Climate Change Data Portal
| DOI | 10.1016/j.scitotenv.2024.171588 |
| Socio-economic variables improve accuracy and change spatial predictions in species distribution models | |
| 发表日期 | 2024 |
| ISSN | 0048-9697 |
| EISSN | 1879-1026 |
| 起始页码 | 924 |
| 卷号 | 924 |
| 英文摘要 | In an era marked by increasing anthropogenic pressure, understanding the relations between human activities and wildlife is crucial for understanding ecological patterns, effective conservation, and management strategies. Here, we explore the potential and usefulness of socio-economic variables in species distribution modelling (SDM), focusing on their impact on the occurrence of wild mammals in Poland. Beyond the environmental factors commonly considered in SDM, like land-use, the study tests the importance of socio-economic characteristics of local human societies, such as age, income, working sector, gender, education, and village characteristics for explaining distribution of diverse mammalian groups, including carnivores, ungulates, rodents, soricids, and bats. The study revealed that incorporating socio-economic variables enhances the predictive power for >60 % of species and overall for most groups, with the exception being carnivores. For all the species combined, among the 10 predictors with highest predictive power, 6 belong to socio-economic group, while for specific species groups, socio-economic variables had similar predictive power as environmental variables. Furthermore, spatial predictions of species occurrence underwent changes when socio-economic variables were included in the model, resulting in a substantial mismatch in spatial predictions of species occurrence between environment-only models and models containing socio-economic variables. We conclude that socio-economic data has potential as useful predictors which increase prediction accuracy of wildlife occurrence and recommend its wider usage. Further, to our knowledge this is a first study on such a big scale for terrestrial mammals which evaluates performance based on presence or absence of socio-economic predictors in the model. We recognise the need for a more comprehensive approach in SDMs and that bridging the gap between human socio-economic dynamics and ecological processes may contribute to the understanding of the factors influencing biodiversity. |
| 英文关键词 | Biodiversity; Wildlife; Socioeconomy; Random forest; SDM |
| 语种 | 英语 |
| WOS研究方向 | Environmental Sciences & Ecology |
| WOS类目 | Environmental Sciences |
| WOS记录号 | WOS:001218416700001 |
| 来源期刊 | SCIENCE OF THE TOTAL ENVIRONMENT
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/302316 |
| 作者单位 | Polish Academy of Sciences; Mammal Research Institute of the Polish Academy of Sciences |
| 推荐引用方式 GB/T 7714 | . Socio-economic variables improve accuracy and change spatial predictions in species distribution models[J],2024,924. |
| APA | (2024).Socio-economic variables improve accuracy and change spatial predictions in species distribution models.SCIENCE OF THE TOTAL ENVIRONMENT,924. |
| MLA | "Socio-economic variables improve accuracy and change spatial predictions in species distribution models".SCIENCE OF THE TOTAL ENVIRONMENT 924(2024). |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
