Journal of Arid Environments 73 (2009) 521–528
Contents lists available at ScienceDirect
Journal of Arid Environments
journal homepage: www.elsevier.com/locate/jaridenv
Allocation of vegetation biomass across a climate-related
gradient in the grasslands of Inner Mongolia
J.W. Fan a, b, K. Wang a, *, W. Harris c, H.P. Zhong b, Z.M. Hu b, B. Han b, W.Y. Zhang b, J.B. Wang b
a
Institute of Grassland Science, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, P.R. China
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P.R. China
c
Landcare Research, PO Box 40, Lincoln 7640, New Zealand
b
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 21 December 2007
Received in revised form
24 November 2008
Accepted 11 December 2008
Available online 13 January 2009
Biomass was measured at 48 undefoliated grassland sites on a 1900-km transect in Inner Mongolia.
Above-ground biomass was separated into leaf, stem, flower and fruit, and dead matter, and into the five
dominant species at each site. Below-ground biomass was measured to a depth of 30 cm and separated
into 10-cm layers. Changes of these biomass components and their ratios were examined in relation to
gradients of temperature and precipitation, and to the classification of the sites into five grassland types.
Total biomass decreased markedly as site mean annual temperature increased and to a smaller extent as
mean annual precipitation decreased. Averaged over all sites 92% of biomass was below ground. The
proportion of below-ground biomass increased as temperature decreased, and was least and distributed
more deeply in desert grassland. As aridity of the grassland types increased, the proportion of biomass in
the first dominant species and in stem relative to leaf tissue increased. The biomass measurements
provide baseline data required for monitoring sustainable use of Inner Mongolia grassland for livestock
production and its storage of carbon.
Ó 2008 Elsevier Ltd. All rights reserved.
Keywords:
Biomass allocation
Grassland transect
Precipitation gradient
Temperature gradient
1. Introduction
Biomass allocation reflects a balancing strategy of plants in
response to supply of environmental resources (Carnier, 1991;
Enquist and Niklas, 2001, 2002). Changes in biomass allocation
affect the survival, growth and reproduction of individual plants
(Cropper and Gholz, 1994; Grace, 1997; McConnaughay and
Coleman, 1999; Maherali and DeLucia, 2001) as well as biogeochemical cycle processes of terrestrial ecosystems (Friedlingstein
et al., 1999; Bird and Torn, 2006; Litton et al., 2007). Biomass
allocation is the embodiment of the most important factors that
restrict plant growth in ecosystems (Chapin III et al., 2002).
Changes of environmental conditions will produce rapid and
profound influences on vegetation biomass allocation (Farrar, 1999;
Maherali and DeLucia, 2001). Consequently research to determine
how variations of environmental factors affect vegetation biomass
* Corresponding author. Institute of Grassland Science, China Agricultural
University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193,
P.R.China. Tel./fax: þ86 010 62733338.
E-mail addresses: [email protected] (J.W. Fan), [email protected] (K. Wang),
[email protected] (W. Harris).
0140-1963/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jaridenv.2008.12.004
allocation is required to understand mechanisms of ecosystem
adaptation and response to climate change (Cairns et al., 1997).
We consider changes of vegetation biomass allocation in
response to climatic factors from three aspects: changes in the
allocation ratio of above- and below-ground biomass, changes of
allocation proportion to above-ground organs (stem, leaf and
reproductive tissue) and dominant species, and changes of belowground biomass allocation in different soil layers. Most previous
research has focused on analysis of the ratio of above- and belowground biomass, most often shoot:root ratios. This research has
been mainly done for individual species or plant communities
under specific environmental conditions. Few studies have
involved rigorous examination of changes of biomass allocation
along sequences of climate-related variables or vegetation types,
most have involved forest and few have involved grasslands
(Mokany et al., 2006), and most have not included at one time all
the aspects of biomass we define. As examples, Schulze et al. (1996)
studied change of root biomass and root density with soil depth
and distribution of above- and below-ground biomass in relation to
an aridity gradient, Yanagisawa and Noboru (1999) studied rooting
depth in relation to slope, and Luo et al. (2005) studied root
biomass in relation to temperature and precipitation along
subtropical-to-alpine gradients in Tibet.
