Environmental factors affecting damage by wild boars (Sus scrofa) to rice fields in Yamanashi Prefecture, central Japan

Honda, Takeshi; Sugita, Mikio

doi:10.3106/1348-6160(2007)32[173:efadbw]2.0.co;2

Cited by 26 publications

(19 citation statements)

References 3 publications

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“…As environmental factors, we selected distance from forest edges (m), distance from rivers (m), distance from roads (m), distance from settlements (m), overground openness, and population density (people/km 2 ) with 100-m grids (Honda and Sugita 2007). A vegetation map (Ministry of the Environment 1999) was used to calculate the shortest distance from forest edges and from settlements to rice paddies.…”

Section: Data Collectionmentioning

confidence: 99%

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Predicting the risk of wild boar damage to rice paddies using presence-only data in Chiba Prefecture, Japan

Saito

Momose

Mihira

et al. 2012

International Journal of Pest Management

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Population sizes of wild boar (Sus scrofa) and the damage they cause to crops have been increasing in Japan. Reliable techniques are needed to estimate the potential for damage at the landscape scale. Here, we predict the risk of damage to rice (Oryza sativa) paddies by wild boar in Chiba Prefecture, Japan, by means of three different modelling methods -Maxent, generalised linear model (GLM) and generalised additive model (GAM) -using a combination of presence-only damage data obtained from a local agency and environmental information derived from publicly available databases. We used damage locations in 2007 and 2008. To validate the models, we calculated the area under the curve (AUC) and the correct classification rate (CCR) using independent data obtained in field surveys. The three methods gave similar results, indicating that we could construct a predictive model with high accuracy from presence-only data. Among these three, Maxent showed the closest fit, with 0.78 AUC and 72.6% CCR values. Because it is important to estimate the risk of damage to reduce future damage and costs, these damage prediction methods using presence-only data, which administrative agencies can obtain with no cost, this could assist local governments in formulating damage control plans.

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Section: Data Collectionmentioning

confidence: 99%

“…NaughtonTreves 1998; Honda and Sugita 2007;Amano et al 2008;Honda et al 2008b), few have used presence-only data. Predictions using such limited data would be beneficial because many existing data sets, especially those obtained through non-academic administrative activities, are presence-only data.…”

Section: Introductionmentioning

confidence: 98%

Predicting the risk of wild boar damage to rice paddies using presence-only data in Chiba Prefecture, Japan

Saito

Momose

Mihira

et al. 2012

International Journal of Pest Management

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“…There have been some studies on factors influencing wild boar damage worldwide (Meriggi and Sacchi 1992;Welander 2000;Calenge et al 2004;Madden 2004;Honda and Sugita 2007;Cai et al 2008;Schley et al 2008). For example, a shorter distance from forest edges increases the risk (Honda and Sugita 2007;Cai et al 2008), but higher values of distance from roads are related to increased damage (Saito et al 2011).…”

Section: Introductionmentioning

confidence: 95%

“…For example, a shorter distance from forest edges increases the risk (Honda and Sugita 2007;Cai et al 2008), but higher values of distance from roads are related to increased damage (Saito et al 2011). Few studies have been conducted on influencing factors in China except for the one carried out by Cai et al (2008), which was conducted in the northwest of China where the crop structure and environment are quite different from southern China.…”

Section: Introductionmentioning

confidence: 96%

Factors influencing wild boar damage in Taohongling National Nature Reserve in China: a model approach

Shi

Wang

et al. 2012

Eur J Wildl Res

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Conflicts between humans and wildlife, especially wild boar (Sus scrofa), have caused serious problems across the world in recent years. It is necessary to effectively control wild boar agricultural damage that may be influenced by many factors. In this study, we collected data on agricultural damage caused by wild boars from November 2009 to October 2010 using field surveys and social interviews in Taohongling National Nature Reserve of Jiangxi Province, China. We constructed models using binary logistic regression analysis to predict damage risks and to identify the factors influencing damage risks. About 8.1 % of croplands were damaged by wild boars, and the damage to rice, cotton, and other crops were not distributed based on their respective availability as shown by the result of a chisquare goodness-of-fit test. Five factors (Japanese silvergrass, soil conditions, terrain, distances to settlements, and water sources) were explained in a model based on damage area (area-based model) with the prediction accuracy being 72.1 %. In addition to these five factors, one additional factor (i.e. distance to forest edge) was retained in a model based on damage frequency (frequency-based model) with the prediction accuracy being 83.1 %. Caution is needed when we apply these two models to predict boar damage to crops, and it is recommended that both models be used in combination to predict the damage probabilities more accurately.

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“…Relatively convenient road access gives farmers easier access to their cultivated land plots (Honda and Sugita, 2007;Saito et al, 2011) and helps to avoid wild boar damage due to higher population densities, indicating that wild boars avoid human activities. However, some respondents saw wild boars active in residential areas, and during the study period, five people were injured.…”

Section: Cultivated Land Abandonment and Influencing Factorsmentioning

confidence: 99%

Wildlife damage and cultivated land abandonment: Findings from the mountainous areas of Chongqing, China

Hua

Yan

et al. 2016

Crop Protection

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a b s t r a c tHuman-wildlife conflict (HWC) is a growing global issue that seriously threatens agricultural production and livelihoods. Studying the relationship between wildlife damage, land use, and livelihood enables us to understand the dilemma facing current wildlife protection and ecological restoration policies and to amend existing policies effectively. Using participatory rural appraisal (PRA), quantitative analysis, and a Multilevel Logit regression model, this paper analyzed land use and livelihoods among 160 households subject to wild boar (Sus scrofa) damage in four villages within Youyang County in the poor mountainous areas of Chongqing, China. The findings showed the following: (i) wild boars in Youyang County were responsible for large-scale crop and property damage; (ii) cultivated land abandonment has become a significant trend in land use, and the most important perceived driver for abandoning farmland is the land plot's vulnerability to wild boar damage; (iii) when protecting cultivated land plots, households tend to protect those plots that are close to the road, have larger land area, and have a slight or abrupt slope; however, households with more members working in non-farm labor, more female agricultural workers, and/or higher non-farm income are more inclined to abandon protection of their plots. This paper discusses seven main measures that are frequently adopted by farmers to protect their crops and livestock and are perceived by these farmers as the most effective and sensible countermeasures.

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Environmental factors affecting damage by wild boars (Sus scrofa) to rice fields in Yamanashi Prefecture, central Japan

Cited by 26 publications

References 3 publications

Predicting the risk of wild boar damage to rice paddies using presence-only data in Chiba Prefecture, Japan

Predicting the risk of wild boar damage to rice paddies using presence-only data in Chiba Prefecture, Japan

Factors influencing wild boar damage in Taohongling National Nature Reserve in China: a model approach

Wildlife damage and cultivated land abandonment: Findings from the mountainous areas of Chongqing, China

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