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ORIGINAL ARTICLE
Modelling the distribution of key tree species used by liontamarins in the Brazilian Atlantic forest under a scenario of futureclimate change
Nima Raghunathan • Louis Francois •
Marie-Claude Huynen • Leonardo C. Oliveira •
Alain Hambuckers
Received: 28 February 2013 / Accepted: 16 April 2014 / Published online: 14 August 2014
� Springer-Verlag Berlin Heidelberg 2014
Abstract We used three IPCC climate change scenarios
(A1B, A2 and B1) in a dynamic vegetation model (CA-
RAIB), to determine the potential future distribution of 75
tree species used by two endemic primate species from the
Brazilian Atlantic Forest (BAF). Habitat conservation is a
vital part of strategies to protect endangered species, and
this is a new approach to understanding how key plant
species needed for survival of golden lion tamarins
(Leontopithecus rosalia) and golden-headed lion tamarins
(L. chrysomelas) might be affected by climate change and
what changes to their distribution are likely. The model
accurately predicted the current distribution of BAF veg-
etation types, for 66 % of the individual tree species with
70 % agreement obtained for presence. In the simulation
experiments for the future, 72 out of 75 tree species
maintained more than 95 % of their original distribution
and all species showed a range expansion. At the biome
level, we note a substantial decrease in the sub-tropical
forest area. There is some fragmentation of the savannah,
which is encroached mostly by tropical seasonal forest.
Where the current distribution shows a large sub-tropical
forest biome, it has been replaced or encroached by tropical
rainforest. The results suggested that the trees may benefit
from an increase in temperature, if and only if soil water
availability is not altered significantly, as was the case with
climate simulations that were used. However, these results
must be coupled with other information to maximise use-
fulness to conservation since BAF is already highly frag-
mented and subject to high anthropic pressure.
Keywords Conservation � Climate change � Modelling �Brazilian Atlantic Forest � Lion tamarins � Dynamic
vegetation model (DVMs)Editor: Wolfgang Cramer.
Electronic supplementary material The online version of thisarticle (doi:10.1007/s10113-014-0625-9) contains supplementarymaterial, which is available to authorized users.
N. Raghunathan (&) � M.-C. Huynen � A. Hambuckers
Behavioural Biology Unit, Department of Biology, Ecology, and
Evolution, University of Liege, Quai Van Beneden, 22,
Liege 4020, Belgium
e-mail: [email protected]
M.-C. Huynen
e-mail: [email protected]
A. Hambuckers
e-mail: [email protected]
L. Francois
Climate Modelling and Biogeochemical Cycles Unit,
Astrophysics, Geophysics and Oceanography Department,
University of Liege, Allee du 6 Aout, 17, Liege 4000, Belgium
e-mail: [email protected]
L. C. Oliveira
Programa de Pos-Graduacao em Ecologia, Universidade Federal
do Rio de Janeiro, CP. 68020, Rio de Janeiro CEP 21941-590,
Brazil
e-mail: [email protected]
L. C. Oliveira
Programa de Pos-Graduacao em Ecologia e Conservacao da
Biodiversidade, Universidade Estadual de Santa Cruz,
Santa Cruz, Brazil
L. C. Oliveira
Bicho do Mato Instituto de Pesquisa, Belo Horizonte, MG,
Brazil
123
Reg Environ Change (2015) 15:683–693
DOI 10.1007/s10113-014-0625-9
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Introduction
Tropical forests all over the world are facing increased risks
of conversion and species extinction. Exacerbating the
problem of deforestation and habitat conversion is climate
change. Studies show that changes in regional climates are
forcing species to adapt their distribution by seeking suit-
able conditions, or altering their phenology, and those that
are unable to react are facing extinction risks (Thuiller et al.
2008; Wright et al. 2009; Lurgi et al. 2012). For more than a
decade, there is convincing evidence of such adaptations
already occurring in the temperate regions and at higher
latitudes (Hughes 2000; Parmesan and Yohe 2003; Root
et al. 2003; Gian-Reto et al. 2005; Walther et al. 2005;
Lenoir et al. 2008, Thomas 2010), but less has been docu-
mented for tropical regions where a particular emphasis has
been put on changes in mountains (Colwell et al. 2008;
Raxworthy et al. 2008; Thomas 2010; Chen et al. 2011).
