The impact of land use on soil carbon in Miombo Woodlands of Malawi

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Forest Ecology and Management 203 (2004) 345–360

The impact of land use on soil carbon in Miombo

Woodlands of Malawi

Sarah M. Walkera,*, Paul V. Desankerb,1

aDepartment of Environmental Sciences, University of Virginia, Clark Hall,

291 McCormick Road, Charlottesville, VA 22904, USAbPenn State University/Geography, 202 Walker Building, University Park, PA 16802, USA

Received 16 February 2004; received in revised form 13 August 2004; accepted 13 August 2004

Abstract

In the Miombo Woodlands Region of south-central Africa, it is estimated 50–80% of the total system’s carbon stock is found

in the top 1.5 m belowground. Deforestation and rapid population growth rates have led to reduced fallow periods and

widespread land degradation in the south-central Africa area of the Miombo Woodlands. The impact of this land use conversion

on belowground carbon and nitrogen stocks within the Miombo Woodlands has not been examined extensively in the past. We

addressed how the soil carbon profile reacts to conversion to agriculture, the continuation of agriculture, and the ability of the soil

carbon budget to recover following abandonment within the Chimaliro Forest Reserve and surrounding villages in Kasungu,

Malawi. Protected natural Miombo Woodlands sites, agricultural fields of increasing ages, and fallow fields of increasing ages

were sampled. Surface carbon levels in Miombo soils varied from 1.2 to 3.7%. Agricultural soil carbon was significantly

depressed with surface layers ranging from 0.35 to 1.2% carbon. Unexpectedly, fallow carbon and nitrogen levels continued to

be significantly repressed (surface soils 0.65–2.3% C), pointing out the possible unsustainability of the current agricultural

management cycle dominant in the area. On average, agricultural soils contain 40% less soil carbon than the natural Miombo

Woodlands. Soil carbon declined logarithmically with depth within all land use types. Clay content was significantly positively

correlated with soil carbon in the top 40 cm and therefore areas of higher clay content contained elevated carbon levels.

Although a common attribute to many agricultural systems, bulk densities were not significantly altered by land use changes.

# 2004 Elsevier B.V. All rights reserved.

Keywords: Miombo; Dry tropical forest; Soil carbon; Shifting-cultivation; Agriculture; Land use change

* Corresponding author. Tel.: +1 434 924 4303;

fax: +1 434 982 2137.

E-mail address: [email protected] (S.M. Walker),

[email protected] (P.V. Desanker).1 Tel.: +1 814 865 1748; fax +1 814 863 7943.

0378-1127/$ – see front matter # 2004 Elsevier B.V. All rights reserved

doi:10.1016/j.foreco.2004.08.004

1. Introduction

Recently there has been a growing interest in

understanding the carbon stocks of each ecosystem

worldwide. As negotiations of the Kyoto Protocol

progress, knowing the size of these carbon stocks and

the factors that impact them is becoming economically

.

S.M. Walker, P.V. Desanker / Forest Ecology and Management 203 (2004) 345–360346

important to countries. Estimates of aboveground

biomass stocks exist for most ecosystems, however

carbon belowground in roots and soil is less well

characterized. The ancient soils of the Basement

Complex in south-central Africa covered by the

Miombo Woodlands present local farmers with

nutrient poor soils and crop yields in this part of

Africa are some of the lowest worldwide. Currently

this region is enduring extensive deforestation and

land degradation owing to population increases,

escalating agricultural production, and woodfuel

demands. Much of the newly cropped land is

unsuitable for agriculture and degrades quickly,

thereby forcing the farmer to convert even more land

to agriculture. The impacts of agricultural conversion

and shifting-cultivation on nutrient cycling and

ecological health, however, have not been studied

extensively in the Miombo Woodlands Region.

Owing to slow soil organic matter turnover rates, as

compared to aboveground vegetation, soil carbon

levels do not react as quickly to changes in land use.

Due to this property, soil carbon levels measured

through time can establish the long-term productivity

and possible sustainability of that land use system. In a

nutrient poor system, soil organic matter (SOM) can

play an important role in the stability, quality, and

Scheme 1. Location of study site, Chimaliro Forest Reserve in Malaw

fertility of the soil. Farmers and land use planners are

therefore interested in land use management that will

enhance soil carbon levels.

In most ecosystems worldwide the conversion of

land to agriculture will drastically change natural

internal nutrient cycling and nutrient loss will exceed

nutrient gain. Under agriculture, biomass litter inputs

become minimal and tillage will split up soil

aggregates, increasing decomposition (Allen, 1985;

Tate, 1987). Soil carbon is reduced most drastically in

the plow layers of the soil. Generally, as the labile

carbon from the previous land use is decomposed,

agricultural conversion results in soil carbon loss that

tends to be rapid in the years immediately after

conversion. The rate of loss then diminishes over time

and Soil Organic Carbon (SOC) may reach a new

equilibrium (Houghton et al., 1983; Schlesinger, 1986;

Davidson and Ackerman, 1993).

