Separating direct and indirect effects of rising temperatures on biogenic volatile emissions in the Arctic

Abstract

Volatile organic compounds (VOCs) are released from biogenic sources in a temperature-dependent manner. Consequently, Arctic ecosystems are expected to greatly increase their VOC emissions with ongoing climate warming, which is proceeding at twice the rate of global temperature rise. Here, we show that ongoing warming has strong, increasing effects on Arctic VOC emissions. Using a combination of statistical modeling on data from several warming experiments in the Arctic tundra and dynamic ecosystem modeling, we separate the impacts of temperature and soil moisture into direct effects and indirect effects through vegetation composition and biomass alterations. The indirect effects of warming on VOC emissions were significant but smaller than the direct effects, during the 14-y model simulation period. Furthermore, vegetation changes also cause shifts in the chemical speciation of emissions. Both direct and indirect effects result in large geographic differences in VOC emission responses in the warming Arctic, depending on the local vegetation cover and the climate dynamics. Our results outline complex links between local climate, vegetation, and ecosystem-atmosphere interactions, with likely local-to-regional impacts on the atmospheric composition.

Keywords: climate change; ecosystem modelling; ecosystem–atmosphere interactions; vegetation change.

Fig. 1.

Effects of environmental variables on VOC emissions. Density distributions of mean standardized effect sizes of five environmental variables in six different VOC groups. The effect sizes (β-estimates) correspond to linear slope parameters derived from multivariable mixed effect models containing sampling year, study site, and local habitat manipulation as random effects (see SI Appendix, Table S1 and Fig. S1 for further details). All β-estimates are adjusted for seasonal variation in VOC emissions, assuming an increase in the spring and a decrease in late summer.

Fig. 2.

Structural equation models representing direct and indirect linkages of environmental factors on VOC emission. (A) The conceptual model tested, in which temperature and soil moisture affect VOC emissions directly or indirectly by structuring the vegetation cover. (B) An example of a final SEM model for isoprene emission. Solid arrows represent significant linear paths supported by the model; dashed lines are omitted paths. Values represent standardized effect sizes. (C) Effect sizes on each VOC group summed across the SEM models for temperature and soil moisture, respectively. Direct effect sizes (green) correspond to parameter estimates between VOC and the given parameter. Indirect effects (purple) correspond to the mediated effect of a variable via the vegetation cover PC axis. All numbers are scaled to z-scores in order to enable comparisons of effect sizes across variable types. All deviations from 0 are significant.

Fig. 3.

Changes in modeled annual isoprene (A) and monoterpene (B) emissions due to direct and indirect effects, and the isoprene-to-monoterpene ratio for emissions (C) from each model simulation averaged over the Pan-Arctic land area. DIR were determined from the difference between the scenarios with 2 °C (DIR T2) or 4 °C (DIR T4) warming impacts on VOC production/emission and the control run. IND were determined from the difference between the simulations with both direct and indirect effects and those with only direct effects. Note the different y axis scales.

Fig. 4.

Relative changes in isoprene emission under direct and indirect effects of warming by 2 °C (A and B) and 4 °C (C and D). A and C show the DIR on isoprene production and emission rate, and (B and D) show the IND mainly through changes in vegetation composition and vegetation-related processes averaged for the period 1999–2012.