Irene Martins , Alexandra Guerra , Cândida Gomes Vale , Cândido Xavier , Inês Martins , Marlene Pinheiro , Teresa Neuparth , Joana R. Xavier , Pedro Duarte , Miguel M. Santos , Ana Colaço
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Scenario simulations were conducted to mimic the effects of increased concentrations of toxic sediment plumes on mussel filtration rates, the absorption of reduced substrates by their endosymbionts, and the energetic costs associated with metal toxicity. Data were sourced from <em>B. azoricus</em> and, when necessary, from proxy species. One disturbance scenario (EF1) incorporated measured rates and realistic parameters, while the other (EF2) was intentionally designed to encompass cumulative effects and uncertainties, representing a potential worst-case scenario. Both disturbance scenarios were initiated at three different timings (0, 1200 and 2400 days) to accommodate the mining effects at different stages of the mussels' life cycle. Results indicate that <em>B. azoricus</em> is significantly impacted by toxic sediment plumes, particularly during earlier life stages, potentially leading to severe growth impairment and mortality. These results were integrated into a food web model of the MG vent field, revealing that disruptions to the energetic balance of the vent mussel have widespread consequences for the entire ecosystem. 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引用次数: 0
摘要
由于一直缺乏对深海采矿情景的环境风险评估(ERA),该行业对海洋生态系统的潜在影响在很大程度上仍不为人所知。为了填补这一空白,开发了一个动态能量预算(DEB)模型,以研究深海采矿产生的有毒沉积物羽流对大西洋深海贻贝 Bathymodiolus azoricus 的能量预算的影响。模型校准基于在 Menez Gwen(MG)喷口区(大西洋中脊-MAR)观测到的环境条件,假设 B. azoricus 的寿命为 10 年,壳的最大长度为 119 毫米。进行情景模拟是为了模拟有毒沉积物羽流浓度增加对贻贝过滤速率的影响、贻贝内共生体对减少的基质的吸收以及与金属毒性相关的能量成本。数据来源于 B. azoricus,必要时也来源于替代物种。其中一种干扰情景(EF1)包含了测量速率和现实参数,而另一种干扰情景(EF2)则是有意设计的,包含了累积效应和不确定性,代表了潜在的最坏情况。两种干扰情景都在三个不同的时间(0、1200 和 2400 天)启动,以适应贻贝生命周期不同阶段的采矿影响。结果表明,B. azoricus 受到有毒沉积物羽流的严重影响,尤其是在早期生命阶段,可能导致严重的生长障碍和死亡。这些结果被整合到 MG 喷口场的食物网模型中,揭示了喷口贻贝能量平衡的破坏会对整个生态系统产生广泛的影响。总之,我们认为这一数值框架为在深海工业采矿背景下开展 ERA 和环境影响评估(EIA)提供了宝贵的工具。
Developing a dynamic energy budget model to project potential effects of deep-sea mining plumes on the Atlantic deep-sea mussel, Bathymodiolus azoricus
Due to the consistent lack of Environmental Risk Assessment (ERA) for deep-sea mining scenarios, the potential impacts of this industry on marine ecosystems remain largely unknown. In order to fill this gap, a Dynamic Energy Budget (DEB) model was developed to study the consequences of toxic sediment plumes derived from deep-sea mining on the energy budget of the Atlantic deep-sea mussel, Bathymodiolus azoricus. Model calibration was based on environmental conditions observed at the Menez Gwen (MG) vent field (Mid-Atlantic Ridge- MAR), assuming a B. azoricus lifespan of 10 years and a maximum shell length of 119 mm. Scenario simulations were conducted to mimic the effects of increased concentrations of toxic sediment plumes on mussel filtration rates, the absorption of reduced substrates by their endosymbionts, and the energetic costs associated with metal toxicity. Data were sourced from B. azoricus and, when necessary, from proxy species. One disturbance scenario (EF1) incorporated measured rates and realistic parameters, while the other (EF2) was intentionally designed to encompass cumulative effects and uncertainties, representing a potential worst-case scenario. Both disturbance scenarios were initiated at three different timings (0, 1200 and 2400 days) to accommodate the mining effects at different stages of the mussels' life cycle. Results indicate that B. azoricus is significantly impacted by toxic sediment plumes, particularly during earlier life stages, potentially leading to severe growth impairment and mortality. These results were integrated into a food web model of the MG vent field, revealing that disruptions to the energetic balance of the vent mussel have widespread consequences for the entire ecosystem. Overall, we argue that this numerical framework offers a valuable tool for conducting ERA and Environmental Impact Assessments (EIA) in the context of industrial deep-sea mining.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.