Introduction
Between 9000 and 6000 years BP, a wet phase peaked
across north Africa. During this so-called “African Humid Period” (AHP),
large areas of the nowadays hyperarid Sahara and arid Sahel region were
vegetated , a dense fluvial network was
developed, and open surface water was widespread .
Fossil pollen records indicate that the Sahel boundary was shifted northwards
by 5 to 7∘ to at least 23∘ N and
tropical plant taxa might have used river banks as migration paths to enter
drier environments . Vegetation cover was a diverse mosaic
of xeric and tropical species whose ranges do not overlap today
. This “greening” was triggered by changes in the Earth's
orbit, resulting in a stronger insolation and higher temperatures in the
boreal summer, accompanied by an intensification of the summer monsoon
. However, the increase in insolation alone
is insufficient to explain the vegetation coverage reconstructed from palaeo
records. It has been shown that several feedback mechanisms including ocean
, surface water coverage by lakes and
wetlands , and vegetation and soil albedo
could have amplified the
orbital forcing. We here provide a conceptual model adjusted to AHP plant
types as a tool to study how plant diversity as an additional parameter might
have affected the climate–vegetation interaction under changing
precipitation regimes.
first proposed a positive feedback between vegetation and
precipitation in the Sahel to explain the self-stabilization of deserts. This
positive feedback provides a mechanism that might allow for the existence of
multiple stable equilibria, first shown in coupled model simulations by
and . Depending on climate and
environmental conditions, the Sahara could exist in a “green” state with
high vegetation cover and a “desert” state without vegetation
. The potential non-linearity of this
feedback might cause an abrupt transition between these states when the
system reaches a “tipping point” . Several climate
model studies reproduced such an abrupt transition from “green” to
“desert” state at around 5500 years BP for western Africa
e.g. and reconstructions
of dust flux in the Atlantic supported an abrupt ending of the AHP at least
for the western part of the Sahara .
Later studies highlighted the complexity of desertification history and the
variety in timing and rate of regional changes. They challenged the
hypothesis of an abrupt vegetation decline and doubted the existence of
a strong positive climate–vegetation feedback in subtropical Africa. Pollen
and sediment records from Lake Yoa in eastern Africa indicated a more gradual
transition from “green” to “desert” Sahara
, implying that the vegetation-climate
feedback was rather weak. Palaeo-hydrologically dated records from fluvial,
lacustrine, and palustrine environments supported a gradual transition from
wet to dry conditions . Observation based
estimates of feedback strength in northern Africa showed little direct
evidence of a strong positive vegetation effect on large-scale precipitation
. In the framework of the Paleoclimate Modeling
Intercomparison Project, Phase II (PMIP2), some models even suggested
a negative feedback over northern Africa for the mid-Holocene
. demonstrated an abrupt
vegetation collapse in coupled transient simulations, but the authors
attributed this to a non-linear vegetation response to a precipitation
threshold in the presence of strong climate variability, independent of
a climate–vegetation feedback. recently showed
a positive effect of vegetation on precipitation caused by evapotranspiration
effects rather than albedo effects.
introduced a new aspect in the discussion, stating that
plant diversity in terms of moisture requirements could affect the strength
of climate–vegetation feedback. In a conceptual model study, with
hypothetical discrete plant types, they demonstrated that in coupled
interaction with precipitation, sensitive plant types tend to sustain longer
with decreasing precipitation, while resilient plant types disappear earlier
than they would do on their own. The mean vegetation coverage decreased more
gradually with strong fluctuations under drying conditions, capturing
the decline in pollen influx into Lake Yoa between 6000 and
4000 years BP fairly . Plant diversity might therefore
increase the stability of the climate–vegetation system in semi-arid
regions, buffer the strength of individual plant–precipitation feedback and
prevent an abrupt vegetation collapse. The authors suggested that plant
composition is of high importance for the rate of transition and a reduction
in functional plant diversity may lead to an abrupt regime shift.
We critically reassess the conceptual mode by here
from an ecological point of view, and provide an improved version that
represents the diversity of AHP plant types. Referring to the current state
of knowledge in ecological literature we evaluate the representation of
plant–plant interaction and plant–climate feedback in the conceptual
approach. We further discuss how the suggested conclusions fit in an
ecological context. Based on the assessment, we adjust the original model to
AHP vegetation by the modification of four fundamental aspects. First, the
growth ranges in terms of moisture requirements are extended by upper limits
to represent full environmental envelopes. Second, data-based AHP plant types
replace the hypothetical plant types. Third, the tropical gallery forest
type, indirectly linked to local precipitation, follows mainly the gradual
insolation forcing with a linear approximation. Fourth, we replace the
dimensionless vegetation cover fraction with individual effective leaf areas
to capture different contributions to climate–vegetation feedback. These
changes allow for studies on the roles of different real plant types in an
ecosystem and their combined climate–vegetation feedback under changing
environmental conditions.
