Wetland vegetation response to record-high Lake Ontario water levels

Smith, Ian M.; Fiorino, Giuseppe E.; Grabas, Greg P.; Wilcox, Douglas A.

doi:10.1016/j.jglr.2020.10.013

Cited by 30 publications

(17 citation statements)

References 29 publications

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“…In accordance with the CWMP protocol, the transect 3 bearing shifted slightly to avoid sampling a shrub-dominated area. While the submergent zone extent decreased in 2016, emergent and wet meadow zones expanded and shifted farther inland following trends similar to those reported by Hartsock et al (2022) and Smith et al (2021). In contrast to 2011, all emergent zones along the transects exceeded 11 meters in 2016.…”

Section: Transects and Sampling Pointssupporting

confidence: 82%

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Discovery of European frogbit (Hydrocharis morus-ranae L.) in Oconto County, Wisconsin: A summary of physical and plant community changes at a Lake Michigan coastal marsh

Rutherford

Hartsock

Danz

2022

Preprint

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Located in Oconto County, Wisconsin, Oconto Marsh #2 is a Great Lakes Coastal Wetland Monitoring Program (CWMP) study site that borders the shoreline of Lake Michigan. Plant communities were characterized at Oconto Marsh #2 along three fixed transects in 2011, 2016, 2017 and 2021, a period when Lake Michigan water levels increased by two meters. Transects were placed to intersect with three vegetation zones: submergent, emergent, and wet meadow. Here, we highlight physical landscape changes and the vegetation composition changes that occurred from 2011 to 2021. From satellite imagery, we estimate the vegetated wetland area decreased by 50 percent. High energy wave action and ice scour penetrating farther inland are likely most responsible for causing these changes. Using multivariate ordination and PERMANOVA, we show plant composition in 2011 and 2021 was different from years 2016 and 2017. While invasive Phragmites australis was treated with herbicide in 2014 (herbicide treatment completed by non-CWMP groups), disturbance from progressively increasing water levels has facilitated considerable species turnover since monitoring began. Despite successful treatment of P. australis, the establishment of additional non-native species has caused site-wide mean coefficient of conservatism scores to decline from a calculated score of 4.2 in 2011 to 3.3 in 2021. Of critical importance, we discovered the highly invasive species European frogbit (EFB) (Hydrocharis morus-ranae L) near the research transects in 2021. This is the first documented occurrence of EFB in Wisconsin. The newly discovered EFB range spans 31 km along the general shoreline from Marinette to Oconto, WI.

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Section: Transects and Sampling Pointssupporting

confidence: 82%

“…The plant communities that form coastal wetland vegetation zones generally sort out based upon their water-depth preferences (Sculthorpe 1967, Spence 1982, Kozlowski 1984). Further, these communities are dynamic, and may shift from one location to another in response to natural water level uctuations (Smith et al 2021).…”

Section: Location and Climatementioning

confidence: 99%

Discovery of European frogbit (Hydrocharis morus-ranae L.) in Oconto County, Wisconsin: A summary of physical and plant community changes at a Lake Michigan coastal marsh

Rutherford

Hartsock

Danz

2022

Preprint

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“…Extreme water levels in the upper Great Lakes in 2017 resulted in increased flows into downstream Lake Ontario and elevated lake levels. Smith et al (2021), who found decreases in cover of Typha from 2009-2016 to 2017 across most elevations in 12 Lake Ontario wetlands, with some recovery occurring in 2018 but not to previous levels. This study was able to demonstrate the utility of airborne HSI, lidar, and true-color RGB imagery for the classification and monitoring of target wetland species and classes, specifically the dense and aggressive Typha community.…”

Section: Discussionmentioning

confidence: 99%

Classification ofTypha-dominated wetlands using airborne hyperspectral imagery along Lake Ontario, USA

Suir

Wilcox

Reif

2021

Aquatic Ecosystem Health &Amp; Management

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Shoreline wetlands along Lake Ontario are valuable, multi-functional resources that have historically provided large numbers of important ecosystem goods and services. However, alterations to the lake’s natural hydrologic regime have impacted traditional meadow marsh in the wetlands, resulting in competition and colonization by dense and aggressive Typha angustifolia and Typha x glauca (Cattails). The shift to a Typha-dominated landscape resulted in an array of negative impacts, including increased Typha density, substantial decreases in plant species richness and diversity, and altered habitat and changes in associated ecosystem services. Successful long-term adaptive management of these wetland resources requires timely and accurate monitoring. Historically, wetland landscapes have been surveyed and mapped using field-based surveys and/or photointerpretation. However, given their resource- and cost-intensive nature, these methods are often prohibitively time- and labor-consuming or geographically limited. Other remote sensing applications can provide more rapid and efficient assessments when evaluating wetland change trajectories or analyzing direct and indirect impacts across larger spatial and temporal scales. The primary goal of this study was to develop and describe methodology using U.S. Army Corps of Engineers National Coastal Mapping Program hyperspectral imagery, light detection and ranging data, and high-spatial resolution true-color imagery to provide updated wetland classifications for Lake Ontario coastal wetlands. This study used existing field-collected vegetation survey data (Great Lakes Coastal Wetland Monitoring Program), ancillary imagery, and existing classification information as training data for a supervised classification approach. These data were used along with a generalized wetland schema (classes based on physical and biological gradients: elevation, Typha, meadow marsh, mixed emergent, upland vegetation) to generate wetland classification data with Kappa values near 0.85. Ultimately, these data and methods provide helpful knowledge elements that will allow for more efficient inventorying and monitoring of Great Lake resources, forecasting of resource condition and stability, and adaptive management strategies.

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“…Recent extreme changes in the Great Lakes water levels (highest recorded lake levels in 2017 and 2019) are impacting coastal wetlands. Specifically, Smith et al [9] showed that extreme highwater levels led to a decrease in vegetation coverage, and that low-water levels increase the coverage of invasive wetland species such as Typha.…”

Section: Introductionmentioning

confidence: 99%

Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie

et al. 2022

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Ecosystems at coastal terrestrial–aquatic interfaces play a significant role in global biogeochemical cycles. In this study, we aimed to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region. We investigated the heterogeneity of coastal ecosystem structures as a function of along-shore distance and transverse distance, based on the spatial data layers, including topography, wetland vegetation cover, and the time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. Results showed that the topographic metrics (elevation and slope), soil texture, and plant productivity influence the spatial distribution of wetland land-covers (emergent and phragmites). These results highlight a natural organization along the transverse axis, where the elevation and the EVI increase further away from the coastline. In addition, the clustering analysis allowed us to identify regions with distinct environmental characteristics, as well as the ones that are more sensitive to interannual lake-level variations.

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Wetland vegetation response to record-high Lake Ontario water levels

Cited by 30 publications

References 29 publications

Discovery of European frogbit (Hydrocharis morus-ranae L.) in Oconto County, Wisconsin: A summary of physical and plant community changes at a Lake Michigan coastal marsh

Discovery of European frogbit (Hydrocharis morus-ranae L.) in Oconto County, Wisconsin: A summary of physical and plant community changes at a Lake Michigan coastal marsh

Classification ofTypha-dominated wetlands using airborne hyperspectral imagery along Lake Ontario, USA

Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie

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