Indian River Lagoon: An Environmental History by Nathaniel Osborn

Evidence of sewage-driven eutrophication and harmful algal blooms in Florida's Indian River Lagoon

Nutrient over-enrichment and light limitation of seagrass communities in the Indian River Lagoon, an urbanized subtropical estuary

This paper describes the results of 10 years of water quality monitoring in the Indian River Lagoon Florida, with special emphasis on the relationships between trends in climatic conditions and the distribution, composition, and abundance of the phytoplankton community. The Indian River Lagoon, which spans 220 km of Florida’s east coast, is a region of particular concern because of the rapid rate of human development throughout the region and the hydrologically restricted character of the lagoon, which heightens the potential for algal bloom. Water sampling was carried out on a monthly to twice-monthly basis at six sites located in the northern and central lagoon. The 10-year study included both extended periods of below and above average rainfall. A number of ecologically distinct regions exist within the lagoon, which differ considerably in water exchange properties and watershed inputs. The northern lagoon is characterized by longer water residence times, lower phosphorus concentrations, higher nitrogen concentrations, and more stable salinity conditions than the central lagoon. Mean phytoplankton biovolumes were substantially higher at the sites in the northern lagoon than at the sites in the central lagoon, and algal blooms were more common and intense in the former region. Inter-annual patterns of phytoplankton biovolume were also different in the northern and central lagoon. In the northern lagoon, phytoplankton biovolumes were lowest during the drought period, from the autumn of 1998 to the spring of 2001. By contrast, algal bloom events in the central lagoon were not only less frequent but were not tied to periods of high rainfall. The most widespread and common bloom formers were the potentially toxic dinoflagellate Pyrodinium bahamense var. bahamense and two centric diatoms, Dactyliosolen fragilissimus and Cerataulina pelagica. Many of the biovolume peaks observed over the study period were attributable to these three species. The results of time series modeling of phytoplankton dynamics further highlighted the disparities between the two regions of the lagoon in terms of the suite of parameters that best predict the observed trends in the biomass of phytoplankton. Overall, the outcome of this initial modeling effort in the Indian River Lagoon suggests that time series approaches can help define the factors that influence phytoplankton dynamics.

The Indian River Lagoon Observatory (IRLO) is investigating ecological relationships in the Indian River Lagoon (IRL) and how they are impacted by natural and human-induced stressors. An important IRLO component is a network of advanced observing stations: the Indian River Lagoon Observatory Network of Environmental Sensors (IRLON). IRLON has 10 sites in the IRL and St. Lucie Estuary (SLE) to provide real-time, high-accuracy, and high-resolution water quality and weather data through an interactive website. This network enables researchers to follow environmental changes in the IRL, assist resource and planning managers to make informed decisions, model and correlate environmental data to biological, chemical and physical phenomena, and contribute to education and public outreach on the lagoon. Here we contrast two years of water quality conditions in the IRL and SLE. 2016 was a very “wet” year, including nine months of freshwater releases from Lake Okeechobee, which resulted in cyanobacteria blooms, and the nearby passage of Hurricane Matthew, which caused much shorter-term impacts in water quality. 2017 was a “dry” year, a significant drought early in the year, and major water quality parameters were substantially different than in 2016, until the nearby passage of Hurricane Irma. These high-frequency, continuous observatory data enable better quantification and modeling of relationships between environmental factors and biological processes in estuaries with tremendous climate-related interannual variability. This technology enables scientists, managers, educators, students, and the public to directly observe both long-term ecosystem changes and those driven by events, such as freshwater discharges, droughts, storms, and algal blooms.

Dynamics of microcystins and saxitoxin in the Indian River Lagoon, Florida

Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses

The Indian River Lagoon (IRL) on Florida’s east-central coast is a highly eutrophic, urbanized estuary where, beginning in 2011, multiple harmful phytoplankton blooms were followed by catastrophic seagrass losses. Since then, in many locations where seagrass was lost, the rhizophytic green macroalga Caulerpa prolifera has become the dominant benthic cover. Although the habitat value of C. prolifera compared to the seagrass Halodule wrightii was assessed in the IRL during the late 1980s, there is no information regarding its current habitat value following the catastrophic losses of seagrass. Therefore, the habitat function of C. prolifera in the IRL was assessed during a period of very low seagrass cover by quantitively sampling epifauna inhabiting this macroalga. The benthic habitat cover and faunal composition of four C. prolifera sites in the IRL were determined between 2020–2021. Benthic cover varied by site and event with variable % cover of C. prolifera overall. The faunal composition of C. prolifera was similar to what was previously observed for H. wrightii in the IRL, however faunal densities were significantly lower than historic estimates, which is critical information for resource managers. Incidentally sampled red drift macroalgae supported epifaunal species similar to C. prolifera also demonstrating its current habitat value in the IRL. Thus, these macroalgal habitats may be serving as refugia for estuarine fauna in the relative absence of seagrasses, however faunal densities may have declined from historic levels. These findings may be useful to other locations experiencing catastrophic seagrass losses combined with large-scale macroalgal blooms.

