Reconstructing midge consumer–resource dynamics using carbon stable isotope signatures of archived specimens

Abstract

Population cycles can be caused by consumer–resource interactions. Confirming the role of consumer–resource interactions, however, can be challenging due to an absence of data for the resource candidate. For example, interactions between midge larvae and benthic algae likely govern the high-amplitude population fluctuations of Tanytarsus gracilentus in Lake Mývatn, Iceland, but there are no records of benthic resources concurrent with adult midge population counts. Here, we investigate consumer population dynamics using the carbon stable isotope signatures of archived T. gracilentus specimens collected from 1977 to 2015, under the assumption that midge δ13C values reflect those of resources they consumed as larvae. We used the time series for population abundance and δ13C to estimate interactions between midges and resources while accounting for measurement error and possible preservation effects on isotope values. Results were consistent with consumer–resource interactions: high δ13C values preceded peaks in the midge population, and δ13C values tended to decline after midges reached high abundance. One interpretation of this dynamic coupling is that midge isotope signatures reflect temporal variation in benthic algal δ13C values, which we expected to mirror primary production. Following from this explanation, high benthic production (enriched δ13C values) would contribute to increased midge abundance, and high midge abundance would result in declining benthic production (depleted δ13C values). An additional and related explanation is that midges deplete benthic algal abundance once they reach peak densities, causing midges to increase their relative reliance on other resources including detritus and associated microorganisms. Such a shift in resource use would be consistent with the subsequent decline in midge δ13C values. Our study adds evidence that midge–resource interactions drive T. gracilentus fluctuations and demonstrates a novel application of stable isotope time-series data to understand consumer population dynamics.