Spatial dynamics of biological soil crusts: bush
canopies, litter and burial in Kalahari rangelands
Berkeley, A., Thomas, A.D. and Dougill, A.J.
Proposed Journal – Journal of Arid Environments (??)
Too long for African J. of Ecology => target for an associated Dougill and Thomas paper
with our data from Mabuha / Tshane
Abstract
Introduction
The Kalahari is the vast, semi-arid savanna landscape that comprises much of Botswana
(Thomas et al., 2000). Livestock farming in the Kalahari is typified by the use of boreholes that
provide groundwater reserves to cattle. Intensive grazing pressure around these waterpoints,
has led to widespread concerns over rangeland degradation (e.g. Moleele & Perkins, 1998;
Dougill et al., 1999; Moleele et al., 2002), notably over the increased dominance of woody bush
species (Moleele, 1998). This process, referred to as bush encroachment, has been linked to
spatial heterogeneity of soil resources, capable of facilitating a reorganization of the community
into so-called ‘islands of fertility’ (Titus et al., 2002) that can contribute to the competitive
advantage of encroaching bush species (Schlesinger et al., 1990; Dougill & Thomas, 2004).
This paper aims to improve understanding of the mechanisms controlling relations between the
encroaching bush cover and sub canopy soil biochemical characteristics that will control future
ecological changes in Kalahari rangelands.
One component of the Kalahari system that has been largely overlooked in past research are
biological soil crusts, comprising cyanobacteria, green algae, lichens, mosses, microfungi and
other bacteria (USGS, 2001). Biological soil crusts are present in all arid and semi-arid regions
(Belnap & Lange, 2003). The ecological roles of these crusts include; increasing soil surface
stability by binding erodible soil particles into less vulnerable soil aggregates, thus decreasing
erosion by wind and water (Eldridge & Leys, 2003); fixing atmospheric nitrogen (Aranibar et al.,
2003), which is vital as nitrogen, after water, is the resource most limiting to primary
productivity in drylands (Belnap, 2002); also, some communities of biological crust have a
considerable photosynthetic element and so sequester soil organic carbon (Zaady et al., 2000).
Although crusts are usually associated with finer grain soils, Dougill & Thomas (2004)
documented a biological soil crust cover of between 19 - 40 % at a range of sites on Kalahari
sand soils. Fundamental to understanding the ecological significance of biological soil crusts in
the Kalahari is a comprehension of their spatial distribution. Several factors are recognised as
influencing crust distribution and development, especially substrate character, vegetation type
and cover, and disturbance levels. Thomas et al. (2002) have documented the differences in
biological crust cover for several substrate types in the Southern Kalahari. However, the
relationship between crust cover, vegetation cover and disturbance regime remains uncertain.
It has been demonstrated that plants growing in crusted soils may exhibit enhanced nutrient
levels, as compared to those growing on non-crusted surfaces (Belnap, 2002). However, it is
also reported that vegetation cover and biotic crust cover are negatively related due to the
effects of competition for light and moisture (Malam Issa et al., 1999), and nutrients (Harper &
Belnap, 2001). It is generally accepted that trampling, as a result of continuous grazing,
destroys biologically crusted surfaces (e.g. Eldridge, 1998). It follows that, in areas of intense
grazing such as around Kalahari boreholes, the spatial distribution of biological soil crusts will
be limited. However the hypothesis that crust cover will increase with distance from borehole
(i.e. with decreasing disturbance) is yet to be examined and may be complicated by the
increase in bush cover away from waterpoints (Ward et al., 2000).
Zaady & Bouskila (2002) describe disturbances as the key factors in determining crust
development in areas where physical conditions are relatively constant. Given the spatial
homogeneity of the Kalahari, in terms of altitude, relief and surface water (Thomas & Shaw,
1993), it is reasonable to impart a significant role to grazing disturbances in determining the
distribution of biological soil crusts. In this context bush canopies may represent quasi-discrete
environments, in which the response of crusts to local disturbance regimes is altered. This
phenomenon is yet to be tested with direct reference to disturbance intensity (i.e., with
disturbance as the independent variable), but could be vital in controlling response of the
Kalahari ecosystem to grazing related disturbance and to the relative abundance of grasses
and shrubs. That biological soil crusts may develop differentially within these sub-canopy
habitats would have important implications in terms of the spatial heterogeneity of resources,
ecosystem resilience and long-term ecological stability of rangelands.
