Ecological Archives C006-056-A1

Marijn Bauters, Evy Ampoorter, Dries Huygens, Elizabeth Kearsley, Thales De Haulleville, Giacomo Sellan, Hans Verbeeck, Pascal Boeckx, and Kris Verheyen. 2015. Functional identity explains carbon sequestration in a 77-year-old experimental tropical plantation. Ecosphere 6:198. http://dx.doi.org/10.1890/es15-00342.1

Appendix A. A list of the abbreviations of the full scientific names of planted species, a list of H:DBH relations, and compositional parameters and planted species of the different plots.

Table A1. A list of the abbreviations of the full scientific names of all planted species in the plantation, along with the full and correct scientific name, family and subfamily. Species were identified by the local botanists of the INERA (Institut National pour l’Etude et la Recherche Agronomique Yangambi). There was no consensus about the species-level identification of one planted species of the Phyllanthus genus.

Abbreviation

Full scientific name

Family

Subfamily

A.c.

Autranella congolensis (De Wild.) A. Chev.

Sapotaceae

 

A.n.

Antrocaryon nannanii De Wild.

Anacardiaceae

 

B.w.

Blighia welwitschii (Hiern) Radlk.

Sapindaceae

 

C.a.

Chrysophyllum africanum A. DC.

Sapotaceae

 

C.p.

Carapa procera DC.

Meliaceae

 

D.l.

Drypetes likwa J. Leonard

Euphorbiaceae

 

E.a.

Entandrophragma angolense (Welw. ex C. DC.) C. DC.

Meliaceae

 

E.c.

Entandrophragma cylindricum (Sprague) Sprague

Meliaceae

 

G.c.

Guarea cedrata (A. Chev.) Pellegr.

Meliaceae

 

K.a.

Khaya anthotheca (Welw.) C.DC.

Meliaceae

 

L.t.

Lovoa trichilioides Harms

Meliaceae

 

M.a.

Mammea africana Sabine

Clusiaceae

 

M.e.

Milicia excelsa (Welw.) C.C. Berg

Moraceae

 

P.e.

Pericopsis elata (Harms) Meeuwen

Fabaceae

Papilionoideae

P.m.

Pentaclethra macrophylla Benth.

Fabaceae

Mimosoideae

P.o.

Panda oleosa Pierre

Pandaceae

 

P.s.

Pterocarpus soyauxii Taub.

Fabaceae

Papilionoideae

P.sp.

Phyllanthus species

Phyllanthaceae

 

P.t.

Pachyelasma tessmannii (Harms) Harms

Fabaceae

Caesalpinioideae

S.g.

Strombosia grandifolia Hook. f.

Olacaceae

 

S.t.

Strombosiopsis tetrandra Engl.

Olacaceae

 

T.a.

Treculia africana Decne.

Moraceae

 

Z.g.

Zanthoxylum gilletii (De Wild.) P.G. Waterman

Rutaceae

 

 

Table A2. List of H:DBH relations, and additionally their types and references, that were fitted to the tree heights and diameters, measured in the field. Per plot, the best fit was used to estimate the other tree heights, based on their diameter. H is tree height, DBH stands for diameter breast height and a, b, and c are the equation’s variable parameters. The last column indicates which formula was selected for each plot, based on the best fit.

H:D relation

Type

Reference

Plot

H=1.3 + a x (1 - exp(-b x DBHc)

Weibull

Huang, Titus, and Wiens 1992

22

H=a x (1 - exp(-b x DBHc)

Weibull

Scaranello et al. 2012

 

H=1.3 + a x (1 - exp(-b x DBH)

Chapman-Richards

Huang, Titus, and Wiens 1992

 

H=a x (1 - exp(-b x DBH))c

Chapman-Richards

Scaranello et al. 2012

 

H=exp(a + b x log(DBH))

/

Brown, Gillespie, and Lugo 1989

 

H=1.3 + a x (1 + b x exp(-c x DBH)) -1

Logistic

Scaranello et al. 2012

2, 7, 9, 13, 25

H=1.3 + a x (1 + b-1 x DBH-c) -1

Modified logistic

Huang, Titus, and Wiens 1992

3

H=1.3 + exp(a + b x (DBH + 1) -1)

