Southern Great Plains Research Articles

Atmospheric and Surface Dynamics During Winter Warm Spells in the Southern Great Plains: Insights From the 2021 Case Study

AbstractTwo 2021 winter warm spell events experienced near record extreme surface temperatures, anomalies exceeding C, during the winter season in 2021 across the Southern Great Plains (SGP). Extreme heat during the winter season results in similar detrimental socioeconomic impacts compared to their counterpart summer heat wave events. Winter warm spell events across the SGP have been historically increasing over the last several decades, and as such, it is crucial to investigate the drivers of these extreme events. In this study, we use ERA‐5 reanalysis data to investigate the atmospheric and surface characteristics associated with these two extreme events (i.e., (a) 29 November–17 December 2021 and (b) 22 December–31 December 2021). A prolonged period of positive geopotential height anomalies amplified subsidence in combination with increased incoming solar radiation and surface heat fluxes aiding extreme surface temperatures during the first winter warm spell event. However, a more prominent atmospheric blocking high (i.e., Alaskan Ridge) initiated and intensified the extreme heat during the second winter warm spell. Increased incoming solar radiation and positive sensible heat flux due to a dry surface fostered extreme heat during the second winter warm spell event. Warm air advection throughout both winter warm spell events supported the extreme surface temperatures. Discovering potential crucial drivers to winter warm spells identifies the sources of predictability to improve prediction of these extreme heat events.

The effect of land use intensity and habitat characteristics on butterfly community composition within the Southern Great Plains of the United States

AbstractBackgroundAs grasslands decline, grassland‐dependent species such as grassland butterflies have experienced widespread population losses. To manage remaining grasslands, prescribed fire, grazing, and haying are common management practices across the Southern Great Plains of the United States. However, the impacts of management and land use intensity (LUI) on butterfly community composition and butterfly community traits are not well understood. Additionally, local habitat characteristics such as vegetation height and cover, as well as broader landscape categorization, including how much agriculture or urbanization is occurring around the habitat, can alter butterfly communities.MethodsWe conducted standardized butterfly and flowering forb surveys at grassland sites across north‐central Oklahoma.ResultsLUI influenced overall butterfly community composition with sites managed only with fire having the most dissimilar butterfly community compared to three other management regimens. The amount of agriculture, urbanization, and wetlands surrounding study sites also influenced butterfly community composition. Flowering forb community measures differed by site with sites managed by fire alone having lower blooming forbs species richness, diversity, and abundance than sites with other management regimens.ConclusionsSites managed with only prescribed fire had the most disparate butterfly community in comparison to other management methods, suggesting that specialist butterfly species may be sensitive to increasing disturbance.

Producer Willingness to Accept Incentive Levels for Cover Crop Adoption in the Southern Great Plains

Abstract The purpose of this study is to analyze agricultural producers’ willingness to adopt regenerative cover crop practices in their operation and the effects of producer and farm characteristics on willingness to accept (WTA) values. The paper utilizes the double-bounded contingent valuation method to analyze survey responses submitted by producers and non-operating landowners in the Texas and Oklahoma portions of the Southern Great Plains. Results showed an average WTA of $26.38/acre for producers to adopt cover crops and that programs aimed at increasing adoption rates may require more substantial investment compared to those focused on continuity with current adopters.

Tropical Interbasin Interaction as Effective Predictors of Late-Spring Precipitation Variability in the Southern Great Plains

