Floodplain wetlands, which are critical for ecosystem health and human well-being, are increasingly threatened by intensified hydrological variability and extreme hydrological events. However, it remains unclear how floodplain wetlands respond to these hydrological changes. Here, from the perspective of both endogenous and exogenous memory of vegetation, we explored the response of Poyang Lake Wetland (PYLW) to multi-timescale hydrological dynamics. First, we applied a dynamic threshold method to extract land surface phenology from 2011 to 2020, subdividing the year into four sub-seasons. Next, based on wetland vegetation mapping, the Carnegie-Ames-Stanford Approach (CASA) was used to simulate monthly net primary productivity (NPP). Then, with the NPP and inundation frequency time-series data, we assessed the time-lagged and cumulative response of PYLW vegetation to hydrological variability (exogenous memory) through Pearson rank correlation analysis. Subsequently, we employed partial correlation analysis, with the control of critical temporal hydrological variability, to evaluate the seasonal vegetation growth carryover (VGC) effect (endogenous memory). Finally, we proposed to use the seasonal VGC effect for modelling vegetation vulnerability under various extreme hydrological scenarios. The results reveal that the time-lagged and cumulative effects of hydrological variability on vegetation growth in PYLW reached the peak averagely after 6.51 and 7.08 months, respectively. The extreme hydrological scenarios in PYLW were categorized into three types of flood-only, flood-after-drought, and flood-before-drought. In the flood-after-drought scenario, vegetation generally showed high vulnerability, and the most vulnerable vegetation type varied across different scenarios. Our findings provide effective support for vegetation restoration, hydrological management, and biodiversity conservation in floodplains.

中文翻译：

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洪泛区湿地植被脆弱性评估——基于各种极端水文情景下季节性生长的遗留效应


洪泛区湿地对生态系统健康和人类福祉至关重要，但日益受到加剧的水文变化和极端水文事件的威胁。然而，目前尚不清楚洪泛区湿地如何应对这些水文变化。在这里，从植被的内生和外生记忆的角度，我们探讨了鄱阳湖湿地 （PYLW） 对多时间尺度水文动力学的响应。首先，采用动态阈值法提取 2011—2020 年地表物候，将一年细分为 4 个子季节。接下来，基于湿地植被制图，使用 Carnegie-Ames-Stanford 方法 （CASA） 模拟每月净初级生产力 （NPP）。然后，利用 NPP 和淹没频率时间序列数据，我们通过 Pearson 秩相关分析评估了 PYLW 植被对水文变化（外生记忆）的时间滞后和累积响应。随后，我们采用偏相关分析，在控制临界时间水文变化的情况下，评估季节性植被生长遗留 （VGC） 效应（内生记忆）。最后，我们建议使用季节性 VGC 效应来模拟各种极端水文情景下的植被脆弱性。结果表明，水文变化对PYLW植被生长的时间滞后和累积效应分别在6.51 和7.08 个月后达到峰值。PYLW 中的极端水文情景分为三种类型：仅洪水、干旱后洪水和干旱前洪水。在干旱后涝情景中，植被通常表现出高度脆弱性，最脆弱的植被类型在不同情景中有所不同。 我们的研究结果为洪泛区的植被恢复、水文管理和生物多样性保护提供了有效支持。