As is common in drier systems (Woomer et al.,

1997), in the Miombo Woodlands ecosystem of south-

central Africa roughly 60% the total carbon stock is

found belowground (Campbell et al., 1998a,b). The

range of soil carbon levels across the Miombo region

and the main environmental regulators are somewhat

known, however there has been little research on how

land use conversion will alter these carbon stocks. This

i, and the distribution of the Miombo Woodlands (White, 1983).

S.M. Walker, P.V. Desanker / Forest Ecology and Management 203 (2004) 345–360 347

study builds on our understanding of how the

dominant land use pattern impacts soil carbon levels

and the soil carbon vertical structure by comparing soil

carbon stocks within the dominant land cover types:

Miombo Woodland, agricultural fields, and fallow

fields. Differences in soil carbon stocks as agricultural

fields increased in age are explored by sampling fields

of differing ages. Likewise, the possible recovery of

soil carbon stocks within abandoned fields reverting to

woodlands is estimated in fallow fields of increasing

age.

2. Methods

2.1. Study area

The Miombo region spans 2.8 million km2 of

south-central Africa (Scheme 1). Precipitation ranges

from 650 to 1500 mm and 95% of annual precipitation

occurs during the hot wet season (Campbell, 1996;

Desanker et al., 1997). The natural ecosystem is an

open woodland (20–60% canopy cover) with a grass

understory (Trapnell, 1959; Rodgers, 1996). The

aboveground biomass of the Miombo Woodlands

ranges from 37,000 to 95,000 kg/ha (Malaisse et al.,

1975; Chidumayo, 1990; Tietema, 1993; Chidumayo,

1995; Campbell et al., 1998a,b). On average, fires burn

the understory every 3 years across the Miombo and

savannas and therefore greatly impact the vegetation

dynamics of the system and biomass litter levels

reaching the soil (Boaler, 1966). Most trees are able to

resprout if cut or burned and this allows trees to persist

within agricultural fields for many years and regrow

from rootstocks if a field is left fallow (Chidumayo,

1997).

The current study took place within the Chimaliro

Forest Reserve (12.5S, 33.55E) near Kasungu in

Malawi and surrounding villages in coordination with

the Forestry Research Institute of Malawi (FRIM) and

the Department of Forestry of Malawi (Scheme 1).

The area receives roughly 1000 mm of precipitation a

year (Steve Makungwa, personal communication, July

1999). The tall grass understory within the reserve is

collected for thatching during the dry season followed

by controlled burning by the forest reserve guards.

Village chiefs control public land and field allocation

is relatively stable. Although varying between farm-

ers, many farmers keep a section of allocated land

unplowed for use as a firewood and pole resource.

Some farmers rotate this fallow area more frequently

than others. This fallow/degraded woodland is the

most common form of Miombo Woodlands now

occurring in Malawi.

2.2. Field methods

The dominant land use types were identified in the

area in coordination with FRIM, Malawi Department

of Forestry employees, and local farmers. Sites were

selected randomly within each land use type

stratification. Sampling occurred at 5 sites within

the Chimaliro Forest Reserve, 11 agricultural fields,

and 6 fallow fields. General site characteristics were

recorded. The land use history of each site was

documented by interviewing either the forest guard or

the owner of the field. At each site, a random number

was generated for the number of steps into a site and

the direction to be walked. Once at this point, four

1 m2 plots were laid out 20 m away east, west, north

and south from the central point. All vegetation within

the 1 m2 plot was cut off at its base and weighed.

Surface litter was also removed and weighed. Soil and

roots samples were collected in a 1 m2 pit. Soil

samples were taken at the following depths: 0–10 cm,

10–20 cm, 20–40 cm, 40–60 cm, 60–100 cm, 100–

150 cm.

At all depths, soil was taken from each section of

the pit and placed in a large basin, thoroughly mixed,

and a 500 g subsample of soil collected. At sites in

which no roots were found four auger cores were taken

within the pit to collect a sample for the 60–100 and

100–150 cm. Bulk density samples were taken at each

depth using a known volume metal container. Only

one set of bulk density samples were taken per site. All

samples were air dried.

2.3. Laboratory methods

Soil texture measurements were performed on soil

from one pit per site, on depths 0–10, 20–40, and 60–

100 cm. Bulk density measurements were performed

at the University of Virginia by drying the soil at

105 8C for 2 days and then reweighing the samples.

Bulk density samples for five sites were lost in

shipping samples to the USA, therefore at these sites


bulk density measurements from a site with similar

land use were used as estimations in data analysis. Soil

samples were sieved to 2 mm, soaked in 10% HCl to

remove any carbonates from the soil and then put in a

45 8C oven until dry. Soils were then ground and

analyzed for carbon and nitrogen using a Carlo Erba

elemental analyzer. For each sample, the elemental

analysis was repeated three times and the average C

and N values used in the analysis. Carbon and nitrogen

densities were calculated by multiplying the soil

concentrations by the bulk density (% C � BD).

