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Shifting dynamics of climate-functional groups in old-
growth Amazonian forests
Nathalie Butt 
a
 
g
 , Yadvinder Malhi 
a
 , Mark New 
a
 
h
 
i
 , Manuel J. Macía 
b
 , Simon L. Lewis
c
 
d
 , Gabriela Lopez-Gonzalez 
c
 , William F. Laurance 
e
 , Susan Laurance 
e
 , Regina Luizão
f
 , Ana Andrade 
f
 , Timothy R. Baker 
c
 , Samuel Almeida 
j
 & Oliver L. Phillips 
c
a
 Oxford University School of Geography and the Environment , Oxford , UK
b
 Departamento de Biología , Área de Botánica, Universidad Autónoma de Madrid , Spain
c
 Earth and Biosphere Institute, School of Geography, University of Leeds , UK
d
 Department of Geography , University College London , London , UK
e
 James Cook University , Cairns , Australia
f
 INPA , Manaus , Brazil
g
 School of Biological Sciences , University of Queensland , Brisbane , Australia
h
 African Climate and Development Initiative
i
 Department of Environmental and Geographical Science , University of Capetown ,
South Africa; Died 2011
j
 Died 2011
Accepted author version posted online: 30 Jul 2012.Published online: 02 Oct 2012.
To cite this article: Nathalie Butt , Yadvinder Malhi , Mark New , Manuel J. Macía , Simon L. Lewis , Gabriela Lopez-
Gonzalez , William F. Laurance , Susan Laurance , Regina Luizão , Ana Andrade , Timothy R. Baker , Samuel Almeida &
Oliver L. Phillips (2014) Shifting dynamics of climate-functional groups in old-growth Amazonian forests, Plant Ecology &
Diversity, 7:1-2, 267-279, DOI: 10.1080/17550874.2012.715210
To link to this article:  http://dx.doi.org/10.1080/17550874.2012.715210
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Plant Ecology & Diversity, 2014
Vol. 7, Issues 1–2, 267–279, http://dx.doi.org/10.1080/17550874.2012.715210
Shifting dynamics of climate-functional groups in old-growth Amazonian forests
Nathalie Butta,g*, Yadvinder Malhia , Mark Newa,h,i , Manuel J. Macíab , Simon L. Lewisc,d , Gabriela Lopez-Gonzalezc ,
William F. Laurancee , Susan Laurancee , Regina Luizãof , Ana Andradef , Timothy R. Bakerc , Samuel Almeida+
and Oliver L. Phillipsc
aOxford University School of Geography and the Environment, Oxford, UK; bDepartamento de Biología, Área de Botánica, Universidad
Autónoma de Madrid, Spain; cEarth and Biosphere Institute, School of Geography, University of Leeds, UK; dDepartment of Geography,
University College London, London, UK; eJames Cook University, Cairns, Australia; fINPA, Manaus, Brazil; gSchool of Biological
Sciences, University of Queensland, Brisbane, Australia; hAfrican Climate and Development Initiative; iDepartment of Environmental
and Geographical Science, University of Capetown, South Africa; +Died 2011
(Received 1 February 2012; final version received 20 July 2012)
Background: Climate change is driving ecosystem shifts, which has implications for tropical forest system function and
productivity.
Aim: To investigate Amazon forest dynamics and test for compositional changes between 1985 and 2005 across different
plant groups.
Methods: Tree census data from 46 long-term RAINFOR forest plots in Amazonia for three climate-functional groups were
used: dry-affiliate, climate-generalist and wet affiliate. Membership of each group was ascribed at genus level from the dis-
tribution of individuals across a wet–dry gradient in Amazonia, and then used to determine whether the proportions of these
functional groups have changed over time, and the direction of any change.
Results: In total, 91 genera, representing 59% of the stems and 18% of genera in the plots, were analysed. Wet-affiliates
tended to move from a state of net basal area gain towards dynamic equilibrium, defined as where gain ≈ loss, governed by
an increase in loss rather than a decrease in growth and mainly driven by plots in north-west Amazonia, the wettest part of the
region. Dry-affiliates remained in a state of strong net basal area gain across western Amazonia and showed a strong increase
in stem recruitment. Wet-affiliates and climate-generalists showed increases in stem mortality, and climate-generalists showed
increased stem recruitment, resulting in overall equilibrium of stem numbers.
Conclusions: While there were no significant shifts in most genera, the results suggest an overall shift in climate-func-
tional forest composition in western Amazonia away from wet-affiliates, and potential for increased forest persistence under
projected drier conditions in the future.
Keywords: climate trends; forest composition; moisture affiliation; moisture seasonality; tropical forest
Introduction
A number of studies worldwide have shown that climate
change elicits forest ecosystem responses such as changes
in phenology, forest composition and productivity (Nemani
et al. 2003; Parmesan and Yohe 2003; IPCC 2007). The
tropics host the most diverse and productive forest sys-
tems on Earth (Beer et al. 2010) yet, until the end of the
twentieth century, they were relatively poorly studied, for
reasons of remoteness and inaccessibility. While research
on the impacts of climate change has typically focused
elsewhere, changes in ecosystem structure and function
are also very likely to be occurring in the tropics where
climate-driven changes may affect the role forests play
as carbon sinks (Lewis et al. 2004a, 2009). Analysis of
long-term Amazon plot data, part of the RAINFOR project
(Malhi et al. 2002), has shown that old growth forests have
increased in biomass in recent years (Baker et al. 2004), and
that Amazonian forests generally have become more, pro-
ductive and dynamic in terms of rates of stem recruitment,
mortality and turnover (Phillips et al. 1998, 2004; Baker
et al. 2004; Lewis et al. 2004b). Such changes in structure
*Corresponding author. Email: n.butt@uq.edu.au
have included an Amazon-wide increase in stem recruit-
ment and mortality (Phillips et al. 2004), and a Neotropical
increase in above-ground woody biomass (Phillips et al.
