WinterTurf: A Holistic Approach to Understanding the Mechanisms and Mitigating the Effects of Winter Stress on Turfgrasses in Northern Climates

WINTERTURF: A HOLISTIC APPROACH TO UNDERSTANDING THE MECHANISMS AND MITIGATING THE EFFECTS OF WINTER STRESS ON TURFGRASSES IN NORTHERN CLIMATES

Sponsoring Institution

National Institute of Food and Agriculture

Project Status

ACTIVE

Funding Source

OTHER GRANTS

Reporting Frequency

Annual

Accession No.

1027439

Grant No.

2021-51181-35861

Cumulative Award Amt.

$8,000,000.00

Proposal No.

2021-07748

Multistate No.

(N/A)

Project Start Date

Sep 1, 2021

Project End Date

Aug 31, 2026

Grant Year

2021

Program Code

[SCRI]- Specialty Crop Research Initiative

Recipient Organization
UNIV OF MINNESOTA
(N/A)
ST PAUL,MN 55108

Performing Department
Dept of Horticultural Science

Non Technical Summary
Winter stresses have long been a challenge for professional turfgrass managers. The long term goal of this project is to better understand turfgrass winter stresses and then identify solutions to this important specialty crop problem. Our approach will include research in plant breeding, genetics, and physiology; efforts to improve resistance to plant disease and thereby reduce pesticide applications; new technological innovations to predict winter stress damage more precisely; and modern approaches to engage and educate stakeholders. In our first objective, we will monitor turfgrass stands in cold climates to gain knowledge about the processes that lead to winter damage and how a changing climate will bring new challenges; we will then use this information to both inform research and create a web-based winter stress injury prediction application. In Objective 2, we will increase basic understanding of turfgrass injury due to ice cover and freeze/thaw events. Next, in Objective 3, we will deepen our understanding of snow mold pathogens and develop alternative, non-fungicidal strategies for their control in managed turf. Breeding and genetics efforts in Objective 4 will focus on germplasm improvement for winter stress tolerance. In Objective 5, we will develop strategies for mitigation and recovery from winter stress damage and investigate the economic effects of winter stress damage. Finally, in Objective 6, we will coordinate a comprehensive outreach effort designed to educate multiple audiences and implement research recommendations. We aim to provide stakeholders with solutions to combat the challenge of winter stresses.

Animal Health Component

25%

Research Effort Categories

Basic

25%

Applied

25%

Developmental

50%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
201	2130	1081	20%
206	2130	1020	15%
601	2130	3010	10%
132	2130	2070	10%
903	2130	3030	25%
205	2130	1060	20%

Knowledge Area
601 - Economics of Agricultural Production and Farm Management; 206 - Basic Plant Biology; 205 - Plant Management Systems; 132 - Weather and Climate; 201 - Plant Genome, Genetics, and Genetic Mechanisms; 903 - Communication, Education, and Information Delivery;

Subject Of Investigation
2130 - Turf;

Field Of Science
2070 - Meteorology and climatology; 1060 - Biology (whole systems); 1081 - Breeding; 3010 - Economics; 1020 - Physiology; 3030 - Information and communication;

Keywords

Goals / Objectives
The long-term goal of this project is to better understand turfgrass winter stresses, and to then identify and implement solutions to reduce the impact of these stresses. Our comprehensive, trans-disciplinary approach will generate new ways of meeting winter stress challenges that will positively impact stakeholders with economic (reduced recovery costs) and environmental (soil stabilization, reduced runoff, etc.) benefits. In Obj. 1, we will assess turf stands in cold climates to gain knowledge about the processes that lead to winterkill in a changing climate. We will use that information to define and prioritize main types of environments (envirotypes) that lead to winter stress damage of turf, and create a winter stress injury prediction model that can help turfgrass managers make data-driven decisions before, during, and after winter stress. In Obj. 2 we will design and execute experiments based on envirotypes identified in Obj. 1, while at the same time substantially improving our understanding of the physiological factors associated with turfgrass injury and tolerance due to stressors such as ice cover and freeze-thaw events. In Obj. 3 we will monitor the environmental conditions that lead to disease development and learn more about the basic biology of snow mold pathogens and their level of fungicide resistance, which will allow us to develop more integrated snow mold management strategies, including new resistant cultivars. In Obj. 4, our breeding and genetics efforts will focus on germplasm improvement for minimizing winter stresses in creeping bentgrass and perennial ryegrass. In Obj. 5 we will develop strategies for management of, and recovery from, winter stress damage and study the economics of turfgrass winter stresses. Finally, in Obj. 6 we will develop and implement an extensive outreach program aimed at multiple stakeholder audiences to disseminate recommendations resulting from our research, establish a portfolio of tools and resources, and facilitate local knowledge sharing among peers.

