Wind damage risk estimation for strip cutting under current and future wind conditions based on moment observations in a coastal forest in Japan

Suzuki, S., et al., 2016. Journal of Forest Research

Original research (primary data)
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In Japan, coastal forests have been constructed along the seashore to prevent houses and fields from disasters caused by strong winds. A management method needs to be established to regulate the stand density. There is also the possibility that wind speed will increase in the future because of the increasing strength of tropical cyclones caused by climate change. We evaluated the current and future risk of wind damage associated with strip cutting of Japanese black pine forest based on moment work on sample trees. We established a research site consisting of three groups of trees: group A faced a 1.2-m cutting strip, group B faced a 5-m cutting strip, and group C was the control. Group B was vulnerable to strong winds because the normalized critical wind speed (CWSnml) was significantly smaller than that in the other groups. The damage risk was evaluated by comparing CWSnml with the criterion, a 50-year return period of wind speed. In the current conditions, 5-m cutting had a certain degree of risk, and 1.2-m cutting showed a low risk. Under the future wind conditions, 5-m cutting was found to show high risk so that most of the trees did not meet the criterion. The 1.2-m cutting showed a low risk even in the future conditions. Our results clearly reveal the significant changes in the stability of remaining trees against strong winds after strip cutting. This study suggests a method to quantify the risk involved in forest management.

Case studies

Basic information

  • Case ID: INT-179-1
  • Intervention type: Created habitats
  • Intervention description:

    Regulating strip cutting to ensure enough wind protection from constructed pine coastal forests in Japan. This is an experimental study to determine the optimal strip cutting width Sakamoto et al. (2010) discussed the importance of regulating the stand density while avoiding disasters in coastal areas. Strip cutting is a method used to manage forests by making row-cut blocks at regular intervals. It is usually performed to regulate the stand density by cutting with a narrow width or to encourage regeneration with a relatively wide width. In 2010, strip cutting was performed in a N30E–S30W direction as an attempt to manage the naturally regenerated forest [note – this is natural regeneration of an artificial/constructed pine] with very high stand density by Aichi Prefecture. Strip cutting of one line and the remaining three lines of trees is often performed in coastal forests in Japan (Sakamoto et al. 2007). Strip cutting with widths of 1.2 m in this study was performed every 3.6 m of the remaining trees, mimicking the regular management. On the other hand, strip cutting with a width of 5 m is also performed for carrying the harvested trees out of the stands easily. Considering these practical methods of strip cutting, we used the width of 1.2 m as standard strip cutting width and 5 m as wider strip cutting width in this study “The forest was originally established during 1952–1956 by authorities in Aichi Prefecture. However, it is now a naturally regenerated forest after severe damages by primarily two events, a typhoon in 1959 and pine wilt disease that started in 1975 caused by nematodes.”

  • Landscape/sea scape ecosystem management: No
  • Climate change impacts Effect of Nbs on CCI Effect measures
    Wind damage  Positive normalized critical wind speed (CWSnml); derived from mechanical modeling
  • Approach implemented in the field: Yes
  • Specific location:

    Japanese black pine forest in Ichizenmatsu, Aichi Prefecture, Japan

  • Country: Japan
  • Habitat/Biome type: Created forest |
  • Issue specific term: Not applicable


  • Notes on intervention effectivness: They measured normalized critical wind speed (CWSnml), the larger this value the more resistant to wind the tree stand IS . They evaluated the damage risk in the face of climate change by comparing CWsnml with potential increases in windspeed due to climate change. a natural, uncut forest stand is effective at preventing wind damage. however, forest management is necessary, including some strip cutting (e.g. to encourage regeneration). therefore, they test which width of strip cutting can still prevent wind damage. they deduce that 5 is too great but 1.2 is optimal. no significantly increased risk compared to uncut stand. therefore the comparator is the uncut stand, the intervention is 1.2 m strip cutting, and it is effective “We evaluated the wind damage risk for the individual trees by a comparison between CWSnml and the wind speed of 50-year return period…When the CWSnml was greater than the wind speed of the return period, we decided that the tree had enough strength for a rare strong wind We attempted to consider the case of climate change by increasing the wind speed by 10, 20, and 30 %. It is estimated that the maximum wind speed at the research site increased by 7 m/s in the case of the 30 % increase” The latter would appear to be akin to scenario modeling, to predict effectiveness; however, this is not a scenario modeling exercise at its core because the outcome variables are modeled from observed empirical measures (e.g. wind speed)
  • Is the assessment original?: Yes
  • Broadtype of intervention considered: Not applicable
  • Compare effectivness?: No
  • Compared to the non-NBS approach: Not applicable
  • Report greenhouse gas mitigation?: No
  • Impacts on GHG: Not applicable
  • Assess outcomes of the intervention on natural ecosystems: No
  • Impacts for the ecosystem: Not reported
  • Ecosystem measures: n/a
  • Assess outcomes of the intervention on people: No
  • Impacts for people: Not reported
  • People measures: n/a
  • Considers economic costs: No
  • Economic appraisal conducted: No
  • Economic appraisal described:
  • Economic costs of alternative considered: No
  • Compared to an alternative: Not reported

Evaluation methodology

  • Type of data: Quantitative
  • Is it experimental: Yes
  • Experimental evalution done: In-situ/field
  • Non-experimental evalution done: Not applicable
  • Study is systematic: