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Protocol 15. Vegetation Structure and Diversity (Trees, Palms and Bushes)

Coordinator:
Dr. Leandro Valle Ferreira (MPEG) • E-mail: lvferreira@museu-goeldi.br
Protocol researchers:
East Pará - Dr. Leandro V. Ferreira (MPEG)
West Pará - MSc. Chieno Suemtsu (UFOPA)
Amapá - MSc Rosangela Sarquis (IEPA)
Maranhão - Dra. Francisca Muniz (UEMA)
Mato Grosso - Dr. Célia Regina Araújo Soares (UNEMAT/AF)

Groups of interest and estimated diversity of species per grid: Annonaceae (60), Euphorbiaceae (50), Leguminosae (200), Rutaceae (10), Sterculiaceae (8), Moraceae (45) and Arecaceae (30).

Biological role of the group: trees determine the architecture and microclimatic conditions of the forest. All of the families to be studied play a fundamental role in the food chain as suppliers of flowers, fruit and nectar for animals that participate in the pollination and dispersal process throughout the forest. Trees also offer a support structure for epiphytic plants (such as orchids, bromeliads and araceae), lianescent plants (vines) and parasitic plants, as well as providing habitats for organisms such as fungi, bryophytes (mosses and hepaticas), lichens and insects (termites, ants, bees, beetles, lizards, etc). In the case of Leguminosae, this is the second most important family in terms of Amazon forest vegetation, some of these species playing an important role as nitrogen fixers. Annonaceae and Euphorbiaceae stand out through their ability to produce biologically active antimicrobial substances, for example, restricting attacks from pests and allergens, as well as being aromatic, astringent and lactiferous. Economic importance: the three families have important medicinal values (e.g. the production of chemical compounds) as well as timber, melliferous, lactiferous qualities (Euphorbiaceae), as producers of fiber (bast, in the case of Annonaceae) and fruit. All families are widely used by traditional populations. Arecaceae is one of the families with the greatest economic importance for traditional populations, being a source of fiber and wood for construction and handicraft activities, providing edible fruit and the extraction of oil.

Technique 1. Collection of individual fertile specimens

The collection methods to be adopted for the study of taxonomic groups (Phanerogams) during the Biodiversity Research Program (PPBIO) will be those traditionally used for floristic surveys (Fidalgo & Bononi, 1984). This collection procedure will be carried out, continuously, by specially trained woodsmen. Fertile samples will be collected, i.e. specimens with flowers and fruit, while respecting exceptions on the part of the specialist (e.g. for rare specimens, new occurrences, probable new species etc.), samples not necessarily being included within existing Herbaria. A minimum of 5 and a maximum of 10 branches or offshoots (samples) will be taken from each fertile plant, using pruning sheers and/or trimmers. The samples will be placed onto individual sheets of paper (84 cm high x 50 cm wide), being sealed externally by a sheet of cardboard at the front and at the back, pressed between a corrugated sheet of aluminium, also at the front and back, and so on for all included samples. All samples will then be bound together and pressed between blocks of wood, using thick string to secure the pile. The information that needs to be recorded in the field at the time of sample collection is outlined in protocol 18 (VEGETATION STRUCTURE). The name and number of the collector will be noted down in pencil on the sheets of paper for all samples that originate from the same plant.

Sampling unit: each individual specimen.

Sampling design: Samples must be collected from all of the individual specimens found within each plot or along each trail. In species with clonal reproduction, the stems will be counted as individuals.

Method of preserving the collected material: the samples will be dried in gas or electric ovens, preferably in the field or, alternatively, at the laboratory. Material sent to the laboratory must be soaked in 70% alcohol, ensuring greater durability and avoiding the loss of leaves and reproductive parts. All other procedures will then be carried out at the laboratory (identification, mounting, recording and sample inclusion). The collected samples will be deposited in INPA, MPEG and other trustworthy Amazon depository collections.

Important environmental data for this group: altitude, incline, soil (texture, fertility, hydric potential). Restrictions on activities that could potentially damage protocol development: removal of bushes for marking out areas, or the felling of trees.

