bush encroachment in african savannas david ward
TRANSCRIPT
Bush encroachment in African savannas
David Ward
How do we go from this ?
to this ?
Namibia
India
Bush encroachment affects between 12- 20 million hectares of
South Africa
This is a biodiversity problem that is also
an agricultural problem
A multi-species grass sward is transformed into an impenetrable and
unpalatable thicket dominated by a single species of thorn tree
Heavy Grazing is often considered to be the cause
of bush encroachment
• Walter’s (1939) two-layer model – – grasses outcompete trees in open savannas by
growing fast and intercepting moisture from the upper soil layers,
– trees are thereby prevented from gaining access to moisture in the lower soil layers where their roots are mostly found.
– when heavy grazing occurs, grasses are removed and soil moisture then becomes available to the trees, allowing them to recruit en masse.
Post hoc ergo propter hoc
• The fact that many bush-encroached areas are heavily grazed means neither that grazing causes encroachment nor that Walter’s model is correct
• Bush encroachment is widespread in areas where there is a single soil layer and where grazing is infrequent and light
Magersfontein battlefield in 1899 and 2001 – it is now bush encroached in spite of an
absence of heavy grazing
Distribution of A. mellifera
Pniel study site (nr. Kimberley)
Acacia mellifera
Resource allocation models of plant community structure
David Tilman
Univ. of Minnesota
In order to predict the outcome of competition for a single limiting
resource, it is necessary to know:
• The resource level (=R*) at which the net rate of population change for a species is zero
• This occurs when vegetative growth and reproduction balance the loss rate the species experiences in a given habitat
R* and loss or disturbance rates
• The loss rate of a population is caused by numerous components, including disturbance, seed predation, fire and herbivory
• Independent of the causes of losses, the number of species competing, or competitive abilities of species in a habitat, average (equilibrial) resource levels (R*) will increase with the loss rate
R, Resource level
R*
Growth
Loss
Gro
wth
or
Lo
ss r
ate,
dB
/Bd
t
A population can only be maintained in a habitat if its growth rate > loss rate
R* will increase with the loss rate
Species C will exclude the other 2 species in competition because it has the lowest R*
R, Resource levelR*B
Growth
LossA
Gro
wth
or
Lo
ss r
ate,
dB
/Bd
tSpecies A
Species B
Species C
LossB
LossC
R*AR*C
Resource-dependent Growth Isoclines
• When a species consumes 2 or more resources, it is necessary to know the total effects of the resources on the growth rate of the species
• These effects can be summarized by the zero net growth isocline (ZNGI)
• This isocline shows the levels of 2 or more resources at which the growth rate per unit biomass of a species balances its loss rate
Perfectly essential resources
Population size decreases for resource levels in the white region and increases in
the green region
If a habitat is at point x, an increase in R1 will not affect population size. However, any increase in R2 will cause an increase in population size (& vice versa for habitat at y).
R2
R1
x
y
00
R2
When the ZNGI cross, each species will have a range of R* for the 2 resources where it will dominate
Species A dominant
Species B dominant
R1
A
B
Bc1
R2
R1
Bc2Bc
The consumption vector, Bc, has 2 components: c1 = amount of resource 1 consumed per unit biomass per unit time and c2 (~ for R2)
•Thus far, we have considered resource availability•Consumption also needs to be considered because it affects subsequent availability
The consumption vectors are
determined in large part by the plasticity
of plant growth
e.g. If R1 = a nutrient and R2 = light, the plant must allocate resources to above-ground growth (towards the light) and to below-ground growth (towards the nutrients)
Bc1R2 (l
igh
t)
R1 (nutrient)
Bc2Bc
When there are perfectly essential resources, the optimal strategy for a plant is to growso that the 2 resources are consumed in a way that they equally limit growth
R2
R1
cA
cB
A wins
B wins
A + BStably coexist
B
A
So
il W
ater
Soil Nitrogen
+N
+H2O
In South African savannas
Treeswin
Grasses win
Stablycoexist
Gra
sses
Grasses
Aca
cia
Acacia
How do grazing or fire affect the isoclines ?
• Grazing/Fire increase the loss rate for grasses
• Thus, R* for grasses is raised relative to that of the Acacia trees
So
il W
ater
Soil Nitrogen
Grasses
+N+H2O
Either of these scenarios is possible
Gra
sses
Aca
cia
Acacia
When ZNGIs do not cross, Acacias always outcompete grasses
So
il W
ater
Soil Nitrogen
GrassesAca
cia
Global climate change models predict that C3 trees will grow faster following climate
change than C4 grasses
C3 (trees)
C4 (grass)30
20
10
CO2 (ppm)200 600 1000
Ph
ot o
syn
thes
i s (m
ol. m
-2.s
-1)
Now Predicted
Increased atmospheric CO2 levels will mean that:
•Net photosynthetic rates of C3 trees will increase more than those of grasses
•Consequently, growth rates of trees will increase, and…….
