Changes in invertebrate food web structure between high- and low-productivity environments are driven by intermediate but not top-predator diet shifts. (26th October 2022)

• Record Type: Journal Article
• Authors: Miller-ter Kuile, Ana; Apigo, Austen; Bui, An; Butner, Kirsten; Childress, Jasmine N.; Copeland, Stephanie; DiFiore, Bartholomew P.; Forbes, Elizabeth S.; Klope, Maggie; Motta, Carina I.; Orr, Devyn; Plummer, Katherine A.; Preston, Daniel L.; Young, Hillary S.
• Is Part Of: Biology letters. Volume 18:Number 10(2022)
• Publication Date: 2022-10-26
• Subjects: food chain -- Araneae -- diet DNA metabarcoding -- stable isotope analysis; Biology -- Periodicals; 570.5
• DOI: 10.1098/rsbl.2022.0364
• Languages: English
• ISSNs: 1744-9561

Abstract

Abstract : Predator–prey interactions shape ecosystem stability and are influenced by changes in ecosystem productivity. However, because multiple biotic and abiotic drivers shape the trophic responses of predators to productivity, we often observe patterns, but not mechanisms, by which productivity drives food web structure. One way to capture mechanisms shaping trophic responses is to quantify trophic interactions among multiple trophic groups and by using complementary metrics of trophic ecology. In this study, we combine two diet-tracing methods: diet DNA and stable isotopes, for two trophic groups (top predators and intermediate predators) in both low- and high-productivity habitats to elucidate where in the food chain trophic structure shifts in response to changes in underlying ecosystem productivity. We demonstrate that while top predators show increases in isotopic trophic position ( δ 15 N) with productivity, neither their isotopic niche size nor their DNA diet composition changes. Conversely, intermediate predators show clear turnover in DNA diet composition towards a more predatory prey base in high-productivity habitats. Taking this multi-trophic approach highlights how predator identity shapes responses in predator–prey interactions across environments with different underlying productivity, building predictive power for understanding the outcomes of ongoing anthropogenic change.