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Quercus myrsinifolia is one of the dominant species in the evergreen broad-leaf forest on the southern slope of Shennongjia. The study of spatial distribution pattern and spatial correlation of Q. myrsinifolia population will help to understand population development and potential ecological processes; as well as the structure and biodiversity maintenance mechanism of evergreen broad-leaf forests at the northern edge of the subtropics. Based on forest dynamic monitoring data from one 1 hm2 permanent plot on the southern slope of Shennongjia' we employed pair correlation functions g( r) and marked correlation functions to analyze the diameter structure of the Q. myrsinifolia population; spatial distribution patterns at different diameter classes; and intraspecific and interspecific spatial associations. The results showed that diameter structure of Q. myrsinifolia population exhibited an inverted ' J ' - shaped distribution; suggesting a healthy regeneration status and belonging to a growing population type. The spatial distribution showed a decreasing trend in aggregation with increasing diameter. Positive correlations among individuals strengthened with closer diameter classes; while weakening with larger diameter differences. Interspecific spatial associations showed an increasing correlation of Q. myrsinifolia with understory dominant species with increasing spatial scales; but no correlation was observed with canopy-dominant species. Our results suggested that the spatial pattern of Q. myrsinifolia populations on the southern slope of Shennongjia was mainly influenced by habitat filtering ' seed dispersal limitation; and intraspecific and interspecific competition. Furthermore; the adaptive strategies of Q. myrsinifolia varied when they coexisted with different species. [ABSTRACT FROM AUTHOR]

Mixed evergreen-deciduous broadleaved forest is the transitional type of evergreen broadleaved forest and deciduous broadleaved forest, and plays a unique eco-hydrologic role in terrestrial ecosystem. We investigated the spatio-temporal patterns of throughfall volume of the forest type in Shennongjia, central China. The results indicated that throughfall represented 84.8% of gross rainfall in the forest. The mean CV (coefficient of variation) of throughfall was 27.27%. Inter-event variability in stand-scale throughfall generation can be substantially altered due to changes in rainfall characteristics, throughfall CV decreased with increasing rainfall amount and intensity, and reached a quasi-constant level when rainfall amount reached 25 mm or rainfall intensity reached 2 mm h−1. During the leafed period, the spatial pattern of throughfall was highly temporal stable, which may result in spatial heterogeneity of soil moisture.

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Phenology is an important factor indicating environmental changes and regulates the variations of carbon, water, and energy exchange. However, phenology models exhibit large uncertainties due to limited understanding of its mechanisms. In this study, we modified deciduous phenology scheme based on the evaluation of different phenological models using long‐term observations at Chinese Ecosystem Research Network with CLM4.5. The alternating leaf unfolding model and summer‐influenced autumn leaf falling model that we proposed, performed best in simulating leaf‐unfolding and leaf‐falling. Compared with the observed and remote‐sensed phenology, the modified model could better simulate the phenological dates at the site and regional scale. Moreover, the modified model improved the simulation of gross primary productivity (GPP) by decreasing the errors of modeled carbon uptake duration and amplitude. Furthermore, the advance in leaf‐unfolding slowed down from 0.20 days/year during 1981–2015 to 0.11 days/year during 2016–2100 under RCP4.5 because of the slowdown of climate warming, but the delay in leaf‐falling changed little. By the last decade of the twenty‐first century, the leaf‐unfolding would advance (8 days) and leaf‐falling would delay (16 days). The subtropical region had large interannual variation (IAV) in leaf‐unfolding because of the high sensitivity to temperature. The phenological dates IAV in the cold temperate region increased due to enhanced temperature IAV. We suggest that the deciduous phenology models, especially the leaf‐falling process, used in Community Land Model need to be improved to reduce the errors in predicting phenology and carbon flux in the future. Plain Language Summary: As an important factor indicating climate and environmental changes, phenology plays an important role in regulating the variation of carbon, water, and energy exchange. Due to limited understanding of phenology mechanisms, the simulation of phenology remains large uncertainties. In this study, we evaluated and modified the leaf unfolding and leaf falling models using the long‐term phenological observations with the Community Land Model (CLM4.5), validated the modified leaf‐unfolding and leaf‐falling models by observed phenology and remote‐sensing phenology data, examined the ability of CLM4.5 with modified deciduous phenology submodels in simulating gross primary productivity, and used the modified phenology models to predict the changes in phenological dates in the future. Our results suggest that the deciduous phenology models, especially the leaf‐falling process, used in the CLM is urgent to be improved to reduce the errors in predicting growing season length and carbon fluxes in deciduous forests in the context of climate change. Key Points: The involvement of chill accumulation with heat requirement in leaf unfolding models can improve the model performanceWe propose a new leaf falling model by considering the relationship between summer temperature and aging state threshold, which improves the model performanceThe revise of deciduous phenological model in CLM4.5 improves the simulation of gross primary productivity by influencing carbon uptake duration and amplitude [ABSTRACT FROM AUTHOR]