Among the possible impacts of climate change on the
environment, the 2007 IPCC report suggests that between
20 and 30 % of plant and animal species could be at
increased risk of extinction if global average temperatures
increase by 1.5–2.5 �C (IPCC 2007). To assess changes in
the tropics, several approaches are used, such as detecting
temporal changes in composition of species assemblages
(Gonzalez-Megıas et al. 2008; Bertrand et al. 2011; Chen
et al. 2011), analysing temperature performances of species
(Williams et al. 2008; Berg et al. 2010; Clusella-Trullas
et al. 2011; Huey et al. 2012) or modelling the climatic
range (Thuiller et al. 2008). Modelling the habitat including
biotic interaction of the species is rarely used (Keith et al.
2008; Preston et al. 2008) despite calls for the use of this
approach (Brooker et al. 2007; Van der Putten et al. 2010).
Indeed, one of the ways to think about conservation of
endangered fauna is to understand how its habitat may shift
as climate regimes change—if the major food sources,
sleeping sites, nesting sites or preferred vegetation type are
able to withstand the impacts of climate change, one might
hope that the fauna will follow. The viability of species in
their natural range comes from the fact that satisfactory
levels are reached for all the requirements, including the
biotic environment furnishing food and shelter. This allows
for considering the ecosystem or the habitat as well, rather
than just understanding a single species’ response to climate
change.
This study focussed on the future of the golden lion
tamarins (GLTs, Leontopithecus rosalia) and golden-headed
lion tamarins (GHLTs, L. chrysomelas), two endangered
endemic species (IUCN 2013) of the Brazilian Atlantic
Forest (BAF). The BAF is a biodiversity hotspot (Myers
et al. 2000; Mittermeier et al. 2005). Its mosaic habitats,
proximity to the coastline and extreme fragmentation makes
it an interesting ecosystem to study. Conservation at the
nexus of high endemism, primary, secondary and degraded
habitats, high fragmentation, and agro-forestry systems
could well be the future; understanding how climate change
could impact this region will be very important to ensure the
conservation of the BAF. We studied the growth of vege-
tation types and tree species, which are important resources
for the tamarins, using a process-oriented vegetation model.
Thus, the vegetation types and the tree species form the
biotic environment of the tamarins. Otherwise, it is difficult
to evaluate the importance of changes in climatic variables
on the biology of the tamarins themselves, because their
distribution is very narrow and may not be limited by cli-
matic constraints alone. While the number of tree species
listed is not exhaustive, this study is, to our knowledge, the
first of its kind to consider climate change impacts on so
many vegetation species (75) at one time.
To model tree species and vegetation type response, we
used the CARAIB (Francois et al. 1998, 2006) dynamic
vegetation model (DVM). DVMs have a long history of
integrating climate model results to understand plants’
response to climate change. DVMs are comprehensive
models, which include vegetation dynamics as well as bio-
geochemical processes (Cramer et al. 2004). DVMs grow
objects representing the plants as plant functional types
(PFTs, Violle et al. 2007), biological affinity groups (BAGs,
Laurent et al. 2004) or individual plant species. PFTs are
defined according to plant life forms (tree, shrub, herb/grass,
etc.) and morpho-physiological and phenological traits
(broadleaves-needle leaves, deciduous, evergreen, etc.)
while BAGs are defined from plant species with similar bio-
climatic and structural characteristics. Tolerances and
threshold values of each type of object to be grown are
inferred from their actual distribution. Here, the CARAIB
model was used to simulate and to compare the growth of
preferred tree species and the growth of the vegetation types
as PFTs under present climate and CO2 conditions and under
future standard scenarios for the period 2071–2100.
