资源环境科技发展态势分析平台

Biotic disturbances (BDs, for example, insects, pathogens, and wildlife herbivory) substantially affect boreal and temperate forest ecosystems globally. However, accurate impact assessments comprising larger spatial scales are lacking to date although these are critically needed given the expected disturbance intensification under a warming climate. Hence, our quantitative knowledge on current and future BD impacts, for example, on forest carbon (C) cycling, is strongly limited. We extended a dynamic global vegetation model to simulate ecosystem response to prescribed tree mortality and defoliation due to multiple biotic agents across United States forests during the period 1997-2015, and quantified the BD-induced vegetation C loss, that is, C fluxes from live vegetation to dead organic matter pools. Annual disturbance fractions separated by BD type (tree mortality and defoliation) and agent (bark beetles, defoliator insects, other insects, pathogens, and other biotic agents) were calculated at 0.5 degrees resolution from aerial-surveyed data and applied within the model. Simulated BD-induced C fluxes totaled 251.6 Mt C (annual mean: 13.2 Mt C year(-1), SD +/- 7.3 Mt C year(-1) between years) across the study domain, to which tree mortality contributed 95% and defoliation 5%. Among BD agents, bark beetles caused most C fluxes (61%), and total insect-induced C fluxes were about five times larger compared to non-insect agents, for example, pathogens and wildlife. Our findings further demonstrate that BD-induced C cycle impacts (i) displayed high spatio-temporal variability, (ii) were dominated by different agents across BD types and regions, and (iii) were comparable in magnitude to fire-induced impacts. This study provides the first ecosystem model-based assessment of BD-induced impacts on forest C cycling at the continental scale and going beyond single agent-host systems, thus allowing for comparisons across regions, BD types, and agents. Ultimately, a perspective on the potential and limitations of a more process-based incorporation of multiple BDs in ecosystem models is offered.