The conceptual approach by Claussen et al. (2013)
The model formulation by Claussen et al. (2013)
The approach by is based on a conceptual description of
climate–vegetation feedback in semi-arid regions
. The applicability is restricted to a region
that experiences a uniform climate, which approximately corresponds to the
grid size of a general circulation model (GCM) in the order of
100 km2. Within this region, the diversity of coexisting plant
types i=1,…,N reflects the heterogeneity of the environment that
provides ecological niches for N different plant types. Diversity is
defined here in terms of specific moisture requirements and sensitivities to
changes in mean annual precipitation P. The model does not explicitly
account for direct plant–plant interactions such as competition or
facilitation. assume that each plant type can occupy
a share of 1/N of the ecological space. The assumption of niche
stability/conservatism – a concept that assumes species maintaining the
parameters of their ecological niche following environmental change
– prohibits the
replacement of disappearing plants by remaining plant types. These
assumptions are hereinafter referred to as the “niche approach”
. The change of relative vegetation cover fraction
Vi (non-dimensional between 0 and 1) under external forcing is
determined by
dVidt=ViE(P)-Viτ,
with the time step t in years, setting t=0 for present day and negative
values for the past, and the vegetation equilibrium timescale τ=5 years . The equilibrium vegetation cover fraction
ViE is a function of mean annual precipitation P, and is
shaped by lower and upper precipitation thresholds, PiC1 and
PiC2, respectively. Their difference DiC=PiC2-PiC1>0 determines the slope of ViE(P) in
the intermediate precipitation regime
ViE(P)=1P≥PiC2(P-PiC1)DiCPiC2>P>PiC10P≤PiC1.
When all plant types interact together with climate, the mean vegetation
cover fraction VS is calculated as the average of all individual plant
types:
VS=1N∑i=1NVi≤1,
assuming that the atmosphere reacts to the average properties of the whole
area. The justification for this assumption is that the difference in crucial
surface parameters such as albedo and hydrological properties is smaller
between considered plant types than the contrast to desert.
Accounting for climate–vegetation feedback, precipitation is a combination
of a background precipitation Pd in absence of vegetation that
changes with external gradual insolation forcing, and a precipitation
component induced by vegetation feedback. The equilibrium precipitation
PE is defined as
PE(VS,t)=Pd(t)+DB⋅VS,
with the climate feedback coefficient DB that determines the feedback
strength. For simplicity, assumed the same DB=140 mmyr-1 for all plant types , implying that
the feedback is only sensitive to vegetation cover but not to composition.
The background precipitation Pd changes linearly with time, mimicking
the weakening of the west African monsoon due to continuous change in
insolation forcing:
Pd(t)=Pd01-t+6500/T,
where Pd0=300 mmyr-1 is the initial precipitation of the
simulation period T=6500 years . The
natural variability in precipitation, independent from vegetation, is
implemented as additional white noise forcing PN(t) in the total
precipitation
P(VS,t)=max((PE(VS,t)+PN(t),0)).
The intersections of P and V in a vegetation–precipitation diagram
indicate equilibrium-coupled states, see Fig. 1. System instability and
multiple equilibria only exist for a sufficiently strong positive vegetation
feedback with DB>DiC .
Vegetation–precipitation stability diagram (ViE,
PE) for two hypothetical plant types i=1,2 after
. Full lines depict the equilibrium curves for
vegetation cover ViE(PE) for plant type 1 which
is sensitive (red) and for plant type 2 which is resilient (green) to changes
in precipitation. Dashed blue lines show hypothetical equilibrium
precipitation curves PE(ViE) for different time
slices (4500, 4900, 5300, 5700, 6100, and 6500 years BP, from left to
right). Intersections between the two types of curves indicate equilibrium
coupled states which can be stable or unstable.
Assessment of the model set up by Claussen et al. (2013)
The basic units in the conceptual model by are plant
types that reflect the heterogeneity of the environment, occupying different
n dimensional niches. In the actual realization of plant types in the model
formulation, plant diversity is only expressed in terms of different
precipitation thresholds as a proxy for moisture requirements, which reduces
the fundamental multidimensional niche to one portion of its climatic
component. The choice of thresholds implicitly defines plants' sensitivities
to changes in precipitation. Moisture requirement is an established measure
to characterize diversity in recent African ecosystems , and
the measure is appropriate in the conceptual model because hydrology is the
main determinant of plant growth in the subtropics on the considered scale of
the order of 100 km2 . For a more versatile
description of plants' niches and the explanation of actual vegetation
composition and spatial distribution within the considered region, further
crucial determinants need to be taken into account. The coexistence of trees
and grasses in subtropical regions and the maintenance of their ratios is
a complex topic, studied for years in the framework of the “savanna
question”, but still not well understood
. The complexity
arises from the many aspects involved such as mean annual precipitation,
seasonality, soil type, soil moisture, surface water availability, community
structure, competition, community history, and disturbances (fire,
herbivory).
With the niche approach, design the effective
interaction between vegetation and climate from bottom up. Each plant type
has specific requirements and responds individually to changes in mean annual
precipitation, but the combined interaction of all considered plant types
with precipitation determines and smooths the evolution of mean vegetation
cover on a larger scale. This approach is supported by who
propose that higher order features of ecosystems emerge from plants'
individual responses to changing environmental conditions. Ecosystem features
such as composition and physiognomy have a large impact on the exchanges of
energy, moisture, aerosols, and trace gases between the land surface and
atmosphere and finally on precipitation.
