Fertilizer Research 44: 87-99, 1996. 87 © 1996 Kluwer Academic Publishers. Printed in the Netherlands.

Potential impact of agroforestry on soil nutrient balances at the farm scale in the East African Highlands

K.D. S h e p h e r d 1, E. Oh l s son l, J.R. O k a l e b o 2 & J.K. N d u f a 3 1ICRAF (International Centre for Research in Agroforestry), P.O. Box 30677, Nairobi, Kenya; 2KARl (Kenya Agricultural Research Institute), NARC Maguga, P. O. Box 30148, Nairobi, Kenya; 3 KEFRI (Kenya Forestry Research Institute), P O. Box 25188, Otonglo, Kisumu, Kenya

Received 18 November 1994; accepted in revised form 3 August 1995

Key words: agroforestry, integrated nutrient management, Kenya, manure, mineralization, N losses, mineral fertilizers

Abstract

There is much current interest in the potential role of agroforestry in the mitigation of nutrient depletion in Sub- Saharan Africa. Using data from farm surveys and trials, a static model of N and P flows was constructed for a standard farm system, representative of typical subsistence farms in humid parts of the East African Highlands, The model was used to explore the possible impact of improved agroforestry systems on nutrient budgets, to identify priorities for research.

Soil nutrient balances in the standard farm system were - 107 kg N and - 8 kg P ha- 1 yr - 1. Agroforestry systems did not significantly reduce the N deficits except when a high proportion of the total biomass was returned to the soil, rather than removed from the farm. Agroforestry increased N input through biological N fixation and deep N uptake, but this was offset by a larger nutrient removal from the farm in harvested products, which increased from 38 kg N in the standard system to 169 kg N ha-1 yr-1 in an intensive dairy-agroforestry system. Agroforestry did not increase P inputs, and harvested P increased from 6 kg P in the standard farm system to 29 kg P ha-1 yr-1 in the dairy-agroforestry system. Thus, moderate P inputs, of 20 kg P ha-1 yr-1 were required to maintain soil P stocks.

N leaching from the field was the most significant nutrient loss from the farm system, with a range of 68 to 139 kg N ha- 1 yr - 1. The capture of subsoil N by deep-rooted trees in agroforestry systems substantially increased N-use efficiency, providing 60 kg N ha-1 yr-1 in the dairy-agroforestry system. The budgets were sensitive to N mineralization rates in subsoils, N losses from soils and manures, and effectiveness of deep-rooted plants in subsoil N capture, for which there is little data from the region. Therefore, high priority should be given to research in these areas.

The current model can not account for important feedback mechanisms that would allow analysis of the long-term effects of nutrient budgets on nutrient availability and plant productivity. Dynamic models of farm nutrient budgets that include such interactions are needed to further assess the sustainability of farming systems.

Introduction

Nutrient depletion of agricultural soils is a major con- cern in sub-Saharan Africa, resulting from crop pro- duction with low levels of nutrient inputs coupled with poor nutrient conservation practices. Rates of nutri- ent depletion are highest in areas with favourable cli- mate for crop production and high population density,

most notably in the East African Highlands (Stoorvo- gel et al., 1993). For example, the aggregated nutrient balance in the rootable soil layer for Kisii District in Kenya, has been estimated at - 112 kg N, - 3 kg P, and - 7 0 kg K ha- l yr - 1 (Smaling et al., 1993).

There is much current research interest in the role of agroforestry systems and improved management of organic resources (e.g. animal manures, composts)

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for the improvement of soil fertility on smallholder farms in the tropics. However, much of the exper- imental work to test hypotheses on nutrient cycling (Young, 1989) is done at plot level, without regard to the limits on the availability of nutrient resources at farm or regional scales. There is thus a need for thor- ough ex ante analysis of technologies at these larger scales, to direct long-term experiments on improved management systems. Examples of quantitative mod- els of nutrient cycling and budgets at the regional scale are given by Smaling et al. (1993) and van der Pol (1992), and at the agro-ecosystem or farm scale by Fris- sel (1977), Powell and Mohamed-Saleem (1987) and Swift et al. (1989). In this paper, a simple static model of nutrient flows on mixed farms in the humid high- lands of western Kenya is used, to explore the possible impact of agroforestry management systems on soil nutrient balances at the farm scale. This model results could be used to identify priorities for research.

The nutrient budget model

A time-static model was constructed of the annual inputs and outputs (harvests and losses) of nitrogen and phosphorus to and from a farm, and the annu- al flows of these nutrients between field and livestock compartments within the farm (Fig. 1). This is a simpli- fied model based on a previous six-compartment mod- el (Shepherd et al., 1995). The field compartment in the current model represents production from cropped land, soil conservation structures, and hedgerows on farm boundaries. Nutrient resources outside the farm's external fence, in the atmosphere above the farm, or in the soil below a depth of 0.5 m were considered external to the farm system. The aggregated nutrient flows in Fig. 1 were estimated from their respective sub-flows (Table 1).

