Diospyros texana (Texas persimmon) is a secondary species in most Juniperus ashei/Quercus fusiformis woodlands in central Texas. It has high density, but plants are mostly in the community understory. Light response c...Diospyros texana (Texas persimmon) is a secondary species in most Juniperus ashei/Quercus fusiformis woodlands in central Texas. It has high density, but plants are mostly in the community understory. Light response curves at ambient and elevated levels of CO<sub>2</sub> and temperature were measured for D. texana. The A<sub>net</sub> (photosynthetic rate) increased significantly as both light level and CO<sub>2</sub> levels increased but not temperature. The A<sub>max</sub> (maximum photosynthetic rate) of D. texana in full sun at elevated levels of CO<sub>2</sub> was increased for all treatments. Stomatal conductance increased with levels of CO<sub>2</sub> but only if the interaction was removed from the model. Intercellular levels of CO<sub>2</sub> increased with both temperature and CO<sub>2</sub> treatments as did water use efficiency (WUE). Furthermore, light saturation (L<sub>sat</sub>) increased with CO<sub>2</sub> treatments and light compensation (L<sub>cp</sub>) increased with temperature. The dark respiration (R<sub>d</sub>) increased with both temperature and CO<sub>2</sub> treatments. Markov population models suggested D. texana populations would remain ecologically similar in the future. However, sub-canopy light levels and herbivory should be considered when examining population projections. For example, Juniperus ashei juveniles are not recruited into any canopy unless there are high light levels. Herbivory reduces the success of Quercus juveniles from reaching the canopy. These factors do not seem to be a problem for D. texana juveniles which would allow them to reach the canopy without need of a high light gap and are not prevented by herbivory. Thus, Juniperus/Quercus woodlands will change in the future to woodlands with D. texana a more common species.展开更多
funded by the program supported by the National Key Technologies R＆D Program of China during the 11th Five-Year Plan period （2009BADA8B02）;the Fundamental Research Funds for the Central Universities, China （KYZ201...funded by the program supported by the National Key Technologies R＆D Program of China during the 11th Five-Year Plan period （2009BADA8B02）;the Fundamental Research Funds for the Central Universities, China （KYZ201202-3）展开更多
Rice （Oryza sativa L.） is an important food crop and requires larger amount of water throughout its life cycle as compared to other crops. Hence, water related stress cause severe threat to rice production. Drought ...Rice （Oryza sativa L.） is an important food crop and requires larger amount of water throughout its life cycle as compared to other crops. Hence, water related stress cause severe threat to rice production. Drought is a major challenge limiting rice production. It affects rice at morphological （reduced germination, plant height, plant biomass, number of tillers, various root and leaf traits）, physiological （reduced photosynthesis, transpiration, stomatal conductance, water use efficiency, relative water content, chlorophyll content, photosystem II activity, membrane stability, carbon isotope discrimination and abscisic acid content）, biochemical （accumulation of osmoprotectant like proline, sugars, polyamines and antioxidants） and molecular （altered expression of genes which encode transcription factors and defence related proteins） levels and thereby affects its yield. To facilitate the selection or development of drought tolerant rice varieties, a thorough understanding of the various mechanisms that govern the yield of rice under water stress condition is a prerequisite. Thus, this review is focused mainly on recent information about the effects of drought on rice, rice responses as well as adaptation mechanisms to drought stress.展开更多
Droughts occur in all climatic regions around the world costing a large expense to global economies. Reasonably accurate prediction of drought events helps water managers proper planning for utilization of limited wat...Droughts occur in all climatic regions around the world costing a large expense to global economies. Reasonably accurate prediction of drought events helps water managers proper planning for utilization of limited water resources and distribution of available waters to different sectors and avoid catastrophic consequences. Therefore, a means to create a simplistic approach for forecasting drought conditions with easily accessible parameters is highly desirable. This study proposes and evaluates newly developed accurate prediction models utilizing various hydrologic, meteorological, and geohydrology parameters along with the use of Artificial Neural Network (ANN) models with various forecast lead times. The present study develops a multitude of forecasting models to predict drought indices such as the Standard Precipitation Index with a lead-time of up to 6 months, and the Soil Moisture Index with a lead-time of 3 months. Furthermore, prediction models with the capability of approximating surface and groundwater storage levels including the Ross River Dam level have been developed with relatively high accuracy with a lead-time of 3 months. The results obtained from these models were compared to current values, revealing that ANN based approach can be used as a simple and effective predictive model that can be utilized for prediction of different aspects of drought scenarios in a typical study area like Townsville, North Queensland, Australia which had suffered severe recent drought conditions for almost six recent years (2014 to early 2019).展开更多
