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Divergent response of seasonally dry tropical vegetation to climatic variations in dry and wet seasons

机译:季节性干燥热带植被对干湿季节气候变化的发散响应

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Interannual variations of photosynthesis in tropical seasonally dry vegetation are one of the dominant drivers to interannual variations of atmospheric CO2 growth rate. Yet, the seasonal differences in the response of photosynthesis to climate variations in these ecosystems remain poorly understood. Here using Normalized Difference Vegetation Index (NDVI), we explored the response of photosynthesis of seasonally dry tropical vegetation to climatic variations in the dry and the wet seasons during the past three decades. We found significant (p&0.01) differences between dry and wet seasons in the interannual response of photosynthesis to temperature ((int)) and to precipitation ((int)). (int) is similar to 1%degrees C-1 more negative and (int) is similar to 8% 100mm(-1) more positive in the dry season than in the wet season. Further analyses show that the seasonal difference in (int) can be explained by background moisture and temperature conditions. Positive (int) occurred in wet season where mean temperature is lower than 27 degrees C and precipitation is at least 60mm larger than potential evapotranspiration. Two widely used Gross Primary Productivity (GPP) estimates (empirical modeling by machine-learning algorithm applied to flux tower measurements, and nine process-based carbon cycle models) were examined for the GPP-climate relationship over wet and dry seasons. The GPP derived from empirical modeling can partly reproduce the divergence of (int), while most process models cannot. The overestimate by process models on negative impacts by warmer temperature during the wet season highlights the shortcomings of current carbon cycle models in representing interactive impacts of temperature and moisture on photosynthesis. Improving representations on soil water uptake, leaf temperature, nitrogen cycling, and soil moisture may help improve modeling skills in reproducing seasonal differences of photosynthesis-climate relationship and thus the projection for impacts of climate change on tropical carbon cycle.
机译:热带季节性干燥植被中光合作用的依赖性变化是持续变化的大气二氧化碳增长率的主导司机之一。然而,光合作用对这些生态系统中气候变化的季节性差异仍然明白很差。在这里,使用归一化差异植被指数(NDVI),我们探讨了过去三十年中季节性干燥热带植被的光合作用对湿季节的气候变化。我们发现在光合作用对温度((int))和沉淀((int))之间的干燥和潮湿季节之间的显着(p& 0.01)差异。 (int)类似于1%的C-1更负,(int)类似于旱季的旱季中的8%100mm(-1)。进一步的分析表明,(INT)的季节差异可以通过背景水分和温度条件来解释。阳性(int)发生在湿季,平均温度低于27℃,并且沉淀比潜在的蒸发至少60mm。两种广泛使用的总初级生产率(GPP)估计(通过应用于助焊塔测量的机器学习算法和九个过程的碳循环模型的实证建模),用于GPP-气候关系,对潮湿和干燥的季节。源自经验建模的GPP可以部分再现(int)的分歧,而大多数过程模型不能。潮湿季节温暖温度对负面影响的过程模型高估突出了当前碳循环模型的缺点,代表了光合作用温度和水分的交互式影响。改善土壤水吸收,叶温,氮循环和土壤水分的表现可能有助于提高繁殖光合气候关系季节性差异的建模技巧,从而投影气候变化对热带碳循环的影响。

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