and Joly, CA.
Programa de Pós-graduação em Ecologia, Instituto de Biologia – IB,
Departamento de Biologia Vegetal, Instituto de Biologia – IB,
Received January 8, 2010 – Accepted July 5, 2010 – Distributed October 31, 2010
(With 6 figures)
After 500 years of exploitation and destruction, the Brazilian Atlantic Forest has been reduced to less the 8% of its
original cover, and climate change may pose a new threat to the remnants of this biodiversity hotspot. In this study
we used modelling techniques to determine present and future geographical distribution of 38 species of trees that are
typical of the Brazilian Atlantic Forest (Mata Atlântica), considering two global warming scenarios. The optimistic
scenario, based in a 0.5% increase in the concentration of CO
in the atmosphere, predicts an increase of up to 2 °C
species registered in literature, the Genetic Algorithm for Rule-set Predictions/GARP and Maximum entropy modeling
/MaxEnt we developed models of present and future possible occurrence of each
species, considering Earth’s mean temperature by 2050 with the optimistic and the pessimistic scenarios of CO
as well as a shift towards southern areas of Brazil. Using GARP, on average, in the optimistic scenario this reduction
is of 25% while in the pessimistic scenario it reaches 50%, and the species that will suffer the worst reduction in their
possible area of occurrence are: Euterpe edulis, Mollinedia schottiana, Virola bicuhyba, Inga sessilis and Vochysia
. Using MaxEnt, on average, in the optimistic scenario the reduction will be of 20% while in the pessimistic
scenario it reaches 30%, and the species that will suffer the worst reduction are: Hyeronima alchorneoides, Schefflera
, Andira fraxinifolia and the species of Myrtaceae studied.
Brazilian Atlantic Forest trees, climate change, species niche modeling, GARP, MaxEnt.
Nos últimos 500 anos de ocupação da costa brasileira, de um total de 1.300.000 km
, apenas cerca de 8% da cobertura
tamanhos, formas, estádios de sucessão e situação de conservação. Cerca de metade dos remanescentes florestais de
grande extensão estão protegidos na forma de Unidades de Conservação. A maioria desses fragmentos se encontra
hoje nas regiões serranas, principalmente a fachada da Serra do Mar, por serem impróprias para práticas agrícolas.
Neste estudo, usamos técnicas de modelagem para determinar a distribuição geográfica presente e futura de 38 espécies
arbóreas típicas da Mata Atlântica lato sensu, considerando dois cenários de aquecimento global. O cenário otimista
prevê uma taxa anual de 0,5% de aumento na concentração de CO
na atmosfera e um aumento médio da temperatura
espécies e o algoritmo genético para previsões baseadas em regras pré-estabelecidas (GARP), desenvolvemos modelos
da distribuição futura das espécies estudadas, considerando as temperaturas projetadas para 2050. Os resultados obtidos
mostraram uma alarmante redução na área que as espécies estudadas poderão ocupar, bem como um deslocamento
da ocorrência atual em direção ao sul do Brasil. Na média, com o cenário otimista, a redução da área potencial de
ocorrência é de 25%, enquanto que no cenário pessimista este patamar é da ordem de 50%. As espécies que sofrerão
a maior redução na área de ocorrência são: Euterpe edulis, Mollinedia schottiana, Virola bicuhyba, Inga sessilis e
Mata Atlântica lato sensu; mudanças climáticas, modelagem de nicho de espécie, GARP, MaxEnt.
secondary forests and small fragments (<100 ha), this
percentage increases to 11.4% (Ribeiro et al., 2009).
Considering the changes in climate forecasted by
the International Panel on Climate Change (IPCC, 2007)
it is important to consider the consequences of indirect
anthropic actions, such as global warming, on the potential
distribution of Atlantic Forest trees.
The Genetic Algorithm for Rule-set Prediction/
GARP is one of the tools developed to determine the
potential distribution of species, and therefore the possible
consequences of changes in temperature, rainfall and humidity
(Stockwell and Noble, 1992; Stockwell and Peters, 1999).
To establish the model of species distribution, GARP uses
points of occurrence of the species studied, relating them
with the climatic and topographic characteristics of the
place of occurrence. Models generated from this algorithm
are described in several publications (Peterson et al., 1999,
2002; Peterson, 2001; Elith et al., 2006). The rules of species
distribution generated by GARP may then be projected
for altered climatic scenarios of the future (Siqueira and
Peterson, 2003) as well as for paleo scenarios (Martinez-
Meyer et al., 2004).
