Abstract
Objectives: To evaluate species-area relationship of the sal (Shorea robusta) dominated tropical dry deciduous forest of Chota Nagpur plateau, India. Methods/Statistical analysis: One hectare (ha) plot was selected in which quadrats of 10 m x 10 m size were equally disturbed. In each specific quadrant, the number of species and density of adult trees was determined. Species-area relationship was analyzed by plotting an increasing number of species as a purpose of plot size. The Species-Area Relationships (SAR) were compared by using the Power curve, the Exponential curve, and the Logistic curve. Findings: The major finding in terms of density comprises of 436 adult stems having a diameter greater than and equal to 9.6 cm, 874 saplings having a diameter greater than and equal to 3.2 cm but less than 9.6 cm, and 6147 seedlings having a diameter less than 3.2 cm in one ha. The observed species-area curves were firstly steep, followed by continuing species accumulation. Where curves were best fitted by the power model because of low P value (possibility underneath the null hypothesis), high F ratio (regression mean square more the error mean square) and high Ra2 (adjusted coefficient of determination) representing one ha study area. Moreover, the high P value, low F ratio, and low Ra2 of exponential and logistical models showed an extreme deviation from the observed fashions of species-area for the plant species. In this study, the Z-value decreased with increase in C-value, indicating both were directly fitted constant and autonomous of biotic and a biotic features of the study area. Application/Improvements: The species-area relationships expressed distinct habitat heterogeneity and dispersal constraint of plant species in the Sal forest. Keywords: Exponential Curve, Logistic Curve, Power Curve, Sal Forests, Species-area Relationships
Highlights
The tropical forest area was 52% of the total forests, and about 42% of this forest were categorised as dry forest[1]
Species-Area Relationships (SAR) can be used for forecasting the degree of extinction of a species from habitat loss[24,25], for prophesying the species richness of assured taxa based on richness of other species[26], for calculating human influences on biodiversity[27], for identifying hotspots and geographical regions of high species richness[28], for designing optimal reserve sizes[29], and for assessing the species richness of enormous areas[30]
Example[32] in a study of Iberian plant diversity, used species-area curves to calculate roughly species richness at two scales: 100-m2 of total sites. They found that species richness at the confined scale were negatively correlated with precipitation in different seasons, but not at the landscape scale, and that limitation vanishes the adaptation to harsh environments possible had a higher effect at smaller spatial scales
Summary
The tropical forest area was 52% of the total forests, and about 42% of this forest were categorised as dry forest[1]. Recognition was made by essential observations of the specimen and examination of relevant literature[5] It is globally well-know that forests would be managed in an ecologically sustainable environment[6,7]. Example[32] in a study of Iberian plant diversity, used species-area curves to calculate roughly species richness at two scales: 100-m2 of total sites. They found that species richness at the confined scale were negatively correlated with precipitation in different seasons, but not at the landscape scale, and that limitation vanishes the adaptation to harsh environments possible had a higher effect at smaller spatial scales. In39–42 this study, the objective was to identify the species-area relationships and to decipher the best-fit curve in the lack of asymptotic species richness
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