Project Methods
Objective 1 (Remote Sensing): Before developing solutions to minimize the effects of winter stresses, we need to better understand how various environmental conditions act synergistically to kill managed turfgrasses under field conditions. To do this, we will define envirotypes, which are recurrent environmental scenarios that are likely to take place with a certain probabilistic certainty in a given location Our proposed data collection system will integrate data from 4 different platforms: (a) ground sensing above and below the turf surface; (b) data collection by golf course superintendents; (c) unmanned aerial vehicle-based sensing to characterize the spatial variation in green damage (UAV sensing); and (d) satellite remote sensing to enable the scaling of insights from the platforms a-c to golf courses that do not have data collection platforms. This data will be useful in defining envirotypes that will drive work described in Obj. 2. Next, we will identify a typology of different main winter environment types that turfgrass is facing across cold climates, which will further help define target tolerance traits and management strategies. Time series classification (i.e., damage and no-damage) will be based on the integrated data from the four sensing platforms, combined with other climate factors. At the higher level, we will investigate multiple state-of-the-art time series representation learning algorithms to identify specific weather patterns (envirotypes) that lead to turfgrass winter injury. The secondary level will further classify climate-driven envirotypes based on information collected from the four sensing systems described above. Specifically, we will incorporate derived parameters from hyperspectral and remote sensing data with measured parameters from ground sensors. We will project how envirotypes will change over time using future climate projections to inform breeders and managers. We will build spatial learning and predictive models that can forecast the performances of turfgrass based on these physical and climatic characteristics. These prediction models will be used to create a web-based winter injury risk prediction tool described below. Climate projections will be used to analyze the future likelihood conditions leading to winter stress damage, inform the prioritization of envirotypes, and to drive simulations of a land surface model that will dynamically represent growth and disturbance of turf.Objective 2 (Plant Physiology): First, we will develop a high-throughput method for determination of leaf recovery and develop novel crown viability assays to correlate with whole-plant survival. Next, we will develop a high-throughput vascular phenotyping method for evaluating freezing tolerance in turfgrasses. For the third component of this objective, we will evaluate alternative methods for exposing turfgrasses to oxygen deprivation (anoxic and hypoxic conditions). Next, we will examine the physiological effects of reintroducing plants into an aerated environment and determine post-anoxia interactions with temperature and light intensity. Finally, we will conduct a series of experiments to test the effects of variable photoperiod, twilight red:far red ratio, and light intensity on cold acclimation and freezing tolerance development in turfgrasses.Objective 3 (Snow Mold Management): Specific environmental parameters that lead to snow mold disease development remain poorly understood. We will utilize 20 locations from Obj. 1 from varying climates and varying disease pressures to serve as snow mold host sites in Years 1-3. Disease severity and environmental data will be collected in Years 1-3 and used to develop a predictive model. During Year 1 we will solicit turfgrass samples displaying symptoms of each of the major snow mold diseases from turf managers participating in Obj. 1, with the goal of obtaining at least 20 samples of each pathogen for use in a genetic diversity study. Using the same fungal isolates, we will determine how isolates respond to various environmental conditions present during two critical periods for disease development by mimicking fall and late winter conditions in a growth chamber through manipulation of daylength, light quality, and temperature. We will also assess fungicide resistance in M. nivale and determine the effects of potassium on disease development. Finally we will study tree leaf impact on snow mold development and assess plant protectants as alternatives to fungicides for disease control. Objective 4 (Breeding/Genetics): We will screen for three known weaknesses of creeping bentgrass: (1) snow mold resistance, (2) wear/traffic tolerance during winter months, and (3) germination rate and seedling vigor under cold temperatures common during spring winter recovery periods.A transcriptome analysis will be conducted to identify candidate genes responsible for snow mold tolerance in creeping bentgrass genotypes. In combination with the transcriptome analysis, genome-wide association analysis will be conducted to identify candidate genes affecting snow mold tolerance. For perennial ryegrass, we will use both field and laboratory approaches to identify winter hardy germplasm, including both molecular and metabolomic approaches. Multi-site testing of turfgrass selections and cultivars will help identify winter stress tolerant germplasm.Objective 5 (Turfgrass Management): Our research team will be creative in testing methods to prevent winterkill based on climate change prediction, envirotype prioritization, modeling, and plant physiology research. We will use the results from sensor-enabled golf greens in Obj. 1 as a basis for the design of improved environmental sensors for use in monitoring winter stresses of managed turf. We will conduct surveys with golf course and sports turf managers to assess the economic consequences caused by winter injury in the northern U.S. and Canada. In a separate survey, we will conduct choice experiments with golf course superintendents and sports field managers to investigate their willingness to pay for various tools to monitor winter conditions and injury on their turfgrasses. Finally, we will investigate if it is profitable for private companies to mass produce the environmental sensors developed in Obj. 1.Objective 6 (Outreach): We plan to use mixed engagement methods to convey our findings. We will use these traditional methods to share our research findings across northern regions. State and regional conferences take place across all locations, and we will organize special winter stress sessions highlighting our research progress at annual turfgrass conferences in our states and at national conferences. Beyond the traditional approaches, we will use modern information and communication technologies like social media and websites. Additionally, we will pilot new approaches to engage with turfgrass users (golfers, athletes, residential lawn owners) and higher-level policy makers (board members, elected officials, government agencies). The web-based application developed in Obj. 1 will be a cornerstone of outreach to promote adoption of this technology and consolidate stakeholder feedback. Ultimately, our goal is to create an application in which we can help predict the likelihood of winter injury to a turfgrass area. To promote adoption of this new technology, we will provide a training program with several opportunities for engagement.

Progress 09/01/23 to 08/31/24

Outputs
Target Audience: Nothing Reported Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Faculty collaborators in this project have continued to mentor graduate students and postdoctoral associates throughout the grant period. These scholars are being trained in a number of areas beyond discipoinary specific methods. For our third team project meeting, a number of graduate students and postdoctroal associates attended; they were brought into a number of rich transdisciplinary conversations where they began to see the many ways our project benefits from diverse viewpoints. How have the results been disseminated to communities of interest?We have communicated to stakeholders through talks at scientific meetings, professional conferences, articles in magazines published by professional societies, blog posts, and an email newsletter. In Minnesota, a field day was held in earlly April 2024that focused entirely on projects from this project. What do you plan to do during the next reporting period to accomplish the goals?Objective 1: Assess turfgrass stands in cold climates to gain knowledge about the processes that lead to winterkill We will deploy sensors in fall 2024 for the 2024-2025 winter season and continue to collect survey data from golf courses across northern latitudes. Preliminary work on envirotyping using novel deep learning dimensionality reduction techniques is informing controlled trial data in the other objectives and forecasting work will continue. Results will be regularly communicated to researchers working on other objectives so that projects can be driven by this robust data collection effort. Objective 2: Increase our understanding of factors associated with winterkill to inform turfgrass management and breeding approaches We will continue analysis of xylem traits with the goal of confirming traits within a larger number of genotypes. In addition, new experiments will be initiated based on envirotyping data generated from the Objective 1 research. The repeated experiments evaluating interactions of light, temperature and low oxygen will be summarized for publication. Objective 3: Develop improved integrated snow mold management strategies The field studies investigating the influence of fertility on snow mold development and tree leaf mulching on soil health will continue for one more winter in Wisconsin and Michigan. Disease predictive models first tested in the field in 2023-2024 were updated following an evaluation of their performance and are being tested in the field again in Oregon and Wisconsin. Alternative snow mold control products, phylogenetic analysis of the snow mold isolate collection, and fungicide resistance assays have all been completed and will be written up for publication within the next year. Objective 4: Improve creeping bentgrass and perennial ryegrass germplasm for traits associated with superior winter hardiness We plan to continue trait characterization of anatomy and physiological traits in genotypes that are known to contrast for freeze tolerance in the field. Environmental and phenotypic data will be analyzed alongside survival data from the field locations to identify promising winter hardy germplasm and understand underlying genotype x environment interactions. Ice encasement screening will focus on perennial ryegrass populations and we will continue to screen bentgrass germplasm for winter wear tolerance. Genome-wide association study of creeping bentgrass will be conducted. Transcriptome analyses will be completed for both snow mold resistance in creeping bentgrass. Metabolomic analysis of a large perennial ryegrass panel growing under fall acclimation conditions (parameters informed by field collected sensor data in Objective 1) will be completed and results will be used to identify a subset of genotypes for further transcriptomic study. Objective 5: Develop strategies for mitigation of and recovery from winter damage in turfgrass systems The topdressing research aimed at evaluating the effects of late-season sand topdressing rates on putting greens will be repeated in Michigan, Minnesota, Norway, Oregon, and Wisconsin over the 2024-2025 season. In addition, we will prepare field plots for a study on approaches to reducing cold temperature photoinhibition on creeping bentgrass seedlings. We will also survey turfgrass managers about their potential use of environmental sensing nodes for on-site winter stress prediction. Objective 6: Educate stakeholders about winter stresses As results from completed studies are known, we will communicate with stakeholders through multiple in person and virtual channels. We will continue expanding our network of turfgrass managers for data collection (https://winterturf.umn.edu/dashboard). Blog posts with research results will be published on our WinterTurf project website and our monthly WinterTurf newsletter will continue to be sent to subscribers.