The niche approach also implies that once a specific plant type retreats
owing to water scarcity, there may not be any other type that is able to
occupy its place in the ecological space. From an ecological point of view,
existing plants likely benefit from the extinction of others by having less
competition and more resources available. It is questionable whether these
succeeding species can occupy the niches (ecological space) of disappearing
species, including their way of using resources, and overtake their ecosystem
functions, or if they just occupy the available barren area (geographical
space).
Apart from the diversity in moisture requirements, the variety in feedback
strength and climate impact arising from the particular plant properties is
not sufficiently reflected in the original model: the dimensionless potential
vegetation cover and the homogeneous climate feedback coefficient DB
mainly account for the albedo effect of the total area while inter-plant
deviations in colour, reflectance properties, surface roughness, potential
leaf area, and evapotranspiration capacities are neglected.
Assessment of the interpretation of results by Claussen et al. (2013)
Based on a number of simulations, concluded that
diversity can have a buffering effect on ecosystem performance and further on
the strength of climate–vegetation feedback. They reasoned that in
species-rich ecosystems, the likelihood of some species being pre-adapted to
changing environmental conditions is higher than in species poor systems.
This relationship between high diversity and ecosystem stability has been
debated for several decades, among other things due to the inconsistent
definition of stability. We follow here, who defines
stability as a twofold system property: resilience is the speed with which
a community returns to a former state having been displaced from it by
perturbation, while resistance is the ability to avoid such displacement.
Before 1970, ecologists assumed a positive relationship between biodiversity
and ecosystem stability based on simplified observations
. This intuitive idea was questioned by
, who proposed a destabilizing effect of species richness on
ecosystem dynamics based on a statistical model approach with random
populations. Long-term field studies on grasslands indicated a positive
relation between diversity and ecosystem stability, while functional
diversity seemed to be more important than the total number of species
. The overall opinion is nowadays that
diversity might on average increase the stability of ecosystems while it
serves more as a “passive recipient of important ecological mechanisms that
are inherent in ecosystems” than as the driver of this positive relationship
. On larger scales, extrinsic factors such as disturbance
regimes and site history might become the main determinants of community
stability . In the light of this, the finding of
a positive diversity–stability relationship by is
reasonable for a region of the order of 100 km2. In connection
with this relationship, concluded that the stability of
a climate–vegetation system can determine and arise from individual plant
types' presence over longer timescales. In combined interaction with
climate, sensitive plants likely grow longer than they would do on their own
as they benefit from additional water and facilitation effects in a more
life-sustaining environment. The duration of persistence of resilient plants
is likely shortened as they suffer to a certain degree from additional
competition . This effect occurs in the model even though
interactions are not explicitly modelled.
One of the main conclusions by was that strong or weak
climate–vegetation feedback was hard to diagnose and disentangle regarding
abrupt climate changes on a regional scale. The feedback between climate and
a certain plant type could be strong, but this might be capped in combination
with other plant types, resulting in a gradual decline of total vegetation.
Indeed, vegetation composition can play a crucial role for the ecosystem and
the removal or introduction might change the system stability by changes in
the ratio of individual influences . In order to keep
ecosystem function stable, a minimum number of functional types is required
that occupy a minimum number of niches. The addition of taxa results in
a more and more complex network of interactions. While some taxa are
redundant, others are irreplaceable. If these so-called “keystone species”
disappear, the system might collapse. The appearance of new taxa could also
interfere with networks and change energy and matter fluxes in the system,
resulting in a destabilization of the ecosystem . Hence,
argued ecologically reasonably that it is difficult to
determine the origin of system stability as the overall feedback strength
depends on species composition. These difficulties are not inconsistent with
previous studies that proposed strong climate–vegetation feedback, resulting
in abrupt shifts from a stable “green” state to a stable “desert” state.
For example, simulations by were performed with the
lowest possible number of PFTs, one tree and one grass. The low diversity
implies a high likelihood for abrupt transitions
.
Application of the conceptual model by Claussen et al. (2013)
to AHP vegetation
Does the model by Claussen et al. (2013)
capture the diversity of AHP vegetation?
The approach by offers a useful tool to deal with the
question how diversity might affect climate–vegetation interaction in
semi-arid regions. However, the model reaches its limits when it comes to the
application to AHP vegetation reconstructed from pollen, here referring to
. applied “White's classification of
Africa” () to palaeo-botanical proxy data from several
locations in Africa and from the African Pollen Database in order to
reconstruct the Holocene vegetation distribution in relation to open surface
water, derived from palaeo-hydrological proxies. Pollen samples were grouped
into four phytogeographical types, which are mainly characterized by their
precipitation requirements and physiognomic structure: (1) Guineo–Congolian
type (tropical humid semi-deciduous or evergreen forest taxa,
>1500 mmyr-1); (2) Sudanian type (tropical dry forest,
woodlands, and wooded savanna taxa, 500 to 1500 mmyr-1);
(3) Sahelian type (grassland or wooded grassland taxa, 150 to
500 mmyr-1), and (4) Saharan type (steppe and desert taxa,
<150 mmyr-1).
Throughout this paper, we use the terminology of phytogeographical plant
types after whenever we refer to our work, including the
descriptions of the adjusted model and simulations as well as results,
discussions, and conclusions. Since literature often refers to the terminology
of physiognomic vegetation types, we stick with their terminology in
citations and indicate the corresponding phytogeographical plant types after
in brackets to prevent confusions.
