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Effects of productivity, consumers, competitors, and El Nino events of food chain patterns in a rocky intertidal community
We experimentally manipulated nutrient input to a rocky intertidal community, using nutrient-diffusing flowerpots, to determine (i) whether nutrients limited intertidal productivity, (ii) how a large-scale oceanographic disturbance (an El Nino event) affected patterns of nutrient limitation, (iii) t...
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Published in: | Proceedings of the National Academy of Sciences - PNAS 1996-11, Vol.93 (24), p.13855-13858 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We experimentally manipulated nutrient input to a rocky intertidal community, using nutrient-diffusing flowerpots, to determine (i) whether nutrients limited intertidal productivity, (ii) how a large-scale oceanographic disturbance (an El Nino event) affected patterns of nutrient limitation, (iii) the relative impacts of molluscan grazers and nutrient limitation, and (iv) if responses to experimental nutrient addition among trophic levels were more consistent with prey-dependent or ratio-dependent food chain models. Nutrients measurably increased the abundance of micrograzers (amphipods and chironomid larvae), but not algal biomass, during the summer of an El Nino year. Nutrients had no effects in two non-EI Nino years and during the autumn of an El Nino year. Adding nutrients did not affect food chain stability as assessed by temporal variation in algal biomass and micrograzer abundance. Large molluscan grazers caused large reductions in micrograzers and smaller reductions in algae, indicating consistent consumer effects. The results demonstrate that in this intertidal community, nutrient limitation can occur under conditions of nutrient stress, that top-down grazing effects are typically stronger than bottom-up nutrient effects, and that prey-dependent models are more appropriate than ratio-dependent models |
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ISSN: | 0027-8424 1091-6490 |
DOI: | 10.1073/pnas.93.24.13855 |