Wet deposition (Na~po, Pa~po) and asymbiotic nitrogen fixation (Nayi~) were derived from average annual rainfall (Smaling et al., 1993), while dry depo- sition was assumed to be negligible in humid environ- ments. Biological nitrogen fixation (Nby~) was esti- mated as 50% of the total N content of N-fixing plants (Giller & Wilson, 1991). Deep uptake of N from below 0.5 m (Naacp) was taken as 50% of plant N uptake for deep-rooted plants (shrubs and trees) up to a maxi- mum value equal to the amount of leached N, but zero for other plants. Simulations by van Noordwijk (1989) suggest that deep root systems could capture much of the leached N in humid environments, but field mea-

surements are lacking. For less mobile nutrients (e.g. P, K) Commerford et al. (1984) suggested maximum values of up to 80% of plant uptake from layers below 0.15-0.30 m depth for deep rooted plants, but high val- ues were mainly associated with prolonged dry spells. In the model, however, we did not include deep uptake of P because of the low available P status of the sub- soils. Fertilizer application rates (Nyert, Ptert) were specified as attributes of the farm systems, described below.

N leaching toss (Nt~ach) was calculated as the prod- uct of the amount of leachable N and a N leaching coefficient. This coefficient, expressed as percentage of leachable soil N, was estimated from soil texture and annual rainfall (Smaling et al., 1993). Leachable N was taken as Nj~rt, plus mineralizable soil N. The latter was estimated from total soil N content assuming a fixed annual nitrogen mineralization rate. Leaching of P and volatilization of soil and fertilizer N were assumed to be negligible. Denitrification was assumed to be negligible because of the high porosity of these soils (R.J. Buresh, private communication). Complete volatilization of N (Nvotat), but no loss of P, were assumed when organic residues were burned.

In an alternative version of the model the amount of organic N returned to the field in manure and litter was added to the leachable N pool. This assumed that the manure and litter completely decomposed within one year.

Crop and tree harvests and fodder production from the field (Table 1) were specified for each farm system from (1) dry matter yields of grain crops, fodder crops, shrubs, and upperstorey trees, (2) the fraction of dry matter for each plant type partitioned to grain, green shoot or leaf (green manure or fodder), branch (fuel- wood), trunk (polewood), stover, and litter, (3) the N and P concentration in each plant part. The propor- tions of stover, and green shoot or leaf that were either allocated to fodder or returned to the soil were speci- fied. All litter was taken to be returned to the soil. To enable estimation of the amount of biologically fixed N returned to the field in litter, a root litter fraction was calculated for all plant types as 0.2 of total plant biomass with 1% N and 0.01% P.

Total livestock nutrient intake (livestock inputs plus field fodder, Table lb) was partitioned into milk, and urine plus faeces, using fixed partitioning coefficients for each nutrient specified per livestock breed (Shep- herd et aI., 1995). A fraction of the manure was assumed to be deposited off-farm proportional to the time livestock are grazed off the farm. Nutrient loss-

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Table la. Data sources used to estimate individual fluxes of nitrogen (N) and phosphorus (P) in the farm nutrient budget model: field compartment. The aggregated flows shown in Fig. 1 are indicated in bold script

Flux (kg N or P ha- l yr- 1) Symbol/equation Data source

Atmospheric deposition Ndepo,Pdepo

Asymbiotic fixation Na -f i z

Biological fixation Nb -f i x

Deep uptake Ndeep Fertilizer application N-f e f t , P-f err

Field inputs

Leaching below 0.5 m Erosion Volatilization

Field losses

N.f ield,in = N depo+Na y ix +Nb -f ix +N deep+N -f ert

P y ield,in =Pdepo+P -f ert

Nleach

N~ . . . . P~o~

Nvolat

PIield,lo~=Peros

Grain harvest Ng~ai,~, Pg~ai~

Fuelwood harvest N- fur l , P f u~t

Polewood harvest Npote, Ppot~

Field harvests N -f i . t e ,h~v=N groin + N J . . ,+ Npol. Psi.ze,horv=Pg~oi. +P-f.~z+Ppoz.

f(annual rainfall) f(annual rainfall) f(N uptake of N fixing plants) f(N uptake of deep-rooted plants) Specifed (as attribute of farm system)

f(leachable N, annual rainfall, % clay) f(USLE, enrichment ratio, topsoil N/P concentration) f(amount of biomass N burned)

Specified Specified Specified

USLE = Universal soil loss equation (Wischmeier and Smith, 1978).

es during manure management were specified as fixed fractions of the urine/faeces flux depending on the qual- ity of management.

