Biomass Of Tropical Rain Forest Research Articles

Biomass Allocation of China’s Forests as Indicated by a Literature-Based Allometry Database

Allometry reflects the quantitative relationship between the allocation of resources among different organs. Understanding patterns of forest biomass allocation is critical to comprehending global climate change and the response of terrestrial vegetation to climate change. By collecting and reorganizing the existing allometric models of tree species in China, we established a database containing over 3000 empirical allometric models. Based on this database, we analyzed the model parameters and the effect of climate on forest biomass allocation under the context of ‘optimal allocation theory’. We showed that (1) the average and median exponent of power functions for above-ground biomass were 2.344 and 2.385, respectively, which significantly deviated from the theoretical prediction of 2.667 by metabolic theory (p < 0.01). (2) The parameters of the allometric model were not constant, and not significantly correlated with temperature, precipitation, latitude, and elevation (p > 0.05), but were more closely related to individual size (p < 0.01). (3) Among different types of forests, the proportion of above-ground biomass in tropical rainforests and subtropical evergreen rainforests was significantly higher than that in temperate forests and boreal forests (p < 0.05). The proportion of trunk and branch biomass allocated to tropical rainforest was significantly higher than that of boreal forest (p < 0.05), while the proportion of root and leaf biomass allocated to tropical rainforest was significantly lower than that of boreal forest (p < 0.05). (4) The abiotic environment plays a crucial role in determining the allocation of plant biomass. The ratio of below-ground/above-ground biomass is significantly and negatively correlated with both temperature and rainfall (p < 0.01), and significantly and positively correlated with altitude and latitude (p < 0.01). This means that as temperature and rainfall increase, there is a decrease in the amount of biomass allocated to below-ground structures such as roots. On the other hand, as altitude and latitude increase, there is an increase in below-ground biomass allocation. These findings highlight the importance of considering the influence of abiotic factors on plant growth and development.

Response of tree community composition, plant diversity and aboveground tree biomass in tropical rainforests of Sri Lanka to variation in altitude

Tropical rain forests (TRFs) are a major carbon sink and play an important role in regulating the global climate. Floristic composition, structure and carbon storage in biomass of TRFs could vary substantially with climatic and edaphic factors. Altitudinal transects represent an excellent setting for investigating the responses of TRFs to environmental change. Objectives of this study were to determine the variation patterns and possible inter-relationships between plant community composition, diversity and aboveground biomass (AGB) in TRFs across an altitudinal gradient from 134 m to 1,667 m above sea level in Sri Lanka. Five permanent sampling plots of 1 ha each, consisting of four plots in lowland rainforests in Kanneliya and Pitadeniya- Sinharaja Forest Reserves and one plot in the tropical montane forest in Rilagala, were established. Trees with DBH≥10 cm were measured and taxonomically identified. A total of 3,781 trees, belonging to 191 species from 106 genera and 53 families were recorded, with a total basal area of 203.68 m2. Floristic composition of sampling plots showed substantial variation with altitude. Tree density and numbers of species, genera and families and plant diversity indices (i.e. Shannon-Wiener and Simpson’s Indices, evenness and richness of tree species) showed negative curvilinear declines with increasing altitude. Mean DBH, tree basal area and AGB increased from low- (348 kg ha-1) to midaltitudes (762 kg ha-1) and decreased from mid- to highaltitudes (70 kg ha-1), thus showing second-order polynomial relationships with altitude. Similar trends were shown between AGB and tree species number and diversity indices, thus indicating that AGB is maximum at intermediate vegetation diversity.

Detection of mitochondrial COII DNA sequences in ant guts as a method for assessing termite predation by ants.

Termites and ants contribute more to animal biomass in tropical rain forests than any other single group and perform vital ecosystem functions. Although ants prey on termites, at the community level the linkage between these groups is poorly understood. Thus, assessing the distribution and specificity of ant termitophagy is of considerable interest. We describe an approach for quantifying ant-termite food webs by sequencing termite DNA (cytochrome c oxidase subunit II, COII) from ant guts and apply this to a soil-dwelling ant community from tropical rain forest in Gabon. We extracted DNA from 215 ants from 15 species. Of these, 17.2 % of individuals had termite DNA in their guts, with BLAST analysis confirming the identity of 34.1 % of these termites to family level or better. Although ant species varied in detection of termite DNA, ranging from 63 % (5/7; Camponotus sp. 1) to 0 % (0/7; Ponera sp. 1), there was no evidence (with small sample sizes) for heterogeneity in termite consumption across ant taxa, and no evidence for species-specific ant-termite predation. In all three ant species with identifiable termite DNA in multiple individuals, multiple termite species were represented. Furthermore, the two termite species that were detected on multiple occasions in ant guts were in both cases found in multiple ant species, suggesting that ant-termite food webs are not strongly compartmentalised. However, two ant species were found to consume only Anoplotermes-group termites, indicating possible predatory specialisation at a higher taxonomic level. Using a laboratory feeding test, we were able to detect termite COII sequences in ant guts up to 2 h after feeding, indicating that our method only detects recent feeding events. Our data provide tentative support for the hypothesis that unspecialised termite predation by ants is widespread and highlight the use of molecular approaches for future studies of ant-termite food webs.

