Preventing Invasive Non-Native Species: A Horizon Scanning for the Canary Islands

IF 4.2 2区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION
Ana Clara Sampaio Franco, Carolina Mendes Muniz, Martina Carrete, Pilar Castro-Díez, Miguel Delibes-Mateos, Josep A. Jaques, Mar Leza, Marta López-Darias, Manuel Nogales, Macarena Ros, Xavier Turon, Montserrat Vilà, Óscar Afonso, Inés Álvarez, Andrés Arias, Dani Boix, Carlos Cabido, Eva Cacabelos, Carlos Cano-Barbacil, Miguel Cañedo-Argüelles, Beatriz Dáder, Ramón Gallo-Barneto, Ignacio Gestoso, María González Díaz, David Hernández-Teixidor, José Carlos Hernández, Cayetano Herrera, Marc Martín Solà, Elizabeth Ojeda-Land, Francisco J. Oliva-Paterna, Miguel Antonio Padrón-Mederos, Jairo Patiño, Laura Piñeiro, Núria Roura-Pascual, Marcos Salas-Pascual, Elisa Viñuela, Emili García-Berthou
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引用次数: 0

Abstract

Aim

Oceanic islands host exceptional biodiversity and endemism but are highly vulnerable to biological invasions. We aimed to identify non-native species with high potential to invade the Canary Islands within the next decade and to prioritise them based on their environmental and socioeconomic risks.

Location

The Canary Islands, Macaronesia, northeastern Atlantic Ocean.

Methods

We applied a structured horizon scanning protocol with a global scope. A panel of 37 experts assessed 823 species across five thematic groups (marine species, freshwater animals, terrestrial vertebrates, terrestrial invertebrates and plants) by scoring their likelihood of arrival, establishment and impacts. Impacts were evaluated separately as environmental and socioeconomic. Agreement and consistency among experts were quantified, and two consensus-based ranked lists were developed.

Results

Although agreement in expert scores was relatively low, species rankings showed high consistency. A total of 94 species were identified as priorities for prevention based on environmental impacts (12 very high risk, 82 high risk), while 49 species were prioritized for socioeconomic impacts (2 very high, 47 high). Environmental risks were dominated by lizards, snakes and freshwater fish, whereas socioeconomic risks were mainly concentrated on insects. Environmental and socioeconomic impact scores were only weakly related, underscoring the value of independent evaluation.

Main Conclusions

This study provides a horizon scanning explicitly focused on the Canary Islands, with separate assessments of environmental and socioeconomic risks. Our results highlight taxonomic groups that warrant urgent attention, show that invasion risk patterns vary depending on the spatial and contextual scale of assessment and provide a proactive tool to support surveillance, early warning systems and biosecurity measures. By anticipating future threats, this work contributes methodological and applied advances with broad relevance for conservation biogeography and invasive species management in island ecosystems.

防止外来入侵物种:加那利群岛的水平扫描
目的大洋岛屿拥有独特的生物多样性和地方性,但极易受到生物入侵。我们的目标是确定在未来十年内极有可能入侵加那利群岛的非本地物种,并根据它们的环境和社会经济风险对它们进行优先排序。地理位置:加那利群岛,马卡罗尼西亚,大西洋东北部。方法采用全局范围的结构化水平扫描协议。一个由37名专家组成的小组评估了五个专题组(海洋物种、淡水动物、陆生脊椎动物、陆生无脊椎动物和植物)的823个物种,对它们到达、建立和影响的可能性进行了评分。影响分别评估为环境和社会经济。对专家之间的共识和一致性进行了量化,并制定了两个基于共识的排名表。结果专家评分一致性较低,但物种排序一致性较高。根据环境影响确定了94种(高风险12种,高风险82种),根据社会经济影响确定了49种(高风险2种,高风险47种)。环境风险以蜥蜴、蛇类和淡水鱼为主,社会经济风险以昆虫为主。环境和社会经济影响得分只有微弱的相关性,强调了独立评估的价值。本研究提供了一个明确关注加那利群岛的水平扫描,并对环境和社会经济风险进行了单独评估。我们的研究结果突出了需要紧急关注的分类类群,表明入侵风险模式根据评估的空间和环境尺度而变化,并为支持监测、预警系统和生物安全措施提供了积极的工具。通过预测未来的威胁,这项工作为岛屿生态系统的保护生物地理学和入侵物种管理提供了广泛相关的方法和应用进展。
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来源期刊
Diversity and Distributions
Diversity and Distributions 环境科学-生态学
CiteScore
8.90
自引率
4.30%
发文量
195
审稿时长
8-16 weeks
期刊介绍: Diversity and Distributions is a journal of conservation biogeography. We publish papers that deal with the application of biogeographical principles, theories, and analyses (being those concerned with the distributional dynamics of taxa and assemblages) to problems concerning the conservation of biodiversity. We no longer consider papers the sole aim of which is to describe or analyze patterns of biodiversity or to elucidate processes that generate biodiversity.
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