Structure analysis

Justification

The purpose of this protocol is to sample the structure and floristic diversity of vegetation within a 25 km2 grid, consisting of the sampling network set out for the Biodiversity Research Program (PPBio). Thirty hectares with perimeters of 250 m x 40 m must be marked out within this grid, structural variable measurements then being taken and plants being inventoried in order to calculate the diversity, wealth and phytosociological indices of the forest vegetation.

The structure of the forest vegetation is multidimensional, i.e. stratified into several layers, enabling animals and even other plant forms, to cultivate their own habitats and provide a certain level of territorial exclusion, occupying niches and other areas that can then be explored for available resources. Birds, mammals (flying and non-flying), non-social and social insects (bees, termites, wasps and ants), amphibians and reptiles use this structure (or part of it) for nests, perches, food, pollination, and even reproduction.

Monitoring of tropical forest structures, taking place within permanent forest plots (PFPs) such as those outlined within this protocol, are very important for measuring the likely effects of Greenhouse Gas Emissions (GGEs) in relation to global warming, especially CO2, released into the atmosphere in large quantities due to the burning and cutting of vegetable biomass, from accelerated deforestation that has now been verified within the region.

As for diversity, the indices that measure and estimate the diversity and wealth of species at local level will be calculated from within and between the plots, it then being possible to compare these indicators between sites. Models for predicting the number of species will also be used based on the wealth and abundance data recorded within the plots.

Detailed characterization and descriptions of this structure will enable planning and design of the sampling strategies of various zoological groups to go ahead, improving our understanding of how animals use their own habitats for the maintenance of their own populations.

The main purpose of this protocol is to characterize the structure and floristic diversity of the vegetation found within the thirty, 1 hectare PPBio grid plots, creating a database based on this information. Some parameters, such as the leaf area index (LAI) of the vegetation and the mapping out of natural clearings, as well as the mapping out of plants within the plots, will also be carried out during the research. This will facilitate comparison between independent plots and other PPBio sites.

Methodology

Sampling plots

The plots will be 250 m in length, but vary in width depending on the groups of plants to be sampled, up to 40 m in total, i.e. 20 m on each side of the central axis (see Table 1). The plots will be set out in straight lines. The initial marking out of the plot will be by means of a central line, stretched out and joining PVC posts, fixed into the soil at every 10 m. The side lines will then be marked out in accordance with the width needed for the sampling of every group. The plot will be measured out within the 25 km2 grid (5 x 5 km, with 1 km spacing). At each side of the centerline will be a 1 m wide strip of land so that researchers can move back and forth, the sampling areas being established beyond this transit area.

Table 1. DBH classes of all individual trees and lianas to be sampled within the PPBio grid plots.

Records and field measurements (variables)

Record of species – floristic

All plants sampled within the plots will be registered and documented (as herbarium specimens, photos, etc), with at least 4 (four) examples of each type of plant being collected using pruning sheers and/or trimmers. The samples will be placed onto individual sheets of paper (84 cm high x 50 cm wide), externally sealed by a sheet of cardboard at the front and at the back, pressed between a corrugated sheet of aluminium, also at the front and back, and so on for all included samples. All samples will then be bound together and pressed between blocks of wood, using thick string to secure the pile. Identification in terms of family and genus (100%) will take place in the field. A large part of this material (60%) will also have been identified at species level by specialists, for confirmation purposes. Method of preserving the collected material: the samples will be dried in gas or electric ovens, preferably in the field or, alternatively, at the laboratory. Material sent to the laboratory must be soaked in 70% alcohol, ensuring greater durability and helping to avoid the loss of leaves and reproductive parts. All other procedures, after the drying process, will be carried out at the laboratory (identification, mounting, recording and inclusion of the sample). All material will be taken to the Herbarium at the center closest to the regional collection site, for herborization, sorting and checking, as well as for improving the level of identification. Sample data will be entered into the SINBIO database; fertile material data being entered into the BRAHMS system. Duplicates of fertile specimens will be distributed among herbaria associated with the PPBio network and, where appropriate, sent to specialists in Brazil and abroad. The collected samples will be deposited in INPA, MPEG and other trustworthy Amazon depository collections.