Descript ion of the land use system

The study area was chosen to represent an area having high agricultural potential, but severe nutrient deple- tion. It includes parts of Siaya, Kisumu and Vihiga Districts in the highlands of western Kenya located between 0 ° and 05 ~ S and 0 ° 10 ~ N, to 340 31 ~ E to 34 ° 40 ~ E, with a humid climate and an altitude of about 1500 m (Ndufa et al . , 1992). The area has an annual rainfall of 1600-1800 mm with a mean annual tem- perature of 21 °C. The landscape is gently undulating, with predominantly Acrisols, Nitisols, and Ferralsols (Andriesse and van der Pouw, 1985). The area has a subsistence-level mixed crop/livestock farming sys- tem. The major crops are maize (mostly unimproved varieties), beans, cassava, bananas, sweet potatoes, and sorghum. There are two cropping seasons, the

first rains from March to August, and the second rains from September to December. Cattle (mostly unim- proved breeds of zebu) are kept mainly as a source of liquid capital, though there is increasing interest in small-scale dairying. Average farm size ranges from 0.5 to 2.0 ha and population density varies from 300 to over 1000 persons km -2 in some areas (KEFINCO, 1990).

Standard fa rm system

A standard farm system was defined to represent the existing situation for farms of median size and resources, according to farm surveys. A survey of soil nutrient stocks for cropped fields of 32 farms was exe- cuted to assess the main variation in soils in the area. A composite of 24 soil auger samples from 0-0.15 m and 12 samples from 0.15-0.50 m depth were taken per farm and air-dried before analysis (Table 2). Data on farmers' soil fertility management practices were obtained from (1) multi-visit informal interviews with

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Table lb. Data sources for individual fluxes of nitrogen (N) and phosphorus (P) in the farm nutrient budget model: livestock/manure compartments. The aggregated flows shown in Fig. 1 are indicated in bold script

Flux (kg N or P ha-1 yr-1) Symbol/equation Data source

Off-farm grazing Ngraz,Pgraz Mineral supplement Prnlner

Livestock inputs

Milk harvest

Livestock harvests

Manure deposition off farm

Losses during manure handling

Manure losses

Field fodder (internal flux) Urine/faeces (internal flux)

Manure (internal flux)

Field balance

]Vlstck,in = Ngra z Plstck,in = Pgraz+Pminer

i~milk, Pmilk

l~lstck,harv=Nmilk Plstck,harv=Pmilk

Nmanof y,Pmanof f

Nrnan,loss=Nmanoy f+Nmanteach Pman,loss=Pmanof y+Prnanleach

NIield,lstck, Pfield,lstck Nlstck,man=Nfield,lstck-]Vletck,harv Pt s tck,man=Pf ield,l s tak'Plstck,harv Nman,yield=]Vlstck,man-Nman,lvss Pman,¢ ietd=Pgstck . . . . -eman,to, s

Yfield,bal=Nfield,in + Nman,f ield-2~ ] ield,loss-N f ield,harv -N f ield,l stck

Pyietd,baz=Pfield,in +Pman,fietd" Pfield,loss-Pfietd,harv-Pfield,lstck

Specified (as attribute of farm system)

Specified

f(fodder N/P intake, partitioning coefficient)

f(urine/faeces N/P flux, time livestock graze off farm) f(urine/faeces N/P flux, loss coefficients)

Specified

Table 2. Soil properties for 32 farm fields in western Kenya (Kisumu, Siaya and Vihiga Districts)

0-0.15 m layer 0.15-0.50 m layer Min Median Max Min Median Max

Clay (%) 18 34 pH (1:2.5 w/v water) 5.0 5.9

Organic C a (g kg -1) 5.2 12.4 Total N b (g kg -1) 0.5 1.3 N avail, index c (mg kg -1) 3 17

Extractable pd (mg kg- 1) 1 2 Exch. bases e (cmolc kg -1) 1.7 5.2 Exch. acidity e (cmolc kg -1) 0 0

44 21 44 59

6.9 5.0 5.7 6.9

17.8 6.6 10.5 15.8

2.3 0.5 1.0 1.8 36 5 12 26

3 4 <1 1 14 13.6 1.4 5.4 11.7 1.0 0 0 1.4

aWet oxidation by acidified dichromate. bKjeldahl with sulphuric acid. CAnaerobic incubation, Page et al. (1982). dBicarbonate-EDTA extractable e KC1 extractable.

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Harvests

Inputs Inputs Farm system boundary

Fodder ~] FIELD Manure LIVESTOCK

Harvests ,,,=

MANURE L. Urine/Faeces r

fLosses ~Losses

Fig. 1. Overview of a simplified model of nutrient flows on a mixed farm. The boxes represent nutrient stocks and the arrows indicate aggregated annual flows of nutrients into or out of the farm or between stocks within the farm system. The livestock and manure stocks were assumed to be in steady state (no change in storage).

11 farmers using a checklist of questions on five top- ics: soil erosion control, fallows and rotations, man- agement of manure and organic residues, use of fer- tilizers, and knowledge of soils and (2) a formal sur- vey of 71 randomly selected farmers to quantify the main findings (Shepherd et al., 1995). Data on crop and shrub yields and nutrient contents were derived from a farmer-managed hedgerow intercropping trial (24 farms) conducted in the area (Ndufa et al., 1992). Other data were based on the literature as indicated below.

