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Modelling black fly production dynamics in blackwater streams
Author(s) -
BENKE ARTHUR C.,
PARSONS KEITH A.
Publication year - 1990
Publication title -
freshwater biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.297
H-Index - 156
eISSN - 1365-2427
pISSN - 0046-5070
DOI - 10.1111/j.1365-2427.1990.tb00316.x
Subject(s) - blackwater , snag , environmental science , biomass (ecology) , streams , hydrology (agriculture) , ecology , habitat , hydrobiology , black fly , biology , geology , computer network , geotechnical engineering , environmental engineering , aquatic environment , computer science , larva
SUMMARY. 1. Two predictive models were employed along with intensive field sampling to estimate production of black flies ( Simulium spp.) on snags (submerged wood) in three blackwater streams on the Georgia Coastal Plain of the southeastern U.S.A. One model predicts daily growth rate from temperature and hydrograph pattern; the other predicts habitat abundance (of snags) from river height. 2. In the sixth order Ogeechee River, annual production was twice as high in 1982 (7.1 g dry mass [=DM] m −2 of snag surface) as in 1983 (3.6 g DM m −2 ). When converted to production per m 2 of river bottom, values were 35–40% of the snag surface estimates. Annual production was much lower in fourth order Black Creek (1982, 1.3 g DM m −2 of snag surface) and much higher in the sixth order Satilla River (1975, 15.6–40.0 g DM m −2 ). 3. There was a distinct bimodal pattern of black fly production in the Ogeechee River in both years, with peaks occurring in winter and summer. Similar bimodal patterns of production were found in Black Creek and in the Satilla River. Although there appears to be an intrinsic component to the bimodal pattern, production peaks (growth rate and biomass) appear to be associated with initial stages of flooding. 4. Annual production/biomass ratios (37–85) are the highest reported for black fly populations. The variation of annual P/B ratios among sites was more strongly dependent on the temporal distribution of standing stock biomass than on differences in growth rates. Variation in production among sites appears to be due to differences in current velocity, hydro‐graph variability, and abundance of coexisting consumers.