When defining the precipitation thresholds for each plant type, a direct
relation between precipitation and plant available water was assumed by
. This is not appropriate for all AHP plant types.
Tropical Guineo–Congolian taxa (GC type) cannot be captured with this
approach using the parameters of because the initial
precipitation P(VS,-6500) is too low to reach their minimum threshold
PGCC1. These species grow in gallery forest or ripicolous
stripes where a high water availability is more or less constantly provided,
and local precipitation is of minor importance. Xeric species of the Saharan
and Sahelian type have special adaptations such as deep trap roots or
succulent tissues e.g. that allow them to grow far
below the minimum threshold for a phytogeographic plant type given by
literature. Nonetheless, growth ranges of phytogeographic plant types provide
a point of reference, and expose the fact that the range of precipitation thresholds
assumed by , between 150 and 370 mmyr-1, is
far below the variety of thresholds of AHP vegetation reconstructed from
pollen .
Regarding the calculation of mean vegetation with the niche approach,
climate–vegetation interaction provides the expected gradual decline in mean
vegetation cover towards the end of the AHP. Niches can only be occupied by
specialized plant types, for instance gallery forests (GC) cannot grow beyond
a certain distance from surface water while steppe plants (Saharan type) do
not survive on moist soils along river banks. However, the niche approach
does not account for the evolution of vegetation composition in terms of
spatial succession. Pollen data from eastern Africa suggest the decrease in
tropical trees and grasses (GC and Sudanian type) starting at around
5500 cal yr BP going hand in hand with the expansion of characteristic
desert taxa (Saharan type). The demise of tropical trees (GC and Sudanian
type) was temporarily compensated by Sahelian elements .
For the geographically explicit simulation of vegetation change, a model more
sophisticated than our conceptual approach is required.
The large diversity of plant properties besides moisture requirements
highlights the importance of plant-specific feedback strengths. With
a dimensionless vegetation cover fraction, mainly
account for a homogeneous albedo. Differences in colour and reflectance
properties are not implemented. Generally, tropical leaves (GC and Sudanian
type) are darker than steppe grasses (Saharan type) and
their albedo-feedback impact should be weighted differently. Structural
properties are homogenized, assuming the same feedback coefficient for all
plant types. The leaf area of tropical taxa (GC and Sudanian type) might be
up to 3 times higher than that of steppe taxa (Saharan type)
, resulting in strong evapotranspiration differences.
Evapotranspiration seems to be involved in important feedback mechanisms that
influence the strength of the west African monsoon .
In summary, the original conceptual model by seems to
capture the stabilizing effect on ecosystem performance by accounting for
differential moisture requirements and homogeneous feedback for all plant
types. Important determinants of vegetation cover, such as fire or
competition, and individual feedback strengths due to albedo and
evapotranspiration differences are omitted. The diversity of AHP vegetation
reconstructed from pollen data cannot be captured; especially tropical
gallery forest plant types (GC type) are not represented.
Model adjustment
In order to apply the conceptual model by to AHP
vegetation, we modify different aspects as described in the present section.
The environmental envelopes in terms of moisture requirements are extended by
an upper precipitation threshold. Data-based AHP plant types are implemented,
namely the Saharan type, Sahelian type, Sudanian type, and Guineo–Congolian
type. Specific tolerance threshold values for these plant types, except for
the Guineo–Congolian gallery forest type, are derived from observations on
characteristic species (see Table 1), implicitly accounting for competitive
interactions and fire that cannot be separated from water constraints. The
optimum growth ranges are based on pollen analysis by . The
relative vegetation cover fraction (initially Vi,max=1) is
replaced by a weighting factor modelled after the leaf area index. This
effective leaf area Li (in m2 per unit niche area) of each
plant type i changes according to Vi in Eq. (1). In equilibrium,
LiE is specified as a function of total precipitation P:
LiE(P)=0P≥PiC4Li,max-(P-PiC3)⋅Li,maxDiC2PiC4>P≥PiC3Li,maxPiC3>P≥PiC2(P-PiC1)⋅Li,maxDiC1PiC2>P≥PiC10P<PiC1,
with a maximum potential extension Li,max. DiC1=PiC2-PiC1>0 for the increasing branch and DiC2=PiC4-PiC3>0 for the decreasing branch of the environmental
envelope. For simplicity, we aggregate all surface parameters crucial for
climate–vegetation feedback – leaf area, albedo, and hydrological properties
– in Li, and keep the climate feedback coefficient DB constant
for all plant types. This is possible because LS and DB show up
as a product in our model (see Eq. 11). Values for Li,max are
chosen to qualitatively represent the variety of these aggregated properties
following observation-based classifications . A high
Li also indicates a dark leaf colour, characteristic for tropical taxa
(GC and Sudanian type), which is related to a low albedo, a strong
climate-feedback, and a potentially abrupt collapse. A lower Li
represents dry bright leaves, characteristic for xeric taxa (Saharan and
Sahelian type), and is associated with a low albedo feedback potential. The
differences between considered plant types might be smaller than the contrast
to desert, but investigating individual roles necessitates disentangling the
contributions.
Precipitation thresholds PiC1 to PiC4 (in
mm yr-1) and maximum effective leaf area Li,max (in
m2 per unit niche area) for the African Humid Period (AHP) plant
types: Saharan type, Sahelian type, and Sudanian type.
