Large-scale interventions may delay decline of the Great Barrier Reef

On the iconic Great Barrier Reef (GBR) the cumulative impacts of tropical cyclones, marine heatwaves and regular outbreaks of coral-eating crown-of-thorns starfish (CoTS) have severely depleted coral cover. Climate change will further exacerbate this situation over the coming decades unless effective interventions are implemented. Evaluating the efficacy of alternative interventions in a complex system experiencing major cumulative impacts can only be achieved through a systems-modeling approach. We have evaluated combinations of interventions using a coral reef meta-community model. The model consisted of a dynamic network of 3753 reefs supporting communities of corals and CoTS connected through ocean larval dispersal, and exposed to changing regimes of tropical cyclones, flood plumes, marine heat waves and ocean acidification. Interventions included reducing flood plume impacts, expanding control of CoTS populations, stabilising coral rubble, managing solar radiation, and introducing ..., The datset consists of the model plus model generated outputs associated with the publication: Large-scale interventions may delay decline of the Great Barrier Reef (RSOS-201296). 

NetLogo code for the Coral Community Network (CoCoNet) model: CoCoNet2_RSOS.nlogo (NetLogo version 6.04 or later: http://ccl.northwestern.edu/netlogo/).
GIS files used by the CoCoNet code: GBR_reef_* and Coastline.*

Excel file containing model outputs (averaged over all reefs) covering the historical period used for model calibration: Condie et al 1985-2020 model data.xlsx

Excel file containing model outputs (averaged over all reefs) covering the future projection period used to test interventions: Condie et al 2000-2070 model data with interventions.xlsx

, All data within Excel files are averaged across all reefs on the Great Barrier Reef.Â

在标志性的大堡礁（Great Barrier Reef, GBR），热带气旋、海洋热浪以及定期爆发的食珊瑚长棘海星（crown-of-thorns starfish, CoTS）的累积影响已严重削弱了珊瑚覆盖率。气候变化将在未来数十年进一步加剧这一态势，除非采取有效干预措施。在遭受多重累积性严重影响的复杂生态系统中，评估不同干预手段的有效性唯有通过系统建模方法方可实现。我们借助珊瑚礁元群落模型对多种干预组合进行了评估。该模型构建了由3753个珊瑚礁组成的动态网络，这些珊瑚礁承载着珊瑚与长棘海星群落，并通过海洋幼体扩散相互连接，同时受热带气旋、洪水羽流、海洋热浪以及海洋酸化的动态环境胁迫。干预手段包括减轻洪水羽流影响、扩大长棘海星种群防控、稳定珊瑚碎屑、管理太阳辐射以及引入……。本数据集包含该模型以及与发表论文《大规模干预或可延缓大堡礁的衰退》（RSOS-201296）相关的模型生成结果。
珊瑚群落网络（Coral Community Network, CoCoNet）模型的NetLogo代码：CoCoNet2_RSOS.nlogo（需使用NetLogo 6.04或更高版本：http://ccl.northwestern.edu/netlogo/）。
CoCoNet代码所使用的GIS文件：GBR_reef_* 与 Coastline.*。
包含模型输出结果（所有珊瑚礁的平均值）的Excel文件，该数据集覆盖用于模型校准的历史时期：Condie et al 1985-2020 model data.xlsx。
包含模型输出结果（所有珊瑚礁的平均值）的Excel文件，该数据集覆盖用于测试干预措施的未来预测时期：Condie et al 2000-2070 model data with interventions.xlsx。
所有Excel文件中的数据均为大堡礁全部珊瑚礁的平均值。