Stocks of carbon and nitrogen were calculated by

multiplying the carbon or nitrogen density by the

depth of soil sampled (% C � BD � depth).

2.4. Statistical analysis performed

All statistical measures were completed using SAS

(SAS Institute, 1989). Carbon and nitrogen values

were log transformed for all future statistical tests in

order to meet normality assumptions of statistical

tests. The variables included in the analysis were: log

carbon, log nitrogen, field age, bulk density, % clay, %

silt, and % clay + % silt.

Comparisons of data across land uses were

completed using PROC GLM, an analysis of variance

procedure in SAS (SAS Institute, 1989). Site was

nested within land use (LU) type and depth was nested

within site and LU type. Where appropriate, % clay, %

silt, % clay + % silt, and/or BD were added as

covariates. Within the agricultural sites, the ages of the

fields were categorized into three groups: four young

(1–5 years), four medium (10–20 years), and three old

(30–40 years).

A suite of equation types was fitted to the carbon

and depth measurements. A log carbon–log cm

regression best represented the relationship. A

regression was then performed on all the data and

one overall representative equation was developed by

including land use type dummy variables and (land use

type dummy variable) � (log cm) variables. Regres-

sion equations were also performed for each land use

type and for each individual site. The regression

equations for each type and for each of the sites were

then compared to the overall equation by comparing

the intercept, slope, and both, of each equation to the

overall equation. This was also done between the site

equation and the type equation and the overall

equation determined for this study. Additionally,

stepwise multiple regressions on both log % carbon

and log carbon density were completed for each land

use type. Soil texture, bulk density, depth, and age of

agricultural field were included in the stepwise

regressions.

Because of differences in bulk density, the mass of

soil within a particular depth range will not be the

same across all areas. Therefore, a number of

researchers have suggested recalculating carbon

volume estimates based on the mass of soil to a

depth within the natural land use type to correct for

this difference (Mann, 1986; Brown and Lugo, 1990b;

Neill et al., 1997). A Miombo Woodlands average bulk

density was found for each depth and this was

multiplied by the width of each sampling depth. This

Miombo mass of soil for each depth was then

multiplied by the % carbon found at each depth for

each site. This then produced a ‘mass corrected’

volume of carbon for each site. A t-test was performed

to compare this volume with the observed volumes

and an ANOVA was completed to examine differences

between land use types using this carbon volume

estimate.

3. Results

3.1. Explanation of sites

The five Miombo woodland sites measured

contained mixed aged trees that did not show signs

of coppicing or firewood collection. Grass grows to

about 1 m in height and is often collected for thatch at

the end of the dry season. Maize is the dominant crop

sown at the agricultural sites but other crops included

tobacco, millet and groundnuts. Fertilizers were only

used when tobacco was planted and would be applied

at very small levels due to the substantial cost for the

farmer. Age of agricultural field in 11 sites measured

ranged from 1 to 30 years of continuous agriculture.

Within the four young fields (less than 5 years),

coppicing trees less than 0.5 m in height were in

abundance around the field. In the three fields

cultivated for more than 30 years, there were very

few trees still coppicing. The six fallow sites contained

a mix of both coppicing trees and trees growing from

seed. These are areas within the farmer’s allocated


land that the farmer has stopped farming in the past

and uses as an area for firewood and pole collection

and possibly for grazing. Therefore, the areas are not

recovering naturally but are instead being impacted at

a relatively constant low level.

3.2. Changes in soil texture and bulk density within

a profile and differences across land use types

Across the sites, clay content ranges 12–45% clay

at the surface (Table 1). On average, the clay content is

30% lower in the top 10 cm than the depths below

20 cm. This downward eluviation of clay to the

subsurface and surface kaolinate decomposition fits

well with the ferrasol soil type FAO map classification

(FAO–UNESCO, 1988). Although the sites span a

range of soil textures, soil texture did not differ

significantly between land use types for each depth.

Clay content is significantly correlated with bulk

density measurements. However, the correlation is

only strong in the top layers of the agriculture and

fallow land uses. The bulk density of the agricul-

tural sites were not significantly different from the

Miombo sites, however fallow sites have signifi-

cantly higher BD levels than Miombo in the top 20 cm

(Table 1).

3.3. Changes in soil nutrients within a profile

After exploring a large number of equation types, a

log carbon–log cm equation was found to best

represent soil carbon and soil nitrogen with depth

(Fig. 1). At all sites soil carbon is greatest at the

surface and then declines rapidly with depth. Below

60 cm, carbon and nitrogen values change only

slightly with depth. The variance between sites of

the same land use and within a site is also highest at the

surface and values become very similar by 40 cm

(Table 1; Fig. 1) Within the top 1.5 m, roughly 25% of

the soil carbon is stored in the surface layer (Fig. 2a).

