厦门大学学报（自然科学版）2025，Vol.64Issue(3)：433-445,13.DOI:10.6043/j.issn.0438-0479.202410008
基于Ecospace模型的七连屿多元生境海洋生态系统空间结构和功能分析
Spatial structure and function analyses of marine ecosystem in multi-habitats of the Qilianyu Islands based on Ecospace model
摘要
Abstract
[Objective]The coral reefs,seagrass beds,and open waters of the Xisha Islands form interconnected habitats that are crucial for biodiversity and ecosystem services.However,human activities and environmental pressures are threatening their ecological balance.This study aims to use the Ecopath and Ecospace models to analyze the spatial distribution patterns of energy and material flows in these habitats in the waters of the Qilianyu Islands in the Xisha Islands.The research objectives include assessing the maturity and stability of the ecosystem,as well as the contributions of specific habitats to biodiversity and trophic dynamics,to provide a basis for targeted conservation strategies.[Methods]This study combines the Ecopath model,which is used to quantify energy flow and trophic interactions,with the Ecospace model to assess the spatial heterogeneity of habitats.Data were obtained from comprehensive fishery resource surveys and underwater visual surveys in the Qilianyu area.The Ecopath model covers various functional groups ranging from primary producers(such as phytoplankton,algae and seagrass)to top predators(such as cartilaginous fish),while the Ecospace model maps the biomass distribution of coral reefs,seagrass beds,and open waters.Key parameters include the production/biomass ratio,the food matrix,and the productivity of specific habitats.[Results]The ecosystem of the Qilianyu Islands shows relatively low maturity and stability,as indicated by a system connectance index of 0.31 and an omnivory index of 0.24.The trophic levels range from 1.00(primary producers)to 3.76(cartilaginous fish).The total primary production/respiration ratio(TPP/TR)and the primary production/biomass ratio(TPP/TB)are 2.47 and 13.91,respectively,reflecting a moderate energy transfer efficiency primarily driven by the grazing food chain(with 60％dependence on primary producers).The analysis of specific habitats shows that the seagrass bed has the highest biomass density(228.89 t/km2)but the lowest average trophic level(2.18),highlighting its role as a nursery ground and carbon sink.The coral reef ranks second in biomass(213.32 t/km2)but exhibits the highest biodiversity(Simpson index:2.64;Shannon index:2.50;evenness index:0.80),emphasizing its ecological complexity and resilience.The open water has the lowest biomass(96.74 t/km2)and biodiversity(Shannon index:2.30;Simpson index:2.40;evenness index:0.73),but it supports a higher trophic level(average value:2.50),indicating its importance for top predators and the pelagic food web.The energy flow forms a pyramid structure,with a total transfer efficiency of 16.19％.The seagrass bed makes a particularly prominent contribution to the system productivity,while the coral reef maintains the stability of the ecosystem through diverse trophic interactions.[Conclusion]Although coral reefs have lower biomass than seagrass beds,They are biodiversity hotspots and play a key role in maintaining ecosystem stability.The seagrass bed promotes biomass accumulation,but it needs to be protected to avoid sediment accumulation and eutrophication.Although the open water has relatively low productivity,it maintains a higher trophic level network that is crucial for fisheries.The low system maturity(TPP/TR＜3)indicates that the ecosystem is vulnerable to external stress factors such as overfishing and climate change.Management efforts should prioritize cross-habitat conservation measures,such as expanding marine protected areas in coral reef areas,regulating fishery activities in open waters,and restoring seagrass habitats to enhance carbon sequestration capacity.关键词
西沙群岛/珊瑚礁/海草床/Ecospace模型/海洋生态系统Key words
Xisha Islands/coral reef/seagrass meadow/Ecospace model/marine ecosystem分类
海洋学引用本文复制引用
王昊宇,张新艳,陈炜霖,李元超,邱书婷,陈琳,杜建国..基于Ecospace模型的七连屿多元生境海洋生态系统空间结构和功能分析[J].厦门大学学报（自然科学版）,2025,64(3):433-445,13.基金项目
国家自然科学基金(42176153) （42176153）
国家重点研发计划(2022YFF0802204) （2022YFF0802204）
