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Irruptive or boom-and-bust population dynamics, also known as ‘outbreaks’, are an important phenomenon that has been noted in biological invasions at least since Charles Elton’s classic book was published in 1958. Community-level consequences of irruptive dynamics are poorly documented and invasive species provide excellent systems for their study. African Jewelfish (Rubricatochromis letourneuxi, “jewelfish”) are omnivores that demonstrate opportunistic carnivory, first reported in Florida in the 1960s and in Everglades National Park (ENP) in 2000. Twelve years after invasion in ENP, jewelfish underwent a 25-fold increase in density in one year. By 2016, jewelfish represented 25–50% of fish biomass. Using a 43-year fish community dataset at two sites (1978–2021), and a 25-year dataset of fish and invertebrate communities from the same drainage (1996–2021), with additional spatial coverage, we quantified differences in fish and invertebrate communities during different phases of invasion. During jewelfish boom, abundant, native cyprinodontiform fishes decreased in density and drove changes in community structure as measured by similarity of relativized abundance. Density of two species declined by > 70%, while four declined by 50–62%. Following the jewelfish bust, some species recovered to pre-boom densities while others did not. Diversity of recovery times produced altered community structure that lagged for at least four years after the jewelfish population declined. Community structure is an index of ecological functions such as resilience, productivity, and species interaction webs; therefore, these results demonstrate that irruptive population dynamics can alter ecological functions of ecosystems mediated by community structure for years following that population’s decline. 

Seagrasses are long-lived, clonal plants that can integrate fluctuations in environmental conditions over a range of temporal scales, from days to years, and can act as barometers of coastal change. There are many estimated seagrass traits and ecosystem parameters that have the potential to reflect ecosystem status, linking seagrass condition to natural and anthropogenic drivers of change. We identified five seagrass indicators and seven metrics that are suitable, affordable and frequently measured by 38 monitoring programs across the Gulf of Mexico (GoM). A specific set of ratings and assessment points were formulated for each measurable metric. We determined metric ratings (Acceptable, Concerning, Alarming) and validated assessment points using long-term monitoring data from Texas and Florida, coupled with existing literature and input from a panel of seagrass biologists. We reported scores using a blue-gray-orange (Acceptable-Concerning-Alarming) scale to summarize information in a format accessible to the public, resource managers, stakeholders, and policymakers. Seagrass percent cover, shoot allometry and species composition were sensitive indicators of large-scale climatic disturbances (droughts, hurricanes). Severe drought led to reductions in total seagrass cover and leaf length in Upper Laguna Madre, Texas, and Florida Bay; however, Syringodium filiforme was disproportionally affected in Texas while Thalassia testudinum beds responded strongly to drought impacts in Florida. Hurricanes Harvey (TX) and Irma (FL) also resulted in loss of seagrass cover and diminished leaf length in the Texas Coastal Bend and Florida Keys; both storms largely impacted T. testudinum and to a lesser extent, S. filiforme. Many of the metrics within these affected bays and basins received either a “Concerning” or “Alarming” rating, driven by the impacts of these disturbances. Our proposed indicators serve as a tool to evaluate seagrass condition at the bay or basin scale. Moreover, the indicators, metrics, and assessment points are amenable to large-scale evaluations of ecosystem condition because they are economically feasible. This framework may provide the foundation for a comprehensive assessment of seagrass status and trends across the entire GoM. 

Over the last century, direct human modification has been a major driver of coastal wetland degradation, resulting in widespread losses of wetland vegetation and a transition to open water. High-resolution satellite imagery is widely available for monitoring changes in present-day wetlands; however, understanding the rates of wetland vegetation loss over the last century depends on the use of historical panchromatic aerial photographs. In this study, we compared manual image thresholding and an automated machine learning (ML) method in detecting wetland vegetation and open water from historical panchromatic photographs in the Florida Everglades, a subtropical wetland landscape. We compared the same classes delineated in the historical photographs to 2012 multispectral satellite imagery and assessed the accuracy of detecting vegetation loss over a 72 year timescale (1940 to 2012) for a range of minimum mapping units (MMUs). Overall, classification accuracies were >95% across the historical photographs and satellite imagery, regardless of the classification method and MMUs. We detected a 2.3–2.7 ha increase in open water pixels across all change maps (overall accuracies > 95%). Our analysis demonstrated that ML classification methods can be used to delineate wetland vegetation from open water in low-quality, panchromatic aerial photographs and that a combination of images with different resolutions is compatible with change detection. The study also highlights how evaluating a range of MMUs can identify the effect of scale on detection accuracy and change class estimates as well as in determining the most relevant scale of analysis for the process of interest. 