Abstract The southern Great Plains experience fluctuating precipitation extremes that significantly impact agriculture and water management. Despite ongoing efforts to enhance forecast accuracy, the underlying causes of these climatic phenomena remain inadequately understood. This study elucidates the relative influence of the tropical Pacific and Atlantic basins on April–May–June precipitation variability in this region. Our partial ocean assimilation experiments using the Community Earth System Model unveil the prominent role of interbasin interaction, with the Pacific and Atlantic contributing approximately 70% and 30%, respectively, to these interbasin contrasts. Our statistical analyses suggest that these tropical interbasin contrasts could serve as a more reliable indicator for late-spring precipitation anomalies than El Niño–Southern Oscillation. The conclusions are reinforced by analyses of seven climate forecasting systems within the North American Multi-Model Ensemble, offering an optimistic outlook for enhancing real-time forecasting of late-spring precipitation in the southern plains. However, the current predictive skills of the interbasin contrasts across the prediction systems are hindered by the lower predictability of the tropical Atlantic Ocean, pointing to the need for future research to refine climate prediction models further. Significance Statement Agriculture and infrastructure in the southern plains face challenges from severe late-spring precipitation extremes. Traditional predictors like El Niño–Southern Oscillation (ENSO) lose effectiveness during the critical spring-to-summer transition, creating a forecasting gap. This study introduces the concept of tropical interbasin interactions, known to enhance seasonal predictability for late-spring precipitation in the southern plains. Novel climate model experiments highlight contributions from the tropical Pacific and Atlantic, offering a promising predictability that potentially surpasses the limitations of ENSO-based predictions. These outcomes hold the potential for developing operational forecasts of late-spring precipitation anomalies in the southern plains, enabling proactive risk management.

Influence of clouds on planetary boundary layer height: A comparative study and factors analysis

Clouds are one of the key factors influencing the evolution of the planetary boundary layer (PBL). Understanding the complex interactions between clouds and PBL height (PBLH) is essential for accurately simulating and predicting PBL processes. This study investigates the impact of clouds on PBLH evolution based on the lidar, radiosonde, ceilometer, and meteorological parameters observations at the Southern Great Plains site during the period January 2013 to December 2020. The findings indicates that the presence of clouds has an impact on the evolution of the PBLH. During the daytime, PBLH is lower under cloudy conditions than clear conditions, whereas during nighttime, PBLH is higher under cloudy conditions. This phenomenon arises because the intense solar radiation on clear days and strong turbulent mixing on cloudy nights contribute to the formation and maintenance of PBLH. Furthermore, during the daytime, clouds scatter and absorb solar radiation, leading to lower net radiation (NetR), sensible heat flux (SHF), surface temperature (TEM), and soil temperature (SoilT). These conditions, coupled with weaker turbulence intensity and high relative humidity (RH), leading to lower PBLH under cloudy conditions. Although TEM and SoilT are relatively high during clear nights, rapid surface radiative cooling and strong atmospheric stability inhibit the development of the PBLH. Consequently, during cloudy nights, clouds absorb and reflect longwave radiation from the surface, reducing surface radiative cooling rates, enhancing atmospheric instability and turbulence intensity. Furthermore, higher NetR and SHF, along with decreased RH, result in slightly deeper PBLH compared to clear conditions. Overall, this study systematically elucidates the influence of clouds on PBLH evolution and contributes to the understanding of the modulation of cloud on PBL structure.

Economic comparison of stocker cattle performance on winter wheat vs. summer-dormant tall fescue with nitrogen or interseeded alfalfa in the southern great plains.

Winter wheat (Triticum aestivum L.) is a significant forage source for livestock grazing in the Southern Great Plains (SGP). However, increasing input costs and changing climate conditions compel producers and researchers to search for alternative forage systems, such as cool-season perennials. Specifically, cool-season perennials with summer dormancy traits can survive droughts in the SGP. This paper aimed to determine the net returns of three different types of cool-season perennial summer-dormant tall fescue [Schedonorus arundinaceus (Schreb.) Dumort., nom. cons.] systems either with N fertilizer or interseeded with alfalfa (Medicago sativa L.) and the traditional graze-out annual winter wheat forage system. The data were from a 5-yr experiment conducted in south-central Oklahoma. Animal performance results indicated that the traditional graze-out winter annual wheat forage system provided more total gains at 434kg ha-1 than the three tall fescue variety systems at 326kg ha-1 (P = 0.006) due to more grazing days. Thus, the gross revenue estimated at a cost of gain of $1.60kg-1 gain for wheat at $694 ha-1 was greater than the average gross revenue of $521 ha-1 for the tall fescue systems. However, the average total cost for the perennial tall fescue systems ($374 ha-1) was less than the total cost ($594 ha-1) of the wheat system. Overall, the average net returns were similar for all grazing systems at about $145 ha-1.