As demonstrated above, it is probable that the roles of vegetation and disturbance on
biological crust distribution are not mutually independent of one another. The aim of this study
is to describe the distribution of biological soil crusts at grazed Kalahari study sites in terms of
the overlapping domains of vegetation and disturbance. In order to address this aim the
following objectives were chosen: (1) To deductively test models that suggest that there are
species-specific, sub-canopy protection impacts on the form and characteristics of biological
soil crusts; (2) To concurrently make an inductive survey of the association of both litter and
sediment burial, with the spatial distribution of biological soil crusts, that are potential
explanatory variables which have received little attention within the literature.
Research Design and Site Selection
This study aims to ascertain knowledge on the existence of relationships, principally between
bush species cover, disturbance and biological crust cover. In order to test the model proposed
by Thomas et al. (2002) regarding the protective capacity of encroaching bush species, two
explanatory variables – bush species (as well as bush interspace as a control; these variables
will be described as sub-habitats hereinafter) and disturbance – were sought. Analysis of crust
distribution in the bush interspaces was necessary to make sound inferences on the additional
role of bush canopies on crust development. In order to clarify that any differences in crust
cover between these habitats can be attributed to disturbance, it was necessary to record them
at differing levels of disturbance. Consequently, several sites were chosen for data collection,
at which crust distribution was recorded within the discrete habitats of bush sub-canopy and
interspace.
Research was undertaken during July 2003 on communal grazing lands adjacent to
Berrybush Farm, near Tshabong, Southern Kgalagadi District, Botswana. Four sites, at
different settings around a borehole, were selected for data collection. Given that disturbance
characteristics are likely to be very variable, disturbance was quantified at each site using a
disturbance index rather than the proxy of distance from borehole, as used in other studies
(e.g. Moleele & Perkins, 1998). The closest and furthest sites, with respect to the borehole,
correspond to the ‘sacrificial zone’ (Site 1) and ‘un-encroached zone’ (Site 4) of the piosphere
model described by Moleele et al. (2002), with the intermediate sites representing the ‘bush
encroached’ (Site 2) and ‘mixed’ (Site 3) zones respectively (Figure 1).
In addition to site disturbance, and site sub-habitat as independent variables, litter was used
as a further explanatory variable of crust development. This was achieved by concurrently
recording in situ litter cover within the crust cover survey. Although it is somewhat unexplored
in the literature, and thus essentially unknown, it is possible to attach a priori hypotheses to the
nature of crust response to litter. Litter may smother biotic crust and prevent photosynthesis, or,
alternatively, may only shade crust and provide a moister habitat more conducive to crust
development. Either way, the null hypothesis of no correlation makes this variable deductively
testable. In addition, there are no well-established theories on the occurrence of buried crust,
and only anecdotal references to the process appear in the literature (Belnap, 2002; Belnap &
Gillette, 1998; Harper & Belnap, 2001).
Given that biological crust cover has been shown to reduce sediment entrainment (Belnap &
Gillette, 1998; Eldridge & Leys, 2003), it is reasonable to assume that the magnitude of
sediment redistribution at a given site is inversely proportional to the amount of surface crusted
(i.e. in proportion to the ‘unconsolidated cover’). It is not possible to place an absolute value on
sediment redistribution based on the amount of substrate which is unconsolidated, since the
degree of entrainment and transport may be site specific, based on factors such as sediment
grain size, local wind regime and vegetation. However, the actual extent of redistribution, will
be proportional to the area of ground that is unconsolidated. In simple terms: a site with, say,
only 5 % biotic crust cover (and therefore 95 % unconsolidated) will have more mobile
sediment than a site will 60 % of the substrate crusted (40 % unconsolidated). Furthermore, it
is reasonable to suggest that the probability that mobilised sediment will settle upon an area of
biotic crust is equal to the area of biotic crust covered. That is, sediment blown across a site
with 90% biotic crust cover has a 90% chance of being deposited upon, and thus burying, biotic
crust. That the occurrence of crust burial is proportional to both crust cover and the amount of
ground which is unconsolidated, can be written in mathematical terms as:
Cburied = kC(100 – C).