Farm size was specified as 1.0 ha. Crop dry matter production from the field was set to 1 Mg ha-1 yr-1 maize grain (1.5% N, 0.20% P) plus 0.3 Mg ha - l yr - t of field beans (3.5% N, 0.50% P). For simplicity, a harvest index of 0.5 was assumed for both crops, with 0.6% N and 0.06% P in maize stover and 0.8% N and 0.08% P in bean stover. To reflect common farming practice (Shepherd et al., 1995), we specified no fer- tilizer use, and partitioned half of the crop residues to fodder, the remainder being left in the field. Produc- tion was taken as 1 Mg ha-1 above-ground biomass of weeds, 5 Mg ha -1 of natural grass (both at 3.0% N and 0.33% P; Sands, 1983), and 5.0 Mg ha -1 of shrub, partitioned into leaf/twig biomass (0.84 of total

biomass, 1.8% N, 0.09% P) and branch biomass (0.16 of total biomass, 0.73% N, 0.06% P). The shrubs were assumed to be unimproved species that do not fix N. Upperstorey tree production was calculated assuming five seven-year-old Grevillea robusta trees were har- vested each year (Muturi and Franzel, 1992). Total dry matter per tree was 142 kg (partitioned into 0.12 leaf/twig, 0.17 branch, and 0.71 trunk) with nutrient concentrations of 1.5% N and 0.16% P in leaf/twig; 0.3% N and 0.04% P in branch; and 0.31% N and 0.06% P in the trunk (Visser, 1960). We assumed that natural grass was used for fodder, the tree trunk compo- nent for poles, the hedge and tree branch components for fuelwood, and that the leaf material was returned to the field.

For the leaching calculations average annual rain- fall was taken as 1800 mm, and the leaching coeffi- cient as 26%, corresponding with a clay content of 35-50%. Nitrogen concentrations of these soils vary widely (Table 2), but a default value of 1 g kg- 1 for the 0-0.5 m soil layer was used, with a soil bulk density of 1.3 Mg m -3. We assumed an annual N mineralization rate of 3% (Young, 1989).

In terms of the original USLE units, the rainfall erosivity (R) factor has been estimated at 500 for the

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western Kenya highlands around Lake Victoria (Wen- ner, 1981). The soil erodibility factor (K), which ranges from 0.04 on stable soils (e.g. kaolinitic Ferralsols and Nitisols), to 0.2 on less stable soils (e.g. Acrisols; Bar- ber et al., 1979), was set to 0.1. Slope gradients in the study area are generally between 0 and 10%, and a median value of 6% from the farm survey (71 farms) was used as a default value, giving a slope gradient factor of 0.56 (Wenner, 1981). The slope length fac- tor was derived from the slope length (Wenner, 1981) measured in the farm survey (average distance between soil conservation structures). This had a median value of 35 m (range 5-154 m), giving a median slope length factor of 1.26. A land cover factor of 0.3 was used to represent maize/beans intercropping (Smaling et al., 1993). The land management factor was set to 0.3 to represent slopes of 6%, with contour farming plus strip cropping (Wenner, 1981). Nutrient loss in eroded soil was calculated using the total N and P contents of the topsoil (default values were 1 g N kg-1 and 333 mg P kg-1), and an enrichment factor of 1.5 (Gachene, 1989).

For the livestock compartment; we assumed four zebu cows, with off-farm grazing restricted to 0.10 ha of roadside grass yielding 5 Mg ha -1 yr -1 with 3% N and 0.3% P (Sands, 1983), giving an annual off-farm intake of 15 kg N and 1.5 kg P. The milk partitioning coefficient was 0.20 for N and 0.31 for P, and the proportion of manure production that was deposited off-farm was set to 25%, to reflect six hours per day off-farm grazing (Shepherd et al., 1995).

Nitrogen losses during manure management may occur through volatilization, leaching, and denitrifica- tion, as well as through physical losses, but informa- tion is lacking. There is less opportunity for loss of P, although substantial amounts of P are known to accu- mulate under cattle pens with earth floors (Probert et al., 1992). Reported recovery fractions on compost- ing are in the range 0.41-0.85 for N and 0.72-0.88 for P (Kwakye, 1980; Guar et al., 1984). The propor- tion of nutrient lost during manure management was set to 0.6 for N and 0.1 for P, to reflect the generally poor standards of manure management (Shepherd et al., 1995).

Simulation of improved farm systems

We designed a series of improved farm systems to examine their potential impact on nutrient budgets.

Improved boundary planting

Improved boundary planting was simulated with Gre- viIlea robusta trees planted every 2.5 m along the exter- nal farm boundaries and along contour bunds, 35 m apart, giving 400 trees per farm. Assuming a seven- year rotation, 57 trees could be harvested each year. We also assumed that poles were harvested for con- struction or sale, branches were utilized for fuelwood, and the leaf fraction was retained in the feld. We also assumed that the additional tree growth did not affect the growth of other field or hedgerow vegetation.

