. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

/pdf/tree-height-integrated-into-pantropical-forest-biomass-46lsmnqbtw.pdf

Tree height integrated into pantropical forest biomass estimates

http://www.afritron.org/upload/publication-store/2012/marshall_measuring_modelling_agc_BC2012.pdf

Measuring and modelling above-ground carbon and tree allometry along a tropical elevation gradient

https://eprints.ncl.ac.uk/file_store/production/238604/4D3D87B8-89B4-4CAC-AE1C-BF324DF4386F.pdf

New insights on above ground biomass and forest attributes in tropical montane forests

Permanent sampling plots (PSPs) are a powerful and reliable methodology to help our understanding of the diversity and dynamics of tropical forests. Based on the current inventory of PSPs in Indonesia, there is high potential to establish a long-term collaborative forest monitoring network. Whilst there are challenges to initiating such a network, there are also innumerable benefits to help us understand and better conserve these exceptionally diverse ecosystems.

/pdf/opportunities-and-challenges-for-an-indonesian-forest-319nnm5zk3.pdf

Opportunities and challenges for an Indonesian forest monitoring network

Floristic inventory and diversity assessments are necessary to understand the present diversity status and conservation of forest biodiversity. Studying the variation height-diameter woody provides insight into the general characteristics of the trees diversity pattern. This study mainly focuses on aimed to assess the effectiveness of trees diversity and structure in two study sites. The study was conducted at Ipendja evergreen lowland moist forest in northern Republic of Congo. The sampling design was systematic consisted of parallel transect 1 or 2 km part, and divided into consecutive rectangular plots, each 5000m2 (25 x 200 m, i.e. 0.5 ha). Within eight plots censuses, all trees with a DBH  10 cm were identified and measured. A total of 1340 trees has been recorded belonged 145 species and 36 families (n = 607 and n = 733, respectively in Mokelimwaekili and Sombo sites). The results show that the leading botanical families were Sapotaceae follows by Euphorbiaceae, Meliaceae, Caesalpiniaceae, Sterculiaceae, Annonaceae and Rubiaceae. The most representative species were C. mildbraedii, S. kamerunensis and P. oliveri, i.e. 62.06%, 30.34% and 28.27% respectively, suggested that they were the leading dominant species of this forest ecosystem. Shannon index were 4.29 bits for Mokelimwaekili and 4.22 bits for Sombo. While Pielou’s evenness index was between 0.88 and 0.90, respectively for the Mokelimwaekili and Sombo sites. The similarity coefficient for Jaccard was 62% and 58% for Sorensen. There are highlight variations in tree diversity indices across sites and plots in Ipendja forest.

/pdf/ecological-and-structural-analyses-of-trees-in-an-evergreen-2uke8015rl.pdf

Ecological and Structural Analyses of Trees in an Evergreen Lowland Congo Basin Forest

Aim To test the extent to which the vertical structure of tropical forests is determined by environment, forest structure or biogeographical history. Location Pan-tropical. Methods Using height and diameter data from 20,497 trees in 112 noncontiguous plots, asymptotic maximum height (HAM) and height–diameter relationships were computed with nonlinear mixed effects (NLME) models to: (1) test for environmental and structural causes of differences among plots, and (2) test if there were continental differences once environment and structure were accounted for; persistence of differences may imply the importance of biogeography for vertical forest structure. NLME analyses for floristic subsets of data (only/excluding Fabaceae and only/excluding Dipterocarpaceae individuals) were used to examine whether family-level patterns revealed biogeographical explanations of crosscontinental differences. Results HAM and allometry were significantly different amongst continents. HAM was greatest in Asian forests (58.3 7.5 m, 95% CI), followed by forests in Africa (45.1 2.6 m), America (35.8 6.0 m) and Australia (35.0 7.4 m), and height– diameter relationships varied similarly; for a given diameter, stems were tallest in Asia, followed by Africa, America and Australia. Precipitation seasonality, basal area, stem density, solar radiation and wood density each explained some variation in allometry and HAM yet continental differences persisted even after these were accounted for. Analyses using floristic subsets showed that significant continental differences in HAM and allometry persisted in all cases. Main conclusions Tree allometry and maximum height are altered by environmental conditions, forest structure and wood density. Yet, even after accounting for these, tropical forest architecture varies significantly from continent to continent. The greater stature of tropical forests in Asia is not directly determined by the dominance of the family Dipterocarpaceae, as on average non-dipterocarps are equally tall. We hypothesise that dominant large-statured families create conditions in which only tall species can compete, thus perpetuating a forest dominated by tall individuals from diverse families.

Smithsonian Tropi

Papers

architecture? Testing environmental, structural and floristic drivers