Periphyton carbon and nitrogen stable isotopes detect agricultural stressors in low-order streams
Cite this dataset
Whorley, Sarah (2022). Periphyton carbon and nitrogen stable isotopes detect agricultural stressors in low-order streams [Dataset]. Dryad. https://doi.org/10.5061/dryad.05qfttf35
Shifts in the stable isotope signatures of carbon (C) and nitrogen (N) in ecological materials have the potential to indicate environmental disturbances. This study examined the δ13C‰ and δ15N‰ ratios of stream water and periphyton from low-order streams in a landscape influenced by agricultural activities. Our key purpose was to assess the influence of best management practice (BMP) presence and age on C and N isotope values as a potential water-quality assessment. We collected stream water and periphyton from 19 streams within the Upper Delaware River watershed in New York, USA, in each of 4 management categories: 1) recently applied BMP treatments, 2) long-standing BMPs, 3) streams lacking BMPs, and 4) minimally disturbed reference streams. We sampled and analyzed water and periphyton for δ13C‰ and δ15N‰ in a repeated-measures design (BMP category ´ time) from April to November 2013. There were large seasonal differences in stream water δ13C-dissolved organic C (DIC)‰ and δ15NO3-N‰, with strong differences between reference and agricultural streams. Periphyton δ13C‰ and δ15N‰ values also differed strongly across streams draining land with agricultural activities, with 85% higher periphyton δ15N‰ signals in all agricultural categories vs reference streams. Periphyton diatom and chlorophyte taxonomic proportions showed the strongest relationship with periphyton δ13C‰ values, where diatoms were negatively associated with increasing δ13C‰. These results suggest that aqueous and periphytic stable isotopes were sensitive in detecting persistent effects of agriculture on these streams despite BMP mitigation, where nutrient (orthosphosphate, nitrite, and ammonia) levels were non-indicative. These results also suggest that BMPs may not have fully eliminated the negative impacts of agricultural stressors on water quality in impacted streams.
Please see associated manuscript methods for sample collection and data generation processes.
Use Excel to read data. ReadMe.txt file contains definitions for all variables. Please see published manuscript for methodologies for all variables.