Browsing by Author "White, John R."
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Item Open Access Emerging resilience metrics in an intensely managed ecological system(Elsevier, 2024-01-05) Toumasis, Nikolaos; Simms, Daniel; Rust, Will; Harris, Jim A.; White, John R.; Zawadzka, Joanna; Corstanje, RonThere is growing interest in understanding resilience of ecosystems because of the potential of abrupt and possibly irreversible shifts between alternative ecosystem states. Tipping points are observed in systems with strong positive feedback, providing early warning signals of potential instability. These points can be detected through metrics like critical slowing down (CSD), such as increased recovery time, variance, and autocorrelation. These indicators have been tested in laboratory experiments and field settings, ignoring trait changes. Here we present a long-term temporal analysis of several large, intensely monitored constructed wetlands, the Everglades Stormwater Treatment Areas (STAs), in which sudden changes in plant community composition have been observed. Using wavelet analysis, significant increases and decreases of variance properties (long-term flow data, water quality and nutrient TP loads) across these systems can indicate when and which STAs are less resilient to perturbations. In this study, continuous wavelet transform (CWT) was used to determine the periodicity of any cyclical activity in the data and to determine changes in autocorrelation and variance as measures of CSD. The change detection methods were used to find significant changes in variations and correlations across the time series. By employing these techniques, we were able to spot substantial shifts in model-observed wavelet correlation and model residual wavelet variance and thereby identify where these systems exhibit CSD. Although our analysis is limited to historical data, the proposed approach has practical value in that it identifies STAs that may be vulnerable to perturbation. The study also presents one of the few studies in which CSD is observed in practice rather than modelled in theory.Item Open Access Spatial and temporal changes to a hydrologically-reconnected coastal wetland: implications for restoration(Elsevier, 2020-03-23) Spera, Alina C.; White, John R.; Corstanje, RonaldMississippi River Delta wetlands were isolated from river influence due to levee construction beginning in the early 1900's. Surface water diversions were primarily designed to manage salinity and maintain marsh vegetation by reintroducing Mississippi River water and nutrients into adjacent wetlands. Phosphorus (P) is a major limiting nutrient that can control productivity, but in excess can contribute to wetland eutrophic conditions and water quality degradation. Most wetland soil characterization assessments consider soil total P, however, this parameter alone cannot describe P bioavailability due to differences in organic and inorganic forms. A soil characterization of the Davis Pond diversion was done in 2007, before full-scale operation began, and in 2018 after 11 years of river loading. The top 10 cm of soil from 140 stations each year were analyzed for physiochemical properties and both organic and inorganic P forms. Mineral content is used to delineate areas of river diversion influence and compare P stocks between hydrologically isolated marsh areas and where effective river diversion reconnection took place. The river diversion resulted in a nearly 100% increase in soil mineral content and 58% increase in bulk density. The dominant source of soil P has changed from organic P to inorganic P in 29% of the wetland area, significantly associated with mineral content of the soil. Inorganic P stocks in diversion influenced areas are 9 times higher than those which remained isolated from riverine materials. The study demonstrates that long-term addition of mineral sediments and inorganic P did not lead to deleterious effects in the wetland soil. This is the first study in the Mississippi River delta to spatially track river reconnection driven wetland P dynamics and can provide valuable information for predictive models for sediment diversions for coastal restoration.