Variation in Detrital Resource Stoichiometry Signals Differential Carbon to Nutrient Limitation for Stream Consumers Across Biomes
Stoichiometric ratios of resources and consumers have been used to predict nutrient limitation across diverse terrestrial and aquatic ecosystems. In forested headwater streams, coarse and fine benthic organic matter (CBOM, FBOM) are primary basal resources for the food web, and the distribution and quality of these organic matter resources may therefore influence patterns of secondary production and nutrient cycling within stream networks or among biomes. We measured carbon (C), nitrogen (N), and phosphorus (P) content of CBOM and FBOM and calculated their stoichiometric ratios (C/N, C/P, N/P) from first- to fourth-order streams from tropical montane, temperate deciduous, and boreal forests, and tallgrass prairie, to compare the magnitude and variability of these resource types among biomes. We then used the ratios to predict nutritional limitations for consumers of each resource type. Across biomes, CBOM had consistently higher %C and %N, and higher and more variable C/N and C/P than FBOM, suggesting that microbial processing results in more tightly constrained elemental composition in FBOM than in CBOM. Biome-specific differences were observed in %P and N/P between the two resource pools; CBOM was lower in %P but higher in N/P than FBOM in the tropical montane and temperate deciduous forest biomes, while CBOM was higher in %P but similar in N/P than FBOM in the grassland and boreal forest biomes. Stable 13C isotopes suggest that FBOM likely derives from CBOM in tropical and temperate deciduous forest, but that additional non-detrital components may contribute to FBOM in boreal forests and grasslands. Comparisons of stoichiometric ratios of CBOM and FBOM to estimated needs of aquatic detritivores suggest that shredders feeding on CBOM are more likely to experience nutrient (N and/or P) than C limitation, whereas collector–gatherers consuming FBOM are more likely to experience C than N and/or P limitation. Our results suggest that differences in basal resource elemental content and stoichiometric ratios have the potential to affect consumer production and ecosystem rates of C, N, and P cycling in relatively consistent ways across diverse biomes.
Keywordsnitrogen phosphorus benthic organic matter elemental ratios macroinvertebrate lotic aquatic ecosystem threshold elemental ratio
We appreciate the help of Matthew Bosiak, John Brant, Walter Dodds, Claire Ruffing, Geoffrey Schwaner, and Katherine Swan in the collection of field samples, and thank Jason Coombs, along with Tom Maddox and Emmy Deng of the University of Georgia Analytical Chemistry Lab for assistance in sample processing. Chao Song, Ford Ballantyne, and Mary Freeman provided guidance on statistical analyses. Logistical support was provided by the US Forest Service Coweeta Hydrologic Laboratory and Luquillo Experimental Forests and LTER sites, and the Konza Prairie and Bonanza Creek LTER sites. Members of SCALER, Dr. Stuart Bunn, and two anonymous reviewers provided constructive comments that greatly improved this manuscript. Funding was provided by a National Science Foundation (NSF) Grant (EF-1064998) to ADR and JSK and an NSF Research Experiences for Undergraduates supplement to ADR and JSK. Field collections were also supported by NSF Grants EF-1065286 (LUQ), EF-1065255 (KNZ), and EF-1065055 (CPC). Partial support during manuscript preparation was provided to KJF from EF-1702506 and ICER-1517823.
