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公民科学提高了一种强湿地入侵物种的已知和潜在分布:对生态位模型和入侵管理的启示。

Citizen Science Improves the Known and Potential Distribution of a Strong Wetland Invader: Implications for Niche Modeling and Invasion Management.

机构信息

Centro de Ecología Aplicada del Litoral (CECOAL-CONICET-UNNE). Laboratorio de Herbivoría y Control Biológico, Corrientes, Argentina.

Department of Biology, Ecology Biodiversity Research Unit, Vrije Universiteit Brussel (VUB), Brussels, Belgium.

出版信息

Environ Manage. 2023 Jun;71(6):1176-1187. doi: 10.1007/s00267-023-01802-3. Epub 2023 Mar 3.

Abstract

Invasive alien species are one of the main causes of biodiversity loss and ecosystem alteration. Obtaining up-to-date occurrence records and accurate invasion risk maps has become crucial to develop timely and effective management strategies. Unfortunately, gathering and validating distribution data can be labor-intensive and time-consuming, with different data sources unavoidably leading to biases in the results. In this study, we evaluated the performance of a tailored citizen science project compared with other data sources, in mapping the current and potential distribution of Iris pseudacorus, a strong invasive alien plant in Argentina. To do so, we used geographic information systems and ecological niche modeling with Maxent, and compared data from: i) a citizen science tailored project; ii) the Global Biodiversity Information Facility (GBIF); and iii) an exhaustive professional data collection (i.e. field samplings across Argentina, literature and collections review). Results suggest that the citizen science tailored project provided a larger and more diversified amount of data compared to the other sources. All data-sources showed good performance in the ecological niche models, however, data from the tailored citizen science project predicted a greater suitable area, including regions not yet reported. This allowed us to better identify critical and vulnerable areas, where management and prevention strategies are necessary. Professional data provided more reports in non-urban areas, whereas citizen science based data sources (i.e. GBIF and the citizen science project conducted in this study) reported more sites in urban areas, which indicates that different data-sources are complementary and there is a big potential in combining methods. We encourage the use of tailored citizen science campaigns to gather a more diverse amount of data, generating better knowledge about aquatic invasive species and helping decision-making in ecosystem management.

摘要

入侵物种是生物多样性丧失和生态系统改变的主要原因之一。获取最新的发生记录和准确的入侵风险图已成为制定及时有效的管理策略的关键。不幸的是,收集和验证分布数据可能是劳动密集型和耗时的,不同的数据来源不可避免地导致结果存在偏差。在这项研究中,我们评估了定制的公民科学项目与其他数据源在绘制阿根廷强入侵外来植物鸢尾的当前和潜在分布方面的表现。为此,我们使用地理信息系统和 Maxent 的生态位模型,并比较了来自以下三个数据源的数据:i)定制的公民科学项目;ii)全球生物多样性信息设施(GBIF);iii)详尽的专业数据收集(即阿根廷各地的实地采样、文献和收藏审查)。结果表明,与其他来源相比,定制的公民科学项目提供了更多且更多样化的数据。所有数据源在生态位模型中表现良好,但来自定制公民科学项目的数据预测了更大的适宜区域,包括尚未报告的区域。这使我们能够更好地确定关键和脆弱地区,需要采取管理和预防策略。专业数据在非城市地区提供了更多的报告,而基于公民科学的数据源(即 GBIF 和本研究中进行的公民科学项目)在城市地区报告了更多的地点,这表明不同的数据来源是互补的,并且结合方法有很大的潜力。我们鼓励使用定制的公民科学活动来收集更多样化的数据,更好地了解水生入侵物种,并为生态系统管理中的决策提供帮助。

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