The top 30 cm contains about 50% of all the carbon

found to a depth of 1.5 m. Nitrogen is not as dominant

at the surface, nonetheless about 20% of nitrogen is

found above 10 cm and about 10% between 10 and

20 cm (Fig. 2b).

The carbon to nitrogen ratio of the soil generally

declines slightly with depth. On average the C:N ratio

is about 16 at the surface and declines to 10 at depth

(Table 1). The 10–20-year-old agricultural fields have

the lowest C:N ratios. In agricultural fields, the oldest

fields have the highest C:N ratio, evidencing the

reduction in nitrogen through the years. These oldest

fields have had no chemical fertilizer additions.

3.4. Factors influencing carbon and nitrogen

content levels

Clay, silt, and BD are all correlated with % carbon

of the soil. Clay content impacts carbon levels most

strongly in the surface layers and significantly to

40 cm (Fig. 3). Clay dominated soils and soils with

lower bulk densities have the highest carbon levels.

Age of the agricultural field is correlated with carbon

as well as nitrogen density above 40 cm. Medium and

young aged fields are not significantly different from

each other. Young fields differ significantly from the

older fields to a depth of 60 cm. However there is not a

gradual decline in carbon levels through time, with

some younger fields having the same level of carbon as

older fields (Fig. 4).

The stepwise multiple regression constructed using

all data points was able to explain a substantial amount

of the variation in carbon levels (R2 = 0.778). Of

course, depth explained the majority of the variation

(R2 = 0.613) and was the only substantial contributor.

% Clay, % silt, and BD were all included as significant

contributions however the partial R2 was very small

for BD. Within the Miombo land use multiple

regression, depth accounted for a much higher

proportion of the variation than other land use type

equations. In contrast, clay accounted for 19% of the

variation in the fallow sites. For the agricultural sites,

age was included as a variable in the multiple

regression although it only explained 2% of the

variation.

3.5. Differences in carbon and nitrogen content

between different land use types

Because of the correlation of clay, silt, and BD with

carbon and BD and clay with each other, these

variables were added to the analysis as covariates.

However, the inclusion of the covariates did not alter

the statistical results. The observed carbon and

nitrogen levels of Miombo sites are significantly

different from all other land use types to a depth of


Table 1

Average values for each land use type

Land use type Depth

(cm)

% C % N C:N C density

(g/cm3)

N density

(g/cm3)

BD

(g/cm3)

