Geographic variation and environmental correlates of functional trait distributions in palms (Arecaceae) across the New World Bastian Göldel 1 , W. Daniel Kissling 2 and Jens-Christian Svenning 1 1 Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Ny Munkegade 114, DK-8000 Aarhus C, Denmark 2 Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, P.O. Box 94248, 1090 GE Amsterdam, The Netherlands Correspondence: Bastian Göldel; Department of Bioscience, Aarhus University, Ny Munkegade 114, 8000 Aarhus C, Denmark. E-mail: [email protected]Running title: Functional traits in New World palms (Arecaceae) Word count: Manuscript text (including title, abstract, keywords, acknowledgements and references, but excluding legends and tables): 9205 ABSTRACT Functional traits play a key role in driving biodiversity effects on ecosystem functioning. Here, we examine the geographic distributions of three key functional traits in New World palms (Arecaceae), an ecologically important plant group, and their relationships with current climate, soil and glacial-interglacial climate change. We combined palm range maps for the New World (n = 541 species) with data on traits (leaf size, stem height and fruit size) —representing the Leaf-Height-Seed (LHS) plant strategy scheme of Westoby (1998)— to estimate median trait values for palm species assemblages in 110×110-km grid cells. We used the Akaike Information Criterion to identify minimum adequate models and then applied spatial autoregressive models to account for spatial autocorrelation. Seasonality in temperature and precipitation played a major role in explaining geographic variation of all traits. Mean annual temperature and annual precipitation were important for median leaf and fruit size, while glacial-interglacial temperature change and present-day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
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Geographic variation and environmental correlates of functional trait distributions in palms (Arecaceae) across the New World
Bastian Göldel1, W. Daniel Kissling2 and Jens-Christian Svenning1
1Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Ny Munkegade 114, DK-8000 Aarhus C, Denmark2Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, P.O. Box 94248, 1090 GE Amsterdam, The Netherlands
Correspondence: Bastian Göldel; Department of Bioscience, Aarhus University, Ny Munkegade 114, 8000 Aarhus C, Denmark. E-mail: [email protected]
Running title: Functional traits in New World palms (Arecaceae)
Word count: Manuscript text (including title, abstract, keywords, acknowledgements and references, but excluding legends and tables): 9205
ABSTRACT
Functional traits play a key role in driving biodiversity effects on ecosystem functioning. Here, we examine
the geographic distributions of three key functional traits in New World palms (Arecaceae), an ecologically
important plant group, and their relationships with current climate, soil and glacial-interglacial climate
change. We combined palm range maps for the New World (n = 541 species) with data on traits (leaf size,
stem height and fruit size) —representing the Leaf-Height-Seed (LHS) plant strategy scheme of Westoby
(1998)— to estimate median trait values for palm species assemblages in 110×110-km grid cells. We used
the Akaike Information Criterion to identify minimum adequate models and then applied spatial
autoregressive models to account for spatial autocorrelation. Seasonality in temperature and precipitation
played a major role in explaining geographic variation of all traits. Mean annual temperature and annual
precipitation were important for median leaf and fruit size, while glacial-interglacial temperature change and
present-day precipitation of the driest month were especially important for median fruit size, but also for
median stem height. Our results suggest that both current climate (notably seasonality) and glacial-
interglacial temperature change are important drivers for functional trait distributions of palms across the
Interestingly, median fruit size was as the only trait investigated also linked to Quaternary glacial-
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interglacial-climate change, notably strongly positive to temperature change, i.e., with higher values of
median fruit size in areas with relatively high glacial cooling. In other words, the more temperature unstable
areas with stronger temperature oscillations over time showed larger median fruit size than climatically
stable areas (Table 2, Figure 2c). ,. Notably, larger seed mass and fruit size enable seedlings to better
survival hazards (e.g. droughts) while tropical understory palms are especially sensitive to drought (Wright,
1992; Westoby et al., 1996). Greater temperature oscillations might therefore favor palm species and clades
with larger fruit sizes which would result in a positive correlation between assemblage level fruit size and
LGM ANOM TEMP. For instance, African palm species were detected to be majoritarian large fruited, what
could be explained by Cenozoic drying having a strong effect on the trait composition of palm species
assemblages in this region (Kissling et al., 2012b). This finding is also consistent with the positive
correlation between phylogenetic clustering of palm assemblages and LGM ANOM TEMP that was found
for South America where a changing climate and habitat loss throughout the Cenozoic had strong impacts on
the phylogenetic structure of regional species assemblages in the tropics (Kissling et al., 2012b). In the