Methods
Tree species geographic and climatic distributions
A literature review (Lapenta et al. 2003; Catenacci 2008;
Oliveira et al. 2010) of commonly foraged tree species and
commonly used species for sleeping sites was conducted
for two out of the four lion tamarin species (L. rosalia—
GLTs and L. chrysomelas—GHLTs). A sample of their
distribution was obtained from the Tropicos online data-
base (www.tropicos.com). For some endemic species,
coordinates were obtained from an on-going study—groups
of L. chrysomelas were followed from sleeping site to
sleeping site, and the geographic location of all trees that
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were foraged upon, and/or used as sleeping sites, was
recorded using a GPS (Oliveira et al. 2010, 2011). Where
elevation data were available along with the coordinates,
these data were also collected, and otherwise the GTOPO-
30 database (http://eros.usgs.gov/#/Find_Data/Products_
and_Data_Available/gtopo30_info) was used to estimate
the mean elevation of the 30’’ by 30’’ pixel in which a
given coordinate was present. Using these coordinates,
climate data (mean and diurnal temperature amplitude,
precipitation, wind speed, relative sunshine hours and rel-
ative humidity) were extracted over the geographic distri-
bution of each of the 75 species from New et al. (2002).
Temperatures attributed to each record in a given pixel
were corrected based on its elevation (either as reported in
the database or obtained from GTOPO-30) and using mean
values of monthly lapse rates from NCEP re-analysis
(http://www.esrl.noaa.gov/psd/data/reanalysis/reanalysis.
shtml). No corrections were made on other climate vari-
ables. While most species had a set of coordinates dis-
tributed in a relatively regular way, there was a great deal
of heterogeneity and bias for some of the tree species,
particularly those species which are endemic to the BAF,
where few specimens had been collected, or those species
where extensive sampling was done only in a part of their
full range and was limited in other regions. Of the 75
species, nearly one-third (26) are endemic to Brazil, with
most of them having their range in the BAF and neigh-
bouring caatinga (neighbouring dry shrubland ecosystem
with complex borders with the BAF).
Simulations
The CARAIB model was originally developed to under-
stand the role of vegetation in the carbon cycle. It has been
used to model present-day carbon cycle (Warnant et al.
1994; Gerard et al. 1999), potential vegetation distribution
in past climates (e.g. Miocene, Francois et al. 2006; Henrot
et al. 2010; last glacial maximum, Francois et al. 1998) and
potential vegetation distribution, net primary productivity
(NPP), and wild fires in the future (Dury et al. 2011).
Detailed descriptions of CARAIB modules are found in
Otto et al. (2002), Dury et al. (2011) and Francois et al.
(2011). The model calculates carbon flows between
atmosphere and ecosystems on grid spreading at selected
spatial scales, global to regional. Monthly climatic fields
(mean and diurnal temperature amplitude, precipitation,
wind speed, relative sunshine hours and relative humidity)
and soil texture and colour were used as inputs; a stochastic
generator produced daily values of climatic variables. It
calculates photosynthesis, respiration and finally NPP of a
predefined set of objects representing plants (PFTs, BAGs
or species) by taking into account competition for space,
light, water and threshold values of climatic variables
controlling germination or increasing mortality under stress
conditions (Otto et al. 2002; Dury et al. 2011). For ger-
mination, we used the following thresholds: minimum of
yearly sum of daily temperature above 5 �C (GDD5) and
maximum of driest month’s soil water (SWmaxg) allowing
germination. We used SWmaxg only for the drought-
deciduous trees, and shrubs (broadleaf evergreen xeric and
sub-desertic) PFTs and not for the individual BAF tree
species, because this is not a constraint in tropical moist
forests. To initiate stress conditions, we used the following
thresholds: coldest day temperature (Tmins) and soil water
of the driest month (SWmins). During conditions of severe
hydric stress, the model also considers the response related
to stomatal closure (under lower relative air humidity or
decreased soil water), as well as a progressive decrease in
the leaf area index, when soil water decreases. Thus, NPP
and growth tend to decrease, when soil water levels
decrease. For the tree species, the climatic threshold values
for germination and growth were the 1 % or the 99 %
quantile of the obtained climatic distributions. BAF vege-
tation was simulated using a 26 PFT classification, which is
an upgrade from the 15 PFTs originally described in Ute-
scher et al. (2007) and Francois et al. (2011). For the
simulations described here, we were not able to use spe-
cies-specific morpho-physiological values, because they
are not available uniformly for many species. While the fire
module in CARAIB was run, this version of CARAIB did
not use its output, so that impacts of fire events on standing
biomass related to increased dryness could not be
accounted for. Land-use changes, principally conversion of
forest to agricultural or urban use, which can impact NPP
(usually a decrease, e.g. DeFries 2002), were not also taken
into account in this version.