1998, 2002; Baker et al. 2004), albeit perhaps temporar-
ily reversed by an intense drought in 2005 (Phillips et al.
2009).
There have been few studies of trends in func-
tional composition in old-growth tropical forests, although
Phillips et al. (2002) have shown that large lianas in intact
western Amazon forests have recently increased in relative
dominance, a pattern that may extend across the Neotropics
(Wright et al. 2004; Schnitzer and Bongers 2011) and
Laurance et al. (2004) found increasing rates of growth in
most relatively abundant tree genera in a central Amazonian
landscape, and a general increase in rates of tree mortal-
ity and recruitment. The results suggested that numbers
of faster-growing old-growth genera (primarily canopy
trees) increased, while slower-growing understory genera
decreased. Pan-tropical analyses by Chave et al. (2008) and
Lewis et al. (2009) also showed a significant increase in
biomass across 10 and 156 forest plots respectively.
© 2012 Botanical Society of Scotland and Taylor & Francis
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268 N. Butt et al.
Changes in climate variables such as temperature, pre-
cipitation, solar radiation and diffuse fraction of solar radi-
ation, more important for sub-canopy species (cf. Nemani
et al. 2003), are possible drivers of this observed accel-
erated growth, as is the increase of atmospheric CO2
concentration (Curtis and Wang 1998; Norby et al. 1999;
Cramer et al. 2001). While water use efficiency (WUE)
is predicted to increase with rising atmospheric CO2 con-
centrations (Farquhar 1997; Winter et al. 2001), rising
temperatures may increase transpiration rates and water
stress (Malhi et al. 2009), and across the region there
was a long-term trend of temperature increase of 0.26 ◦C
decade−1 (Malhi and Wright 2004). With plant moisture
availability the strongest of several environmental and bio-
physical variables in terms of forest structure (Toledo et al.
2011a), precipitation seasonality is an important factor in
plant species richness and diversity and the composition of
plant assemblages (Gentry 1988; ter Steege et al. 2003; Butt
et al. 2008). Although changes in interannual and seasonal
precipitation amounts were insignificant across the region
overall (Malhi and Wright 2004), there has been a trend
of increasing dry season length (Marengo et al. 2011), a
significant decrease in dry season cloud fraction and cloud-
related diffuse radiation, of about 8% (Butt et al. 2009), and
an increasing trend of incoming short-wave solar radiation
(Hashimoto et al. 2010). While it has not been estab-
lished whether other climatic or environmental variables
may be influencing tropical biodiversity and productivity,
these three factors may act to increase seasonal water stress
even in the absence of changes in the rainfall regime.
From the perspective of plot dynamics, this paper sets
out to investigate temporal trends in forest community com-
position across Amazonian old-growth forests utilising a
large and unique database. While earlier studies examined
shifts in species in relation to drought (Condit 1998;
Enquist and Enquist 2011; Feeley et al. 2011), they were
focussed on single sites or smaller areas; possible trends
in relation to water availability have not been previously
investigated across a large number of sites. The aim of the
work is to establish if there have been any shifts or trends
in proportions and dynamics of wet-affiliate, dry-affiliate
and climate-generalist tree genera on a decadal level, and to
quantify the magnitude of any change. Moisture affiliation
is related to drought and shade tolerance, and productivity
is a function of the potential trade-off between drought tol-
erance and growth, which may also be determined by CO2
concentration. We therefore expect that, in response to envi-
ronmental trends: 1) increasing seasonality would favour
more drought-tolerant plant groups; and that 2) increasing
ambient CO2 concentrations might favour more drought-
sensitive plant groups by improving water use efficiency.
Materials and methods
Floristic data
Floristic data were extracted from the RAINFOR database
(www.forestplots.net; Lopez-Gonzalez et al. 2011) in
November 2006. The RAINFOR census plots are located
across the Amazon region and the data vary greatly in
temporal range. Measurement details and methodology
have been previously described (e.g. Phillips et al. 2002).
For this analysis we selected plot censuses which spanned
at least 10 years, with at least two census intervals. In total,
46 plots below 1000 m a.s.l. were used in the analysis. The
plots were allocated to one of three regions: south-west
and north-west, at either end of the north–south moisture
gradient (north→south = wetter→drier) across western
Amazonia, and east-central Amazonia (Figure 1), which
are characterised by different climates. Mean monthly
Figure 1. Distribution of the RAINFOR census plots in Amazonia used in this analysis.
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Compositional shifts in lowland Amazon forests 269
dry quarter rainfall over the period covering the census
monthly data (1985–2005), was 202 mm for the north-west
region, 74 mm for the east-central region and 36 mm
for the south-west (University of Delaware (UDEL) and
Climate Research Unit, University of East Anglia (CRU)
long-term data).
As the temporal range of the plot censuses varied so
greatly, the investigation focused on the 20-year period
from 1985 until 2005, ending immediately prior to the
Amazon drought of 2005 (Phillips et al. 2009). Overall,
24 plots had 15 or more years of census data. The num-
ber of plots per region was as follows: for the east-central
region, n = 17; for the north-west region, n = 11, and for
the south-west region, n = 18. Plot details are given in
Appendix 1.
Climate functional groups
We previously investigated generic affiliations with the pre-
cipitation gradient in western Amazonia (Butt et al. 2008),
quantifying the relationship between moisture seasonality
and plant abundance for nearly 100 common woody plant
genera using all woody stems ≥ 2.5 cm dbh in 39 plots
(0.1 ha) below 1000 m elevation (lowland), and west of
62◦ W, of the Gentry sample plot dataset (http://www.
salvias.net/pages/index.html) (Appendix 2). Of the 91 gen-
era analysed, there were significant correlations for a
third of the genera with either wetter (designated as
‘wet-affiliates’) or drier conditions (designated as ‘dry-
affiliates’), and two-thirds, with no moisture seasonality
affiliation, were designated as ‘climate-generalists’. In the
current analysis, the climate functional groups represent
about 60% of individuals and 18% of genera in the plots
analysed.
