Carbon and nitrogen stoichiometry and nitrogen cycling rates in streams

TitleCarbon and nitrogen stoichiometry and nitrogen cycling rates in streams
Publication TypeJournal Article
Year of Publication2004
AuthorsDodds, WK, Marti, E, Tank, J, Pontius, JL, Hamilton, SK, Grimm, NB, Bowden, WB, McDowell, WH, Peterson, BJ, Valett, HM, Webster, JR, Gregory, S
Pagination458 -467
Accession NumberKNZ00925
Keywordscarbon, Carbon:Nitrogen ratio, nitrogen, stoichiometry, streams

Stoichiometric analyses can be used to investigate the linkages between N and C cycles and how these linkages influence biogeochemistry at many scales, from components of individual ecosystems up to the biosphere. N-specific NH4 + uptake rates were measured in eight streams using short-term 15N tracer additions, and C to N ratios (C:N) were determined from living and non-living organic matter collected from ten streams. These data were also compared to previously published data compiled from studies of lakes, ponds, wetlands, forests, and tundra. There was a significant negative relationship between C:N and N-specific uptake rate; C:N could account for 41% of the variance in N-specific uptake rate across all streams, and the relationship held in five of eight streams. Most of the variation in N-specific uptake rate was contributed by detrital and primary producer compartments with large values of C:N and small values for N-specific uptake rate. In streams, particulate materials are not as likely to move downstream as dissolved N, so if N is cycling in a particulate compartment, N retention is likely to be greater. Together, these data suggest that N retention may depend in part on C:N of living and non-living organic matter in streams. Factors that alter C:N of stream ecosystem compartments, such as removal of riparian vegetation or N fertilization, may influence the amount of retention attributed to these ecosystem compartments by causing shifts in stoichiometry. Our analysis suggests that C:N of ecosystem compartments can be used to link N-cycling models across streams.