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J.W. Fan et al. / Journal of Arid Environments 73 (2009) 521–528
Table 1
Geographical extent, climatic ranges and characteristic species of sites sampled in five major grassland types of Inner Mongolia.a
Grassland type
and no. of sites
sampled
Latitude and
longitude
Mean annual
temperature
( C)
Mean annual
precipitation
(mm)
Dominant and indicator species
Meadow Steppe (n ¼ 10)
41–50 N, 117–127 E
4 to 5
350–450
Typical Steppe (n ¼ 18)
38–46 N, 108–118 E
2 to 5
250–350
Desert Steppe (n ¼ 14)
Steppe Desert (n ¼ 3)
Typical Desert (n ¼ 3)
37–45 N, 106–114 E
38–42 N, 105–110 E
38–42 N, 97–106 E
4 to 6
5 to 9
6 to 10
200–250
180–200
<50–150
Leymus chinense, Stipa baicalensis, Cleistogenes polyphylla, Filifolium sibiricum,
Artemisia laciniata, Carex lanceolata
Leymus chinense, Stipa grandis, S. klyrovii, Artemisia frigida, Agropyron cristatum,
Cleistogenes squarrosa, Artemisia intramongolica, A. holoderdron
Stipa klemenzii, S. breviflora, S. gobica, Cleistogenes songorica, Artemisia frigida, Artemisia spp.
Salsola passerina, Reaumuria soongorica, Caragana spp., Stipa spp., Artemisia spp.
Ceratoides lateens, Salsola abrotanoides, S. passerine, R. soongorica, Kalidium foliatum
a
Data from ECGRIM (1990), DAHV (1996).
The most important grassland resources of China are located in
Inner Mongolia. Due to the effect of the Pacific monsoon, the
grasslands of Inner Mongolia show a remarkable transition of
character in climate and vegetation from north-east to south-west
(ECGRIM, 1990; DAHV, 1996). Especially as the region has relatively
flat topography this provides a suitable location for research on
various characteristics of grasslands in relation to climatic gradients –
and this suitability has been used in several studies of aspects of
plant production and species composition (Bai et al., 2000; Zhou
et al., 2002; Ni, 2004; Hu et al., 2007). However, we know of only
one study using the climatic gradients in the region to study their
relationships with variations of biomass allocation and this was
a single-species study involving Leymus chinensis (Wang et al.,
2001, 2003; Wang and Gao, 2003).
With the objective of improving understanding of the nature and
mechanisms of climatic control of biomass allocation in grasslands,
our study records measurements of the spatial pattern of biomass
allocation in the temperate grasslands of Inner Mongolia in relation
to temperature and precipitation gradients, using transect research
methodology. We began with the hypotheses that (1) above-ground
biomass, below-ground biomass and total biomass decrease, and
the ratio of below- to above-ground biomass increases with the
increase of aridity across the climatic gradient, (2) the proportion of
stem in above-ground biomass increases and the leaf proportion
decreases with the increase of aridity, and (3) that the proportion of
below-ground biomass increases with increasing soil depth as
aridity increases. We also examine how these aspects of biomass
allocation differ for the grassland types of the region and their
dominant species. The results are discussed in regard to their relevance to predictions of effects of climate change on the capacity of
the grasslands to store carbon and for management of their
sustainability as a resource for the production of forage for livestock.
The selection of 48 sample sites was principally defined by
a transect across the area in a band approximately 1900 km long by
150 km wide, from Hailar (49150 N, 119150 E) in the east to Alxa
(38 070 N, 101550 E) in the west (Fig. 1). This transect traversed all
the zonal grassland vegetation types of Inner Mongolia (Table 1). To
achieve systematic sampling the distance between each sampling
site was about 50 km. The geographical location and altitude of
each site was determined by a GPS device and records were made of
soil condition, grassland type, total vegetation cover, the proportion
of cover provided by the dominant species, and the height of the
dominant species.