We simulated the present-day distributions of the tree
species and the PFTs in the BAF, using 330 ppmv of
carbon dioxide and corresponding climate variables,
between 1961 and 1990 (New et al. 2002). For future-
scenario simulations, we used three ARPEGE-CLIMATE
scenarios (CMIP3) as outlined by the 2007 IPCC report
(IPCC 2007) to reach equilibrium for an average climate
between 2071 and 2100 (A1, A1B and A2). The model
chosen for these future simulations is coherent with the
mean values of the CMIP5 scenarios, which were not
available when these simulations were performed. For
example, in the most pessimistic A2 scenario, the annual
precipitation for this region has a slight increase that is
consistent with the mean values for annual precipitation
from CMIP5. However, the precipitation in the driest
month(s) can still decrease and lead to hydric stress, the
effects of which can be diminished due to fertilisation by
increased CO2 concentrations. Within the A1 scenario,
A1B includes balancing sources of fuel (fossil and non-
fossil based), and of the three scenarios being modelled,
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this shows the second highest carbon dioxide levels at
660 ppmv. The B1 is the most optimistic scenario which
assumes emissions levels up to 530 ppmv. The A2 sce-
nario assumes low population and economic growth, but
also low technological change and caps carbon dioxide
levels at 750 ppmv. None of the IPCC scenarios comes
with a probability value. Other, more regional models, or
global models projected from Latin America were not
available at that time either. Models such as the BESM
(Brazilian Model of Global Climate System) were
developed later and do not necessarily guarantee higher
precision, as the spatial resolution is lower than some of
the CMIP5 models. The ARPEGE CMIP3 does not have a
uniform grid; for the Atlantic Forest in our simulated
zone, it has an effective resolution of 1.2–1.8�, compared
to 1.875� for the BESM.
We generated a ‘‘present-day’’ distribution scenario,
showing the full areas where the trees and the region’s
biomes could theoretically be present. To test the accu-
racy of predicted current distribution, we overlaid the
known coordinates per species over maps showing
modelled species NPP distribution within the simulated
area. An NPP cut-off point at 100 g C/m2/year was
considered as presence of the species. To determine the
level of agreement between the model’s current distri-
bution and actual distribution, we calculated a kappa
value, J = [Pr_a - Pr_e]/[1 - Pr_e], where Pr_a is the
proportion of agreement between the model’s predicted
presence and the actual presence, and Pr_e is the
hypothetical probability of chance agreement. Pr_e is
obtained as the proportion of presence calculated by the
model over the entire area of the simulation (which
includes the entire BAF region and extends westwards to
65�W). Kappa values above 0.41 indicate moderate
levels of agreement, between 0.61 and 0.80 substantial
agreement and almost perfect agreement above 0.8
(Landis and Koch 1977) (Table 1 in Electronic Supple-
mentary Material).
For the future simulations, the potential distribution of
the same trees was re-plotted, based on the changes in the
climatic variables. Similar simulations were conducted
based on PFTs to highlight potential biome-level changes.
Additionally, the areas of overlap between the current and
future distributions, and the overall increase or decrease in
distribution were calculated.
Results
Present-day distributions
The superposition of the distribution of observed individual
trees species on the maps of the simulated NPP showed that
the model predicted the distribution accurately for 66 % of
the individual tree species (43 of 75) with more than 70 %
agreement obtained for presence. Of the remaining 32
species with less than moderate agreement, 16 tree species
are endemic to Brazil (the comprehensive analysis with
tree usage by the primates and threshold values is given by
species in Table 1 of Electronic Supplementary Material).
For these ones, the number of occurrences obtained was
very low, though we do not know whether this is because
of a natural rarity or a lack of sampling over the entire
distributions. Additionally, there is no information to
indicate whether the endemism is linked to climatic factors
or other variables such as dispersion or soil factors. Since
the model does not take into account such factors, it is
difficult to obtain accurate predictions for these species.
