A history of deer management and abundance estimation in Japan: past lessons and future challenges

During the past decades, the overabundance of deer species has been reported worldwide. To manage their population and its impacts, making evidence-based management policy and implementing it are essential. In this review, I provide a brief history of deer management policy in Japan and the methods used to estimate deer abundance. In Japan, overexploitation of sika deer (Cervus nippon) occurred about 150 years ago, but their protection was delayed. After long-term protection of sika deer, the abundance of sika deer and their impacts on human activity and the ecosystem became apparent in 1980, but the policy change was delayed again. Currently, monitoring of the sika deer population is well established at the prefectural level, enabling adaptive management. However, the assessment of the methods used to estimate deer abundance is insufficient. Knowledge of various methods for estimating deer abundance and understanding of their characteristics are necessary. Over the past century, methods for estimating abundance have changed from invasive, low-precision, and labor-intensive methods, such as pedestrian counts and pellet surveys, to non-invasive, high-precision, and cost-effective methods, such as camera-trapping and genetic capture–recapture, and from snapshot estimates to dynamic modeling. In Japan, the harvest-based model, which estimates deer abundance from harvest size and a relative abundance index, is a popular method. Furthermore, the integration of some methods makes it possible to estimate deer abundance at spatially and temporally high resolution. Because of budget constraints and limited human resources in an actual management situation, integrating various data will be important in the near future. At the same time, the incorporation of more efficient calculation algorithms and machine-learning techniques contributes to faster feedback on monitoring results for the deer manager.

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Publication Details

Journal
Animal Production Science
Published
2025-12-21
DOI
https://doi.org/10.1071/an25387
Citations
1
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
1.72
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A history of deer management and abundance estimation in Japan: past lessons and future challenges

1 citations
Animal Production Science
Wildlife Ecology and Conservation
1.72
article

A history of deer management and abundance estimation in Japan: past lessons and future challenges

article en
1 citations

Abstract

During the past decades, the overabundance of deer species has been reported worldwide. To manage their population and its impacts, making evidence-based management policy and implementing it are essential. In this review, I provide a brief history of deer management policy in Japan and the methods used to estimate deer abundance. In Japan, overexploitation of sika deer (Cervus nippon) occurred about 150 years ago, but their protection was delayed. After long-term protection of sika deer, the abundance of sika deer and their impacts on human activity and the ecosystem became apparent in 1980, but the policy change was delayed again. Currently, monitoring of the sika deer population is well established at the prefectural level, enabling adaptive management. However, the assessment of the methods used to estimate deer abundance is insufficient. Knowledge of various methods for estimating deer abundance and understanding of their characteristics are necessary. Over the past century, methods for estimating abundance have changed from invasive, low-precision, and labor-intensive methods, such as pedestrian counts and pellet surveys, to non-invasive, high-precision, and cost-effective methods, such as camera-trapping and genetic capture–recapture, and from snapshot estimates to dynamic modeling. In Japan, the harvest-based model, which estimates deer abundance from harvest size and a relative abundance index, is a popular method. Furthermore, the integration of some methods makes it possible to estimate deer abundance at spatially and temporally high resolution. Because of budget constraints and limited human resources in an actual management situation, integrating various data will be important in the near future. At the same time, the incorporation of more efficient calculation algorithms and machine-learning techniques contributes to faster feedback on monitoring results for the deer manager.

Animal Production ScienceVol. 66(2)
Forestry and Forest Products Research Institute (JP)
Openalex Percentile: Top 12%
Wildlife Ecology and Conservation
1.72
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A history of deer management and abundance estimation in Japan: past lessons and future challenges · Animal Production Science (2025) | TGRS Research Map | TGRS