% Clay + silt

Miombo ave. 0–10 2.31 0.138 16.40 0.0266 0.00160 1.19 s 46 bb

(S.D.) 1.052 0.055 1.62 0.0111 0.00058 0.111 16.8

Miombo ave. 10–20 1.16 0.078 14.58 h 0.0134 0.00091 1.22 t u

(S.D.) 0.416 0.021 2.40 0.0049 0.00024 0.089

Miombo ave. 20–40 0.62 0.050 12.47 i 0.0073 0.00058 1.20 v 67 cc

(S.D.) 0.207 0.009 2.95 0.0026 0.00011 0.062 18.2

Miombo ave. 40–60 0.43 0.037 11.66 j 0.0054 0.00046 1.29 x

(S.D.) 0.167 0.008 3.79 0.0024 0.00011 0.119

Miombo ave. 60–100 0.24 0.026 9.57 k 0.0029 0.00031 1.24 y 59 ee

(S.D.) 0.068 0.005 3.28 0.0008 0.00006 0.088 18.4

Miombo ave. 100–150 0.15 a 0.020 f 8.22 l 0.0019 m 0.00024 q 1.32 z aa

(S.D.) 0.051 0.006 2.71 0.0006 0.00007 0.168

Agric. ave. 0–10 0.87 b 0.058 g 14.62 0.0109 n 0.00075 r 1.31 s 44 bb

(S.D.) 0.349 0.022 2.71 0.0042 0.00024 0.127 8.5

Agric. ave. 10–20 0.50 c 0.038 12.89 h 0.0061 0.00047 1.23 t

(S.D.) 0.198 0.011 3.37 0.0024 0.00014 0.106

Agric. ave. 20–40 0.34 d 0.033 11.13 i 0.0041 o 0.00039 1.20 v 54 cc dd

(S.D.) 0.146 0.014 3.82 0.0018 0.00016 0.089 9.7

Agric. ave. 40–60 0.24 e 0.026 9.96 j 0.0028 p 0.00031 1.19

(S.D.) 0.075 0.012 2.83 0.0010 0.00014 0.059

Agric. ave. 60–100 0.18 0.022 8.76 k 0.0023 0.00027 1.25 y 57

(S.D.) 0.113 0.010 3.47 0.0014 0.00012 0.043 13.8

Agric. ave. 100–150 0.13 a 0.022 f 6.83 l 0.0014 m 0.00026 q 1.22 z

(S.D.) 0.088 0.011 3.62 0.0011 0.00013 0.059

Fallow ave. 0–10 1.03 b 0.058 g 17.72 0.0133 n 0.00074 r 1.37 s 37 bb

(S.D.) 0.69 0.036 2.72 0.0078 0.00040 0.106 15.7

Fallow ave. 10–20 0.66 c 0.035 20.57 0.0085 0.00046 1.38 u

(S.D.) 0.495 0.025 10.11 0.0059 0.00030 0.111

Fallow ave. 20–40 0.38 d 0.024 16.54 0.0045 0.00029 1.29 v 47 dd

(S.D.) 0.205 0.013 5.41 0.0022 0.00014 0.121 17.2

Fallow ave. 40–60 0.25 e 0.017 16.61 0.0032 o 0.00021 1.27 x

(S.D.) 0.237 0.015 6.47 0.0031 0.00020 0.021

Fallow ave. 60–100 0.14 0.012 18.62 0.0019 p 0.00015 1.30 y 44 ee

(S.D.) 0.059 0.007 16.19 0.0008 0.00009 0.055 16.8

Fallow ave. 100–150 0.10 0.012 11.73 l 0.0012 0.00016 1.33 aa

(S.D.) 0.070 0.011 34.91 0.0010 0.00015 0.055

Like letters signify no significant differences between land uses for that depth.

100 cm. Using observed values, if each depth is

analyzed separately, observed % C and carbon density

of agriculture and fallow sites are not significantly

different at most depths (Table 1).

If the slope and intercept of the fitted logarithmic

regression equations are compared to each other, about

half of the agricultural site regression equations were

not significantly different from the overall equation.

The slopes of the regression equations for most sites

were similar but the intercepts were not.

Although the amount of carbon in the soil is

different between land uses, the proportional distribu-

tion of carbon throughout the profile is not sig-

nificantly different (Fig. 2a). However, the proportion

of carbon in the top 10 cm is significantly different

between Miombo and agriculture at a 0.09 p-value,

displaying the lower proportion of carbon found in

surface agricultural soil. Nitrogen in agriculture is

lower proportionally at the surface compared to fallow

at a p-value of 0.07 (Fig. 2b).


Fig. 1. Land use type regression of carbon and nitrogen density with depth (bars signify standard error).


Fig. 2. Proportional distribution of carbon and nitrogen within each depth to 1.5 m (bars signify standard error): (a) carbon; (b) nitrogen.

When the carbon is summed for the entire profile,

the differences between each land use type become

more apparent. The volume of carbon for the entire pit

in Miombo sites is significantly different from

agricultural and fallow sites (Table 2; Fig. 5a).

Nitrogen volumes are even more significantly differ-

ent from each other (Table 2; Fig. 5b). Using the ‘mass

corrected’ values of carbon volumes, significant

differences still exist between the land use types

(Table 2) except agriculture and fallow sites. Contrasts

continue to show differences of Miombo versus

agricultural and fallows sites at each depth except

Fig. 3. The influence of soil texture on soil carbon levels in top

20 cm.

below 1 m. However, the Tukey results do not show

‘mass corrected’ carbon value differences between

land use types when each depth is examined

separately.

4. Discussion

4.1. Carbon within the profile

The regression type found to most appropriately

describe carbon changes with depth in this study also

significantly characterized 76% of the 2700 world-

wide soil profiles compiled in a study by Jobbagy and

Jackson (2000). All sites could accurately be

portrayed by the log carbon, log depth equation type

except one site that had unusually high carbon levels at

depth. The Miombo surface SOC values in this study

are slightly higher than most previous studies in the

Miombo Region (Fig. 6a). Below roughly 40 cm the

estimates in this study are more similar to those found

previously. Past research in the region examining soil

carbon in agriculture, found the log-log relationship of

carbon with depth to have disappeared, with carbon

levels changing only minimally with depth (Fig. 6b).

The higher variability of carbon at the surface

between sites in the present study is likely due to small

scale differences between sampling locations, such as


Fig. 4. Correlation between age of land use and surface soil carbon density.

position in comparison to trees, past fire history at site,

proximity of termite mounds, slope position, and

grazing intensity. Carbon deeper in the profile will

represent the integration of many years of biological

inputs. Because of the logarithmic nature of carbon

with depth, the majority (�60% on average) of carbon

is found above 40 cm and more than 40% in the top

20 cm. The higher in the profile, the greater influence

land use change will have on the carbon levels. The

surface layers will contain the most labile carbon

sources, i.e., those most readily decomposed by soil

microbes Therefore, if carbon inputs are reduced, the

Table 2

Average total volume of carbon and nitrogen to a depth of 1.5 m

Average (kg/ha) S.D. (kg/ha)

Carbon

Miombo 82517 32684

Agriculture 49031 10799

Fallow 52201 23882

Average 57952 23268

Carbon: mass corrected

Miombo 79623 35981


Fallow 44857 22328

Average 51550 22368

Nitrogen

Miombo 6838 845


Fallow 3877 1349

Average 4997 1654

microbes will continue to decompose the existing

organic matter until the majority of the carbon will

exist as stable, inert complexes. Soil at depth will

generally be relatively old and will not be easily

influenced by land practices happening at the surface

(unless deep rooted plants begin to grow), hence the

low variability of SOC at depth. In comparison with

Jobbagy and Jackson (2000), this study found

proportionally more carbon at the surface than was

seen in other tropical deciduous forests or savannas.

