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Digital and Intelligent Strategies and Path Analysis for Prevention and Control of Biological Invasion
LIUChuanxin, QIUJinmin, GEYugang, SUNJiayi, YANGXintong, WUDongyan, WANGJinglei, JIYuhan, DUYong, XIEHongtao
Journal of Agriculture ›› 2025, Vol. 15 ›› Issue (12) : 27-33.
PDF(1585 KB)
PDF(1585 KB)
Digital and Intelligent Strategies and Path Analysis for Prevention and Control of Biological Invasion
This study aims to study the application strategies of new technologies such as Internet+, 3S, AI, and big data in biological invasion prevention and control, and analyze the application paths of digital intelligent platforms in biological invasion prevention and control, so as to solve the problem of inefficiency and time-consuming in traditional invasive biological prevention and control. We used field surveys, literature reviews, and typical case analysis to comprehensively evaluate the role of digital and intelligent platforms in biological invasion monitoring and prevention. The results show that the ways to improve digital intelligence in biological invasion prevention and control include solution design and platform construction, digital intelligence improvement in data collection and processing, and implementation and application in specific ecosystem types. The focus is on the use of Internet+, 3S technology, AI big data analysis, data mining and data cleaning and other technical means to build an intelligent monitoring and early warning system for invasive organisms, so as to achieve the management of basic information on biological invasive species, visualize its spatial distribution and hazard degree, and focus on the application of drones, sensors, and etc. in the detection and removal of biological invasion. The results are expected to provide scientific reference for improving the efficiency of biological invasion prevention and control and building a digital intelligent platform.
biological invasion prevention and control / GIS+ / digital technology / intelligent monitoring / Internet+ / big data.
| [1] |
|
| [2] |
章莹. 中国沿海滩涂入侵物种互花米草(Spartina alterniflora)的空间分布及生物质能估测研究[D]. 杭州: 浙江大学, 2010.
|
| [3] |
钱翌. 生态入侵的危害及防范对策[J]. 新疆农业大学学报, 2001(4):62-64.
|
| [4] |
杜元宝, 涂炜山, 杨乐, 等. 外来入侵脊椎动物对生物多样性危害的研究进展[J]. 中国科学:生命科学, 2023, 53(7):1035-1054.
|
| [5] |
汪长友. 水葫芦疯长泛滥对网箱养鱼的危害及防治方法[J]. 渔业致富指南, 2011(17):62-63.
|
| [6] |
赵光华, 高明龙, 王朵, 等. 全球入侵植物的经济成本评估[J]. 草业学报, 2024, 33(5):16-24.
植物是入侵生物中种类和数量最多的类群,对入侵植物开展经济成本评估可为后续风险管理和相关政策的制定提供参考依据。本研究基于InvaCost数据库评估获得了1970-2017年全球入侵植物的经济成本,研究结果表明:1)入侵植物的保守经济成本为1943.65亿美元,年均40.49亿美元,其中,直接经济损失达1004.68亿美元,占比为51.69%;2)在64个国家和地区中,美国的经济成本最高,其次为澳大利亚,我国208.31亿美元(1407.07亿人民币)排名第三。凤眼莲是全球最昂贵的入侵植物种类,其危害所产生的成本高于排名5~10名的入侵植物成本之和;3)过去的近50年里,入侵植物的经济成本呈上升趋势,模型测算2017年入侵植物的可能成本为34.38亿~104.52亿美元,最高置信值为77.25亿美元。本研究有助于加深对入侵植物危害严重性的客观认识,可为我国开展更为积极的入侵植物治理提供科学依据。
|
| [7] |
|
| [8] |
王燕梅. 我国外来生物入侵的现状及对策[J]. 中国环境管理书, 2009(1):22-24+21.
|
| [9] |
曹志玲. 外来物种随跨境携带物及邮寄物非法入侵的危害分析[J]. 质量安全与检验检测, 2021, 31(5):53-55.
|
| [10] |
唐千鸿. 基于物种分布模型的农业生态系统和人居环境典型入侵生物的潜在威胁分析[D]. 大理: 大理大学, 2023.
|
| [11] |
赵紫华, 涂雄兵, 张泽华, 等. 警惕沙漠蝗种群持续增加和入侵我国边境地区的风险[J]. 植物保护学报, 2021, 48(1):5-12.