However, for six (6) endemic species, despite the low
number of occurrences (B10), the model was able to pre-
dict correctly the distribution (J C 0.41). Overall, con-
sidering the limitations in the actual occurrence data, the
model was able to accurately predict presence for 57.3 %
of the species with a moderate or higher level of agreement
(Fig. 1). At biome level (Fig. 2), statistical comparisons are
difficult, given that there are different interpretations of
biomes (extent and class) and the existing vegetation maps
are often not concordant between themselves, e.g. Otto
et al. (2002) reported an agreement of only 74 % between
two global maps of natural vegetation. In addition, the
usefulness of simulating biomes is mostly to detect changes
in the potential vegetation distribution under future climate
change scenarios. Nevertheless, a visual comparison of the
biome distribution simulated by the model and the potential
vegetation distribution in the same area showed substantial
concordance along the coast, tropical rainforest, sub-trop-
ical forest and some tropical seasonal forest in the BAF
area and northeast of this region, savannahs in the caatinga
area. Further west under the correctly predicted Amazon
rainforest, the model uniformly simulated tropical seasonal
forest over the cerrado. This area, despite its exposition to
tropical seasonal climate with annual rainfall averaging
1,500 mm, is covered by an ecotone consisting of sa-
vannahs integrated with more or less deciduous forests.
The main determinants are soil dystrophy, aluminium
toxicity and fire (Mistry 2000). Since CARAIB does not
take into account soil chemistry, it was unable to predict
this particular vegetation but this had limited consequence
to our conclusions since the cerrado was outside our area
of direct interest.
Future distributions
For the distribution of individual species, the predicted
future area of all the individual species increased in the
three scenarios (B1, A1B and A2), with respect to the
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simulation of the present-day area of distribution. For 72
out of 75 species, more than 95 % of the original area
remained in the future simulations, and only three species
showed any substantial change ([15 % decrease) (Fig. 4;
Table 2 in Electronic Supplementary Material). Consider-
ing that the modelled area was just a little over
7,200,000 km2, the species that were already distributed
over a majority of the modelled area naturally showed a
smaller per cent increase in their future distribution.
Additionally, considering the importance of these tree
species to the endemic primates, they also remained within
the BAF biome.
With regard to the biome, in all three future scenarios,
we note in the BAF area a substantial decrease in the sub-
tropical forest replaced by tropical rainforest and towards
the north, a slight thinning of the tropical rainforest
replaced by tropical seasonal forest or possibly by
savannahs (Fig. 3d). Additionally, there is some fragmen-
tation of the savannahs in the caatinga area (towards the
north), which is replaced mostly by tropical seasonal forest.
In all three scenarios, where the current distribution shows
a large sub-tropical forest biome, it has been replaced by
tropical rainforest, the A2 scenario showing the maximum
change. Whether this is a product of ‘‘fully replacing’’ the
biome or merely an increased number of tropical species
‘‘moving in’’ to the area is hard to say.
To understand the changes in the vegetation distribution,
we looked at soil water availability, which under climate
warming is the principal limiting factor in the model on
germination through SWmaxg and on mortality through
SWmins and temperature, which impacts mortality through
Tmins and controls germination through GDD5. For
instance, the analysis of annual mean temperature anoma-
lies between the future scenarios and the current
Fig. 1 Examples of
superposition of actual
coordinates indicating tree
presence and distribution
predicted through CARAIB.
a Substantial (kappa [ 0.8)
agreement for species with large
distribution through tropical
South America; b substantial
(kappa [ 0.8) agreement for
endemic species; c slight to no
agreement for endemic species
with few coordinates
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distribution showed most drastic differences in the A2
scenario (maximum anomaly less than 5 �C), which is
concordant with the high emissions scenario (Fig. 3a).
There is a slight overall increase in the mean annual pre-
cipitation for a large part of the modelled area (B300 mm
difference between scenarios); however, the precipitation
in the driest month decreases in all three scenarios, com-
pared to the present day, leading to increased dryness
during the dry season (Fig. 3b). Figure 3c shows minimum
monthly soil water availability anomalies for the three
scenarios (maximum difference at -0.3), and we see some
increased dryness in the caatinga region as the most
drastic, with some slight decreases as we move towards the
Amazon region. CARAIB’s fire module predicts a signifi-
cant increase in fire frequency, due to increased droughts in
the dry period, but this is most prevalent in the caatinga
region, and is much less frequent in the Atlantic Forest. It
can be expected that reduction in biomass linked to fires in
the Atlantic Forest will be limited in the future.
