Abstract
The analysis of interaction networks across spatial environmental gradients is a powerful approach to investigate the responses of communities to global change. Using a combination of DNA metabarcoding and traditional molecular methods we built bipartite Drosophila – parasitoid food webs from six Australian rainforest sites across gradients spanning 850 m in elevation and 5°C in mean temperature. Our cost‐effective hierarchical approach to network reconstruction separated the determination of host frequencies from the detection and quantification of interactions. The food webs comprised 5–9 host and 5–11 parasitoid species at each site, and showed a lower incidence of parasitism at high elevation. Despite considerable turnover in the relative abundance of host Drosophila species, and contrary to some previous results, we did not detect significant changes to fundamental metrics of network structure including nestedness and specialisation with elevation. Advances in community ecology depend on data from a combination of methodological approaches. It is therefore especially valuable to develop model study systems for sets of closely‐interacting species that are diverse enough to be representative, yet still amenable to field and laboratory experiments.
Highlights
The geographic distribution of a species is determined by its intrinsic abiotic limits and by its interactions with other species
One valuable approach for understanding how ecological communities will respond to environmental change is to study how food webs and other networks of interspecific interactions vary along elevational gradients (Tylianakis and Morris 2017, Pellissier et al 2018, Baiser et al 2019, Gravel et al 2019)
Contrary to expectations based on previous work (Kitson et al 2019), metabarcoding did not allow parasitoid identification and we could not use this approach to document and quantify host–parasitoid interactions
Summary
The geographic distribution of a species is determined by its intrinsic abiotic limits and by its interactions with other species. Individual populations of species do not respond to environmental changes in isolation from the species with which they interact. Interspecific interactions themselves respond to environmental change in diverse ways (Tylianakis et al 2008, Guiden et al 2019, Thierry et al 2019). One valuable approach for understanding how ecological communities will respond to environmental change is to study how food webs and other networks of interspecific interactions vary along elevational gradients (Tylianakis and Morris 2017, Pellissier et al 2018, Baiser et al 2019, Gravel et al 2019). The structure of communities can be summarised with network-level metrics that can reveal shifts that are not apparent in simple connectance food webs or in qualitative descriptors of diversity such as species richness (Tylianakis et al 2007, Delmas et al 2019)
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