Project Amazonia: Solutions - Indexation of Forest Health
We must keep in mind that there are an enormous number of factors that contribute to the health of the ecosystem. All of these factors cannot be measured independently, so in order to come up with a hypothetical index number, we will consider the plant biomass because the amount of plant biomass is a direct consequence of all the biotic and abiotic factors.
To address this need, a study quantified the total aboveground plant biomass (TAGPB) and forest structure in tropical forest sites in Brazil. The TAGPB of intact forest range from 288 to 346 Mg ha-1, with a mean of 313 Mg ha-1; dense forest TAGPB range from 298 to 533 Mg ha-1, with a mean of 377 Mg ha-1; and ecotone forests TAGPB range from 298 to 422 Mg ha-1, with a mean of 350 Mg ha-1. In general, the mean TAGPB is 341 Mg ha-1. Non-tree components comprise 22% of TAGPB. This is noteworthy because the non-tree components are often omitted from forest biomass/carbon pool estimates.
Information on total aboveground plant biomass (TAGPB) is scarce for Amazonian forests. Indirect estimates based on commercial volume from forest inventory data1, as well as direct field measurements of individual trees have been used to predict TAGPB2. Estimates for TAGPB in the Brazilian Amazon have ranged from 155 to 555 Mg ha-1.
TAGPB will be estimated by measuring all organic materials above mineral soil. TAGPB will be divided into "tree" (broad-leaved trees) and "non-tree" (other components, predominantly palms) components based on structural and ecological significance and practicality of measurement.
Tree diameter will be measured at 1.37 m above the ground (dbh). Trees will be separated into seven diameter classes based on dbh (<10, 10-30, 30-50, 50-70, 70-100, 100-200 and >200 cm dbh). Palms will be sampled separately from broadleaf trees. We will divide them into three categories (basal palms with no trunks, <10 and 10 cm dbh). Vines and lianas will be placed in two size classes (<10 and 10 cm dbh). Other components include small dicots (plants <1.37 m in height), litter/rootmat (forest floor), standing dead trees and palms, and dead and downed coarse woody debris (CWD).We will divide CWD into two categories: 2.5-7.6 and 7.6 cm diameter3. The forest floor component is composed of litter, small wood debris (<2.5 cm diameter), and rootmat. Rootmat contains a large amount of decomposing organic matter, as well as live roots.
Individual equations for each forest component will be used for calculating the biomass (Table 2 and Table 3). Biomass of trees 5 cm dbh will be calculated from equations based on dbh given by Higuchi et al. (1998) for Amazonian trees. Biomass of trees <5 cm dbh will be calculated from equations based on dbh given by Hughes et al. (1999). Tree height will be estimated from a regression equation with tree diameter as the independent variable.
Steps involved with the methodology:
Biomass of CWD will be calculated by using the methods of Van Wagner. Transects to measure mass of CWD 7.6 cm in diameter were 15 m long. Pieces of CWD that are 2.5-7.6 cm in diameter will be measured along the central 5 m of the 15-m transect. Coarse woody debris will be further separated into tree (dicot) wood or palm wood components. The 7.6-cm diameter class will also be separated into sound or rotten classes following the methods of Kauffman et al. (1988) and Brown (1971).
For the 2.5-7.6 cm diameter classes, the diameter and angle from the horizontal of 65 individual pieces of biomass along a 100 m transect will be measured to calculate the quadratic mean diameter and wood particle tilt4. Thereafter, we will only count pieces that intersect the line, and we used density, quadratic mean diameter, and wood particle tilt variables to calculate biomass.
To calculate forest floor biomass, each sample will initially be weighed in the field. Sub-samples will then be oven-dried to determine the ratio of wet-to-dry weight. This ratio will then be applied to the entire sample to convert from wet-to-dry weight.
To estimate biomass of basal leaf palms, the number of leaves of each individual palm encountered in the 2 mÅ~10 m plot will be counted and multiplied by a mean weight per leaf derived from a random sample of 30 basal leaves that will have been oven-dried and weighed. Three equations will be necessary to ascertain biomass of palms: biomass of Attlea sp. 1.78 m high will be calculated with the model developed by Anderson (1983); biomass of other palm species 10 cm dbh will be estimated with the model of Frangi and Lugo (1985); and biomass of palms <10 cm dbh will be calculated by using a model developed specifically for this study.
Vine biomass estimates will be calculated with the model given by Putz6. All seedlings (<1.37 m height) will be counted in each of the 16 (1 mÅ~1 m) plots per site. Seedling biomass will be based on sub-sample of 50 randomly collected oven-dried seedlings from which an average weight per seedling will have been determined.