Large-scale mapping of aboveground biomass of tropical rainforest in Sulawesi, Indonesia, using Landsat ETM+ and MODIS data

This study combined 30-m spatial resolution Landsat Enhanced Thematic Mapper Plus (ETM+) data and 500-m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data, together with field data, to up-scale aboveground biomass (AGB) of tropical rainforests in Sulawesi, Indonesia. Contrasting to usual up-scaling approaches, this study uses in the intermediate step an estimation method based on application of geostatistics in the Landsat ETM+ spectral feature space. To connect ground-based measurements with spectral reflectance in Landsat ETM+ bands, this method employs ordinary Kriging in the three-dimesional (3-D) space where spectral features of satellite data are used instead of geographic coordinates. The most appropriate combination of the 3-D space spectral bands (bands 4 and 5) was then assigned with corresponding MODIS bands. In the final step, AGB could be mapped over the large area covered by the MODIS data. The results of the study indicate the effectiveness of the developed up-scaling method with respect to dealing with the problem of resolution mismatch between the ground sampling plots and the MODIS data.

Modifying geographically weighted regression for estimating aboveground biomass in tropical rainforests by multispectral remote sensing data

The present study uses a local regression approach for estimation of aboveground biomass (AGB) in a tropical rainforest area with highly diverse terrain conditions from remote sensing-based multi-spectral vegetation indices (VI). By incorporating altitudinal effects into the spatial weighting matrices of the common geographically weighted regression (GWR), an extended GWR model, geographically and altitudinal weighted regression (GAWR), has been developed to deal with both spatial (horizontal) and altitudinal (vertical) non-stationarity in the data set. Unlike the common GWR model, the presented GAWR approach captures both horizontal and altitudinal drifts in the relationships between aboveground biomass and remote sensing data. In order to test its improved performance, the GAWR method was compared with the traditional GWR technique and global ordinary least squares regression (OLS) in a region of mountainous tropical rainforest in Sulawesi, Indonesia. The relationships between AGB and VIs were found to be significantly spatially variable. The results showed that there were substantial benefits in capturing both horizontal and vertical non-stationarity simultaneously. The GAWR method significantly improved AGB prediction in all simulations relative to both the traditional GWR and OLS methods, as indicated by accuracy and precision statistics. From the results of empirical tests, it seems proper to say that for this data set, the GAWR model is better than the traditional GWR model.

Assessing the above‐ground biomass of a complex tropical rainforest using a canopy crane

Abstract Current estimates of the total biomass in tropical rainforests vary considerably; this is due in large part to the different approaches that are used to calculate biomass. In this study we have used a canopy crane to measure the tree architectures in a 1 ha plot of complex mesophyll vine forest at Cape Tribulation, Australia. Methods were developed to measure and calculate the crown and stem biomass of six major species of tree and palm (Alstonia scholaris (Apocynaceae), Cleistanthus myrianthus (Euphorbiaceae), Endiandra microneura (Lauraceae), Myristica insipida (Myristicaceae), Acmena graveolens (Myrtaceae), Normanbya normanbyi (Arecaceae)) using the unique access provided by the crane. This has allowed the first non‐destructive biomass estimate to be carried out for a forest of this type. Allometric equations which relate tree biomass to the measured variable ‘diameter at breast height’ were developed for the six species, and a general equation was also developed for trees on the plot. The general equation was similar in form to equations developed for tropical rainforests in Brazil and New Guinea. The species equations were applied at the level of families, the generalized equation was applied to the remaining species which allowed the biomass of a total of 680 trees to be calculated. This has provided a current estimate of 270 t ha−1 above‐ground biomass at the Australian Canopy Crane site; a value comparable to lowland rainforests in Panama and French Guiana. Using the same tree database seven alternative allometric equations (literature equations for tropical rainforests) were used to calculate the site biomass, the range was large (252–446 t ha−1) with only three equations providing estimates within 34 t ha−1 (12.5%) of the site value. Our use of multiple species‐specific allometric equations has provided a site estimate only slightly larger (1%) than that obtained using allometric equations developed specifically for tropical wet rainforests. We have demonstrated that it is possible to non‐destructively measure the biomass in a complex forest using an on‐site canopy crane. In conjunction the development of crown maps and a detailed tree architecture database allows changes in forest structure to be followed quantitatively.

Aboveground biomass of tropical rain forest stands in Indonesian Borneo

Aboveground plant biomass was examined in a tall virgin tropical lowland evergreen rain forest dominated by Dipterocarpaceae in Sebulu, East Kalimantan, Indonesia, with special reference to the gap-, building- and mature phases of the forest growth cycle. From the records of dimensions of sample trees examined by the stratified clip technique and DBH inventory data of trees in a study plot, the biomass of larger trees (DBH ≥4.5 cm) was estimated by the allometric correlation method. The biomass of smaller plants (DBH < 4.5 cm) was estimated by harvesting the plants in small quadrat plots. Although large differences were found between aboveground-biomass-estimates in different patches of different growth stages, the aboveground biomass in a 1.0 ha plot was 509 t/ha, and the one-sided LAI was 7.3 ha/ha. These values seem to result from the tall forest architecture with huge emergent trees (over 70 m high) and a moderate packing of plant mass indicated by the basal area value of 38.8 m2/ha for trees with DBH ≥4.5 cm.