Here we use data for stems ≥ 10 cm dbh from the
RAINFOR dataset and first divide the genera into the three
climate functional groups; the remainder (those genera not
previously tested) were grouped as ‘unknown’ (430 gen-
era). Relative abundances were calculated using the data
for all stems, including the ‘unknown’ group as well as the
three functional groups.
We used plots with at least two census intervals and
standardised the dataset to analyse three censuses with two
census intervals of about the same length to avoid possible
census interval effects confounding the results. The average
date of the first, mid and final censuses was 1988, 1994 and
2003. The first census interval, on average, was 6.4 ±
1.9 years (standard deviation; range 4–11 years); the second
was 8.1 ± 2.5 years (range 4–13 years). The regions varied
from each other only slightly in this respect, with a first
census interval of 5.9 years for the north-west, 6.1 years for
the south-west, and 7.1 years for east-central. The second
census interval was 8.5 years for the north-west and east-
central regions, and 7.6 years for the south-west region. The
mean plot size was 1.4 ± 0.2 ha (range 0.4–9 ha).
We examined net changes, between ∼1985 and
∼2005, for each of the three climate functional groups
(wet-affiliate, climate-generalists and dry-affiliates). We
calculated basal area (BA) and stem density at each cen-
sus, BA growth and mortality rates, and stem recruitment
and mortality rates, for both census intervals, and used
Wilcoxon two-sample tests (as the rates were not normally
distributed) to establish the significance of the differences
over time. The calculations were as follows (cf. Lewis et al.
2004b):
Mortality λ = [ln n0 − ln(n0 − Dt)] /t 1
λ × 100 gives percent per annum, where λ is the mortality
coefficient, n0 is the total BA or number of stems at the start
of the interval, Dt is the BA or stem loss during the interval,
and t is the interval (in years).
Recruitment μ = [ln nt − ln(n0 − Dt)] /t 2
ln nt is the value for BA or stems at the end of the inter-
val. These calculations allowed us to compare mortality and
growth/recruitment for BA and stem density across the cli-
mate functional groups, overall, and by region. We used a
log-linear analysis in order to retain normal distributions in
the analysis.
We assessed whether the climate functional groups,
overall and by region, are in (or close to) dynamic equi-
librium, defined as where the level of gain is similar to
that of loss, and examine changes between intervals. We
determined these measures for all woody plants overall, by
climate functional group, and by region, and considered
whether the changes over time were driven by mortality
or growth. Within a plot, changes in BA correlate strongly
with changes in biomass (Malhi et al. 2006), and hence
the BA dynamics can be taken to be broadly indicative of
changes in biomass dynamics, neglecting net changes in
tree allometry and wood density.
Results
Distribution and abundance of the climate functional
groups
The ‘dry’ group (four genera) was present in 41 of the
46 plots at the beginning of the period of study. The
plots where it was not present were primarily in the north-
west, the wettest Amazonian region. The ‘wet’ (27 genera)
and ‘generalist’ (60 genera) groups were present in all
plots. The dominant genera in the wet-affiliate group were:
Eschweilera and Protium (>15% each of classified wet-
affiliate stems); Pouteria and Iriartea each contributed
more than 10% of stems to the generalist group; in the
dry-affiliate group Aspidosperma overwhelmingly domi-
nated, with around 90% of classified stems. The relative
abundance, in terms of proportional BA and individuals,
of the three climate functional groups varied by region
with the climate-generalists dominating in the south-west
region and the wet-affiliates dominating in the north-west
and east-central regions (Table 1).
In terms of stem numbers, but not BA, the dry-affiliates
were more abundant in the south-west and east-central
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270 N. Butt et al.
Table 1(a). Relative abundance (%) by region, by climate func-
tional group as a proportion of all stems, including the ‘unknown’
group.
Climate functional group
Wet Generalist Dry Unknown
South-west
% BA 12 41 1 45
% stems 17 48 1 34
East-central
% BA 26 19 2 52
% stems 35 24 1 40
North-west
% BA 30 24 2 43
% stems 32 28 0.3 39
Table 1(b). Absolute stem numbers by region and by climate
functional group, including the ‘unknown’ group.
Wet Generalist Dry Unknown
All regions
Census 1 9684 11589 237 13456
Census 2 9689 11674 231 13415
Census 3 9411 11537 235 14386
South-west
Census 1 2150 6206 127 4551
Census 2 2144 6372 122 4494
Census 3 2113 6505 128 4648
East-central
Census 1 6008 4081 94 7035
Census 2 5962 3999 93 7071
Census 3 5682 3778 90 7816
North-west
Census 1 1526 1302 16 1870
Census 2 1583 1303 16 1850
Census 3 1616 1254 17 1922
regions, more than twice as abundant as in the north-west.
However, the dry-affiliate group as defined in our analysis
comprised less than 2% of stems or BA in any of the regions
(Table 1(a), and Table 1(b) for absolute stem numbers).
Temporal trends in climate functional group growth and
mortality
We present statistically significant results in the figures,
and all results in Table 2 (Wilcoxon analyses at P <0.05).
Overall, there was a clear relationship between climate
functional group and dynamism, with wet-affiliates being
the most dynamic, and dry-affiliates the least dynamic.
