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Study on Web-Site Attributes and Predatory Efficiency of Dark Tetragnathid Spider in Point Calimere Wildlife and Bird Sanctuary

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Abstract:

Spiders represent one of the most abundant components of the predatory arthropods in terrestrial ecosystem. Their effectiveness at restricting pest populations, both alone and as part of natural enemy complex has well demonstrated in many countries. The web, web-site attributes and predatory efficiency of Dark Tetragnathid Spider Tetragnatha mandibulata were assessed in Point Calimere Wildlife and Bird Sanctuary between August 2015 and March 2016. In the present study, the spiders used limited number of plants species. The relationship between web architecture and web-site attributes was estimated using Pearson’s correlation. Number of spiders recorded in the web showed the positive correlation with web horizontal and vertical length of the capture areas (p<0.05). Similarly, the web circumference showed the positive interaction with plant height and canopy width (p<0.05), which clearly indicated the importance of vegetations across the webs of Dark Tetragnathid Spider. Further, the microhabitat selection and utilization could also be impacted by non-trophic factors like structural features of plants that provide architectural supports to spiders. A total of 4620 insect pests comprising seven orders were entangled by the webs of dark tetragnathid spiders. Number of spiders in the web were positively correlated with number of insect pests (p<0.05), which clearly explained that the Dark Tetragnathid spiders restricting pest populations and therefore they are considered as useful organism in biological control.

Info:

Periodical:
International Letters of Natural Sciences (Volume 62)
Pages:
11-19
DOI:
10.18052/www.scipress.com/ILNS.62.11
Citation:
S. Jayakumar et al., "Study on Web-Site Attributes and Predatory Efficiency of Dark Tetragnathid Spider in Point Calimere Wildlife and Bird Sanctuary", International Letters of Natural Sciences, Vol. 62, pp. 11-19, 2017
Online since:
Mar 2017
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