|
| [12] |
黄建花. 上海地区气传花粉监测[D]. 上海: 华东师范大学, 2013.
|
| [13] |
刘绍芹, 吕国忠. 豚草及豚草的综合治理[A].中国植物病理学会.中国植物病理学第七届青年学术讨论会论文集[C]. 沈阳农业大学植保学院, 大连民族学院生物资源与环境科学研究所, 2005:6.
|
| [14] |
刘宪斌, 杨楠茜, 李涛, 等. 紫茎泽兰在云南亚热带常绿阔叶林中的入侵格局和生境分析[J]. 中南林业科技大学学报, 2024, 44(1):128-139.
|
| [15] |
陈凤新, 蒙彦良, 杜杰, 等. 中国外来生物入侵与社会经济因素多元回归分析[J]. 植物检疫, 2021, 35(4):8-14.
|
| [16] |
杨朗, 黄立飞, 姜建军. 警惕和关注中国-东盟贸易区的入侵生物[A].中国植物保护学会生物入侵分会,第三届全国生物入侵大会论文摘要集[C]. 北京: 中国植物保护学会生物入侵分会, 2010.
|
| [17] |
The potential harmful effects of non—indigenous species introduced for biological control remain an important unanswered question, which we addressed by undertaking a literature review. There are few documented instances of damage to non—target organisms or the environment from non—indigenous species released for biological pest control, relative to the number of such releases. However, this fact is not evidence that biological control is safe, because monitoring of non—target species is minimal, particularly in sites and habitats far from the point of release. In fact, the discovery of such impacts usually rests on a remarkable concatenation of events. In addition to trophic and competitive interactions between an individual introduced species and a native one, many effects of introduced species on ecosystems are possible, as are numerous types of indirect interactions. Predicting such impacts is no mean feat, and the difficulty is exacerbated by the fact that introduced species can disperse and evolve. Current regulation of introduced biological—control agents, particularly of entomophages, is insufficient. At the very least, strong consideration should be given to the likely impact of both the pest and its natural enemy on natural ecosystems and their species, and not only on potential costs to agriculture, silvi—culture, and species of immediate commercial value.
|
| [18] |
|
| [19] |
向言词, 彭少麟, 周厚诚, 等. 生物入侵及其影响[J]. 生态科学, 2001, 20(4):68-72.
|
| [20] |
高增祥, 季荣, 徐汝梅, 等. 外来种入侵的过程、机理和预测[J]. 生态学报, 2003, 23(3):559-570.
|
| [21] |
段瑜东. 基于互联网技术的外来生物灾害应急管理系统的研究[D]. 长沙: 湖南农业大学, 2019.
|
| [22] |
张华纬, 赵健, 李志鹏. 基于GIS的入侵生物适生区预测——以桔小实蝇为例[J]. 测绘与空间地理信息, 2021, 44(6):59-64.
|
| [23] |
苏梦可, 高灵旺. 外来入侵物种的大数据获取及预测分析方法研究进展[J]. 植物保护, 2022, 48(6):214-220.
|
| [24] |
张利茹. 环境DNA技术及其应用[J]. 水利信息化, 2023(4):97-98.
|
| [25] |
孙全胜. 新时代中国生态治理现代化的要求与实现路径[J]. 云南行政学院学报, 2024, 26(2):65-73+98.
|
| [26] |
曾建文. 对互联网+网络安全入侵检测技术的研究[J]. 中国新通信, 2020, 22(15):47-48.
|
| [27] |
陆渊章, 夏玉果, 董天天. 人工智能技术在大数据时代智能信息处理中的应用分析[J]. 山东商业职业技术学院学报, 2019, 19(3):112-114.
|
| [28] |
刘晗, 李凯旋, 陈仪香. 人工智能系统可信性度量评估研究综述[J]. 软件学报, 2023, 34(8):3774-3792.
|
| [29] |
杨力凤, 杨楠, 付海滨, 等. 环境DNA技术在生物入侵研究中的应用进展[J]. 植物保护学报, 2023, 50(1):1-10.
|
| [30] |
卢依雯, 张璐, 李海玲, 等. 环境DNA技术在环境监测与动物生产管理中的应用进展[J]. 环境监测管理与技术, 2023, 35(3):11-16.
|
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