在北美多样化的草原上预测赛季结束时间
Alison K Post1,2, Andrew D Richardson3
1Center for Ecosystem Science and Society, and School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA. alison.post@colorado.edu.
Oecologia
|February 28, 2025
概括
新的草原模型使用温度,干燥度和季节开始 (SOS) 数据准确预测季末 (EOS) 时间. 这些模型改善了地球系统模型中的生态预测.
科学领域:
- 生态生态学 生态生态学
- 气候科学 气候科学
- 遥感 遥感 遥感 遥感
背景情况:
- 气候变化对植被现象学产生重大影响,影响生态系统过程.
- 现有的赛季末 (EOS) 模型在草原上表现不佳,并为森林开发.
- 准确的EOS预测对于了解气候变化对草原的影响至关重要.
研究的目的:
- 开发和验证一个改进的EOS草原现象学模型.
- 确定影响草原EOS时间的关键驱动因素.
- 增强地球系统模型对草原生态系统的预测能力.
主要方法:
- 利用来自PhenoCam网络的重复数字图像在44个北美草原地区进行EOS日期提取.
- 通过使用212个站点年的数据,对比了20个新的EOS模型与3个现有模型.
- 为六个不同的气候区域优化了模型参数,以提高准确性.
主要成果:
- 与现有模型 (RMSE 43-46 天) 相比,新开发的 EOS 模型表现出大幅改善的性能 (RMSE 22-33 天).
- 性能最好的模型包含了累积的寒冷或干燥的值,取决于赛季开始后的天数 (SOS).
- 包括SOS日期在内显著改善了所有型号的合适性,突出了赛季开始和结束时间之间的相关性.
结论:
- 草地EOS时间受天气变量 (温度,湿度) 和生长季节 (SOS) 开始时间的组合的影响.
- 区域特定参数优化进一步提高了模型性能 (RMSE 4-19 天).
- 预计开发的EOS模型将在地球系统模型中改善草原动态和生态系统过程的预测.
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