Abstract
AbstractRoot diseases are known to suppress forest regeneration and reduce growth rates, and they may become more common as susceptible tree species become maladapted in parts of their historic ranges due to climate change. However, current ecosystem models do not track the effects of root disease on net productivity, and there has been little research on how the dynamics of root disease affect carbon (C) storage and productivity across infected landscapes. We compared the effects of root disease against the effects of other types of forest disturbance across six national forest landscapes, 1990–2011. This was enabled by a monitoring tool called the Forest Carbon Management Framework (ForCaMF), which makes use of ground inventory data, an empirical growth model, and time series of Landsat satellite imagery. Despite several large fires that burned across these landscapes during the study period, retrospective ForCaMF analysis showed that fire and root disease had approximately equal impacts on C storage. Relative to C accumulation that would have occurred in their absence, fires from 1990 to 2011 were estimated to reduce regionwide C storage by 215.3 ± 19.1 g/m2 C, while disease in the same period was estimated to reduce storage by 211.4 ± 59.9 g/m2 C. Harvest (75.5 ± 13.5 g/m2 C) and bark beetle activity (14.8 ± 12.5 g/m2 C) were less important. While long‐term disturbance processes such as root disease have generally been ignored by tools informing management of forest C storage, the recent history of several national forests suggests that such disturbances can be just as important to the C cycle as more conspicuous events like wildfires.
Highlights
In forest ecosystems, managers are often interested in the impact of different management and disturbance processes upon fixation and storage of atmospheric carbon (C), an ecosystem benefit that may mitigate climatic effects of rising fossil fuel emissions
Mapped severity levels matched field observations at 46% of the plots. This success/failure rate and the validation results presented in Table 1 were used to constrain probabilistic Forest Carbon Management Framework (ForCaMF) simulations through the “PDF Weaving” process described in Appendix S1 and by Healey et al (2014)
Monte Carlo simulations were constrained to reflect the prevalence of root disease in the Forest Inventory and Analysis (FIA) sample; the root disease risk map was only used to target simulation units for FIA-b ased rates of infection
Summary
In forest ecosystems, managers are often interested in the impact of different management and disturbance processes upon fixation and storage of atmospheric carbon (C), an ecosystem benefit that may mitigate climatic effects of rising fossil fuel emissions. Biogeochemical models are a primary source of this information, and leading models allow assessment of the C storage impact of different disturbance processes such as fire (Yang et al 2015), timber harvest (Peckham et al 2013), and insect outbreaks (Kurz et al 2008a, Albani et al 2010). Development of such models is often informed, and sometimes motivated, by empirical study of current or historical trends.
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