Spatio-temporal dynamics and drivers of public interest in invasive alien species

被引:0
|
作者
Yuya Fukano
Masashi Soga
机构
[1] The University of Tokyo,Graduate School of Agricultural and Life Sciences
来源
Biological Invasions | 2019年 / 21卷
关键词
Google trends; Internet; Management; Invasive species; Fire ant; Culturomics;
D O I
暂无
中图分类号
学科分类号
摘要
Understanding the dynamics of public interest in invasive alien species (IAS) is important for the establishment of effective strategies to prevent their spread and mitigate the negative social impacts thereof. Our knowledge of this topic is still limited, however, largely because of the difficulty in collecting data regarding public interest in IAS at a sufficiently large scale and for a long period. Here, we use relative search volume (RSV) on Google as a proxy of the general public’s interest in IAS and investigate its spatio-temporal distributions and drivers in Japan. We analyzed the data for 31 major IAS in Japan and found that the spatial distribution of RSV was predicted by both the actual distribution of IAS and the number of news articles featuring these species. Path analyses revealed that the presence of IAS increased RSV both directly and indirectly thorough an increase in the total number of news articles in local newspapers. Also, time-series analysis of the RSV for serial invasion of Solenopsis invicta, a recently detected IAS in Japan, demonstrated that the local RSV for this species increased sharply after the official announcement of its invasion was made. Overall, our study demonstrates that public interest in IAS varies greatly both spatially and temporally, and this variation was predicted by both ecological and social factors associated with IAS. Understanding the patterns of variation in public interest in IAS and its key drivers should help us to design more responsive and effective strategies to control these species.
引用
收藏
页码:3521 / 3532
页数:11
相关论文
共 50 条
  • [1] Spatio-temporal dynamics and drivers of public interest in invasive alien species
    Fukano, Yuya
    Soga, Masashi
    [J]. BIOLOGICAL INVASIONS, 2019, 21 (12) : 3521 - 3532
  • [2] GIATAR: a Spatio-temporal Dataset of Global Invasive and Alien Species and their Traits
    Saffer, Ariel
    Worm, Thom
    Takeuchi, Yu
    Meentemeyer, Ross
    [J]. SCIENTIFIC DATA, 2024, 11 (01)
  • [3] Drivers of spatio-temporal population dynamics of game species in a mountain landscape
    Erich Tasser
    Birgith Unterthurner
    Andreas Agreiter
    Lothar Gerstgrasser
    Marco Giardino
    Ulrike Tappeiner
    Janette Walde
    Johannes Rüdisser
    [J]. Scientific Reports, 14
  • [4] Drivers of spatio-temporal population dynamics of game species in a mountain landscape
    Tasser, Erich
    Unterthurner, Birgith
    Agreiter, Andreas
    Gerstgrasser, Lothar
    Giardino, Marco
    Tappeiner, Ulrike
    Walde, Janette
    Ruedisser, Johannes
    [J]. SCIENTIFIC REPORTS, 2024, 14 (01)
  • [5] Bayesian inference for the spatio-temporal invasion of alien species
    Cook, Alex
    Marion, Glenn
    Butler, Adam
    Gibson, Gavin
    [J]. BULLETIN OF MATHEMATICAL BIOLOGY, 2007, 69 (06) : 2005 - 2025
  • [6] Bayesian Inference for the Spatio-Temporal Invasion of Alien Species
    Alex Cook
    Glenn Marion
    Adam Butler
    Gavin Gibson
    [J]. Bulletin of Mathematical Biology, 2007, 69 : 2005 - 2025
  • [7] Accurate Recognition of Spatial Patterns Arising in Spatio-Temporal Dynamics of Invasive Species
    Petrovskaya, Natalia
    Zhang, Wenxin
    [J]. CURRENT TRENDS IN DYNAMICAL SYSTEMS IN BIOLOGY AND NATURAL SCIENCES, 2020, 21 : 19 - 41
  • [8] Spatio-temporal dynamics of the invasive plant species Elytrigia atherica on natural salt marshes
    Veeneklaas, Roos M.
    Dijkema, Kees S.
    Hecker, Norbert
    Bakker, Jan P.
    [J]. APPLIED VEGETATION SCIENCE, 2013, 16 (02) : 205 - 216
  • [9] Visual Analysis of Spatio-Temporal Event Predictions: Investigating the Spread Dynamics of Invasive Species
    Seebacher, Daniel
    Haeussler, Johannes
    Hundt, Michael
    Stein, Manuel
    Mueller, Hannes
    Engelke, Ulrich
    Keim, Daniel
    [J]. 2017 IEEE VISUALIZATION IN DATA SCIENCE (VDS), 2017, : 1 - 6
  • [10] Visual Analysis of Spatio-Temporal Event Predictions: Investigating the Spread Dynamics of Invasive Species
    Seebacher, Daniel
    Hauessler, Johannes
    Hundt, Michael
    Stein, Manuel
    Mueller, Hannes
    Engelke, Ulrich
    Keim, Daniel A.
    [J]. IEEE TRANSACTIONS ON BIG DATA, 2021, 7 (03) : 497 - 509