where Cburied is the amount of crust buried, C is the percentage of ground crusted (the sum 100
– c representing the percentage area uncrusted, or unconsolidated), and k is the constant of
proportionality which, in this case, may describe the combined influences of climate, grain size,
and vegetation.
This model predicts maximum values for crust burial at those sites where crust cover and
unconsolidated substrate share a mutual maximum (i.e. ~ 50% each), and minimum values of
buried crust where the crust cover is either too high (too little unconsolidated substrate for
reworking), or too low (probability of burial too low). So it seems, theoretically at least, that the
process of crust burial is a trade off between sufficient crust cover to be buried and sufficient
unconsolidated substrate to supply the material for burial. Tthe aim here is to provide a basic,
inductive description of buried crust distribution. In this respect the incidence of buried crust
was added to that of regular biotic crust as one of the dependant variables. However, it is
hoped that the proposed model may provide a starting point from which to interpret the results.
Data Collection
Quantification of level of disturbance
At each site, disturbance levels were quantified using cattle track and dung frequency (as per
Dougill and Thomas, 2004). At each site, a 50m x 50m grid was established. The grid was
crossed at 10m intervals in two, perpendicular, directions. Cattle tracks and dung were counted
along each of these gridlines, cattle tracks being defined as well established ‘routes’, and dung
laying only within 0.5m either side of each gridline counted. The 0.5m value is arbitrary and for
the sake of consistency only. Values of dung indicate ‘sitings’ as opposed to total fragments.
Assessment of biological crust cover in interspaces
Crust cover data were estimated using a 0.5 m x 0.5 m quadrat at intervals of 10 m within a
50 m x 50 m grid. Percentage cover was estimated for each successionary stage of biological
soil crust (according to the morphological classification system of Dougill and Thomas, 2004),
buried crust, unconsolidated soil, litter and grass within five 0.5 m x 0.5 m quadrats.
Assessment of crust cover beneath bush canopies
The two most common bush encroaching species (Reed & Dougill, 2002) at the study area
were selected for sampling, the thorny Acacia mellifera and the non-thorny Grewia flava. The
sampling regime was simple – every bush within the aforementioned 50m x 50m quadrat was
studied. The canopy dimensions were measured taking the longest diameter on each bush,
and then the perpendicular diameter. To measure crust cover, several 0.5m x 0.5m quadrat
estimates were taken adjacent to one another along a line extending from the bowl to the
canopy edge in two directions – north and south – so as to account for any orientation
controlled differences in crust cover. Within each quadrat, crust cover (and morphological type
as per classification of Dougill and Thomas, 2004) was estimated, as well as buried crust,
unconsolidated substrate and litter.
Results
Bush canopies and biological crust cover
Table 1 summarises the main results obtained across all sites and sub-habitats. In order to
test the hypothesis that Acacia mellifera sub-canopies exhibit enhanced crust cover, analyses
were required in two contexts; between sites and between sub-habitats (Figure 2). One-way
ANOVA showed that there is a statistically significant difference between sites for the crust
cover in interspace sub-habitat (F3, 140 = 42.683, p < 0.01), rejecting the null hypothesis of no
disturbance-mediated impact on crust development across this zone. A Bonferroni adjustment
demonstrated significant differences between Sites 2 and 3 (Site 2, the least disturbed site,
having a crust cover significantly greater than Site 3; p < 0.01), and Site 3 having significantly
greater crust cover than both Sites 1 and 4 (p< 0.01), between which there was no significant
difference. Similarly, crust cover beneath the canopy of Grewia flava was differed significantly
between sites (F3, 252 = 27.837, p < 0.01). Within this sub-habitat, values of crust cover at Sites
2 and 3 were statistically taken from the same population, as were Sites 1 and 4; the former
pair nevertheless exhibiting significantly greater crust cover than the latter (p < 0.01). However,
beneath Acacia mellifera, there was no statistically significant difference in crust cover between
sites (F3, 504 = 1.862, p = 0.135; see Figure 2, top). This infers that Acacia mellifera equalizes
the effects of local disturbance by protecting the sub-canopy soil from disturbance, whereas the
two other sub-habitats show statistically significant variations across the disturbance gradient.
