanak W.
2 3 1 1
1
1
Live biomass
Cover
Biomass Dead biomass
In
0·9 ± 0·8 1-6 ± 1·2 5·7 ± 2,5* 5'5 ± 16'4 2·4 ± 5·5 10'6 ± 13-3t 15·6 ± 15,6* 13'4 ± 9'0* 5'6 ± Nt
Out
In
Out
3·7 ± 3·4 5·0 ± 3,7* 2·2 ± 3·7 1-3 ± 1'3 3·2 ± 3'1 4'0 ± 2'7 3'7 ± z-z
5-4 ± 6'8t 7·7 ± 5,8* 7'4 ± 4'3* 2'3 ± 2'4
0'7 ± 0'7 1'4 ± 1·7 1'4 ± 1'7 1'1 ± 0'8
* Significant exclosure effect p < 0'05. [ Significant exclosure effect p < 0'01.
1983. Total biomass in shaded habitats was not consistently greater than in unshaded habitats, but there was usually more green biomass in shade. Sites farther south and west were more productive, though this gradient was much less pronounced than in 1981-82. Total biomass remained constant but green biomass declined through May and June, and grasses were much greener in shade during that period. There was considerable decline in both live and standing dead through July, though rains at some sites promoted additional growth. Late August rains produced a large growth pulse at all sites. Litter biomass of 1983 was collected only in April-May. There was 0 g/m2 at N. site, 35 at Lokosimaekori, 63 at Katapadwell, 33 at Ngatagoi, 13 at Katamanock, 133 at Kalimnarok, and 28 g/m 2 at Kadangoiy. This litter probably represented part of the production response to the rains of November 1982. The rains of 1984 failed and this year was considered by the Turkana to be one of the 'bad' years that occurs every 4-5 years. Sampling in early May 1983 yielded very little biomass (Table 3). Biomass concentrations on patches of perennial bunchgrass (Leptathrium senegalense) at Katapadwell were 25 g/m 2 (mean) ± 17g/m 2 (stand. dev.) live and 78 ± 48 g/m 2 dead. By early September there was no green biomass and very little dead biomass remaining either inside or outside the grazing exclosures, indicating significant losses due to weathering rather than to grazing. However, standing dead was significantly greater inside all of the samples exclosures. No standing dead was visible in or around nine of the exclosures that were not sampled. At the remaining four unsampled exclosures there were no visible grazing effects and biomasses were visibly similar to those observed at the other sites. A regression analysis showed that dry weight of standing dead in late 1984 was significantly correlated with percent cover as: g/m2 = 14·8 + 2.7 x cover%,';' = 0'77 at Katapadwell, and g/m 2 = 0·8 + 0·033 x cover%,';' = 0·78 at the other sites. There was a significant positive relationship between herbaceous production and rainfall over the 4-year period (Fig. 3). Points representing shaded habitats appeared to lie above the regression line, however there was no significant difference between the means of shaded and unshaded habitats (z-test). At low rainfall (below 200 mm), it appeared that shaded habitats produced more than sunlit, however this difference was also nonsignificant. Rainfall data from 1979-87 were subjected to rainfall-elevation analysis (Fig. 4). In 5 of the 8 years there were significant rainfall-elevation relations (Table 1). These relations varied from year to year. Realistic rainfall maps could be produced only for the years 198287 because of the absence of data from Lokichar station in 1979-81. The Lokichar data
154
M. B. COUGHENOUR ET AL. 400 ,..---------------~-------___,
o
0
300
N
0
E
+
<,
2:
c: 0
+o
200
0
+
:>
-e
e
0 + +
c,
+ +
100
+
...+ 0
-lof-
+0 +
+
0
.
0
·0 300
200
100
400
Rainfall (rnm)
Figure 3. Cumulative aboveground net primary production versus cumulative rainfall at sites sampled in the wet seasons of 1981 and 1982, and April-September 1983 (see Table 3). The line indicates y = -20 + 0'71x, ,;. = 0'74, n = 55, P « 0·001. Each point represents a cumulation of current production since onset of rains.•, annual sun; +, annual shade; D, perennial; - - y = -20,0 + 0'7x;';' = 0·74. were critical because this site typically deviates below the rainfall-elevation relationship and because it was the only site in the north-eentral part of the study area. Individual maps from 1982-87 were averaged together to produce a 6-year average rainfall map (Fig. 5). The resultant rainfall map was used in conjunction with the production versus rainfall regression equation to calculate a map of mean annual herbaceous aboveground production for the 6-year period (Fig. 6). Annual herbaceous ANPP derived by this method was 214 ± 124 g/m 2 averaged over the region.