Impacts
What was accomplished under these goals? Objective 1: Assess turfgrass stands in cold climates to gain knowledge about the processes that lead to winterkill Data were again collected and integrated into a standardized dataset for the research team. This includes sensor data, survey data, unmanned aerial vehicle data, satellite remote sensing data, and ancillary data such as digital elevation models. We have also added access to future climate forecasts for Minnesota to the database and our fleet of sensing devices has expanded to 86 nodes. Devices were again deployed across the northern United States, Canada, and Europe with annual repairs and maintenance performed to ensure data quality. The project team has worked to standardize quality assurance and control procedures across the analysis teams. Work is ongoing to develop statistically downscaled satellite estimates of soil moisture for golf course greens. Preliminary work on envirotyping using novel deep learning dimensionality reduction techniques is informing controlled trial data in the other objectives and forecasting work is ongoing. Objective 2: Increase our understanding of factors associated with winterkill to inform turfgrass management and breeding approaches We exposed three turfgrass species to controlled environment ice encasement to examine mechanisms of anoxia tolerance. Perennial ryegrass (freeze tolerant and freeze susceptible) were examined for differences in vascular traits, indicating that freezing sensitive plants maintain higher metaxylem size in roots and leaves compared to freeze tolerant plants. We also confirmed a strong interaction between light and post-anoxic conditions, suggesting a role for light intensity promoting stress following ice encasement. Objective 3: Develop improved integrated snow mold management strategies Field studies were conducted across multiple locations in the U.S. and Norway on numerous projects investigating the influence of various fertilizer rate and application timings on snow mold severity, the efficacy of non-traditional snow mold control products, and the impacts of tree leaf mulching on snow mold development and soil health in home lawns. In addition, two predictive models for gray/pink snow mold and Microdochium patch were tested in the field for the second consecutive winter. Finally, a phylogenetic analysis of the 73 Microdochium nivale isolates collected in 2022 was completed using the ITS gene as a target and a fungicide resistance assay was conducted on a subset of these isolates using 4 commonly-applied fungicides. Objective 4: Improve creeping bentgrass and perennial ryegrass germplasm for traits associated with superior winter hardiness Creeping bentgrass improvement efforts focused on evaluating both turfgrass plots and mowed spaced plant breeding trials for winter wear tolerance. In addition, we identified M. nivale susceptible and tolerant creeping bentgrass genotypes for transcriptomic analysis to identify candidate genes involved in disease response. Perennial ryegrass improvement efforts included two years of winter stress tolerance evaluation of a 100-accession panel planted in field plots located in St. Paul, Minnesota; Amherst, Massachusetts; and Landvik, Norway. Top performing accessions will be advanced to our breeding programs. We have also studied perennial ryegrass genotypes contrasting for winter stress tolerance for transcriptomic and metabolomic responses. Finally, we have completed multiple metabolomics method development projects (sampling time, plant sampling protocols, controlled environmental condition optimization, etc.) that will inform the final design of an extensive metabolomic screening that includes over 190 diverse perennial ryegrass genotypes. Objective 5: Develop strategies for mitigation of and recovery from winter damage in turfgrass systems Turfgrass managers in cold climates need to re-establish winter damaged turfgrass areas at times when temperatures are not conducive for seed germination. We completed the second year of research on seeding into an annual bluegrass green that was killed with herbicides to simulate winterkill; the objective of this study was to evaluate spring establishment rate of creeping bentgrass and annual bluegrass seeded over three consecutive weeks. Timing of seeding was significant at the beginning of establishment period with the first seeding date having the highest percent cover in both years but by the end of the study, timing of seeding was not significant. Based on our roundtable discussions with U.S. turfgrass stakeholders (Objective 6) it is clear that late-season sand topdressing is a common winterkill prevention strategy on putting greens in the northern climates; however, there is little research to either support or refute the practice. To address this, we evaluated the effects of sand topdressing rate (none, medium, high) on winter stress injury in Michigan, Minnesota, Norway, Oregon, and Wisconsin. Topdressing was applied in a single application after the final mowing of the season and before the first anticipated snowfall. Surface temperatures were higher for the high topdressing rate treatments which may result in increased biological activity for snow mold pathogens; in Wisconsin, this was the case, with more snow mold on the high topdressing rate treatments. In Oregon, surface temperature and quality increased with topdressing rate, while winter damage decreased with increasing topdressing rates; although three weeks after snow melt there were no differences in winter damage. Objective 6: Educate stakeholders about winter stresses To communicate our research results, we continued to publish content, including 24 blog posts, on our WinterTurf project website (https://winterturf.umn.edu), as well as in our monthly WinterTurf newsletter with 786 subscribers. We hosted field days to show field results to turfgrass managers and sought their input on future projects, and gave numerous talks at conferences and professional meetings. We also expanded our outreach to additional states to gain greater participation in on-site data collection (Objective 1).

