QUANTATIVE ANALYSIS USING POINT- CENTER-QUARTER METHOD AT SITIO PANLALAGUAN , SAN JUAN, BATANGAS. Capoquian, Lyrech Shaun Hibo, Emma Rose Padilla, Jayrah Penetrante, Gerson Kim Prado, Lorelyn Villafranca, Mark Anthony
Aug 28, 2014
Quantative Analysis Using Point-Center-Quarter Method at Sitio Panlalaguan , San Juan, Batangas.
Quantative Analysis Using Point-Center-Quarter Method at Sitio Panlalaguan , San Juan, Batangas.
Capoquian, Lyrech Shaun
Hibo, Emma Rose
Padilla, Jayrah
Penetrante, Gerson Kim
Prado, Lorelyn
Villafranca, Mark Anthony
Introduction
Vegetation field studies began in the early 19th century with the contributions of Alexander van Humbolt (Randall, 1978).
Vegetation analysis was a study of Spatial distribution of taxa and their evolutionary relationships.
It has become the classic of the natural sciences concerning dispersal for it helps in determining facts and their interpretations needed for formulating certain natural laws and principles (Nichols, 1930).
A wide variety of methods aside from aerial surveys or photographs have been formulated to determine some forest structure parameters which includes:
Population density
Basal area
Biomass
Vegetative sampling falls into two broad categories:
Plot-based
Plotless
In such terms, the Plot-less method including PCQM is faster, require less equipment, and may require fewer workers.
The point-center quarter method was considered to be of the most efficient for obtaining quantitative data on forest trees (Mitchell, 2007).
The significance of this activity is allow researchers to measure species changes within communities and to better understand succession within a given natural community or the impacts of specific land-management plans.
Therefore, as an objective of this activity, the students determined the:
Mean distance
Mean area
Sampled area
They also identified which species is the:
most dominant
most numerous
most frequent
most important
Methodology
Sampling
The quantitative analysis using PCQM was held at the Sitio Panlalaguan, San Juan, Batangas.
Ten points were sampled using a 100 meter calibrated transect rope.
Each point represented the center of the measurement area.
The imaginary quadrants were assigned in reference to the first point were the first sampling was conducted.
In each of the quadrant, the closest tree was determined, identifying its species and distance from the center point.
Then, the trees diameter breast height (1.30 m above) and basal area (0.30 m above) were measured
Computation
Formula for the overall quantitative analysis of the tree species are the following:
Mean distance= Total distance (d)/ No. of distance (n)
Mean area= (d/n)
Sample area=(100 m x mean distance)/ 100
The values for finding the most dominant, most frequent, most numerous, and most important are the following:
Absolute density=number of tree species/ hectare
Relative Density=density of each species/ density of all species
Absolute dominance= basal area of each tree species/hectare
Relative Dominance=(basal area of each species/ basal area of all species) x 100
Relative Frequency=number of trees per species/ total number of trees
Importance value= relative density + relative dominance + relative frequency
Results
Mean Distance1.6 mMean Area2.56 mSampled Area0.016 hectaresAbsolute Dominance0.002956Table 1. Overall Mean Distance, Mean Area, and Sampled Area in the Site
A total number of 246 trees were surveyed and these tree species were identified
At least 72 different species seen on the study site.
Cococs nucifera which has a mean value of 7.164 m for the basal area is the most dominants species regarding its area covered which measures 0.0007164
In contrast, the least dominant species is Lagerstemia periformis which garners a basal area of 8.8 x 10^-8 and covered area of 8.8 x 10^-12.
For the density, the most numerous species is Bambusa sp., with a total of 40 trees surveyed and an absolute density of 0.004 trees per hectares.
Bambusa sp. Was also the most frequent species garnering a relative frequency of 16.260162 m with respect with the other trees surveyed.
Finally, the highest importance value was also possessed by Bambusa sp. with a value of 33.056 and an Importance of 11.02%.
Discussion
Biases are somehow seen upon using the PCQM.
One reason for the use of quantitative techniques is that the resulting data are not tinged by the partiality of the investigator.
The advantage is speed, the sacrifice would be the accuracy in the process.
A ten point sampling per One-hundred meters may only be adequate on certain forest types.
Conclusions
The mean distance is 1.6 m, mean area is 2.56 m, sampled area is 0.016 hectares and the absolute dominance of trees species is 0.00295 hectares.
The most dominant is Cocos nucifera.
The most frequent, dense, and important plant is the Bambusa sp. over the 1 hectare study site.
Recommendations
An extensive identification and classification of plant species is recommended for more exact and precise values.
It is also recommended that other quantitative methods should be used for more data accuracy.