Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability

Abstract

We assess the significance of high-frequency variability of environmental parameters (sunlight, precipitation, temperature) for the structure and function of terrestrial ecosystems under current and future climate. We examine the influence of hourly, daily, and monthly variance using the Ecosystem Demography model version 2 in conjunction with the long-term record of carbon fluxes measured at Harvard Forest. We find that fluctuations of sunlight and precipitation are strongly and nonlinearly coupled to ecosystem function, with effects that accumulate through annual and decadal timescales. Increasing variability in sunlight and precipitation leads to lower rates of carbon sequestration and favors broad-leaved deciduous trees over conifers. Temperature variability has only minor impacts by comparison. We also find that projected changes in sunlight and precipitation variability have important implications for carbon storage and ecosystem structure and composition. Based on Intergovernmental Panel on Climate Change model estimates for changes in high-frequency meteorological variability over the next 100 years, we expect that terrestrial ecosystems will be affected by changes in variability almost as much as by changes in mean climate. We conclude that terrestrial ecosystems are highly sensitive to high-frequency meteorological variability, and that accurate knowledge of the statistics of this variability is essential for realistic predictions of ecosystem structure and functioning.carbon fluxes | climate variability | climate-ecosystem models | terrestrial biosphere | Harvard Forest

Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) dynamic vegetation–land surface model

“…As DSTs gradually fell, NE trees captured more light but had a lower needle temperature, resulting in lower NPP. Such strong photosynthesistemperature responses have been found to play a major role when simulating future vegetation dynamics (Sitch et al, 2008;Medvigy et al, 2010) and carbon cycle-climate feedbacks (Matthews et al, 2005). Figure 3 shows the impact of the outbreak on four variables (two related to carbon cycling, one to energy exchanges, and one to water cycling) over different timescales (yearly, monthly, and daily).…”

A dynamical systems analysis of the data assimilation linked ecosystem carbon (DALEC) models

“…We also acknowledge that smoothing the drivers takes away the natural variability, to which ecosystems respond. According to 27 , removal of high-frequency variability significantly enhances decadal Net Ecosystem Production, NEP (measurement of the net gain or loss of carbon in a system over a period of time), GPP and total respiration. Interestingly, they also show that solar radiation has a strong effect, whereas temperature variability only has a minor impact by comparison.…”

Amplification and dampening of soil respiration by changes in temperature variability

“…The effect of changes in the variance of different climatic variables on photosynthesis can offset the changes produced on respiration (Medvigy et al, 2010). For analyses at the ecosystem level, the analytical framework provided here can serve as a basis to identify the functions that would present a larger response to the variance of climatic variables by studying the degree of convexity of these functions and the expected changes in variance of those variables.…”

“…The implications of this inequality for temperaturerespiration studies are: (1) estimates of respiration from temperature data gathered at large spatial and temporal scales include bias or aggregation error (Rastetter et al, 1992;Kicklighter et al, 1994). (2) Modeling studies using average temperature as a driving variable will obtain lower values of respiration than if they were using temperature from weather records; (e.g., Notaro, 2008;Sierra et al, 2009;Medvigy et al, 2010). (3) Long-term incubation experiments at constant temperatures will result in lower respiration rates than experiments in which temperature is allowed to vary but without changing the average value.…”