Publications

Type: Peer Reviewed Journal Articles Status: Published Year Published: 2024 Citation: Gendjar, M., D. Chalise, R. Beaudry and E. Merewitz (2024). Influence of controlled condition ice encasement of creeping bentgrass and annual bluegrass on plant recovery, gas evolution, and metabolites. J. Amer. Soc. HortSci. 149:230-242.
Type: Theses/Dissertations Status: Published Year Published: 2024 Citation: Perkinson, P. C. 2024. Spring establishment of creeping bentgrass and annual bluegrass on putting greens following simulated winterkill. Masters thesis, Michigan State University. https://doi.org/doi:10.25335/yaz4-w279
Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Liess, S., and T. Twine, et al. 2024. Adaptation and resilience workshop. IMPACT conference. 30 April 2024. St. Paul, Minnesota. https://www.usgbc.org/event/impact-conference-2024
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Liess, S. and T. Twine, et al. 2023. A23Q-2594: Fine-scale climate projections over Minnesota for the 21st century. AGU Fall Meeting. 11-15 December 2023.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Liess, S. and T. Twine, et al. 2023. County-scale climate projections over Minnesota for the 21st century. 2023 Midwest Climate Resilience Conference. 25-27 October 2023. Duluth, Minnesota.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Freund-Saxhaug, K., A. Hegeman, and E. Watkins. 2023. Optimizing methods for turfgrass metabolomics. ASA, CSSA, SSSA International Annual Meeting. St. Louis, MO.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Petrella, D. P., Sessoms, F., & Watkins, E. 2023. Response of hard fescue (Festuca brevipila) genotypes to light intensity and light quality in controlled environments. ASA, CSSA, SSSA International Annual Meeting. St. Louis, MO.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Arghavani, M., and M. DaCosta. 2023. Evaluation of freezing recovery of creeping bentgrass seedlings. ASA, CSSA, SSSA Annual Meeting, St. Louis, MO.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Lu, J.H., M. Arghavani, K. Wester, S. Dalmannsdottir, T.S. Aamlid, E. Watkins, and M. DaCosta. 2023. Exploring genetic variation in post-hypoxia recovery of cool-season grass species following ice cover. ASA, CSSA, SSSA Annual Meeting, St. Louis, MO.
Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Yang, C. 2024. Detection on golf courses through drone-based multispectral imaging. Artificial Intelligence in Agriculture conference. 15 April 2024.
Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Perkinson, P.C., K.W. Frank, and E. Galbraith. 2024. Spring establishment of creeping bentgrass (Agrostis stolonifera L.) and annual bluegrass (Poa annua var. reptans (Hauskn.)) following simulated winterkill on an annual bluegrass putting green. Agronomy Abstracts. Madison, WI.
Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Perkinson, P.C., K.W. Frank, and E. Galbraith. 2024. Late-season topdressing on cool-season putting greens in Michigan. Agronomy Abstracts. Madison, WI.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Perkinson, P.C., K.W. Frank, E. Watkins, D.J. Soldat, A. Thoms. 2023. Spring establishment of creeping bentgrass (Agrostis stolonifera L.) and annual bluegrass (Poa annua var. reptans (Hauskn.)) following simulated winterkill on putting greens. Agronomy Abstracts. Madison, WI.
Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Frank, K. Winterkill: strategies for minimizing damage and reestablishment techniques. Peaks and Prairies GCSA Almost Spring Meeting. March 2024. Billings, MT.
Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Frank, K. Dead greens coming out of winter: now what? New England Regional Turfgrass Foundation Turfgrass Conference and Show. March 2024. Providence, RI.
Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: Yue C., U. Parasuram, E. Watkins, D. Soldat, P. Koch, K. Frank, and M. DaCosta. 2024. Economic impact of winter injuries on golf courses in North America. American Society for Horticultural Science Annual Conference.

Progress 09/01/22 to 08/31/23

Outputs
Target Audience: Nothing Reported Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Faculty collaborators in this project have continued to mentor graduate students and postdoctoral associates throughout the grant period. These scholars are being trained in a number of areas beyond discipoinary specific methods. For our second team project meeting, a number of graduate students and postdoctroal associates attended; they were brought into a number of rich transdisciplinary conversations where they began to see the many ways our project benefits from diverse viewpoints. How have the results been disseminated to communities of interest?We have communicated to stakeholders through talks at scientific meetings, professional conferences, articles in magazines published by professional societies, blog posts, and an email newsletter. In Minnesota, a field day was held in earlly April 2023that focused entirely on projects from this project. This type of focused educational event will serve as a model for other collaborators as we move forward through the grant period. What do you plan to do during the next reporting period to accomplish the goals?Objective 1: Assess turfgrass stands in cold climates to gain knowledge about the processes that lead to winterkill We will continue to collect data across North America and Europe, and release improved datasets to the data science team. The data science team will improve the models and begin to report on their findings in academic conferences and start preparing journal articles. The sensing systems are now stable and intellectual property on CO2 sensing will be disclosed to University of Minnesota Technology Commercialization. Additionally, we will begin exploring the use of future climate scenarios to project out in the future how envirotypes will change due to climate change now that those data are available. Objective 2: Increase our understanding of factors associated with winterkill to inform turfgrass management and breeding approaches We will continue to use data from Objective 1 to inform improved research methodology aimed at better understanding tolerance to ice encasement and other important winter stress survival traits. Additional experiments are planned to examine xylem traits in a larger number of perennial ryegrass genotypes. We will also focus on determining the most optimal crown cell viability methods via staining techniques. In addition, new experiments will be focused on testing the effects of various light treatments that simulate changes in spectral quality that occur at the end of the day and in the morning in perennial ryegrass genotypes. Objective 3: Develop improved integrated snow mold management strategies All of the field studies conducted during the winter of 2022-2023 will be repeated in 2023-2024 at sites in Wisconsin, Oregon, Michigan, Massachusetts, and Norway. The disease predictive models first tested in the field last year were updated following an evaluation of their performance and are being tested in the field again this winter in Oregon and Wisconsin. Additional phylogenetic analysis of the snow mold isolate collection will be conducted using the ELF1-alpha gene to further assess genetic diversity within snow mold fungi. Objective 4: Improve creeping bentgrass and perennial ryegrass germplasm for traits associated with superior winter hardiness Creeping bentgrass: Further screening of targeted creeping bentgrass plants for pink snow mold resistance will be conducted in the growth chamber to quantify resistance for potential future evaluation in the field. Individual creeping bentgrass genotypes with snow mold tolerance will be identified and used for transcriptome and genomic analysis. Progeny from the two bentgrass populations listed above will be screened for wear tolerance through the winter months. Additionally, two more field trials will be screened for winter wear tolerance in early 2024. This will include progeny screening in preparation for selection for this trait in the future. Perennial ryegrass: The multi-location competitive spaced plant nursery will be evaluated for one additional winter; results will be used to identify a subset of materials that can be advanced in germplasm improvement efforts at Minnesota and Rutgers. In addition, genotypes showing differential responses will be useful for physiological studies (Objective 2). After completion of metabolomics method development, another experiment will be conducted prior to metabolomic and transcriptomic analysis of the full perennial ryegrass genotype panel. To determine when peak gene expression for cold tolerance occurs in perennial ryegrass, which is needed to know when best to sample throughout acclimation, six perennial ryegrass genotypes ranging in cold tolerance will be assessed. Briefly, clones of these six genotypes will undergo acclimation and will be sampled regularly for metabolomic and transcriptomic analyses. Once optimal harvest times are determined, the full panel will be assessed. Objective 5: Develop strategies for mitigation of and recovery from winter damage in turfgrass systems Management: Researchers in Norway and Michigan will continue to investigate seeding creeping bentgrass into existing annual bluegrass stands during early spring. Two new multi-location research studies will be initiated: 1) the effect of late fall sand topdressing on turfgrass performance and winter survival, a project developed directly in response to stakeholder feedback at winter stresses roundtables (Objective 6) and 2) the use of shade cloth during cool periods in early spring to reduce photoinhibition on newly seeded bentgrass in cold climates. Economics: More data will be collected to understand the economic impact of winter injuries from both US and Canada golf courses. For the economics of winter stress monitoring tools, we will complete the theoretical model and then will design the survey based on the model and start to collect data after the survey is developed. Objective 6: Educate stakeholders about winter stresses As results from completed studies are known, we will prepare talks, reports, articles, and papers reporting results to multiple stakeholder groups. We also continue to work on ways to engage turfgrass managers with collaborative data collection, similar to how managers can now view images and data from other data collectors throughout the world (https://winterturf.umn.edu/dashboard). Our team will also continue to discuss how to reach key stakeholders who have budgetary oversight at professional turfgrass facilities in cold climates. New blog posts with research results will be published on our WinterTurf project website and our monthly WinterTurf newsletter will continue to be sent to subscribers.