A further vindication of this appears when analysing between-sub-habitats at each respective
site. At Site 1 (Dung count = 7.2, the site most intensely disturbed), interspace and Grewia
flava crust cover were seen to be statistically indistinguishable from each other, although
ANOVA detected a significant difference between the three sub-habitats (F2, 266 = 33.045, p <
0.01). The difference occurred with Acacia mellifera showing significantly higher crust cover
than the other sub-habitats (p < 0.01; see Figure 2, bottom). At Site 2 (Dung count = 2.1, the
site least intensely disturbed), ANOVA revealed no difference in sub-habitat crust cover (F2, 225
= 0.449, p = 0.639). At Site 3 significant sub-habitat-differences for Site 3 were found (F2, 204 =
3.939, p < 0.05) with Grewia flava sub-canopies enjoying a statistically significant higher share
of crust cover, anomalous to our model. At Site 4, the sites differ significantly (F2, 201 = 10.364,
p < 0.01), with Acacia mellifera displaying significantly greater crust cover than Grewia flava (p
< 0.05) and the interspaces (p < 0.01).
Litter and biological crust cover
Litter was found to share no statistically significant relationship with crust cover at the quadrat
scale in each of the three sub-habitats. However, by comparing bush-averaged values for
crust cover and litter cover, a statistically significant, negative relationship is present for the
sub-canopy environment of Acacia mellifera (F1, 63 = 16.21, p < 0.01, R2 = 20.46%; see Figure
3A). Specifically, those bushes with a greater sub-canopy litter cover have significantly lower
biological crust cover. Furthermore, the variability in litter density beneath Acacia mellifera is
not random but related to bush size. As Acacia mellifera grow larger, the proportion of ground
covered by litter increases (F1, 63 = 7.42, p < 0.01, R2 = 10.53%; see Figure 3B). In contrast, no
significant statistical relationship between litter and biotic crust, nor between litter and bush
size, was detected beneath Grewia flava canopies. If litter is alleged to have a detrimental
effect on crust development, and is an increasing function of bush size, it follows that larger
bushes should host lower biological crust cover. This is demonstrated for Acacia mellifera in
the regression model of Figure 3C where sub-canopy biological crust cover is shown to be a
statistically significant function of bush size; relative sub-canopy crust area decreasing with
increasing bush size (F1, 63 = 61.46, p < 0.001, R2 = 49.38%). Again, no relationship of this type
was apparent beneath Grewia flava.
Additional support for the deterministic role of litter on crust development beneath the canopy
of Acacia mellifera is revealed when comparing the north and south axes of the bush. North
facing sides of Acacia mellifera were seen to have significantly less litter deposition than the
south facing sides (paired t test; t = 6.996, df = 64, p < 0.01), but significantly more biological
crust cover (t = 3.546, df = 64, p < 0.01). Whilst Grewia flava also exhibited a statistically
greater litter load beneath its southern facing portion (t = 3.278, df = 62, p < 0.01), crust
characteristics in the two directions were statistically indistinguishable (t = 0.210, df = 62, p =
0.417). Figure 3D shows, in sub-canopy profile, the nature of the relationship between crust
and litter. Litter appears to increase steadily from the canopy edge towards the base,
eventually gaining a density great enough to produce a decline in crust cover. Maximum
biological crust development appears to be juxtaposed between the disturbance-intense
canopy edge, and the litter-dense bush interior (Figure 3D).
