日本地球惑星科学連合2018年大会

講演情報

[EE] Eveningポスター発表

セッション記号 A (大気水圏科学) » A-OS 海洋科学・海洋環境

[A-OS09] Marine ecosystems and biogeochemical cycles: theory, observation and modeling

2018年5月23日(水) 17:15 〜 18:30 ポスター会場 (幕張メッセ国際展示場 7ホール)

コンビーナ:伊藤 進一(東京大学大気海洋研究所)、平田 貴文(北海道大学地球環境科学研究院)、Eileen E Hofmann (共同)、Enrique N Curchitser (Rutgers University New Brunswick)

[AOS09-P11] Modeling the coastal ecosystem complex: present situation and challenges

*伊藤 幸彦1竹茂 愛吾2笠井 亮秀3木村 伸吾1 (1.東京大学大気海洋研究所、2.水産研究・教育機構国際水産研究所、3.北海道大学水産学部)

キーワード:沿岸複合生態系、個体群連結性、ハビタット非均一性、個体発生、栄養的相互作用

To enhance numerical modeling of the coastal ecosystem complex (CEC), we reviewed the CEC and related concepts along with the current coastal ecosystem model framework in this study. We identified two model implementation paths from the initial objectives to numerical models: specific model building, and the use of existing model frameworks. As the CEC is still at the conceptual stage, both paths are possible. Four important ecological features of CEC modeling (population connectivity, habitat heterogeneity, ontogeny of organisms, and trophic interactions) were also identified. Models for population connectivity, species distributions, life histories, and food webs were categorized using these features. We found that some previously established concepts (between–habitat interactions, coastal ecosystem mosaic, and seascape nursery) overlap with the CEC concept. Several existing integrated model frameworks were reviewed, focusing on their potential to simulate CEC processes. Building specific models for the CEC at the current conceptual stage will be challenging, and modification of existing models will be needed if they are to be used for CEC modeling. Habitat function, ontogenetic development in early life stages, and recruitment variability are important factors when modifying existing models for the development of CEC models. Although model complexity should become high to reproduce observed ecoclogical processes, an intermediate level of model ccomplexity is feasible to decrease parameter uncertainty in models for fisheries management.