GC053
GeoAI for Ecosystem Services and Biodiversity: Innovations in Monitoring, Modeling, and Integration
Session ID#: 251945
Session Description:
Human health and well-being are tied to ecosystem services—from food and water security to climate regulation and cultural benefits. In response to global initiatives such as UNEP TEEB, IPBES, the SDGs, and the 2050 Vision for Biodiversity, there is a growing need for integrated, data-driven assessments that make nature’s benefits more visible. This session invites interdisciplinary contributions that leverage Geospatial Artificial Intelligence (GeoAI) for advancing biodiversity and ecosystem services research. We welcome studies on: (1) applications of GeoAI to quantify the supply, demand, and flows of ecosystem services using multimodal data sources, including but not limited to remote sensing, citizen science, mobile, and other crowdsourced data; (2) advancements in GeoAI methods (e.g., multimodal learning, foundation models, knowledge-informed machine learning); (3) model-data integration to evaluate and forecast spatio-temporal dynamics and interactions among multiple ecosystem services and biodiversity across scales; and (4) interpretation, quantification, and communication of uncertainties in GeoAI model predictions.
Co-Sponsor(s):
Index Terms:
0439 Ecosystems, structure and dynamics [BIOGEOSCIENCES]
1640 Remote sensing [GLOBAL CHANGE]
1926 Geospatial [INFORMATICS]
1942 Machine learning [INFORMATICS]
Primary Convener: Chang Zhao, University of Florida, Agronomy Department, Gainesville, United States
Conveners: Nikolaos Tziolas, University of Florida, Department of Soil, Water, and Ecosystem Sciences, Immokalee, United States, Jiangxiao Qiu, University of Florida, School of Forest, Fisheries, and Geomatics Sciences, Gainesville, United States and Corey Callaghan, University of Florida, Department of Wildlife Ecology and Conservation, Gainesville, United States
Student/Early Career Convener: Hao-Yu Liao, University of Florida, Agronomy Department, Gainesville, United States
Do forest management strategies in the U.S. optimize ecosystem service supply? (1868495)
Hazhir Karimi1, Christina L Staudhammer2, Matthew D Therrell1, William Kleindl3, Leah Mungai1, Amobichukwu Amanambu1 and C. Nathan Jones4, (1)University of Alabama, Department of Geography and the Environment, Tuscaloosa, United States, (2)University of Alabama, Department of Biology, Tuscaloosa, United States, (3)Montana State University, Land Resources and Environmental Sciences, Bozeman, United States, (4)University of Alabama, Biological Sciences, Tuscaloosa, Alabama, United States
Fire and Recreation in the U.S. West: Modeling Impacts of Wildfire and Prescribed Fire on Non-Material Contributions of Nature (1873151)
Kyle Manley1, Spencer Wood2, Jennifer Balch3, Cody Evers4, Ashley Cale5, Holly Nowell6, Anna LoPresti7, Tyler McIntosh8, Laura E Dee7 and Katherine Siegel9, (1)Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States, (2)University of Washington Seattle Campus, Seattle, United States, (3)University of Colorado Boulder, CIRES, ESIIL, Boulder, United States, (4)Portland State University, Portland, United States, (5)University of Nevada Reno, Natural Resources and Environmental Science, Reno, United States, (6)Tall Timbers, Tallahassee, United States, (7)University of Colorado Boulder, Ecology & Evolutionary Biology, Boulder, United States, (8)University of Colorado Boulder, CIRES, Earth Lab, Boulder, United States, (9)Cooperative Institute for Research in Environmental Sciences, Boulder, United States
Advancing Scalable Biodiversity Monitoring with Partnerships and Edge Computing: NASA and California’s 30x30 Mission (1880076)
Keiko Nomura, NASA Ames Research Center, Moffett Field, CA, United States, Ian G Brosnan, NASA Ames Research Center, Earth Science Division, Moffett Field, CA, United States, Gary Bucciarelli, University of California Davis, Department of Wildlife, Fish, and Conservation Biology, Davis, United States, Collin A Bode, NCED UC Berkeley, San Francisco, CA, United States and Zhongqi Miao, Microsoft, Seattle, United States