Neotropics, phylogenetic clustering increases with stronger effects of glacial-interglacial climate oscillations
and shows that specific clades perform better in climatically unstable regions, just as the Cerrado in our
study. Subsequently, many taxa are endemic to certain regions and local areas, such as the dominance of the
subfamily Cocoseae in the Neotropics (Kissling et al., 2012b) or the genus XX within the savanna area of the
Cerrado. Furthermore, phylogenetic clustering and functional trait distributions might also be related to
glacial environmental filtering and postglacial dispersal limitation. For New World palms, postglacial
migrational lag has been invoked to the current distribution and ongoing range dynamics in the rain-forest
understory palm Astrocaryum sciophilum Pulle (Charles-Dominique et al., 2003). These findings are similar
to those for other plants from higher latitudes which are more impacted by glaciations. Notably, postglacial
dispersal limitation has been shown to shape species ranges (Normand et al., 2011) and range filling in trees
across Europe (Nogués-Bravo et al., 2014). Our findings suggest that glacial survival and postglacial range
dynamics in New World palms are probably influenced by the size of their fruits and seeds, reflecting their
role in plant dispersal and stress tolerance. Importantly, large fruits may be subsequently conferred to
relatively low rates of range expansion due to dispersal limitations from these stable, glacial refugia
(Campbell, 1982; Nogués-Bravo et al., 2014). These findings are also consistent with the increasing
evidence that glacial and deeper-time paleoclimate still shape palms species richness of palms in the
Neotropics (Kissling et al., 2012a,b) and Africa (Blach-Overgaard et al., 2013; Rakotoarinivo et al., 2013).
In addition to the drivers discussed above, it has to be mentioned that geographic variation in
median trait values was also related to unknown spatially-structured variables, i.e. for leaf size 41% (R2FULL-
R2PRED), for stem height 62% and for fruit size 60% (Table 2). This unexplained variation could be attributed
to unmeasured environmental factors, dispersal limitation or diversification processes. Notably, we only
detected a relation of paleoclimate to assemblage median fruit size, but not to the other trait variables. Thus,
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the strong unexplained spatial components could also contain unexplained historical processes such as large-
scale dispersal limitation (Svenning & Skov, 2005). Another possible explanation could be that spatially
autocorrelated environmental variables are missing or that patterns of species are consistent with greater
ecological specialization, e.g. adaptations to high temperatures or soil sandiness (Svenning & Skov, 2005).
Furthermore, humans could impact median trait distributions by e.g. introductions and naturalizations of
species to enable them to grow beyond their native ranges (Svenning & Skov, 2005). Another aspect that
could impact functional trait distribution is fire, due to long dry and hot periods in seasonal climates (Grau &
Veblen, 2000; Furley, 2002), but also as caused by humans (e.g. Hoffmann, 1999; Michalski and Peres
2005). Human introduced fires are known to have influenced species richness and composition (Hoffmann,
1999), especially in southern Amazonia and the Cerrado (Ratter et al. 1997; Pennington et al., 2000;
Michalski and Peres, 2005). Not only species diversity might have been impacted by fire, but also
adaptations in ecology and functional traits, such as a thick, corky bark and scleromorphic leaves
(Pennington et al., 2000; Furley, 2002). Furthermore, fire frequency might determine whether a species will
decline towards extinction or become abundant under a particular fire regime, causing shifts in the plants’
size and have large effects on the physical structure of the vegetation as it was shwon for the Cerrado
(Hoffmann, 1999). Taller and thicker stems might be an advantage of robustness against (human induced)
fires while smaller species and individuals might not be able to handle fire disturbance and go extinct
(Williams et al., 1999). For instance, along the Xingu river in eastern Amazonian Brazil, an area with high
species diversity, human induced fires changed species composition towards extensive stands of tall species,
namely the babacu palm Attalea speciosa Mart. which shows several adaptations to fire, such as a tall stem
and large, thick endocarped fruits (Smith, 2015).
Overall, we used Westoby’s (1998) LHS plant strategy scheme to explain distribution of three
key functional traits by environmental correlates. We chose the trait variables leaf size, stem height and fruit
size as they were proposed in his study to capture the main trait axes of a plant species responses to different
factors such as e.g. competition and disturbance, and being supposed to be applied for every species.
Assemblage medians for palm functional traits in the New World were strongly related to current climate
and in particular to seasonality, with much weaker links to past climate change and soil. Theoretically, a
weak or missing soil effect on functional trait distributions in the New World could be due to the coarse
grain size of our analyses. Notably, Eiserhardt et al. (2011) reviewed that palm diversity can be influenced
by soil chemistry on a continental scale and palm community composition on a regional to local scale.