As in GARP, the Maxent algorithm is another important
tool to model species distribution, mainly when data
available is only of occurrence, not presence/absence data,
since it is based on the principle of maximum entropy
(Phillips et al., 2006).
The main objectives of this paper are: to compare
projected Atlantic Forest tree species distribution shifts
and/or reductions due to global climate change, to similar
data produced by Siqueira and Peterson (2003) for Cerrado
(another Brazilian biodiversiy hotspot) trees; and, using
the same set of data, compare the projections made using
GARP with those made using Maxent.
2. Material and Methods
2.1. Area of study
We have used the area established by IBGE (1988) as
Atlantic Forest, which comprises the following types of
vegetation: Ombrophylus Dense and Mixed Ombrophylus
(Araucaria forest) Forests, Seasonal Semideciduous and
Deciduous Forests, Coastal Plain Restingas, Mangroves
and Dunes as well as high altitude rocky outcrop vegetation
(Figure 1). This concept of Atlantic Forest, as proposed by
Joly et al. (1999) and Oliveira Filho and Fontes (2000) has
been recently recognised by the Brazilian National Congress
through Law number 11.428 from December 2006.
2.2. List of species, data on distributions
and ecological dimensions
Based on the work of Oliveira (2001) and Scudeller
and Martins (2003), who compared more the 100 lists of
arboreal species from phytossociologic studies carried out
within the Atlantic Forest Biome, we selected 38 species for
which there was sufficient data on its current distribution, and
categorised them with early secondary and late secondary,
based on Rodrigues et al. (2007) (Table 1). As in Siqueira
The Brazilian Atlantic Forest sensu lato is classified as an
area that comprises three types of forests: Ombrophylus Dense
forests, Semideciduous and Deciduous Stationary forests
from the South and Southern regions, and Ombrophylus Mist
forest, also known as Araucaria forest from Southern Brazil
(Joly et al., 1999; Oliveira Filho and Fontes, 2000).
The always green dense forest occurs in an ombrophylus
climate without a biologically dry period throughout
the year and exceptionally with two months of scarce
humidity. The average temperatures are between 22 and
25 °C. Semideciduous and deciduous forests occur in
areas with 2 to 5 months of dry season, with the same
range of temperatures. On the other hand, the Araucaria
forest of Southern Brazil occurs in areas with a subtropical
mesotermic climate, with temperature in the range of
12 to 22 °C.
Our current knowledge indicates that this complex
biome contains a species diversity higher than most of
the Amazon forests. Species richness, the extremely high
levels of endemism and the small fraction of the original
forest left, led Myers et al. (2000) to rank the Brazilian
Atlantic Forest among the top biodiversity hotspots. In the
region of Santa Tereza, Espírito Santo State, Thomaz and
Monteiro (1997) recorded 443 species of tree per hectare
and the tree diversity index can be as high as H’ = 4.48
in the Submontane forests of Serra do Mar State Park in
São Paulo State (Rochelle, 2008).
Although there is some controversy about the exact
age of the Atlantic Forest, it is regarded as the oldest
Brazilian forest (Rizzini, 1997). It is made up of a mixture
of species that have evolved from native vegetation from
the era in which South America was separating from Africa,
65 million years ago, with the original Ombrophylus dense
forest cover. On the other hand, in the northeast and in the
south, the Atlantic Forest expanded and retracted during
the Quaternary (Brown Jr., 1987; Behling and Negrelle,
2001; Ledru et al., 2005; Bush and Oliveira, 2006). There is
also abundant information about possible past connections
between the Atlantic Forest and the more recent Forests of
the Amazon Basin (Thomas et al., 1998; Costa, 2003)
During the last 500 hundred years, the Atlantic Forest
has been exploited and destroyed, being replaced first by
sugarcane in the NE region (XVI century), and then later
by coffee in Rio de Janeiro and São Paulo (XVIII and XIX
century), by cattle ranching in São Paulo and Minas Gerais
(XIX and XX century), by cocoa in Bahia (XX century),
and more recently by Eucalyptus forest for cellulose and
paper production. The forest was also replaced by cities,
being the homeland of about 125 million Brazilians, since
all state capitals from the S, SE and NE region, including
Porto Alegre, Curitiba, São Paulo, Rio de Janeiro, Belo
Horizonte, Salvador and Recife, are within the Atlantic
Forest domain. Therefore, there is only 7.6%, of the original
Atlantic Forest left, and less then 50% of the remnants
are protected in Conservation Units (Fundação SOS
Mata Atlântica and INPE, 1998). Including intermediate
Hydro-1K data set), and aspects of climate including
diurnal temperature range; mean annual precipitation;
maximum, minimum, and mean annual temperatures;
and vapor pressure (annual means 1960-1990) from the
Intergovernmental Panel on Climate Change (http://www.
ipcc.ch/), exactly the same used by Siqueira and Peterson
(2003) to project possible climate change consequences
for Cerrado trees.
