Aridity and land use negatively influence a dominant species' upper critical thermal limits

Abstract

Understanding the physiological tolerances of ectotherms, such as thermal limits, is important in predicting biotic responses to climate change. However, it is even more important to examine these impacts alongside those from other landscape changes: such as the reduction of native vegetation cover, landscape fragmentation and changes in land use intensity (LUI). Here, we integrate the observed thermal limits of the dominant and ubiquitous meat ant Iridomyrmex purpureus across climate (aridity), land cover and land use gradients spanning 270 km in length and 840 m in altitude across northern New South Wales, Australia. Meat ants were chosen for study as they are ecosystem engineers and changes in their populations may result in a cascade of changes in the populations of other species. When we assessed critical thermal maximum temperatures (CT_max) of meat ants in relation to the environmental gradients we found little influence of climate (aridity) but that CT_max decreased as LUI increased. We found no overall correlation between CT_max and CT_min. We did however find that tolerance to warming was lower for ants sampled from more arid locations. Our findings suggest that as LUI and aridification increase, the physiological resilience of I. purpureus will decline. A reduction in physiological resilience may lead to a reduction in the ecosystem service provision that these populations provide throughout their distribution.

Keywords: Ant; Climate change; Critical thermal maximum; Critical thermal minimum; Formicidae; Insect; Land cover; Land use; Landscape adaptation; Thermal stress.

Figure 1. Sites used in this study in northern New South Wales, Australia (see insert) with relative values for CT_max (A), land use intensity (B), aridity (C) and clay (D) shown.

Maps generated using Map data © OpenStreetMap contributors. The size of the circle is indicative of the mean value of the given variable (i.e. the larger the circle, the higher the value and the contrary). Image produced using the Leaflet package (version 1.1.0.9000, http://rstudio.github.io/leaflet/) within R statistical software (version 3.4.3). The R package OpenStreetMap is licensed under a GNU General Public License (GPL-2) (https://cran.r-project.org/web/packages/OpenStreetMap/index.html) and was used to extract map tiles from OpenStreetMap which is licensed on terms of the Open Database License, ‘ODbL’ 1.0. (http://wiki.osmfoundation.org/wiki/Licence).

Figure 2. Random effect estimates of model coefficients using best linear unbiased prediction (BLUP) and 95% confidence intervals of the intercepts (A and C) and CT_max (B) and CT_min (D) across sites.

Figure 3. 95% confidence intervals on the selected CT_max and CT_min models for the factors: land use intensity (LUI: A and C) and clay (B and D).

Figure 4. Three measures of warming tolerance (3 months, 12 months and 36 months); based on location modelled ANUCLIM data for three different sampling periods) relative to aridity index for each site.