Discussion
In situ conservation is the method of choice for protecting
biodiversity because it provides maximal viability, it is
often the most cost-effective method, and it covers
unknown species with the species of direct interest (Possiel
et al. 1995). The extent of the supposed displacement of
species climate envelopes owing to future climate changes
raises the question of the adequacy between protected area
limits and the future distribution of the species. The results
of growth simulation with the CARAIB DVM showed that
most of the tree species supporting the activity of two
endemic primate species would rather remain in the same
area and increase their range a little in the same biomes
under future predicted climate. This bodes well for con-
serving the associated fauna. DVMs running at continental
or global scale broadly indicate a decrease in species
diversity, but with respect to NPP, their results are variable
(White et al. 1999; Alo and Wang 2008; Sitch et al. 2008;
Reu et al. 2011). Modelling studies focussing on tropical
regions of limited extension are rather rare because there
are little data available (Feeley and Silman 2011). Never-
theless, our results are not fully in accordance with niche-
based model studies. For instance, Colombo and Joly
(2010) evaluate, with two niche-based models (GARP and
MaxEnt), the future distribution of 38 well-represented
trees species typically found in the BAF using climate
simulations produced under conditions similar to B1 and
A1FI scenarios. Their results show a substantial decrease in
the future distribution of many of the species modelled and
a shift towards southern areas of Brazil. For our simula-
tions, the southward shift is reproduced for many species,
but the overall distribution of the species’ is increased
rather than reduced. In the cerrado region adjacent to the
cFig. 3 Annual mean temperature anomalies degree Celsius (a),
precipitation anomalies in the driest month mm/month (b), minimum
monthly soil water availability anomalies, in relative units (SW–WP/
FC–WP; SW soil water, WP wilting point, FC field capacity)
(c) between present-day simulation at 330 ppmv and the three future
climate change scenarios. Simulated biome distribution (d) for the
same future climate change scenarios
Fig. 2 Visual comparison between actual vegetation map and biome distribution simulated by the model for present-day (1961–1990) scenario.
Map on right adapted from Instituto Brasileiro de Geografia e Estatısticas (http://www.ibge.gov.br/home/presidencia/noticias/21052004bio
mashtml.shtm)
688 N. Raghunathan et al.
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Modelling the distribution of key tree species 689
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BAF, Siqueira and Peterson (2003) also found a substantial
reduction ([50 %) in the original ranges with a similar
method. By contrast, processes-based model studies
focussing on tropical areas rather concluded to increased
growth of the plant under future conditions. For example,
using direct observations and models with parametrisation
of leaf-level photosynthesis incorporating known temper-
ature sensitivities, Lloyd and Farquhar (2008) concluded
that the tropical forests are not ‘‘dangerously close’’ to their
optimum and that the new conditions of temperature, water
availability and CO2 concentration would produce higher
growth rate. Gopalakrishnan et al. (2011) using a DVM to
model climate change impacts on Tectona grandis in India
found that despite increased vulnerability of the species to
climate, there would be an increase in its NPP and biomass
due to increased CO2 concentration. These conclusions
agree with Lewis et al. (2009) review over recent decade
changes in the tropical forests. Analysing the results of
several complementary approaches such as permanent plot
studies or physiology experiments, they reached the con-
clusion that both gross and net primary productivity have
increased, as have tree growth, recruitment, and mortality
rates, and forest biomass.
The scope of conclusions of modelling studies dealing
with organisms and climate change is limited by the
ability to reproduce the current distributions but also by
the hypothesis of the physiological response to new
conditions to simulate the future distributions. Concerning
ability to reproduce current distribution, a significant
proportion of the species modelled in this study obviously
suffered from too few calibration data. The CARAIB
model does not include important processes such as
migration, biotic interactions or preference for particular
soil conditions. However, the question of the physiologi-
cal responses to climate change is a cornerstone to make
predictions of the future distribution of the organisms, but
only the processes-based models explicitly treat the
problem. Resistance of plants to water stress increases
with atmospheric CO2 concentration because CO2 can be
more easily absorbed minimising transpiration by stoma-
tal closure (Fitter and Hay 2002). It becomes obvious that
enhanced CO2 concentration in the atmosphere could
effectively stimulate tree growth in temperate regions
(Leaky et al. 2009). These effects are clearly reproduced
by the CARAIB model over Europe when comparing the
results of simulations for future climates with or without
increasing atmospheric CO2 concentration (Dury et al.
