Formation of Assimilating Surface Areas and Photosynthetic Potential of Various Assimilating Parts of Wheat Species under Drought Conditions

Some of environmental factors (weather sharp fluctuations) may accrue stress within a few minutes, while others may not be long for this period of stress in this situation. It has formed stress in organisms, to eliminate the stress, there starts over various biochemical and physiological mechanisms for protection. Therefore, a large variety of plants to examine ways of increasing the resistance against stress factors have a scientific and practical importance. Thus, the primary processes of photosynthesis, based on the results of the study and its corresponding morphophysiological higher photochemical activity, has been found in a range of genotypes. Their leaves and plants assimilate the biological productivity of the intensity of the symptoms associated with the use of photosynthetic learned of the opportunity to create a new perspective varieties. This allows the research to prove the expansion of the electronic delivery of high-yielding genotypes and phosphorised chloroplast high speed, as well as the pH of thylacoid membranes are characterized by a great price, also photosynthetic electron transport, CO2 assimilation and it was approved to be the link between productivity.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Analysis of Drought in Poyang Lake

[Objective] The drought situation and causes in Poyang Lake were analyzed.[Method] In response to the drought in Poyang Lake in ten years ago and in recent 10 years,the causes of drought in Poyang Lake were discussed.[Result] Drought occurred frequently in Poyang Lake and the consecutive serious drought occurred now and then.The water level in Poyang Lake since 21st century was lower.The drought in Poyang Lake was due to reduction of precipitation,low water level in Yangtze River and 'five lakes',hydraulic project,industrial and agricultural water increase and other aspects.[Conclusion] The study provided theoretical basis for the formulation of drought prevention measures by relevant departments.

Analysis of the forest fires in the Antalya region of Turkey using the Keetch–Byram drought index

We investigated the correlation of large fires（[300 ha） from 1992 to 2013 within the borders of the Antalya Regional Directorate of Forestry using the Keetch–Byram drought index（KBDI）. Daily KBDI values were calculated for each year, and values for the period before the year 2000 differed significantly from those after2000. After 2000（large fires occurred in 2004, 2006, 2007,2008, 2010, and 2013）, when KBDI values increased, the KBDI, but not the number of fires, was inversely correlated with the natural log of the burned area（NLBA）. While there were both high and low KBDI values when the NLBA was small, only high KBDI values were associated with high NLBA values. Particularly for logarithmic values of 4 and higher, KBDI values increased in parallel with increases in NLBA values. On the basis of a Mann–Whitney U test done in addition to a Pearson correlation test, we found that when the burned areas were grouped according to small and large areas, the KBDI could be used to distinguish the two groups. Using a conditional probability analysis, we found that 4th, 5th and 6th class KBDI values may lead to large fires at the 60 % possibility.Similarly, the possibility of large fires greater than the median burned area in any given 6 years was found to be48 %. In addition, while the mean value of KBDI is 390.51 for the period from May to September for these 6 years, it is 359.93 for the other years. Consequently, the area burned also increased as the KBDI classes（Class 0： 0–99, Class 1：100–199, Class 2： 200–299, Class 3： 300–399, Class 4：400–499, Class 5： 500–599, Class 6： 600–699, and Class 7：700–800） increase.