Saharan type
Sahelian type
Sudanian type
PiC1
0
20
150
absolute minimum
Acacia tortilis
Celtis integrifolia
PiC2
100
150
500
Saharan desert boundary
100 mm isohyet
PiC3
150
500
1500
PiC4
600
900
1800
Ziziphus mauritiana
Balanites aegyptiaca
Pterocarpus erinaceus
Li,max
1
2
3
The Guineo–Congolian plant type cannot be captured with this approach as the
initial precipitation P(VS,-6500) is too low to reach its minimum
threshold PGCC1. This tropical plant type grows in gallery
forest or ripicolous stripes where a high water availability is more or less
constantly provided. Local precipitation is less important than the large-scale
climate which is assumed to be determined by orbital forcing. In order
to account for this special relation to water availability, the effective
leaf area LGCE of this plant type is prescribed with
a linear approximation, following the gradual insolation forcing and P:
LGCE(t,P)=-a-1b⋅t+c⋅P.
The parameters a, b and c are tuned such that
LGCE=0.5 for P= 500 mmyr-1 because
gallery forests potentially cover only a small fraction of semi-arid regions
and play therefore only a limited role in climate–vegetation feedback, and
LGCE=0 for t=-3000 because this is the timing
of disappearance reconstructed from pollen .
The effective leaf area LS of all plant types together is unconstrained
and calculated with the niche approach:
LS=1N∑i=1NLi.
For sensitivity studies on the role of plant composition and the effect of
introducing or removing single functional plant types, LS is calculated
with a modified version of the niche approach
LS=1n∑i=1NLi,N≤n,
where n is the number of existing niches that can be occupied by N
different plant types. This calculation implies the lack of relevant
ecosystem functions when a niche is not occupied. We use n=N+1 in our
simulations.
The total precipitation is calculated in an analogous manner to
(see Eq. 5) as a combination of a background
precipitation Pd in absence of vegetation, and a precipitation
component induced by vegetation feedback
PE(LS,t)=Pd(t)+DB⋅LS,
with a constant climate feedback coefficient DB=140 mmyr-1 . Results from sensitivity
studies on DB ranging from 0 to 150 mmyr-1 are provided in the Supplement. The initial
background precipitation is set to Pd0=500 mmyr-1 which
supports an average woody fraction of around 80 %, based on observational data , the potential maximum cover in
climate-driven savannas . The natural variability in
precipitation, independent of vegetation, is implemented as additional
white noise forcing PN(t) in the total precipitation
P(LS,t)=max((PE(LS,t)+PN(t),0)).
Results from the adjusted model
The environmental envelopes for the four AHP plant types are shown in Fig. 2.
Upper and lower precipitation thresholds mark the growth ranges based on
moisture requirements, the limiting and therewith determining factor for
plant growth in semi-arid regions (Shelford's law of tolerance
). Since thresholds are derived from empirical
relationships between observed species distributions and environmental
variables, the implemented envelopes correspond to the “realized niches” or
“climatic niches” that are narrower than the potential “fundamental
niches” of plant types, as they implicitly account for further abiotic and
biotic constraints . This constrains the
comparison between plants interacting individually or together with climate.
Environmental envelopes in terms of moisture requirements of four
African Humid Period (AHP) plant types in the adjusted set up. The effective
leaf area Li is plotted as a function of mean annual precipitation P
for the Saharan type (red), Sahelian type (green), Sudanian type (blue), and
Guineo–Congolian type (light blue).
In our implementation of the vegetation types described by ,
plant types range from xeric desert shrubs and grasses
(<150 mmyr-1) to large tropical trees
(>1500 mmyr-1). Biome sensitivity assessment studies support
this setup of plant sensitivities, suggesting that the percentage of rainfall
decrease necessary to shift from one biome to another seems to be lowest for
deciduous forests, followed by semi-deciduous forest, evergreen forest,
grasslands, open and finally closed savannas . It is not
clear whether gallery forests are as sensitive to decrease in rainfall as
other forest types. Once being established in savannas, positive feedback
effects may come into play and stabilize their expansion .
The sensitivities of these plant types to changing environmental conditions
are represented by the slopes of the curves in Fig. 2. Saharan and Sahelian
plant taxa are mainly drought-adapted species that survive until conditions
become very harsh, and they respond quickly if precipitation occurs. The
Sudanian type includes herbaceous and woody savanna taxa that grow under
a wide range of conditions, so the gradual decline with decreasing
precipitation seems reasonable. The prescription of the Guineo–Congolian
tropical gallery forest plant type as a linear function of the orbital
forcing and local precipitation with relatively low LGC, max
accounts for internal stability.
The effective leaf area Li introduces an additional degree of freedom in
the model, acting as a weighting factor for each plant type in the combined
interaction with climate. All surface parameters crucial for
climate–vegetation feedback – leaf area, hydrological properties, and
albedo – merge in Li. Tropical plants, especially trees, usually
achieve higher leaf areas and higher evapotranspiration rates than grasses or
other steppe vegetation. Higher evapotranspiration has in turn a larger
impact on atmospheric processes and the formation of precipitation than the
low leaf area of steppe vegetation.
Simulations of AHP vegetation interacting individually and together with
climate, and the corresponding precipitation curves, are shown in Fig. 3.