The scenario models used are described in detail in
Siqueira and Peterson, (2003) and are similar to scenarios
B1 and A1F1 from the latest report of the International Panel
on Climate Change (IPCC, 2007). The optimistic scenario
forecasts an increase of 0.5% per year in the concentration
in the atmosphere, projects an average increase in
≤2 °C, while the pessimistic scenario
forecasts an increase of 1%/yr CO
and projects a mean
used the projection layers from climate changes for the
next 50 years and the same data for topographic aspects,
taking into account the little probability of topographic
change for the next 50 years. These projections from
climate layers have a resolution of 50 × 50 km, showing,
therefore, a low accuracy as they generalise the climatic
data. This difference in scale, 50 × 50 km of the climate
layers, and 1 × 1 km of topographic layers, produces loss
of quality and interferes with the definition of the potential
distribution of the species. Aiming at the minimisation
of such difficulty, all maps were rebuilt for a resolution
of 5 × 5 km (Chapman et al., 2005) cut for the Brazilian
territory, making the process of development of models
more efficient, rapid, and minimising the loss of data of
the more detailed models (1 × 1 km).
In order to produce data comparable to Cerrado trees,
we used the Genetic Algorithm for Rule-set Prediction
(GARP) as Siqueira and Peterson (2003) did in their study.
Using the software DesktopGarp 1.1.4, freely available
at (http://www.lifemapper.org/desktopgarp/), 114 models
of distributions were generated, being 38 models for the
current distribution of each species, and 76 projections
for future scenarios (38 projections using the pessimistic
scenario and 38 for the optimistic scenario). For each
species, the minimum of points considered was 30,
being 1/3 of them previously separated randomly for the
external validation of the models, and the other 2/3 were
effectively used to establish the model of distribution
of each species. Each distribution model is the result of
100 runs, to reach a coefficient of conversion of 0.01 and
a maximum of interactions of 1,000 per species, using
four rules: anatomy, range, denied range, and logistic
It is important to stress that GARP works only with
points of occurrence and thus the software selects internally
Figure 1. Phytophysiognomies of the Atlantic Forest lato
sensu (IBGE, 1993).
Floresta ombrófila densa
Floresta ombrófila aberta
Floresta ombrófila mista
Floresta estacional decidual
Floresta estacional semidecidual
Formações pioneiras (restinga, manguezal
campo solino, vegetação com influência
fluvial ou lecuatre)
Campos de altitude, encraves de cerrado,
zonas de tensão ecológica
and Peterson (2003) a limitation of this study is that only
those species for which >30 unique occurrence records
were available were used. Hence, we considered only those
species with relatively broad geographic distribution.
Distributional data representing 2,837 records (i.e.,
unique species × latitude-longitude combinations) for
these 38 species were assembled from the databanks of
the BIOTA/FAPESP Program (SinBiota, 2006) and the
FITOGEO databank (Scudeller and Martins, 2003). These
data were selected and transformed into decimal degrees,
and adjusted to DATUN WGS84 (Figure 2). Duplicated data
and those with errors of coordinates were excluded.
Aiming to produce data comparable to that of Siqueira
and Peterson (2003), environmental data included 9 electronic
map layers summarising slope, aspect, and upward curvature
“topoind” (from the U.S. Geological Survey’s (http://edc.
points of pseudo-absence in the development of its models
and also uses only a percentage of the total points for the
effective establishment of the models, using the rest for test
intrinsic to the program (Siqueira and Peterson, 2003). In
this work, we used the tool denominated Best subset, which
selects the 10 highest models in relation to the maximum
amount of points of intrinsic tests contained in the resultant
models. There were randomly selected 50% of points for the
internal, intrinsic validation with a minimum of 20 points
for creating the models, therefore, with an omission rate
of 10% and a commission rate of 50%.
