Spatial and temporal distribution of trichoptera (Insecta) larvae in the manzanares river sierra nevada of santa marta (Colombia)

Abstract

The aquatic insects are important bioindicators of water quality in rivers and streams. The order Trichoptera is part of this group, plays an important role in aquatic systems and because of the multiple functions they fulfill, it is essential to know about their biodiversity. This study aimed to know the Trichoptera composition, and its spatial and temporal distribution, in close relationship with the available microhabitats, and some physical and chemical variables, in the middle and lower sections of the Manzanares river basin (Sierra Nevada of Santa Marta, Colombia). A total of eight microhabitats were sampled in three sites from August 2002 to February 2003, and during the rainy and dry seasons. A total sample of 3 316 Trichoptera larvae were collected, belonging to 10 family and 14 genera; six of these genera and one family are new records for the Magdalena department. The caddisflies presented the greatest abundance and richness on leaves in pool, leave in riffles and stones in riffle, where Nectopsyche (28%), Leptonema (17%) and Smicridea (15%) were the more predominant genus. Structure and composition of Trichoptera genus in each site changed in function to the rainfall pattern, and physical and chemical variables presented in the basin, showing the lowest abundance and richness during high rainfall period (October and November), and the greatest abundance and richness in low rainfall period (December, January and February). Likewise, stations with higher values of dissolved oxygen and lower in temperature and conductivity reported the greatest abundance of Trichoptera. The Trichoptera showed affinity to the specific microhabitats, variations in their composition in relationship whit climatic periods and pollution levels of the river. To know others aspects about the Trichoptera distribution, we recommended continuing these studies including annual cycles and increasing the altitudinal gradients.