The Indian River Lagoon (IRL), a 156-mile-long estuary located on the eastern coast of Florida, experiences phytoplankton bloom events due to increased seasonal temperatures coupled with anthropogenic impacts. This study aimed to gather data on the toxicity to human cells and to identify secondary metabolites found in water samples collected in the IRL. Water samples from 20 sites of the IRL were collected during the wet and dry seasons over a three-year period. A panel of cell lines was used to test cytotoxicity. Hemagglutination, hemolysis, and inhibition of protein phosphatase 2A (PP2A) were also measured. Cytotoxic blooms were seen both in the south (Microcystis) and the north (Pyrodinium) of the IRL. Each toxin induced a consistent pattern of cytotoxicity in the panel of human cell lines assayed. During blooms, cytotoxicity due to a single type of toxin is obvious from this pattern. In the absence of blooms, the cytotoxicity seen reflected either a mixture of toxins or it was caused by an unidentified toxin. These observations suggest that other toxins with the potential to be harmful to human health may be present in the IRL. Moreover, the presence of toxins in the IRL is not always associated with blooms of known toxin-producing organisms.

Coastal eutrophication and freshwater inputs drive acidification in the Indian River Lagoon, Florida.

Eutrophication leads to food web enrichment and a lack of connectivity in a highly impacted urban lagoon

Seagrasses have been considered one of the most critical marine habitat types of coastal and estuarine ecosystems such as the Indian River Lagoon. They are an important part of biological productivity, nutrient cycling, habitat stabilization and species diversity and are the primary focus of restoration efforts in the Indian River Lagoon. The areal extent of seagrasses has declined within segments of the lagoon over the years. Light availability to seagrasses is a major criterion limiting their distribution. Decreased water clarity and resulting reduced light penetration have been cited as the major factors responsible for the decline in seagrasses in the lagoon. Hence, light is a critical factor for the survival of seagrass species. Light attenuation coefficient is an important parameter that indicates the light attenuated by the water column and can therefore be used as an indicator of seagrass vigor. A number of region-specific linear light attenuation models have been proposed in the literature. Though, in practice, linear light attenuation models have been commonly used, there is need for a flexible and robust model that incorporates the non-linearities present in coastal and estuarine environments. This paper presents a neural network based model to estimate light attenuation coefficient from water quality parameters and thereby indirectly monitor seagrass population in the Indian River Lagoon. The proposed neural network models were compared with linear regression models, step-wise linear regression models, model trees and support vector machines. The neural network models performed fairly better compared to the other models considered.

During the spring of 2011 an unprecedented “Super” algal bloom formed in the Indian River Lagoon (IRL), with Chlorophyll a (Chl a) concentrations over eight times the historical mean in some areas and lasted for seven months across the IRL. The European Space Agency’s MEdium Resolution Imaging Spectrometer (MERIS) platform provided multispectral data at 665 and 708 nm, which was used to quantify the phytoplankton Chl a by fluorescence while minimizing the effects of other water column constituents. The three objectives were to: (1) calibrate and validate two Chl a algorithms using all available MERIS data of the IRL from 2002 to 2012; (2) determine the accuracy of the algorithms estimation of Chl a before, during, and after the 2011 super bloom; and (3) map the 2011 algal bloom using the Chl a algorithm that was proven to be effective in other similar estuaries. The chosen algorithm, Normalized Difference Chlorophyll Index (NDCI), was positively correlated with the in-situ measurements, with an R2 value of 0.798. While there was a significant (62.9 ± 25%) underestimation of Chl a using MERIS NDCI, the underestimation appears to be consistent across the data and mostly in the estimations of lower concentrations, suggesting that a qualitative or ratio analysis is still valid. Analysis of the application of the NDCI processed MERIS data provided additional insights that the in-situ measurements were unable to record. The time series MERIS Chl a maps along with in-situ water quality monitoring data depicted that the 2011 IRL bloom started after a heavy rainfall in March 2011 and peaked in October 2011 after a decrease in temperature. The bloom collapse also coincided with heavy rainfall and rapidly decreasing temperatures and salinity through October to November 2011.

