To assess the impacts of non-point source pollution on Ontarios wetlands I examined the landuse in the watershed, the water and sediment quality, and the aquatic vegetation in 22 wetlands. I characterized the primary contaminants that enter marshes in Ontario and relate their concentrations to the relative amounts and types of land use in their watershed. I measured levels of nutrients, suspended particulates and trace organics in water and sediment. Species richness and structural diversity of the vegetative community was used as an indicator of wetland health. I included a comparison of two techniques, immunoassays and gas-chromatography (GC) to measure trace organics (PAHs and metolachlor; Chapter 1). Comparison of results from both techniques indicated that immunoassays overestimated analyte concentration by approximately a third. I utilized the immunoassay results, along with selected water quality variables, to characterize contaminants entering these wetlands (Chapter 2). Watersheds containing greater than 95% agriculture contributed the highest suspended particulate, compared with those dominated by urban or forested land. Using multivariate statistics I identified important water and sediment variables that structured these wetlands to be: total phosphorus (TP), ammonia nitrogen (TAN), suspended solids (TSS), specific conductance (COND), sediment phosphorus CTPsed) and inorganic material (lnorgsed) in the sediment. Of these TP, COND and Inorgsed were negatively related to the submergent plant community, while TPsed was positively related. There was no relationship between water quality and the floating or emergent plants but the structural diversity of the plant community was negatively affected by poor water quality. The negative impact of developed land in the watershed on the health of the aquatic plant communities underscores the need to maintain natural areas to trap nutrients and sediments in runoff. / Thesis / Master of Science (MS)

The Green Swamp Preserve is a large geographic area that has sustained many changes since Europeans settled in Florida. There has been little published research on the impacts of anthropogenic activity on this system. This thesis research seeks to document more recent changes in the Green Swamp and to evaluate the effects of various human activities on the system. The study period is from 1985 to 2015. For this time period changes in land use and landcover were examined using neural network classifications. Changes in vegetation health were evaluated by examining Normalized Difference Vegetation Index (NDVI) and Green Vegetation Index differences. Field site visits were made to document current conditions at thirty sample locations within the study area. Changes in land use and landcover and vegetation health were evaluated in relation to anthropogenic activities such as proximity to pollution sources, conservation lands and restoration sites. Statistical analysis was conducted to determine if statistically significant clustering occurred in these changes and if present geographically weighted regressions were performed to determine if a significant spatial relationship existed between the clustering and the various human activities. WAP data showed an overall decline in wetland health at the assessment sites and showed a trend of lower wetland health at sites within 2 Km of pollution sources, specifically petroleum tank contamination sites and state roads. The statistically significant clustering identified in land use landcover changes from 1985 to 2015 were in relation to changes from field, forested and wetland landcover types to built environments. Spatial relationships were identified between the proximity of petroleum tank contamination sites, state roads and solid waste facilities and clustering of NDVI decreases from 1985 to 2015. NDVI increases in the study area from 1985 to 2015 also showed statistically significant clustering in relation to conservation lands and lands purchased by the Southwest Florida Water Management District for environmental protection. These preliminary findings suggest that human activities may have influenced changes in the health of the Green Swamp. Further, more extensive research is suggested to confirm these findings.

Wetlands are vital ecosystems providing essential services to both humans and the environment, yet they face threats from human activities leading to loss and disturbance. This study utilizes remote sensing (RS) methods, including object-based image analysis (OBIA), to map and assess wetland health in Kristianstad’s Vattenrike in the southernmost part of Sweden between 2015 and 2023. Objectives include exploring RS capabilities in detecting wetlands and changes, deriving wetland health indicators, and assessing classification accuracy. The study uses Sentinel-2 imagery, elevation data, and high-resolution aerial images to focus on wetlands along the river Helge å. Detection and classifications were based on Sentinel-2 imagery and elevation data, and the eCognition software was employed. The health assessment was based on the spectral indices Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (mNDWI). Validation was conducted through aerial photo interpretation. The derived classifications demonstrate acceptable accuracy levels and the analysis reveals relatively stable wetland conditions, with an increase in wetland area attributed to the construction of new wetlands. Changes in wetland composition, such as an increase in open meadows and swamp forests, were observed. However, an overall decline in NDVI values across the study area indicates potential degradation, attributed to factors like bare soil exposure and water presence. These findings provide insights into the local changes in wetland extent, composition, and health between the study years.