Natural and Improved fallows

We simulated a natural weedy fallow compared with an improved fallow. In both systems, the field area was allocated to maize and beans in the first rains, as in the standard system. In the natural fallow the field was assumed to be under weedy fallow during the second rains. In the improved system we assumed that Ses- bania sesban was intersown with the maize and beans during the first rains, and grew as a single tree stand during the second rains (ICRAF, 1994). Nutrient cap- ture at depth was assumed to occur in the improved fallow but not in the natural fallow: the authors have observed roots of sesbania below 4 m depth within 10 months of sowing, in trials in the study area. Crop yields during the first rains were set to 0.6 times the default annual crop yield, and crop production was increased by a factor of two in the natural fallow sys- tem, and a factor of three in the improved fallow sys- tem. We assumed the natural fallow vegetation (2.5 Mg ha -1 shoot biomass, 1.5% N, 0.15% P) was burned before subsequent cropping, whereas the sesbania fal- low (3 Mg ha- 1 shoot biomass) with a leaf/twig frac- tion of 0.36 (1.8% N, 0.09% P) which is returned to the soil as green manure, and a branch fraction of 0.64 (0.73% N, 0.06% P) utilized for fuelwood (Shepherd et al., 1995).

Hedgerow intercropping

We assumed hedges of improved N-fixing shrubs (e.g. Calliandra calothyrsus) planted 4 m apart on the field area, yielding annually 5 Mg ha-l of above-ground biomass in prunings. The leaf/twig fraction was appor- tioned to the soil as green manure, while the branch fraction was allocated for fuelwood using the same nutrient partitioning parameters as in the standard sys-

tem, but the shrubs were assumed to fix N. Field erosion was set to zero.

High fertilizer inputs

Based on the results of fertilizer trials in the region (Jaetzold and Schmidt, 1982), annual fertilizer inputs of 120 kg N and 20 kg P ha-1 were assumed to produce 4 Mg ha -1 of maize grain and 400 kg ha -1 of bean seed from the field. Otherwise specifications were identical to the standard system.

Dairy-agroforestry system

The system combined boundary planting, hedgerow intercropping, moderate fertilizer inputs, and a well- managed zero-grazing dairy unit. The field area was modelled as 50% under napier grass, and 50% under a high input maize/beans intercrop as specified above. We assumed that the napier received recommended fer- tilizer rates of 100 kg N plus 20 kg P ha -1 and yielded 25 Mg shoot dry matter ha -1 at 1.5% N and 0.30% P (Bayer, 1990). The whole field area was assumed under hedgerow intercropping with the leaf/twig frac- tion allocated to fodder. Boundary planting was spec- ified at 200 trees per farm, half the density used in the improved system. We simulated a zero-grazing unit with four pure-bred cows, utilizing of all the crop stover as fodder. Minerals were supplied at 20 kg yr-1 per cow containing 11.8% P, but the legume fodder was used as a substitute for concentrates. The milk paititioning coefficient was set to 0.39 for N and 0.45 for P. Good manure management was assumed, giving a manure loss fraction of 0.2 for N and 0.1 for P.

Simulation results

Model limitations

The modelling approach used has several limitations. Firstly, the static nature of the model prevents an assessment of the long-term effects of nutrient budgets on nutrient availability and plant productivity. Sec- ondly, there are major uncertainties in the estimates of soil N loss by leaching and during manure manage- ment, and yet these constitute the main sources of N loss from the farm system. Thirdly, several feedback mechanisms can not be accounted for, like reductions in N leaching through increased N uptake, and the possible effects of quality of organic inputs on micro-

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bial activity and immobilization. Despite these limita- tions, the results illustrate important potential effects of agroforestry systems on soil nutrient flows and budgets (Table 3), and reveal some critical knowledge gaps.

Potentially critical feedback mechanisms with respect to the design of dynamic models include: (1) plant productivity determined by N and P availabili- ty, (2) competition between plant types for available nutrient, (3) N leaching modified by plant N uptake, (4) uptake of available subsoil N determined by amount of fine root in the subsoil relative to the topsoil, and plant N demand, (5) biological N fixation reduced at high N availability, and (6) decomposition rates of fresh organic matter reduced if there is insufficient N or P relative to carbon to meet microbial demand.

Nutrient losses

N leaching from the field was the major loss pathway from the farm system (Table 4), with a range of 51-82 kg ha -1 yr -1 for the different farm systems. The loss- es increased to 68-139 kg ha -1 yr -1 when N release from decomposing organic residues was included in the leachable N pool (Table 5). Thus, the risk of leach- ing loss is likely to increase with the use of higher rates of inorganic N fertilizers and organic N applications, as farming systems intensify. In practice, the amount of N leached below 0.5 m would be expected to be less in the more productive systems, where there is a larger plant sink for N uptake, than in the systems with lower productivity, but there was insufficient knowl- edge to include this interaction simply in the model. However, the N losses could potentially range from half to twice these values on different farms, on the basis of the range in soil N contents (Table 2). More- over, if total N in the 0-0.15 m layer, rather than in the 0-0.5 m layer, is used as the basis for predicting miner- al N, the losses would approximately be half. Indeed, in these soils there appears to be substantial potential for mineralization in the subsoil. Based on laborato- ry incubations, the median N availability index in the 0.15-0.5 m layer was 1.2% of total N (by weight), almost the same as in the topsoil at 1.3% of total N.

