ENHANCING U.S. BIOSECURITY WITH IMPROVED PEST FORECASTS AND PUBLIC ENGAGEMENT

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: NEW
• Funding Source: AFRI COMPETITIVE GRANT
• Reporting Frequency: Annual
• Accession No.: 1028273
• Grant No.: 2022-68013-37138
• Project No.: ORE01017
• Proposal No.: 2021-11300
• Program Code: A1181
• Project Start Date: Apr 15, 2022
• Project End Date: Apr 14, 2025
• Grant Year: 2022

Project Director
Coop, L. B.

Recipient Organization
OREGON STATE UNIVERSITY
(N/A)
CORVALLIS,OR 97331

Performing Department
Ag OR IPM Center

Non Technical Summary
Invasive species have been an increasingly challenging and expensive threat to U.S. agriculture in recent decades. Tools and technologies that can help detect invasive pests are urgently needed because early detection and rapid response practices are the most cost-effective and efficient method to reduce these threats. Our project will provide science-based forecasts of when pests are active - termed phenology -- and where the pests are likely to be found in the conterminous U.S to agricultural stakeholders. This information can help ensure that surveillance operations take place in the right place and at the right time, allowing new pest populations to be detected and eradicated before they can establish and spread. For this project, we will produce regularly updated (every 2-3 days) forecasts of the potential distribution and phenology of five high-priority invasive species; three insects (emerald ash borer, spotted lanternfly, and Asian giant hornet), one plant disease complex (brown rot of tree fruits), and one weed (cheatgrass). We will generate these forecasts using our existing modeling tool known as DDRP (Degree-Day, establishment Risk, and Phenological event mapping system). The specific objectives of our project are to 1) extend the DDRP tool to include rainfall and soil moisture so that we can forecast pests whose activity and distribution is limited by these factors; 2) develop models and forecasts for five invasive species that represent major biosecurity threats to U.S. agricultural production systems; and 3) seek involvement from forecast users to improve these products, as well as provide observations of the pests' locations and timing of activity to evaluate forecast performance. Expanding the DDRP tool to include moisture variables like precipitation, relative humidity and soil moisture will enable us to ultimately produce forecasts for a much broader range of pests including plant diseases, weeds, and certain insects, as many of these species' distribution and activity is limited by moisture variables. We have comprehensive extension, outreach, and feedback programs planned to maximize adoption and implementation of model forecasts. Email newsletters, webinars, two advisory panels, recruitment and support of citizen science data collection, usability product testing, and interactive websites will all be developed in these communication and engagement efforts. The outcomes of this project will provide critically needed decision support and citizen engagement to help rapidly detect and respond to a wide range of major invasive pest species beginning with the five focal species for this work. End users can use forecasts for the present-day or near future to help make tactical (within-season) decisions, or forecasts for the more-distant future for help with strategic (long-term) decisions. The long-range benefits resulting from this project will include 1) reduced expenses involved with detecting and responding to the target invasive pests, 2) greater sustainability of crop, tree, horticulture, and livestock production, 3) increased security of the nation's supply of food, forage, timber, and horticultural products, 4) support of efforts to conserve and protect natural resources including native ecosystems, and 5) protection of life and property from pest-driven events such as wildfires and massive tree die-offs.

Animal Health Component

2%

Research Effort Categories

Basic

5%

Applied

60%

Developmental

35%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
211	1119	1130	10%
216	0610	3030	10%
721	3010	1130	10%
212	1119	1102	10%
216	1621	1140	10%
132	2410	2080	10%
903	2410	3030	20%
136	2410	2070	20%

Knowledge Area
212 - Pathogens and Nematodes Affecting Plants; 211 - Insects, Mites, and Other Arthropods Affecting Plants; 136 - Conservation of Biological Diversity; 216 - Integrated Pest Management Systems; 132 - Weather and Climate; 903 - Communication, Education, and Information Delivery; 721 - Insects and Other Pests Affecting Humans;

Subject Of Investigation
1119 - Deciduous tree fruits, general/other; 0610 - Conifer forests of the North; 1621 - Cool season perennial grasses; 2410 - Cross-commodity research--multiple crops; 3010 - Honey bees;

Field Of Science
2070 - Meteorology and climatology; 1130 - Entomology and acarology; 1102 - Mycology; 2080 - Mathematics and computer sciences; 1140 - Weed science; 3030 - Information and communication;

Keywords

climate suitability

establishment risk

invasive insects

phenology model

plant disease

weeds

Goals / Objectives
Our overall goal is to develop decision support tools that provide both strategic and real-time (tactical) predictions of invasive pest activities. In this effort, we will extend an established predictive tool (DDRP) to model a wider range of agricultural biosecurity threats, solicit feedback from end-users, and engage citizen scientists in contributing observations for forecast validation. Our specific objectives are to: 1) Expand the models ability to process real-time moisture data and run models for moisture-sensitive species; (2) Build and validate models for five invasive species (three insects, one plant pathogen species group, and one weed) that have major impacts on agricultural production systems, several of which are moisture-sensitive; and (3) Seek feedback from stakeholders through workshops and webinars, iteratively improve products based on stakeholder input, and solicit ground-based observations for use in forecast validation.

Project Methods
Objective 1: Add moisture processing capabilities to DDRP to improve model realism and broaden the range of organisms that may be modeled. We will extend the spatialized, real-time capable modeling platform DDRP (Degree-days, Risk, and Phenological event Mapping) by incorporating moisture data as daily average relative humidity (RH), precipitation (using PRISM or DAYMET data), and soil moisture (using NASA SMAP data). For climate suitability, we will develop moisture and dry stress accumulation approaches, following methods used for temperature stress. For example, when a species threshold is exceeded for a given factor, it will no longer support survival. For plant disease infection processes, we will use a combination of temperature and leaf wetness, that replicates the "degree-hours during periods of leaf wetness" approach typically used infection risk models. Our climate suitability models for all factors (cold stress, heat stress, dry stress, and wet stress) can be readily calibrated within DDRP using comparisons with the global CLIMEX modeling platform, which allows modeling of a species native range and then applying it to regions that it has not yet fully invaded. We will also calibrate these models using DDRP in other regions, such as Europe and Brazil, where the target species distribution is known, and where we have access to climate data.Our calibration and evaluation of spatial DDRP models for phenology and plant disease infection risk will involve comparing multiple site-based location models to our DDRP platform, adjusting parameters to provide similar results.Objective 2: Build and validate models for at least five insect, plant pathogen, and weed species that represent major biosecurity threats to US agricultural production systems and the nation's food supply, and operationalize these models to generate forecasts of each pest's potential distribution and phenology.For each species or species complex, we will build, calibrate and validate new DDRP models. All available published and online data will be considered for model building. These resources will include the USDA CAPS Pest Tracker website, www.inaturalist.org, USA-NPN Nature's Notebook, the Global Biodiversity Information Facility, and the Bugwood Center for Invasive Species. Observations made by collaborators such as USDA Agricultural Research Service, US Geological Survey, and state departments of agriculture will also be sought out (see letters of support). We will fit CLIMEX climate suitability models for each species using well-documented methods (Barker et al. 2020). This includes fitting geographic ranges to presence observations from sources just listed. We will preserve 25% of observations for validations. Phenological models will be fitted using degree-day modeling methodologies, using published phenological observations and scientific publications on developmental rates vs. temperature.For the emerald ash borer, which has already decimated ash trees throughout much of the Eastern US, and is still spreading to new regions, we will collaborate with USDA researchers with expertise on the biology of this insect (letters of support) to assure accurate model construction. Key model predictions will include forecasts of adult emergence and egg-laying to assist monitoring efforts.For the spotted lanternfly, a rapidly spreading invasive sap-feeding planthopper that poses a serious threat to multiple crops, we will construct a new DDRP phenological and update a CLIMEX model that includes moisture effects, based upon multiple recently published research studies. Predictions of interest are egg hatch and nymph emergence dates, to assist treatment and surveillance programs.For Asian giant hornet, a major threat to the honeybee and pollination services industries and to human health, we will construct a new phenological model from at least three identified published sources. Moisture is likely to be a range-limiting factor, as determined by published correlative niche modeling studies, which will be helpful in fitting a DDRP model for this species. Time of springtime queen foraging, and fall emergence of overwintering queens are events of interest for model parameterization.Brown rot, caused by Monilinia spp., is a destructive disease of stone fruits (M. fructicola, also M. laxa in the West) in warm, humid climates. Closely related M. fructigena is a disease of pome fruits (apple and pear) in Europe, and is at high risk of invasion in the U.S. Brown rot disease models will be developed from published works for use as a decision support aid for the three species depending on the host and region. Feedback from usability and outreach activities for M. fructicola and M. laxa will help with improvement of the model for use by first responders in new detections of the invasive M. fructigena. Cheatgrass or downy brome is perhaps the most destructive invasive weed in the semi-arid West. We will extend an existing phenology model for cheatgrass to assist pest management programs (see letters of support). We will test the use of soil moisture to increase predictive accuracy of the model, with supporting phenological data from collaborators at USGS and Montana State University. USGS Earth Resources Observation and Science center will provide satellite land-cover data of cheatgrass abundance and phenology to help calibrate and evaluate our models. All models will be implemented by extending the DDRP modeling platform at OSU servers, with outputs shared at least weekly with USA-NPN, who will develop and promote output products listed previously and described below.Objective 3: Engage stakeholders of DDRP products in the design and delivery of the forecasts; deliver and communicate model products in a range of user-friendly, readily accessible formats to enable wide adoption; and collect ground-based observations to validate forecastsOver the course of this project, we will seek feedback from end-users of DDRP products to iteratively improve product format and delivery. We will host: several workshops in each project year, a series of online training webinars, develop short training videos, conduct multiple software usability testing sessions, host two advisory groups, make use of email-based push notifications of model forecasts, and participate in regional and national invasive species in-person meetings to present results and seek feedback using formal and informal methods. USA-NPN will lead communications and engagement activities with the use of a bimonthly e-newsletter, usage of social media channels (Twitter, Facebook, etc.), and regular website updates. Additional promotion of DDRP products and project activities will involve the use of trade journals, the popular press, partner newsletters, and regular USA-NPN outlets. DDRP code and supporting documentation will be shared as open-source code and data using the GitHub repository, and directly with USDA PPQ S&T, who provide decision support to CAPS monitoring programs.Model validations and evaluations will be supported, in addition to published sources mentioned, by use of ground-based observations. This will build upon the Nature's Notebook and EDDMapS programs, plus other citizen science data collection efforts previously mentioned, and with scientific collaborators depending on the species. These data collection resources will be encouraged by communicating through trade journals, blogs, social media, state-level IPM programs, and our working/advisory groups.A graduate level hybrid in-person and online course will be taught each year at OSU, covering systems and population modeling methods for pest species using R.p { margin-bottom: 0.1in; line-height: 115%; background: transparent }a:link { so-language: zxx; text-decoration: underline }

