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Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS-II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short-term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon-juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought-induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles., (Published 2014. This article is a U.S. Government work and is in the public domain in the USA.)

Three young northern temperate forest communities in the north-central United States were exposed to factorial combinations of elevated carbon dioxide (CO2 ) and tropospheric ozone (O3 ) for 11 years. Here, we report results from an extensive sampling of plant biomass and soil conducted at the conclusion of the experiment that enabled us to estimate ecosystem carbon (C) content and cumulative net primary productivity (NPP). Elevated CO2 enhanced ecosystem C content by 11%, whereas elevated O3 decreased ecosystem C content by 9%. There was little variation in treatment effects on C content across communities and no meaningful interactions between CO2 and O3 . Treatment effects on ecosystem C content resulted primarily from changes in the near-surface mineral soil and tree C, particularly differences in woody tissues. Excluding the mineral soil, cumulative NPP was a strong predictor of ecosystem C content (r(2) = 0.96). Elevated CO2 enhanced cumulative NPP by 39%, a consequence of a 28% increase in canopy nitrogen (N) content (g N m(-2) ) and a 28% increase in N productivity (NPP/canopy N). In contrast, elevated O3 lowered NPP by 10% because of a 21% decrease in canopy N, but did not impact N productivity. Consequently, as the marginal impact of canopy N on NPP (∆NPP/∆N) decreased through time with further canopy development, the O3 effect on NPP dissipated. Within the mineral soil, there was less C in the top 0.1 m of soil under elevated O3 and less soil C from 0.1 to 0.2 m in depth under elevated CO2 . Overall, these results suggest that elevated CO2 may create a sustained increase in NPP, whereas the long-term effect of elevated O3 on NPP will be smaller than expected. However, changes in soil C are not well-understood and limit our ability to predict changes in ecosystem C content., (© 2014 The Authors Global Change Biology Published by John Wiley & Sons Ltd.)