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Abstract BackgroundPrescribed fire is an essential tool employed by natural resource managers to serve ecological and fuel treatment objectives of fire management. However, limited operational resources, environmental conditions, and competing goals result in a finite number of burn days, which need to be allocated toward maximizing the overall benefits attainable with fire management. Burn prioritization models must balance multiple management objectives at landscape scales, often providing coarse resolution information. We developed a decision-support framework and a burn prioritization model for wetlands and wildland-urban interfaces using high-resolution mapping in Everglades National Park (Florida, USA). The model included criteria relevant to the conservation of plant communities, the protection of endangered faunal species, the ability to safely contain fires and minimize emissions harmful to the public, the protection of cultural, archeological, and recreational resources, and the control of invasive plant species. A geographic information system was used to integrate the multiple factors affecting fire management into a single spatially and temporally explicit management model, which provided a quantitative computations-alternative to decision making that is usually based on qualitative assessments. ResultsOur model outputs were 50-m resolution grid maps showing burn prioritization scores for each pixel. During the 50 years of simulated burn unit prioritization used for model evaluation, the mean burned surface corresponded to 256 ± 160 km2 y−1, which is 12% of the total area within Everglades National Park eligible for prescribed fires. Mean predicted fire return intervals (FRIs) varied among ecosystem types: marshes (9.9 ± 1.7 years), prairies (7.3 ± 1.9 years), and pine rocklands (4.0 ± 0.7 years). Mean predicted FRIs also varied among the critical habitats for species of special concern:Ammodramus maritimus mirabilis(7.4 ± 1.5 years),Anaea troglodyta floridalisandStrymon acis bartramibutterflies (3.9 ± 0.2 years), andEumops floridanus(6.5 ± 2.9 years). While mean predicted fire return intervals accurately fit conservation objectives, baseline fire return intervals, calculated using the last 20 years of data, did not. Fire intensity and patchiness potential indices were estimated to further support fire management. ConclusionsBy performing finer-scale spatial computations, our burn prioritization model can support diverse fire regimes across large wetland landscape such as Everglades National Park. Our model integrates spatial variability in ecosystem types and habitats of endangered species, while satisfying the need to contain fires and protect cultural heritage and infrastructure. Burn prioritization models can allow the achievement of target fire return intervals for higher-priority conservation objectives, while also considering finer-scale fire characteristics, such as patchiness, seasonality, intensity, and severity. Decision-support frameworks and higher-resolution models are needed for managing landscape-scale complexity of fires given rapid environmental changes. 

River networks serve as conduits for dissolved organic matter (DOM) and carbon (DOC) from inland to coastal waters. Human activities and climate change are altering DOM sources, causing hydrological and biogeochemical shifts that impact DOC concentrations and changing the transport and transformation of DOM and DOC. Here, we synthesize current knowledge of changing DOM sources, DOC concentrations, and the associated hydrological and biogeochemical changes during transport along inland-to-coastal gradients, focusing on impacts to coastal and estuarine DOM and DOC. We project that continued land-use changes, hydrological management, and sea-level rise will result in more microbial and labile DOM, higher DOC concentrations, and an overall decoupling of DOC quantity and DOM quality. Understanding how these changes vary among river networks is essential to forecast coastal and estuarine water quality, ecosystem health, and global carbon cycling. 

Abstract Hurricanes are among the most destructive natural disturbances in mangroves, altering community structure and ecological processes. Despite their impacts, few studies have assessed changes in belowground root processes (i.e., biomass, production, decomposition) following major hurricanes. Here, we quantified and compared changes in mangrove root processes in the Florida Coastal Everglades before (pre‐hurricane period: 2000–2004) and after post‐hurricane periods (post‐Wilma, May 2012; immediate‐post‐Irma, March 2018; post‐Irma, March 2023). We assessed spatiotemporal patterns in root dynamics across four mangrove sites (upstream, midstream, downstream, and estuary mouth) along a well‐defined soil phosphorus fertility gradient in the Shark River estuary. Root biomass carbon stocks were highest in the immediate‐post‐Irma and post‐Irma periods. The midstream site had the highest root C stocks, whereas the downstream site had the lowest across periods. Root size class distribution shifted considerably post‐hurricane, with fine roots accounting for 32% (post‐Wilma) to 66% (immediate‐post‐Irma and post‐Irma) of the total root C stocks across sites. However, root production did not vary among periods at any site, although estimates were higher midstream compared to upstream or downstream. Root total nitrogen and P were ~1.3 times higher in the post‐Irma period compared to other periods, with root P consistently increasing from upstream to the estuary mouth. Fine root turnover rates were lower post‐hurricane compared to pre‐hurricane across sites. Root decay rates declined post‐Irma at all sites, except at the midstream site. Our findings suggest that P‐rich sediments deposited by hurricanes can enhance belowground C allocation by increasing root biomass and nutrient uptake, while reducing root turnover to facilitate forest recovery. These responses underscore the strong phenotypic plasticity and resilience of mangrove roots in P‐limited carbonate settings, highlighting their critical role in C sequestration, resilience, and ecosystem stability as climate‐related disturbances and sea‐level rise intensify. 

