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Some ecosystems require regular disturbances to maintain their biological and structural diversity. However, shifts in climate and changes in land management practices have altered global fire regimes, making it challenging to determine the most effective approach to maintain fire-dependent ecosystems. Measuring how ecosystems respond to disturbances can offer valuable insights into the effects of fire under contemporary conditions. In Everglades pinelands, we used satellite data to develop a machine learning model for the normalized difference vegetation index (NDVI), an effective proxy for primary productivity. Our findings showed that NDVI values ranged from 0.2 to 0.4 for Everglades pinelands, which were significantly influenced by fire history. Areas that experienced more frequent and more recent fires exhibited higher NDVI values compared to those that were less frequently burned. Conversely, pinelands that had not burned for an extended period (>15 years) showed signs of transitioning to less fire-dependent ecosystems. Following contemporary fires in Everglades pinelands, there was an initial reduction in NDVI of ∼6 %. However, on average, within 2 years, pinelands recovered to a higher post-fire NDVI (∼27 %) compared to their pre-fire levels. Our results suggest that more frequent fires enhance productivity and promote faster post-fire recovery in subtropical fire-dependent pinelands. 

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. 

Coastal ecosystems rapidly transform as sea levels rise faster than ecosystems can build elevation through biological processes that accrete organic matter and inorganic sediment. Benthic microbial communities (periphyton) are a crucial driver of sediment accretion in coastal wetlands by forming, trapping, and stabilizing sediments. Inorganic sediments can be either generated in situ by mineral-accreting organisms (e.g., calcium carbonates by periphyton), or materials can be transported from a different origin when sediments become resuspended and displaced, such as during high-wind weather events. In situ-generated sedimentary materials may contribute significantly to elevation gains. This study examines the drivers of coastal periphyton mineral production and whether periphytic diatoms may be used to characterize gradients in these drivers. Periphyton mineral production rates and diatom assemblage composition were measured along three coastal gradients of surface water salinity, conductivity, pH, and periphyton nutrient content in the Biscayne Bay Coastal Wetlands of South Florida. Periphyton mineral production rates ranged from 0.20-0.53 g/m2/d and were greatest at sites with the highest periphyton total carbon and mineral content while lowest at sites with the highest periphyton organic content and total nitrogen and soil depth. Diatom assemblages that sorted consistently along the coastal salinity gradient were reliable indicators of periphyton mineral production, with seven taxa indicating high rates and seven indicating low rates. Diatoms can provide a helpful link between biotic and abiotic processes, indicating where periphyton-driven mineral production contributes most to inorganic carbon cycling and mineral-driven elevation recovery and, hence, to resiliency to sea level rise. 

Abstract Pulses of resource availability along environmental gradients can filter the local and regional distribution of macrophyte and microbial mat communities in wetlands. Wetlands that experience short hydroperiods (i.e., <6 months with standing water) may cause macrophyte and microbial mat competition for water. However, the stress gradient hypothesis predicts that abiotic stress should increase facilitative co‐regulation of producer dynamics. To determine if and how macrophyte and microbial mat biomass covary along a hydrologic gradient, we conducted two observational surveys and a biomass removal experiment in Everglades National Park, FL, USA. In the survey, macrophyte and microbial mat biomass were measured over a two‐year period across nine hydrologically regulated macrophyte community types to determine drivers of biomass and macrophyte–microbial mat interactions along a hydroperiod gradient (3–8 months) using a structural equation model. In the experiment, the effect of hydrology on the interaction between macrophytes and microbial mats was quantified by measuring the effect of bimonthly removal of macrophyte or microbial mat biomass on the biomass of both communities in plots in wetlands with contrasting hydroperiods (3–6 months). Hydrology and biological interactions influenced macrophyte and microbial mat biomass, with stronger interactions observed in the shortest hydroperiod transect sites dominated bySchoenus nigricansandCladium jamaicense. Along the hydrologic gradient, we found direct negative effects of macrophyte biomass on microbial biomass and vice versa, and a significant positive effect of microbial response to flooding duration on macrophyte biomass. Experimental macrophyte removal in shorter‐hydroperiod wetlands resulted in a significant increase in microbial biomass while microbial mat removal reduced biomass of the dominant macrophyteC. jamaicense. The facilitative effect of microbial mats on macrophyte biomass in shorter‐hydroperiod wetlands may be driven by mats prolonging soil moisture retention due to their desiccation‐resistant structure. Stress‐induced facilitation supported the stress gradient hypothesis across the short‐hydrologic gradient, while competitive interactions were also observed. As climate and human drivers continue altering hydrology in aquatic systems, the type and strength of community interactions will continue to shift and alter distributions across the landscape. 