2.2. Sampling and separation of biomass components
Samples were taken during August to October (when most
dominant species were at the late flowering stage or fruiting) in
2003 and 2004 from areas that had not been cut or grazed in the
previous year. Three 1-m2 quadrats were sampled at each of the 48
sites, providing a total of 144 quadrats for analysis. Where shrubs or
small trees were present at a site the 1-m2 quadrats were randomly
placed within 10 10-m or 50 50-m quadrats used to measure
woody biomass.
Above-ground biomass within the small quadrats was harvested
to ground level and separated into living (green), dead biomass
attached to plants, and litter biomass. The above-ground living
biomass was further separated into leaf, stem, and sexually reproductive (flower and fruit) components. There was also separation
into fractions for five or fewer of the dominant species, and
remaining species were bulked as ‘‘other species’’. Dominant
2. Methods
2.1. Research area and sample sites
The research area traversed much of the Inner Mongolian
Plateau, where the landscape is mostly flat with slight undulations.
The area has been divided into five climatic regions from the northeast to south-west according to aridity: humid, semi-humid, semiarid, arid, and extreme-arid. Generally soils are steppe soils often
with a calcic horizon in the profile. From east to west soil types
grade from phaeozem, chernozem, castanozem, brown calcic soil,
desert calcic soil, to grey-brown desert soil. There are some intrazonal soils such as meadow soil and aeolian sandy soil. Determined
mainly by climatic factors there are, in order from north-east to
south-west, five major vegetation types located in specified latitudinal and longitudinal and climatic ranges, and characterised by
dominant and indicator species (Table 1).
Fig. 1. Locations in Inner Mongolia of 48 undefoliated grassland sample sites.
J.W. Fan et al. / Journal of Arid Environments 73 (2009) 521–528
523
Table 2
Multiple regression relationships of MAT and MAP with latitude and longitude.a
Y Climatic variable
a (constant)
bX1 (latitude)
Standardized coefficients (beta)
cX2 (longitude)
Standardized coefficients (beta)
F
P Multiple regression
MAT ( C)
MAP (mm)
60.04
1599.63
0.42
15.84
0.47, P < 0.001
0.72, P < 0.001
0.34
22.75
0.52, P < 0.001
1.42, P < 0.001
322.24
51.70
<0.001
<0.001
a
The regression model is Y ¼ a þ bX1 þ cX2. Latitude and longitude use decimalized degrees; n ¼ 48.
species were determined according to their numbers, cover, and
biomass in the grassland communities sampled.
Below-ground biomass was mostly sampled by taking 9–36 soil
cores of 3.1-cm diameter in 10-cm depth layers to 30 cm within
each quadrat, but some were obtained by digging out 25 25-cm
pits. Roots and other below-ground biomass were separated from
soil by washing with water through a 0.3-mm-mesh sieve.
The numbers of each shrub and tree species present in the 100-m2
or 2500-m2 quadrats were recorded. Nine of these trees or shrubs
were sampled from the large quadrat for the determination of
biomass, with three each representative of small, medium and large
plants. The roots of these woody plants were excavated to a depth
of 30–50 cm. The biomass samples were oven-dried at 80 C for
24 h.
2.3. Climatic data
Climatic data for the sample sites were obtained from the China
Climate Grid Database (1 1 km) constructed by the Chinese
Ecosystem Research Network (CERN), Chinese Academy of Sciences
(CAS). The database was produced by spatial interpolation of values
in ANUSPLIN using mean annual temperature (MAT) and precipitation (MAP) data from weather stations throughout China recorded from 1971 to 2004, and geographical data.
patterns resulted in the lowest temperature and the highest
precipitation in north-east Inner Mongolia and the highest
temperature and lowest precipitation in the south-west of the
region. This resulted in a negative correlation between site
temperatures and precipitation (R2 ¼ 0.507, P < 0.001), making it
difficult to separate temperature and precipitation effects on
biomass. Analyzed according to standardized coefficients, the order
of the trends of MAT in relationship to latitude and longitude were
similar, but for MAP the longitudinal trend was more marked than
for latitude (Table 2).