After the creation and identification of the 10 best models
for each species and each scenario (present, optimistic
future and pessimistic future), these were summed through
the software ArcView 8
, resulting in a unique model of
we have calculated the size of the area of distribution from
the amount of cells of each model (transforming them in
area – km
) for comparing it with the other models of each
The statistical analyses were carried out using the
software BIOSTAT 2, matching the set of intrinsic data (1/3 of
the points that were not used in the creation of the models)
with the area of likely occurrence of the present species,
therefore, performing a binomial test of two proportions to
verify whether the present distribution obtained is different
from a distribution with random points.
To compare data generated by GARP with those using
Maxent, we used the same set of present occurrence data,
as well as the same size of cells and the same climate
change projections. Maxent models were generated
using the following standards: Convergence Threshold:
0.00001; Maximum Iterations: 500; Auto-features: yes;
exported to ArcView 9 and re-sampled in a 1-100 scale.
Thereafter we used the same specifications used for the
GARP projections, so that it was possible to compare results
without further transformation and/or analysis.
All GARP and Maxent projection models of the present
area of occurrence of the 38 species presented a high level
of significance (Binomial Test: two proportions, p < 0.05
for all species); showing that the models based only on
an increase in up to 2 °C in mean average temperatures,
i.e., the change in the potential distribution will be near the
error margins of the methods used (
± 10%) (Figure 4a, b);
a second group of 32 species that will effectively have a
significant reduction in their distribution areas, from which
2 will lose more than 50% of its occurrence area. If we
consider the pessimistic scenario, 50% of the 38 species
studied will have reductions of more than 50%.
Climate change will affect species with very restricted
present occurrence area, such as Vochysia magnifica as
climatic and topographic variables could not present
such distribution only by chance (Figure 3). As expected,
the area projected by MaxEnt, a deterministic tool, is
smaller than that projected by GARP, a probabilistic tool
(Peterson et al., 2007).
3.1. Using GARP
The species studied can be divided in two major groups, if
we consider the more optimistic scenario of climate change:
one group, of 6 species, that will be marginally affected by
and future geographic distribution. Class = classification in functional groups: E = early secondary; L = late secondary, based
on Rodrigues et al. (2007).
(Cham.) Frodin & Fiaschi
Moric. ex DC.
(Planch. & Triana) Zappi
(Schott) Poepp. ex Baill.
(Nees & Mart.) Mez
(Sw.) R. Br. ex Roem. & Schult.
Figure 4. Calyptranthes grandifolia O.Berg. (Myrtaceae): a) Present occurrence; and b) occurrence projected if tempera-
≤2 °C. Euterpe edulis Mart. (Arecaceae): c) Present occurrence; and d) occurrence projected if temperature
≤2 °C. Both using GARP.
C. Both using GARP.
Some species like Marlierea tomentosa and Rollinia
presented less then 10% of reduction in their
occurrence area, if we consider the optimistic scenario
(Table 2). While for Marlierea obscura, Ocotea dispersa,
, Schefflera angustissima, Eugenia
and Myrcia pubipetala the expected reduction
is below 20% (Table 2). On the other hand, for species
like Vochysia magnifica and Ecclinusa ramiflora this small
increase in average temperatures (
≤2 °C) is sufficient to
reduce dramatically, by more than 50%, their occurrence
area (Table 2).
well as those occupying today a wide range of conditions
and latitudes within the Atlantic Forest biome, such as
(Figure 5a, b).
Another striking result is that only one species, 2.5%
of our sample, will increase its potential occurrence
area, but only if the temperatures increase by up to 2 °C.
is very common in a wide
range of areas covered by the Atlantic Forest (Oliveira
Filho and Fontes, 2000), but does not have any known
special feature which explains why it could benefit from
a warmer climate.
simistic scenarios, using GARP.
The four species that presented an increase in their
occurrence area, in both the optimistic and pessimistic
scenarios, have high phenotypic plasticity and are benefitted
by a more homogeneous environment imposed by higher
temperatures, or are not occurring in its best conditions
Using GARP, the average reduction of occurrence
areas found for these 38 species of trees from the Atlantic
Forest is lower than that reported by Siqueira and Peterson
(2003) for Brazilian Cerrado species. Using the same
climatic scenarios that we have used, they reported that 91,
from the 162 tree species studied, should have more than
90% of reduction in its occurrence if mean temperatures
increase by up to 2 °C. This number increases to 123 when
the pessimistic scenario is used. More significant than this
high percentage of reduction is the fact that 18 species in
the optimistic scenario, and 56 in the pessimistic scenario,
tend to extinction, since the predicted potential area of
occurrence is null (Siqueira and Peterson, 2003).