o
0·2
0,3 004 0·5
0·6 0·7 0·8 0·9
1·0
1·1
1·2
OL---'-..L..L--'----'---,---'-----'--
0·3 0'4 05 0·6 07 0·8 0'9
1·0
1'1
1'2
Elevation (1000 m)
Figure 4. Analysis of rainfall versus elevation for the years 1979-1987 employing data from permanent stationsonly. Only significant regressions(P < 0'05) are shownaslines. (a) , 1979; + 1980;-+-.1981; D, 1982;0,1983. (b)., 1984;-+-, 1985;--e-, 1986; "'<)"',1987.
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Annual Rainfall mm (mean 1982-1987)
Figure 5. The distribution of mean annual rainfall (mm) over the study area, obtained as the average of individual distributions for each year 1982-1987.
Discussion
Effects on productivity The linear relationship of accumulated NPP on rainfall (Fig. 3) was very similar in terms of both slope and intercept to analogous relations observed over East Africa as a whole y = -19·6 + 0·85x (Deshmukh, 1984), and the Mediterranean basin y = -41 + 0·87 (Lel-louerou & Hoste, 1977). The regression line fell above a relation for the Sahel-Sudan y = 10·5 + 0·26x (Lel-louerou & Hoste, 1977) due to larger slope and smaller intercept, and above a line for the Serengeti y = -102 + 0·69x (McNaughton, 1985) due to larger slope and intercept. A positive x-intercept is usually observed in such relations and interpreted as the threshold amount of annual rainfall necessary to initiate growth (NoyMeir, 1973; Sala, Parton et al., 1988). The threshold effect was observed in the Turkana regression at about 28 mm. Growth after a dry season has indeed been observed with as little as 20-30 mm rainfall (personal observation, M. B. Coughenour). The slope, or the efficiency with which rainfall is converted to production (RUE) fell well within a range of observations made elsewhere (Lerlouerou, 1984). The slope of the Turkana relation indicates a RUE of 7 kg/mm/ha. The nearest comparable data, for Marsabit District in north-central Kenya (Herlocker & Dolan, 1980; Lamprey & Yusuf, 1981; Lusigi, 1981), indicated a RUE of2·2 to 9·2 for herbaceous vegetation. RUEs of 8-9 occurred in South African (Rutherford, 1978) as well as East African (Deshmukh, 1984) and Mediterranean grasslands (Lel-louerou & Hoste, 1977). A range of 3 to 6 is generally applicable for reasonably managed grasslands (Lelfouerou, 1984).
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Aboveground NPP g/m2 (mean 1982-1987)
Figure 6. The distribution of mean annual aboveground production (g/rrr') over the study area for the years 1982-1987.
Below 300-500 mm rainfall sandy soils such as those covering much of South Turkana have shown a greater potential for primary production than finer-textured soils (NoyMeir, 1973). Very low productivities have been observed on silt and loam soils below 300 mm rainfall in the Sahel, but higher productivities occurred on sandy soils (Bremen, Cisse et aI., 1979/80). In general, sandy soils hold water less tightly so it may be easier for plants to extract water when little is available. At higher availability, finer soils will store more water. The principle of this inverse texture hypothesis could promote higher production on Turkana sandy soils, although the exact thresholds between converse effects of fine and coarse soils will depend upon local evaporation and soil fertility. Nutrient concentrations in sandy soils of Turkana are very low (about 0·04% Nand 6 /J-g extractable PIg soil), but increasing nutrient levels may have little effect on herbaceous RUE because of low rainfall, and small nutrient requirements of C4 annual grasses (Breman, Cisse et al., 1979/80). Thus, while water was more limiting than nutrients below 300 mm rainfall, above 300 mm production was increased five-fold by fertilization (Breman & DeWit, 1983).