Investigating the Impact of Multiphysics on Modeled Planetary Boundary Layer Height Estimates during the PECAN Field Campaign

Abstract Accurate representation of the planetary boundary layer (PBL) in numerical weather prediction is crucial to air quality, weather forecasting, and climate change research and operations. Here, we evaluate the estimates of PBL height (PBLH) from a set of convective-permitting simulations conducted using the Weather Research and Forecasting (WRF) Model during the Plains Elevated Convection at Night (PECAN) campaign (from June to mid-July 2015). Our analysis aims to quantify the variability in PBLH, along with its associated surface variables and atmospheric profiles, to gauge the influence of model physics on the accuracy of simulated PBL properties. Specifically, we conducted twenty-four 45-day retrospective simulations encompassing different combinations of three PBL and two microphysics schemes, two initial and boundary condition (ICBC) datasets, and two model vertical grid spacings. We compare these simulations with measurements from surface sites and radiosonde launches across four sites in the southern Great Plains during PECAN. Our findings indicate that deriving PBLH from modeled atmospheric profiles yields a narrower spread (200–300 m) compared to PBLH calculated from the model’s PBL scheme (400–500 m) relative to radiosonde-derived PBLH under fair weather conditions. The choice of PBL scheme and ICBCs exerts the most significant impact (by up to 400 m) on the spread of modeled PBLH and associated atmospheric profiles, primarily influencing the representation of surface heating, transport, and mixing processes in the model. The model has difficulty reproducing the correct thermodynamic profile under cloud-intense conditions. These results underscore the benefit of using the physically consistent approach in retrieving, evaluating, and assimilating PBLH estimates, as well as the utility of multiphysics to better address model uncertainties. Significance Statement Studies on weather forecast models typically involve running the model multiple times and adjusting model inputs slightly each time to produce a range of predicted variables. This range is crucial for evaluating forecast probabilities and integrating observations into the model. We found that using different model physics schemes can result in an equal or greater spread for predicted variables (here, we focus on boundary layer height and related variables), compared to input tweaks alone. Additionally, a particular scheme can introduce biases. These findings underscore the importance of employing multiple physics schemes in the model, as they widen the coverage (potentially doubling) of outputs, and thus better address forecast uncertainties.

Anthropogenic Extremely Low Volatility Organics (ELVOCs) Govern the Growth of Molecular Clusters Over the Southern Great Plains During the Springtime

AbstractNew particle formation (NPF) often drives cloud condensation nuclei concentrations and the processes governing nucleation of molecular clusters vary substantially in different regions. The growth of these clusters from ∼2 to >10 nm diameters is often driven by the availability of extremely low volatility organic vapors (ELVOCs). Although the pathways to ELVOC formation from the oxidation of biogenic terpenes are better understood, the mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are less well understood. We integrate measurements and detailed regional model simulations to understand the processes governing NPF and secondary organic aerosol formation at the Southern Great Plain (SGP) observatory in Oklahoma and compare these with a site within the Bankhead National Forest (BNF) in Alabama, southeast USA. During our two simulated NPF event days, nucleation rates are predicted to be at least an order of magnitude higher at SGP compared to BNF largely due to lower sulfuric acid (H2SO4) concentrations at BNF. Among the different nucleation mechanisms in WRF‐Chem, we find that the dimethylamine (DMA) + H2SO4 nucleation mechanism dominates at SGP. We find that anthropogenic ELVOCs are critical for explaining the growth of particles observed at SGP. Treating organic particles as semisolid, with strong diffusion limitations for organic vapor uptake in the particle phase, brings model predictions into closer agreement with observations. We also simulate two non‐NPF event days observed at the SGP site and show that low‐level clouds reduce photochemical activity with corresponding reductions in H2SO4 and anthropogenic ELVOC concentrations, thereby explaining the lack of NPF.