文摘Diospyros texana (Texas persimmon) is a secondary species in most Juniperus ashei/Quercus fusiformis woodlands in central Texas. It has high density, but plants are mostly in the community understory. Light response curves at ambient and elevated levels of CO<sub>2</sub> and temperature were measured for D. texana. The A<sub>net</sub> (photosynthetic rate) increased significantly as both light level and CO<sub>2</sub> levels increased but not temperature. The A<sub>max</sub> (maximum photosynthetic rate) of D. texana in full sun at elevated levels of CO<sub>2</sub> was increased for all treatments. Stomatal conductance increased with levels of CO<sub>2</sub> but only if the interaction was removed from the model. Intercellular levels of CO<sub>2</sub> increased with both temperature and CO<sub>2</sub> treatments as did water use efficiency (WUE). Furthermore, light saturation (L<sub>sat</sub>) increased with CO<sub>2</sub> treatments and light compensation (L<sub>cp</sub>) increased with temperature. The dark respiration (R<sub>d</sub>) increased with both temperature and CO<sub>2</sub> treatments. Markov population models suggested D. texana populations would remain ecologically similar in the future. However, sub-canopy light levels and herbivory should be considered when examining population projections. For example, Juniperus ashei juveniles are not recruited into any canopy unless there are high light levels. Herbivory reduces the success of Quercus juveniles from reaching the canopy. These factors do not seem to be a problem for D. texana juveniles which would allow them to reach the canopy without need of a high light gap and are not prevented by herbivory. Thus, Juniperus/Quercus woodlands will change in the future to woodlands with D. texana a more common species.
基金funded by the program supported by the National Key Technologies R&D Program of China during the 11th Five-Year Plan period (2009BADA8B02)the Fundamental Research Funds for the Central Universities, China (KYZ201202-3)
文摘funded by the program supported by the National Key Technologies R＆D Program of China during the 11th Five-Year Plan period （2009BADA8B02）;the Fundamental Research Funds for the Central Universities, China （KYZ201202-3）
基金supported by the Department of Science & Technology, New Delhi, India
文摘Rice （Oryza sativa L.） is an important food crop and requires larger amount of water throughout its life cycle as compared to other crops. Hence, water related stress cause severe threat to rice production. Drought is a major challenge limiting rice production. It affects rice at morphological （reduced germination, plant height, plant biomass, number of tillers, various root and leaf traits）, physiological （reduced photosynthesis, transpiration, stomatal conductance, water use efficiency, relative water content, chlorophyll content, photosystem II activity, membrane stability, carbon isotope discrimination and abscisic acid content）, biochemical （accumulation of osmoprotectant like proline, sugars, polyamines and antioxidants） and molecular （altered expression of genes which encode transcription factors and defence related proteins） levels and thereby affects its yield. To facilitate the selection or development of drought tolerant rice varieties, a thorough understanding of the various mechanisms that govern the yield of rice under water stress condition is a prerequisite. Thus, this review is focused mainly on recent information about the effects of drought on rice, rice responses as well as adaptation mechanisms to drought stress.
文摘Droughts occur in all climatic regions around the world costing a large expense to global economies. Reasonably accurate prediction of drought events helps water managers proper planning for utilization of limited water resources and distribution of available waters to different sectors and avoid catastrophic consequences. Therefore, a means to create a simplistic approach for forecasting drought conditions with easily accessible parameters is highly desirable. This study proposes and evaluates newly developed accurate prediction models utilizing various hydrologic, meteorological, and geohydrology parameters along with the use of Artificial Neural Network (ANN) models with various forecast lead times. The present study develops a multitude of forecasting models to predict drought indices such as the Standard Precipitation Index with a lead-time of up to 6 months, and the Soil Moisture Index with a lead-time of 3 months. Furthermore, prediction models with the capability of approximating surface and groundwater storage levels including the Ross River Dam level have been developed with relatively high accuracy with a lead-time of 3 months. The results obtained from these models were compared to current values, revealing that ANN based approach can be used as a simple and effective predictive model that can be utilized for prediction of different aspects of drought scenarios in a typical study area like Townsville, North Queensland, Australia which had suffered severe recent drought conditions for almost six recent years (2014 to early 2019).