Exponential

Scaranello et al. 2012

5, 12, 14, 21, 24

H=1.3 + a x exp(b x (DBH + c) -1)

Exponential

Huang, Titus, and Wiens 1992

 

H=a - b x exp(-c x DBH)

Exponential

Feldpausch et al. 2012

 

H=a x (1 - exp(-b x DBH))

Exponential

Banin et al. 2012

1, 18

H=1.3 + a x DBH x (b + DBH) -1

Hyperbolic

Scaranello et al. 2012

4, 10, 16, 19, 23, 26, 27, 28, 29

H=a x exp(-b x exp(-c x DBH)

Gompertz

Scaranello et al. 2012

 

H=1.3 + a x DBHb

Power

Scaranello et al. 2012

6, 8, 15, 17, 20

H=a x DBHb

Power

Scaranello et al. 2012

11

 

Table A3. Compositional parameters and planted species of the different plots, calculated from the different subplots. AGC is above ground carbon in the woody biomass of the trees, BA is basal area and WD wood density. All values represent plot-level averages and standard deviations are calculated with the averages of the subplots within the plot, without taking into account the within-subplot variation. For wood density, we used data from the same species that were measured in the surrounding natural forest (Kearsley et al. 2013). The effective species richness represents the number of occurring tree species (including the spontaneous ingrowth).). BApl is the ratio of basal area of the planted species to the total stand basal area in the plot (including spontaneous ingrowth). Effective Simpson’s diversity is calculated on the present trees. All species’ abbreviations are explained in Table A1.

Plot

AGC
(Mg C ha-1)

Stem Density
(ha-1)

BA
(m² ha-1)

WD
(g cm-3)

Effective species
richness (#)

Effective
Simpson diversity

BApl

Planted Species 1

Planted Species 2

1

294.49 ±63.01

702.8 ±113.5

45.06 ±8.28

0.65 ±.01

7.22 ±0.83

0.75 ±.04

0.78 ±.09

P.e.

B.w.

2

200.08 ±61.91

336.1 ±96.1

32.02 ±10.16

0.63 ±.02

5.89 ±2.42

0.70 ±.09

0.61 ±.20

P.e.

 

3

218.01 ±72.70

544.4 ±87.3

37.34 ±9.74

0.57 ±.02

10.33 ±1.80

0.81 ±.05

0.74 ±.14

P.e.

G.c.

4

277.53 ±116.10

397.2 ±61.8

41.56 ±14.77

0.69 ±.02

7.67 ±1.87

0.80 ±.06

0.79 ±.10

P.m.

Z.g.

5

319.11 ±83.03

531.3 ±37.5

47.33 ±10.76

0.65 ±.01

6.25 ±0.50

0.74 ±.07

0.79 ±.18

P.e.

P.o.

6

338.77 ±126.70

619.4 ±137.4

49.81 ±15.97

0.69 ±.03

8.67 ±2.83

0.70 ±.13

0.71 ±.15

A.c.

 

7

173.51 ±66.20

586.1 ±98.5

36.69 ±10.01

0.55 ±.03

12.44 ±2.51

0.87 ±.03

0.42 ±.14

P.s.

T.a.

8

152.09 ±54.32

433.3 ±91.0

32.42 ±8.57

0.56 ±.03

10.89 ±2.26

0.87 ±.04

0.28 ±.22

P.s.

 

9

171.78 ±43.42

616.7 ±101.6

34.63 ±5.61

0.54 ±.01

10.67 ±2.45

0.80 ±.07

0.68 ±.18

E.c.

A.n.

10

121.85 ±62.75

411.1 ±79.2

21.78 ±7.90

0.63 ±.04

8.56 ±0.73

0.80 ±.06

0.36 ±.15

P.m.

C.p.

11

100.99 ±54.43

375.0 ±136.4

22.60 ±8.79

0.54 ±.03

8.56 ±2.19

0.84 ±.04

0.32 ±.16

M.e.

 

12

239.25 ±59.47

662.5 ±59.5

42.22 ±8.48

0.56 ±.01

7.00 ±2.45

0.46 ±.17

0.78 ±.15

G.c.

 

13

243.37 ±42.73

362.5 ±92.4

34.39 ±4.49

0.63 ±.04

6.75 ±2.06

0.72 ±.17

0.62 ±.42

P.e.