Changes in Extreme Daily Precipitation over the Contiguous United States from Convection-Permitting Simulations

Abstract The potential for changes in extreme precipitation events due to anthropogenic climate change may have significant societal impacts (e.g., agricultural productivity, property loss, mortality). This project uses a dynamically downscaled, convection-permitting regional climate model to investigate extreme daily precipitation in the CONUS, defined explicitly as the 99th percentile 24-h accumulated value. The simulation output includes a historical baseline (HIST; 1990–2005) and two epochs at the end of the twenty-first century (EOC; 2085–2100) under intermediate and pessimistic emissions scenarios. Independent observations illustrate that HIST admirably represents extreme precipitation climatology for most locations in the domain. Comparisons between HIST and the two EOC scenarios for the 99th percentile of daily precipitation show statistically significant increases during Dec–May across the Midwest and Ohio Valley and statistically significant decreases for the southern Great Plains during Dec–Feb. Extreme value analysis further reveals increasing variability in precipitation extremes for eight climatologically unique cities across the CONUS by the end of the twenty-first century and significant increases in return period precipitation amounts for most cities examined. These results provide additional guidance for stakeholders to reduce societal impacts and economic loss from daily precipitation extremes and create a more climate-resilient society.

Aerosol Vertical Turbulent Mass Flux Retrievals Through Novel Remote Sensing Algorithm

AbstractIntegrated measurements of aerosol, radiation, cloud, and turbulent transport in the planetary boundary layer (PBL) are essential for understanding and modeling climate and air quality. Here, we developed a new technique for the identification of convective turbulent regions and deriving the vertical distribution of aerosol turbulent mass fluxes within PBL. The algorithm uses retrievals from coherent Doppler lidars and a high spectral resolution lidar. The technique was applied to study particle mass fluxes over 2 months (November–December 2020) during the campaign conducted at the DOE Atmospheric Radiation Measurement Southern Great Plains (SGP) site in Lamont, Oklahoma. The algorithm developed here is capable of continuously deriving vertically resolved (curtains) aerosol mass fluxes. Our data analysis shows that at the site, the 30‐min averaged fluxes at 135 m above the surface were mainly positive (upward) at ∼1 μg m−2 s−1, suggesting that the surface is the primary source of the particle mass supplied to the boundary layer at the SGP site. Analyses of the individual case studies have revealed that not all the derived fluxes can be linked to surface emissions. Both positive and negative values in a range of ±5 μg m−2 s−1 can be caused by convective thermals interacting between the residual layer and the mixed layer and by rotation of the horizontal wind with the height. Large erroneous negative fluxes can also be caused by drizzling/precipitating clouds. We anticipate that the application of the current technique will lead to a more realistic representation of aerosol mass budgets and bidirectional mixing rates.

Convectively Induced Secondary Circulations and Wind‐Driven Heat Fluxes in the Surface Energy Balance Over Land

AbstractIncreased resolution has enabled kilometer‐scale weather and climate models to partially resolve secondary circulations, including horizontal convective rolls (HCRs) and cold pool gust fronts. Although these circulations are ubiquitous in convective boundary layers over land, their impacts on the surface energy balance are largely unknown. Doppler lidar and surface observations were combined with DOE E3SM land model experiments, revealing increased surface winds (5 m/s) and heat fluxes (50 W/m2) in convergent branches of HCRs. Larger wind‐driven flux responses (up to 150 W/m2) were found along gust fronts. Surface energy balance shifts to accommodate wind‐driven fluxes, reducing ground heat conduction and longwave cooling. Our findings from the US Southern Great Plains are broadly relevant to modeling convective boundary layers. In particular, widely used subgrid wind gust parameterizations were found to be physically inconsistent with resolved secondary circulations and could worsen climate prediction biases at kilometer‐scales.