Using MaxEnt the average reduction of occurrence
area is lower both for early secondary species, 22.01%
in the optimistic scenario and 28.32% in the pessimistic
scenario, and late secondary species, 18.34 and 29.47%,
respectively. Nevertheless the pattern of the tendency,
reduction in the area of occurrence and shift towards more
southern areas of Brazil, are the same.
If we consider the sum of the maps of today’s occurrence
of the Atlantic Forest species studied, there are several areas
where there is a high probability (>80%) of a concomitant
occurrence of those 38 species. For instance: the Northern
part of Rio Grande do Sul State; the extreme West and
the coastal area of Santa Catarina State; the Centre and
North-western parts of Paraná State; the entire coast of
Considering the pessimistic scenario, in which the
increase in average temperatures will be
≥3 °C, all species
studied will have their occurrence area significantly
reduced. For species like Calyptranthes grandifolia,
, Cupania oblongifolia, Rollinia
, Sclerolobium denudatum, Maytenus robusta, Myrcia
, Marlierea tomentosa and Marlierea obscura
this reduction will stay between 30 and 40% of the present
occurrence area (Table 2). While for Virola bicuhyba, Inga
Ecclinusa ramiflora and Vochysia magnifica this
reduction will reach more then 60% (Table 2).
After analysing individually each species, the projected
reductions were all summed to present a general panorama of
the consequences of global warming for the most endangered
Brazilian forest (Figure 6). The general result shows not
only a significant reduction in the potential distribution of
the species studied but also that the Atlantic Forest may be
restricted to a more southern position in Brazil.
Projection models produced using MaxEnt can be
divided into three groups (Table 3): species that showed
exactly the same behaviour observed in GARP models
(30); species that showed an increase in the potential area
of occurrence with the optimistic scenario (4); species that
presented an increase in the potential area of occurrence
in both scenarios (4). These last two groups may indicate
that some species of the Atlantic Forest are not occupying
their optimal area of occurrence today, which can be due
to competition or to the present distribution of pollinators
For the 30 species that presented a significant reduction
in their potential area of occurrence, global warming has
a strong negative impact and displacement towards higher
latitudes (South in the case of Brazil) is a strong tendency.
The same pattern was observed using GARP.
rence of species; b) occurrence of species in the optimistic scenario; and c) occurrence of species in the pessimistic scenario,
Catarina State; the Serra do Mar and coastal areas from
Paraná, São Paulo and Rio de Janeiro states; some areas
of Minas Gerais and Espírito Santo states. Extremely
important areas included in these projections are the
Cantareira-Japi region and areas along the Paraíba River
valley in São Paulo State.
The shift towards more southern and cooler areas has
also been observed for the Cerrado trees (Siqueira and
São Paulo State; the South-eastern region and the Zona
da Mata of Minas Gerais State; the Central part of Rio
de Janeiro State, and finally, the Central mesoregion of
Espírito Santo State (Figure 6).
But if we consider the maps of potential distribution
of the species in the future, these areas of concomitant
occurrence of those 38 species are reduced to the North-
west of Rio Grande do Sul State; the West of Santa
Table 3. Data on present occurrence area in square kilometres, projection of occurrence areas with the optimistic and pes-
simistic scenarios using MaxEnt.
Now, in the same way as happened with the air pollution
of a major chemical-petrochemical and fertilizer industrial
area in Cubatão (Klockow et al., 1997; Klump et al.,
2002), which has eliminated a large number of species of
plants and animals in a part of the Serra do Mar known
as Serra de Paranapiacaba, it is not physical occupation
but the atmospheric changes that is the new threat to this
– We would like to thank the team at CRIA
for all the fruitful discussions and suggestions, as well as for the
technical support for developing and testing the models. We are
also grateful to Dr. Fernando Roberto Martins, from the Botany
Department at IB/UNICAMP, for the use of his databank on
Atlantic Forest species, as well as for helping us to select the
target species used. This research was partially supported by
the State of São Paulo Research Foundation (FAPESP) as part
of the Thematic Project Functional Gradient (Process Number
03/12595-7), within the BIOTA/FAPESP Programme - The
Biodiversity Virtual Institute (http://www.biota.org.br). COTEC/
IF 41.065/2005 and IBAMA/CGEN 093/2005.permits.
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