Supplemental Material
Supplemental methods
For all species included in the study, leaf tissue samples were collected from 1-3
individuals, dried in silica gel and sent to the Smithsonian Institution’s
5
Laboratories for Analytical Biology for sequencing and phylogenetic
reconstruction. Methods of DNA extraction, PCR and sequencing are reported in
detail in Fazekas et al. (2012), and are summarized here. We disrupted leaf tissue
that had been sorted into 96 well plates, and used glass fiber filtration to extract
and purify DNA. PCR for three DNA barcode markers, rbcL, matK and psbA-
10
trnH, was conducted on each sample, and sequencing was done via the Sanger
Sequencing protocol. Raw sequence data for each sample was assembled into a
contig (by marker), edited and then verified for taxonomy by comparison with
internally validated reference database using the program Geneious. Sequence
data for each of the three markers were aligned separately, following Erickson &
15
Driskell (2012), and then the three aligned markers were concatenated into a 3
gene matrix for use in phylogenetic reconstruction. We submitted the data to the
CIPRES portal (Miller et al. 2010) where we used GARLI (Zwickl 2008), a
maximum likelihood phylogenetic reconstruction algorithm. We initiated 100
separate runs to evaluate variation in tree topology, and used the best scoring
20
maximum likelihood molecular phylogeny for subsequent analysis. For each of
the 100 separate runs, we also used a phylogenetic constraint tree (see Kress et al.
1
2010) derived from the supertree web portal Phylomatic (Webb & Donoghue
2005), which uses the APGIII (The Angiosperm Phylogeny Group 2009) family
level land plant phylogeny to generate a phylogeny that can be used to enforce
25
topological relationships. We used the constraint to enforce relationships among
orders, but allowed the molecular data to infer lower-level topology and branch
lengths throughout the phylogeny. The best scoring molecular phylogeny then
was rooted and transformed into a dated chronogram using the program PATHd8
(Britton et al. 2007), and a set of dates derived from (Magallón & Castillo 2009)
30
for selected plant orders.
References cited:
35
40
45
50
1.
Britton, T., Anderson, C.L., Jacquet, D., Lundqvist, S. & Bremer, K. (2007).
Estimating Divergence Times in Large Phylogenetic Trees. Syst. Biol., 56, 741–
752.
2.
Erickson, D. & Driskell, A. (2012). Construction and Analysis of Phylogenetic
Trees Using DNA Barcode Data. In: DNA Barcodes, Methods in Molecular
Biology (eds. Kress, W.J. & Erickson, D.L.). Humana Press, pp. 395–408.
3.
Fazekas, A.J., Kuzmina, M.L., Newmaster, S.G. & Hollingsworth, P.M. (2012).
DNA Barcoding Methods for Land Plants. In: DNA Barcodes, Methods in
Molecular Biology. pp. 223–252.
4.
Kress, W.J., Erickson, D.L., Swenson, N.G., Thompson, J., Uriarte, M. &
Zimmerman, J.K. (2010). Advances in the Use of DNA Barcodes to Build a
2
Community Phylogeny for Tropical Trees in a Puerto Rican Forest Dynamics
Plot. PLoS ONE, 5, e15409.
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65
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5.
Magallón, S. & Castillo, A. (2009). Angiosperm diversification through time. Am.
J. Bot., 96, 349–365.
6.
Miller, M.A., Pfeiffer, W. & Schwartz, T. (2010). Creating the CIPRES Science
Gateway for inference of large phylogenetic trees. In: Gatew. Comput. Environ.
Workshop GCE 2010. IEEE, pp. 1–8.
7.
The Angiosperm Phylogeny Group. (2009). An update of the Angiosperm
Phylogeny Group classification for the orders and families of flowering plants:
APG III. Bot. J. Linn. Soc., 161, 105–121.
8.
Webb, C.O. & Donoghue, M.J. (2005). Phylomatic: tree assembly for applied
phylogenetics. Mol. Ecol. Notes, 5, 181–183.
9.
Zwickl, D.J. (2008). Genetic algorithm approaches for the phylogenetic analysis
of large biological sequence datasets under the maximum likelihood criterion.
80
3
Table S1. Information on eight 1-ha study plots in northeastern Costa Rica. This
table is modified from Table 1 of Chazdon et al. (2010) and Table S1 of Lasky et
al. (2014).
