Estimation of potential evapotranspiration from extraterrestrial radiation, air temperature and humidity to assess future climate change effects on the vegetation of the Northern Great Plains, USA

The potential evapotranspiration (PET) that would occur with unlimited plant access to water is a central driver of simulated plant growth in many ecological models. PET is influenced by solar and long wave radiation, temperature, wind speed, and humidity, but it is often modeled as a function of temperature alone. This approach can cause biases in projections of future climate impacts in part because it confounds the effects of warming due to increased greenhouse gases with that which would be caused by increased radiation from the sun. We developed an algorithm for linking PET to extraterrestrial solar radiation (incoming top-of atmosphere solar radiation), as well as temperature and atmospheric water vapor pressure, and incorporated this algorithm into the dynamic global vegetation model MC1. We tested the new algorithm for the Northern Great Plains, USA, whose remaining grasslands are threatened by continuing woody encroachment. Both the new and the standard temperature-dependent MC1 algorithm adequately simulated current PET, as compared to the more rigorous PenPan model of Rotstayn et al. (2006). However, compared to the standard algorithm, the new algorithm projected a much more gradual increase in PET over the 21st century for three contrasting future climates. This difference led to lower simulated drought effects and hence greater woody encroachment with the new algorithm, illustrating the importance of more rigorous calculations of PET in ecological models dealing with climate change

Estimation of potential evapotranspiration from extraterrestrial radiation, air temperature and humidity to assess future climate change effects on the vegetation of the Northern Great Plains, USA

The potential evapotranspiration (PET) that would occur with unlimited plant access to water is a central driver of simulated plant growth in many ecological models. PET is influenced by solar and long wave radiation, temperature, wind speed, and humidity, but it is often modeled as a function of temperature alone. This approach can cause biases in projections of future climate impacts in part because it confounds the effects of warming due to increased greenhouse gases with that which would be caused by increased radiation from the sun. We developed an algorithm for linking PET to extraterrestrial solar radiation (incoming top-of atmosphere solar radiation), as well as temperature and atmospheric water vapor pressure, and incorporated this algorithm into the dynamic global vegetation model MC1. We tested the new algorithm for the Northern Great Plains, USA, whose remaining grasslands are threatened by continuing woody encroachment. Both the new and the standard temperature-dependent MC1 algorithm adequately simulated current PET, as compared to the more rigorous PenPan model of Rotstayn et al. (2006). However, compared to the standard algorithm, the new algorithm projected a much more gradual increase in PET over the 21st century for three contrasting future climates. This difference led to lower simulated drought effects and hence greater woody encroachment with the new algorithm, illustrating the importance of more rigorous calculations of PET in ecological models dealing with climate change

Climatic controls of aboveground net primary production in semi‑arid grasslands along a latitudinal gradient portend low sensitivity to warming

Although climate models forecast warmer temperatures with a high degree of certainty, precipitation is the primary driver of aboveground net primary production (ANPP) in most grasslands. Conversely, variations in temperature seldom are related to patterns of ANPP. Thus forecasting responses to warming is a challenge, and raises the question: how sensitive will grassland ANPP be to warming? We evaluated climate and multi-year ANPP data (67 years) from eight western US grasslands arrayed along mean annual temperature (MAT; ~7–14 °C) and mean annual precipitation (MAP; ~250–500 mm) gradients. We used regression and analysis of covariance to assess relationships between ANPP and temperature, as well as precipitation (annual and growing season) to evaluate temperature sensitivity of ANPP. We also related ANPP to the standardized precipitation evaporation index (SPEI), which combines precipitation and evapotranspiration to better represent moisture available for plant growth. Regression models indicated that variation in growing season temperature was negatively related to total and graminoid ANPP, but precipitation was a stronger predictor than temperature. Growing season temperature was also a significant parameter in more complex models, but again precipitation was consistently a stronger predictor of ANPP. Surprisingly, neither annual nor growing season SPEI were as strongly related to ANPP as precipitation. We conclude that forecasted warming likely will affect ANPP in these grasslands, but that predicting temperature effects from natural climatic gradients is difficult. This is because, unlike precipitation, warming effects can be positive or negative and moderated by shifts in the C3/C4 ratios of plant communities

Estimation of potential evapotranspiration from extraterrestrial radiation, air temperature and humidity to assess future climate change effects on the vegetation of the Northern Great Plains, USA

The potential evapotranspiration (PET) that would occur with unlimited plant access to water is a central driver of simulated plant growth in many ecological models. PET is influenced by solar and longwave radiation, temperature, wind speed, and humidity, but it is often modeled as a function of temperature alone. This approach can cause biases in projections of future climate impacts in part because it confounds the effects of warming due to increased greenhouse gases with that which would be caused by increased radiation from the sun. We developed an algorithm for linking PET to extraterrestrial solar radiation (incoming top-of atmosphere solar radiation), as well as temperature and atmospheric water vapor pressure, and incorporated this algorithm into the dynamic global vegetation model MC1. We tested the new algorithm for the Northern Great Plains, USA, whose remaining grasslands are threatened by continuing woody encroachment. Both the new and the standard temperature-dependent MC1 algorithm adequately simulated current PET, as compared to the more rigorous PenPan model of Rotstayn et al. (2006). However, compared to the standard algorithm, the new algorithm projected a much more gradual increase in PET over the 21st century for three contrasting future climates. This difference led to lower simulated drought effects and hence greater woody encroachment with the new algorithm, illustrating the importance of more rigorous calculations of PET in ecological models dealing with climate change.Keywords: Potential evapotranspiration, Great Plains USA, Climate change, Vegetation dynamics, MC

