Oral Presentation Society for Freshwater Science 2025 Annual Meeting

Environmental influences on loose equilibrium in benthic insect communities: are time-lagged effects the norm? (117623)

Daniel J McGarvey 1 , Hector J Esparra-Escalera 2 , Stephanie M Parker 3 , Beija K Gore 4 , Jonathan R Juarez 5 , Hazel D Quarterman 6 , Natalia Vargas López 7 , Rodrigo M Gonzalez 8 , Victoria M Secondine 9 , Jordyn R Solliday 10 , Jason Aguirre 11 , Carlos Vargas 12 , Alexis Reifsteck 13 , Alexandra Yokomizo 14 , Eli Wess 15 , Breanna Ondich 16 , Deandre Presswood 17 , Patina Mendez 18
  1. Virginia Commonwealth University, Richmond, VIRGINIA, United States
  2. Wayne State University, Detroit, MI, USA
  3. National Ecological Observatory Network, Battelle, Boulder, CO, USA
  4. Virginia Tech, Blacksburg, VA, USA
  5. California State University, Bakersfield, Bakersfield, CA, USA
  6. Georgia Southern University, Statesboro, GA, USA
  7. University of Georgia, Athens, GA, USA
  8. University of Nebraska, Omaha, Omaha, NE, USA
  9. University of Kansas, Lawrence, KS, USA
  10. Montana State University , Bozeman, MT, USA
  11. University of Pittsburgh, Pittsburgh, PA, USA
  12. University of Georgia, Athens, GA, USA
  13. Missouri State University , Springfield, MO, USA
  14. University of California, Davis , Davis, CA, USA
  15. University of Central Arkansas, Conway, AR, USA
  16. University of Georgia, Athens, GA, USA
  17. University of Nevada, Reno, Reno, NV, USA
  18. University of California, Berkeley, Berkeley, CA, USA

Prior examination of National Ecological Observatory Network (NEON) data found that benthic insect communities are largely stable through time, consistent with the loose equilibrium hypothesis. This study extends the previous analysis by searching for environmental effects of insect community structure. Time-series of six environmental variables – discharge, water temperature, dissolved oxygen, specific conductivity, nitrate, and turbidity – were downloaded for each of 20 NEON streams, then compared to time-series of the insect community data. Specifically, we: (i) calculated the distance between each insect community sample and the centroid of the respective ordination plot (non-metric multidimensional scaling); (ii) built a monthly time-series of the sample-to-centroid distances for insect community (i.e., NEON stream); (iii) compared the insect time-series with time-series (mean monthly averages) for each of the six environmental variables; and (iv) used Pearson correlation coefficients to assess the strength of association between insect and environmental time-series. Cross-correlation was also used to test for lagged or delayed environmental effects because insect community structure at a given moment may reflect antecedent, rather than contemporary environmental conditions. Time lags ranging from 0-6 months were simulated by shifting the insect time-series backwards, then recalculating correlation coefficients. Contemporary environmental conditions showed the strongest correlation in only 20 of 120 comparisons (6 variables × 20 streams). In most comparisons, the strongest correlation occurred at a lag of 4-6 months. This project highlights the potential importance of antecedent environmental effects and demonstrates the flexibility of NEON data.