Chapter 22 : Northern Great Plains. Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Volume II

Conant, Richard T.; Kluck, Doug; Anderson, Mark L.; Badger, Andrew M.; Boustead, Barbara Mayes; Derner, Justin D.; Farris, Laura; Hayes, Michael J.; Livneh, Ben; McNeeley, Shannon M.; Peck, Dannele E.; Shulski, Martha; Small, Valerie A.

doi:10.7930/nca4.2018.ch22

Cited by 28 publications

(33 citation statements)

References 102 publications

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“…Precipitation characteristics are of great importance to the central United States, a significant grain growing region in North America and the breadbasket of the world (USDA, 2019). While rainfall with extreme intensity can induce flooding and cause significant economic losses and impact livelihoods (Conant, 2018;Kloesel, 2018), the timing and frequency of nonextreme rainfall events during the warm season can significantly impact vegetation productivity, which is intricately linked to agriculture and livestock in the region (Angel et al, 2018;Conant, 2018;Feng et al, 2013;Jay, 2018;Knapp et al, 2008). Therefore, it is critical to better understand the rainfall characteristics in the central United States and their long-term changes, especially given their significant impacts on human-ecosystem interactions that have large downstream consequences (Conant, 2018;Knapp et al, 2008;Weltzin et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Observed Warm‐Season Characteristics of MCS and Non‐MCS Rainfall and Their Recent Changes in the Central United States

Leung

Feng

2020

Geophysical Research Letters

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Warm‐season rainfall characteristics in the central United States are investigated as they play important roles in ecohydrology and agricultural productivity. Using rainfall observations, we compare the April–August mesoscale convective systems (MCS) and non‐MCS rainfall characteristics and examine their linear trends between 1997 and 2018. MCS rainfall is found to be approximately seven times more intense than non‐MCS rainfall but it occurs less frequently in time and space. MCS rainfall peaks in nocturnal hours, with synchronized timing of rainfall intensity, area, and occurrence, while non‐MCS rainfall peaks in late‐afternoon hours, mostly attributed to the timing of peak rainfall area. MCS rainfall has increased in the last 22 years due to an increase in frequency and a longer duration per MCS. In contrast, non‐MCS rainfall has decreased mainly due to a reduction in rainfall area, leading to fewer total wet days and increased dry intervals between events.

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Section: Introductionmentioning

confidence: 99%

Observed Warm‐Season Characteristics of MCS and Non‐MCS Rainfall and Their Recent Changes in the Central United States

Leung

Feng

2020

Geophysical Research Letters

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“…In conjunction with the development of cold-tolerant and shorter season varieties of corn and soybean, the environment in North and South Dakota has also changed in the past several decades (Conant et al, 2018). The recent increases in air temperatures are the continuation of a long-term trend, as temperatures in North Dakota have been increasing since 1895 at a rate of 0.15 • C per decade, the fastest rate in the nation (NOAA, 2013) These temperature increases, especially in the winter and spring, have extended the growing season, defined as the time between the last thaw in the spring and the first freeze in the fall.…”

Section: Environmentmentioning

confidence: 99%

Cropping pattern changes diminish agroecosystem services in North and South Dakota, USA

et al. 2020

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In the past several decades, North and South Dakota have experienced increased agricultural expansion and crop rotation simplification, namely an increase in corn (Zea mays L.)– soybean [Glycine max (L.) Merr.] systems. This review investigates the nature and extent of those changes, the underlying causes, and the consequences they have on ecosystem services. The framework of ecosystem services is underutilized in agricultural research, but it can be used to describe the sustainability, resistance, and resilience of the system in relation to these land use changes. The current trends are focused on maximizing provisioning services (i.e., food and fuel) at the expense of regulating, cultural, and supporting services. The decline of regulating services can be seen in increased peak river flow (up to 100% and 200% increases in South and North Dakota, respectively), as well as by the 100% increase in area treated by chemicals, partially due to diminished bioregulation of pests and weeds. The effects on supporting services are demonstrated by altered C balances and water cycling, while the loss of cultural connection to the land is evidenced by a 40% decrease in land conservation since 1997. Overall, these changes are making the land in North and South Dakota more susceptible to stressors, such as drought, crop pests, or even economic trends that could greatly harm these agroecosystems and have nationwide ramifications. To address these changes, producers need to provide a balance of agroecosystem services by optimizing currently available management strategies and possibly transforming agricultural practices for long‐term system stability.

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“…Some potential explanations include the increase in extreme events due to climate change and effects due to land use conversion. Variability is expected to continue to increase in the region [38].…”

Section: Study Region and Datamentioning

confidence: 99%

A predictive model for seasonal pond counts in the United States Prairie Pothole Region using large-scale climate connections

Abel

Rajagopalan

Ray

2020

Environ. Res. Lett.

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The Prairie Pothole Region (PPR), located in central North America, is an important region hydrologically and ecologically. Millions of wetlands, many containing ponds, are located here, and they serve as habitats for various biota and breeding grounds for waterfowl. They also provide carbon sequestration, sediment and nutrient attenuation, and floodwater storage. Land modification and climate change are threatening the PPR, and water and wildlife managers face important conservation decisions due to these threats. We developed predictive, multisite forecasting models using canonical correlation analysis (CCA) for pond counts in the southeast PPR, the portion located within the United States, to aid in these important decisions. These forecast models predict spring (May) and summer (July) pond counts for each region (stratum) of the United States Fish and Wildlife Service's pond and waterfowl surveys using a suite of antecedent, large-scale climate variables and indices including 500 millibar heights, sea surface temperatures (SSTs), and Palmer Drought Severity Index (PDSI). Models were developed to issue forecasts at the start of all preceding months beginning on March 1st. The models were evaluated for their performance in a predictive mode by leave-one-out cross-validation. The models exhibited good performance (R values above 0.6 for May forecasts and 0.4 for July forecasts), with performance increasing as lead time decreased. This simple and versatile modeling approach offers a robust tool for efficient management and sustainability of ecology and natural resources. It demonstrates the ability to use large-scale climate variables to predict a local variable in a skilful way and could serve as an example to develop similar models for use in management and conservation decisions in other regions and sectors of the environment.

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Chapter 22 : Northern Great Plains. Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Volume II

Cited by 28 publications

References 102 publications

Observed Warm‐Season Characteristics of MCS and Non‐MCS Rainfall and Their Recent Changes in the Central United States

Observed Warm‐Season Characteristics of MCS and Non‐MCS Rainfall and Their Recent Changes in the Central United States

Cropping pattern changes diminish agroecosystem services in North and South Dakota, USA

A predictive model for seasonal pond counts in the United States Prairie Pothole Region using large-scale climate connections

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