The response of respiration to temperature in plants can be considered at both short- and long-term temporal scales. Short-term temperature responses are not well described by a constant Q10 of respiration, and longer-term responses often include acclimation. Despite this, many carbon balance models use a static Q10 of respiration to describe the short-term temperature response and ignore temperature acclimation.
We replaced static respiration parameters in the ecosystem model photosynthesis and evapo-transpiration (PnET) with a temperature-driven basal respiration algorithm (Rdacclim) that accounts for temperature acclimation, and a temperature-variable Q10 algorithm (Q10var). We ran PnET with the new algorithms individually and in combination for 5 years across a range of sites and vegetation types in order to examine the new algorithms' effects on modeled rates of mass- and area-based foliar dark respiration, above ground net primary production (ANPP), and foliar respiration–photosynthesis ratios.
The Rdacclim algorithm adjusted dark respiration downwards at temperatures above 18°C, and adjusted rates up at temperatures below 5°C. The Q10var algorithm adjusted dark respiration down at temperatures below 15°C. Using both algorithms simultaneously resulted in decreases in predicted annual foliar respiration that ranged from 31% at a tall-grass prairie site to 41% at a boreal coniferous site. The use of the Rdacclim and Q10var algorithms resulted in increases in predicted ANPP ranging from 18% at the tall-grass prairie site to 38% at a warm temperate hardwood forest site.
The new foliar respiration algorithms resulted in substantial and variable effects on PnETs predicted estimates of C exchange and production in plants and ecosystems. Current models that use static parameters may over-predict respiration and subsequently under-predict and/or inappropriately allocate productivity estimates. Incorporating acclimation of basal respiration and temperature-sensitive Q10 have the potential to enhance the application of ecosystem models across broad spatial scales, or in climate change scenarios, where large temperature ranges may cause static respiration parameters to yield misleading results.