Progress 04/15/22 to 04/14/23

Outputs
Target Audience:This is the entirety of the invasive species, agricultural biosecurity, and IPM communities, in general. In particular, decision makers and practitioners involved in the CAPS (Cooperative Agricultural Pest Survey) programs, state survey programs for invasive pests, and the general public who often serve as first responders and citizen scientists in assisting with data collection. Changes/Problems:- One of the key personnel for this project, Chris Hedstrom, left the OIPMC in Spring 2023. Chris was responsible for outreach activities that target stakeholders in the Pacific Northwest, including web developments, newsletter materials, course materials, industry articles, and webinars. These duties will be delegated to one of the two IPM Educators that were recently hired at the OIPMC. What opportunities for training and professional development has the project provided?- In addition to the modeling course described under objective (4) under accomplishments: - Assist in training 1 undergraduate student intern. Summer 2023. Training in phenological data analysis and model validation. Working with Japanese Beetle, an invasive pest of turf and ornamentals. - Taught IPM modeling concepts at several Pesticide Safety Education Program events. How have the results been disseminated to communities of interest?Via publications, websites, on-line models, trainings, oral and poster presentations, collaborations with several groups including the biosecurity community, extension and outreach events, popular press articles, email newsletters, and other activities described above. What do you plan to do during the next reporting period to accomplish the goals?We are making excellent progress towards achieving all objectives for this project, and plan to continue along the original timeline described in the proposal.

Impacts
What was accomplished under these goals? Objective (1) - Developed a daily time-step algorithm that estimates plant disease infection risk using near real-time daily temperature, relative humidity, and precipitation data, available in the PRISM database. This method was developed for a traditional "heat units during leaf wetness periods" type of infection risk model, that has been implemented for the DDRP model for boxwood blight. It can be readily adapted for brown rot (Monilinia spp.) for this NIFA project. - Developed initial methodologies to download and work with NASA Soil Moisture Active Passive (SMAP) soil moisture data, which will be instrumental in modeling oinvasive plants. SMAP data will be incorporated into DDRP for the cheatgrass model for this project. - Obtained agreement from the PRISM group to acquire daily high resolution (30 second = 800 meter) PRISM data, both past years (back to 2000) and for real-time acquisition, to use for DDRP models for this project. The data are being used for a high-resolution version of the DDRP model for boxwood blight, which serves as a prototype for developing a similar model for Monilinia (brown rot) species. Objective (2) - In the first year of this project, we refined and operationalized the DDRP model for emerald ash borer (EAB), Agrilis planipennis, including parameter optimization and validation with ground observations contributed by several partners. The manuscript describing this model evaluation and improvement (Barker et al. 2023) was accepted for publication by the journal "Frontiers in Insect Science", and is now in press. The code for the EAB model and DDRP platform is deposited at GitHub (https://github.com/bbarker505/ddrp_v2.git) and Zenodo (https://doi.org/10.5281/zenodo.7493142). - On March 31, 2023, the USA-NPN operationalized the new EAB model forecasts of adult emergence and egg hatch through the Pheno Forecast infrastructure, including maps available via OGC-compliant web services, the USA-NPN visualization tool and forecast landing pages. The forecast package includes complete metadata, and email notifications (currently to 362 subscribers) is available at http://usanpn.org/data/forecasts/EAB. The email notifications provide advanced warnings (3, 2, and 1-week) of when these events are predicted to occur in the area. Users can interact with forecasts using the Visualization Tool (https://data/usanpn.org/vis-tool). - USPest.org also hosts EAB DDRP forecasts for CONUS (https://uspest.org/CAPS) and for Oregon with an interactive version of the model (https://uspest.org/CAPS/EAB_OR/home.html). Oregon has been experiencing a new EAB outbreak since June 2022. - We operationalized a site-based version of this new EAB phenology model, with access to over 32,000 weather stations, at USPest.org (https://uspest.org/dd/model_app?spp=eab2). - We developed and operationalized a new phenology model for spotted lanternfly at USPest.org (https://uspest.org/dd/model_app?spp=slf), as a first step toward developing a new DDRP model for this species. Model documentation is at: https://uspest.org/wea/spotted_lanternfly_model.pdf. The climate suitability analysis is underway. - We continue to gather references and data sources to construct and validate the remaining models for this project. Objective (3) - Engaged over 40 managers, foresters, scientists, and volunteers in reviewing and providing feedback on USA NPN's forecast prototypes for EAB in Fall 2022. Of these, 65% indicated that they view forecasts during the winter to help plan future management activities, while 87% indicated that they view forecasts during the active season for real-time decision support. This feedback led us to optimize a forecast display in which phenological events are shown a full year in advance, but with sufficient temporal detail to support managers using the forecast during the active season. - Engaged volunteer scientists in collecting EAB observations through the USA-NPN's Pest Patrol Campaign and EDDMaps over entire project year. These data will be used to validate EAB forecasts in future project years. - Advertised the new forecasts for EAB via newsletter, social media, and trade journals: - Published article in City Trees, the Magazine of the Society of Municipal Arborists (Crimmins et al. 2023) - Contacted 362 subscribers of EAB forecasts to announce the release of the new forecasts and learning module on April 12, 2023 (https://conta.cc/3MVyh15) - Reported on the new forecasts in the Feb-Mar issue of USA-NPN's Connection newsletter (2,753 subscribers) on April 3, 2023 (https://conta.cc/3KO37st) - Reported on the new forecasts in the Spring issue of USA-NPN's Leaflet newsletter (929 subscribers) on May 1, 2023 (https://conta.cc/3IWS7b1) - Reported on the new forecasts in the Apr-May issue of the Connection newsletter on May 31, 2023 (https://conta.cc/43qt3kT) - Reported on the new EAB and SLF weather station-based models in the Oregon IPM News email newsletter, on Feb 1, 2023 and May 24, 2023 (https://agsci.oregonstate.edu/oipmc/outreach-and-events) - Met with APHIS PPQ Science & Technology SAFARIS modeling group in North Carolina in November 2022. Presented on the DDRP platform and EAB model, discussed opportunities for collaboration, and compared technological developments. - Developed learning module on EAB life history, collecting phenology observations and using the forecast (https://learning.usanpn.org; 57 have taken the course so far) Objective (4) - Instructed "Ecological Systems Modeling" 3-credit course, HORT 499/599X in Winter 2023. Key deliverable: training of students in developing and applying models, with a focus on applications for agricultural systems and biosecurity threats.