Conversely, the average agricultural fields in Jobbagy

and Jackson (2000) contained proportionally more

S.E. (kg/ha) Percent reduction from Miombo

Top 10 cm Top 1.5 m

23111

7636 �55 �41

16887 �43 �37

16453

25443

8367 �61 �47

15788 �47 �44

15817

598

1101 �50 �26

954 �48 �46

1169


Fig. 5. Carbon and nitrogen stock within one ha of each land use

(with standard error of entire depth, different letters signify sig-

nificant differences between LU).

surface carbon than this study found. In comparison to

other studies within Miombo, this study also found

proportionally greater levels of carbon at the surface in

agricultural fields (Fig. 6b).

The surface soils of the agricultural fields are

expected to have a lower C:N ratio than the Miombo

Woodlands, as the amount of new inputs into the soil

has been reduced and therefore the majority of SOM is

expected to be older, highly decomposed material

(Waksman, 1924). Additionally there could be a build

up of fertilizer through time. However, this reduced

C:N ratio was found only in some of the older

agricultural sites (at which no fertilizer had ever been

used) and some fallow sites. King and Campbell

(1994) found similar C:N ratios at Miombo sites,

averaging 15 at the surface and 7 at 20 cm and only

slightly lower C:N ratios in the agricultural sites,

averaging 12 at the surface. Other studies in Miombo

Woodlands areas also had surface C:N ratios similar to

those found in the present study, ranging from a low of

8 to a high of 15 (Stromgaard, 1991, 1992; Murwira

and Kirchmann, 1993).

4.2. Soil texture and bulk density

The range of agricultural soil texture was not

significantly different from the Miombo sites, there-

fore it does not seem that soil texture is a factor for

farmers in choosing the location of agricultural fields.

It is difficult to tell if the same is true for all fallow

sites. It is possible that the farmers holding the two

sandier fallow sites that also have low carbon levels

have retained the areas as woodlots because they

believe the areas will not be productive farmland.

Unfortunately, the farmers were not questioned about

their views on the ability of that land to recover in

comparison to other plots.

Due to the break up of soil aggregates by plowing

(Davidson and Ackerman, 1993), increases in bulk

density when land is converted to agriculture are

extremely common worldwide, however no significant

changes were seen in the current study. This may be

due to the naturally lower perturbation level of hand

plowing. King and Campbell (1994) in Zimbabwe

found BD levels very comparable to those in this

study, with Miombo sites having BD of 1.3 g/cm3 and

the arable plots having a higher BD of 1.5 g/cm3. A

bulk density of �1.2–1.4 g/cm3 is very common

worldwide for native vegetation without a thick

organic horizon and agricultural conversion raises

that to �1.5 g/cm3 (Brown and Lugo, 1990b;

Davidson and Ackerman, 1993; Rosell and Galantini,

1997; Batjes and Dijkshoorn, 1999; Feller et al.,

2001). The increased bulk density in fallow fields may

be due to the hoof traffic of grazing animals or from

the higher sand content at some sites.

As in this study, many researchers have also found

some correlation between BD and % clay to exist,

although an adequate predictive relationship between

them has not been found (Curtis and Post, 1964;

Barahona and Santos, 1981; Rodriguez-Murillo,

2001). The higher sand levels in two of the fallow

sites probably contributed to the higher BD levels

found at those sites. This interaction was accounted for

in the analysis of land use impacts on carbon levels,

but its inclusion did not alter the statistical results.


Fig. 6. Soil carbon in vertical profile within various published Miombo studies in comparison to the current study: (a) Miombo Woodlands

(Astle, 1969; Brocklington, 1956; Campbell et al., 1995; Campbell et al., 1988; Mapiki, 1988; Nyamapfene, 1991; Robertson, 1984; Stromgaard,

1984; Trapnell et al., 1976; Watson, 1964; Young, 1976), (i = taken from Campbell, 1996); (b) agricultural fields (Mugwira and Nyamangara,

1998; Kirchmann and Eklund, 1994; Chivaura-Mususa and Campbell, 1998).

