Our answers are important in guiding manufacturing management and long-lasting planning of Taiwan green jujube in Fujian Province.To explore the effects of future climate change on springtime phenology stages (first leaf storey growth stage, spring flowering phase) of rubber tree in Hainan Island, we established a rubber tree springtime phenology simulation design in line with the crop time clock model and developed a pc pc software RubberSP. The model simulation accuracy was analyzed with experimental noticed phenology information. Five international climate models (GCMs) from the combined Model Intercomparison Project state 5 (CMIP5) had been integrated making use of Bayesian Model averaging strategy (BMA) to anticipate the impacts of environment modification regarding the spring phenology of rubberized tree in 2020-2099 (relative to 1986-2017) under climate scenarios of RCP2.6, RCP4.5 and RCP8.5, correspondingly. The outcomes indicated that the RubberSP model had good simulation reliability, with the dedication coefficient (R2) values ranging between 0.73-0.87, the root suggest square error (RMSE) including 3.26 to 4.15 d, and the normalized root mean square error (NRMSE) of 3.4%-7.4% between measured and simulated phenology stages. The doubt of a single GCM could be prevented by BMA strategy, which could better mirror the change trend of temperature. Temperature of Hainan Island in the end of 21 century, beneath the situations of RCP2.6, RCP4.5 and RCP8.5, would boost by significantly more than 0.3, 1.0 and 2.5 ℃ compared to the baseline, correspondingly. The spring phenology stages seems early in the day and yield would upsurge in the near future environment scenario. The full time isoline of spring phenology stages would go forward to northwest, which suggested that most suitable area for plastic tree plantation in Hainan Island would increase into the northwest. The spatial huge difference associated with the very first leaf storey growth stage could be much more evident, but not for spring flowering phase. The amplitude of rubber tree springtime phenology variations ended up being closely pertaining to the increases of temperature under various RCP situations, with the most obvious change under RCP8.5 situation and most mild change under RCP2.6 scenario.Grassland is a vital kind of terrestrial ecosystem. Utilizing remote sensing technology to examine the change and driving force of native grassland output at-large scale is a vital way to comprehend the ecological status of grassland. In this research, potential and actual net primary productivity (NPP) of Xilingol steppe from 2000 to 2018 had been analyzed based on climatic design and light-use performance model, respectively. NPP damage worth driven by person tasks had been computed from the distinction between prospective and actual NPP. The least square strategy was used to evaluate the temporal and spatial variation of NPP in Xilingol therefore the driving role of environment and person activities on NPP. The outcome revealed that NPP in Xilingol increased from west to east, with mean yearly NPP being 271.54 g C·m-2·a-1, the area with increased NPP (grassland restoration) being 36500 km2, plus the area with decreased NPP (grassland degradation) being 59900 km2. The possibility NPP tended to increase underneath the power of temperature and precipitation, with a typical 2-DG price annual boost of 6.5 g C·m-2·a-1, which suggested that local weather played a confident role in the enhancement of NPP in Xilingol steppe, and therefore peoples activities were the primary power for grassland degradation. The value of NPP harm driven by real human activities decreased from east to west and from south to north, utilizing the highest worth in Wuzhumuqin meadow and south steppe. Real human tasks, such as for instance mining and reclamation, had the most obvious negative impact on grassland NPP.Under the backdrop of weather modification, the spatial-temporal distribution of precipita-tion in Heilongjiang Province is unequal, and drought and flood usually modification, which will be not conducive to the safety of soybean manufacturing for the province. To make clear the impact process of drought and flood when you look at the growing season on soybean yield in Heilongjiang Province, we analyzed the time-series qualities of drought and flood in soybean developing period as well as its impact on soybean yield in different development phases, based on data of day-to-day precipitation from 60 meteorological stations during 1961 to 2018 and soybean yield in identical period, with the standard precipitation list (SPI) whilst the drought and flooding assessment list. The outcome indicated that, from 1961 to 2018, the influence array of drought in soybean growing period in Heilongjiang Province showed a weak decreasing trend, while compared to flooding revealed a weak increasing trend. In the same period, the strength of both drought and flood revealed a weak incrhere was a little bit more precipitation, nevertheless the reasonable and above-moderate degrees of flooding would cause the reduction. When you look at the North, the fluctuation of soybean yield ended up being primarily impacted by flooding, whilst in the East, the results of drought and flood on soybean yield were similar.To comprehend the dynamics of temperate woodland in Northeast Asia as well as its response to climate change under the scenario of worldwide change, we examined the temporal and spatial modifications of normalized distinction plant life index (NDVI) and their particular correlation with temperature and precipitation of Changbai Mountain Nature Reserve into the developing period during 2001 and 2018, in line with the remote sensing database of MODIS with an answer of 250 m, land area temperature information with a resolution of just one km and meteorological information into the examined and surrounding area.