In terms of net changes between intervals, wet-affiliates
moved from experiencing strong net gain in BA in the first
interval towards dynamic equilibrium (not significantly dif-
ferent from the one-one line), in the second as BA loss rates
increased. Wet-affiliates maintained high dynamism over-
all (Figure 2(a)). Climate-generalists maintained a slight
net BA gain while dry-affiliates remained in a strong
dynamic disequilibrium (significantly different from the
one-one line) of net BA gain. Analysis of stem dynamics
by climate functional group indicates that the wet-affiliate
and climate-generalist groups showed increases in stem
mortality (P < 0.05, z1.645 P = 0.2, z0.842 respectively)
(Figure 2(b)), and both groups shifted slightly away from
dynamic equilibrium (from P = 0.7, z−0.524 to P <
0.05, z1.645 for wet-affiliates; P = 0.5, z−0.01 to P <
0.05, z1.645 for climate-generalists): the first interval was
not significantly different from dynamic equilibrium. Dry-
affiliates, the least dynamic group of the three, showed a
strong increase in recruitment and weaker decrease in mor-
tality (P < 0.08, z1.405, P = 0.7, z−0.524 respectively),
and moved from a state of net stem loss to net stem gain.
Temporal trends in climate functional group growth
and mortality by region
All groups in the north-west plots gained in BA in the first
interval (Table 2, Figure 3(a)). Wet-affiliates and climate-
generalists all showed a significant (P < 0.05, z1.645 and
P < 0.01, z2.326) increase in BA loss, and climate-
generalists also showed a significant increase in BA gain
(P < 0.05, z1.645). The most marked change was that wet-
affiliate and climate-generalist groups showed a significant
increase in stem mortality (P < 0.05, z1.645 and P < 0.01,
z2.326, respectively), causing an overall increase in stem
mortality (P < 0.05, z1.645) (Table 2, Figure 3(b)).
Dry-affiliates showed a significant increase in stem
recruitment in the south-west (P < 0.01, z2.326) and moved
from net stem loss to net stem gain (Figure 4). This large
increase in dry-affiliate stem recruitment was not driven by
one plot but is seen in most plots. There was no significant
change in dry-affiliate BA.
As the dry-affiliate group is dominated by a single
genus Aspidosperma (∼90% of all dry-affiliate individ-
uals), analyses were performed to investigate whether
this genus alone was driving the dynamics of the dry-
affiliate group. There were 24 species of Aspidosperma
distributed across the plot network in the north-west and
south-west, which indicates a potentially high level of
intra-generic ecophysiological variability. For the north-
west plots, Aspidosperma was the sole driver of changes
in stem mortality (and thus BA loss) and stem recruit-
ment in the dry-affiliate group. However, there was a larger
difference (increase) in BA gain between the two cen-
sus intervals when Aspidosperma was excluded from the
analysis, i.e. the increase in growth over time was more
pronounced in the other dry genera than in Aspidosperma
(Figure 5(a)). In the other region where dry-affiliates
other than Aspidosperma were recorded, the south-west,
BA gain and stem recruitment were both higher between
intervals when Aspidosperma was excluded, while stem
mortality increased rather than decreased (but not sig-
nificantly) (Figure 5(b) and Table 3). Hence exclusion
of Aspidosperma enhances the trends in the dry-affiliates
rather than suppressing them. Further investigation of the
other dry-affiliates indicated that the trends reported over-
all for dry-affiliates were consistent across plots and genera:
no single genus or plot was driving the results.
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Compositional shifts in lowland Amazon forests 271
Table 2. Mean and standard error values for plant climate functional group basal area loss and growth and stem mortality and recruit-
ment, for all groups and all regions, for the two intervals. Significant changes between interval highlighted; ∗, P < 0.05; ∗∗, P < 0.01
significant change (Wilcoxon test statistic).
Basal area loss Std error Basal area growth Std error
Wet affiliate Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2
North-west ∗1.66 ∗3.28 0.28 0.43 2.69 2.93 0.21 0.16
East-central 1.46 1.37 0.36 0.13 1.41 1.55 0.1 0.07
South-west 2.62 2.76 0.41 0.34 3.04 2.93 0.15 0.19
Stem mortality Std error Stem recruitment Std error
Wet affiliate Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2
North-west ∗1.61 ∗2.44 0.24 0.22 2.22 2.48 0.31 0.34
East-central 1.57 1.32 0.34 0.09 1.23 0.77 0.17 0.13
South-west 2.61 2.73 0.28 0.23 2.59 2.48 0.23 0.3
Basal area loss Std error Basal area growth Std error
Climate generalist Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2
North-west ∗∗1.66 ∗∗3.05 0.39 0.28 ∗2.40 ∗2.95 0.2 0.32
East-central 1.86 1.32 0.39 0.17 1.43 1.52 0.09 0.13
South-west 2.18 2.11 0.29 0.16 2.41 2.48 0.13 0.14
Stem mortality Std error Stem recruitment Std error
Climate generalist Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2
North-west ∗∗1.87 ∗∗2.85 0.21 0.22 ∗1.81 ∗2.40 0.24 0.23
East-central 1.77 1.38 0.37 0.11 1.08 0.83 0.15 0.17
South-west 1.83 2.11 0.1 0.11 2.15 2.18 0.23 0.19
Basal area loss Std error Basal area growth Std error
Dry affiliate Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2
North-west 0.02 0.01 0.02 0.01 1.4 2.22 0.43 0.58
East-central 0.69 1.11 0.4 0.74 0.97 1.12 0.16 0.22
South-west 0.94 1.06 0.62 0.52 1.77 1.97 0.37 0.41
Stem mortality Std error Stem recruitment Std error
Dry affiliate Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2 Interval 1 Interval 2
North-west 0.6 0.4 0.6 0.4 0.6 0.47 0.6 0.47
East-central 1.07 0.53 0.69 0.1 0.68 0.16 0.4 0.1
South-west 1.51 0.44 0.26 0.98 ∗0.44 ∗2.29 0.26 0.65
Discussion
Our analysis demonstrates the forest change that occurred
in Amazonia between 1985 and 2005: wet affiliates
showed a relative decrease in both BA and stem number
overall, while generalists and dry affiliates showed relative
increases in these two metrics. Recent findings from an
analysis of species composition in plots in Costa Rica,
on Barro Colorado Island, and across a Panama-wide
precipitation gradient, also indicated an increase in the rep-
resentation of drought-tolerant taxa in forest community
composition, which may suggest widespread shifts in
similar directions (Enquist and Enquist 2011; Feeley et al.