Machine Learning Estimation of Soil Microbial Diversity Using Remote Sensing Data (1896442)
Samuel Aregbesola, University of Florida, Soil, Water, and Ecosystems Sciences, Immokalee, United States and Nikolaos Tziolas, University of Florida, Department of Soil, Water, and Ecosystem Sciences, Immokalee, United States
MODELING FUTURE PLANT SPECIES OCCURRENCE USING MACHINE LEARNING TRAINED ON PALEO-CLIMATE TRENDS, eDNA, AND POLLEN DATA (1938482)
DongHun Lee, Myongji University, Department of Environmental Engineering and Energy, Yongin-si, South Korea, Hyo-Jong Song, Myongji University, Dept. of Environmental Engineering and Energy, Seoul, South Korea, Jong-Yeon Park, Jeonbuk National University, Department of Environment and Energy, Department of Earth and Environmental Sciences, Jeonju, South Korea and Chae-Eun Lim, National Institute of Biological Resources, Climate Change and Environmental Biology research Division, Incheon, South Korea
SAV Detection Across Diverse Aquatic Systems Using Low-Cost Sonar and AI Image Segmentation (1962887)
Linus Soong1, Cameron Bodine2, Kayla Clauson3, Carter DuVal4, Stephanie Dohner5 and Arthur C Trembanis2, (1)Binghamton University, Binghamton, NY, United States, (2)University of Delaware, School of Marine Science and Policy, Newark, United States, (3)Delaware Department of Natural Resources and Environmental Control, Division of Watershed Stewardship, Dover, United States, (4)National Research Council Postdoctoral Fellow, Stennis Space Center, MS, United States, (5)Naval Research Lab Stennis Space Center, Ocean Sciences Division, Stennis Space Center, United States
Monitoring Forest Loss and Biodiversity in the Context of Large-Scale Land Acquisitions in Ethiopia: Integrating Remote Sensing, Ecological Field Data, and Household Perspectives (1976328)
Audrey Smith1, Jane Southworth1, Masoukur Rahaman1 and Carly Muir2, (1)University of Florida, Department of Geography, Gainesville, United States, (2)Virginia Commonwealth University, Center for Environmental Studies, Richmond, United States
FoundationSoil: A GeoAI Framework for Mapping Soil Organic Carbon Stocks Using Foundation Models and Explainable Machine Learning (1978815)
Jiayi Song, University of Florida, School of Natural Resources and Environment, Gainesville, United States, Chang Zhao, University of Florida, Agronomy Department, Gainesville, United States and Wei Shao, University of Florida, Department of Medicine, Gainesville, United States; University of Florida, Department of Electrical and Computer Engineering, Gainesville, United States
Mapping Cultural Ecosystem Service Flows from Crowdsourced Imagery: A Zero-Shot Learning Approach with the Vision–Language Model CLIP (1981246)
Hao-Yu Liao1, Chang Zhao1, Caglar Koylu2, Haojie Cao3, Jiangxiao Qiu4, Corey Callaghan5, Jiayi Song3 and Wei Shao6, (1)University of Florida, Agronomy Department, Gainesville, United States, (2)University of Iowa, School of Earth, Environment, and Sustainability, Iowa City, United States, (3)University of Florida, School of Natural Resources and Environment, Gainesville, United States, (4)University of Florida, School of Forest, Fisheries, and Geomatics Sciences, Gainesville, United States, (5)University of Florida, Department of Wildlife Ecology and Conservation, Gainesville, United States, (6)University of Florida, Department of Medicine, Gainesville, United States
Toward 30x30: How Effective Is Egypt’s Protected Area Coverage from a GeoAI Perspective? (1999817)
Heba Bedair, Tanta University, Faculty of Science, Botany Department, Tanta, Egypt; University of Wisconsin-Madison, Department of Forest and Wildlife Ecology, Madison, United States and Volker Radeloff, University of Wisconsin Madison, Department of Forest and Wildlife Ecology, Madison, United States
Filling the Gaps: Expert-Informed Multimodal Species Distribution Modeling for Data-Sparse Regions (2001919)
Elena Sierra1,2, Levente Klein2, Timm Haucke1, Sara M. Beery1 and Campbell Watson2, (1)Massachusetts Institute of Technology, Cambridge, United States, (2)IBM Research USA, Yorktown Heights, United States