Biotic crust burial
Buried crust was seen to be universally present across all sites and within all sub-habitats
(Table 1). Figure 4 compares the prevalence of interspace crust burial with that predicted by
the mathematical model introduced earlier. As predicted by the model, low biotic crust cover
(sites 1 & 4, 6 – 12 %) appears to produce a low incidence of crust burial (1 - 5 %), whilst those
sites with the highest values for crust burial (sites 2 & 3, 10 – 27 %) host intermediate biotic
crust cover (33 – 47 %).
Discussion
The limited migratory range of livestock, whose physiology constrains them to graze within
several kilometres of drinking water (Moleele & Perkins, 1998), has the effect of concentrating
cattle into stocking densities greater than those generally presented to the Kalahari ecosystem
by nomadic pastoralism or wildlife (Leggett et al., 2003). Because of the intense, localized
grazing pressure, a zone of decreasing intensity of disturbance (or piosphere) radiates from
waterpoints (Moleele & Perkins, 1998). This adds a new environmental gradient to the ecology
(Moleele et al., 2002) of a region subject to otherwise relatively homogenous environmental
conditions. This recent ecological forcing has led to the encroachment of bush species, notably
Acacia mellifera and Grewia flava (Moleele & Perkins, 1998; Reed & Dougill, 2002). The
mechanism appears species-specific, owing much to the selectivity of browsing livestock, but
also potentially the relationships between bush canopies and the underlying soil properties. It
has been suugested that once established the bush encroachers may monopolize the soil
moisture and nutrients (Moleele et al., 2002), preventing the original vegetation from
recovering, especially if nutrients and water retention is increased in sub canopy habitats
resulting from increased crust cover (Dougill & Thomas, 2004). Bush encroachment represents
the shifting of the ecosystem into another stability domain, as described by Bengtsson (2002)
and conceptually modelled by Dougill et al. (1999).
However, the causal mechanisms
affecting the stability of this ecological domain remain uncertain and require investigations on
grazing disturbance gradients to investigate them further.
Results presented in this paper support those given by Dougill & Thomas (2004) and Thomas
et al. (2002) which describe enhanced biotic crust cover beneath the canopies of shrubs, as
compared to the more crust sparse shrub interspaces. Furthermore, this study has shown that,
whilst biological crust cover in the shrub interspaces and beneath the canopy of Grewia flava
varies significantly across a disturbance gradient, biological crust cover beneath Acacia
mellifera remains at the same elevated level. At the least disturbed site all three sub-habitats
(the sub-canopy zones of Acacia mellifera and Grewia flava, and the interspace) shared similar
levels of crust cover. This is an important result as it shows that, where disturbance is limited,
the three habits converge in terms of crust cover. That is, when disturbance is sufficiently low,
each sub-habitat will provide equally suitable habitats for crust development, suggesting that
disturbance is the variable that mediates the disparities in crust cover. Consequently, the crust
cover beneath Acacia mellifera canopies across a disturbance gradient is comparable to the
crust cover seen in the interspaces (and underneath Grewia flava) at low disturbance. This
demonstrates that Acacia mellifera mitigates the effects of local disturbance. Given that a
similar effect is not seen with Grewia flava, this impact is species-specific resulting from the
dense, thorny nature of the Acacia mellifera canopy.
Aranibar et al. (2004) found that, although no Acacia species showed evidence of direct
nitrogen fixation they nevertheless maintain a high N content, suggesting another mechanism
of N acquisition. If it can be demonstrated that Acacia mellifera are the recipients of crust
associated nutrients (as demonstrated elsewhere for other species, e.g. Evans & Belnap, 1999;
Harper & Belnap, 2001) then an important symbiosis may be revealed. Such a relationship
would suggest that the alternative stability domain established with bush encroachment may
exhibit intrinsic resilience due to the association between bush canopies and sub-canopy
biological soil crust development.