Except for the Guineo–Congolian type, all plant types show an abrupt decline
and a pronounced hysteresis effect when they interact individually with
climate (Fig. 3a). This low stability results from the strong chosen climate
feedback coefficient of 140 mmyr-1. The corresponding
precipitation curves go in conjunction with the abruptness of Li decline
(Fig. 3c). In single interaction with climate, the Guineo–Congolian type
declines linearly until it disappears at around year -3000. The Sudanian
type starts with LSudanian, max=3 and collapses abruptly at
around year -3600 due to the strong feedback. It develops a hysteresis of
around 500 years. The Sahelian type starts with LSahelian
of around 1.2, reaches LSahelian, max=2 at year -4600 and
collapses abruptly at around year -2200. It develops a hysteresis of around
1000 years. The Saharan type gradually increases from an initial
LSaharan of around 0.1 to LSaharan, max=1 at around
year -3200, before it collapses at around year -2900. It develops
a hysteresis of around 300 years.
Transient dynamics of four African Humid Period (AHP) plant types
interacting individually (a–c) and together (d–f) with
climate. The effective leaf areas Li and the corresponding precipitation
amounts Pi are shown for the Saharan type (red), Sahelian type (green),
Sudanian type (blue), and Guineo–Congolian type (light blue). Mean effective
leaf area LS and the corresponding precipitation P are calculated with
the niche approach (black) (see Eq. 9). Simulations without background noise
(a, e) include forward simulations (solid lines) and simulations
backward in time (dashed lines). Simulations with background noise are
depicted in (b, e) for Li and LS, and for precipitation
P in (c, f). Thin lines show annual mean values and thick lines
show a 100 year running mean.
When all plant types interact together with climate, we observe more gradual
responses to the orbital forcing, changes in appearance over time, and the
almost complete disappearance of hysteresis effects (Fig. 3d–e). This can be
interpreted as an enhancement of system stability . The
precipitation curve resulting from feedback with LS shows a smooth
decline (Fig. 3f). In combined interaction with the other plant types, the
Guineo–Congolian type starts with a higher LGC than alone
because this type benefits from local precipitation. The appearance over time
does not change as orbital forcing surpasses the beneficial effect from local
precipitation enhancement. A high potential effective leaf area puts the
Sudanian type in a dominant position in the multi-niche system.
LSudanian starts to decline 1500 years earlier than on its
own, but it finally disappears after a more gradual decline around
200 years later than alone. Hence, its abundance is reduced over time
due to the presence of other plant types, while its absolute appearance over
time is extended. The hysteresis almost disappears. The decline of the
Sahelian type starts 1100 years earlier in the combined interaction,
happens more gradually and ends around 1000 years earlier than alone.
The period of maximum abundance is shifted deeper in the past and the
absolute appearance over time is shortened in the considered time frame. The
hysteresis almost disappears. The Saharan type starts in combined interaction
from LSaharan=0, increases gradually from year -6000 to its
full potential cover at around year -3500 before it disappears again
between year -3300 and -3200. The time span of maximum abundance as well
as the total appearance over time are reduced due to the presence of the
other plant types. The hysteresis almost disappears. The Saharan type is
largely outcompeted by other plant types in higher precipitation regimes. It
only succeeds in the short period of low precipitation amounts.
Under the assumption of a full environmental envelope, the niche approach
gives reasonable results for LS regarding functional diversity. The
evolution of LS can be divided into three main phases (Fig. 3e). At the
beginning of the simulation, LS is not at its maximum which could be
explained in consideration of the physiognomic community structure in
reality. Under a high precipitation regime, the Sudanian type has the largest
share of vegetation, including many tree species that outcompete undergrowth.
With decreasing precipitation in the first phase from year -6500 to
-5200, tree cover and therewith ground shading effects are reduced and it
becomes easier for undergrowth species to establish. While the composition
changes substantially under decreasing precipitation, LS only increases
by 0.2. In the second phase between year -5200 and -3400, LS slowly
decreases by 0.3, slightly below the initial level of 1.1. With the total
disappearance of the Sudanian type at around year -3400, the third phase is
initiated and therewith a steeper and fluctuating, but still gradual
transition to a desert state. The system has now simplified to just two plant
types and those are nearing their thresholds, which causes the increase in
fluctuations. The increase in fluctuations is one of the proposed early
warning signals for regime shifts . After
year -3000, vegetation is completely absent.
Stepping back to the reconstructions by , our simulations
show an evolution of plant diversity similar to reconstructions north of
20∘ N. proposed that all these plant types
were present around year -6000, diversity was highest in and within plant
types, and tropical types (Guineo–Congolian and Sudanian type) reached their
maximum extension and abundance. After year -6000, pollen abundance and
diversity decreased for all plant types. Tropical types apparently declined
in conjunction with latitudinal humid surfaces as they grew mainly in gallery
forests. Regarding the abundance of pollen in , vegetation
was completely absent after year -3000 north of 20∘ N. All
these observations are also true for our simulations, except for the lack of
the Saharan type in the beginning of our simulations in year -6000 due to
the assumed low maximum precipitation threshold. Quantitative comparison
between and our simulations is not possible because their
reconstructions rely on pollen richness and abundance while we consider the
area of growth. High richness and abundance of individual types should not be
equated with high plant cover.
