Prediction model of the occurrence probability of bark-stripping by sika deer (Cervus nippon) in plantation forests in Kumamoto prefecture

T. Inoue, J. Miyajima, T. Murakami, Y. Mitsuda, Shigejiro Yoshida, M. Imada

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We analyzed the characteristics of 283 sites where sika deer aused bark-stripping damage in plantation forests in Kumamoto Prefecture, between 2000 and 2001. We developed four prediction models of the occurrence probability of bark-stripping damage using logistic regression. As independent variables, we used 16 factors, including topographic (elevation and slope angle), geographic (distance from the nearest road, etc.), vegetation (the number of cells used for forestry, agriculture, etc.), and stand (planted species and stand age) factors. The model with the lowest Akaike Information Criterion (AIC) and the greatest accuracy of classification showed that bark-stripping damage was strongly related to elevation, slope angle, and distance from the nearest road. The accuracy of the model was improved when the factors "planted species" and "stand age" were added. Finally, we drew a map showing the probability of bark-stripping damage. Such information should prove very useful in forest management planning.

Original languageEnglish
Pages (from-to)111-116
Number of pages6
JournalNihon Ringakkai Shi/Journal of the Japanese Forestry Society
Volume87
Issue number2
Publication statusPublished - 2005

Fingerprint

Cervus nippon
Deer
forest plantations
deer
bark
plantation
Forestry
damage
prediction
Age Factors
slope angle
Agriculture
roads
Cell Count
Logistic Models
road
topographic slope
Akaike information criterion
forest management
logistics

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences (miscellaneous)

Cite this

Prediction model of the occurrence probability of bark-stripping by sika deer (Cervus nippon) in plantation forests in Kumamoto prefecture. / Inoue, T.; Miyajima, J.; Murakami, T.; Mitsuda, Y.; Yoshida, Shigejiro; Imada, M.

In: Nihon Ringakkai Shi/Journal of the Japanese Forestry Society, Vol. 87, No. 2, 2005, p. 111-116.

Research output: Contribution to journalArticle

Inoue, T. ; Miyajima, J. ; Murakami, T. ; Mitsuda, Y. ; Yoshida, Shigejiro ; Imada, M. / Prediction model of the occurrence probability of bark-stripping by sika deer (Cervus nippon) in plantation forests in Kumamoto prefecture. In: Nihon Ringakkai Shi/Journal of the Japanese Forestry Society. 2005 ; Vol. 87, No. 2. pp. 111-116.
@article{daa905103d864843aa95fcc48abf8258,
title = "Prediction model of the occurrence probability of bark-stripping by sika deer (Cervus nippon) in plantation forests in Kumamoto prefecture",
abstract = "We analyzed the characteristics of 283 sites where sika deer aused bark-stripping damage in plantation forests in Kumamoto Prefecture, between 2000 and 2001. We developed four prediction models of the occurrence probability of bark-stripping damage using logistic regression. As independent variables, we used 16 factors, including topographic (elevation and slope angle), geographic (distance from the nearest road, etc.), vegetation (the number of cells used for forestry, agriculture, etc.), and stand (planted species and stand age) factors. The model with the lowest Akaike Information Criterion (AIC) and the greatest accuracy of classification showed that bark-stripping damage was strongly related to elevation, slope angle, and distance from the nearest road. The accuracy of the model was improved when the factors {"}planted species{"} and {"}stand age{"} were added. Finally, we drew a map showing the probability of bark-stripping damage. Such information should prove very useful in forest management planning.",
author = "T. Inoue and J. Miyajima and T. Murakami and Y. Mitsuda and Shigejiro Yoshida and M. Imada",
year = "2005",
language = "English",
volume = "87",
pages = "111--116",
journal = "Nihon Ringakkai Shi/Journal of the Japanese Forestry Society",
issn = "0021-485X",
publisher = "Nihon Ringakkai",
number = "2",

}

TY - JOUR

T1 - Prediction model of the occurrence probability of bark-stripping by sika deer (Cervus nippon) in plantation forests in Kumamoto prefecture

AU - Inoue, T.

AU - Miyajima, J.

AU - Murakami, T.

AU - Mitsuda, Y.

AU - Yoshida, Shigejiro

AU - Imada, M.

PY - 2005

Y1 - 2005

N2 - We analyzed the characteristics of 283 sites where sika deer aused bark-stripping damage in plantation forests in Kumamoto Prefecture, between 2000 and 2001. We developed four prediction models of the occurrence probability of bark-stripping damage using logistic regression. As independent variables, we used 16 factors, including topographic (elevation and slope angle), geographic (distance from the nearest road, etc.), vegetation (the number of cells used for forestry, agriculture, etc.), and stand (planted species and stand age) factors. The model with the lowest Akaike Information Criterion (AIC) and the greatest accuracy of classification showed that bark-stripping damage was strongly related to elevation, slope angle, and distance from the nearest road. The accuracy of the model was improved when the factors "planted species" and "stand age" were added. Finally, we drew a map showing the probability of bark-stripping damage. Such information should prove very useful in forest management planning.

AB - We analyzed the characteristics of 283 sites where sika deer aused bark-stripping damage in plantation forests in Kumamoto Prefecture, between 2000 and 2001. We developed four prediction models of the occurrence probability of bark-stripping damage using logistic regression. As independent variables, we used 16 factors, including topographic (elevation and slope angle), geographic (distance from the nearest road, etc.), vegetation (the number of cells used for forestry, agriculture, etc.), and stand (planted species and stand age) factors. The model with the lowest Akaike Information Criterion (AIC) and the greatest accuracy of classification showed that bark-stripping damage was strongly related to elevation, slope angle, and distance from the nearest road. The accuracy of the model was improved when the factors "planted species" and "stand age" were added. Finally, we drew a map showing the probability of bark-stripping damage. Such information should prove very useful in forest management planning.

UR - http://www.scopus.com/inward/record.url?scp=33845605453&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33845605453&partnerID=8YFLogxK

M3 - Article

VL - 87

SP - 111

EP - 116

JO - Nihon Ringakkai Shi/Journal of the Japanese Forestry Society

JF - Nihon Ringakkai Shi/Journal of the Japanese Forestry Society

SN - 0021-485X

IS - 2

ER -