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Simulating climate change scenarios established by the Intergovernmental Panel on Climate Change in aquatic mesocosms

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DataCite Commons2025-09-29 更新2026-04-25 收录
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https://figshare.com/articles/dataset/Simulating_climate_change_scenarios_established_by_the_Intergovernmental_Panel_on_Climate_Change_in_aquatic_mesocosms/30197941/1
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Climate change poses a major threat to ecosystems worldwide, with temperature changes being a key driver of ecological disruption in aquatic environments due to the limited ability of many aquatic species to relocate in response. Despite advances in aquatic experimental approaches to temperature control, most studies rely on simplified warming models that fail to capture the temporal complexity projected in climate change scenarios. Bridging the gap between predictive modeling and realistic field simulations remains a key challenge in climate research. Here, we present a novel method for simulating projected temperature changes predicted by the Intergovernmental Panel on Climate Change in field-based aquatic mesocosms. We manipulated temperature trajectories according to three climate scenarios represented by historical baseline conditions, a mitigation (RCP 4.5), and a business-as-usual (RCP 8.5) future scenario for Rio de Janeiro, Brazil. We employed an automated temperature control system, the Nayad Limno device, designed to replicate projected temperature trajectories with high precision within a three-hour window. The Nayad Limno device achieved an overall accuracy of 95% in maintaining target temperatures across all scenarios, with low error margins (MAD < 0.1°C; RSME < 1.0°C). Time series and ARIMAX analysis supported strong alignment between observed and modeled temperatures, despite sensor-level variability. The system can be readily adapted to diverse experimental contexts by following the methodology established here, using low-cost and commercially available components. Our approach enhances the realism of climate change simulations in aquatic environments, offering a flexible and scalable framework for investigating ecosystem responses under projected climate scenarios.
提供机构:
figshare
创建时间:
2025-09-29
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