Impacts
What was accomplished under these goals? Objective 1: Assess turfgrass stands in cold climates to gain knowledge about the processes that lead to winterkill Data were collected and integrated into a standardized dataset for the research team. These include environmental sensor data, survey data, unmanned aerial vehicle data, and satellite remote sensing data; we also added future climate forecasts to this database. This was the second season of environmental sensing data collection. We expanded our deployed fleet to just over 61 nodes. These devices were deployed in partnership with golf courses across the northern United States, Canada, and Europe. Over the past two field seasons, we have collected over 23 million sensor observations and integrated them into a standardized dataset. Surveys were refined and sent at the beginning of the winter season, weekly throughout, and then after the season ended. We received over 1100 survey responses. With two seasons of data collected, the team has started to perform machine learning analyses. These include advancing envirotyping work through correlation analysis, cluster analysis with K-means, among other machine learning approaches. Preliminary forecasting work is being done for winterkill using multiple machine learning methods. Objective 2: Increase our understanding of factors associated with winterkill to inform turfgrass management and breeding approaches Progress was made on testing novel methods for assessment of crown survival using automated, real-time equipment within high-throughput Dynamic Environmental Photosynthetic Imaging chambers. Experiments were completed testing known freeze susceptible and tolerant genotypes of perennial ryegrass for metaxylem traits, which included laser ablation tomography images (xylem vessel/vascular bundle size in roots/leaves) and gas exchange (water movement). A second year of experiments were completed examining the interactive stresses associated with post-anoxia conditions. Growth chambers with specialized lighting were developed for testing interactive temperature and light quality experiments. Objective 3: Develop improved integrated snow mold management strategies Field studies initiated in the last year across multiple locations in the U.S. and Norway include those investigating the ability of various fertilizer rate and application timings on snow mold severity, the efficacy of non-traditional snow mold control products, and the impacts of tree leaf mulching on snow mold development and soil health in home lawns. In addition, two predictive models for gray/pink snow mold and Microdochium patch were tested in the field for the first time. Finally, a phylogenetic analysis of the 73 Microdochium nivale isolates collected in 2022 was completed using the ITS gene as a target. Objective 4: Improve creeping bentgrass and perennial ryegrass germplasm for traits associated with superior winter hardiness Creeping bentgrass: Two creeping bentgrass populations were screened for resistance to pink snow mold in the growth chamber and potential sources of resistance were identified. The progeny from these two populations were planted in a mowed spaced-plant trial in New Jersey to screen for winter wear tolerance. Two replicated bentgrass trials, one maintained at putting green height and one at fairway height, were also screened for winter wear tolerance. Perennial ryegrass: A perennial ryegrass mapping population was screened for ice encasement resilience for multiple durations and using different methods in controlled environments at Michigan, with the goal of using additional information from envirotyping in Objective 1 to develop optimal screening conditions for this important trait. We evaluated an established competitive spaced plant nursery consisting of 100 half-sib families; this trial is located in Massachusetts, Minnesota, and Norway. Due to limited winter injury in 2022-2023, this trial continues to be evaluated. To prepare for a larger multi-omics study, we finalized a 196 genotype perennial ryegrass genotype panel. A number of method development studies have been conducted, including evaluations of solvent systems and extraction methods, comparison of metabolite profiles within and across tissue types, and optimization of LC-MS parameters. This information will be used to inform metabolomics approaches during the upcoming year. Objective 5: Develop strategies for mitigation of and recovery from winter damage in turfgrass systems Management: Turfgrass managers in cold climates need to re-establish winter damaged turfgrass areas at times when temperatures are not conducive for seed germination. To see if creeping bentgrass cultivars differed in their ability to establish during the early spring, two different seeding trials were conducted in spring 2023. In the first trial, conducted in Michigan, Minnesota, Iowa, and Wisconsin, we seeded four creeping bentgrass cultivars, 'Two-Putt' annual bluegrass, and a 50/50 by weight mix of 'Two-Putt' annual bluegrass and 'Pure Distinction' creeping bentgrass on 3 different dates in early spring into a bare soil seedbed. Results differed by location but generally there were few significant differences among the creeping bentgrass cultivars. At some locations the early seeding date had the most rapid establishment, but the effect of seeding date only lasted for the first three weeks of establishment. In the second trial, conducted in Michigan and Norway, we seeded creeping bentgrass cultivars, 'Two-Putt' annual bluegrass, and a 50/50 by weight mix of 'Two-Putt' annual bluegrass and 'Pure Distinction' creeping bentgrass on 3 different early spring dates into an annual bluegrass putting green that was killed with herbicides to simulate winterkill. Locations differed in results with few differences in cultivar in establishment rate and similar to the bare soil trial, the early seeding date had the most rapid establishment but the effect was short lived. Economics: Damage caused by winter injury on golf courses is a significant financial risk to golf courses. After completing a survey to understand the economic impact of turfgrass winter injury on the economics of golf course facilities in the U.S. and Canada, we have begun data analysis. For the economics of winter stress monitoring tools, we have begun developing a theoretical model. Objective 6: Educate stakeholders about winter stresses Our outreach team held regional stakeholder roundtables to discuss common winter issues in Iowa, Massachusetts, Michigan, Minnesota, Oregon, and Wisconsin. Within these roundtable discussions we identified the most common stressors faced by superintendents: moisture regulation, weather variability, ice formation, traffic, and snow. Alongside identifying stressors, we gathered information on the most common management techniques used to counteract them including: applying snow mold fungicide, topdressing before winter, and altering mowing practices in late fall among many others. Finally, we gathered common concerns and questions from stakeholders to help guide our outreach and education work in the future. The findings from this work were delivered directly to stakeholders in Minnesota via a summary article published in a trade magazine. To communicate our research results, we continued to publish content, including 25 blog posts, on our WinterTurf project website (https://winterturf.umn.edu), as well as in our monthly WinterTurf newsletter with 760 subscribers.