So far, we have considered the interaction of AHP plant types interacting
individually or all together with climate. We now address the role of plant
composition and completeness of required functional types.
stated that climate–vegetation feedback strength could
change if certain plant types were removed or introduced by some external
forcing.
Our simulations with different combinations of plant types highlight the
importance of plant composition on system stability, but we can only make
qualitative statements about different scenarios. Figure 4 shows LS
computed from Eq. (10) with different combinations of plant types. In each
simulation, one plant type is absent and its niche is not occupied. The
removal of tropical plant types tends to enhance the fluctuations and
steepness of the transition while the lack of drought-adapted plant types
causes a more gradual decline that starts earlier. It is not possible to
determine with the conceptual approach used here if one of the considered
plant types actually played a key role for the stability of the
climate–vegetation system during the mid-Holocene, but the Sudanian type
seems to have a large impact on our simulations. This is mainly because the
Sudanian type was prescribed the highest potential effective leaf area, and
its removal leaves the interaction with climate to the Saharan and the
Sahelian type, which are both sensitive to changes in precipitation and
respond abruptly when their minimum thresholds PiC1 are crossed.
Nonetheless, we show that there might be large differences in the mean cover
over time depending on the involved plant types, the overlap of environmental
envelopes, and the individual response to changing conditions.
Transient dynamics of mean effective leaf area LS illustrate
the impact of the removal of plant types. Panels (a–e) show
100 year running means of different simulation set ups. The mean
effective leaf area LS accounting for all plant types (N=n=4 in
Eq. 10) is shown as a reference (a). In each of the other
simulations, one niche is not occupied (N=3 and n=4 in Eq. 10): no
Saharan type (b), no Sahelian type (c), no Sudanian type
(d) or no Guineo–Congolian type (e).
Limitations of the adjusted model
The adjustment of the model by to AHP plant types
reconstructed from pollen improves the representation of
plant diversity during the mid-Holocene and provides a tool to investigate
the impact that different plant types might have on the stability of
a climate–vegetation system. Nonetheless, the model's simplicity limits its
application.
As mentioned in Sect. 2.2, moisture requirement is an established measure to
characterize diversity in recent African ecosystems. However the measure is
insufficient to describe plants' niches and to explain actual vegetation
composition and spatial distribution within the considered region, because
determinants other than precipitation amounts are not taken into account. We
do not explicitly implement additional plant growth determining parameters in
the adjusted model, but moisture requirements from empirical data implicitly
account for such additional factors. Niches in the model describe “realized
niches”, and contributions of determinants such as fire or competition for
nutrients cannot be separated from the difference in water requirements. This
complicates the comparison between plant types interacting individually or
together with climate because the actual simulation of individual growth is
not possible. Nonetheless, water is the limiting factor in subtropical Africa
and the effects of additional or reduced precipitation due to the presence of
other plant types can be considered with our model.
Another shortcoming is the merging of all surface parameters crucial for
climate–vegetation feedback – leaf area, albedo, and hydrological properties
– in Li. The individual importance of each of these parameters
regarding the effect on atmospheric dynamics and precipitation patterns
varies over different latitudes in subtropical Africa :
in the Sahara, an increase in plant growth results in a net warming because
the surface heating due to albedo decrease surpasses the increase of latent
heat flux; the Sahel experiences a net cooling with additional vegetation
because evapotranspiration cooling exceeds the albedo warming effect; south
of the Sahel, where tree cover and water availability are generally high, the
stomatal resistance limits the latent heat flux which results in a net
warming. This heterogeneous pattern makes an individual consideration of
feedback determinants important, but cannot be performed with our approach as
contributions enter the product of LS and DB which makes
disentangling impossible.
The same applies to the assumption of a homogeneous feedback coefficient
DB for all plant types which does not account for diversity in
feedback strength, but it could not be separated from the product with
LS anyway. Another shortcoming of DB is its arbitrary choice to force
strong feedback and abrupt state transition . Quantitative
estimates of the climate feedback coefficient DiB based on remote
sensing observations of monthly fraction of photosynthetically active
radiation show on average a positive feedback on precipitation in the Saharan
region, values range in subtropical Africa from -60 to
120 mmyr-1, but little evidence of strong
vegetation–precipitation feedback . Sensitivity studies with
various combinations of DiB show only minor changes in the
evolution of LS over time (see Supplement).
Summary and conclusions
In the scope of this paper, we critically reassess the conceptual model by
in the light of recent ecological literature, and
provide an improved version that accounts for plant diversity during the
African Humid Period (AHP) as it was reconstructed from pollen by
.
Despite its simplicity, the original conceptual model by
seems to capture the main features of different plant types interacting
together with climate, namely the enhancement of climate–vegetation system
stability. The underlying assumptions are reasonable in an ecological context
concluded from literature.
The definition of diversity in terms of moisture requirements is an
established and appropriate approach for semi-arid regions because
precipitation is the main determinant of plant growth there. Neglecting
further crucial factors for vegetation composition and distribution such as
fire or competition is therefore reasonable in the simple approach.
