Wetlands provide ecosystem services critical to the well-being of human populations, yet they have undergone massive loss and degradation. Illinois and Indiana alone have lost 85-90% of their historical wetland extent, which could impact the region’s resilience to climatic events and stressors. In response, agencies are dedicating substantial resources to restoring wetlands and their ecological functions. However, maintaining high quality, resilient habitats in human-dominated landscapes is challenging. Current literature reports a wide range of response to restoration interventions. Gathering long-term, consistent data on restored and protected wetlands is key to advancing our understanding of the root causes of this variability. This project will identify remote sensing-based indicators of vegetation composition and ecological functions to facilitate the consistent and large-scale monitoring of Lake Michigan wetlands. As a result, the project will generate three outputs aligned with the strategic goals of the IISG: (1) a literature review, to be published in a peer-review journal, summarizing current knowledge on the relationships between remote sensing-based indicators and transformations in plant communities; (2) a detailed script and tutorial, to be made available to scholars and stakeholders, showing users how to derive indicators of wetland health and recovery from free remote sensing datasets; and (3) a case study in a subsample of wetlands to serve as a proof of concept for the larger proposal.   

During the given one-year research period, I plan to develop a data-driven model integrating the physical model of infrastructure vulnerable to hazard and artificial intelligence machine learning algorithms to offer precautions and suggestions to resist natural hazards and enhance infrastructure flood resilience for the southern Lake Michigan communities. The proposed research targets to provide coastal communities with on-time and accessible suggestions to resist flooding attacks, support coastal industrial development without interference, give organizations reasonable, efficient recommendations to minimize the flooding impact on infrastructure, and offer the government customized design advice for infrastructure in the southern Lake Michigan region. Most importantly, this research will call public attention to the resilience of coastal communities and infrastructure.

Our overall goal is to provide quantitative  descriptions of species characteristics that increase the probability of successful invasion.

To evaluate the effect of culture temperature on growth, survival, and body composition of largemouth bass.

The overarching objective of this proposed study is to advance a systems-level understanding of nutrient pollution dynamics in the Lake Michigan Basin. This will be achieved by integrating spatial analysis, nutrient surplus-export coupling, and scenario-based modeling to support targeted, climate-resilient watershed management strategies. Objective 1: Classify watershed typologies based on surplus–export relationships and identify nutrient pollution hotspots. Objective 2: Develop a conservation framework that integrates hotspot identification, factor analysis, and targeted interventions. Objective 3: Evaluate the effectiveness of management scenarios under projected climate and hydrologic conditions using modeling approaches.

• Develop a suite of candidate functional indicators to identify human impacts to Great Lakes wetlands and characterize the functional nature of these systems