Publications

• Type: Journal Articles Status: Awaiting Publication Year Published: 2023 Citation: Barker, B. S., L. Coop, J. Duan, and T. Petrice. 2023. An integrative phenology and climatic suitability model for emerald ash borer. Frontiers in Insect Science, Section Invasive Insect Species. Special issue: Forest Insect Invasions  Risk Mapping Approaches and Applications. Accepted for Publication July 31, 2023 doi: 10.3389/finsc.2023.1239173
• Type: Journal Articles Status: Published Year Published: 2022 Citation: Barker, B. S., L. Coop, and C. Hong. 2022. Potential distribution of invasive boxwood blight pathogen (Calonectria pseudonaviculata) as predicted by process-based and correlative models. Biology. 11(6), 849. 32 pp. Special issue: Biological invasions: From Prevention and Management to Ecosystem Restoration. https://doi.org/10.3390/biology11060849
• Type: Book Chapters Status: Published Year Published: 2022 Citation: Bowers, J. H., Malayer, J. R., Mart�nez-L�pez B., LaForest, J., Bargeron, C., Neeley, A. D., Coop, L., Barker, B. S., Mastin, A. J.; Parnell, S., Cosse, A. A., McCluskey, B.J., Isard, S. C., and Russo, J. M. 2022. Surveillance for Early Detection of High-Consequence Pests and Pathogens. in: Tactical Sciences for Biosecurity of Animal and Plant Systems. K. F. Cardwell and K. L. Bailey, eds. IGI Global, Hershey, Pennsylvania, USA. 78pp.
• Type: Websites Status: Published Year Published: 2023 Citation: USA National Phenology Network. 2023. Emerald Ash Borer Pheno Forecast, USA National Phenology Network. Available at https://usanpn.org/data/forecasts/EAB accessed 07-26-2023.
• Type: Websites Status: Published Year Published: 2023 Citation: USA National Phenology Network. 2023. Emerald Ash Borer Phenology Learning Module, USA National Phenology Network. Available at: http://learning.usanpn.org/ accessed 07-26-2023
• Type: Websites Status: Published Year Published: 2023 Citation: Coop, L., and B. S. Barker. 2023. Version 2 of a degree-day/phenological model for emerald ash borer, online May 10, 2023. Available at: https://uspest.org/dd/model_app?spp=eab2
• Type: Websites Status: Published Year Published: 2022 Citation: Coop, L. and Barker, B.S. 2022. Emerald ash borer spatial model for Oregon  online mapping interface. Available at: https://uspest.org/CAPS/EAB_OR/home.html
• Type: Other Status: Published Year Published: 2023 Citation: Coop, L., and B. S. Barker. 2023. Emerald ash borer (Agrilus planipennis) phenology/degree-day and climate suitability model analysis. Feb 2023. Spreadsheet analysis available at: https://uspest.org/wea/emerald_ash_borer_model_V2.pdf.
• Type: Other Status: Published Year Published: 2023 Citation: Coop, L., and B. S. Barker. 2023. Spotted lanternfly (Lycorma delicatula) phenology/degree-day model analysis. June 2023. Spreadsheet analysis available at: https://uspest.org/wea/spotted_lanternfly_model.pdf.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Barker, B. S., and L. Coop. 2022. DDRP: phenology and climate suitability modeling to predict when and where invasive and IPM pests can arise. Oral presentation at the Oregon State Agency IPM Coordinating Committee Semiannual Meeting, Feb. 2, 2022. Online event. 13 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Barker, B.S, Coop, L., and Crimmins, T. 2022. DDRP: a modeling tool to guide decision making for pest surveillance and management. Poster presentationat the 10th International IPM Symposium. Mar 2, 2022. Denver, CO. Available at: https://ipmsymposium.org/2021/posters.html. 300 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Coop, L, S. Dorman, and J. Green. 2022. Decision support tools and data visualization. Oral presentation at the fourth annual Oregon IPM summit, Mar. 14, 2022 Corvallis, OR. ca. 25 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Rivedal, H., Barker, B. S., and I. Sandlin. 2022. Barriers for exports and predictive tools for invasive pests. Oral presentation at the 4th annual Oregon IPM Summit, Mar. 14, 2022. Corvallis, OR. ca. 8 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Barker, B. S., Coop, L., and T. Crimmins. 2022. DDRP: a modeling tool to forecast insect phenology and risk of establishment. Oral presentation at the Ecological Forecasting Initiative conference, May 23, 2022. Online event. Available at: https://uspest.org/ipm/Barker_EFI_talk.mp4.