Planktonic microbial communities mediate many vital biogeochemical processes in wetland ecosystems, yet compared to other aquatic ecosystems, like oceans, lakes, rivers or estuaries, they remain relatively underexplored. Our study site, the Florida Everglades (USA)—a vast iconic wetland consisting of a slow-moving system of shallow rivers connecting freshwater marshes with coastal mangrove forests and seagrass meadows—is a highly threatened model ecosystem for studying salinity and nutrient gradients, as well as the effects of sea level rise and saltwater intrusion. This study provides the first high-resolution phylogenetic profiles of planktonic bacterial and eukaryotic microbial communities (using 16S and 18S rRNA gene amplicons) together with nutrient concentrations and environmental parameters at 14 sites along two transects covering two distinctly different drainages: the peat-based Shark River Slough (SRS) and marl-based Taylor Slough/Panhandle (TS/Ph). Both bacterial as well as eukaryotic community structures varied significantly along the salinity gradient. Although freshwater communities were relatively similar in both transects, bacterioplankton community composition at the ecotone (where freshwater and marine water mix) differed significantly. The most abundant taxa in the freshwater marshes include heterotrophic Polynucleobacter sp. and potentially phagotrophic cryptomonads of the genus Chilomonas, both of which could be key players in the transfer of detritus-based biomass to higher trophic levels. 

Pink shrimp (Farfantepenaeus duorarum) are an economically important species in Biscayne Bay, FL, and support both food and bait commercial fisheries. Pink shrimp are also an important food resource for higher trophic level finfish species. This includes those fishes that support Florida’s iconic and highly valued recreational flats fisheries—which have experienced a severe decline in recent decades and may be impacted by the pink shrimp fisheries. Despite their economic and ecological importance, few studies have evaluated the long-term trends in Biscayne Bay’s pink shrimp fisheries. In this study, we evaluated over 30 years (1987–2020) of fisheries-dependent and economic data on the pink shrimp bait and food fisheries in Biscayne Bay with segmented regression to identify trends and potential breakpoints. We also evaluate trends in Biscayne Bay bonefish (Albula vulpes) over 25 years (1993–2018), based on recreational angler interview data, and assess potential interactions with the shrimp fisheries. We found that landings, value, effort, and participation (number of vessels and dealers) in both Biscayne Bay pink shrimp fisheries have exhibited declines from peaks in the late 1990s. No significant trends were detected in annual bonefish catch or catch per unit effort (catch/trip), but fishing effort declined over the time series. We did not find a significant relationship between annual bonefish catch per unit effort and commercial shrimp fishing landings or effort, suggesting that the pink shrimp fisheries are not a primary factor contributing to declines in the Biscayne Bay bonefish fishery. 

Coastal wetlands are globally important stores of carbon (C). However, accelerated sea-level rise (SLR), increased saltwater intrusion, and modified freshwater discharge can contribute to the collapse of peat marshes, converting coastal peatlands into open water. Applying results from multiple experiments from sawgrass (Cladium jamaicense)-dominated freshwater and brackish water marshes in the Florida Coastal Everglades, we developed a system-level mechanistic peat elevation model (EvPEM). We applied the model to simulate net ecosystem C balance (NECB) and peat elevation in response to elevated salinity under inundation and drought exposure. Using a mass C balance approach, we estimated net gain in C and corresponding export of aquatic fluxes ( ) in the freshwater marsh under ambient conditions (NECB = 1119 ± 229 gC m−2 year−1; FAQ = 317 ± 186 gC m−2 year−1). In contrast, the brackish water marsh exhibited substantial peat loss and aquatic C export with ambient (NECB = −366 ± 15 gC m−2 year−1; FAQ = 311 ± 30 gC m−2 year−1) and elevated salinity (NECB = −594 ± 94 gC m−2 year−1; FAQ = 729 ± 142 gC m−2 year−1) under extended exposed conditions. Further, mass balance suggests a considerable decline in soil C and corresponding elevation loss with elevated salinity and seasonal dry-down. Applying EvPEM, we developed critical marsh net primary productivity (NPP) thresholds as a function of salinity to simulate accumulating, steady-state, and collapsing peat elevations. The optimization showed that ~150–1070 gC m−2 year−1 NPP could support a stable peat elevation (elevation change ≈ SLR), with the corresponding salinity ranging from 1 to 20 ppt under increasing inundation levels. The C budgeting and modeling illustrate the impacts of saltwater intrusion, inundation, and seasonal dry-down and reduce uncertainties in understanding the fate of coastal peat wetlands with SLR and freshwater restoration. The modeling results provide management targets for hydrologic restoration based on the ecological conditions needed to reduce the vulnerability of the Everglades' peat marshes to collapse. The approach can be extended to other coastal peatlands to quantify C loss and improve understanding of the influence of the biological controls on wetland C storage changes for coastal management.