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Phenological modeling is not only important for the projection of future changes of certain phenophases but also crucial for systematically studying the spatiotemporal patterns of plant phenology. Based on ground phenological observations, we used two existing tem-perature-based models and 12 modified models with consideration of precipitation or soil moisture to simulate the bud-burst date (BBD) of four common herbaceous plants—Xanthium sibiricum, Plantago asiatica, Iris lactea and Taraxacum mongolicum—in temperate grasslands in Inner Mongolia. The results showed that (1) increase in temperature promoted the BBD of all species. However, effects of precipitation and soil moisture on BBD varied among species. (2) The modified models predicted the BBD of herbaceous plants with R2 ranging from 0.17 to 0.41 and RMSE ranging from 9.03 to 11.97 days, better than classical thermal models. (3) The spatiotemporal pattern of BBD during 1980–2015 showed that species with later BBD, e.g. X. sibiricum (mean: day of year 135.30) exhibited an evidently larger spatial difference in BBD (standard deviation: 13.88 days) than the other species. Our findings suggest that influences of temperature and water conditions need to be considered simultaneously in predicting the phenological response of herbaceous plants to climate change.

Significance Decline in winds over past decades were observed over high northern latitudes (>50°), yet its influence on the date of autumn leaf senescence (DFS) remains unknown. Using ground observations, flux measurements, and remote sensing imagery, here we show that decline in winds significantly extended DFS over high latitudes at a magnitude comparable with the temperature and precipitation effects. We found that decline in winds reduces evapotranspiration, causes fewer damaging effects, and also results in decreased cooling effect. Our results therefore are of great significance for carbon cycle modeling because an improved algorithm based on these findings projected overall widespread earlier DFS by the end of this century, contributing potentially to a positive feedback to climate., The high northern latitudes (>50°) experienced a pronounced surface stilling (i.e., decline in winds) with climate change. As a drying factor, the influences of changes in winds on the date of autumn foliar senescence (DFS) remain largely unknown and are potentially important as a mechanism explaining the interannual variability of autumn phenology. Using 183,448 phenological observations at 2,405 sites, long-term site-scale water vapor and carbon dioxide flux measurements, and 34 y of satellite greenness data, here we show that the decline in winds is significantly associated with extended DFS and could have a relative importance comparable with temperature and precipitation effects in contributing to the DFS trends. We further demonstrate that decline in winds reduces evapotranspiration, which results in less soil water losses and consequently more favorable growth conditions in late autumn. In addition, declining winds also lead to less leaf abscission damage which could delay leaf senescence and to a decreased cooling effect and therefore less frost damage. Our results are potentially useful for carbon flux modeling because an improved algorithm based on these findings projected overall widespread earlier DFS than currently expected by the end of this century, contributing potentially to a positive feedback to climate.

Extending phenological records into the past is essential for the understanding of past ecological change and evaluating the effects of climate change on ecosystems. A growing body of historical phenological information is now available for Europe, North America, and Asia. In East Asia, long-term phenological series are still relatively scarce. This study extracted plant phenological observations from old diaries in the period 1834–1962. A spring phenology index (SPI) for the modern period (1963–2009) was defined as the mean flowering time of three shrubs (first flowering of Amygdalus davidiana and Cercis chinensis, 50% of full flowering of Paeonia suffruticosa) according to the data availability. Applying calibrated transfer functions from the modern period to the historical data, we reconstructed a continuous SPI time series across eastern China from 1834 to 2009. In the recent 30 years, the SPI is 2.1–6.3 days earlier than during any other consecutive 30 year period before 1970. A moving linear trend analysis shows that the advancing trend of SPI over the past three decades reaches upward of 4.1 d/decade, which exceeds all previously observed trends in the past 30 year period. In addition, the SPI series correlates significantly with spring (February to April) temperatures in the study area, with an increase in spring temperature of 1°C inducing an earlier SPI by 3.1 days. These shifts of SPI provide important information regarding regional vegetation-climate relationships, and they are helpful to assess long term of climate change impacts on biophysical systems and biodiversity.