Diameter of the trunk

The diameter will be measured at 1.30 m from the ground (DBH), except for plants with diameters below 5 cm; the basal diameter being measured 20 cm from the ground. For trees with large buttresses (sapopemas), the diameter must be measured around 50 cm above the endpoint of the buttress (measurement point, MP). Should trunk irregularities occur, the measurement point will be shifted to a more cylindrical section of the stem.

A graduated tape measure marked with tenths of centimeters, or a diameter tape (D-tape), both having a precision of ± 1 mm, will be used for diameter measurements. A caliper rule will be used for individual specimens that have a diameter of less than 5 cm or a circumference of less than 15.71 cm, positioning the device towards the larger diameter at the time of taking the reading.

Mapping and marking out of plants

All individual specimens that have diameters within the above determined limits will be mapped out with x and y coordinates, where x is the distance along the plot's axis and y is the distance of the intersection until it reaches the plant. This measurement needs to be taken by extending the measuring tape out so that it remains horizontal. This is important for the inclusion of individual specimens when referring to the distances measured on the horizontal plane, like a map.

Trees will be measured and marked out sequentially within the plot, in order to facilitate future re-measurements. Plants will be marked with ink (yellow or orange, usually) at the point where the DBH measurement is made, in order to facilitate more accurate monitoring of growth.

Each plant will receive a standard size (3 x 7 cm) aluminium label with a three-phase numbering sequence. The first phase refers to the hectare, the second to the sub-plot, and the third to the plant itself. For example: 01-02-100. This it the one hundredth tree, located within the second sub-plot of the first hectare. The labels will be tied to the tree using 1.3 mm plastic fishing line.

Mapping out of natural clearings

Natural clearings caused by falling trees or parts thereof, will be recorded and measured in each plot.

The extent of the clearing will also be recorded, i.e. recent (less than two years, with average regeneration of up to 2 m), intermediate clearings (between two and five years, with average regeneration above 2 m), or ancient clearing (more than five years, regeneration at the point of closing the canopy opening); including the number of trees involved and the type of tree mortality (tree standing but dead, uprooted, broken at the base or in the middle of the trunk, crown completely broken, partially broken etc.).

Structural parameters and diversity: calculations and estimates.

The following structural parameters will be produced by measuring certain sets of variables:

Relative Density (RD) and Absolute Density (DA)

Density is commonly defined as the proportion of the number of individual specimens of a community per area unit, in this particular case known as relative density (RD). The density of individual specimens will be calculated for each 250 m x 40 m plot (one hectare), taking into consideration the size classes of plants and strata. The absolute density (AD) corresponds to the number of individual examples in the plots, or per size classes.

Abundances will also be calculated in relation to families and plant species, whenever there is the need for this type of information.

Basal Area

The basal area (BA) expresses the dominance of a size class or species within a community. The basal area of a plant community is obtained by the proportion of the soil occupied by the perpendicular projection of the cross sections of the trunks of trees. The basal area is obtained by measuring the DBH of all individual examples present within the plot, or of a specific class. The B.A. calculation will be determined by means of the following equation:

B.A. (m2) = Pi*(DBH2/4)*0.0001

In which:

Pi = 3.14159

DBH = diameter at breast height, measured at 1.3 m above the ground.

0.0001 = transformation from cm2 to m2.

The BA of a plot is obtained by summing up the individual basal areas of all of the plants within a determined plot, or for a specific size class. The same applies for calculating the BA at family or species level.

Standing plant biomass at ground level (BAC)

Aerial standing plant biomass, or above ground level (BAC), will be calculated from the regression models developed for tropical forests, including the Amazon forest. These models estimate biomass through the use of DBH data. The models to be used were developed by various authors at different locations within the region (PHILLIPS, 1998; BAKER, et al. 2004; PHILLIPS, 2004).