Publications

Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Chou, M., E. Braithwaite, B. McDonald, A. Kowalewski, and P. Koch. 2023. Developing risk predictive models for Microdochium patch in amenity turfgrass with machine learning algorithms to optimize fungicide use. American Phytopathological Meeting.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: DaCosta, M. Transitioning from Winter to Spring: Understanding factors impacting turfgrass recovery following ice cover. Norwegian Institute of Bioeconomy Research. June 21, 2023. Kristiansand, Norway.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: DaCosta, M. Strategies for enhancing Creeping bentgrass re-establishment following winterkill. Norwegian Institute of Bioeconomy Research. June 21, 2023. Kristiansand, Norway.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Jung, G. Turfgrass Diseases: diagnosis and management. Korean Society of Plant Pathology, Oct. 19, 2023. Jeju, South Korea.
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Liess, S., T. E. Twine, H. A. Roop, P. Snyder, P. Neff, S. Clark, and B. Hoppe. County-scale climate projections over Minnesota for the 21st century. Minnesota Supercomputing Institute Research Symposium (4/25/23).
Type: Journal Articles Status: Other Year Published: 2023 Citation: Min, S. and G. Jung. 2023. 2022-23 Evaluation of snow mold products on golf course fairways in New England. 2023. Plant Disease Management Reports.
Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Stover, C., A. Kowalewski, E. Watkins, and C. Yang. 2022. Remote sensing of winter injury on golf courses. ASA-CSSA-SSSA International Meeting. November 2022. Baltimore, MD. https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/143953
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Till, J.L., J. Zhou, Q. Yang, E. Watkins, and Z. Jin. 2023. Envirotyping analysis for predicting winterkill of U.S. wheat crops. American Geophysical Union Fall Meeting, San Francisco, California.
Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Watkins, E., B. Runck, A. Hollman, B. Schulz, and J. Bishop. 2022. Using environmental sensors on golf course greens to improve knowledge and management of winter stresses in cold climates. ASA-CSSA-SSSA International Meeting. November 2022. Baltimore, MD. https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/142867
Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Yue, C., U., Parasuram, E, Watkins, K. Frank, P. Koch, D. Soldat, and A. Thoms. 2023. The challenges of turfgrass winter injuries: Perspectives of golf course superintendents. American Society of Horticultural Science Annual Conference. July 31-August 4, 2023. Orlando, FL.

Progress 09/01/21 to 08/31/22

Outputs
Target Audience: Nothing Reported Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Faculty collaborators in this project have hired new graduate students and postdoctoral associates who will be mentored throughout the grant period. These scholars will be trained in a number of areas beyond discipoinary specific methods. For our first team project meeting, a number of graduate students and postdoctroal associates attended; they were brought into a number of rich transdisciplinary conversations where they began to see the many ways our project benefits from diverse viewpoints. How have the results been disseminated to communities of interest?We have communicated to stakeholders through talks at scientific meetings, professional conferences, articles in magazines published by professional societies, blog posts, and an email newsletter. In Minnesota, a field day was held in earlly April, 2022 that focused entirely on projects from this project. This type of focused educational event will serve as a model for other collaborators as we move forward through the grant period. What do you plan to do during the next reporting period to accomplish the goals?Objective 1: Assess turfgrass stands in cold climates to gain knowledge about the processesthat lead to winterkill Data: We will deploy additional nodes to get to a fleet of 70-80 in total. We will further refine the standard operating procedures for node deployment. Additionally, we will begin writing up the sensing systems and their verification for publication. We will manage the return of all devices, recalibration, and refurbishing, and then work with team members to do data integration again. We will also begin supporting model building by the machine learning team members. For drone imagery, we will expand the coverage of our drone image collection trips in Minnesota and Oregon. Both hyperspectral and multispectral image sets will be collected. Spring image sets will be used for data analysis, with the fall image sets as the baseline. In addition, we will conduct flights over field experiments in Minnesota. For all types of data collection in our project, many factors, including human errors and environmental conditions (e.g., light intensity), may impact the data quality. Hence, a pre-processing step is required to reduce noise and missing data to construct a reliable ground truth before processing via advanced spatial data science techniques, including hotspot detection and spatial prediction. We plan to investigate the application of spatiotemporal algorithms (e.g., spatial co-occurrence discovery) to detect hotspots of diseases and further analyze the underlying factors that cause the disease or damage due to ice or water cover. We plan to develop a regression model, namely a spatiotemporally aware recurrent neural network (e.g., CRNN), to estimate turfgrass quality rating based on the physical, climatic characteristics, and temporal data corrected for environmental conditions and noise. Modeling: We are evaluating global datasets of statistically downscaled climate projections to use for our study domain outside of Minnesota. One dataset includes soil temperature and moisture which may aid in the land surface model development. In Year 2 we will analyze our dynamically and statistically downscaled datasets to provide metrics of climate change to other Objectives. We will also collaborate with other PIs on developing turfgrass in the land surface model. Once site-level winter damage observations are available, we will explore ways to predict those damages based on weather, soil, and satellite data. Objective 2: Increase our understanding of factors associated with winterkill to informturfgrass management and breeding approaches Experiments will be initiated to test high-throughput methods for determination of crown viability correlated with whole plant survival (Obj. 2.1). We will phenotype and analyze winter survival data from the competitive spaced plant perennial ryegrass nursery in Minnesota, Massachusetts, and Landvik, Norway to identify a set of germplasm that contrast in winter survival and which will be used for Obj. 2.2 experiments. We will conduct comprehensive experiments to identify physiological and metabolic factors associated with anoxia tolerance (Obj 2.3). Lastly, experiments are planned to evaluate interactive effects of light and temperature on post-anoxia recovery (Obj. 2.3) and enhancement of cold acclimation (Obj. 2.4). Objective 3: Develop improved integrated snow mold management strategies In the spring of 2023 we will rate disease severity on the fertilizer rate and timing, tree leaf mulching, alternative control studies, and light supplementation studies. We will also evaluate the accuracy of our predictive models in Wisconsin and Oregon. We will conduct a phylogenetic analysis of the 73 snow mold isolates collected in 2022 and attempt to collect additional isolates for further taxonomic analysis. Objective 4: Improve creeping bentgrass and perennial ryegrass germplasm for traitsassociated with superior winter hardiness Team members in Norway, Massachusetts, and Minnesota will establish the SCANGREEN cultivar trial in summer 2023; in this trial, turfgrass cultivars of several cool-season species are tested under low-input management and assessed primarily for winter performance. We will use the new perennial ryegrass association panel, with over 200 diverse genotypes, to do an untargeted metabolomics analysis that will help identify clusters of similar accessions that can inform targets for transcriptomic analysis. Controlled freezing tests will be conducted on breeding material from both the Rutgers and Minnesota breeding programs. Breeding and evaluation work will continue on creeping bentgrass, with particular emphasis on screening for snow mold and resistance to winter wear. Objective 5: Develop strategies for mitigation of and recovery from winter damage inturfgrass systems Management: In spring of 2023, a seeding study will be conducted on bare soil of these greens. This will allow us to evaluate temperature effects on creeping bentgrass and annual bluegrass germination without the complicating factor of an existing bentgrass stand that is not dead. In addition to this study, in Michigan and Norway, an annual bluegrass green will be killed with a non-selective herbicide. This will allow us to assess the impact of an annual bluegrass green seed bank on reestablishment. We also plan to investigate how late-season applications of various wetting agents and application timings can help limit winterkill on sand-based athletic fields. Simulated traffic will be applied in the fall and then the application of wetting agents will be applied in late fall and green-up will be tracked in the spring. Economics: We will continue to encourage survey participation to get more responses in the coming months. Once we complete the survey data collection, we will conduct formal analysis on the survey data. IMPLAN software will be employed to investigate the economic impact of winter injuries. Objective 6: Educate stakeholders about winter stresses We will hold roundtable discussions, based on our experience in New England, in Michigan, Minnesota, Oregon, and Wisconsin; in addition, we are presenting project results at a national golf course superintendent association conference, where we will also conduct a roundtable discussion. These roundtables will help us identify current practices used by golf course superintendents and allows us to get feedback from practitioners.