In many ecosystem types, soil carbon is commonly

seen to be positively correlated with clay and/or clay +

silt including the Jobbagy and Jackson (2000) study

which examined a large number of profiles worldwide,

and Birch and Friend (1956), Foster (1981), and Bird

et al. (2000) in east and southern African soils. Feller

et al. (2001) maintains that within latitudinal

gradients, SOC stocks will be very dependent on

the soil mineralogy and soil texture. Carbon levels

tend to increase with increasing clay content because

carbon is often captured within small pores of clay

particles that are then not physically accessible to

microbes or bound in the interlayers of silicate clays

(Paul, 1984; Lepsch et al., 1994; Lilienfein et al.,

1998). In the current study, a significant but low R2

regression exists between carbon and % clay + silt in

the top 40 cm of observed soils. Clay content does not

influence SOC below 40 cm, perhaps due simply to the


low variability of carbon at depth. The inclusion of soil

texture within the multiple regression equations points

to the significant influence it has on carbon levels.

4.3. Differences due to land use type

In the Chimaliro area, agriculture reduced observed

carbon and nitrogen stocks on average by 40%. This

reduction level is typical of semi-arid and tropical

areas (Allen, 1985; Davidson and Ackerman, 1993;

Sombroek et al., 1993; Tiessen et al., 1998; Solomon

et al., 2000). Reviewing 36 agricultural studies

worldwide, Allen (1985) found that in tropical old

parent material soils, organic C, total N, and CEC

decreased 50% more than in other soil types and bulk

density increased significantly more than in other soil

types. Davidson and Ackerman (1993) found carbon

losses of between 20 and 40% due to land use

conversion to agriculture at various ecosystems

worldwide. In the present study, this depression in

SOC stocks did not recover significantly when fields

were abandoned, as observed soil carbon and nitrogen

at most fallow fields remained lower. Statistically

controlling for influences of soil properties by adding

soil texture and BD as covariates did not change these

results and therefore land use had an overriding

influence on soil carbon levels. As was hypothesized,

the majority of the differences in soil carbon occurred

in the top 40 cm although differences were signifi-

cantly different between land uses to a depth of

100 cm. Although Miombo sites varied greatly in

carbon levels, the observed Miombo carbon stocks

exceeded observed agricultural carbon at all sites.

Performing the ‘mass correction’ on the carbon

stocks actually results in a slightly greater percent

reduction in carbon stocks due to land use conversion.

In other studies when bulk density is used to calculate

carbon volumes by depth, the SOC reduction by

agriculture can be partially masked by the larger

density of soil within a certain depth (Davidson and

Ackerman, 1993). However, this effect is not seen here

since agriculture did not significantly increase BD.

Soil carbon levels in young and medium aged

agricultural fields were very similar and therefore one

could not estimate carbon values based on the age of

the field. Carbon did not appear to decline slowly as

the age of the field increased. Many studies have found

a rapid decline in soil carbon that is then followed by

SOC reaching a new equilibrium point (Houghton et

al., 1983; Schlesinger, 1986; Davidson and Ackerman,

1993; Solomon et al., 2000). For example, in Puerto

Rico, Brown and Lugo (1990a) found surface soil

carbon to not differ significantly between a 10-, 60-,

and 100-year-old agricultural field. Unlike these other

studies, in the present study the three older agricultural

sites contained depressed carbon values in comparison

to the average young field carbon level. However, two

of the younger fields also had carbon levels compar-

able to the older agricultural fields so it is not known if

these older fields equilibrated at a lower carbon level

soon after land use conversion or if they continued to

decline further over time. This situation exemplifies

some of the problems of using space for time in

determining the impact of land use. Although age was

significantly included in the multiple regression of the

agricultural fields, it adds very little explanation to the

variance.

The continued depressed carbon value in the fallow

fields, except for one site, is alarming. It was expected

that a recovery rate of carbon, or an estimate of

roughly how many years it would take for carbon

levels to recover, could be determined, however this

was not possible since carbon values were low at all

but one site. It is common for carbon levels in fallow

fields to fall in the first 2–5 years of abandonment but

most studies have found levels start to increase after

about 5 years (Aweto, 1981; Kleinman et al., 1996;

Szott and Palm, 1996; Szott et al., 1999). The

compilation by Szott et al. (1999) found that N and P

stocks also decrease after abandonment but then

recover more rapidly than carbon, needing an

estimated 2 years to recover. However in the current

study, nitrogen was actually lower in fallow sites than

in the agricultural sites except for one site which also

had elevated carbon levels. Szott et al. (1999) do note

that ecosystems will accumulate less N if biomass

accumulation or N2 fixation are impeded. Knops and

Tilman (2000) also suggest nitrogen fixation and

atmospheric deposition as a major control on carbon

accumulation in fallow fields. N2 fixers are not the

dominant species within Miombo and perhaps this

reduced the rate of N2 fixation in contrast to other

ecosystems. In addition, grazing and firewood collec-

tion are regularly removing biomass and therefore

reducing the rate of AG carbon sequestration and

removing nutrients from the system. Unfortunately,


farmers were not questioned about the initial fertility

of the soil when the land was first deforested, and

therefore it is not known if these sites inherently

contained less C and N. All of the Chimaliro fallow

sites had a tall layer of C4 grass and in Zambia it has

been found that grass fallows can immobilize N

(Barrios et al., 1997). In an acacia woodland in

Tanzania, degradation through selective logging for

charcoal production reduced the labile portions of soil

carbon and nitrogen but only slightly increased the

C:N ratio (Solomon et al., 2000).