With the niche approach, the effective feedback between vegetation and
climate emerges from the interacting properties of different plant types
fulfilling specific ecosystem functions. Once a plant type disappears as
precipitation drops below the requirements, other plant types cannot occupy
its niche (ecological space). The prohibition of replacement depicts the
fundamental ecological niche in its original sense, but the approach does not
allow for a geographically explicit description of vegetation cover
evolution. Further, the changes in niches available for occupation that
result from substantial changes in the environment over millennia are not
implemented.
Regarding the interpretation of transient simulations, the conclusions made
by fit in the ecological state of knowledge. After
decades of debating, ecologists nowadays agree that biodiversity can have
a stabilizing effect on ecosystems, especially under changing environmental
conditions (see Sect. 2.3). concluded that the stability
of a climate–vegetation system can determine and arise from plants'
appearance over time. Sensitive plants likely benefit from additional water
and facilitation effects in a more life-sustaining environment, whereas
resilient plants might suffer to a certain degree from additional
competition. argued ecologically reasonably that it is
difficult to determine the origin of system stability as the overall feedback
strength depends on species composition. These difficulties are not
inconsistent with previous studies that proposed strong climate–vegetation
feedback, resulting in abrupt shifts from a stable “green” state to a
stable “desert” state. Simulations by were performed
with the lowest possible number of PFTs, one tree and one grass. The low
diversity implies a high likelihood for abrupt transitions
. In previous studies that focused on
multiple stable states of the climate–vegetation system in north Africa,
including those of , , and
, it was argued that an abrupt change emerging from the
loss of stability of one of the stable climate–vegetation states causes
abrupt changes in both the vegetation record and the hydroclimatic record.
Our study, however, supports the hypothesis of that in
an ecosystem with rich plant diversity, multiple stable states can exist,
even if the hydroclimate record shows a gradual transition. Hence the latter
studies do not invalidate the earlier considerations.
When it comes to the application to AHP vegetation reconstructed from pollen
data , the model by reaches its limits.
The diversity of AHP vegetation in terms of moisture requirements and climate
impact cannot be captured. The direct relation between precipitation and
plant cover does not hold for highly specialized xeric plant types or
tropical plant types indirectly linked to regional precipitation, and the
diversity of feedback strength and climate impact arising from different
plant properties is not sufficiently reflected in the original model.
Our modifications refine the model setup and account for a more realistic
spectrum of plant types, interactions, and feedbacks. The extension of
environmental envelopes enables coexistence and superseding of different
plant types when conditions and the set of available niches change. The
implementation of the vegetation types described by provides
an insight into plant diversity during the AHP. Plant types range from xeric
desert shrubs and grasses to large tropical trees. Since precipitation
thresholds are derived from observational data, abiotic and biotic
constraints cannot be completely separated. Together with the full
environmental envelopes, the prescribed retreat of tropical gallery forest
taxa allows for the representation of a mosaic like spatial environment as it
was reconstructed from pollen. The effective leaf area introduces an
additional degree of freedom that acts as a weighting factor for each plant
type in the combined interaction with climate, accounting for differences in
leaf area, albedo and hydrological properties.
Simulations with the adjusted model version support the stabilizing effect of
functional diversity on ecosystem performance and precipitation proposed by
, but provide more details on plant turnover. When all
plant types interact together with climate, we observe rather gradual
responses to decreasing precipitation, changes in appearance over time and
the almost complete disappearance of hysteresis effects. Over a period of
around 3100 years, the mean cover varies little while composition
changes completely. The disappearance of tropical types initiates the final
steeper and fluctuating, but still gradual, transition to a desert state
within 400 years. After year -3000, vegetation is completely absent.
The temporal evolution of plant types compares well with reconstructions by
north of 20∘ N.
The importance of plant composition for the stability of a
climate–vegetation system becomes clear comparing different combinations of
plant types. Apparently, the Sudanian type played a leading role for the
stability of the climate–vegetation system, but we cannot determine if one
of the considered plant types actually played a key role during the
mid-Holocene with our model. Nonetheless, we can show that there might be
large differences in the mean cover over time depending on the involved plant
types, occupied niches and their overlap, and the individual sensitivities to
changing conditions.
For further studies on the effect of plant diversity on the stability of
climate–vegetation systems, we propose not to complicate the conceptual
model any further by introducing more ad hoc tunable parameters, but to
transfer the lessons learned from this study to a comprehensive dynamic
vegetation model.
Our Earth system model MPI-ESM did not show abrupt transitions of large-scale
vegetation cover in previous transient Holocene simulations, and the
understanding we gained in this study can help to investigate whether this is
an effect emerging from the representation of diversity in our land surface
model JSBACH. This process-based model offers the possibility to represent
different degrees of plant diversity in various plant properties, and a
variety of interactions with the atmosphere to address the arising question:
could a more complex model depict AHP plant diversity and reproduce the
results from our qualitative conceptual study? Would changes in plant
diversity stabilize or destabilize the climate vegetation system in coupled
GCM simulations? Could new PFTs designed after pollen reconstructions better
represent plant diversity in subtropical Africa? Could the implementation of
additional processes in JSBACH, such as root competition or light competition, or
additional plant properties, such as fire-resistance, lead to new effects on
the climate–vegetation system stability?
In summary, a deeper understanding of the role that plant diversity can play
in climate–vegetation interaction, and an improved representation of plant
diversity based on pollen reconstructions, could
allow for a more realistic consideration of plant–plant interaction and
climate–vegetation feedback in coupled GCM simulations.