Because more carbon will be available:
• Acacia trees will be able to invest more in carbon-based defences, such as condensed tannins (see e.g. Lawler et al. 1997, Kanowski 2001, Mattson et al. 2004)
•Consequently, loss rates of Acacias are likely to decline
Increased growth and decreased loss for Acacias results in a lower R*
R, Resource levelR*now
Growth
Gro
wth
or
Lo
ss r
ate,
dB
/Bd
t
Growth – after climate change
Growthnow
Lossnow
Loss – after climate changeR*predicted
This resource allocation model predicts that this will lead to bush encroachment because the ZNGI of Acacias will be lower (closer to the origin) than that of grasses on both axes
So
il W
ater
Soil Nitrogen
Aca
cia
Grasses
Do we have any empirical support for this model ?
So
il W
ater
Soil Nitrogen
+N
+H2O
Treeswin
Grasses win
Stablycoexist
Gra
sses
Grasses
Aca
cia
Acacia
• Treatments: rain, nutrients, grazing
• Completely crossed design
Pot ExperimentPot Experiment
Rainfall frequency overwhelmingly more important
than other factors
0
20
40
60
80
RN_ RO_ RNG ROG DN_ DO_ DNG DOG
Me
an
# s
urv
ivin
g p
lan
ts (
+S
E)
R = rain
D = dry
N = nitrogen
O = no nitrogen
G = grazing
_ = no grazing
Field experiment - randomized block designTreatments: rain, fire, nutrients, grazing
Rainfall addition increased Acacia
germination & survival
01234567
NitrogenAdded
Control
No.
Tre
e S
eedl
ings
0
1
2
3
4
5
Rain Added Control
No
. Tre
e S
eed
lings
Nitrogen addition decreased Acacia germination & survival
Grass No Grass
15N
Nat
ura
l Ab
un
dan
ce
-1
0
1
2
3
4
5
6
F(2, 165) = 93.9, p < 0.001
Competition
Jack Kambatuku, a PhD student of mine, has shown that Δ15N is related to competition with grass
Jack has shown that dry matter production is affected by competition
with grass
No Grass Grass
Dry
Mat
ter
Pro
du
ctio
n (
g)
0
2
4
6
8 = Total D.M. Production= AboveGround D.M. Prod.= BelowGround D.M. Prod.
Jack has also shown that free-growing trees have higher nitrogen content than trees growing with grasses
Interaction effect (Rain*Seeds): F=7.961, p=0.006
Vertical bars denote 0.95 confidence intervals
Added ControlSeeds
-1
0
1
2
3 130 year Max. Rainfall Natural Rainfall
See
dlin
g s
urv
ival
per
Plo
t
Experimental results thus far
• Grazing and fire not important• Rainfall far more important than other
factors• Rainfall frequency more important than
rainfall amount • Nutrients = second-most important factor• More nutrients = competitive advantage to
grasses = tree suppression• Thus, the resource allocation model
seems appropriate
The relationship between grass/tree biomass and rainfall
Annual Rainfall
Bio
mas
s
Trees
Grass
Without grazingOpen Savanna
In areas prone to bush encroachment, farmers should limit stock in WET years
Annual Rainfall
Bio
mas
s With heavy grazing
GrassTrees
We are also using Spatially-explicit Patch Dynamic
Models of Savanna Dynamics
Experiments show that mature trees are competitively superior to grasses while
grasses tend to outcompete immature trees
• This asymmetry in competitive effects implies instability
• However, weakening the suppressive effect of the grass layer on young trees in a patch of a few hectares can lead to an open savanna patch being converted to a tree-dominated thicket (bush encroachment)
• Once established, the thicket may take decades to revert to an open savanna
Figures show a time series of hexagonal subsets of a larger patch. Each (small) hexagonal represents a bush, the relative sizes of the hexagonals represent
relative bush sizes
A B C
D E F
Honeycomb rippling model
The predictions of the honeycomb rippling model are consistent with field data that
show that:
• Distances between trees increase with age
• Trees become more evenly spaced as they age
Distances betweentrees increase as they age
Variabilityin distances betweentrees decreases as they age
c.v.
Nea
rest
Nei
gh
bo
ur
Dis
tan
ce N
eare
st
Nei
gh
bo
ur
Dis
tan
ce
We showed experimentally that there is significant competition
between trees
0
5
10
15
20
25
30
% Size Increase
Neighboursremoved
Control
We have shown that:
•Any process that weakens the suppressive effect of grasses on young trees can convert an open savanna patch into a tree-dominated thicket (= bush encroachment)
•Thicket may eventually revert to an open savanna as a result of intra-specific competition between trees (= cyclical succession)
Viewed this way, bush encroachment may be a natural stage in savanna dynamics
Summary of patch dynamic model results
Another South African example of cyclical succession – Karen Esler
One of our students, Jana Förster, has shown that there may be strong
competition between two encroaching species, Acacia mellifera and Tarchonanthus camphoratus
Uncut plots
Cut plots
a
b
A. mellifera
T. camphoratus
With A. mellifera removed, T. camphoratus gets larger and has recruitment
>
>
Rel
ativ
e fr
equ
ency
Rel
ativ
e fr
equ
ency
Canopy diameter, cm
2 44 86 120 168 210 260 292 >
2 44 86 120 168 210 260 292 >
Overall Conclusions• Heavy grazing is only one of several sources of
loss to plants that affect R* and consequently competitive ability of trees against grasses
• Rainfall frequency and nutrient availability are important in initiating encroachment
• Resource allocation models are useful for predicting changes in savanna dynamics
• Patch dynamic models can explain bush encroachment as a natural stage in savanna dynamics