Observed soil carbon values in the Miombo

vegetation land use type vary more greatly than

expected. More measurements within this land use

type need to be collected along with other variables

that will influence SOC such as: AG Biomass, annual

litter levels, fire frequency, termite density, and slope

position. Agricultural fields are more similar to each

other and one generalized regression equation could

be used to estimate SOC at an acceptable error level.

The greatest variance in soil carbon occurs in the

surface layers and the standard error of carbon levels

below 60 cm is relatively small (Table 1; Fig. 1).

5. Conclusions

The rapid changes taking place in the populations

of south-central Africa are resulting in a greater area of

land under human control and more intense use of the

land than ever before. Processes or management

practices that alter the inputs of organic matter into the

soil carbon pool or the decomposition rate of SOM

will affect soil carbon levels.

This study examined a number of both natural and

human driven factors influencing soil carbon levels in

the Miombo Woodland Region. By removing the

majority of aboveground biomass, conversion to

agriculture breaks the cycle of carbon movement in

the ecosystem. Carbon in the soil is not replenished at

a rate to keep up with decomposition and carbon

declines. Even in an agricultural system using hand

plowing, SOC levels cannot be maintained. Nitrogen

generally follows the same trend as carbon. Field

experiments and modeling studies should be initiated

to examine potential sustainability improvements

using different agricultural management techniques

such as reduced tillage, application of manure, the

rotation of cover and N-fixing crops, and improved

fallows (Lal et al., 1995; Anderson, 1998; Lal, 1998;

Six et al., 1998).

From the study conducted it appears that the

dominant fallow field land management technique is

not allowing for nutrient recovery. The nutrient

dynamics of these abandoned fallow fields are in

great need of further study. A SOC recovery rate could

not be determined because only one fallow site had

made any type of carbon gain. The extremely low

levels of carbon and especially nitrogen in these

regrowing Miombo sites need to be addressed by

agricultural extension officers. As the area of land

converted to agriculture across the Miombo Region

increases, land in this regrowth state will most likely

become the dominant form of Miombo Woodlands.

Therefore studies of the nutrient dynamics in this type

of land cover will be essential. Land cover estimates of

the area of regrowth have not been estimated for the

region. When preparing land cover maps, these

regrowing areas are often classified as wooded

grassland, bushland, or shrubland depending on the

country, making it impossible to distinguish natural

wooded grassland areas (or at least those not formed

by agricultural abandonment) from regrowth areas on

the current land cover maps. Reevaluation of labeling

methods should be completed to address this issue.

Clay content increased the amount of carbon able

to be stored in the soil within all land use types due to

the protective nature of clay particles. Because of its

positive influence, clay content is an essential site

attribute that must be collected alongside carbon

measurements. Soil texture will need to be considered

in understanding the degree of carbon loss expected

from conversion to agriculture or the possibility of

carbon sequestration. Using a ‘mass corrected’ carbon

estimate was not useful in this study because

conversion to agriculture did not significantly alter

the bulk density of the soils, although some increase

did exist in the older agricultural fields. However, bulk

density was higher in a number of fallow fields, most

likely due to the soil texture and animal traffic.

The current research exhibited the reduced SOC

pool resulting from the dominant agricultural manage-

ment method. If current conditions continue, the

fertility of this land will continue to decline. This will

result in even lower crop yield, leading to increased

poverty and economic instability. Initiation of


improved agricultural management techniques may

allow for greater soil fertility sustainability.

Acknowledgements

This work has taken place as part of the ‘Coupling

Land Use and Land Cover Changes, and Ecosystem

Processes in Miombo Woodlands’ project funded by

NASA’s LCLUC (Land-Cover and Land-Use Change)

program (NAG5-6384). This work was conducted in

association with Steve Makungwa and Alex Mangu-

lana at the Forestry Research Institute of Malawi and

Richard Chatchuka of the Kasungu District Forestry

Office. We owe much gratitude to the farmers

surrounding the Chimaliro forest reserve for their

warm hospitality and especially to Edward Sambo,

Felix Zimba and Andrea Phiri for their excellent field

assistance. We thank Hank Shugart and Stephen

Macko for their scientific and editorial advice,

Howard Epstein and Margot Miller for assistance

with laboratory work and David Richardson for

assistance with the statistical analysis.

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Documents

The impact of land use on soil carbon in Miombo Woodlands of Malawi