2011). Concerning plant response to temperature increase,
two phenomena have to be considered, heat injury and net
photosynthesis (NP). Heat injury is observed more on
stems than on leaves, close to the soil when surface
temperatures reach between 52 and 66 �C. It eventually
leads to plant death and is caused by direct solar radiation
or by heat conducted or radiated from soil having low
heat capacity and conductivity. This response, which
could be associated with the effect of mortality inducing
maximal temperature, is not considered in CARAIB
because it is rare in nature, compared to cold injury or
death associated with a minimal temperature (Kozlowski
and Pallardy 1997). The maximal soil temperatures cal-
culated by CARAIB never reached the lower end of the
threshold (52 �C), even in the driest regions of the sim-
ulated area, where highest temperatures are found. The
NPP response to temperature increase follows an asym-
metric bell curve with optimum response depending on
bio-climatic origin of the species and adaptation to season
or station (Berry and Bjorkman 1980; Fitter and Hay
2002). The components of NPP, gross photosynthesis
(GPP) and plant respiration (Ra) have contrasted respon-
ses to temperature. GPP rate gently increases with tem-
perature to peak at values between 10 and 39 �C at least,
following values reviewed by Cannell and Thornley
(1998). On the contrary, Ra rate sharply increases in the
region of 20 �C until a compensation temperature where
Ra overtakes GPP and there is no NPP or growth. These
mechanisms are simulated in CARAIB with standard
parameterisation, i.e. the same values for all the simulated
objects. The importance of the above consideration
regarding temperature effects is sustained by the results of
Vetaas (2002). This author demonstrated that four Rho-
dodendron species are able to withstand a broader range
of temperatures at the warmer end but not at their colder
end of their natural tolerance range. The author suggests
that cold temperatures may set a boundary in terms of
range expansion, but species may be more likely to
Fig. 4 Fertilisation effect of increased CO2 concentrations in the A2
scenario. Three species lost more than 15 % of their original
distribution in the A2 scenario with high emissions, compared to 38
species that lost more than 15 % of the original distribution in the
modified A2 scenario with 330 ppmv of CO2
690 N. Raghunathan et al.
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survive warmer temperatures in situ. In our simulation,
the future climates imposed higher temperatures (up to
5 �C difference), and low change in precipitation (mini-
mum precipitation did not fall by more than 40 mm),
when combined resulted in some water stress. The plants
were still able to resist this stress thanks to stomatal
closure. Indeed, this resistance is not seen when CO2
concentration is fixed to 330 ppmv in the A2 pessimistic
scenario, where 38 species showed a reduction C15 % in
the original area of distribution compared to the three
species in A2 with 750 ppmv. Niche-based models are
generally only susceptible to capture natural tolerance
ranges, which could be a serious limitation of their ability
for predicting the future range of species sensitive to
temperature. For instance, Zelazowski et al. (2011) found
some risk of forest retreat of humid tropical forest zone
using a niche-based model under 17 climate projections
but, when the results are refined by considering physio-
logical responses to atmospheric CO2, they found possible
niche expansion in many regions.
Finally, another limitation within the results is the
potential increased risk of fire, as outlined by Nepstad et al.
(2008) and Alo and Wang (2008). Even though the plants
could resist increased temperatures and water stress under
future climate, the forest litter would become drier, which
fosters conditions favouring fire ignition. However, barring
an exceptional level of drought (leading to lowered soil
water levels), both in severity and frequency—which was
not foreseen in these simulations over the Atlantic Forest—
the impacts appear to be relatively limited on tree growth.
If our results are correct, in the long term an increase in
temperature may not negatively impact the distribution of
BAF trees. It would be advantageous to test these same
scenarios with climate data from other general circulation
models in a transient way—especially those built specifi-
cally for South America, (e.g. Brazilian Model of Global
Climate System; Nobre et al. 2009, 2013)—because there
are important differences in the future climate predictions
for this region (IPCC 2007). In the meantime, short-term
conservation strategies must focus on the immediate threats
of land-use patterns and land conversion, to ensure that the
BAF habitat and the monkeys are able to survive in the
long term.
Acknowledgments We would like to acknowledge Michel Deque
CNRM-GAME (Meteo-France, CNRS) who provided the ARPEGE
climatic data for the future. Part of this work was funded by the
BIOSERF project of BELSPO.
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