Improving spatial predictions These principles suggest that regional predictions from rainfall alone could be enhanced by development of separate NPP-rainfall relations for fine and coarse textured soils (e.g., Sala, Parton et al., 1988) and by development of different curves for rainfalls above and
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below the nutrient limitation threshold. Furthermore, it would be beneficial to document spatial distributions of nutrient limited soils over areas where rainfall is above the threshold. The variance among yearly relationships between elevation and rainfall (Table 1) demonstrates that a single relationship cannot be assumed over all time periods. In general, relations were poorer, and slopes were lower in drier years. We have applied this methodology to generate monthly rainfall maps for the area (Coughenour, unpublished), and have found that regressions must be developed on a monthly basis as well. In general, a regression should be developed from data covering the time period of attempted prediction and spatial interpolation. Prins and Loth (1988) found that relations between elevation and rainfall in Tanzania were generally poorer in the short rainy season and dry season than in the long rainy season. Short rains and dry season rains seemed to be produced by individual convective cells within a larger system, while long rains were generated by large monsoonal systems. Rainfall in dry years and months in Turkana also result from smaller convective systems, so the same lack of elevation effect on convective rainfall may be operating here. Consideration of additional variables would improve predictions of forage response to rainfall. Rain use efficiency is decreased by runoff and infiltration, and throughflow out of thin rocky soils. Distributions of woody canopy cover and explicit consideration of effects on shading and rainfall interception would be profitable. More accurate understanding is needed of elevational effects on rainfall where high elevation areas are small in relation to surrounding lowlands. Consideration of these effects would be facilitated by storing and utilizing topography, soils, woody canopy cover and other data in a geographic information system along with parameters describing forage responses under these differing conditions.
Significance to pastoralists The spatial pattern of NPP in Turkana predicted from rainfall maps displayed an overall south-west to north-east regional gradient. Part of this gradient was due to generally greater elevations in the south-west, however part was unrelated to elevation and appeared to be a result of regional weather patterns. Within the regional gradient, pronounced peaks of production were predicted from local increases in elevation. Both the regional and subregional rainfall gradients are actively exploited by the nomadic pastoralists. During and shortly after rainy seasons the drier areas are exploited for their herbaceous production (McCabe, 1983; Coppock, Ellis et al., 1986, 1988). The greater ephemerality of production and biomass there dictates that forage be utilized when it is available. Otherwise, forage nutrient contents will decline with senescence, and even the standing dead material will increasingly be lost. The ephemerality of standing forage in this environment was demonstrated by rates of decrease in standing crops in 1981 and 1982 (Fig. 2) and by nearly equal disappearance of tissues inside and outside exclosures in 1983 and 1984. By late 1984 only a few ofthe exclosures had significantly more standing dead within, and these levels were extremely low (5-15 g/nr'), Scarcity of standing dead is likely to be due in part to simple abiotic weathering from hot desiccating winds and possibly wind-borne sand (Pratt & Gwynne, 1977). Significant quantities of dead tissues may also be eaten by termites, small mammals or insects. It is more likely that areas on the wetter part of the gradient will experience a more sustained pulse of production because more water will be stored in the soil. Perennial species with coarser leaves become more common where temperatures are lower and greater abundance of woody vegetation may reduce wind, so abiotic weathering may be reduced. Therefore, it would be more urgent to utilize areas on the dry end of the gradient early in the wet season. As the low elevation areas on the wetter part of the gradient become exhausted, higher elevation areas with more difficult terrain and greater distances to water are increasingly utilized by cattle (McCabe,
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1983; Coppock, Ellis et aZ., 1988). Since rainfall at higher elevations results in more growth, it is more likely that a reservoir of unused forage will be found there at the time of most critical need. Patterns of migratory movement into lower rainfall areas in the wet season are observed among wild ungulates elsewhere in Africa (Pennycuick, 1975; Fryxell & Sinclair, 1988). One reason suggested for exploitation of drier areas of the Serengeti in the wet season is that forage there may be more nutritious (Kruelen, 1975; McNaughton, 1985). Much of this effect may be related to more nutrient-rich soils in the drier areas. Where water is more abundant, grasses tend to be taller, more stemmy, and more lignified (Boutton, Tieszen et aZ., 1988). A more parsimonious explanation for use of drier areas in the wet season is that herbivores should simply exploit all available resources; thus failure to move into the drier areas in a timely manner would represent a significant lost opportunity. As Fryxell, Greever et al. (1988) argue, migrants may be more numerous than residents because they use a larger area and they make more efficient use of resources. Regional rainfall gradients are probably a significant aspect of many pastoral ecosystems. Where topography is pronounced rainfall gradients are likely to be sharper and of greater significance. It is important to quantify these gradients, determine their dependence on regional topography and their significance for spatio-temporal forage distributions. This work was supported by grants BSR-8612109, BSR-8206864 and DEB-8004182 from the National Science Foundation. Christy Proctor-Gregg, Paul Bovitz, and Robert Popp provided excellent technical support. The field expertise of Mohammed Bashir and Lopayone were invaluable. Jay Hart encoded the DEM. We thank the Kenyan Government for research permission and rainfall data, and the people of South Turkana for their cooperation.
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