Climate adaptive silviculture strategies: How do they impact growth, yield, diversity and value in forested landscapes?

2020 
Abstract Forest managers have been wrestling with questions of how best to prepare today’s forests for a future climate that may be quite different from the climate under which they were established. We used the LANDIS forest landscape model to conduct a factorial simulation experiment to assess the landscape-wide effects of alternative cutting and planting practices in northern Wisconsin (USA) under three climate change scenarios simulated for 300 years to allow demographic legacies to be overcome by the experimental treatments. Our objective was to assess the relative ability of actionable components of silvicultural strategies to maintain productivity and economical and ecological values of forests under future climates compared to a “business as usual” (BAU) silviculture scenario representing current sustained yield practices. We found that the general effect of climate change was to increase the biomass of all species (CO2 fertilization and increased growing season), although the most cold-adapted species eventually declined under warming climate scenarios. Two alternative silvicultural strategies produced clearly different outcomes compared to the BAU scenario. Total landscape tree biomass was least under BAU, reflecting its high biomass removal rates, and greatest under the most aggressive climate-adapted silviculture strategy coupled with a high CO2 climate scenario due to increased growth and relatively high removal rates. Harvested outputs responded to both climate and silvicultural strategy, with the high CO2 scenario reducing biomass available for harvesting compared to a moderate CO2 scenario, except under the aggressive climate-adapted strategy. Our study suggests that creative silvicultural practices can be developed (and tested) to maintain productive and ecologically healthy forests under future climate conditions.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    77
    References
    5
    Citations
    NaN
    KQI
    []