Estimating plant β-diversity using airborne and spaceborne imaging spectroscopy

ABSTRACT The increasing threats to grassland ecosystems from land-use/land-cover change, disturbances, and invasive species underscore the importance of monitoring grassland plant diversity. While most remote sensing studies have mainly focused on quantifying α-diversity (diversity within communities), less attention has been given to remotely estimating β-diversity (diversity between communities) in naturally-assembled grasslands. In this study, we used remote sensing to map plant β-diversity in a naturally-assembled grassland managed using prescribed fire and grazing in a North American tallgrass prairie ecosystem within the US Southern Great Plains. We aimed to assess the impact of time since fire on the relationship between in situ plant β-diversity and remotely–sensed β-diversity, also known as spectral β-diversity. We collected in situ observations at 60 m × 60 m, 120 m × 120 m, 180 m × 180 m, and 240 m × 240 m plots, alongside airborne and spaceborne DESIS imaging spectroscopy data with spatial resolutions of 1 m and 30 m, respectively. To assess how management practices influenced β-diversity, we grouped our in situ observations into three categories based on time since fire, including recently-burned (burn age <1 year), transitional (burn age of 1–2 years), and unburned (burn age >2 years). Our findings showed that the association between in situ and spectral β-diversity was strongly influenced by time since fire. Excluding plots with high soil cover (≥50%) improved our remote estimation of β-diversity, despite soil exposure effects. Our study demonstrated that remote sensing of β-diversity in grassland ecosystems is influenced by spatial scale, time since fire, and soil exposure, all of which can be addressed with scale-appropriate imaging spectrometry. This study also highlighted the capability of spaceborne imaging spectrometers to estimate β-diversity of grassland ecosystems across large spatial domains.

Interactions between Sudangrass Lines Selected for Differing Nitrate Expression and Sorghum Aphid

Sudangrass (Sorghum sudanense Stapf) is widely cultivated as a summer annual forage across the southern Great Plains because of its robust forage yield potential. However, the accumulation of nitrates and the potential harm to livestock have restricted the use of Sudangrass for feeding ruminants. Since 2013, the sorghum aphid (SA), Melanaphis sorghi (Theobald) (Hemiptera: Aphididae), has been damaging sorghum and Sudangrass production. However, the interaction between SA feeding and nitrate accumulation in Sudangrass has not been determined. In this study, we evaluated the effect of SA feeding on different Sudangrass lines, comparing them to a susceptible and a resistant sorghum variety and measuring the physiological responses and nitrate concentration after aphid feeding. Additionally, we evaluated the use of these grass lines on SA demographics. Initial infestations of 100 SA per plant that were allowed to feed and proliferate for 20 days increased nitrate concentrations in Sudangrass by more than 60% compared to controls. Concurrently, the Sudangrass lines selected for high nitrate levels drastically reduced SA demographic parameters, comparable to those of the resistant sorghum control. Although the adoption of resistant cultivars is recommended for aphid management, the Sudangrass lines selected may not be the best option for SA management because their accumulation of nitrates in response to herbivory can cause ruminant poisoning.

