Data from: Urbanization-driven climate change increases invertebrate lipid demand, relative to protein—a response to dehydration
Cite this dataset
McCluney, Kevin; Becker, Jamie (2020). Data from: Urbanization-driven climate change increases invertebrate lipid demand, relative to protein—a response to dehydration [Dataset]. Dryad. https://doi.org/10.5061/dryad.jm63xsj8q
1. Climatic change alters not only animal energy balance, but also water balance, but this latter topic has received less attention. Water can be obtained through consumption of moist food and metabolism of dry food. The breakdown of carbohydrates, lipids, and proteins can produce metabolic water. Metabolism of lipids produces large amounts of water, whereas excretion of nitrogenous waste related to protein metabolism requires water losses.
2. Here we tested the hypothesis that climatic shifts associated with urbanization influences animal lipid demand relative to protein, due to shifts in water balance.
3. We placed artificial diets high in lipid or protein, and either with or without supplemented water, at 16 pairs of sites along an urbanization gradient in Toledo, OH, USA.
4. Lipid consumption, relative to protein, increased with urbanization and mean temperature, but water supplementation reduced the magnitude of this association. Ants were ~50% of the observed consumers.
5. These results suggest that shifts in nutritional demand with climatic change are partially predictable from physiological first principles related to water balance and nutrient metabolism. Because ants and other arthropods play key roles in many food webs and ecosystems, increased demand for lipids with urbanization or climate change could have major consequences for ecosystem services (e.g. urban waste removal, seed predation). Overall, our results suggest that warming related to urbanization increases animal demand for lipids, in part to maintain water balance, and this could have important implications for both animal health and ecosystem services.
We selected 16 pairs of sites along an urbanization gradient (Figure 1, Table S1) within Toledo, OH and surrounding areas, examining the effects of impervious surface at local scales (50 m radius buffer) nested within a coarser scale (500 m radius buffer). Pairs were distributed throughout the region, no more than 15 km from the city center and no less than 3 km from each other. We selected each site pair by considering Toledo’s landscape features (e.g. impervious surface), accessibility of sites, and obtained permissions.
Diets and Consumption Measurement
Two artificial diets varying in lipid and protein were used in this study. The high-lipid diet was composed of 1:1:5 Protein: Carbohydrate: Lipid (P: C: L) and the high-protein diet had a 5:1:1 P: C: L ratio (Table S2). The protein components were composed of three different foods, because each food item did not offer an even and complete suite of amino acids. The diet’s final amino acid profile was validated by Lebensmittel Consulting Co, Fostoria, OH. Diets were deposited into clean metal bottlecaps and dried at 50°C in a drying oven (100L Gravity Oven, model 51030520, Fisher Scientific, Hampton, NH). Bottlecaps were then attached to small petri dishes (Figure S1) with a non-toxic glue dot (0.5” removable dot, Glue Dots Intl., Germantown, WI). The bottlecaps were used for simplicity, while the small petri dish captured particles of food displaced from the bottlecap (modified from Clissold et al. 2014). Food-filled bottlecaps were placed inside small labeled plastic bags and then weighed to 0.01 mg (Micro Balance, model XPE56, Mettler Toledo, Columbus, OH). When diets were collected from the field, they were placed into the same bags as before. Diets were then dried inside their open plastic bags, dirt and frass was removed, then they were weighed a final time within their bags, with differences in mass indicating consumption.
Within each site, we selected six trees that were no less than 10 m apart and placed one set of consumption measurement materials at each tree (Figure S1). Each consumption measurement setup was comprised of a high-lipid and high-protein diet, a wet or dry water pillow (small pouches filled with a polymer that absorbs water; Cricket water pillows, Zilla, Franklin, WI), and a cage to exclude mammals. The addition of a water source allowed us to isolate the effects of water balance from metabolic rate on consumption. The wet and dry pillows were assigned to measurement locations in a stratified order at each site. Cages were made of hardware wire laced together with green floral wire and were fixed to the ground with landscape staples. To prevent rain or UV radiation from altering the pillows and diet, we placed a covering on the cages, made of a large petri dish sprayed with translucent UV protectant (Model 1305 Gallery Series, Krylon Products Group, Cleveland, OH). The lid could also be removed to make observations with minimal disturbance to the arthropods inside.
We measured consumption three times at each site, from June – August 2016, shuffling the order in which sites were visited (pairs of sites were initially randomly assigned to one of four groups and within each group the order of site visits was reversed during the second trial). Each measurement took place over three days: cages were placed on the first day, sites were visited during the morning and at night on the second day, to make observations of consumption, and cages were removed on the third day. Cages were not placed during a storm, but cages were visited on the second and third day, regardless of weather conditions.
We measured temperature and humidity for each survey using three data loggers (Thermochron iButton, model DS 1923, Maxim Inc., San Jose, CA), placed within cages, spread evenly within a site. Each iButton was attached to a Styrofoam covering protecting it from solar radiation while allowing exchange with the atmosphere. With each visitation, we measured soil moisture (SM 150 soil moisture sensor, Dynamax, Houston, TX) and canopy cover (Mobile application software, HabitApp v. 1.1, Scrufster) three times, within 0.5 m of each cage. Canopy cover measures via HabitApp were verified to be comparable to a densiometer before use. We also identified invertebrates located in our experimental setups during each visit via photographs. Most of these photographs were taken by the same person (J. Becker) and this person performed all identifications from photographs. Some invertebrates moved too quickly to be photographed. These individuals were noted, but not included in analyses, due to the lack of identification. This could have resulted in under-recording highly-mobile taxa.
AvgPerImp = The mean percentage of impervious surface within 50 m radius of the site
AvgLeaten = The mean amount of lipid consumed for that cage, across all dates, in mg
AvgPeaten = The mean amount of protein consumed for that cage, across all dates, in mg
AvgCeaten = The mean amount of carbohydrate consumed for that cage, across all dates, in mg
AvgLtoP = The mean ratio of lipid to protein consumed for that cage, across all dates
AvgLandCeaten = The mean amount of carbohydrate and lipid (combined) consumed for that cage, across all dates, in mg
AvgLandCtoP = The mean ratio of carbohydrate and lipid (combined) to protein consumed for that cage, across all dates
AvgRH = The mean relative humidity for a site, across all dates
AvgCan = The mean % canopy cover for a cage, across all dates
AvgSM = The mean volumetric soil moisture (%) near a cage, across all dates
AvgTemp = The mean temperature for a site, across all dates