Plot name
(abbreviation)
El Bejuco
(EB)
Juan Enriquez
(JE)
Lindero Sur
(LSUR)
Tirimbina
(TIR)
Lindero El
Peje
secondary
(LEPS)
Cuatro Rios
(CR)
Year
abandoned
1995
1995
1985
1982
1977
1972
Year
sampling
initiated
2005
2005
1997
1997
1997
1997
Location
Chilamate
Chilamate
La Selva
La Virgen
La Selva
La Virgen
Latitude
10.46°N
10.46°N
10.41°N
10.40°N
10.43°N
10.39°N
Longitude
Surrounding
landscape
84.06°W
Pasture, oldgrowth and
secondgrowth
forest
84.07°W
Pasture, oldgrowth and
secondgrowth
forest
Old-growth
and secondgrowth
forest
84.03°W
Pasture,
plantations,
and secondgrowth
forest
84.11°W
Old-growth
and secondgrowth
forest
84.03°W
Pasture,
secondgrowth and
old-growth
forest
84.13°W
4
Lindero El
Peje primary
(LEPP)
Selva Verde
(SV)
Old-growth
Old-growth
2005
2005
La Selva
Chilamate
10.42°N
10.44°N
Old-growth
forest
84.04°W
Pasture,
secondgrowth and
old-growth
forest
84.07°W
85
5
90
Table S2. Estimated variance of random effects at the individual yearly quadrat
observation level (“Obs”, εit in eqn. 6 of the main text), at the year level (“Year”,
vt in eqn. 6 of the main text), and at the quadrat level (“Quadrat”, ui in eqn. 6 of
the main text).
Successional Diversity
stage
metric
Total
Δbiomass
Obs.
Growth
Δbiomass
Year
Quadrat
Obs.
Mortality
Δbiomass
Year
Quadrat
Obs.
Year
Quadrat
Early
TD
0.168
0.078
0.287
0.099
0.041
0.232
0.224
0.083
0.239
Early
PD
0.168
0.081
0.290
0.100
0.040
0.229
0.224
0.084
0.242
Early
FDLDMC
0.167
0.083
0.288
0.100
0.038
0.232
0.225
0.087
0.240
Early
FDSLA
0.166
0.081
0.290
0.099
0.039
0.230
0.223
0.084
0.241
Early
FDWSG
0.164
0.084
0.281
0.099
0.037
0.222
0.223
0.087
0.241
Early
FDAll traits
0.164
0.076
0.276
0.099
0.035
0.217
0.222
0.085
0.238
Mid
TD
0.124
0.027
0.201
0.049
0.021
0.131
0.183
0.031
0.242
Mid
PD
0.123
0.027
0.198
0.048
0.020
0.130
0.185
0.029
0.234
Mid
FDLDMC
0.123
0.026
0.199
0.048
0.019
0.130
0.184
0.031
0.236
Mid
FDSLA
0.122
0.027
0.203
0.048
0.021
0.131
0.184
0.031
0.240
Mid
FDWSG
0.124
0.027
0.200
0.049
0.020
0.130
0.185
0.032
0.235
Mid
FDAll traits
0.124
0.027
0.202
0.049
0.020
0.129
0.184
0.033
0.234
Old-growth
TD
0.117
0.103
0.223
0.027
0.048
0.108
0.138
0.052
0.222
Old-growth
PD
0.120
0.049
0.225
0.028
0.054
0.108
0.140
0.069
0.225
Old-growth
FDLDMC
0.120
0.052
0.224
0.028
0.041
0.108
0.139
0.102
0.222
Old-growth
FDSLA
0.119
0.058
0.224
0.028
0.040
0.109
0.139
0.074
0.224
Old-growth
FDWSG
0.121
0.053
0.228
0.028
0.062
0.108
0.141
0.052
0.225
Old-growth
FDAll traits
0.121
0.049
0.228
0.028
0.040
0.108
0.141
0.068
0.226
6
95
100
Table S3. Estimated coefficients of relating stand age category (covariate) to
quadrat diversity metrics (response variables). Plots were categorized into three
stand age categories and category was tested as an ordinal covariate effect on
diversity (covariate values: early successional = 1, mid-successional = 2, old
growth = 3). Here we show 95% credible intervals (CIs) of stand age category
effects. All values are in SD(diversity)/age category. Significant covariates are
shown in bold.
Diversity metric
95% CI of stand age category
effect
Species richness
Phylogenetic diversity
FDLDMC
FDSLA
FDWSG
FDAll traits
0.16, 0.23
0.20, 0.27
0.05, 0.12
0.11, 0.19
0.02, 0.09
-0.04, 0.04
7
105
Table S4. Standardized regression coefficients (with 95% credibility intervals)
giving the effect of different diversity metrics on Δbiomass. Significant effects are
highlighted in bold. Total Δbiomass and Δbiomass due to growth are in units of
log(Δbiomass) SD(diversity)-1. Δbiomass due to mortality is in units of
asin(Δbiomass 0.5) SD(diversity)-1.