2011).
Although overall most genera did not show significant
changes, the pronounced increase in BA loss and stem mor-
tality for wet-affiliates would suggest a potential slowing of
growth rates for this group, which could be an indication
of climate sensitivity or long-term successional processes.
These changes, combined with an increase in all four mea-
sures of dynamism for climate-generalists in the north-west
broadly reflects earlier findings (Lewis et al. 2004b; Phillips
et al. 2004), that forests in the west of the region have been
changing more rapidly than those in the east. Wet-affiliate
BA gain decreased in the south-west, while stand-level
analyses showed no significant change in stem numbers.
If this group is decreasing in gain and increasing in loss (in
the north-west), a shift in community composition could be
suggested. It is difficult to isolate this as a marked trend,
although it is supported by the strong relative increase in
dry-affiliate numbers in the region.
Our climate analyses showed no significant changes
in precipitation seasonality in the north-west and south-
west, which suggests that any changes in forest compo-
sition with regard to our climate functional groups are
unlikely to be driven by changes in rainfall regime alone
in this region. However, while interannual precipitation
trends were insignificant in the three regions (Malhi and
Wright 2004), the increasing dry season length com-
bined with the changes in dry season cloud fraction and
cloud-related diffuse radiation, temperature and incoming
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272 N. Butt et al.
Figure 2. Direction and magnitude of changes in (a) basal area loss and gain and (b) stem mortality and recruitment between Interval
1 and Interval 2 for all plots, mean plot %, by climate functional group. Standard error bars (95% confidence limits). The rates of change for
each of the three functional groups and across each region separately are shown in gain vs. loss plots to illustrate both absolute magnitude
and changes in parameters. For basal area, ‘gain’ here includes recruitment and growth, while stem gain is recruitment only; ‘loss’ for
basal area and stems is mortality. Net change is the difference between gain and loss. In these figures, points close to the 1:1 line are in
dynamic equilibrium (gain ≈ loss); P values give the significance of difference from the 1:1 line. Points below the line indicate greater
gain than loss, and points above the line greater loss than gain. Distance from the origin is an indicator of overall dynamism and turnover
(but not equal to turnover sensu strictu). The error bars represent standard error.
short-wave solar radiation (Malhi and Wright 2004; Butt
et al. 2009; Hashimoto et al. 2010; Arias et al. 2011;
Marengo et al. 2011), may increase transpiration and hence
seasonal water stress even with no change in precipita-
tion seasonality. They may thus be responsible for the
increase in dry-affiliate stem recruitment in the south-west,
while wet-affiliates and climate-generalist groups may be
becoming more vulnerable to moisture stress induced by
higher dry season transpiration rates (Malhi et al. 2009).
In addition, temperature increase may drive increases in
nutrient availability through more rapid decay and miner-
alisation of litter, and the more dynamic species or groups
(including drier groups) are able to respond rapidly (Lewis
et al. 2004a; 2009).
A drought classification and subsequent analysis of
forest dynamics derived from trees in plots across the
same (as above) Panama moisture gradient, using a similar
method to our work, concluded that species distribution
and forest composition was driven by seasonal and spa-
tial variation in moisture availability, especially in drier
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Compositional shifts in lowland Amazon forests 273
Figure 3. Gain/loss diagram for (a) basal area gains and losses, and (b) stem recruitment and mortality, for all climate-functional groups,
for the north-west region. The total for all climate-functional group stems, ‘all’ (the three functional groups combined) is included (grey
line). Wet-affiliates and climate-generalists all showed a significant (P < 0.05, z1.645 and P < 0.01, z2.326) increase in basal area loss,
which brought them into dynamic equilibrium in the second interval (gain ∼ loss). Climate-generalists also showed a significant increase
in basal area gain (P < 0.05, z1.645). Wet-affiliates moved from a state of net stem gain (P < 0.07, z1.484) into dynamic equilibrium
(P < 0.9, z−1.315), while a significant increase (P < 0.01, z2.326) in climate-generalist dynamism moved this group into disequilibrium
(net stem loss). Wet-affiliate and climate-generalist groups showed a significant increase in stem mortality (P < 0.05, z1.645 and P < 0.01,
z2.326, respectively), causing an overall increase in stem mortality (P < 0.05, z1.645). The dry-affiliate group, a very small component of
trees in these plots, has extremely low dynamism and was in equilibrium.
years, when moisture stress increased (Engelbrecht et al.
2007; Comita and Engelbrecht 2009). This suggests that
changes in moisture seasonality would drive shifts in for-
est composition; an increase in seasonality would therefore
support our first hypothesis, that drought-tolerant groups
would be favoured by these changes. Drought-intolerant
genera, while increasing in mortality, showed no decrease
in growth, suggesting that the rising CO2 concentrations
(from 346 ppmv in 1985 to 380 ppmv in 2005 – Carbon
Dioxide Research Group, Mauna Loa) have counteracted
any negative impacts of moisture stress for this group.
There are indications of some changes in stand-level
stem numbers and BA for the different climate-functional
groups. Wet-affiliates, or drought-intolerant plants, also
tend to be shade tolerant (Butt et al. 2008), and the fact
that they showed significant increases in both BA loss
and stem loss, but no significant gains in either BA or
stem recruitment, in the wetter north-west could suggest
that forests are beginning to shift towards more generalist
communities. If the climate functional groups are also
associated with shade tolerance and temperature sensi-
tivity, these factors could be driving such a shift. The
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274 N. Butt et al.