3.2. Changes of proportions of above- and below-ground biomass in
relation to climate gradients and grassland types
Site means for biomass (above-ground, below-ground and total;
g/m2) are plotted against site MAT and MAP in Fig. 2. Total
(R2 ¼ 0.633, P < 0.001) and below-ground (R2 ¼ 0.624, P < 0.001)
biomass showed well-defined decreases as MAT increased whereas
the similar trend for above-ground biomass was weaker
(R2 ¼ 0.275, P < 0.001, Fig. 2a). Total (R2 ¼ 0.278, P < 0.001) and
below-ground biomass (R2 ¼ 0.275, P < 0.001) increased, and
a
4000
2.4. Data analysis
3. Results
Biomass (g/m2)
3000
2000
1000
0
-4
-2
0
2
4
6
8
10
Mean annual temperature (°C)
b
4000
3000
Biomass (g/m2)
Biomass data collected for shrubs and trees from the 100-m2 or
2500-m2 quadrats were combined with those of herbaceous
biomass from the small quadrats to determine the biomass fractions as DM/m2.
Analysis of variance provided standard errors of means and tests
for the significance of differences of biomass components between
sample sites and grassland types. Relationships between MAT and
MAP for 1971–2004 and measurements of the biomass components
at the 48 sites were examined using two-dimensional plots with
fitted regressions plotted where these were significant. The site
temperature and precipitation means for the 34-year period were
closely related to the means obtained for the sites in 2003 and 2004
(MAT: R2 ¼ 0.987, P < 0.001; MAP: R2 ¼ 0.691, P < 0.001) when we
made the biomass measurements. We used the longer-term means
because we considered the biomass values we recorded, especially
below-ground biomass, were in part the product of biomass accumulation that occurred in years before 2003. Correlation and
regression analysis was done using SPSS14.0. The quadratic
regression with 45 d.f. was plotted as the best description of the
relationships.
2000
1000
3.1. Climate gradients
MAT was lowest (3 to 5 C) in north-east Inner Mongolia in
the Daxinan (Hinggan) Mountain area, gradually rising to 8–9 C in
the Alxa Desert area in the south-west. MAP was highest in the
north-east mountainous area (450 mm) and gradually decreased
towards the south-western inland desert area (50 mm). These
0
50
150
250
350
450
Mean annual precipitation (mm)
Fig. 2. Relationships between site means of above-ground (-, – – –), below-ground
(6, - - -) and total biomass (A, d) and (a) MAT and (b) MAP of 48 undefoliated
grassland sites in Inner Mongolia.
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J.W. Fan et al. / Journal of Arid Environments 73 (2009) 521–528
above-ground biomass (R2 ¼ 0.144, P < 0.05) showed a marginal
increase as MAP increased (Fig. 2b). When the MAT and MAP effects
on biomass were accounted for together in a multiple regression
the MAP effect was not significant. Derived from the site means
plotted in Fig. 2 the mean total biomass measured for the study area
was 1600 g/m2 varying between sites from 69 to 3584 g/m2. Mean
total biomass decreased progressively for the grassland type
sequence of Meadow Steppe (2315 178 g/m2), Typical Steppe
(1925 269 g/m2), Desert Steppe (1129 143 g/m2), Steppe Desert
(715 472 g/m2), and Typical Desert (352 107 g/m2). Grassland
type below-ground biomasses ranged from 2138 g/m2 for Meadow
Steppe to 219 g/m2 for Typical Desert. For above-ground biomass
the range was from 177 g/m2 for Meadow Steppe to 88 g/m2 for
Desert Steppe.