It is surprising that despite more than 70 years of agricultural research in the East African Highlands, hardly any data are available on mineralization of N at different depths in the soil, or on rates of N leach- ing or denitrification. Earlier studies on mineralization were confined to the topsoil (Birch, 1958; Semb and Robinson, 1969). However, data from 13 sites in East Africa (Semb and Robinson, 1969) showed no signif-

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Table 3. Summary of main features of improved farm systems compared with the standard farm system and their principal effects on individual nutrient flows (+ denotes an increase, - denotes a decrease in flux)

System type Main difference from standard farm system Main effect on nutrient flow relative to standard farm system

Boundary planting Addition of trees on farm boundary Deep N uptake (+) Wood harvests (+)

Natural fallow Grain harvest (+) N volatilization (+)

Improved fallow Biological N fixation (+)

Hedgerow intercropping

High fertilizer inputs

Dairy-agroforestry

Deep N uptake (+) Grain and fuelwood harvests (+) Biological N fixation (+) Deep N uptake (+) Fuelwood harvest (+) Erosion (-) Grain harvest (+) N leaching (+) N and P fertilizer inputs (+) Biological N fixation (+) Deep N uptake (+) N and P fertilizer inputs (+) P mineral inputs (+) Grain,wood and milk harvests (+) N leaching (+) Erosion loss (-) Fodder and manure fluxes (+)

Field under weedy fallow in second rains Burning of weeds during fallow clearance Field under N-fixing shrubs in second rains

N-fixing hedgerows introduced into field for green manure production

N and P fertilizers applied to field

N-fixing hedgerows introduced into field for fodder production Half of crop land allocated to fodder grass N and P fertilizers applied to field Zero-grazing with improved dairy cows Mineral supplementation of livestock Addition of trees on farm boundary

icant difference in the ratio of N availability index to

total soil N content for the 0 -20 cm layer (N content range 0.2-3.8 mg kg - l ) compared with the 20-40 cm layer (0.02-0.28 mg k g - l ) . Studies at over ten loca- tions in East Afr ica have reported high concentrations of nitrate-N (> 100 mg kg -1) in subsoils at depths of 1-2 m, in situations with a low sink for N uptake, most notably under N-ferti l ized crops that are deficient in P, and under bare fallows (e.g. Mills, 1953; Kabaara, 1964; Robinson et al., 1967). In a recent study on N balances in coffee plantations on Nitisols, at Ruiru in Kenya (average annual rainfall 1058 mm), a nitrate-N accumulation of 2.2 Mg ha-1 at 1 to 5 m soil depth was found, corresponding with a layer of high positive charge (Michori, 1993). Total nitrate-N accumulation to 25 m depth was 3.3 Mg ha -1. 15N studies estimat- ed that 22% of applied fertilizer N was leached below 0.6 m depth within the year of application, but none beyond 150 cm. Another study with maize and beans on an upland soil gave similar results with 12% of lSN fertilizer leached below 30 cm, but none below 150 cm (Ssali, 1990). In Michori ' s study, however,

a further, unaccounted loss, of 34% was attributed to denitrification and volatil ization (Michori, 1993). More significantly, the annual amount of N leached below 60 and 150 cm depth was estimated at 132-155 and 155-177 kg h a - l respectively, on the basis of soil solution sampling. It is apparent that the tSN fertiliz- er recovery studies did not account for the additional leaching of mineralized N down the soil profile and the movement of fertilizer-derived N applied in previous years. Compared to these results our model may have underestimated N losses.

A second potentially important loss pathway for N is associated with manure management, especially in the dairy-agroforestry system characterized by high manure fluxes. Reducing standards of manure manage- ment has larger effects on final manure N in the dairy than in the standard system. For example, increasing the manure-N loss fraction by 0.1 results in a decrease in the amount of manure N applied to the field of 19 kg N h a - 1 y r - 1 in the dairy-agroforestry system, but only of 4 kg N ha -1 yr -z in the standard system. Howev-

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Table 4. Estimated soil N budgets for the field soil in different farm systems (kg N ha -1 yr - l )