- APHA (American Public Health). 2005. Standard methods for examination of water and wastewater. 21st edn. Washington, DC: American Public Health Association.Google Scholar
- Benfield EF, Webster JR, Hutchens JR, Tank JL, Turner P. 2000. Organic matter dynamics along a stream-order and elevational gradient in a southern Appalachian stream. Verhandlungen des Int Verein Limnol 27:1–5.Google Scholar
- Boyero L, Graça MAS, Tonin AM, Pérez J, Swafford A, Ferreira V, Landeira-Dabarca A, Alexandrou M, Gessner MO, McKie BG, Albariño RJ, Barmuta LA, Callisto M, Chará J, Chauvet E, Colón-Gaud C, Dudgeon D, Encalada AC, Figueroa R, Flecker AS, Fleituch T, Frainer A, Gonçalves JF, Helson JE, Iwata T, Mathooko J, M’Erimba C, Pringle CM, Ramírez A, Swan CM, Yule CM, Pearson RG. 2017. Riparian plant litter quality increases with latitude. Sci Rep 7:10562.CrossRefPubMedPubMedCentralGoogle Scholar
- Brett MT, Bunn SE, Chandra S, Galloway AWE, Guo F, Kainz MJ, Kankaala P, Lau DCP, Moulton TP, Power ME, Rasmussen JB, Taipale SJ, Thorp JH, Wehr JD. 2017. How important are terrestrial organic carbon inputs for secondary production in freshwater ecosystems? Freshw Biol 62:1–21.CrossRefGoogle Scholar
- Dodds WK, Collins SM, Hamilton SK, Tank JL, Johnson S, Webster JR, Simon KS, Whiles MR, Rantala HM, McDowell WH, Peterson SD, Riis T, Crenshaw CL, Thomas SA, Kristensen PB, Cheever BM, Flecker AS, Griffiths NA, Crowl T, Rosi-Marshall EJ, El-Sabaawi R, Marti E. 2014. You are not always what we think you eat: selective assimilation across multiple whole-stream isotopic tracer studies. Ecology 95:2757–67.CrossRefGoogle Scholar
- Finlay JC. 2001. Stable-carbon-isotope ratios of river biota: implications for energy flow in lotic food webs. Ecology 82:1052–64.Google Scholar
- Golladay S, Webster JR, Benfield EF. 1983. Factors affecting food utilization by a leaf shredding aquatic insect: leaf species and conditioning time. Holarct Ecol 6:157–62.Google Scholar
- Gulis V, Kuehn KA, Schoettle LN, Leach D, Benstead JP, Rosemond AD. 2017. Changes in nutrient stoichiometry, elemental homeostasis and growth rate of aquatic litter-associated fungi in response to inorganic nutrient supply. ISME J 11:2729–39. https://doi.org/10.1038/ismej.2017.123.CrossRefPubMedGoogle Scholar
- Haugen RK, Slaughter CW, Howe KE, Dingman SL. 1982. Hydrology and climatology of the Caribou-Poker Creeks Research Watershed, Alaska. No. CRREL-82-26.Google Scholar
- Kilpatrick FA, Cobb ED. 1985. Measurement of discharge using tracers. In: Techniques of water-resources investigations of the United States Geological Survey Book 3: Applications of Hydraulics. Department of the Interior, US Geological Survey.Google Scholar
- Kuznetsova A, Brokhoff PB, Christensen RHB. 2016. lmerTest: tests in linear mixed effects models. R Packag version 20-33. https://CRANR-project.org/package=lmerTest. Accessed 1 Mar 2018.
- R Core Team. 2018. R: a language and environment for statistical computing. https://www.r-project.org. Accessed 1 Mar 2018.
- Rüegg J, Dodds WK, Daniels MD, Sheehan KR, Baker CL, Bowden WB, Farrell KJ, Flinn MB, Harms TK, Jones JB, Koenig LE, Kominoski JS, McDowell WH, Parker SP, Rosemond AD, Trentman MT, Whiles MR, Wollheim WM. 2015. Baseflow physical characteristics differ at multiple spatial scales in stream networks across diverse biomes. Landsc Ecol 31:119–36.CrossRefGoogle Scholar
- Sterner RW, Elser JJ. 2002. Ecological stoichiometry. Princeton, NJ: Princeton University Press.Google Scholar
- Trentman MT. 2015. Biotic and abiotic effects on biogeochemical fluxes across multiple spatial scales in a prairie stream network. Master’s Thesis, Division of Biology, Kansas State University.Google Scholar
- Wickham H. 2017. tidyverse: easily install and load the ‘Tidyverse’. R package version 1.2.1. https://cran.r-project.org/package=tidyverse. Accessed 1 Mar 2018.
- Woodward G, Gessner MO, Giller PS, Gulis V, Hladyz S, Lecerf A, Malmqvist B, McKie BG, Tiegs SD, Cariss H, Dobson M, Elosegi A, Ferreira V, Graça MAS, Fleituch T, Lacoursière JO, Nistorescu M, Pozo J, Risnoveanu G, Schindler M, Vadineanu A, Vought LB-M, Chauvet E. 2012. Continental-scale effects of nutrient pollution on stream ecosystem functioning. Science 336:1438–40.CrossRefPubMedGoogle Scholar