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 569:55-75 (2017) - DOI: https://doi.org/10.3354/meps12102 Phytoplankton biomass in a subtropical estuary: drivers, blooms, and ecological functions assessed over space and time using structural equation modeling C. Edward Proffitt* Department of Life Sciences, Texas A&M University - Corpus Christi, Corpus Christi, TX 78412, USA *Corresponding author: ed.proffitt@tamucc.edu ABSTRACT: The Indian River Lagoon (IRL Florida, USA) estuary may be in transition from a benthic productivity state to a phytoplankton-based state because of nutrient inputs, phytoplankton blooms, and light penetration. Variation over both spatial and temporal dimensions reflects a complex ecological topology in the IRL. Understanding features such as phytoplankton blooms and subsequent effects on light penetration, dissolved oxygen, and benthic systems is challenging because of the underlying complexity. Analysis by structural equation modeling can test multivariate hypotheses involving the web of pathways linking biotic and environmental variables. A complex structural equation model composed of linkages among chlorophyll, nutrients, salinity, light penetration, dissolved oxygen (DO), etc. explained phytoplankton biomass (chl a, R2 = 0.46) and relative abundance (chl b and c) and ecological functions (light penetration, R2 = 0.60; DO, R2 = 0.42) across the IRL and over the >20 yr of monitoring data. Results indicate that IRL experiences nitrogen and phosphorus co-limitation of phytoplankton, and that changes in plankton biomass influence ecological functions of DO and light penetration. Partitioning the IRL into regions improved the model fit to observations and showed that different regions of the IRL had different drivers for phytoplankton biomass. Comparing 3 yr groups of data for long and short water residence time regions showed that phytoplankton blooms in the 2010-2012 period (including the ‘superbloom’) were driven primarily by nitrogen and less by phosphorus and that this was associated in part by decomposing phytoplankton producing high concentrations of phosphorus during this period, leading to limitation by nitrogen. KEY WORDS: Phytoplankton · Chlorophyll a · Structural equation modeling · Nutrient · Salinity · Temperature · Indian River Lagoon · Florida Full text in pdf format Supplementary material PreviousNextCite this article as: Proffitt CE (2017) Phytoplankton biomass in a subtropical estuary: drivers, blooms, and ecological functions assessed over space and time using structural equation modeling. Mar Ecol Prog Ser 569:55-75. https://doi.org/10.3354/meps12102 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 569. Online publication date: April 07, 2017 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2017 Inter-Research.

Detection of numerous phycotoxins in young bull sharks (Carcharhinus leucas) collected from an estuary of national significance

Seagrass is a major structural habitat in the Indian River Lagoon. Maps documented locations and areal extents of beds periodically since the 1940s, and surveys of fixed transects yielded changes in percent cover and depths at the end of the canopy since 1994. Areal extent increased by ∼7,000 ha from 1994 to 2009, mean percent cover within beds decreased from ∼40 to 20%, and mean percent cover standardized to maximum transect length remained near 20%. Thus, conditions supported a consistent biomass because cover decreased as areal extent increased. Between 2011 and 2019, ∼19,000 ha or ∼58% of seagrasses were lost, with offshore ends of canopies moving shoreward and shallower, and standardized mean percent cover decreased to ∼4%. These changes coincided with blooms of phytoplankton, and ≤ 27% of incident subsurface irradiance at 0.9 m was stressful. Decreases in mean percent cover per month of stress became larger when initial mean cover per transect was < 20%, which suggested that the ratio of aboveground to belowground tissues in the expanded and sparser beds led to respiratory demand that was not met by photosynthesis. Despite intermittent improvements in light penetration, widespread recovery of seagrasses has not occurred potentially due to detrimental feedbacks. For example, loss of seagrass exposed sediments to waves, and the resulting disturbance may have hampered recruitment of new shoots. The same decreases also made 58–88% of the carbon, nitrogen, and phosphorus in seagrass tissue available to other primary producers. These nutrients did not enhance growth of epiphytes, whose biomass decreased by ∼42%, but they apparently fueled blooms of phytoplankton, with mean chlorophyll-a concentrations increasing by > 900%. Such intense blooms increased shading and loss of seagrasses. Fortunately, data showed that patches of seagrasses at depths of 0.5–0.9 m persisted for 22–24 years, which suggested that this depth zone could hold the key to recovery. Nevertheless, optimistic estimates predict recovery could take 12–17 years. Such a long-term, widespread loss of a key structural habitat may generate multiple adverse effects in the system, and mitigating such effects may entail planting seagrasses to accelerate recovery.