 

14

602.46 ±84.29

731.3 ±82.6

70.23 ±9.74

0.74 ±.00

3.50 ±0.58

0.54 ±.02

0.99 ±.00

A.c.

D.l.

15

228.06 ±143.85

350.0 ±35.4

36.63 ±17.06

0.54 ±.06

4.25 ±2.87

0.38 ±.30

0.60 ±.44

P.o.

 

16

167.61 ±81.97

743.8 ±428.8

33.03 ±14.64

0.51 ±.05

12.50 ±3.87

0.80 ±.06

0.16 ±.10

E.c.

 

17

114.53 ±55.48

237.5 ±85.4

18.20 ±6.43

0.72 ±.06

4.25 ±1.26

0.58 ±.09

0.66 ±.21

P.m.

 

18

102.32 ±80.85

280.6 ±168.1

21.38 ±14.10

0.57 ±.03

7.56 ±3.43

0.80 ±.11

0.18 ±.14

M.e.

P.sp.

19

150.25 ±47.82

306.3 ±55.4

26.67 ±7.15

0.61 ±.00

2.50 ±1.29

0.20 ±.17

0.98 ±.02

S.t.

 

20

258.40 ±20.50

418.8 ±62.5

40.71 ±3.17

0.65 ±.01

3.00 ±1.41

0.55 ±.07

0.98 ±.03

P.e.

S.t.

21

95.85 ±70.07

494.4 ±157.5

23.43 ±12.26

0.52 ±.03

9.89 ±4.01

0.79 ±.11

0.41 ±.27

L.t.

 

22

106.94 ±38.10

394.4 ±91.7

23.68 ±7.99

0.52 ±.02

8.89 ±1.96

0.82 ±.05

0.29 ±.18

L.t.

K.a.

23

144.45 ±64.91

441.7 ±106.8

31.20 ±9.23

0.50 ±.03

8.89 ±2.47

0.82 ±.06

0.45 ±.23

G.c.

L.t.

24

299.49 ±138.66

377.8 ±108.6

48.30 ±20.45

0.62 ±.01

6.00 ±1.66

0.73 ±.05

0.78 ±.10

P.t.

 

25

141.24 ±52.70

558.3 ±114.6

31.66 ±10.86

0.51 ±.03

12.67 ±2.50

0.89 ±.02

0.30 ±.19

E.c.

E.a.

26

130.26 ±105.26

587.5 ±94.6

28.94 ±12.62

0.53 ±.07

9.75 ±0.96

0.79 ±.03

0.22 ±.08

E.a.

 

27

269.35 ±84.00

637.5 ±425.5

43.13 ±11.51

0.62 ±.04

7.50 ±3.11

0.70 ±.08

0.31 ±.36

P.t.

C.a.

28

255.84 ±46.01

356.3 ±94.4

38.74 ±6.05

0.60 ±.00

5.00 ±0.82

0.51 ±.07

0.95 ±.02

M.a.

 

29

255.43 ±166.71

500.0 ±143.6

44.05 ±24.64

0.57 ±.02

10.22 ±3.15

0.83 ±.06

0.52 ±.33

M.a.

S.g.

 

Literature cited

Banin, L., et al. 2012. What controls tropical forest architecture? Testing environmental, structural and floristic drivers. Global Ecology and Biogeography 21(12):1179–1190.

Brown, S., A. J. R. Gillespie, and A. E. Lugo. 1989. Biomass Estimation Methods for Tropical Forests with Applications to Forest Inventory Data. Forest Science, 35(4):881–902.

Feldpausch, T. R., et al. 2012. Tree height integrated into pantropical forest biomass estimates. Biogeosciences, 9(8):3381–3403.

Huang, S., S. J. Titus, and D. P. Wiens. 1992. Comparison of nonlinear height-diameter functions for major Alberta tree species. Canadian Journal of Forest Research, 22.

Kearsley, E., et al. 2013. Conventional tree height-diameter relationships significantly overestimate aboveground carbon stocks in the Central Congo Basin. Nature Communications 4:2269.

Scaranello, M. a., L. F. Alves, S. A. Vieira, and P. B. De. Camargo. 2012. Height-diameter relationships of tropical Atlantic moist forest trees in southeastern. Scientia Agricola, 69(February):26–37.


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