Gjedde Philip, Carrer Fabio, Pettersen Johan Berg, Verones Francesca
Norwegian University of Science and Technology, Trondheim, Norway.
Int J Life Cycle Assess. 2024;29(9):1756-1763. doi: 10.1007/s11367-024-02325-7. Epub 2024 May 30.
Marine vertebrate populations have halved in the past decades, and invasive species are a major driver for this loss. While many model the spread of invasive species, a model to assess impacts of marine invasions, after introduction, has hitherto been missing. We present the first regionalized effect factors for marine invasions. These factors gauge differences in biodiversity impacts after invasions, enabling life cycle impact assessments to highlight biodiversity impacts from invasive species.
Alien species are species that are introduced by humans to ecosystems where they are not native. We combine data from the IUCN red list and the MarINvaders database to identify the potentially disappeared fraction of native species within each marine coastal ecoregion after alien introduction. The effect factors indicate the biodiversity impact from invasions per alien introduction. However, the IUCN red list has a performance bias between taxonomic groups, and both the IUCN and the harmonized citizen science data from MarINvaders have a geographic observer's bias. We address some of this bias by evaluating the number of threatened species per number of assessed species, as well as including machine-learning derived data for data deficient species.
The resulting regional effect factors demonstrate high effects of invasions at high latitudes, which is in line with other findings. Our approach is founded on continuously growing citizen science data and so reflects the biases and uncertainties that follow with this uneven way of data sampling. On the other hand, the continuous data collection by citizen scientists will improve data coverage and thus improve the model. Vice versa, the model itself may be motivation for citizens scientists to collect more data.
The effect of marine invasions presented herein reflects current global information on the issue viewed in a perspective relevant for life cycle impact assessments. The developed effect factors can be used for further assessments that will aid decision-making for policies, industries, and consumers to work towards minimizing impacts of marine invasions and are developed to be compatible with different relevant fate factors.
The online version contains supplementary material available at 10.1007/s11367-024-02325-7.
在过去几十年中，海洋脊椎动物种群数量减少了一半，而入侵物种是造成这种损失的主要驱动因素。虽然许多模型模拟了入侵物种的扩散，但迄今为止，还缺少一个评估海洋入侵引入后影响的模型。我们提出了首个海洋入侵区域化影响因子。这些因子衡量入侵后生物多样性影响的差异，使生命周期影响评估能够突出入侵物种对生物多样性的影响。
外来物种是指被人类引入到其非原生生态系统的物种。我们结合了世界自然保护联盟（IUCN）红色名录和海洋入侵者数据库的数据，以确定外来物种引入后每个海洋沿海生态区域内本地物种可能消失的比例。这些影响因子表明每次外来物种引入对生物多样性的影响。然而，IUCN红色名录在分类群之间存在性能偏差，IUCN和来自海洋入侵者的统一公民科学数据都存在地理观测偏差。我们通过评估每评估物种中受威胁物种的数量，并纳入针对数据不足物种的机器学习衍生数据来解决部分这种偏差。
由此产生的区域影响因子表明高纬度地区入侵的影响很大，这与其他研究结果一致。我们的方法基于不断增长的公民科学数据，因此反映了这种不均衡数据采样方式所带来的偏差和不确定性。另一方面，公民科学家的持续数据收集将提高数据覆盖范围，从而改进模型。反之，模型本身可能会激励公民科学家收集更多数据。
本文提出的海洋入侵影响反映了从与生命周期影响评估相关的角度看待该问题的当前全球信息。所开发的影响因子可用于进一步评估，这将有助于政策制定者、行业和消费者做出决策，努力将海洋入侵的影响降至最低，并且开发这些因子是为了与不同的相关归宿因子兼容。
在线版本包含可在10.1007/s11367-024-02325-7获取的补充材料。
