Environmental and stable isotope data to assess relationships between Anoplolepis gracilipes (yellow crazy ant) abundance and plant-based carbohydrate availability in New Caledonia and Arnhem Land, Australia

Brief description

Environmental, carbohydrate resource, stable isotope, and A. gracilipes abundance data by plot and by site.

Full description

We assessed availability of carbohydrate-rich resources and yellow crazy ant abundance and trophic position in Arnhem Land, Australia and New Caledonia to determine 1) whether yellow crazy ant abundance positively correlates with carbohydrate availability across a range of yellow crazy ant densities; 2) the relative importance of native and non-native sources of carbohydrate; and 3) whether consumption of carbohydrate by yellow crazy ants increases with its availability as evidenced by declining trophic position.  In each location, we selected five 20 m x 20 m sites with similar vegetation that were occupied by yellow crazy ants Within each site, we positioned nine 1 m-diameter sample plots 10 m apart in a 3 row x 3 column grid. We conducted the field work in the early dry season in each country (April in New Caledonia and June 2012 in Arnhem Land).

We obtained four measures of relative yellow crazy ant abundance: abundance on two different kinds of lures (cat food and jam), nest density, and card counts.  For card counts, at the center of each of the nine plots, we placed a 20 x 20 cm laminated card with four equivalent-sized squares on the ground. We recorded the number of yellow crazy ants that walked over the square that was first touched for 30 seconds. After card counts, and in the same plots, we placed lures consisting of half teaspoons of tuna cat food and jam spaced 10 cm apart. Lures were left for 30 minutes after which we counted and identified by sight ants at and within 1 cm of each lure.  We conducted card counts and luring in early morning or late afternoon when temperatures were 22.5-25.5°C. We measured nest density within a central 10 x 10 m plot within each site by placing cat food lures every ~2.5 m and following foraging workers to their nests. We considered a nest entrance closer than 40 cm to the next nearest entrance to be for the same nest. 

To characterize carbohydrate availability, within each 1 m diameter plot we carefully scanned vegetation for hemipterans, flowers, and extrafloral nectaries. When plants had approximately < 100 leaves within the plot, we examined all leaves and the parts of the stem that were within the plot for hemipterans. When plants shorter than 3 m had > 100 leaves within the plot, we examined half of the leaves by selecting every second terminal branch within the plot for examination. We recorded the number of hemipterans and fresh flowers and noted when they were being tended or occupied, respectively, and collected representative samples of tended hemipterans for identification.  We estimated the number of extrafloral nectaries in each plot to be the same as the number of Acacia phyllodes in the plot.   

We calculated honeydew production over 24 hours at each site using the standardised method of (Moir et al. 2018). We did this by weighing and identifying each specimen collected in the field to the lowest taxonomic rank possible.

Within each 1 m diameter plot, we counted the number of stems, estimated leaf area, and characterized the ground cover, canopy cover, and vegetation complexity. To estimate total leaf area contributed by each plant, for plants with fewer than 100 leaves, we counted all leaves; for plants with greater than 100 leaves, we counted a subset of leaves and multiplied by the reciprocal of the fraction the subset represented to achieve the total number of leaves that plant contributed to the plot. For leaves that were more or less ovate, we measured leaf length and width and approximated leaf area with the equation

Leaf area = 0.66256 (l x w)^1.01156

where l= leaf length and w= leaf width (Antunes et al. 2008). Few leaves were not generally ovate; for those we approximated area either as rectangles (e.g., for long thin Acacia phyllodes) or triangles (e.g., bracken).  We characterized ground cover by estimating percent ground cover of bare soil, leaf litter, rocks (>1 cm), grass, stems, and coarse woody debris (> 2 cm diameter). We estimated canopy cover within each 1 m diameter plot at 10 cm, >10 cm-3 m and > 3 m. To assess vegetation complexity, we placed a 2 m pole marked at 10 cm intervals in the middle of each 1 m plot and recorded the number of times plants touched the pole, the number of 10 cm size classes in which a plant touched the pole, and a height profile based on a weighted mean of height touches (Gibson et al. 1987).

We calculated the relative trophic position of yellow crazy ants at all sites with stable isotope analyses. We collected a minimum of four yellow crazy ant samples (consisting of 6-10 ants) per site, and a minimum of three hemipteran, spider, and plant samples per site, froze the arthropods at -20˚C for 24h, and then oven dried all samples at 60˚C for 24 hours. Yellow crazy ants were collected either before lure placement, or during lure placement from areas away from lures. We opportunistically collected hemipterans, spiders, and plants harbouring hemipterans within each 20m x 20m area but only after ant and carbohydrate assessments. Prior to stable isotope analysis, we removed ant gasters to avoid biasing calculations with recently ingested material. A minimum of 0.6 mg of each sample type was ground and weighed into tin capsules. Samples were analysed with a continuous flow system consisting of a Delta V Plus mass spectrometer connected with a Thermo Flush 1112 via Conflo IV (Thermo-Finnigan, Germany) at the West Australian Biogeochemistry Centre at the University of Western Australia.

We calculated trophic position with a modification of Post (Post 2002) as described in Lach et al. (2010).  

Notes

This dataset consists of a workbook containing 3 spreadsheets (metadata, site level data and plot level data for each site) saved in both MS Excel (.xlsx) and Open Document (.ods) formats.