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Barker, B. S. 2022. Spatial modeling in R to help detect emerald ash borer, a new invader in the Pacific Northwest. Lightning talk at the 6th annual Cascadia R Conference, Sep. 17, 2022. Online event. ca. 75 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2022 Citation: Barker, B. S., and L. Coop. 2022. DDRP: real-time mapping of pest phenology and climate suitability. Oral presentation for the USDA APHIS PPQ Plant Pest Risk Analysis group, Nov. 18, 2022. Raleigh, NC. 10 attendees. Invited.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Barker, B. S., Coop, L., Rosemartin, A., and Crimmins, T. 2023. Updates and implementation of a spatialized phenology model for emerald ash borer. Oral presentation at the annual Pacific Northwest Insect Management Conference, Jan. 9, 2023. Portland, OR. ca. 40 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Barker, B. S. 2023. An introduction to using R for horticultural data analysis. Webinar for the American Society for Horticultural Science, Jan. 30, 2023. Online. 149 attendees. Invited.
• Type: Other Status: Published Year Published: 2023 Citation: Crimmins, T.M., E. E. Posthumus, A. Rosemartin, B. S. Barker and L. Coop. 2023. Enhanced forecasts of emerald ash borer activity. City Trees, July/Aug 2023 pp 12-13. Available at: https://read.dmtmag.com/i/1502619-july-august-2023/11?
• Type: Other Status: Published Year Published: 2023 Citation: Hedstrom, C., et al. 2023. What to do about emerald ash borer: Recommendations for tree protection in EAB-infested areas.OSU Extension Article https://extension.oregonstate.edu/forests/cutting-selling/what-do-about-emerald-ash-borer-recommendations-tree-protection-eab
• Type: Other Status: Published Year Published: 2022 Citation: Coop, L., F. Grevstad, B. S. Barker. 2022. User Guide for uspest.org/dd/dodmaps (a version of DDRP). Created for U.S. Dept. Of Defense and USDA APHIS PPQ CPHST & CAPS. 14 pp. Online at:
• Type: Other Status: Published Year Published: 2022 Citation: Barker, B. S., and Park, C. 2022. Tools for forecasting pests extends to annual weeds and biocontrol agents. Newsletter for the Western Society of Weed Science. Winter 2022, 5?6. Available at: https://wsweedscience.org/wp-content/uploads/WSWS-Newsletter-2022-Winter.pdf
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Barker, B. S., Dorman, S., and Rondon, S. 2023. Spatial risk modeling and decision support systems for IPM. [Symposium]. Annual conference of the Entomological Society of America Pacific Branch, Apr. 3, 2023, Seattle, WA. 35 attendees. Abstracts available online: https://esa.confex.com/esa/2023pb/meetingapp.cgi/Session/38793
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Coop, L. and B. S. Barker. 2023. Phenological mapping approaches for IPM decision support. Oral presentation at the Pacific Branch Entomological Society of America. Annual Meeting. Apr. 3, 2023. Seattle, WA. Regional. ca. 30 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Barker, B. S., L. Coop, A. Rosemartin, and T. Crimmins. 2023. Spatial forecast of phenology and climate suitability for emerald ash borer, Agrilus planipennis. Oral presentation at the annual Entomological Society of America Pacific Branch Meeting, Apr. 3, 2023. Seattle, WA. ca. 30 attendees.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Barker, B. S. 2023. Real-time forecasts of phenology and climate suitability for emerald ash borer. Webinar for the EAB University, Apr. 13, 2023. Online event. 17 attendees. Available at: https://youtu.be/GSAird76myM.
• Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2023 Citation: Barker, B. S., L. B. Coop, T. Crimmins, and A. Rosemartin. 2023. Real-time mapping of phenology and establishment risk for emerald ash borer. Oral presentation at the annual Ecological Society of America meeting, Aug. 10, 2023. Portland, OR.
• Type: Other Status: Published Year Published: 2023 Citation: Coop, L. 2023. Using Degree-days to Help Time Crop and Pest Activities. Pesticide Safety Education Webinar Series. Feb. 14, 2023. Online, Regional. 65 participants.
• Type: Other Status: Published Year Published: 2023 Citation: Barker, B. And L. Coop. 2023. Introduction to boxwood blight and infection model risk apps. Pesticide Safety Education Webinar Series. Jan. 18, 2023. Online, Regional. 223 participants.
• Type: Other Status: Other Year Published: 2022 Citation: Coop, L. and B. Barker. 2022. Boxwood blight infection risk app and climate suitability modeling. Oregon Boxwood Health Workshop. Oct. 20, 2022. Aurora, OR. 48 participants.