The BAC1 equation was obtained by utilizing data from 315 trees, collected within 5 plots of 0.04 ha (20 m x 20 m) as part of the Bionte project, close to the Amazon city of Manaus (CHAMBERS et al., 2001). The BAC2 equation is a modified version of the BAC1, incorporating a simple multiplication factor for variations in the density of the wood between species (BAKER et al., 2004). The BAC3 equation was derived from an independent group of diameters and the biomass data of 378 trees (CHAVE et al., 2001); with the BAC4 equation having the same relationship, but including the specific density of the wood (BAKER et al., 2004). The BAC5 equation is based on the same set of samples producing the BAC1 and BAC2 equations, except that the BAC5 calculation is based on the plot and not the trees, using the relationship between the basal area and the fresh biomass above the ground for trees greater than 5 cm in diameter, for the five plots of 0.04 ha (PHILLIPS et al., 1998).

According to Santos and Martins (2004), the diversity indices can be divided into three groups; measurements of wealth (type I), measurements of abundance (type II) and measurements of diversity or heterogeneity (type III). Type II and III indices will be used for this protocol.

Abundance

Abundance will be obtained by using data collected from the plant communities, using variables such as the list of species and their abundances, sorted in descending order so that species can be ranked in terms of most abundant species to the least abundant species. Three principal methods exist:

a) The ‘broken stick’ model, or the 'proportionality of space’ model (McARTHUR, 1957), providing a good fit in relation to data collected in communities that have a small number of functionally similar species. In this particular model, the number of species with ‘n’ individuals can be estimated by the equation:

Where:

S(n) = the number of species in the abundance class with 'n' individuals.

S = total number of species within the community.

N = total number of individuals.

The expected number of species in each abundance class can be calculated by using the above equation. In this sense, the observed number of species in each abundance class can be compared with the expected number.

b) Log-normal model: developed by Preston (1948), this is one of the most frequently encountered models in communities that have many functionally heterogeneous species, the abundance of which being influenced by many independent factors (MAY, 1975). When the number of individuals (abundance) of each species is transformed into a logarithm, with the abundance classes being established, the distribution of the number of species in the abundance classes describes a sinusoidal curve, Gausssian curve, or normal curve, hence the name log-normal model. This curve has a mode that represents the maximum number of species within a certain abundance class. In lower abundance classes (to the left of the modal class) and the higher abundance classes (to the right of the modal class), the number of species rapidly diminishes.

c) Log series distribution model: prepared and deduced by (Fisher et al. 1943), this model is expected in a relatively simple community within a relatively restricted environment, in which very competitive species come and go at random time intervals and occupy the hyper-space of the niches of a still unsaturated environment, in which a small number of very important factors dominate.

Diversity or heterogeneity models

According to Santos and Martins (2004), in order to use one of the abundance distribution models for comparing diversity between communities, it is necessary that the abundance distribution in all of the communities adhere to a single model. The most used type of heterogeneity index is the Shannon index (PIELOU, 1975, 1977), originating from the information theory (SHANNON; WEAVER, 1949), the use of which, as a means of measuring diversity, was initially proposed by Margalef (1957):

(“Em que:" = In which)

ρe = relative abundance of the species, and

ne = number of individuals of the species, and

N = total number of individuals

S = total number of species

The Shannon H’ diversity index is highly influenced by the number of species with relative abundance intermediate values (WHITTAKER, 1972), i.e. it shows a certain shift towards specific types of species wealth within the community (MAGURRAN, 1988). It is therefore also interesting to know the degree of abundance concentration for the first types of species.

The best measure of dominance concentration is the Simpson concentration index:

This index is inversely related to the value of H’: as H’ increases, D decreases also. A number of authors therefore transform the Simpson index to 1-D or 1/D, so that it has a direct relationship with the variation of H' in its transformed format. On the other hand, D also has an inverse relationship with equitability: the greater the equitability, the lower the concentration, and vice-versa. Estimating equitability is very problematic (MAY, 1975), but in spite of this; one of the most used equitability indices, due to the simplicity of the calculation, is the Pielou index (1966):

Referências

BAKER, T.R.; PHILLIPS, O.L.; MALHI, Y.; ALMEIDA, S. et al. Increasing biomass in Amazonian forest plots. Philosophical Transactions of the Royal Society of London, v. 359, p. 353-365, 2004. Series B.