Figure 4. Gain/loss diagram for stem gains and losses, for all climate-functional groups, for the south-west region. The regional total
for each climate-functional group stems, ‘all’ (all three functional groups combined, for each region) is included (grey line). Climate-
generalists and wet-affiliates started in stem equilibrium and remained there in the second interval. Dry-affiliates showed a significant
increase in stem recruitment (P < 0.01) and moved from net stem loss to net stem gain.
parallel increase in dry-affiliates could also support such a
shift. The clear link between climate sensitivity, as defined
here by moisture seasonality affiliation and dynamism, is
ecologically interesting; currently, dry-affiliate plants are
the least dynamic of the climate-functional groups, but
if forest conditions become drier there may be further
increases in dry-affiliates and dry-affiliate dynamism. Such
shifts away from wetter communities and towards more
generalist and drier communities could have positive con-
sequences for forest persistence under future climate drying
conditions, and further implications for forest productivity
and carbon sequestration (Toledo et al. 2011b).
In addition to possible climate drivers of changes
in composition and dynamics, forests may be recover-
ing from previous disturbances and at different stages of
recovery/succession, thus exhibiting shifts in dynamism
(Wright 2005; Lewis et al. 2009; Feeley et al. 2011); how-
ever, the approach we used in this paper, of many plots
spread over a large geographic region, should reduce the
relative importance of disturbance events at stand level.
Other related factors which may influence the estimation
of changes in composition include lag-times: (i) between
seedling recruitment and growing to 10 cm dbh, which may
be very long and stochastic; (ii) for dying, and (iii) for
recovery after drought events. Although our analysis con-
siders changes prior to the extreme droughts of 2005 and
2010 (Lewis et al. 2011), it is possible that earlier droughts
influenced growth rates, maybe even sufficiently to cause a
directional change in composition.
We note that the dry-affiliate functional group as
defined here accounts for only a very small fraction (<2%)
of stem numbers or BA in the plots, and hence does not
indicate a large impact on overall community dynamics or a
strong shift in overall community composition, but rather a
shift related to water status. It is possible, however, that the
group represents part of a wider spectrum of dry-favouring
genera that remain unclassified into functional group, or
allocated as climate-generalists, in which case there may
already have been substantial overall shifts in community
composition in either direction along the wet–dry affiliation
spectrum.
Finally, it should be noted that the period analysed
in this paper (overall, 20 years split in two) is still rela-
tively short for identifying long-term trends. Nevertheless,
parts of Amazonia experienced two strong droughts after
the period of this study, in 2005 (Aragao et al. 2007) and
2010 (Lewis et al. 2011), which may sharpen the tendency
towards increasing abundance of dry-affiliates. The present
analysis provides initial clues to functional compositional
changes occurring in Amazonian forests; these will need to
be tested with longer-term, and more trait-based, analyses
of functional groups.
Acknowledgements
N. Butt’s Ph.D. was funded by the UK Natural Environment
Research Council. We thank those who contributed field data: L.
Arroyo, F. Cornejo, N. Higuchi, E. Honorio, I. Huamantupa, N.
Jaramillo, R. Luizão, A. Monteagudo, D. Neill, A. Pena Cruz, J.
Pipoly, J. Terborgh, M. Silva, P. Nuñez, and R. Vasquez. Thanks
also to Toby Marthews for his help with R coding. Funding
for plot monitoring in Amazonia was provided by grants to OP
and YM from NERC, the EU Framework V, and the National
Geographic Society. OP is supported by an Advanced Grant from
the European Research Council. Simon L. Lewis is supported by
the Royal Society. The manuscript was improved by comments
from Lourens Poorter, Sharon Strauss and two anonymous refer-
ees. This paper is dedicated to the memory of co-author Samuel
Almeida, a committed Amazon forest ecologist who passed away
during the preparation of the manuscript.
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Compositional shifts in lowland Amazon forests 275
Figure 5. Comparison of changes between census intervals for the dry-affiliate group, including and excluding Aspidosperma, for
(a) basal area gain and loss, and (b) stem recruitment and mortality. (East-central is not included as the dry-affiliate group comprised
only Aspidosperma in this region; there were no dry-affiliate-excluding Aspidosperma stem changes in the north-west).
Table 3. Comparison of changes for the dry-affiliate group by
including vs. excluding Aspidosperma.
% annual change between intervals
All dry-affiliates Excluding Aspidosperma
North-west
BA gain 0.82 1.86
BA loss 0.01 0
Stem recruitment −0.13 0
Stem mortality −0.20 0
South-west
BA gain 0.21 0.61
BA loss 0.11 0.08
Stem recruitment −0.95 −1.86
Stem mortality −0.19 0
Notes on contributors
Nathalie Butt is a climate and ecosystem scientist with research
interests in tropical and temperate forest ecology.
Yadvinder Malhi is Professor of Ecosystem Science. He focuses
on interactions between forest ecosystems and the global atmo-
sphere, and carbon, energy and water cycles.
Mark New works on observed climate change and climate change
impacts.
Manuel J. Macía is an assistant professor. He works on the
biodiversity and conservation of vascular plants in north-west
South America and the integration of ecological and ethnobotani-
cal studies.
Simon L. Lewis is a plant ecologist and global change science
researcher.
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276 N. Butt et al.
Gabriela Lopez-Gonzalez researches ecoinformatics and plant
functional characteristics and works on a database of forest inven-
tories (www.forestplots.net) and functional traits information.
William Laurance is a research professor studying the impacts of
land use and climate change on tropical forest ecosystems and
biodiversity.