Along low-elevation coastlines, sea-level rise (SLR) threatens to salinate ecosystems. To understand the effects of SLR and freshwater management on landscape carbon (C) exchange, we measured the net ecosystem exchange (NEE) of CO2 between subtropical wetland ecosystems and the atmosphere along a dynamic salinity gradient. Ecosystems were representative of freshwater marl prairies, brackish ecotones, and saline scrub mangrove forests in the southeastern Everglades. Patterns in NEE explained the landward movement of coastal wetlands, a process observed over the last 70 years. The capacity to capture C was greatest along the coast in the scrub mangrove (−294 ± 0.02 g C m−2 y−1) and declined inland into marl prairies (−47 ± 0.03 g C m−2 y−1). Low resilience to current conditions was evident in marl prairies, a result of the legacy impacts of water diversion throughout the greater Everglades. Although the southeastern Everglades captured approximately 115 metric tons of C in 2021, if the ecotone continues to advance at 25 m y−1 over the next century, we project a 12 % increase (16 mt C y−1) in net CO2 capture. Results emphasize that initial functional responses to changes in conditions may not accurately represent long-term outcomes and highlight the role of brackish ecotone communities as the frontline for climate- and management-induced shifts in coastal ecosystem structure and function. This is the first study to use disequilibrium dynamics to understand landscape-level transitions and their implications for C capture. 

This dataset contains field measurements taken during water sampling from 100 urban stream locations in the greater Miami, Florida metropolitan area. Field collection took place during five synoptic sampling events: Summer 2021 (Wet; July 8 to July 27), Fall 2021 (Wet; September 27 to October 7), Winter 2022 (Dry; January 3 to January 13), Spring 2022 (Dry; April 7 to April 23), and Summer 2022 (Wet; June 1 to June 13) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in a separate dataset. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset. 

This dataset contains dissolved organic carbon concentrations from surface water samples collected at 100 urban stream and canal locations in the greater Miami, Florida metropolitan area. Samples were collected five times across different seasons to capture spatial and seasonal variation in DOC concentration. These events include the wet seasons of 2021 and 2022, as well as the dry season of 2022, specifically: Summer 2021 (Wet; July 8 to July 27), Fall 2021 (Wet; September 27 to October 7), Winter 2022 (Dry; January 3 to January 13), Spring 2022 (Dry; April 7 to April 23), and Summer 2022 (Wet; June 1 to June 13). These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset. 

This dataset contains dissolved organic matter (DOM) characteristics from surface water samples collected at 100 urban stream and canal locations in the greater Miami, Florida metropolitan area. Samples were collected five times across different seasons to capture spatial and seasonal variation in DOC concentration. These events include the wet seasons of 2021 and 2022, as well as the dry season of 2022, specifically: Summer 2021 (Wet; July 8 to July 27), Fall 2021 (Wet; September 27 to October 7), Winter 2022 (Dry; January 3 to January 13), Spring 2022 (Dry; April 7 to April 23), and Summer 2022 (Wet; June 1 to June 13). Fluorescent optical properties were measured on filtered water samples to understand the chemical composition of DOM. Excitation-Emission Matrices (EEMs) were measured using a Horiba Aqualog spectrometer. DOM characteristics were quantified using both standard fluorescence and absorbance metrics as well as through parallel factor (PARAFAC) analysis. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset. 

Monthly litterfall data is being collected in two mangrove-dominated regions (Shark River and Taylor Slough) in South Florida. Three sites (SRS4, SRS5, SRS6) in the Shark River region and one site (TS/Ph8) in the Joe Bay area region were used to characterize patterns of litterfall production. At each mangrove site 10 litter baskets (0.5 x 0.5 m) were placed in two 20 x 20 m plots (five baskets per plot). Data have been collected since January 2001. Statistical analysis is being performed. See also Shark River mangrove litterfall carbon and nutrients data package knb-lter-fce.1266 (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1266). 

This dataset contains dissolved organic carbon (DOC) concentrations from surface water samples collected at 100 urban stream locations in the greater Boston, Massachusetts metropolitan area. Samples were collected four times (September 2021, November 2021, April 2022, and July 2022) to capture spatial and seasonal variation in DOC concentrations. Filtered stream samples were analyzed for dissolved organic carbon concentration. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset. 

Abstract Leaf litter in coastal wetlands lays the foundation for carbon storage, and the creation of coastal wetland soils. As climate change alters the biogeochemical conditions and macrophyte composition of coastal wetlands, a better understanding of the interactions between microbial communities, changing chemistry, and leaf litter is required to understand the dynamics of coastal litter breakdown in changing wetlands. Coastal wetlands are dynamic systems with shifting biogeochemical conditions, with both tidal and seasonal redox fluctuations, and marine subsidies to inland habitats. Here, we investigated gene expression associated with various microbial redox pathways to understand how changing conditions are affecting the benthic microbial communities responsible for litter breakdown in coastal wetlands. We performed a reciprocal transplant of leaf litter from four distinct plant species along freshwater‐to‐marine gradients in the Florida Coastal Everglades, tracking changes in environmental and litter biogeochemistry, as well as benthic microbial gene expression associated with varying redox conditions, carbon degradation, and phosphorus acquisition. Early litter breakdown varied primarily by species, with highest breakdown in coastal species, regardless of the site they were at during breakdown, while microbial gene expression showed a strong seasonal relationship between sulfate cycling and salinity, and was not correlated with breakdown rates. The effect of salinity is likely a combination of direct effects, and indirect effects from associated marine subsidies. We found a positive correlation between sulfate uptake and salinity during January with higher freshwater inputs to coastal areas. However, we found a peak of dissimilatory sulfate reduction at intermediate salinity during April when freshwater inputs to coastal sites are lower. The combination of these two results suggests that sulfate acquisition is limiting to microbes when freshwater inputs are high, but that when marine influence increases and sulfate becomes more available, dissimilatory sulfate reduction becomes a key microbial process. As marine influence in coastal wetlands increases with climate change, our study suggests that sulfate dynamics will become increasingly important to microbial communities colonizing decomposing leaf litter.