Analysis of factors affecting rice-crop damage by sika deer in a landscape context and construction of a risk map in the Boso Peninsula, central Japan

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  • Takada Mayura
    Department of Life Science and Agriculture, Obihiro University of Agriculture and Veterinary Medicine
  • Suzuki Maki
    School of Agriculture and Life Sciences, University of Tokyo
  • Ochiai Keiji
    Natural history Museum and Institute, Chiba
  • Asada Masahiko
    Natural history Museum and Institute, Chiba
  • Miyashita Tadashi
    School of Agriculture and Life Sciences, University of Tokyo

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Other Title
  • 景観構造を考慮したニホンジカによる水稲被害発生機構の解明とリスクマップの作成
  • ケイカン コウゾウ オ コウリョ シタ ニホンジカ ニ ヨル スイトウ ヒガイ ハッセイ キコウ ノ カイメイ ト リスクマップ ノ サクセイ

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Abstract

The sika deer population (Cervus nippon) in the Boso Peninsula of Chiba, central Japan, has expanded dramatically in recent decades, causing serious damage to rice crops. To predict the level of damage, we conducted approximately 350 interviews of paddy field owners and developed a regression model that included local deer density and landscape structure surrounding paddy fields as explanatory variables. Model selection using Akaike's information criterion (AIC) revealed that the level of damage was affected by landscape structure within a 400-m radius of a focal rice field as well as local deer density. This spatial scale was consistent with the home-range size of sika deer as well as the scale determining food quality and the reproductive rate of deer in the Boso Peninsula. The level of damage also increased with an increase in forested area but tended to decrease with increases in the surrounding forest-edge length in areas with higher deer densities. We also constructed a risk map for rice-crop damage to determine local deer densities that could keep damage at low levels using the above regression model. The estimated deer density at which this occurred was highly variable depending on landscape structure. Comparing such risk maps and current local deer density will help to facilitate the establishment of an objective management plan in a heterogeneous landscape.

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