Is the central‐marginal hypothesis a general rule? Evidence from three distributions of an expanding mangrove species, Avicennia germinans (L.) L
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Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.
Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.
In recent years the availability of automated change detection algorithms in Google Earth Engine has permitted cloud-based processing of large time series of satellite imagery. Models such as the Continuous Change Detection and Classification (CCDC), CCDC-Spectral Mixture Analysis (CCDC-SMA), and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) allow users to exploit decades of Earth Observations (EO) , leveraging the Landsat archive and data from other sensors to detect disturbance in forest ecosystems. Despite the wide adoption of these methods, robust documentation and growing community of users, little research has explored their use in mangrove environments. Mangroves are dynamic environments subject to changes due to not only the natural migration of mudflats but also coastal erosion, urban expansion, aquaculture practices, etc. This work aims to identify best practices for the application of these models to identify and monitor changes in the Belizean mangroves, which experienced an estimated 5.4% decrease in extent between 1980 and 2017 (Cherrington et al. 2020). Partnering directly with the Belizean Forest Department, our team will develop a replicable, efficient methodology to annually update the country’s mangrove extent employing EO-based change detection. This collaboration supports Belize’s marine conservation and climate resilience efforts, such as its Blue Bond agreement with the Nature Conservancy, building on national processes to monitor these critical ecosystems.
Rates of emissions of the biogenic sulfur (S) gases carbonyl sulfide (COS), methyl mercaptan (MSH), dimethyl sulfide (DMS), and carbon disulfide (CS2) were measured in a variety of marine and freshwater wetland habitats in the Florida Everglades during a short duration period in October using dynamic chambers, cryotrapping techniques, and gas chromatography. The most rapid emissions of over 500 nmol/sq m/h occurred in red mangrove-dominated sites that were adjacent to open seawater and contained numerous crab burrows. Poorly drained red mangrove sites exhibited lower fluxes of about 60 nmol/sq m/h, which were similar to fluxes from the black mangrove areas which dominated the marine-influenced wetland sites in the Everglades. DMS was the dominant organo-S gas emitted especially in the freshwater areas. Spectral data from a scene from the Landsat TM were used to map habitats in the Everglades. Six vegetation categories were delineated using geographical information system software and S gas emissions were extrapolated for the entire Everglades National Park. The black mangrove-dominated areas accounted for the largest portion of S gas emissions to the area. The large area extent of the saw grass communities accounted for about 24 percent of the total S emissions.
Rates of emissions of the biogenic sulfur (S) gases carbonyl sulfide (COS), methyl mercaptan (MSH), dimethyl sulfide (DMS), and carbon disulfide (CS2) were measured in a variety of marine and freshwater wetland habitats in the Florida Everglades during a short duration period in October using dynamic chambers, cryotrapping techniques, and gas chromatography. The most rapid emissions of greater than 500 nmol/m(sup -2)h(sup -1) occurred in red mangrove-dominated sites that were adjacent to open seawater and contained numerous crab burrows. Poorly drained red mangrove sites exhibited lower fluxes of approximately 60 nmol/m(sup -2)h(sup -1) which were similar to fluxes from the black mangrove areas which dominated the marine-influenced wetland sites in the Everglades. DMS was the dominant organo-S gas emitted especially in the freshwater areas. Spectral data from a scene from the Landsat thematic mapper were used to map habitats in the Everglades. Six vegetation categories were delineated using geographical information system software and S gas emission were extrapolated for the entire Everglades National Park. The black mangrove-dominated areas accounted for the largest portion of S gas emissions to the area. The large area extent of the saw grass communities (42 percent) accounted for approximately 24 percent of the total S emissions.
High intensity storms and coastal development negatively impact the ecosystems of Jobos Bay, Puerto Rico, by causing reductions in mangrove forests and degradation of water quality. These changes can compromise the ecosystem services, economic value, and cultural significance provided to the community by Jobos Bay. In collaboration with the Jobos Bay National Estuarine Research Reserve (JBNERR), the Jobos Bay Water Resources II team used Earth observations to investigate water quality, watersheds land use land cover (LULC) changes, and the impact of Hurricanes Maria and Irma on mangrove forest area. This information will improve JBNERR’s understanding of the impacts of development and weather events on Jobos Bay, and will inform future shoreline management decisions that ensure continued quality of the ecosystem. Mangrove extent was examined using imagery from Landsat 8 Operational Land Imager (OLI), WorldView 2 WV110, and WorldView 3 WV110. Imagery from Sentinel-2 MultiSpectral Instrument (MSI) was used to map watersheds LULC. Landsat 8 OLI and Sentinel-2 MSI data were analyzed with in situ data collected at the time of satellite overpass to investigate water quality in Jobos Bay. Reduction from 2017 mangrove extent was observed in 2018 following the hurricane events, and area of mapped extent was greater than 2018 in 2021. Water quality derived from satellite data was compared to in situ water quality measurements to inform future methodology decisions.
The Marsh Biome, which was modeled after the mangroves and marshes of southwest Florida, has an area of 441.2 sq m separated into three hydrologically independent sections: the Freshwater, Oligohaline and Salt Marshes. The divisions are made based on their salinity (approximately 0, 4, and 34 ppt. respectively), but they also contain different biological communities. The Freshwater and Oligohaline Marshes are mostly filled with various grasses and several trees, while the Salt Marsh houses regions of red, black, and white mangroves (Rhizophora mangle, Avicennia germinans, and Languncularia racemosa respectively). Overall, there are an estimated 80 species of plants within the biome. Water in the Salt Marsh follows a meandering stream from the algal turf scrubbers (apparatuses that clean the water of its nutrients and heavy metals while increasing dissolved oxygen levels) which have an outlet in the Salt Marsh section near sites 4 and 5 to the Fringing Red Mangrove section. The sections of the Salt Marsh are separated by walls of concrete with openings to allow the stream to flow through. Throughout this study, conducted through the months of June and July, many conditions within the biome remained fairly constant. The temperature was within a degree or two of 25 C, mostly depending on whether the sample site was in direct sunlight or shaded. The pH throughout the Salt Marsh was 8.0 +/- 0.2, and the lower salinity waters only dropped below this soon after rains. The water rdepth and dissolved oxygen varied, however, between sites.
Jobos Bay is located on the southern coast of Puerto Rico, which is known for intense hurricane seasons and increased seasonal storm surge. Scientists at Jobos Bay National Estuarine Research Reserve (JBNERR) are concerned that sea level rise will exacerbate coastal damage from these weather events. Using NASA Earth observations, our team analyzed coastal change, land use land cover change (LULC), mangrove forest extent, and water quality of Jobos Bay. Using Google Earth Engine, we evaluated coastal change and mangrove forest habitat within the study region by classifying NASA Earth observation imagery. We created historic LULC composite images to observe how land use changes over time and improve understanding of urbanization in the watershed. Leveraging previous water quality studies, our team compared water quality datasets generated by the Optical Reef and Coastal Area Assessment (ORCAA) tool to in situ sensors provided by JBNERR partners to understand the overall quality of water in the study area with respect to turbidity, chlorophyll-a, sea surface temperature, and colored dissolved organic matter (CDOM) concentrations. We discovered that 17% of the reserve has shifted from land to water since 1997 and lost 4.85 square kilometers of mangrove habitat over the past decade. Results from this study will inform the scientists of JBNERR and community members of the regional impacts of sea level rise. Being the first comprehensive study done in the estuary in nearly a decade, this serves as a baseline for future conservation efforts and research in the estuary.
The author has identified the following significant results. Forest inventory of Thailand was completed in January 1975, using LANDSAT-1 imagery and ground truth survey. Results showed the existing forest covers only 37% of the land area. The last country-wide survey using aerial survey photographs at 1:60,000 scale conducted in 1961 gave the figure of 58%. ERTS-1 imagery showed that Thailand's mangrove forest covers an area of approximately 3130 sq k. The previous aerial survey showed 3681 sq k of mangroves.
The author has identified the following significant results. Major vegetative classes identified by the remote sensing technique were cypress swamp, pine, wetland grasses, salt grass, mixed mangrove, black mangrove, Brazilian pepper. Australian pine and melaleuca were not satisfactorily classified from LANDSAT. Aircraft scanners provided better resolution resulting in a classification of finer surface detail. An edge effect, created by the integration of diverse spectral responses within boundary elements of digital data, affected the wetlands classification. Accuracy classification for aircraft was 68% and for LANDSAT was 74%.
Increasing levels of ultraviolet (UV) radiation reaching the earth's surface which results from stratospheric ozone depletions could have serious implications for terrestrial plants and for aquatic organisms within the euphotic zone. A documented 9% decline in ozone at mid-latitudes is considered to produce a 12% increase in harmful UV radiation. The biologically damaging effects of higher UV levels, particularly W-B (280-320 rim), could manifest earlier in the tropics because of the relative thinness of the earth's equatorial ozone layer. Tropical marine organisms are also living close to their upper tolerance levels of water temperature, However, despite the large potential effects on plants and animals, little is known about UV effects on tropical ecosystems. Long-term ecological studies are needed to quantify the effects of increased UV radiation on terrestrial and marine ecosystems and to produce reliable data for prediction. Plants have developed several mechanisms to protect themselves from harmful UV radiation, one of which is the production of secondary leaf pigments that absorb W-B radiation (screening pigments). A higher concentration of screening pigments (e.g. flavonoids) in leaves may be interpreted as a natural response to increased W radiation. If higher concentrations of flavonoids filter out the excessive W radiation, no damage will occur, as suggested by Caldwell et al. (1989) and Tevini (1993). Failure to screen all W-B may result in deleterious effects on photosynthesis, plant genetic material, and plant and leaf morphology and growth. Eventually this will have an impact on ecosystem processes, structure, species composition, and productivity. This paper describes an ongoing project that is assessing the responses of mangroves, seagrasses and corals to W radiation by studying pigment concentrations, biophysical parameters, and variations in spectral reflectance in the field and in W-reduction experiments. Preliminary results on the distribution of W-absorbing flavonoid compounds in red mangroves (Rhizophora mangle) and the seagrass Thalassia testudinum, are presented. This research also provides, for the first time, a permanent record of daily W irradiance measurements at a tropical -location.
Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.
The Osa Peninsula, located in the southern region of Costa Rica’s Pacific Coast, is one of the most biologically-diverse places on Earth and is a popular ecotourism destination. However, the area faces watershed degradation and loss of biodiversity due to deforestation, pollution from agriculture, and human settlement. The NASA DEVELOP National Program worked with Osa Conservation to analyze land use and land cover change in the Osa Peninsula to better understand threats to river water quality and mangrove health. This project used Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), and Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to create a land cover time series map from 1987 to 2017. These time series data were used to compare land use over time, as well as patterns in water quality, mangrove health, erosion, and deforestation. The time series also helped to identify the impact of the creation of protected areas and the 1996 Forest Law 7575, which aimed to support reforestation and riparian health. Osa Conservation will use and distribute results to the National System of Conservation Areas (SINAC), Ministry of Environment and Energy (MINAE), and local communities to inform land management decisions, policy enforcement, education and outreach initiatives, and watershed restoration and monitoring.
This summer, the Jobos Bay National Estuarine Research Reserve (JBNERR) partnered with NASA DEVELOP to evaluate water quality, mangrove forest extent, sea level rise, and land cover changes in Jobos Bay. DEVELOP is a national capacity building program that connects satellite data with early career scientists and decision makers. Through ten-week feasibility studies, DEVELOP partners with organizations that have the power to enact policy within their communities. Jobos Bay, in the southeast coast of Puerto Rico, has experienced intense hurricane seasons with increased seasonal storm surge, near-shore land use changes, and strong variations in precipitation and runoff. Through proposals, bi-weekly meetings, and frequent email communication, this cross-sector initiative provided valuable results for management decisions within the reserve. Using satellite observations to measure land use change, the team found that 17% of the reserve has shifted from land to water along the coast since 1997. Using Sentinel-2 the team was able to visualize turbidity, chlorophyll-a, and colored dissolved organic matter (CDOM) for Jobos Bay. While some large events such as Hurricane Maria were reflected in the turbidity analysis, chlorophyll-a and CDOM visualizations were limited by the influence of shallow-water bottom reflectance, particularly around reefs and within the Bay. The team also found that Jobos Bay lost 4.9 square kilometers of mangrove habitat over the past decade, calculated using Landsat 7 and 8 within Google Earth Engine. The results from this study will inform JBNERR and its community members on the regional impacts of sea level rise as well as serve as a baseline for future conservation efforts and research in the estuary.
Coastal wetlands play a significant role in the storage of “blue carbon,” indicating their importance in the carbon biogeochemistry in the coastal zone and in global climate change mitigation strategies. We present airborne eddy covariance observations of CO 2 and CH 2 fluxes collected in southern Florida as part of the NASA BlueFlux mission during April 2022, October 2022, February 2023, and April 2023. The flux data generated from this mission consists of over 100 flight hours and more than 6,000 km of horizontal distance over coastal saline and freshwater wetlands. We find that the spatial and temporal heterogeneity in CO 2 and CH 2 exchange is primarily influenced by season, vegetation type, ecosystem productivity, and soil inundation. The largest CO 2 uptake fluxes of more than 20 μmol m -2 s -1 were observed over mangroves during all deployments and over swamp forests during flights in April. The greatest CH 4 effluxes of more than 250 nmol m -2 s -1 were measured at the end of the wet season in October 2022 over freshwater marshes and swamp shrublands. Although the combined Everglades National Park and Big Cypress National Preserve region was a net sink for carbon, CH 4 emissions reduced the ecosystem carbon uptake capacity (net CO 2 exchange rates) by 11%–91%. Average total net carbon exchange rates during the flight periods were −4 to −0.2 g CO 2 -eq m -2 d -1 . Our results highlight the importance of preserving mangrove forests and point to potential avenues of further research for greenhouse gas mitigation strategies.
Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.
The distribution of natural vegetation on North Merritt Island, Florida, was studied by computer analysis of ERTS satellite multispectral-scanner data. The boundaries of six distinct plant associations were located in photos produced on the image analyzer with an insignificant mean error of -24.38 meters. The six plant associations are described as: aquatic estuarine association, mangrove, spartina swamp, wooded swamp, sabal hammock, and oak-palmetto. The difference in average reflectance 'grey level' between the lowest of the four spectral scanning bands and the highest spectral scanning band for each of the six vegetation types is described. The decreasing trend of the differences is strongly negatively correlated with height of land, the coefficient of correlation being -0.9696.