Biomass of standing dead trees <10 cm dbh will be calculated from an equation developed by Hughes et al. (1999). Biomass of standing dead trees 10 cm dbh will be estimated by first calculating volume, then multiplying volume by the mean value of specific gravity of sound dead wood. Standing dead palm biomass will be estimated from an equation developed for this study for palms <10 cm dbh and by multiplying volume by specific gravity (0.327 g cm-3) for palms 10 cm dbh.
Here is the table of the above mentioned equations and methods:
Biological Value:
According to the National Research Council, there are five basic criteria that researchers look at when determining the biological value of a given species or habitat:
1. Richness - the number of species or habitat in a given area. A region with more species per unit area is given a higher value.
Ex. Tropical forests have higher conservation priority than an adjacent tropical dry forest with less richness of species.
2. Endemism - the narrowness of distribution of species in an area. A region with many endemic species has a higher value than a region with fewer endemic species. Endemics are the species that are prevalent in or peculiar to an area.
Ex. Madagascar which has 80% of plant species found nowhere else in the world has high priority.
3. Rarity - the rarity of species in a region. A region with rare species is given a higher value.
4. Ecosystem Services - The importance of the natural habitat or resident single species capable of influencing ecosystem function for various services of importance to humans.
Ex. Forested watershed that is a source of public water has higher conservation value.
5. Protected Status - The relative protection of species that already exists determines the value of a species or habitat.
All in all, species and habitats do not all have equal value when it comes to biodiversity management and conservation, and we must come up with the species and habitats that will best represent the health of the Amazon rainforest as a whole.
1: Brown, S. and Lugo, A.E., 1984. Biomass of tropical forests: a new estimate based on forest volumes. Science 223, pp. 1290¯1293. Abstract-GEOBASE
Brown, S., Lugo, A.E., 1990. Biomass estimates for Brazil's Amazonian moist forests. In: Forest'90: Annals of the First International Symposium on Environmental Studies on Tropical Rain Forests, Manaus, Brazil, pp. 46-52.
Brown, S. and Lugo, A.E., 1992. Aboveground biomass estimates for tropical moist forests of the Brazilian Amazon. Interciencia 17, pp. 8¯18.
Brown, S., Lugo, A.E. and Iverson, L.R., 1992. Processes and lands for sequestering carbon in the tropical forest landscape. Water Air Soil Pollut. 64, pp. 139¯155. (Abstract-Compendex | Abstract-GEOBASE | Abstract-EMBASE)
2: Jordan, C. and Uhl, C., 1978. Biomass of a terra firme forest of the Amazon Basin. Oecologia Plantarum 13, pp. 387¯400.
Klinge, H. and Rodriguez, W., 1973. Biomass estimation in central Amazonian rain forest. Acta Cient. Venez. 24, pp. 225¯237.
Klinge, H., Rodriguez, W., 1974. Phytomass estimation in a central Amazonian rain forest. In: Proceedings of the IUFRO Congress on Forest Biomass Studies, Vol. 15, Rome.
3: Kauffman, J.B., Sanford, R.L., Cummings, D.L., Salcedo, I.H. and Sampaio, E.V.S.B., 1994. Biomass and nutrient dynamics associated with slash fires in neotropical dry forests. Ecology 74, pp. 140¯151.
Kauffman, J.B., Cummings, D.L., Ward, D.E. and Babbit, R., 1995. Fire in the Brazilian Amazon. I. Biomass, nutrient pools, and losses in slashed primary forests. Oecologia 104, pp. 397¯408. (Abstract-Elsevier BIOBASE | Abstract-GEOBASE)
4: Brown, J.K., 1974. Handbook for Inventorying Downed Woody Material. USDA Forest Service, Ogden, UT, 25 pp.
Brown, S., 1997. Estimating Biomass and Biomass Change of Tropical Forests: A Primer. Forestry Paper 134, FAO, Rome.
5: National Research Council, et al. Perspectives on Biodiversity: Valuing its Role in an Everchanging World. Washington, D.C.: National Academy Press, 1999.
6: Putz, F.E., 1983. Liana biomass and leaf area of a terra firme forest in the Rio
Negro Basin, Venezuela. Biotropica 15, pp. 185¯189. Abstract-GEOBASE
7: Van Wagner, C.E., 1968. The line-intersect method in forest fuel sampling. Forest Sci. 14, pp. 20-26.