Austin (2002) suggested that, when dealing with ecological relationships, statistical
significance alone provides an insufficient basis and thus should be accompanied by some
form of ecological rationale. For the case discussed here, although litter was not seen to share
any statistically significant relationship with biological crust cover at the quadrat sample level,
bush averaged values for litter were deterministic of sub-canopy crust cover (Figure 3). An
explanation for this may be based on litter density and simple probability. Given that litter may
be mobile, in situ characteristics of litter recorded at any given point in space and time may be
meaningless with respect to explaining crust development. Having recorded the presence of
litter in a particular quadrat sample it does not necessarily follow that it has lain there for
sufficient time to have any effect on the substrate underneath. It is unknown for how long
crusted ground must be covered before it will die. We suggest that whatever the critical time
period within which a crust will die if smothered, there will be a critical density of litter that,
despite redistribution, will lead to a greater probability that a respective piece of substrate will
remain covered rather than be uncovered. Accumulation of litter cover underneath bush
canopies, especially Acacia mellifera, results from both the significant autochthonous input
from the bush itself (Dougill & Thomas, 2002) and the bush canopy intercepting wind-blown, or
allochthonous material (Titus et al., 2002).
Also of note is the deterministic nature of sub-canopy litter load as dependent on bush size.
As a bush grows, the amount of litter it will produce is not simply proportional to the area it
covers, but is more likely to bush volume. From this, it follows that the rate at which the area
covered by a bush canopy increases when a bush grows, does not produce an equivalent
increase in litter production, but a greater than equivalent increase. However, this three
dimensional biomass is deposited as litter over a two dimensional area so, as the size of the
bush increases the litter per unit area will increase also. Whatever the explanation for the
statistically significant increase in sub-canopy litter beneath Acacia mellifera, the intriguing
question is one of the biological crust response to bush canopies of increasing size and thus,
increasing litter density.
The preceding sections describing Acacia mellifera sub-canopy litter dynamics convey two
main points: (1) that litter imparts an average and detrimental effect upon biological crust
development (Figure 3A), and (2) that sub-canopy litter cover per unit area increases with
Acacia mellifera size (Figure 3B). These two principles are subsumed holistically within the
regression model of Figure 3C, and attach a causation to the statistical model – i.e. sub-canopy
area-relative biological crust cover is reduced beneath Acacia mellifera bushes of increasing
size as a consequence of their increasing litter load. Figure 3D shows that the distribution of
crust and litter beneath the canopy of Acacia mellifera is not uniform or random, but loosely
sorted into an interior dominated by litter and an outer concentric zone of increased biological
crust development. It follows that the net increase in litter cover with increasing bush size, and
corresponding decrease in area-relative crust cover, is mediated through a migrating outward
of the litter-dominated bush interior as total bush volume becomes gradually larger. Figure 5
demonstrates this schematically with reference to an absolute crust model based on the
logarithmic model used in Figure 3C. At relatively small bush sizes most of the sub-canopy
floor is crust dominated, with only a small area dominated by litter (this is supported empirically
by Figures 3A and 3B). As the area underneath the bush increases the zone of litter dominance
increases in proportion with bush volume and thus spreads outwards, pushing the zone still
conducive to crust growth further out. At this stage, the absolute area covered by crust may still
be increasing with bush canopy growth. However, eventually the litter load increases more
rapidly than canopy edge is advancing, resulting in the zone of litter dominance expanding at
the expense of the crust dominant zone. According to the model presented here, the biological
crust is progressively pushed towards the bush exterior until at a radius of 7.41m the bush
produces enough litter as to cover the entire sub-canopy zone with sufficient a density as to
exclude biological crust development. At these sizes, the bush interior may be unfavourable to
photosynthesis and thus a new ‘bush interior’ zone emerges which is conducive to neither
primary production, nor biological crust development. Field observations suggest that Acacia
mellifera rarely reach such sizes and thus the symbiotic relationship between Acacia mellifera
and biological crust communities may be sustained throughout the life cycle of the bush.