Slopes and 95% CIs of diversity effect on ΔAGB
Successional
stage
Diversity
metric
Total
Δbiomass
Slope
2.50%
97.50%
Growth
Δbiomass
Slope
2.50%
97.50%
Mortality
Δbiomass
Slope
2.50%
97.50%
Early
Early
Early
Early
Early
Early
TD
PD
FDLDMC
FDSLA
FDWSG
FDAll traits
0.0275
0.0399
0.0471
0.0601
0.0272
0.0283
0.0113
0.0237
0.0327
0.0461
0.0077
0.0155
0.0434
0.0558
0.0612
0.0737
0.0430
0.0421
0.0218
0.0152
0.0288
0.0274
0.0245
0.0314
0.0111
0.0062
0.0188
0.0187
0.0125
0.0237
0.0317
0.0235
0.0389
0.0372
0.0370
0.0401
0.0226
0.0311
0.0253
0.0492
0.0199
-0.0426
0.0393
0.0474
0.0428
0.0652
0.0350
-0.0274
0.0036
0.0141
0.0076
0.0338
0.0033
-0.0594
Mid
Mid
Mid
Mid
Mid
Mid
TD
PD
FDLDMC
FDSLA
FDWSG
FDAll traits
-0.0298
-0.0053
-0.0155
-0.0245
-0.0078
-0.0136
-0.0439
-0.0177
-0.0281
-0.0370
-0.0214
-0.0293
-0.0161
0.0066
-0.0011
-0.0119
0.0048
0.0021
0.0132
0.0108
0.0065
0.0076
0.0103
0.0164
0.0066
0.0050
0.0011
0.0026
0.0049
0.0102
0.0202
0.0159
0.0116
0.0127
0.0156
0.0226
-0.0718
-0.0243
-0.0272
-0.0315
-0.0296
-0.0622
-0.0528
-0.0066
-0.0068
-0.0143
-0.0119
-0.0444
-0.0903
-0.0422
-0.0472
-0.0494
-0.0492
-0.0837
Old-growth
Old-growth
Old-growth
Old-growth
Old-growth
Old-growth
TD
PD
FDLDMC
FDSLA
FDWSG
FDAll traits
-0.0114
-0.0045
0.0077
0.0019
0.0026
-0.0143
-0.0450
-0.0320
-0.0189
-0.0261
-0.0291
-0.0446
0.0167
0.0276
0.0346
0.0380
0.0381
0.0144
-0.0020
0.0005
0.0043
-0.0045
0.0077
-0.0109
-0.0147
-0.0083
-0.0052
-0.0166
-0.0024
-0.0218
0.0101
0.0111
0.0126
0.0055
0.0183
0.0000
-0.0078
-0.0002
-0.0236
0.0092
-0.0031
0.0047
0.0313
0.0343
0.0071
0.0367
0.0318
0.0384
-0.0375
-0.0310
-0.0515
-0.0197
-0.0391
-0.0316
110
8
Figure S1. Molecular barcode phylogeny of species in our study, used to
calculate community phylogenetic diversity. Variation in leaf dry matter content
(LDMC) is represented from blue (low LDMC) to red (high LDMC). Species
115
lacking LDMC data are shown in black. Palms in our plots are shown in green but
were excluded from analyses because of their distinct DBH-biomass allometry.
Species not found in our plots were pruned from the tree.
9
Ardisia standleyana
Pouteria reticulata
Pouteria
campechiana
Pouteria tor
Chry phyl ta
lum venezu
Pouteso
ria
elanense
Pou
durla
C teraria calistonpdihi
Eslecth
starice ylla
Lecyhweilceora
Cocc this am longirnasis
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chis
p
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N eea loba tuela
r ck h
Neeeea laamplifo
li
e
e
H
a
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t
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ii
Mieniste delic viren
r
a
s
CMel qua ia c tula
Iriar yoisosmratia gouncinn
S
o
B o r t e p d ia n a
P a cr a hila on en
E h ctr ate de w nel sis
W uteolidis ga exltoid arsclsmith
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RPerrestfia r e ptachipaerhiz
OOcohodseaoeaegiarecays ps a
co t os a d
tor ulc
teea te me ec
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uc nu o na s
ox a da
p
yl
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ku
nt
hi
an
a
ifera
Ardisia fimbrillthum
man m
Aspidospermaades
nu
spruceace
Aspidosperm
rpuras ns
Rauvolfia pu na arboreas
aemonatapanameifnlosira
Taberncm
elle his parv cana
La im
rr
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Ch eanipa amm
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G queria latifolieaa
Poso queria occinnsis
Poso iczia ncameensisis
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Bor tria gu alid nsita
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Psyalicouchotr a hootria oopiansa
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x f e
y
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yc tr m ib d l r
Psychomeaarv alliobicwoyeaia s i
u
p
Ps Faraea rdiardiaia dcopnthper
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ra C CCo or ndar ysacoo
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Mara
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h e
nthe Hir tllea triaynlluma
s pa lla le dra
nam ms
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H
ir llansisii
Lica Hiair tella te
s
ediap
hypom
Couen
p
Dystovom ia polyalenuca
paniculadra
Symphonita
ia globulife ta
Garci
intermedra
Calophyllunia
ia
m brasilien
se
Marila pluricostata
Vismia macrophylla
Hi
na
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rn a
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1 sh ris os
sp ar t ulambr e s
ea a h insa u ntlairen sis
t
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co te a dr isa ev
O cocotetan mlaet ique a
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Virompsoneura m
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hnyi
Virola koscifera
seb
Virola colonen
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Piper
Hedyosmum scaberrimum
Balizia elegans
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Inga venusta
Inga le
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10