The percentage of below-ground biomass was generally highest
where MAT was low, peaking in the range 0–3 C (R2 ¼ 0.368,
P < 0.001; Fig. 3a). For MAP the relationship with the proportion of
below-ground biomass was positively curvilinear (R2 ¼ 0.247,
P < 0.001; Fig. 3b), peaking in the range 250–350 mm. Meadow
Steppe (91.8 1.6%), Typical Steppe (86.5 4.2%), and Desert
Steppe (89.8 1.7%) had similar percentages of below-ground
biomass that were distinctly higher than that of the Typical Desert
grassland community (56.4 14.3%). The Steppe Desert
(64.4 20.2%) showed marked variability and consequently did not
differ significantly from the other grassland types.
a
100
3.3. Proportions of above-ground biomass components in relation
to climate gradients and grassland types
For above-ground green (live) biomass (not including standing
dead matter and litter) averaged over all sites, 39.6 3.1% was stem,
55.2 3.2% was leaf, and 5.2 1.0% was flowers and fruit. The
percentages of stem biomass in above-ground green biomass
showed a curvilinear increase with increase of MAT (R2 ¼ 0.503,
P < 0.001; Fig. 4a), and a curvilinear decline with increase of MAP
(R2 ¼ 0.335, P < 0.001; Fig. 4b). The percentage of leaf biomass at
sites showed the converse response to that of stem biomass,
decreasing with increased MAT (R2 ¼ 0.405, P < 0.001; Fig. 4a) and
increasing with increasing MAP (R2 ¼ 0.247, P < 0.001; Fig. 4b).
Differences between the percentage of biomass in flowers and fruit
between sites were not significantly related to site MAT or MAP
(Fig. 4).
The stem fraction of the above-ground green biomass showed
an overall increase in the order Meadow Steppe < Desert Steppe
< Typical Steppe < Steppe Desert < Typical Desert. The leaf fraction
was in the reverse order: Meadow Steppe > Desert Steppe > Typical Steppe > Steppe Desert > Typical Desert. The highest
percentage of biomass in flower and fruit was found in Typical
Steppe grassland and no flower and fruit biomass was recorded for
the Typical Desert sites (Fig. 5).
Averaged over all sites the proportion of above-ground standing
biomass (green and dead matter but not litter) contained in the first
dominant species was 55.6 2.9% of total above-ground standing
biomass. This percentage did not vary significantly in relation to the
gradients of MAT and MAP. Overall the percentage of above-ground
biomass contained in the first dominant species increased across
a
100
60
40
20
0
-4
-2
0
2
4
6
8
10
Above-ground biomass
Below-ground biomass
80
Mean annual temperature (°C)
80
60
40
20
0
-4
b
b
Above-ground biomass
Below-ground biomass
80
60
40
20
0
50
-2
0
2
4
6
8
10
Mean annual temperature (°C)
100
150
250
350
450
Mean annual precipitation (mm)
100
80
60
40
20
0
50
150
250
350
450
Mean annual precipitation (mm)
Fig. 3. Relationships between site means of the percentage of below-ground biomass
and (a) MAT and (b) MAP of 48 undefoliated grassland sites in Inner Mongolia.
Meadow Steppe (A); Typical Steppe (,); Desert Steppe (:); Steppe Desert (>);
Typical Desert (C).
Fig. 4. Relationships between the site means of stem, leaf, and flower and fruit
components of above-ground green biomass and (a) MAT and (b) MAP of 48 undefoliated
grassland sites in Inner Mongolia (A, - - -: stem; ,, d: leaf; :, – – –: flower/fruit).
J.W. Fan et al. / Journal of Arid Environments 73 (2009) 521–528
biomass in the 10–20 cm and 20–30 cm layers showed converse
responses to that of the 0–10 cm layer, increasing with increased
MAT (R2 ¼ 0.162, P < 0.005; R2 ¼ 0.236, P < 0.001, Fig. 7c) and
decreasing with increased MAP (R2 ¼ 0.237, P < 0.001; R2 ¼ 0.229,
P < 0.001; Fig. 7d).
The percentage of below-ground biomass in the first layer
(0–10 cm) decreased progressively across the grassland types from
Meadow Steppe (65.1%) to Typical Desert (51.1%). Biomass in the
second (10–20 cm) and third (20–30 cm) layers increased in the
reverse order, the range from Meadow Steppe to Typical Desert for
the second layer being 22.7–31.1% and for the third layer 12.1–17.8%
(Fig. 8).
