Extrapolating plot-scale CO2 and ozone enrichment experimental results to novel conditions and scales using mechanistic modeling

Abstract

Introduction: The Aspen-FACE experiment was an 11-year study of the effect of elevated CO 2 and ozone (alone and in combination) on the growth of model aspen communities (pure aspen, aspen-birch, and aspen-maple) in the field in northern Wisconsin, USA. Uncertainty remains about how these short-term plotlevel responses might play out over broader temporal and spatial scales where climate change, competition, succession, and disturbances interact with tree-level responses. In this study, we used a new physiologybased approach (PnET-Succession v3.1) within the forest landscape model LANDIS-II to extrapolate the FACE results to broader temporal scales (and ultimately to landscape scale) by mechanistically accounting for the globally changing drivers of temperature, precipitation, CO 2 , and ozone. We added novel algorithms to the model to mechanistically simulate the effects of ozone on photosynthesis through ozone-induced impairment of stomatal control (i.e., stomatal sluggishness) and damage of photosynthetic capacity at the chloroplast level. Results: We calibrated the model to empirical observations of competitive interactions on the elevated CO 2 and O 3 plots of the Aspen-FACE experiment and successfully validated it on the combined factor plots. We used the validated model to extend the Aspen-FACE experiment for 80 years. When only aspen clones competed, we found that clone 271 always dominated, although the ozone-tolerant clone was co-dominant when ozone was present. Under all treatments, when aspen clone 216 and birch competed, birch was always dominant or co-dominant, and when clone 216 and maple competed, clone 216 was dominant, although maple was able to grow steadily because of its shade tolerance. We also predicted long-term competitive outcomes for novel assemblages of taxa under each treatment and discovered that future composition and dominant taxa depend on treatment, and that short-term trends do not always persist in the long term. Conclusions: We identified the strengths and weaknesses of PnET-Succession v3.1 and conclude that it can generate potentially robust predictions of the effects of elevated CO 2 and ozone at landscape scales because of its mechanistically motivated algorithms. These capabilities can be used to project forest dynamics under anticipated future conditions that have no historical analog with which to parameterize less mechanistic models.

Can Future CO2 Concentrations Mitigate the Negative Effects of High Temperature and Longer Droughts on Forest Growth?

“…The temperature multiplier (fTempPsn) equals 1.0 at the optimal temperature for photosynthesis of the species and declines negative-exponentially as temperature departs (in either direction) from that value. There is a conceptually similar CO 2 enrichment multiplier (DelAmax) that exceeds 1.0 as atmospheric CO 2 concentration exceeds 350 ppm, based on equations in Franks et al [9,14]. Photosynthesis occurs only in months where average temperature exceeds the species-specific minimum, which allows phenology to respond dynamically to variation in seasonal temperature.…”

Can Future CO₂ Concentrations Mitigate the Negative Effects of High Temperature and Longer Droughts on Forest Growth?

“…The temperature multiplier (fTempPsn) equals 1.0 at the species-specific optimal temperature for photosynthesis and declines as temperature departs (in either direction) from that value. There is an analogous CO2 enrichment multiplier (Delamax) that increases above 1.0 as atmospheric CO2 concentration exceeds 350 ppm according to the equation of Franks et al [8] [11]. Photosynthesis occurs in the months when average temperature exceeds the species-specific minimum, allowing phenology to respond to variation in seasonal temperature.…”

“…Temperature, precipitation, radiation and CO2 are input to the model as monthly means, which allow growth and establishment rates to vary in response to both gradual change and extreme events. For model details see De Bruijn et al [9] and Gustafson et al [11].…”

“…Charney et al [30] used continent-wide empirical observations of tree sensitivity to climate and CO2 to predict increases in growth across much of North America of up to 60% under the RCP8.5 emissions scenario. In a test of the ability of PnET-Succession to simulate the effects of CO2 enrichment on tree growth and competition in the Aspen-FACE experiment in northern Wisconsin, USA [31], Gustafson et al [11] found good agreement with empirical CO2 effects with no calibration required. Giardin et al [32] found a negative temperature effect (attributed to respiration) on the growth of trees across Canada in the last half of the 20th century, which was not completely mitigated by the CO2 concentrations of that period (<400 ppm).…”

Data_Sheet_1.ZIP

“…The coldest temperature extreme in a month is estimated as Tave-(3 * WinterSTD), where Tave is the average of the monthly minimum and maximum temperature inputs for the month. Elevated CO 2 increases photosynthetic capacity (with acclimation) by increasing CO 2 concentrations within the leaf and increasing water use efficiency (Franks et al, 2013) as described in Gustafson et al (2018). The age reduction factor gradually decreases photosynthesis as age approaches longevity to reflect senescence, ultimately causing respiration to exceed productivity.…”