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Aim: Climate change is expected to have important effects on plant phenology and carbon storage, with further shifts predicted in the future. Therefore, we proposed the community carbon accumulation rate (CAR) from the start of the growing season (SOS) to the peak of the growing season (POS) to fill the gap that the dynamic interactions between plant phenology and plant carbon research. Location: Tibetan Plateau.Major taxa: Alpine grassland plants. Time period: 2015.Methods: We conducted a transect survey across grasslands to measure community aboveground net primary production and carbon concentration. Additionally, phenology indicator data (SOS and POS) were extracted from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index version 3 database. Next, we used 'changepoint' analysis to detect the patterns of CARs, and performed linear regression and one-way ANOVA to explore the

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Scientists have aimed at exploring land use and land cover change (LUCC) and modeling future landscape pattern in order to improve our understanding of the causes and consequences of these phenomena. This study addresses LUCC in the upper reaches of Minjiang River, China, from 1974 to 2000. Based on remotely sensed images, LUCC and landscape pattern change were assessed using cross-tabulation and landscape metrics. Then, using the CLUE-S model, changes in area of four types of land cover were predicted for two scenarios considering forest polices over the next 20 years. Results showed that forestland decreased from 1974 to 2000 due to continuous deforestation, while grassland and shrubland increased correspondingly. At the same time, the farmland and settlement land increased dramatically. Landscape fragmentation in the study area accompanied these changes. Forestland, grassland, and farmland take opposite trajectories in the two scenarios, as does landscape fragmentation. LUCC has led to ecological consequences, such as biodiversity loss and lowering of ecological carrying capacity.

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