100
Stem
Above-ground biomass
90
Leaf
Flower & fruit
80
70
60
50
40
30
20
10
0
MS
TS
DS
SD
TD
Grassland types
4. Discussion
Fig. 5. Mean (SE) proportions of stem, leaf, and flower and fruit in the above-ground
green biomass of five grassland types in Inner Mongolia. MS: Meadow Steppe; TS:
Typical Steppe; DS: Desert Steppe; SD: Steppe Desert; TD: Typical Desert.
the grassland ecological sequence from Meadow Steppe (49.3%) to
Typical Desert (87.6%). Desert Steppe, which had the lowest
percentage of above-ground biomass contained in the first dominant (46.3%), had the greatest percentage (30.9%) in species other
than the first five dominants (Fig. 6).
3.4. Distribution of below-ground biomass in soil depth layers in
relation to climate gradients
Averaged over all sites biomass contained in roots and other
below-ground biomass was mostly in the 0–10 cm layer
(60.5 0.8%), reducing progressively from the 10–20 cm layer
(26.2 0.6%) to the 20–30 cm layer (13.3 0.4%). Well-defined
curvilinear reductions of site below-ground biomass of the three
layers in relation to increases of site MAT were shown (Fig. 7a). The
extent of this reduction was steeper for biomass in the 0–10 cm
layer (R2 ¼ 0.663; P < 0.001) compared with the 10–20 cm
(R2 ¼ 0.525, P < 0.001) and 20–30 cm (R2 ¼ 0.543, P < 0.001) layers.
A similar but converse relationship was shown with site belowground biomass increasing as MAP increased (Fig. 7b). This change
was most marked for the 0–10 cm layer (R2 ¼ 0.304, P < 0.001) and
less so for the 10–20 cm (R2 ¼ 0.211, P < 0.01) and 20–30 cm
(R2 ¼ 0.230, P < 0.005) layers.
The percentage of below-ground biomass in the 0–10 cm layer
showed a linear decrease with increased MAT (R2 ¼ 0.273,
P < 0.001; Fig. 7c), and a linear increase with increased MAP
(R2 ¼ 0.334, P < 0.001; Fig. 7d). The percentage of below-ground
100
Above-ground biomass
90
80
Dom1
Dom2
Dom3
Dom4
Dom5
Other
70
60
50
40
30
20
10
0
MS
TS
DS
525
SD
TD
Grassland types
Fig. 6. Mean (SE) proportions of above-ground biomass in the dominant species of
five grassland types in Inner Mongolia. MS: Meadow Steppe; TS: Typical Steppe; DS:
Desert Steppe; SD: Steppe Desert; TD: Typical Desert.
4.1. Spatial variability of biomass along climate gradients
Many previous studies have indicated that above-ground
biomass or productivity decreases with decreasing MAP (Sala et al.,
1988; Paruelo et al., 1999; Bai et al., 2000; Huxman et al., 2004; Ni,
2004; Hu et al., 2007). Our study also showed that below-ground
biomass decreased as MAP decreased (Fig. 2b) indicating that
reduced precipitation simultaneously restricts accumulation of
above-ground and below-ground biomass in the grassland areas of
Inner Mongolia. We also found that total biomass decreased as MAT
increased (Fig. 2a), a finding in agreement with those of Bai et al.
(2000) and Ni (2004) for the region.
The MAT relationship to biomass accumulation (Fig. 2a) is
influenced by the correlation between the precipitation and
temperature gradients in Inner Mongolia in that dry areas are
associated with high temperatures and humid areas with low
temperatures (Tables 1 and 2). Under drought conditions plant
photosynthesis may be further restrained by high temperature.
This was shown by Xu and Zhou (2005) who reported that high
temperatures resulted in the decline of photosynthetic rate and
biomass of L. chinensis in Inner Mongolia typical steppe. Further,
higher temperature will result in increased evaporation, intensifying drought and reducing biomass. Hu et al. (2007) indicated that
the aridity index, which takes into account both precipitation and
temperature, could explain the spatial variance of ANPP better than
MAP alone. Thus using MAP alone to estimate biomass levels at
a regional scale may involve considerable error.