Since it has been established that a covering of litter may be of detriment to biological crust
development, it is reasonable to suggest that sediment burial may have a similar smothering
effect on crusts. The process has received only passing references in the literature. For
example, Harper & Belnap (2001) sampled from a station “where wind-borne sediment
deposition precluded the growth of crustal organisms” (p. ??), and Belnap (2002) ascribes long
term declines in nitrogenase activity in disturbed crusts to the death of buried material. This
study has presented the first comprehensive survey of the occurrence of biological crust burial.
Buried crusts were found at all sites, and within all sub-habitats, but to differing degrees. The
mathematical model presented to describe crust burial in terms of biological crust cover
appears to provide a good approximation to the burial observed within the interspace subhabitat (Figure 4).
The data shows crust burial not to be a special case but as having ubiquitous presence in the
areas studied. It is unclear what happens to biological crusts after burial. According to Belnap &
Gillette (1998), 75% of the photosynthetic biomass of biological crusts is from organisms in the
top 3 mm, and sediment burial results in the death of these organisms. Should crust burial be
shown to cause microbiological communities to die then the model proposed may have
important consequences. If crust burial is at a maximum where crust cover and unconsolidated
soil are approximately equal (i.e. around 50% each) then it may provide a negative feedback on
spatial crust growth; as the crust cover at a given site increases from low values crust burial will
also become more evident, dampening any further growth. This may explain the apparent 40 %
limit on crust cover in the Kalahari seen in several studies including this one (Thomas et al.,
2002; Aranibar et al., 2003; Dougill & Thomas, 2004). A further consequence may be that
smothered crust, after dying, might release the sediment which had been consolidated by the
former crust, meaning that, especially in times of drought and consequently metabolic latency
in the biological crust (Zaady et al., 2000), the process of crust burial may contribute further
available sediment for redistribution. Issa et al. (2001) however reported that formerly crusted
buried substrates retain their consolidation at depth ‘where filaments enmesh the particles
among which they once grew before they were buried’, suggesting that this scenario maybe
less important.
Conclusion
This study has presented data that supports the view that the bush Acacia mellifera mitigates
the effects of cattle-related disturbance beneath its canopy. The protection offered by this bush
to the sub-canopy soil permits the enhanced development of a biological crust community, as
compared to the more disturbance-intense bush interspaces as well as beneath shrubs less
able to deter cattle, such as Grewia flava. It has been reported in the literature that biological
soil crusts provide additional nutrients to those plants growing in crusted soils. Consequently, it
seems reasonable to suggest that the ability of Acacia mellifera to withstand drought and
grazing and its association with a significant sub-canopy biological crust cover, even in
disturbed areas, leads to the stability of the bush encroached ecosystem state that is now
prevalent across much of the Kalahari. Litter accumulation under Acacia mellifera imparts a
net negative effect on biological crust development, the important variable being litter density
as opposed to any in situ litter characteristics. The incidence of buried crusts highlights the
ubiquity of crust burial, and suggests this as an important (but under-researched) process
regulating the spatial occurrence of biological soil crusts. A model is proposed relating the
extent of crust burial to biological crust cover, portraying crust burial as a non-linear system
with potential feedbacks of direct consequence for the spatial development of biological crust
communities.
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Figure 1: Study site location
Figure 2: Between site and sub-habitat differences in crust cover with respect to disturbance
Figure 4: Relationship between biotic crust cover and crust burial. The model predicts a low
occurrence of buried crusts at the two extremes of crust cover, i.e. very low and very high
values for crust cover. Note that the absolute values predicted here are not important as
sediment redistribution might realistically be site and seasonal specific. What is being proposed
here is that crust burial will be relative to crust cover in the mathematical form described in the
text, and hence, the graphical form shown here, across the potential values for crust cover (i.e.
0-100%). The steepness and vertical position of the curve may alter according to site
characteristics but the basic shape, and consequently values relative to each other, will remain
similar. The data approximates this shape, supporting the model, however too few data points
are present and the spread of values leaves much uncertainty.
Figure 5: Proposed model of crust/litter dynamics beneath the canopy of Acacia
mellifera (see text)