Susan Laurance is a senior lecturer and her research focuses on
tropical forest dynamics and landscape ecology.
Regina Luizão is an ecologist with research interests in
biodiversity and nutrient cycling in tropical forests.
Ana Andrade is the herbarium manager for the Biological
Dynamics of Forest Fragments Project in Manaus, Brazil
(BDFFP).
Timothy Baker is a tropical forest ecologist and works on the
carbon dynamics, evolution and conservation of tropical forest
ecosystems.
Oliver Phillips is Professor of Tropical Ecology. His work focuses
on the dynamics of carbon and biodiversity across the world’s
tropical forests and how these change with changing climate.
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Appendix 1. Plot and census information
Plots sited very closely together and 0.25 ha or less were combined; 12 plots became three in the east-central region.
Plot Plot name Latitude Longitude Plot area (ha) Census 1 Census 2 Census 3
ALM-01 Altos de Maizal −11.8 −71.47 2 1994 1999 2004
ALP-11 Allpahuayo A poorly drained −3.95 −73.43 0.44 1990 1996 2005
ALP-12 Allpahuayo A, very well drained −3.95 −73.44 0.4 1990 1996 2005
ALP-21 Allpahuayo B, sandy −3.95 −73.44 0.48 1990 1996 2005
ALP-22 Allpahuayo B, clayed −3.95 −73.44 0.44 1990 1996 2005
BDF-03 BDFFP, 1101 Gaviao −2.4 −59.9 1 1987 1991 2003
BDF-04 BDFFP, 1102 Gaviao −2.4 −59.9 1 1987 1991 2003
BDF-05 BDFFP, 1103 Gaviao −2.4 −59.9 1 1987 1991 2003
BDF-06 BDFFP, 1201 Gaviao −2.4 −59.9 3 1986 1992 2003
BDF-07 BDFFP, 1105 Gaviao −2.4 −59.9 1 1988 1999 2004
BDF-08 BDFFP, 1109 Gaviao −2.4 −59.9 1 1988 1999 2004
BDF-09 BDFFP, 1113 Florestal −2.4 −59.9 1 1987 1992 2002
BDF-10 BDFFP, 1301 Florestal 1 = plot
1301.1 and 1301.3
−2.4 −59.9 2 1988 1997 2002
BDF-11 BDFFP, 1301 Florestal 2 = plots
1301.4,5,6
−2.4 −59.9 3 1988 1997 2002
BDF-12 BDFFP, 1301 Florestal 3 = plots
1301.7,8
−2.4 −59.9 2 1988 1997 2002
BDF-13 BDFFP, 3402 Cabo Frio −2.4 −59.9 9 1985 1991 2003
BDF-14 BDFFP, 3304 Porto Alegre −2.4 −59.9 1 1987 1992 2003
BNT-01 Bionte 1 −2.63 −60.17 1 1986 1995 2005
BNT-02 Bionte 02 −2.63 −60.17 1 1986 1995 2004
BNT-04 Bionte 4 −2.63 −60.15 1 1986 1995 2005
CAX-01 Caxiuana 1 −1.74 −51.46 1 1994 1999 2004
CUZ-01 Cuzco Amazonico, CUZAM1E −12.58 −69.15 1 1989 1994 2003
CUZ-02 Cuzco Amazonico, CUZAM1U −12.58 −69.15 1 1989 1994 2003
CUZ-03 Cuzco Amazonico, CUZAM2E −12.50 −68.96 1 1989 1994 2003
CUZ-04 Cuzco Amazonico, CUZAM2U −12.56 −69.13 1 1989 1994 2003
JAS-02 Jatun Sacha 2 −1.07 −77.6 1 1987 1994 2002
JAS-03 Jatun Sacha 3 −1.07 −77.67 1 1988 1994 2002
JAS-05 Jatun Sacha 5 −1.07 −77.67 1 1989 1994 2002
JRI-01 Jari 1 −0.89 −52.19 1 1985 1990 1996
MNU-01 Manu, alluvial Cocha Cashu Trail 3, M1 −11.87 −71.35 1 1990 1995 2000
MNU-03 Manu, terra firme terrace, M3 −11.88 −71.35 2 1991 1996 2001
MNU-04 Manu, terra firme ravine, M4 −11.88 −71.35 2 1991 1996 2001
MNU-05 Manu, alluvial Cocha Cashu Trail 12 −11.87 −71.35 2 1989 1994 1999
MNU-06 Manu, alluvial Cocha Cashu
Trail 2 & 31
−11.87 −71.35 2.25 1989 1994 2004
RES-03 Porongaba 1 −10.82 −68.77 1 1991 1999 2003
RES-04 Porongaba 2 −10.80 −68.77 1 1991 1999 2003
SUC-01 Sucusari A −3.25 −72.91 1 1992 1996 2005
SUC-02 Sucusari B −3.25 −72.90 1 1992 1996 2005
SUM-01 Sumaco −1.75 −77.63 1 1989 1996 2002
TAM-01 Tambopata plot zero −12.84 −69.29 1 1987 1994 2003
TAM-02 Tambopata plot one −12.83 −69.29 1 1987 1994 2003
TAM-04 Tambopata plot two swamp edge clay −12.84 −69.28 0.42 1985 1990 2003
TAM-05 Tambopata plot three −12.83 −69.27 1 1986 1994 2005
TAM-06 Tambopata plot four −12.84 −69.30 1 1991 1998 2005
TAM-07 Tambopata plot six −12.83 −69.26 1 1985 1994 2003
YAN-01 Yanamono A −3.44 −72.85 1 1989 1996 2005
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Appendix 2
The Gentry dataset of 0.1 ha floristic samples was used (http://
www.salvias.net/pages/index.html) for all woody stems ≥2.5 cm
dbh. Vouchers of plants were collected and identified at the
Missouri Botanic Garden. The analysis used 39 plots below
1000 m elevation (lowland) and west of 62◦ W, including
additional data for four 0.1 ha plots in Yasuní, Ecuador, provided
by MJ Macia. A measure of relative abundance (percentage
frequency of each tree genus per plot) was calculated to enable
comparisons in the representation of each genus across plots and
varying precipitation regimes, and to account for the differences
in plant numbers between plots. Species diversity was such that
most species were too rare (e.g. fewer than one individual per
sample unit) to include in the analysis. As many more trees were
accurately identified to genus than to species (about 30% of all
trees recorded were not identified to species level, and many
identified only to morphospecies), genus-level plant distribution
data were used. Climate data were obtained from the Climate
Research Unit (CRU) 0.5-degree global dataset (New et al. 1999).