Notably, we only detected a relation of paleoclimate to assemblage median fruit size, but not to the other trait
variables. This suggests that distributions of assemblage trait medians like stem height and leaf size, are not
maintained over a million year time periods although unexplained historical components as well as co-
variation between paleo- and current climates could contribute, as explained above. Particularly, palms are
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known to be strong indicators for current temperature and precipitation (Dransfield et al., 2008). Therefore, a
fast shift in climatic conditions under future climate change could impact palm species distributions (Blach-
Overgaard et al., 2010) and along with it a shift in functional trait distributions (Diaz & Cabido, 1997). It is
likely that towards the end of the century the New World is undergoing an increase in mean annual
temperature and a decrease in mean annual precipitation over most areas, including a more seasonal climate
(especially in regard to precipitation), e.g. in the Andes and Eastern Amazonia (Magrin et al., 2014). This
could be problematic for many palm species because most are sensitive to drought and concentrated in the
wettest parts of the New World tropics (e.g., many understory palm species). Large-stemmed generalist palm
species that are widespread and common in tropical seasonal areas are expected to have an advantage under
drier and warmer conditions and may be able to migrate into new areas, if they can disperse fast enough to
track changing climates. In contrast, especially understory tree species can be highly drought-sensitive and
will suffer from increasing drought, as already documented in tropical moist forests in central Panama
(Condit, Hubbell & Foster, 1996). Furthermore, species with large fruits, which often have advantages in
seedling survival (Lloret et al., 1999), might be able to deal better with dry and more seasonal conditions.
Nevertheless, a considerable movement of large-fruited species with increasing seasonality seems to be
unlikely at a continental scale as our results show that present median fruit size distribution is still related to
Quaternary climate change, likely due to postglacial dispersal limitation, which will be exacerbated by
disperser loss due to current defaunation, especially of large mammal species (Galetti et al., 2006; Beaune et
al., 2013). Altogether, given the strong climate-trait relationships documented in this study we expect that
future climate change has a strong impact on the functional composition of palm communities and thus on
ecosystem dynamics in palm-inhabited parts of the New World, as palms are a keystone family with high
ecological importance here (Dransfield et al., 2008), notably as habitat and food resource for mammals and
birds (Zona & Henderson, 1989; Galetti et al., 2006).
ACKNOWLEDGEMENTS
Our research was supported by the European Research Council (grant ERC-2012-StG-310886-HISTFUNC
to J.-C.S.). W.D.K. acknowledges support from a University of Amsterdam (UvA) starting grant. We also
thank Aarhus University and several people for feedback and support to this study, notably Alejandro
Ordonez, Peder K. Bøcher, Wolf L. Eiserhardt and Henrik Balslev.
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Figure 1: Species richness (a) and community-level median values of (b) leaf size (in m), (c) maximum
stem height (in m) and (d) fruit size (in cm3) for palm assemblages across the New World. Quantile
classification is shown across a grid with 110×110 km cell size (equivalent to c. 1°×1° near the equator) and
a WGS 1984 projection.
Figure 2: Partial residual plots illustrating the relation of three community-level traits (a: leaf size, b: stem
height, and c: fruit size) with their most important environmental predictor variable (compare standardized
coefficients in Table 1). Partial residuals represent the relationship between a response and a predictor
variable when all other predictor variables in the model are statistically controlled for. Specifically, these
partial residual plots are plots of r + b × Environment versus Environment (x-axis), where r is the ordinary
residuals form the multiple-predictor model and b is the regression coefficient estimate for Environment
from the same multiple-predictor model. Abbreviations of predictor variables are explained in Table 1.