N flow Farm system

1 2 3 4 5 6 7

Atmospheric deposition 6 6 6 6 6 6 6

Asymbiotic fixation 4 4 4 4 4 4 4

Biological N fixation 7 7 9 47 54 10 52

Deep uptake 6 32 2 36 50 6 61

Fertilizer application 0 0 0 0 0 120 120

Sum field inputs 23 49 21 93 114 146 243

Sum livestock inputs a 15 15 15 15 15 15 0

Grain harvest 25 25 31 46 26 74 37

Fuelwood harvest 1 5 0 45 11 1 12

Polewood harvest 2 17 2 2 2 2 8

Sum field harvests 28 47 32 92 38 77 58

Sum livestock harvests b 10 10 10 11 10 12 111

Leaching 51 51 51 51 51 82 82

Erosion 11 11 I1 11 0 11 0

Volmilization 0 0 22 0 0 0 0

Sum field losses 62 62 84 62 51 93 82

Off farm manure deposition 10 10 10 10 10 12 0

Manure managernent losses 18 18 18 19 18 21 33

Sum livestock losses 28 28 28 29 28 33 33

Fodder to livestock 34 34 34 38 34 44 278

Manure to field 12 12 12 13 12 14 133

Field balance -89 -83 -118 -86 +3 -54 -41

Farm system: 1 = standard; 2 = boundary planting; 3 = natural fallow; 4 = improved fallow; 5 = hedgerow intercropping; 6 = high fertilizer inputs, and 7 = dairy- agroforestry system '~ Off-farm grazing only bMilk only

Table 5. Estimated soil N leaching loss and N balance for the field soil in different farm systems (kg N ha -1 yr - l ) with organic returns added to the leachable N pool

N flow Farm system

1 2 3 4 5 6 7

Leaching 69 77 70 77 90 107 139

Field balance -107 -109 -138 -112 -36 -78 -98

Farm system: 1= standard; 2 = boundary planting; 3 = natural fallow; 4 = improved fallow; 5 = hedgerow intercropping; 6 = high fertilizer inputs, and 7 = dairy-agroforestry system

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er, data on losses of N during manure management on smallholder farms are lacking (Probert et al., 1992).

The model demonstrates that few pathways exist for P loss from the farm system: the largest potential loss is through erosion (Table 6).

Nutrient inputs

Biological nitrogen fixation constitutes an important potential input in the agroforestry systems largely based on N-fixing shrubs (systems 4, 5 and 7 in Table 4) amounting to about 50 kg N ha-1 yr-1. However, the importance of biological N fixation will be reduced, when large quantities of mineral N are available (Sin- gleton et al., 1991).

N uptake from deep soil layers is also a poten- tially important input (36 to 61 kg N ha -1 yr -1) in systems with high levels of production of deep-rooted trees and shrubs (systems 2, 4, 5 and 7 in Table 4). Agroforestry may have potential for increasing total use of N in the whole soil system, by both intercep- tion of leaching N during the season, and recovery of mineral N leached into the subsoil in previous seasons. Indeed, earlier research in the region has shown that deep-rooted grasses (Pennisetumpurpureum and Chlo- ris gayana) can extract mineral N to 2.7 m depth (e.g. Simpson, 1961; Kabaara, 1964; Jones, 1968; Brunt, 1976). This led to an early recommendation of rota- tion of deep-rooted leys with shallow-rooted crops to improve N cycling (Jones, 1968), however, this rec- ommendation has not been widely adopted, apart from the use of natural fallows of weeds.

Fertilizer provided the only significant input of P into the farm systems, in absolute terms, except for mineral supplements to livestock in the dairy- agroforestry system (Table 6).

Nutrient harvests

Nutrient exports in harvests were substantially high- er in the agroforestry systems than in the unimproved systems. Total harvested N (kg ha-1 yr-1) from the field and livestock was 38 for the standard system, 57 for improved boundary planting, 103 for improved fal- low, and 168 for the dairy-agroforestry system (Table 4). Total harvested P ranged from 6 kg ha -1 yr -1 in the standard system to 29 in the dairy-agroforestry system (Table 6). Nutrient export in harvests in the improved fallow system was substantially higher com- pared with the standard system or the natural fallow system, because of a combination of increased crop

yields and high offtake in fuelwood from the tree fal- low. The high amounts of N and P harvested in milk, as compared to grain, in the dairy-agroforestry sys- tem are also worth noting. The increase in harvested nutrient with hedgerow intercropping compared with the standard system, was due solely to the additional fuelwood harvested, as no effect of the hedgerows on crop productivity was assumed.

Nutrient budgets

The annual N balance for the field soil in the different systems ranged from +3 to - 118 kg N ha -1 (Table 4), or - 3 6 to -138 kg ha-1 when organic N returns were added to the leachable N pool (Table 5). The field N balance for the standard system of - 8 9 kg ha -1 yr -1 is of similar magnitude as estimates for maize-beans systems in Kisii District in western Kenya of - 8 0 kg ha- 1 yr- 1 (Smaling et al., 1993), in contrast with posi- tive balances of> 300 kg ha- 1 yr - 1 on high input dairy farms in Europe (Frissel, 1977). The agroforestry sys- tems did not significantly reduce the magnitude of the N deficits, because most of the additional input through biological N fixation and deep N uptake was exported from the farm system in the additional hatvests. The only exception was the hedgerow intercropping sys- tem, where large quantities of organic N were returned to the soil rather than being removed from the sys- tem, which resulted in a positive balance of 3 kg N ha-1 yr-1. However, green manuring practices have not been widely adopted by smallholders.