Siting Analysis of a Solar-Nuclear-Desalination Integrated Energy System

Nuclear power is typically deployed as a baseload generator. Increased penetration of variable renewables motivates combining nuclear and renewable technologies into Integrated Energy Systems (IES) to improve dispatchability, component synergies and, through cogeneration, address multiple markets. However, combining multiple energy resources heavily depends on the proper selection of each system’s location and design limitations. In this paper, co-siting options for IES that couple nuclear and concentrating solar power (CSP) with thermal desalination are investigated. A comprehensive siting analysis is performed that utilizes global information survey data to determine possible co-siting options for nuclear and solar thermal generation in the United States. Viable co-siting options are distributed across the Southwestern U.S., with the greatest concentration of siting options in the southern Great Plains, although siting with higher solar direct normal irradiance is possible in other states such as Arizona and New Mexico. Brackish water desalination is also attractive across the southwest U.S. due to high water stress, but for brackish water desalination reverse osmosis (an electricity driven process) is most cost- and energy-efficient, which does not require co-siting with the thermal generator. The most attractive state for nuclear and thermal desalination (which is more attractive when using seawater) is Texas, although other areas may become attractive as water stress increases over the coming decades. Co-siting of all CSP and thermal desalination is challenging as attractive CSP sites are not coastal.

Robust future intensification of winter precipitation over the United States

We investigate 21st-century hydroclimate changes over the United States (US) during winter and the sources of projection uncertainty under three emission scenarios (SSP2–4.5, SSP3–7.0, and SSP5–8.5) using CMIP6 models. Our study reveals a robust intensification of winter precipitation across the US, except in the Southern Great Plains, where changes are very small. By the end of the 21st century, winter precipitation is projected to increase by about 2–5% K−1 over most of the US. The frequency of very wet winters is also expected to increase, with 6–7 out of 30 winters exceeding the very wet threshold under the different scenarios. Our results suggest that the enhancement of future winter precipitation is modulated largely by coupled dynamic and thermodynamic responses, though partly offset by thermodynamic responses. Overall, our results highlight a high likelihood of increasing impacts from winter precipitation due to climate change.

Processing time and precision of aging structures for Bighead Carp and Silver Carp in the lower Red River catchment in the southern Great Plains

AbstractObjectivePopulation demographics of invasive species are commonly evaluated to better develop management actions that are useful for reducing their abundance or controlling the population. Bighead Carp Hypophthalmichthys nobilis and Silver Carp H. molitrix are emblematic invaders in the United States, where they continue to expand their range. There is currently no consensus about which hard structure from these species is best for age estimation. Our study objective was to compare the processing time and precision of five hard structures used for age estimation of both species.MethodsWe sampled fish in the lower Red River catchment of Oklahoma, Arkansas, and Texas during summer and autumn 2021–2022 and removed the lapillus otolith, left primary pectoral fin ray, postcleithrum, urohyal bone, and anterior‐most pterygiophore of the dorsal fin from both Bighead and Silver carp. The structures (n = 1204) were either embedded in epoxy or thin‐sectioned and mounted on slides. Two readers estimated the age of the fish by using each structure and came to a consensus. Processing time was recorded from the onset of laboratory processing to the termination of polishing the cross sections for age estimation.ResultProcessing of otoliths was comparable to or faster than processing of the other structures and resulted in the highest between‐reader agreement. The lowest coefficients of variation in age estimation were represented using lapillus otoliths for Bighead Carp and postcleithra for Silver Carp. Our age bias plots indicated that all other structures underestimated age relative to the lapillus otoliths.ConclusionOur results indicated that using lapillus otoliths for age estimation of these species would have the highest between‐reader agreement and would incur no additional laboratory processing time. However, validation is needed to assess whether lapillus otoliths correctly age these species. From a management perspective, use of this structure would facilitate improved population comparisons.

Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains

Abstract. Based on long-term observations at the Southern Great Plains site by the Atmospheric Radiation Measurement (ARM) program for training and validation, a deep-learning model is developed to simulate the daytime evolution of boundary layer clouds (BLCs) from the perspective of land–atmosphere coupling. The model takes ARM measurements (including early-morning soundings and diurnally varying surface meteorological conditions and heat fluxes) as inputs and predicts hourly estimates (including cloud occurrence, the positions of cloud boundaries, and the vertical profile of the cloud fraction) as outputs. The deep-learning model offers good agreement with the observed cloud fields, especially in the accuracy with which cloud occurrence and base height are reproduced. When the inputs are substituted by reanalysis data from ERA5 and MERRA-2, the outputs of the deep-learning model provide a better agreement with observation than the cloud fields extracted from ERA5 and MERRA-2 themselves. Thus, the deep-learning model shows great potential to serve as a diagnostic tool for the performance of physics-based models in simulating stratiform and cumulus clouds. By quantifying biases in clouds and attributing them to the simulated atmospheric state variables versus the model-parameterized cloud processes, this observation-based deep-learning model may offer insights into the directions needed to improve the simulation of BLCs in physics-based models for weather forecasting and climate prediction.

Landowner Perceptions toward Adopting Patch-Burn and Mixed-Species Grazing for Rangelands in the U.S. Southern Great Plains

AbstractThe sustainability of grazed rangelands can be improved by adopting innovative management practices that enhance the ecological resilience, productivity, and long-term viability of rangeland ecosystems. This study applied a bivariate Multiple Indicator–Multiple Causation model to examine how landowner characteristics are associated with their perceptions concerning patch-burn grazing (PBG) and mixed-species grazing (MSG). Data were collected through a mail survey of landowners in the Southern Great Plains who own at least 100 acres. The significant and positive correlation between PBG and MSG suggests that their relative preference tends to change together, potentially allowing them to complement when implemented together.

Precision Irrigation Technologies for Water‐Wise and Climate Resilient Alfalfa Production

AbstractThe future of water‐wise and resilient alfalfa production lies in the integration of precision irrigation technologies and innovative water management strategies. With the continued threat of drought and depleting levels within the Ogallala aquifer in regions like the Southern Great Plains of the United States, it is important to adopt precision techniques that optimize water use while maximizing crop yields and quality. From soil moisture‐based management to canopy‐based monitoring and the development of irrigation decision support systems, farmers and CCAs have many options from commercially available tools at their disposal to navigate water scarcity challenges. The power of artificial intelligence, satellite imagery, and real‐time data analytics can all be integrated together to bring the agricultural community to work towards a future where alfalfa production remains resilient and environmentally sustainable. Earn 1.5 CEUs in Soil &amp; Water Management by reading this article and taking the quiz at https://web.sciencesocieties.org/Learning‐Center/Courses.

Future Climate Change Shifts the Ranges of Major Encroaching Woody Plant Species in the Southern Great Plains, USA

AbstractWoody Plant Encroachment (WPE) is a key driver of grassland collapse in the Southern Great Plain (SGP), resulting in a series of adverse ecological and socioeconomic consequences. Climate change will interact with ongoing WPE as it will likely shift the potential ranges of WPE species. In this study, we employed an ensemble approach integrating results from multiple Species Distribution Models to project future distribution ranges of four major WPE species (Ashe juniper, honey mesquite, post oak, and eastern redcedar) in the SGP across the 21st century. The findings highlighted a noteworthy trend: under future climate conditions, the distribution ranges for these WPE species were projected to shift northward and eastward. Of particular concern is honey mesquite with significant expansion in distribution range, potentially covering up to two‐thirds of the SGP's non‐agricultural area by the end of the 21st century. Conversely, the other three WPE species were expected to experience a contraction in their distribution ranges. Ashe juniper may experience a decline in its current habitats in central Texas but gain new habitats in northern Texas, Oklahoma, and Kansas. The suitable ranges of post oak and eastern redcedar were projected to shrink eastward, primarily being restricted to eastern portions of Oklahoma and Texas under the RCP4.5 and a smaller area in eastern Oklahoma under the RCP8.5. The projected shift in WPE ranges provides a scientific basis for governments to optimize the allocation of management resources and implement timely practices to control the spread of woody plants during the early encroachment stage. Our study methodology is applicable to other regions and continents with WPE issues, including Africa, South America, and Australia.