CARVALHO, J. O. P. de. Análise estrutural da regeneração natural em florestas tropical densa na região do Tapajós no Estado do Pará. 1982. 128f. Dissertação (Mestrado) – Universidade Federal do Paraná, Curitiba, 1982.

CHAMBERS, J. Q.; DOS SANTOS, J.; RIBEIRO, R. J.; HIGUCHI, N. Tree damage, allometric relationships, and aboveground net primary production in a tropical forest. Forest Ecol. Mngmt., v.152, p. 73-84, 2001.

CHAVE, J.; RIERA, B.; DUBOIS, M.-A. Estimation of biomass in a neotropical forest of French Guiana: spatial and temporal variability. J. Trop. Ecol., v. 17, p. 79-96, 2001.

FIDALGO, O.; BONONI, V.L. Guia de coleta, preservação e herborização de material botânico. São Paulo: Instituto de Botânica, 1984. 62 p. (Manual n. 4).

FISHER, R.A.; CORBERT, A.S.; WILLIAMS, C.B. The relation between the number of species and the number of individuals in a random sample of an animal population. Journal of Animal Ecology, v. 12, p. 42-58, 1943.

HIGUCHI, N. et al. Biomassa da parte aérea da vegetação da floresta tropical umidade terra firme da Amazônia brasileira. Acta Amazônica, v. 28, n. 2, p. 153-166, 1998.

MACARTHUR, R.H. On the relative abundance of bird species. Proceedings of the National Academy of Science, v. 43,p. 293-295, 1957.

MAGURRAN, A.E. Ecological diversity and its measurements. Princeton: Princeton University Press, 1988.

MARGALEF, R. La teoría de la información en ecología. Memórias de la Real Academia de Ciencias y Artes de Barcelona, v. 32, p. 373-449, 1957.

MAY, R.M. Patterns of species abundance and diversity. In: CODY, M.L.; DIAMOND, J.M. (Ed.). Ecology and evolution of communities. Cambridge: Belknap Press of the Havard University Press, 1975. p. 81-120.

PHILLIPS, O.L.; BAKER, T.R.; ARROYO, L.; HIGUCHI, N.; KILLEEN, T.J.; LAURANCE, W.F.; LEWIS, S.L.; LLOYD, J.; MALHI, Y.; MONTEAGUDO, A.; NEILL, D.A., NÚÑEZ- VARGAS, P.; SILVA, J.N.; TERBORGH, J.; VÁSQUEZ- MARTÍNEZ, R.; ALEXIADES, M.; ALMEIDA, S. et al. Pattern and process in Amazon tree turnover, 1976-2001. Philosophical Transactions of the Royal Society of London, v. 359, p.381-407, 2004, Series B.

PHILLIPS, O.L.; MALHI, Y.; HIGUCHI, N.; LAURANCE, W.F.; NUÑEZ-VARGAS, P.; VÁSQUEZ-MARTINEZ, R.; LAURANCE, S. G.; FERRIERA, L.V.; STERN, M.; BROWN, S.; GRACE, J. Changes in the carbon balance of tropical forest: evidence from long-term plots. Science, v. 282, p. 439-442, 1998.

PIELOU, E.C. Ecological diversity. New York: Wiley, 1975.

PIRES-O’BRIEN, M. J.; O’BRIEN, C. M. Ecologia e Modelamento de Florestas Tropicais. Belém: FCAP/Serviço de Documentação e Informação, 1995. 400 p.

PRESTON, F.W. The commonness and rarity of species. Ecology, v. 29, p. 254-283, 1948.

RODRIGUES, L. A.; CARVALHO, D. A. de; OLIVEIRA FILHO, A. T. de. Florística e estrutura da comunidade arbórea de um fragmento florestal em Luminárias, MG. Acta Bot. Brasvol., v. 17, n.1, p.71-87, jan./mar. 2003.

SANTOS, F.A.M; MARTINS, F.R. Técnicas usuais de estimativa da biodiversidade. Revista Holos, Rio Claro, p. 236-267, 2004.

SHANNON, C.E.; WEAVER, W. The mathematical theory of communication. Urbana: University of Illinois Press. 1949.

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