scholarly journals Water Stress of Tallgrass Prairie Plants in Central Oklahoma

1984 ◽  
Vol 37 (2) ◽  
pp. 147 ◽  
Author(s):  
D. R. Hake ◽  
J. Powell ◽  
J. K. McPherson ◽  
P. L. Claypool ◽  
G. L. Dunn
Keyword(s):  
Water Stress ◽  
Tallgrass Prairie ◽  
Prairie Plants

The Distribution and Abundance of Tallgrass Prairie Plants: A Test of the Core-Satellite Hypothesis

1987 ◽  
Vol 130 (1) ◽  
pp. 18-35 ◽  
Author(s):  
Nicholas J. Gotelli ◽  
Daniel Simberloff
Keyword(s):  
Tallgrass Prairie ◽  
The Core ◽  
Prairie Plants

Comparison of damage to native and exotic tallgrass prairie plants by natural enemies

Plant Ecology ◽  
2008 ◽  
Vol 198 (2) ◽  
pp. 197-210 ◽  
Author(s):  
Xuemei Han ◽  
Shauna P. Dendy ◽  
Karen A. Garrett ◽  
Liang Fang ◽  
Melinda D. Smith
Keyword(s):  
Tallgrass Prairie ◽  
Natural Enemies ◽  
Prairie Plants

scholarly journals How can the First ISLSCP Field Experiment contribute to present-day efforts to evaluate water stress in JULESv5.0?

2019 ◽  
Vol 12 (7) ◽  
pp. 3207-3240 ◽  
Author(s):  
Karina E. Williams ◽  
Anna B. Harper ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Camilla T. Mathison ◽  
...  
Keyword(s):  
Water Stress ◽  
Field Experiment ◽  
Tallgrass Prairie ◽  
Land Surface ◽  
Carbon Assimilation ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Dry Spell ◽  
Depth Analysis

Abstract. The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Now, 30 years on, we demonstrate how the wealth of data collected during FIFE and its subsequent in-depth analysis in the literature continue to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating “unstressed” vegetation parameters and thresholds for water stress. In particular, the responses to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES.

scholarly journals Revisiting the First ISLSCP Field Experiment to evaluate water stress in JULESv5.0

2018 ◽  
Author(s):  
Karina E. Williams ◽  
Anna B. Harper ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Camilla T. Mathison ◽  
...  
Keyword(s):  
Water Stress ◽  
Field Experiment ◽  
Tallgrass Prairie ◽  
Land Surface ◽  
Carbon Assimilation ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Dry Spell ◽  
Depth Analysis

Abstract. The First ISLSCP Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land-surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Thirty years on, we demonstrate how the wealth of data collected at FIFE and its subsequent in-depth analysis in the literature continues to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating "unstressed" vegetation parameters and thresholds for water stress. In particular, the response to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES.

scholarly journals Codominant grasses differ in gene expression under experimental climate extremes in native tallgrass prairie

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4394 ◽  
Author(s):  
Ava M. Hoffman ◽  
Meghan L. Avolio ◽  
Alan K. Knapp ◽  
Melinda D. Smith
Keyword(s):  
Gene Expression ◽  
Water Stress ◽  
Tallgrass Prairie ◽  
Heat Waves ◽  
Climate Extremes ◽  
High Heat ◽  
Grass Species ◽  
Sorghastrum Nutans ◽  
Transcriptional Responses ◽  
Gene Expression Response

Extremes in climate, such as heat waves and drought, are expected to become more frequent and intense with forecasted climate change. Plant species will almost certainly differ in their responses to these stressors. We experimentally imposed a heat wave and drought in the tallgrass prairie ecosystem near Manhattan, Kansas, USA to assess transcriptional responses of two ecologically important C4 grass species, Andropogon gerardii and Sorghastrum nutans. Based on previous research, we expected that S. nutans would regulate more genes, particularly those related to stress response, under high heat and drought. Across all treatments, S. nutans showed greater expression of negative regulatory and catabolism genes while A. gerardii upregulated cellular and protein metabolism. As predicted, S. nutans showed greater sensitivity to water stress, particularly with downregulation of non-coding RNAs and upregulation of water stress and catabolism genes. A. gerardii was less sensitive to drought, although A. gerardii tended to respond with upregulation in response to drought versus S. nutans which downregulated more genes under drier conditions. Surprisingly, A. gerardii only showed minimal gene expression response to increased temperature, while S. nutans showed no response. Gene functional annotation suggested that these two species may respond to stress via different mechanisms. Specifically, A. gerardii tends to maintain molecular function while S. nutans prioritizes avoidance. Sorghastrum nutans may strategize abscisic acid response and catabolism to respond rapidly to stress. These results have important implications for success of these two important grass species under a more variable and extreme climate forecast for the future.

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