4.2. Spatial variability of the proportion of below-ground biomass
along climate gradients
The observation that the MAT gradient had a stronger influence
on the proportion of below-ground biomass than MAP (Fig. 3) can
be related to studies that have shown that root biomass per
surface area and root:shoot biomass ratios tend to be lower in
tropical than in temperate regions (Cairns et al., 1997; Jackson
et al., 1997; Fan et al., 2008). Further, high below- to above-ground
biomass ratio is a common feature of alpine vegetation (Körner,
1989) and is regarded as an adaptation to the low temperatures of
these environments (Noy-Meir, 1973; Chapin III et al., 1987). It has
been suggested that a large mass of roots in cold environments
maintains higher soil temperature increasing the efficiency of
nutrient absorption by roots (Norbyr and Jackson, 2000). Further,
lower root turnover in extremely cold environments could result
in the accumulation of more below-ground biomass (Chen and
Wang, 2000; Zhou, 2001). Experiments have shown that plants
allocate less biomass to roots at temperatures that are optimum
for growth and more to roots at higher or lower temperature
(Lambers et al., 1998).
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J.W. Fan et al. / Journal of Arid Environments 73 (2009) 521–528
b
2500
2000
1500
1000
500
0
-4
-2
0
2
4
6
8
10
Below-ground biomass (g/m2)
Below-ground biomass (g/m2)
a
2500
2000
1500
1000
500
0
50
d
100
Below-ground biomass
Below-ground biomass
c
80
60
40
20
0
-4
-2
0
2
4
6
8
150
250
350
450
Mean annual precipitation (mm)
Mean annual temperature (°C)
10
Mean annual temperature (°C)
100
80
60
40
20
0
50
150
250
350
450
Mean annual precipitation (mm)
Fig. 7. Relationships between the site means of below-ground biomass (a, b) and the percentage of below-ground biomass (c, d) in three soil depth layers and MAT and MAP of 48
undefoliated grassland sites in Inner Mongolia (A, - - -: 0–10 cm; ,, d: 10 –20 cm; :,– – –:20–30 cm).
It is often assumed that root:shoot ratio increases with
increasing aridity (Sinnot, 1960; Walter, 1963; Pallardy, 1981;
Chapin III et al., 1993). Our observations indicated an opposite trend
with the proportion of below-ground biomass increasing as MAP
increased to the range of 250–350 mm (Fig. 3b). This trend was
reflected in the order of the percentage of below-ground biomass of
the grassland types from meadow steppe to typical desert
following the order of aridity of their environments. Similarly, in
a study of vegetation changes along an aridity gradient in Patagonia, Schulze et al. (1996) found below- to above-ground biomass
ratios of grassland communities declined as precipitation
decreased in the order typical grassland, semi-desert grassland and
desert grassland.
Noy-Meir (1973) indicated that root:shoot ratios between 1 and
20 have been reported for perennial grass and forb species typical
70
0-10 cm
4.3. Spatial variability of biomass allocation to above-ground tissue
fractions and dominant species
20-30 cm
10-20 cm
Below-ground biomass
60
50
40
30
20
10
0
MS
TS
DS
SD
of arid and semi-arid plant communities. For shrubs the root:shoot
ratio is usually between 1 and 3, but for some shrubs in semi-arid
Australia ratios as low as 0.2–0.3 have been found. Thus he
concluded that a high below- to above-ground biomass ratio is not
a universal characteristic of desert vegetation and may be more
closely related to certain life forms or to temperature regimes than
to aridity. Schenk and Jackson (2002) also indicated the ratio of
below- to above-ground biomass appears to increase with
increasing aridity only in herbaceous plants, but not in tree and
shrub plants. In our transect the proportion of shrub species
increased as the aridity of the grassland types increased (Table 1).
Shrubs usually extend roots deeper into the soil and functionally
this would allow uptake of water from a greater volume of soil –
a useful adaptation to arid environments. Adaptation in this way is
supported by the deeper below-ground allocation of biomass as
MAP declined (Fig. 7d) and for the desert grassland type (Fig. 8).