Managing Invasive Plants on Great Plains Grasslands: A Discussion of Current Challenges

The Great Plains of North America encompass approximately 1,300,000 km2 of land from Texas to Saskatchewan. The integrity of these lands is under continual assault by long-established and newly-arrived invasive plant species, which can threaten native species and diminish land values and ecological goods and services by degrading desired grassland resources. The Great Plains are a mixture of privately and publicly owned lands, which leads to a patchwork of varying management goals and strategies for controlling invasive plants. Continually updated knowledge is required for efficient and effective management of threats posed by changing environments and invasive plants. Here we discuss current challenges, contemporary management strategies, and management tools and their integration, in hopes of presenting a knowledge resource for new and experienced land managers and others involved in making decisions regarding invasive plant management in the Great Plains

Managing Invasive Plants on Great Plains Grasslands: A Discussion of Current Challenges

The Great Plains of North America encompass approximately 1,300,000 km2 of land from Texas to Saskatchewan. The integrity of these lands is under continual assault by long-established and newly-arrived invasive plant species, which can threaten native species and diminish land values and ecological goods and services by degrading desired grassland resources. The Great Plains are a mixture of privately and publicly owned lands, which leads to a patchwork of varying management goals and strategies for controlling invasive plants. Continually updated knowledge is required for efficient and effective management of threats posed by changing environments and invasive plants. Here we discuss current challenges, contemporary management strategies, and management tools and their integration, in hopes of presenting a knowledge resource for new and experienced land managers and others involved in making decisions regarding invasive plant management in the Great Plains

Basline Data Collection for Habitat Restoration at the Savanna Army Depot: Vegetation Structure and Composition

ID: 8896; issued November 22, 2000INHS Technical Report prepared for Ed Anderson and Ed Britto

Response of Grassland to Prairie Restoration at Lost Mound NWR: Baseline Data Collection

ID: 8948; issued December 20, 2002INHS Technical Report prepared for Britton, Ed U.S. Fish and Wildlife Service, Region 3 Upper Mississippi River National Wildlife and Fish Refuge, Savanna Distric

Incorporating Biodiversity Into Rangeland Health: Plant Species Richness and Diversity in Great Plains Grasslands

Indicators of rangeland health generally do not include a measure of biodiversity. Increasing attention to maintaining biodiversity in rangelands suggests that this omission should be reconsidered, and plant species richness and diversity are two metrics that may be useful and appropriate. Ideally, their response to a variety of anthropogenic and natural drivers in the ecosystem of interest would be clearly understood, thereby providing a means to diagnose the cause of decline in an ecosystem. Conceptual ecological models based on ecological principles and hypotheses provide a framework for this understanding, but these models must be supported by empirical evidence if they are to be used for decision making. To that end, we synthesize results from published studies regarding the responses of plant species richness and diversity to drivers that are of management concern in Great Plains grasslands, one of North America’s most imperiled ecosystems. In the published literature, moderate grazing generally has a positive effect on these metrics in tallgrass prairie and a neutral to negative effect in shortgrass prairie. The largest published effects on richness and diversity were caused by moderate grazing in tallgrass prairies and nitrogen fertilization in shortgrass prairies. Although weather is often cited as the reason for considerable annual fluctuations in richness and diversity, little information about the responses of these metrics to weather is available. Responses of the two metrics often diverged, reflecting differences in their sensitivity to different types of changes in the plant community. Although sufficient information has not yet been published for these metrics to meet all the criteria of a good indicator in Great Plains Grasslands, augmenting current methods of evaluating rangeland health with a measure of plant species richness would reduce these shortcomings and provide information critical to managing for biodiversity./Los indicadores de la salud de los pastizales generalmente no incluyen una medida de la biodiversidad. El aumento en la atención de mantener la biodiversidad en los pastizales sugiere que esta omisión sea reconsiderada. La riqueza y la diversidad delas especies de plantas son dos parámetros que pueden ser muy u ́tiles y apropiados. Idealmente, su respuesta a una variedad de factores antropogénicos y naturales en el ecosistema de interés se podría entender claramente, proporcionando los medios para diagnosticar la causa del detrimento del ecosistema. Los modelos ecológicos conceptuales basados en principios e hipótesis ecológicos proporcionan un marco para esta comprensión, pero estos modelos deben ser apoyados por evidencias empíricas si van a ser utilizados para la toma de decisiones. De tal manera, resumimos los resultados de estudios publicados con respecto a las respuestas de la riqueza y de la diversidad de las especies de plantas y los factores que son de preocupación a los manejador es de los pastizales de las grandes planicies, uno de los ecosistemas más amenazado de Norte América. En la literatura publicada, el pastoreo moderado generalmente tiene un efecto positivo en estos parámetros en los pastizales altos y un efecto neutro o negativo en los pastizales cortos. La mayoría de las publicaciones sobre la riqueza y diversidad de los pastizales fueron causadas por el pastoreo moderado en los pastizales altos y la fertilización de nitrógeno en los pastizales cortos. Aunque, el clima se cita frecuentemente como la razón de las fluctuaciones anuales considerables en la riqueza y la diversidad, poca información sobre las respuestas de estos parámetros al clima está disponible. Las respuestas de los dos parámetros difirieron a menudo, reflejando discrepancias en su sensibilidad a diversos tipos de cambios en la comunidad de la planta. Aunque suficiente información todavía no se ha publicado para que estos dos parámetros cubran todos los criterios de un buen indicador de los pastizales de las grandes planicies, el incluir en los métodos actuales de evaluación de la salud de los pastizales, una medida de riqueza de las especies de las plantas reduciría estos defectos y proporcionaría la información crítica para el manejo de la biodiversidad.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202