Food‐web structure of willow‐galling sawflies and their natural enemies across Europe

Abstract

Abstract. Communities consist of species and their interactions. They can thus be described as networks, with species as nodes and interactions as links. Within such networks, the diversity of nodes and the distribution of links may affect patterns of energy transfer between trophic levels, the dynamics of the system, and the outcome in terms of ecosystem functioning. To date, most descriptions of networks have focused on single or relatively few sites, and have oftentimes been built on poorly resolved nodes and links. Yet, comparisons of local interaction networks reveal variation in space and in time, thus spurring interest in methods and theory for understanding patterns, drivers, and consequences of this variation. Progress in this field relies on access to replicate samples of comparable food webs across large spatiotemporal scales, resolved to species rather than to compound nodes. Due to the massive efforts required, high-quality data sets are still scarce. We created a data set on a single community type sampled across Europe: willow species (Salix), willow-galling sawflies (Hymenoptera: Tenthredinidae: Nematinae: Euurina), and their natural enemies (hymenopteran parasitoids and coleopteran, lepidopteran, dipteran, and hymenopteran inquilines). Each sample was referenced in space and time, and each node resolved with the highest possible resolution, including taxonomic affinity, gall type (for herbivores), and mode of parasitism (for natural enemies). Galler survival and link structure were resolved by dissection and rearing of gall inhabitants. In total, the data set is based on 641 site visits over 29 years, and on 165,424 galls representing 96 herbivore nodes and 52 plant nodes. The dissections and rearings yielded 42,129 natural enemies belonging to 126 species, and revealed 1,173 different links. The spatiotemporal and taxonomic resolution of these data make them amenable to analyses of both ecological and evolutionary processes of network assembly. Thus, this data set will facilitate testing of important hypotheses in recent community theory, concerning, e.g., the sampling effort needed to adequately describe interaction structure within ecological communities, the impact of environmental conditions and biotic filters on the distribution of species and their interactions, and the relationship between the global "metaweb" and its local realizations.

Bringing Elton and Grinnell together: a quantitative framework to represent the biogeography of ecological interaction networks

“…We now turn to an illustration of our theory with the analysis of an empirical dataset of host-parasite networks sampled throughout the south-north environmental gradient in continental Europe (Kopelke et al 2017). Our objective here is to illustrate potential applications of the approach outlined above, rather than to specifically describe the biogeography of this particular community.…”

“…Full details about data collection and species identification are provided in (Kopelke et al 2017). Full details about data collection and species identification are provided in (Kopelke et al 2017).…”

“…The current study represents the first analysis of the full data set from a spatial perspective. Full details about data collection and species identification are provided in (Kopelke et al 2017). Annual mean temperature and precipitation were obtained from WorldClim using the R package dismo (Hijmans 2015) and GPS coordinates of the sampling locations.…”

Artificial Intelligence for Ecological and Evolutionary Synthesis

“…For Markov logic, it means a set of formulas in first-order logic. For this example, we used Markov logic to build a knowledge base for ecological interactions around the Salix dataset [43]. The Salix dataset has 126 parasites, 96 species of gallers (insects), and 52 species of salix, forming a tritrophic ecological network (P arasite → Galler → Salix).…”

“…A sample of three tables for the Salix dataset[43]. Species are denoted by the first six letters of their names while sites are numbered from 1 to 374.…”