Data for: Arthropod diversity in constructed wetlands is affected strongly by shoreline properties but only weakly by grazing

Aim: Aquatic-terrestrial transition zones contain features essential for many species that often benefit wetland biodiversity. Shallow flood-zone areas and reed beds are indicative of natural wetland habitats, however, how such features affect the native arthropod biodiversity in constructed wetlands is scarcely investigated. We asked how these shoreline features, as well as wetland shoreline properties and grazing management, influence riparian arthropod diversities and habitat specializations.

Location: Constructed wetlands, Sweden. 

Taxa: Araneae, Coleoptera, Diptera.

Methods: Taxonomic-, phylogenetic- and trait diversities, along with habitat specialist species richness, were measured in riparian spiders, beetles and selected diptera in 68 constructed wetlands in two regions of Sweden. We ran structural equation models to estimate direct and indirect effects from shoreline slope, flooded grassland, reed areas and grazing management on group diversities, and used multivariate models to determine drivers on habitat specialist species richness.

Results: Flooded grassland and reed area, along with shoreline slope influenced arthropod diversities, and responses differed between arthropod groups and diversity metrices. Spider trait diversity was greater in wetlands with larger flooded grassland areas, whilst beetle trait diversity was reduced. Spider phylogenetic diversity was greater in wetlands containing larger reed areas and in wetlands with steeper shorelines. However, species richness in predatory flies was greater in wetlands with more gentle shorelines. Grazing management had limited effects on arthropod diversities, however, species richness in wetland specialist and generalist predatory dipterans was greater in the absence of grazers in wetlands with greater flooded grassland areas.

Main conclusions: As requirements vary considerably among arthropods, care must be taken when constructing and managing wetlands to benefit arthropod biodiversity. The present results suggest wetlands with a varied shoreline, albeit with greater proportions of flood areas, or multiple adjacent wetlands with varying shores in a wetlandscape and a mild grazing regiment, would accommodate a more diverse arthropod fauna.

Methods
These datasets were collected in 68 constructed wetlands, within two regions in Sweden (Halland and Uppland). Arthropod samples were collected using three sampling methods; SLAM (Sea, Land and Air Malaise) trapping, Pitfall trapping and suction sampling during three periods during the summer of 2020, 1) lat May to early June, 2) late June to early July, and 3) August to early September. The SLAM traps contained water with detergent and were used to collect flying insects. SLAM traps were placed as close to the wetland waters edge as possible, where triplicate 70mm pitfall traps were spaced 5m apart, perpendicular to the shoreline, and within 10m of the SLAM trap, also containing water with detergent. Both SLAM and pitfall traps were used for a duration of 72h. Suction samples were collected using a converted leaf blower at three sampling points similar to placement of pitfall traps perpendicular to the shoreline by placing a 45cm diameter hoop within which we vacuum collected all ground and vegetation. Pitfall trapping was performed during periods 1 and 3 in Uppland and during period 1 in Halland, whereas suction sampling was performed during periods 1 and 3 in Uppland and 2 and 3 in Halland. SLAM trapping was performed during all periods in both regions. From collected arthropods, we identified species of spiders (Araneae), beetles (Coleoptera), dance flies (Hybotidae), dagger flies (Empididae), long-legged flies (Dolichopodidae), and crane flies (Tipulidomorpha [Tipulidae, Limoniidae, Pediciidae, Cylindrotomitidae, Ptychopteridae]). These groups are found in abundance around wetlands and reasonably easy to identify.

On these groups we calculated four types of diversity: total species richness, rarefied species richness, rarefied phylogenetic diversity and rarefied trait diversity. We also categorized species based on habitat specialization, as either wetland specialists, generalists, or terrestrial specialists, based on classifications of Swedish species. All diversity analyses were calculated using R (R-core team 2022).

Total species richness is the quantification of all species per group found at each site.

Rarefied species richness is based on the same total species richnesss, but where the richness has been rarefied by number of individuals collected, using the alpha function in the BAT package (Cardoso, Rigal & Carvalho 2015)
To estimate rarefied phylogenetic diversity, we constructed phylogenetic trees using phyloT v2 (https://phylot.biobyte.de/) based on NCBI taxonomy on genus level where species branch lengths was equal to zero, and total branch length for all genera being equal.  

Rarefied trait diversity traits included feeding traits (herbivores, carnivores, omnivores and detritivores), body size, prey capture strategy, and dispersal mode. Feeding traits were only included in beetles, as these were the only taxa that included different feeding traits, as spiders, dance flies, dagger flies and long-legged flies are carnivorous, and tipulidomorphs are detritivorous. Dispersal mode (classified as ballooning or non-ballooning, [Bell et al., 2005]) and prey capture strategy (net building strategies [Cardoso et al., 2011]) was only included in spiders. Trait distances between species were then calculated using funct.dist (with gower distances) in package mFD (Magneville et al. 2022) and clustered using hclust before calculating rarefied trait diversity in BAT (Cardoso, Rigal & Carvalho 2015).

Habitat properties were deleniated by measuring area covered in flooded grassland, reed beds, and surrounding pastures and meadows, and was calculated using polygons in qGIS (QGIS 2022) within 500m of SLAM collection point. As a proxy for shoreline slope, we calculated the elevational difference between the SLAM trap position and the water level using 1x1 m2 aerial digital elevation models (Markhöjdmodell grid 1+, downloaded on 2023-02-28 from SLU geodataportalen © Lantmäteriet) for each wetland.

References

Bell, J.R., Bohan, D.A., Shaw, E.M. & Weyman, G.S. (2005) Ballooning dispersal using silk: world fauna, phylogenies, genetics and models. Bulletin of Entomological Research, 95, 69-114.

Cardoso, P., Pekár, S., Jocqué, R. & Coddington, J.A. (2011) Global Patterns of Guild Composition and Functional Diversity of Spiders. PLoS ONE, 6, e21710.

Cardoso, P., Rigal, F. & Carvalho, J.C. (2015) BAT - Biodiversity Assessment Tools, an R package for the measurement and estimation of alpha and beta taxon, phylogenetic and functional diversity. Methods in Ecology and Evolution, 6, 232-236.

Magneville, C., Loiseau, N., Albouy, C., Casajus, N., Claverie, T., Escalas, A., Leprieur, F., Maire, E., Mouillot, D. & Villéger, S. (2022) mFD: an R package to compute and illustrate the multiple facets of functional diversity. Ecography, 2022.

QGIS (2022) QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.org.

R Core Team (2022) R: A language and environment for statistical computing. R  Foundation for Statistical Computing. Vienna, Austria.   URL: https://www.R-project.org/.