Table 2.
Multi-scale, basal-area-weighted mean community wood density for old-growth forests across the lowland tropical forest biome. Data assembled from the peer-reviewed ecological literature, from scales of 100 to 1010 hectares. All values are basal-area-weighted and computed for each plot accounting for taxon-specific wood densitya. Thus, basal-area-weighted community-level WD of each plot was estimated as Σ BAij × WDi, where BAij is the relative basal area of species i in plot j, and WDi is the mean wood density of species i. Values reported here represent the means of wood density from all available forest plots at the appropriate scale. The nested table structure illustrates how even these mean values vary at all scales, including among continents, among regions and nations, among landscapes within nations, and among forest types within landscapes within nations. Note how the scale at which WD is computed always matters. The best mean WD value to apply will depend on the spatial resolution of the remote sensing and mapping
| Continent | Tropical forest climate | Region/nation | Landscape/forest type | Value | Source |
|---|---|---|---|---|---|
| Pan-tropical mean | 0.619 | Mean of Africa, Asia, S. America network mean values assembled hereb | |||
| Africa | Moist | 0.633 (CI =+ 0.0080, n = 260 plots) | Lewis et al. (2013) | ||
| West Africa | 0.61 | Lewis et al. (2013) | |||
| Central Africa | 0.64 | ibid. | |||
| Monodominant | 0.696 | ibid. | |||
| Mixed | 0.627 | ibid. | |||
| East Africa | 0.61 | ibid. | |||
| West and Central Africa | |||||
| Acrisols | 0.609 | Lewis et al. (2013) | |||
| Cambisols | 0.617 | ibid. | |||
| White Sand | 0.660 | ibid. | |||
| Swamp | 0.728 | ibid. | |||
| Central African Republic | Mbaiki: deep resource-rich soils | 0.51c | Gourlet-Fleury et al. (2011) | ||
| Mbaiki: deep resource-poor soils | 0.59c | ibid. | |||
| Mbaiki: physically constrained soils | 0.525c | ibid. | |||
| Asia | Moist | 0.594 (SD = 0.039, n = 71 plots) | Qie et al. (2017) | ||
| Borneo | 0.594 | ibid. | |||
| Old-growth, no edge effects | 0.600 (SD = 0.038, n = 49 plots | ibid. | |||
| Old-growth, edge effects | 0.581 (SD = 0.039, n = 22 plots) | ibid. | |||
| Borneo: Sabah | Sepilok: Alluvial | 0.55 | Jucker et al. (2018a, b) | ||
| Sepilok: White Sand | 0.64 | ibid. | |||
| Central America | 0.540 (SD = 0.063, n = 5 sites) | This paper, from literature sources | |||
| Wet | Costa Rica | La Selva | 0.47d | Muller-Landau (2004) | |
| Panama | Sherman | 0.595 | Stegen et al. (2009) | ||
| Moist | Panama | Barro Colorado Island | 0.51d | Muller-Landau (2004) | |
| Panama | Barro Colorado Island | 0.545 | Stegen et al. (2009) | ||
| Dry | Panama | Cocoli | 0.494 | ibid. | |
| Costa Rica | San Emilio | 0.614 | ibid. | ||
| South America: Amazonia | Moist | All Amazon | 0.629 (SD = 0.081, n = 165 plots) | This paper, from RAINFOR data | |
| Central Amazon | 0.703 (SD = 0.041, n = 37 plots) | This paper; updating Baker et al. (2004), Mitchard et al. (2014) | |||
| Brazilian Shield | 0.591 (SD = 0.048, n = 11 plots) | ibid. | |||
| Guyana Shield | 0.688 (SD = 0.048, n = 41 plots) | ibid. | |||
| Paracou: Terra Firme and Alluvial | 0.67e | Baraloto et al. (2011) | |||
| Paracou: White Sand | 0.72 | ibid. | |||
| Western Amazon | 0.566 (SD = 0.056, n = 76 plots) | This paper, updating Baker et al. (2004), Mitchard et al. (2014) | |||
| Ecuador | Yasuni: Terra Firme | 0.588 | Stegen et al. (2009) | ||
| Peru | Loreto: Terra Firme and Flooded | 0.62e | Baraloto et al. (2011) | ||
| Loreto: White Sand | 0.64 | ibid. | |||
| Peru | Tambopata | 0.554 (SD = 0.053, n = 28 plots) | This paper | ||
| Tambopata: Holocene | 0.521 (SD = 0.049, n = 15 plots) | ibid. | |||
| Tambopata: Pleistocene | 0.591 (SD = 0.029, n = 13 plots) | ibid. | |||
| Tambopata: swamp | 0.467 (SD = 0.034, n = 2 plots) | ibid. |
aMulti-plot studies and compilations that present community-weighted wood density for tropical forests were only included if values were clearly basal-area-weighted and properly identified. Thus, (1) studies that apparently represent the average wood density of all species or stems in plots or other samples (e.g., ter Steege et al. 2006; Slik et al. 2010, Fortunel et al. 2014) were not included, because weighting by relative contribution to basal area is more likely to approximate the contribution of each species to carbon storage than weighting by its relative frequency or abundance (cf. the large differences in Amazon-dominant species as reported by Fauset et al. 2015 and ter Steege et al. 2013 when evaluated by basal area and when evaluated by stem abundance). Similarly, (2) studies based largely or entirely on vernacular name identifications are excluded, as in diverse tropical forests these are less reliable and precise than botanical identifications (cf. Fearnside 1997 for data and discussion of this). Sullivan et al. 2017 is not listed as a source in this table as data plotted in their Fig S16 are mostly available as continent-level mean values in other recent analyses (Lewis et al. 2013 for Africa, Qie et al. 2017 for Borneo, and the current paper for Amazonia)
bThe simple unweighted mean of Amazon, Asian, and African moist forest values here from the plot networks across tropical forest Africa (AfriTRON), Asia (T-FORCES), and South America (RAINFOR), where trees ≥ 10 cm d.b.h. and a standard wood density data source (Zanne et al. 2009) were used. No pan-tropical value could be located in previous literature that was clearly based on plot measurements in which trees were identified to species and trees were all measured
cTrees ≥ 20 cm d.b.h.; from data plotted in Fig. 2 of Gourlet-Fleury et al. (2011)
dTrees > 30 cm d.b.h
eFrom data plotted in Fig. 5 of Baraloto et al. (2011)