@article{montgomery_walden-schreiner_saffer_jones_seliger_worm_tateosian_shukunobe_kumar_meentemeyer_2023, title={Forecasting global spread of invasive pests and pathogens through international trade}, volume={14}, ISSN={["2150-8925"]}, url={http://dx.doi.org/10.1002/ecs2.4740}, DOI={10.1002/ecs2.4740}, abstractNote={Abstract Non‐native plant pests and pathogens threaten biodiversity, ecosystem function, food security, and economic livelihoods. As new invasive populations establish, often as an unintended consequence of international trade, they can become additional sources of introductions, accelerating global spread through bridgehead effects. While the study of non‐native pest spread has used computational models to provide insights into drivers and dynamics of biological invasions and inform management, efforts have focused on local or regional scales and are challenged by complex transmission networks arising from bridgehead population establishment. This paper presents a flexible spatiotemporal stochastic network model called PoPS (Pest or Pathogen Spread) Global that couples international trade networks with core drivers of biological invasions—climate suitability, host availability, and propagule pressure—quantified through open, globally available databases to forecast the spread of non‐native plant pests. The modular design of the framework makes it adaptable for various pests capable of dispersing via human‐mediated pathways, supports proactive responses to emerging pests when limited data are available, and enables forecasts at different spatial and temporal resolutions. We demonstrate the framework using a case study of the invasive planthopper spotted lanternfly ( Lycorma delicatula ). The model was calibrated with historical, known spotted lanternfly introductions to identify potential bridgehead populations that may contribute to global spread. This global view of phytosanitary pandemics provides crucial information for anticipating biological invasions, quantifying transport pathways risk levels, and allocating resources to safeguard plant health, agriculture, and natural resources.}, number={12}, journal={ECOSPHERE}, author={Montgomery, Kellyn and Walden-Schreiner, Chelsey and Saffer, Ariel and Jones, Chris and Seliger, Benjamin J. and Worm, Thom and Tateosian, Laura and Shukunobe, Makiko and Kumar, Sunil and Meentemeyer, Ross K.}, year={2023}, month={Dec} }
 @article{tateosian_saffer_walden-schreiner_shukunobe_2023, title={Plant pest invasions, as seen through news and social media}, volume={100}, ISSN={["1873-7587"]}, DOI={10.1016/j.compenvurbsys.2022.101922}, abstractNote={Invasion by exotic pests into new geographic areas can cause major disturbances in forest and agricultural systems. Early response can greatly improve containment efforts, underscoring the importance of collecting up-to-date information about the locations where pest species are being observed. However, existing invasive species databases have limitations in both extent and rapidity. The spatial extent is limited by costs and there are delays between species establishment, official recording, and consolidation. Local online news outlets have the potential to provide supplemental spatial coverage worldwide and social media has the potential to provide direct observations and denser historical data for modeling. Gathering data from these online sources presents its own challenges and their potential contribution to historical tracking of pest invasions has not previously been tested. To this end, we examine the practical considerations for using three online aggregators, the Global Database of Events, Language and Tone (GDELT), Google News, and a commercial media listening platform, Brandwatch, to support pest biosurveillance. Using these tools, we investigate the presence and nature of cogent mentions of invasive species in these sources by conducting case studies of online news and Twitter excerpts regarding two invasive plant pests, Spotted Lanternfly and Tuta absoluta. Our results using past data demonstrate that online news and social media may provide valuable data streams to supplement official sources describing pest invasions.}, journal={COMPUTERS ENVIRONMENT AND URBAN SYSTEMS}, author={Tateosian, Laura G. and Saffer, Ariel and Walden-Schreiner, Chelsey and Shukunobe, Makiko}, year={2023}, month={Mar} }
 @article{tateosian_glatz_shukunobe_2020, title={Story-telling maps generated from semantic representations of events}, volume={39}, ISSN={["1362-3001"]}, DOI={10.1080/0144929X.2019.1569162}, abstractNote={ABSTRACT Narratives enable readers to assimilate disparate facts. Accompanying maps can make the narratives even more accessible. As work in computer science has begun to generate stories from low-level event/activity data, there is a need for systems that complement these tools to generate maps illustrating spatial components of these stories. While traditional maps display static spatial relationships, story maps need to not only dynamically display relationships based on the flow of the story but also display character perceptions and intentions. In this work, we study cartographic illustrations of historical battles to design a map generation system for reports produced from a multiplayer battle game log. We then create a story and ask viewers to describe mapped events and rate their own descriptions relative to intended interpretations. Some viewers received training prior to seeing the story, which was shown to be effective, though training may have been unnecessary for certain map types. Self-rating correlated highly with expert ratings, revealing an efficient proxy for expert analysis of map interpretability, a shortcut for determining if training is needed for story-telling maps or other novel visualisation techniques. The study's semantic questions and feedback solicitation demonstrate a process for identifying user-centric improvements to story-telling map design.}, number={4}, journal={BEHAVIOUR & INFORMATION TECHNOLOGY}, author={Tateosian, Laura and Glatz, Michelle and Shukunobe, Makiko}, year={2020}, month={Apr}, pages={391–413} }
 @article{tateosian_glatz_shukunobe_chopra_2017, title={GazeGIS: A Gaze-Based Reading and Dynamic Geographic Information System}, ISBN={["978-3-319-47023-8"]}, ISSN={["1612-3786"]}, DOI={10.1007/978-3-319-47024-5_8}, abstractNote={Location is an important component of a narrative. Mapped place names provide vital geographical, economic, historical, political, and cultural context for the text. Online sources such as news articles, travel logs, and blogs frequently refer to geographic locations, but often these are not mapped. When a map is provided, the reader is still responsible for matching references in the text with map positions. As they read a place name within the text, readers must locate its map position, then find their place again in the text to resume reading, and repeat this for each toponym. We propose a gaze-based reading and dynamic geographic information system (GazeGIS) which uses eye tracking and geoparsing to enable a more cohesive reading experience by dynamically mapping locations just as they are encountered within the text. We developed a prototype GazeGIS application and demonstrated its application to several narrative passages. We conducted a study in which participants read text passages using the system and evaluated their experience. We also explored an application for intelligence analysis and discuss how experts in this domain envision its use. Layman and intelligence expert evaluations indicate a positive reception for this new reading paradigm. This could change the way we read online news and e-books, the way school children study political science and geography, the way officers study military history, the way intelligence analysts consume reports, and the way we plan our next vacation.}, journal={EYE TRACKING AND VISUALIZATION: FOUNDATIONS, TECHNIQUES, AND APPLICATIONS, ETVIS 2015}, author={Tateosian, Laura G. and Glatz, Michelle and Shukunobe, Makiko and Chopra, Pankaj}, year={2017}, pages={129–147} }