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COURSE INFO PROVIDER: SWSPCP Webinar
COURSE TITLE: Harnessing AI for Wetlands: Practical Tools and Use Cases for ChatGPT and Beyond

INSTRUCTORS David E. McWhorter, PWS

COURSE DESCRIPTION Abstract:
Artificial Intelligence (AI) tools are rapidly becoming part of the scientific workflow—but for many wetland professionals, their practical use can still feel abstract or out of reach. This webinar provides a grounded introduction to how large language models (LLMs), like ChatGPT, can assist wetland scientists across fieldwork, data processing, reporting, and communication.

Focusing on real-world use cases, attendees will learn how AI can generate field protocols, clean messy datasets, assist in GIS scripting, draft regulatory summaries, and support science communication. Through live demonstrations, the webinar will showcase how AI can speed up repetitive tasks, support early-stage analysis, and reduce time spent on formatting or documentation—while keeping scientists, not software, in the decision-making seat.

The session will also introduce core prompting techniques to improve how tools like ChatGPT respond to wetland-specific questions and workflows. Attendees will see how refining prompts can lead to more accurate and useful outputs, with examples tailored to monitoring data, species identification, and QA/QC documentation.

Important ethical and practical considerations will also be addressed, including data privacy, model accuracy, and regulatory boundaries. Participants will leave with practical examples, clear strategies for incorporating AI into their work, and an understanding of both the opportunities and limits of LLMs in wetland science.

Whether you're just curious or already experimenting with ChatGPT, this session will give wetland professionals applicable, field-tested ideas to work smarter—not harder—in the complex world of wetlands.

Speaker's Bio:
David E. McWhorter is the Data Quality and Analytics Manager for the CRMS and SWAMP programs in Coastal Louisiana. With over two decades of experience in wetland science, ecological monitoring, and environmental data systems, he blends deep field knowledge with advanced technical solutions to support large-scale restoration monitoring.

David is a certified Professional Wetland Scientist (PWS) and leads QA/QC efforts across hydrographic, vegetation, elevation, and water quality datasets. He has developed tools in R, Python, and Excel VBA to streamline data workflows and automation, and has contributed to peer-reviewed research on carbon fluxes and greenhouse gas dynamics in deltaic wetlands.

His recent work focuses on integrating artificial intelligence and machine learning into environmental workflows — using AI to assist with data cleaning, summarization, and regulatory reporting. He also plays a lead role in mentoring junior scientists and supporting innovation initiatives within Jacobs, where he helps guide citizen developers across the Americas.

David holds a B.S. in Biology with a minor in Computer Science from the University of Central Oklahoma and has completed extensive training in data analytics, statistics, and project management. His work bridges the gap between technology and coastal restoration science.

Course Duration: 60 minutes
Credit Points: 0.06

SYLLABUS/TOPICAL OUTLINE -Introduction & Background (5 min) -What Are Large Language Models (2–3 min) -Real-World Applications for Wetland Professionals (25 min) --Field Data Collection & Management --Data Cleaning & Analysis --Report Writing & Regulatory Support --Outreach & Training Tools -Prompting Techniques for Better Results (7–8 min) -Live Demonstration: AI in Action (10 min) -Q&A and Closing (10 min)

COURSE CONTACT

Jason T Tucker
6245 Dawes Lane, Cincinnati, OH 45230
jttucker14@gmail.com
P: 6145816402
F:

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