Impacts
What was accomplished under these goals? Objective 1: Assess turfgrass stands in cold climates to gain knowledge about the processesthat lead to winterkill Data: A data collection system has been progressively developed to collect the required spatiotemporal data. The data collection pipeline integrates spatiotemporal data from different platforms, including ground sensing data above and below the turf surface, satellite remote sensing, and unmanned aerial vehicle-based sensing. Our project relies on golf course superintendent assistance with data collection. We successfully recruited over 100 superintendents to help with data collection during the winter on their courses. Team members created online surveys for golf course superintendents to participate in the weekly qualitative survey throughout each winter, including pre-winter, post-winter, and weekly surveys. We designed and created a comprehensive database holding data from these surveys, along with environmental sensors, satellite imagery, drone imagery from Minnesota and Oregon, and climate/weather data using data management best practices that can be used by all research groups throughout the project. Significant advances were made in the development and deployment of ground-based environmental sensors. In 2021 we designed, manufactured, developed standard operating procedures and installation videos for, and deployed 49 sensor nodes with golf course superintendent help that collected CO2, O2, soil moisture, soil temperature, and photosynthetically active radiation on over 40 golf course greens across the Northern United States, Canada, and Northern Europe. These devices streamed over 10M data packets, on which we performed quality assurance and control and integrated with other data collected by team members. In addition to the field work, we tested the CO2 sensor design in lab validation experiments. Modeling: In Year 1 we have developed our modeling protocol to dynamically downscale CMIP6 global climate model data for Minnesota. Our preliminary tests suggest that we will be able to meet our goal of downscaling 3 GCMs by the middle of Year 2. This testing has included evaluating a snow model within the Weather Research and Forecast regional model because of the focus on winter weather. The first historic run (1980-2005) is nearly complete and will be evaluated to finalize model parameters. Our agricultural modeling team analyzed the impacts of climate change on winter wheat (the only data-rich crop) across the USA using a data-driven approach calibrated on yield data from numerous counties. Our statistical models from 1999-2019, snow cover insulation weakened yield losses due to freezing stress by 22%, and projections show that future reduced snow cover could offset up to one-third of the yield benefit from reduced frost. This research will help inform turfgrass breeders as they consider the complex tradeoffs among warming, reduced snowpack and occasional freezing threats when developing climate-smart cultivars. Objective 2: Increase our understanding of factors associated with winterkill to informturfgrass management and breeding approaches Efforts were focused on method development and adapting experimental techniques to turfgrass plants. We initiated protocols for extracting metaxylem dimensions from perennial ryegrass samples using the laser ablation tomography (LAT) technique. We tested new protocols for exposing perennial ryegrass plants to controlled freeze-thaw cycles and developed protocols to acquire gas samples from potted turfgrass plants exposed to ice encasement conditions. Finally, we completed controlled environment testing to simulate post-anoxia stress conditions. Objective 3: Develop improved integrated snow mold management strategies A total of 73 isolates of M. nivale, T. ishikariensis, and T. incarnata were collected in spring of 2022 from around the U.S. and Norway for use in future experiments. Multiple field studies were established investigating impacts of fertilizer rate and timing on snow mold development, tree leaf mulching impacts on soil health and snow mold development on home lawns, use of alternative products for snow mold control, effect of cultivar and timing on reseeding success, and the application of additional light as a strategy to increase disease resistance in creeping bentgrass. Lastly, we developed multiple snow mold predictive models that will be field validated in 2022-2023. Objective 4: Improve creeping bentgrass and perennial ryegrass germplasm for traitsassociated with superior winter hardiness Creeping bentgrass: Two creeping bentgrass populations (over 30 individuals each) were created in the spring of 2022. These populations will be used for snow mold screening in Wisconsin and additional winter stress phenotyping studies. To simulate golf course wear during winter playing conditions in New Jersey, wear treatments were applied from January to March to a fairway height cultivar trial. Perennial ryegrass: A competitive spaced plant perennial ryegrass nursery, consisting of 100 half sib families from breeding programs and public collections, was established in Norway, Massachusetts, and Minnesota. This nursery will be used to both select for improved winter hardy genotypes and also help identify genotypes with contrasting winter hardiness for future physiology experiments. A panel of accessions and germplasm from our breeding programs is being established for use in metabolomics and transcriptomics projects. Objective 5: Develop strategies for mitigation of and recovery from winter damage inturfgrass systems Management: In the spring of 2022, a seeding trial was conducted in Iowa, Michigan, Minnesota, and Wisconsin to determine the effect of cultivar and date on the success of seeding after winter damage. Establishment rates were low due to very poor spring weather conditions and the trial will be re-initiated in 2023. Economics: We developed the survey to investigate the economic impact of winter injuries on managed turfgrasses. The survey was distributed and we are continuing to accept responses. Objective 6: Educate stakeholders about winter stresses A Winter Injury Roundtable Meeting was organized at the New England Regional Turfgrass Conference (March 9, 2022 in Providence, RI). Approximately 20 golf course managers participated in the panel discussion. Building off of this event, we will expand these discussions to events in several other states. We built and published a new project website (winterturf.umn.edu) where we post regular blogs about ongoing and planned research. In May, we sent out our first monthly WinterTurf monthly email newsletter to over 600 subscribers.

Publications

Type: Other Status: Published Year Published: 2022 Citation: Twine, T.E. 2022. Minnesotas changing winter climate. Hole Notes (Official Publication of the MGCSA), Vol. 57, Number 6, July 2022, pg. 38-40
Type: Other Status: Published Year Published: 2022 Citation: DaCosta, M. 2022. It may be July, but winter injury research is still in full swing at UMass, Amherst! https://winterturf.umn.edu/it-may-be-july-winter-injury-research-still-full-swing-umass-amherst
Type: Other Status: Published Year Published: 2022 Citation: Aamlid, T.S., W. Waalen and J. Hornslien. 2022. Good turn-out to study winter survival of greens at NIBIO Apelsvoll, Norway. STERF popular scientific articles, June 2022. http://www.sterf.org/Media/Get/3913/good-turn-out-to-study-winter-survival-of-greens.pdf
Type: Conference Papers and Presentations Status: Accepted Year Published: 2022 Citation: Yue, C., U. Parasuram, E. Watkins, K. Frank, P. Koch, D. Soldat, and A. Thoms. 2022. Investigating the economic impact of winter stress on U.S. golf courses. Agricultural and Applied Economics Association annual conference, Anaheim, California.
Type: Journal Articles Status: Published Year Published: 2022 Citation: Zhu P., T. Kim, Z. Jin, C. Lin, X. Wang, P. Ciais, N.D. Mueller, A. AghaKouchak, J. Huang, D. Mulla, and D. Makowski. 2022. The critical benefits of snowpack insulation and snowmelt for winter wheat productivity. Nature Climate Change, 12:485490. doi:10.1038/s41558-022-01327-3
Type: Other Status: Published Year Published: 2022 Citation: Runck, B., E. Watkins, and M. Reiter. 2022. Winter turf injury research update: scaling data collection systems with support from superintendents. Minnesota Golf Course Superintendents Association. Hole Notes. April.
Type: Other Status: Published Year Published: 2022 Citation: Frank, K.W. 2022. WinterTurf research update. Michigan Turfgrass Foundation NewsNotes Vol 2(1):p 7-9.
Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: DaCosta, M. 2022. Winter deacclimation dynamics in a changing climate. Symposium on Winter Stresses of Turfgrass. International Turfgrass Society Research Conference. July 15, 2022. Copenhagen, Denmark.
Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Dalmannsdottir, S. 2022. Winter stresses of grasses in the Arctic. International Turfgrass Conference Winter Stress Symposium, July 15, 2022, Copenhagen.
Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Aamlid T.S. 2022. Covering greens to reduce winter stress damage. International Turfgrass Conference Winter Stress Symposium, July 15, 2022, Copenhagen.
Type: Other Status: Published Year Published: 2022 Citation: Watkins E. 2022. UMN turfgrass researchers to lead new $8 million research project on winter stresses of turf https://issuu.com/mgcsa/docs/march_2022-hole_notes
Type: Other Status: Published Year Published: 2022 Citation: Department of Horticultural Science. 2022. Working toward a greener spring: Finding solutions to winter turfgrass damage. https://horticulture.umn.edu/news/winter-turf-working-toward-greener-spring
Type: Websites Status: Published Year Published: 2022 Citation: University of Minnesota. WinterTurf project website. https://winterturf.umn.edu/
Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Watkins, E. 2022. WinterTurf: A new approach to studying turfgrass winter stresses. 14th International Turfgrass Research Conference, International Turfgrass Society, Copenhagen, Denmark. July 15, 2022.