This data package encompasses hydrologic variables, soil depth, hydrologically-regulated macrophyte community types, macrophyte biomass and community structure, and microbial mat biomass that was collected in two observational surveys and one in-situ experimental manipulation in six temporary wetland regions located in the Everglades, FL, USA. The goal of this project was to examine the co-variation in macrophyte and microbial mat biomass along the hydrologic gradient present across wetland regions and to determine the type and strength of interactions occurring between the two communities, which was tested using a biomass (macrophyte or microbial mat) removal experiment. The census observational survey took place at 140 sites from 2003-04-09 to 2004-05-26, which were randomly distributed across the hydrologic gradient present across the six temporary wetland regions. The transect observational survey occurred along six transects and each was deliberately established along the present hydrologic gradient within each region; a total of 254 sites were sampled from 2003-02-19 to 2005-03-04. The experiment took place at three temporary wetland sites with contrasting hydroperiods (3 – 6 months), and four transects were established per site with 24 pairs of control and treatment plots per transect. The removal treatment occurred one year before data collection, and data collection occurred from 2004-06-20 to 2006-11-25. The package includes six datasets, one R code file, and two shape files associated with the R code. Data collection for all datasets is complete. FCE1274_Census_Survey includes hydrologically-regulated macrophyte community type classifications, macrophyte biomass, microbial mat ash-free dry mass, mean soil depth, water depth, mean annual hydroperiod, and vegetation-inferred hydroperiod; each site was sampled once during the survey period and a subset of sites were sampled each year. FCE1274_Transect_Survey includes macrophyte community type classifications, macrophyte biomass, microbial mat ash-free dry mass, mean soil depth, water depth, mean annual hydroperiod, and vegetation-inferred hydroperiod. Each site was sampled once during the survey period; all sites along each transect were sampled before moving to the next transect. FCE1274_Removal_Experiment includes total macrophyte biomass, live macrophyte biomass, dead macrophyte biomass, and live macrophyte stem density within each microbial mat removal control and treatment plot along each transect at all three sites. Microbial mat dry mass, microbial mat ash-free dry mass, microbial mat chlorophyll-a concentration, and microbial mat organic content for each macrophyte removal control and treatment plot along each transect at all three sites are included as well. Data was collected once from each plot during the data collection period, and one pair of macrophyte removal plots and microbial mat removal plots were randomly sampled on a bimonthly basis until all plots had been sampled. FCE1274_Removal_Experiment_Macrophyte_Biomass includes total macrophyte biomass for each macrophyte species found within each microbial mat removal control and treatment plot along each transect at all three sites. Data was collected once from each plot during the data collection period, and one pair of microbial mat removal plots were randomly sampled on a bimonthly basis until all plots had been sampled. FCE1274_Removal_Experiment_Macrophyte_Density includes total macrophyte stem density for each macrophyte species found within each microbial mat removal control and treatment plot along each transect at all three sites. Data was collected once from each plot during the data collection period, and one pair of microbial mat removal plots were randomly sampled on a bimonthly basis until all plots had been sampled. FCE1274_Removal_Experiment_Macrophyte_Codes includes the taxon codes assigned to each macrophyte species identified in the FCE1274_Removal_Experiment_Macrophyte_Biomass and FCE1274_Removal_Experiment_Macrophyte_Density datasets.