The construction of small-scale, quasi-mechanistic spatial models of insect energetics in habitat restoration: a case study of beetles in Western Australia
Tomlinson, Sean (2021), The construction of small-scale, quasi-mechanistic spatial models of insect energetics in habitat restoration: a case study of beetles in Western Australia, Dryad, Dataset, https://doi.org/10.5061/dryad.bk3j9kd7d
Study Location, Animal Source and Maintenance
The Gnangara Mound defines a large, elevated area of sand north Perth, Western Australia, subtended by an aquifer which is currently the single most important source of potable water for the city. Although the native vegetation is predominantly Banksia woodlands, which are a nationally protected community, the area was extensively clear-felled in the late 1920’s for the establishment of commercial pine plantations, the removal and restoration of which are planned by 2028. Much of the rest of the region is semi-rural, with sub-urban residential estates developed in the early 1990s. The projection area described by this data set represents approximately 152 square kilometers of this region, encompassing the majority of pine plantations in the area, extending from the southern border of Yanchep National Park in the north, to the northern border of a private conservation reserve, Whiteman Park, in the south.
Thermo-energetic Landscape Context
While the study region has perviously been the subject of microcliamtic modelling, in this study I used the micro_global algorithm in the ‘NicheMapR’ package to achieve this, and tested the accuracy of the model using the data collected by the temperature loggers in the earlier study. The micro_global algorithim employs quasi-mechanistic statistical downscaling of a global climate model on the basis of local geomorphology, soil properties and vegetation to estimate air temperature, relative humidity and wind speed, solar radiation, precipitation, and soil temperature and moisture content. To maintain precision of the microclimatic models at extremely high resolution, these data were extracted at approximately 1 arc-second resolution from published resources, described more fully in the published manuscript. The resulting microclimate model estimated conditions above and below the soil surface for every hour of every day over a ten-year projection period.
The microclimatic model produced was used as the basis for the ectotherm algorithm to project species distributions and habitat suitability for each species, again in the ‘NicheMapR’ package. The ectotherm algorithm is essentially a biophysical model that solves thermal mass-balance equations to estimate heat, water and energy budgets on the basis of specified morphology (body shape), physiology (thermal tolerance thresholds) and behaviour (diurnality or nocturnality), and can be extended to the calculation of dynamic energy budgets across the whole life cycle. The essential tolerance thresholds for the focal beetle species were estimated from the thermal performance experiments decribed in the published manuscript. I used the resulting models to estimate hourly body temperatures (Tb), metabolic rates (cal.h-1), and the activity of each beetle (0 = inactive, 1 = basking and 2 = active). Habitat suitability for the beetles to actively forage was estimated by dividing the average activity by two to estimate the amount of time spent actively foraging. The resulting data were averaged to two estimates (one during daylight hours, the other at night) of Tb, metabolic rate and activity for each species at each 25m2 grid square for each solar day, which are summarised here as averages for the austral summer (between solar days 335 and 60), autumn (between solar days 60 and 151), winter (between solar days 152 and243), and spring (between solar days 244 and 334).
The data presented here are formatted as an R data set. These will open in R as a set of four data frames, which can subsequently be further summarised or exported in any format using the standard R programming language.
Australian Research Council, Award: LP110200304
Australian Research Council, Award: IC150100041