Figure 1:
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Figure 2:
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Table 1: Predictor variables to explain the geographic variation and environmental correlates of functional
trait distributions in palms across the New World
Abbreviation Predictor variables (units) Data source
Current climatePC-ANNU PCA axis mainly representing
annual precipitation (mm year-1), precipitation of the driest month (mm) and mean annual temperature (°C × 10)
Worldclim dataset (Hijmans et al., 2005)
PC-SEAS PCA axis mainly representing seasonality of temperature (standard deviation of monthly means, °C × 10) and precipitation (coefficient of variation of monthly, mm)
Worldclim dataset (Hijmans et al., 2005)
PC-DRYM PCA axis mainly representing precipitation of the driest month (mm)
Worldclim dataset (Hijmans et al., 2005)
SoilpH pH in topsoil (-log(H+)) Harmonized World Soil
Database (FAO et al., 2012)
sand% Sand fraction in topsoil (%) Harmonized World Soil Database (FAO et al., 2012)
CEC
Quaternary climate change
Cation exchange capacity in topsoil (cmol/kg)
Harmonized World Soil Database (FAO et al., 2012)
LGM ANOM TEMP Anomaly in TEMP between Last Glacial Maximum andpresent (K, originally in °C × 10)
Calculated in ArcGIS using the variables LGM TEMP andTEMP Worldclim dataset (Hijmans et al., 2005)
LGM ANOM PREC Anomaly in annual precipitation between Last GlacialMaximum and present (mm year1)
Calculated in ArcGIS using the variables LGM PREC andPREC from Worldclim dataset (Hijmans et al., 2005)
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Table 2: Multiple predictor models (ordinary least squares: OLS) and multiple predictor spatial autoregressive (SAR) models were used to explain the geographic variation of community-level functional traits (mean leaf size, mean stem height, and mean fruit size) in palm assemblages across the New World. Explanatory variables include current climate (PC-ANNU, PC-SEAS, PC-DRYM), soil (pH, sand%, CEC) and Quaternary climate change (LGM ANOM TEMP, LGM ANOM PREC). For each functional trait variable, a minimum adequate model was selected with the Akaike Information Criterion (AIC) based on a non-spatial model with all explanatory variables (OLS). This model was then fitted with a SAR model. The response variables leaf size and fruit size and the predictor variables CEC and LGM ANOM TEMP were log10-transformed. For the response variable leaf size, all included predictor variables were selected in the most parsimonious model whereas for stem height the predictors pH, sand % and LGM ANOM PREC and for fruit size the predictor pH were not selected (indicated by “--”). Sample sizes are 1498 grid cells of 110×110 km resolution in all analyses.
Abbreviations of predictor variables are explained in Table 1. For each model, the regression coefficients,
the explained variance of the OLS (R2OLS) and SAR models (R2
FULL,R2PRED), the AIC, Moran’s I, and the P-
value of Moran’s I are given. ***P < 0.001; **P < 0.01; *P < 0.05; n.s. not significant; ‘--’ not selected for
the Minimum Adequate Model.
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Appendix
Figure S1: Community-level median values for non-acaulescent palms of (a) leaf size (in m), (b) maximum
stem height (in m) and (c) fruit size (in cm3), and standard deviations of median leaf size (d), stem height (e)
and fruit size (f) for palm assemblages across the New World. Quantile classification is shown across a grid
with 110×110 km cell size (equivalent to c. 1°×1° near the equator) and a WGS 1984 projection.
Figure S2: Maps show the residuals of the OLS for our assemblage median trait distributions of leaf size (a),
stem height (b) and fruit size (c), and for the SAR models of leaf size (d), stem height (e) and fruit size (f).
The diameter of each dot indicates the amount of spatial autocorrelation at this particular area, while the
colors illustrate positive (black) and negative (grey) autocorrelation, respectively.
Figure S3: Moran’s I correlograms of the residuals of the model fit of the raw data (white circle), the OLS
model (grey circle) and the spatial autoregressive model (black circle) separately for the three trait variables
median leaf size (a), median stem height (b) and median fruit size (c).
Figure S4: Histograms for the three different trait variables illustrate the frequency and distribution of the
trait data values for leaf size (a), stem height (b) and fruit size (c) over the whole dataset. Data for traits leaf
size and fruit size are log10-transformed.
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Figure S2:
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(a) Residuals median leaf size
geographical x-coordinates
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(b) Residuals median stem height
geographical x-coordinates
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(c) Residuals median fruit size
geographical x-coordinates
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(d) Residuals median leaf size
geographical x-coordinates
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(e) Residuals median stem height
geographical x-coordinates
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(f) Residuals median fruit size
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Figure S3:
Figure S4:
Table S1: Principal component (PC) analysis for 19 current climate variables of the worldclim
database. Entries are eigenvalues, percentage of variance for each axis and cumulative across all,
and the correlation between the PC axes and the most important climate variables.
PC-ANNU PC-SEAS PC-DRYM
PCA result
Eigenvalue 3.001 1.895 1.640
Percent of variance 49.12 22.85 11.75
Cumulative percent of variance 46.49 69.34 81.09
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Correlation coefficient
Mean annual temperature 0.803 0.352 0.088
Temperature seasonality 0.109 0.795 -0.322
Mean annual precipitation 0.842 -0.412 -0.096
Precipitation of the wettest quarter 0.621 -0.169 0.229
Precipitation seasonality -0.205 0.693 -0.149
Precipitation of the driest month 0.379 -0.128 -0.542
Table S2: All genera including numbers of species per genus, number of estimated values per trait and genus and mean, median and standard deviation for all genera.
Table S3: All species within the dataset (n=541) and attendant references which had been used to fulfill the missing trait values of Henderson et al. (1995).
SpecName References
Acoelorrhaphe wrightii AAU Herbarium; Henderson et al. 1995