TD
Grassland types
Fig. 8. Mean (SE) proportions of below-ground biomass in three soil layers for five
grassland types in Inner Mongolia. MS: Meadow Steppe; TS: Typical Steppe; DS: Desert
Steppe; SD: Steppe Desert; TD: Typical Desert.
The variation of allocation of grassland biomass to leaf, stem,
and flower/fruit has not been studied frequently (Wang et al., 2001;
Fabbro and Körner, 2004). The trends we observed of increased leaf
and reduced stem as MAP increased and MAT declined were well
defined (Fig. 4) and were reflected in the values for the grassland
types in relation to their aridity (Fig. 5). These trends conform to the
classic xeromorphic adaptations of abundant mechanical tissue and
reduced leaf surfaces of plants that tolerate and survive in arid
environments (Sinnot, 1960). Usually in plant communities where
severe environmental stresses test the survival of plants a smaller
number of especially persistent species will be present, but where
environmental factors are not strongly limiting inter-plant
competition will also reduce the number of species (Grime, 1973).
This pattern is indicated by the higher percentage of biomass being
J.W. Fan et al. / Journal of Arid Environments 73 (2009) 521–528
contained in the first dominant of desert grassland compared with
the other grassland types and the greater percentages of other
species in the Typical Steppe and Desert Steppe communities
(Fig. 6). This pattern can be related to non-linear increase of plant
diversity associated with above-ground biomass in the temperate
grasslands of south-eastern Mongolia (Ni et al., 2007). In relation to
this the trends showing the increase in the percentage of stem as
site temperature increased (Fig. 4a) and precipitation decreased
(Fig. 4b) are indicative of the above-ground biomass becoming
more persistent and woody with increased aridity.
4.4. Applications
In providing forage for livestock production the vast grasslands
of Inner Mongolia make a valuable contribution to the economy of
China and to its food security (ECGRIM, 1990). The measurements
of grassland biomass presented provide essential baseline data for
the long-term land management of a region that has been subjected to increasing pressure for food production in recent times
(Du, 2006) and contains ecologically fragile environments (DAHV,
1996) likely to be sensitive to climate change. While the sites were
undefoliated for a period before sampling we are aware that
previous intensive grazing, cutting for forage, and burning related
to human activity (Du, 2006) may have reduced the biomass of the
grassland types studied below their natural levels. Long-term
studies of areas protected from grazing by domestic livestock
(SEPAC, 1992; Chen and Wang, 2000) will be a useful adjunct to this
study in gaining understanding of the biomass accumulation and
carbon storage capacity of the Inner Mongolian grasslands.
Below-ground measurements of biomass are difficult but they
cannot be ignored. This is emphasised by our finding that 92% of the
biomass of the Inner Mongolian grasslands is below ground. The
measurements of biomass and indications of how these are related
to the key climatic variables of temperature and precipitation will
be useful in the validation of models constructed to predict the
effects of climate change (Parton et al., 1992; Cao and Woodward,
1998). Although there is little information about the lability of
below-ground biomass (Fan et al., 2003; Hu et al., 2005), or the
effects of global climate change on the climate of Inner Mongolia
(Li et al., 2002; You et al., 2002; Bai et al., 2006; Hou, 2006), our
results suggest that warming of the Inner Mongolian climate could
reduce the capacity of the region to store carbon. This might be
partly offset if warming is associated with increased precipitation
allowing greater biomass production as predicted by Gao et al.
(2002), You et al. (2002), Jiang et al. (2004), and Ding et al. (2006).
Acknowledgements
The research was funded by the State Key Technologies R&D
Programme 2006BAC08B0304 and 2006BAC08B0504, and National
‘‘973’’ Project 2002CB412501. We are grateful to Lupeng Gao, Cheng
Zhang, Shengchang Qi, Libo Chen, Lei Liu, Qingping Zhou and others
for assisting in the field sampling, and to Christine Bezar, Landcare
Research, New Zealand, for editorial assistance.
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