The annual P balance for the field soil in the dif- ferent systems ranged from - 1 5 to +5 kg ha -I yr -1 (Table 6). The deficits were larger in the improved fallow and boundary planting systems than in the stan- dard system because of the increased harvest of P in wood products in the agroforestry systems. The dairy- agroforestry system required about 20 kg P ha -1 yr -1 to maintain a zero soil balance, but in practice, higher rates of P would be required initially to achieve ade- quate levels of available-P, because of the high sorp- tion capacity of these soils, which may reach 400 mg P kg-1 soil at soil solution concentrations of 0.2 mg P 1-1 (Okalebo, 1987).

Conclusion

The simulations revealed some important concerns and identified several priorities for research on nat-

97

Table 6. Estimated soil P budgets for the field soil in different farm systems (kg P ha- 1 yr -1)

P flow Farm system 1 2 3 4 5 6 7

Atmospheric deposition 1.0 1.0 1.0 1.0 1.0 1.0 1.0 Fertilizer application 0 0 0 0 0 20.0 20.0 Sum field inputs 1.0 1.0 1.0 1.0 1.0 21.0 21.0

Off-farm grazing 1.5 1.5 1.5 1.5 1.5 1.5 0 Mineral supplement 0 0 0 0 0 0 9.6 Sum livestock inputs 1.5 1.5 1.5 1.5 1.5 1.5 9.6

Grain harvest 3.5 3.5 4.2 6.3 3.5 10.0 5.0 Fuelwood harvest 0.1 0.6 0 3.9 1.0 0.1 0.3 Polewood harvest 0.3 3.4 0.3 0.3 0.3 0.3 1.7 Sum field harvests 3.9 7.5 4.5 10.5 4.7 10.4 7.0

Sum livestock harvests a 1.6 1.6 1.6 1.7 1.6 1.9 21.9

Sum field losses b 3.7 3.7 3.7 3.7 0 3.7 0

Off farm manure deposition 0.9 0.9 0.9 1.0 0.9 1.1 0 Manure management losses 0.3 0.3 0.3 0.3 0.3 0.3 2.7 Sum livestock lasses 1.2 1.2 1.2 1.2 1.2 1.4 2.7

Fodder to livestock 3.7 3.7 3.8 4.1 3.7 4.7 39.2

Manure to field 2.4 2.4 2.5 2.6 2.4 2.9 24.1

Field balance -7.9 -11.5 -8.6 -14.7 -5.0 +5.0 -1.0

Farm system: 1 = standard; 2 = boundary planting; 3 = natural fallow; 5 = hedgerow intercropping; 6 = high fertilizer inputs, and system ~Milk only bErosion only

fallow; 4 = improved 7 = dairy-agroforestry

ural resource management in the East African High- lands.

First, intensification of agroforestry systems on smallholder farms for production purposes (fuel, poles, timber, milk) is unlikely to reverse current trends in soil nutrient depletion, and could accelerate depletion if external nutrient inputs are not supplied.

Second, the potential for rapid loss of soil N in culti- vated soils, through rapid mineralization of soil organ- ic matter and large N leaching losses, poses a major economic-ecological concern for the region: because of decreased soil productive capacity and the risk of nitrate pol lut ion of water supplies.

Third, this analysis suggests that there is potential to substantially reduce N leaching losses and increase overall N-use efficiency in highland farming systems.

This can be achieved through strategies that maximize the interception of N, both within the crop root zone (e.g. by alleviating P deficiencies in crops), and in the subsoil by increased use of deep-rooted plants. The opportunity for increasing N-use efficiency through deep N uptake, as well as environmental concerns over nitrate pollution of water supplies, suggest that research on N capture by trees in agroforestry systems should receive high priority in the East African High- lands:

Fourth, there is a need for the development of farm-scale dynamic nutrient budget models to better interpret the implications of negative nutrient balances for the sustainability of farming systems. Measure- ments of N mineralization in different soil layers, and N losses by leaching and denitrification are urgently

98

required to support the development of such models. Also, measurements of nutrient losses during manure management are needed, particularly in the context of intensive dairy fanning with high manure fluxes.

Acknowledgements

We acknowledge the support of the on-farm tech- nical staff of the KEFRI/KERI/ICRAF Agroforestry Research Project at Maseno, the laboratory technical staff of KARI at Maguga, and Paul Smithson and his staff at the ICRAF laboratory at Machakos, Kenya. We thank the Rockefeller Foundation and SIDA for finan- cial support, and Drs J Odera and D Nyamai of KEFRI for facilitating collaborative links between the institu- tions involved. We also thank Dr RJ Buresh (ICRAF) and Professor MJ Swift (TSBF) for their helpful com- ments on the manuscript.

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