From this monthly dataset, precipitation data were used to derive
a measure of dry season intensity for rainfall and rainfall-related
variables. For each half-degree pixel, the sum of the precipitation
in the driest three months was calculated and then used as a dry
season (intensity) measure. Two other precipitation-related vari-
ables were also included: soil water content (SWC) and potential
evapotranspiration minus precipitation (PET - p). The SWC
estimates were obtained from the Sheffield dynamic vegetation
Table A1. Rainfall seasonality ranking for woody genera in the western Amazon. The rankings, derived from Kendall’s t coefficients,
range approximately between 0.5 (strongly wet-affiliated) and −0.4 (strongly dry-affiliated). Generally values between around 0.2 and
−0.2 indicate no significant correlation with rainfall. (The asterisked genera are those with a statistically significant correlation; P < 0.05
or P < 0.01 equivalents after the application of Bonferroni’s correction for multiple comparisons). Source: Butt et al. (2008).
∗Acacia −0.395 Cissus 0.105 ∗Miconia 0.228
∗Arrabidaea −0.380 Tapirira 0.107 Eugenia 0.229
∗Capparis −0.359 Socratea 0.118 ∗Paullinia 0.241
∗Aspidosperma −0.357 Tachigali 0.125 Pithecellobium 0.243
Serjania −0.277 Caraipa 0.128 ∗Coussarea 0.267
Hippocratea −0.273 Geonoma 0.138 ∗Strychnos 0.282
Cydista −0.223 Sorocea 0.138 ∗Talisia 0.289
Hirtella −0.149 Unonopsis 0.142 ∗Theobroma 0.290
Combretum −0.121 Clusia 0.145 ∗Iryanthera 0.295
Forsteronia −0.120 Pourouma 0.146 ∗Licania 0.306
Clytostoma −0.097 Brosimum 0.150 ∗Aniba 0.312
Sclerolobium −0.083 Dalbergia 0.164 ∗Eschweilera 0.314
Zanthoxylum −0.083 Cecropia 0.171 ∗Swartzia 0.330
Adenocalymna −0.080 Doliocarpus 0.171 ∗Virola 0.341
Oenocarpus −0.075 Rinorea 0.175 ∗Duguetia 0.344
Cordia −0.057 Tetragastris 0.183 ∗Perebea 0.347
Piper −0.035 Leonia 0.183 ∗Mabea 0.349
Lonchocarpus −0.033 Casearia 0.185 ∗Protium 0.352
Euterpe −0.025 Salacia 0.187 ∗Endlicheria 0.353
Xylopia −0.019 Naucleopsis 0.200 ∗Guatteria 0.358
Celtis −0.018 Trigynaea 0.201 ∗Bauhinia 0.361
Neea 0.028 Sloanea 0.201 ∗Otoba 0.371
Allophylus 0.039 Ficus 0.203 ∗Cyathea 0.378
Siparuna 0.043 Apeiba 0.205 ∗Faramea 0.381
Scheelea 0.053 Astrocaryum 0.208 ∗Inga 0.391
Quararibea 0.053 Carpotroche 0.208 ∗Guarea 0.424
Coccoloba 0.071 Trichilia 0.215 ∗Psychotria 0.454
Mouriri 0.078 Callichlamys 0.216 ∗Sterculia 0.473
Pseudolmedia 0.086 Pouteria 0.219 ∗Machaerium 0.482
Erythroxylum 0.096 Bactris 0.222
Ocotea 0.104 Iriartea 0.227
global model (Woodward and Lomas 2004), and PET (from CRU)
was calculated from temperature, sunshine/radiation, wind and
humidity data using the Penman–Monteith equation. The dataset
created for the analysis represented the average monthly climate
(1961–98). Relative abundance was determined for each woody
plant genus for each plot and only genera that occurred in one or
more plots (91 genera), with over 1% abundance analysed (rep-
resenting 59% of 20,000 recorded stems in these plots). For each
genus, each moisture variable (dry quarter precipitation, PET - p,
SWC) was correlated with the relative abundance of that genus
across all sites and correlation coefficients (Kendall’s t) averaged
to produce a rainfall seasonality ranking. The 91 genera were then
each initially classified as one of two categories: no correlation
with moisture, or correlation with one, two or three moisture vari-
ables, and, of those correlated with the moisture variables, each
genus was then associated with wetter or drier conditions, accord-
ing to the correlation coefficients (Table A1). The results gave
significant correlations for a third of these genera with either wet-
ter (designated as ‘wet-affiliates’) or drier conditions (designated
as ‘dry-affiliates’): two-thirds, with no moisture seasonality affil-
iation, were designated as ‘climate-generalists’. 12% of genera
and 60% of individuals were thus classified – the remainder was
unclassified because of low abundances (see Butt et al. 2008).
In the current analysis, the climate functional groups represent
about 60% of individuals and >20% of genera in the plots used
(the rest were unclassified, ‘unknown’ and were not included in all
subsequent analyses).
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