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Fire-adaptive traits in plants of tropical and subtropical grassy ecosystems have been the subject of considerable global research, but only recently studied in pyrogenic Florida subtropical grasslands. Plant growth forms, belowground organs, and post-fire recovery strategies were studied for 198 grassland specialists in peninsular Florida. Community types (dry-mesic, mesic, wet-mesic, and wet) were sampled with 1m2 plots along the edaphic-hydrologic gradient and the association between these variables and fire-related plant traits was tested using fourth-corner analysis. Caulescent herbs (43), cespitose graminoids (27), and rosette herbs (31) are the most common growth forms among species sampled. Plants with epigeogenous and hypogeogenous rhizomes dominate the sample plots, including matrix graminoids, shrub geoxyles, and an acaulescent rhizomatous fire-resilient palm (Serenoa repens). Most species (163; 82%) exhibit resprouting, including 30 facultative resprouters and 133 obligate resprouters. All woody rhizomatous species are obligate resprouters, and 35 ephemeral herbaceous species are obligate reseeders. Community type was a better predictor of species abundances than hydrology, however, hydrology was significantly associated with species traits measured, particularly rhizome texture, with woody rhizomes prevalent in all but the wet sites. Belowground organs (xylopodia, geoxylic suffructices) and growth form were associated with frequent fire and phylogeny, suggesting fire regime as a driver of community phylogenetic diversity. Persistence, rapid resilience and co-occurrence of geoxyles align Florida subtropical grasslands with other global geoxyle grasslands. The old-growth, pyrogenic grassy ecosystems of peninsular Florida are the center of geoxyle diversification on the southeastern US coastal plain. [ABSTRACT FROM AUTHOR]

Subtropical calcareous wet grasslands (SCWG) are pyrogenic hyper-seasonal grasslands with exceptional vascular plant biodiversity and conservation value in south-central Florida with floristic affinities to southern Florida marl grasslands, and both are dominated by Muhlenbergia sericea. We sampled 62 sites (n = 124 samples), of which 62 were surface soil samples (upper 1–10 cm), and 62 were subsurface soils (above the spodic horizon) across the edaphic-hydrologic gradient of savanna-grassland landscape in south-central Florida. We sought to determine how soil chemistry (17 variables) and texture (7 categories) might correlate with floristic composition and distinguish SCWG from savanna-grassland community types in peninsular Florida. To test which soil PCA axes were associated with plant community types, we used correlations between NMDS plot scores and the scores of significant soil PCA axes. Surface and subsurface soil chemistry were significantly correlated with dimensions of variation in savanna-grassland plant community types. In SCWG, soil chemistry is segregated because of higher Ca, pH, and percentage base saturation in subsurface soils. Lower cation exchange capacity, surface and subsurface soil texture with greater fine sand particles, lower silt, and higher clay content differentiate SCWG. Our results highlight the edaphic-hydrologic distinctiveness of SCWG, which supports previous recognition based solely on floristic and species composition, where calciphilic habitat specialists coexist with plants otherwise characteristic of brackish marsh, acidic grassland, and xeric sands. [ABSTRACT FROM AUTHOR]

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993–2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997–2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of natural lightning ignitions should be useful as a basis for ecological fire management of humid savanna-grassland landscapes worldwide. [ABSTRACT FROM AUTHOR]

Theory predicts that wildfires will encounter spatial thresholds where different drivers may become the dominant influence on continued fire spread. Studying these thresholds, however, is limited by a lack of sufficiently detailed data sets. To address this problem, we searched for scale thresholds in data describing wildfire size at the Avon Park Air Force Range, south-central Florida. We used power-law statistics to describe the “heavy-tail” of the fire size distribution, and quantile regression to determine how the edges of data distributions of fire size were related to climate. Power-law statistics revealed a heavy-tail, a pattern consistent with scale threshold theory, which predicts that large fires will be rare because only fires that cross all thresholds will become large. Results from quantile regression suggested that different climate conditions served as critical thresholds, influencing wildfire size at different spatial scales. Modeling at higher quantiles (≥75th) implicated drought as driving the spread of larger fires, whereas modeling at lower quantiles (≤25th) implicated that wind governed the spread of smaller fires. Fires of intermediate size were negatively associated with relative humidity. Our results are consistent with the idea that fire spread involves scale thresholds, with the small-scale drivers allowing fires to spread after ignition, but with further spread only being possible when large-scale drivers are favorable. These results suggest that other data sets that have heavy-tailed distributions may contain patterns generated by scale thresholds, and that these patterns may be revealed using quantile regression. [ABSTRACT FROM AUTHOR]

Seasonality drives ecological processes through networks of forcings, and the resultant complexity requires creative approaches for modeling to be successful. Recently ecologists and climatologists have developed sophisticated methods for fully describing seasons. However, to date the relationships among the variables produced by these methods have not been analyzed as networks, but rather with simple univariate statistics. In this manuscript we used structural equation modeling (SEM) to analyze a proposed causal network describing seasonality of rainfall for a site in south-central Florida. We also described how this network was influenced by the El Niño-Southern Oscillation (ENSO), and how the network in turn affected the site’s wildfire regime. Our models indicated that wet and dry seasons starting later in the year (or ending earlier) were shorter and had less rainfall. El Niño conditions increased dry season rainfall, and via this effect decreased the consistency of that season’s drying trend. El Niño conditions also negatively influenced how consistent the moistening trend was during the wet season, but in this case the effect was direct and did not route through rainfall. In modeling wildfires, our models showed that area burned was indirectly influenced by ENSO via its effect on dry season rainfall. Area burned was also indirectly reduced when the wet season had consistent rainfall, as such wet seasons allowed fewer wildfires in subsequent fire seasons. Overall area burned at the study site was estimated with high accuracy (R2 score = 0.63). In summary, we found that by using SEMs, we were able to clearly describe causal patterns involving seasonal climate, ENSO and wildfire. We propose that similar approaches could be effectively applied to other sites where seasonality exerts strong and complex forcings on ecological processes. [ABSTRACT FROM AUTHOR]

In the USA, the United States Department of Agriculture (USDA) Natural Resource Conservation Service (NRCS) has restored millions of acres of wetlands through its Wetland Reserve Easement (WRE) programs. However, few quantitative studies have explored whether WREs have enhanced wetland hydrology and wetland plant communities. Additionally, USDA Compatible Use Permits for cattle grazing and other management practices are sometimes issued for WREs, but little is known about potential benefits/detriments of such practice on the success of wetland restoration. In this study, we tested if hydrological restoration of previously drained species poor pastures increased water depth and hydroperiod. Restoration involved plugging key ditches, adding water control structures and a berm. We also tested if hydrological restoration increased plant diversity (alpha and beta), floristic quality (using coefficient of conservatism) and increased the cover of wetland species (using species wetland status). Finally, we tested if cattle grazing had an effect on the success of restoration by comparing grazed plots to fenced plots. We studied two conservation easements (a total of 748 acres) located on semi-native pastures in central Florida, USA. We monitored vegetation using permanent transects stratified by vegetation type before (2004-2005) and after (2012) the restoration (2008). We assessed wetland hydroperiod using groundwater wells set up in 2003 and located within and outside the boundaries of these two easements. We used linear mixed models and multivariate analyses to compare vegetation and hydroperiods pre- and post-restoration. Number of flooded days increased following restoration in one of the easements, but we did not detect significant changes in hydrology in the other easement. Floristic quality, beta diversity and cover of obligate wetland species increased in both conservation easements and in most vegetation types. These vegetation changes were likely due to restoration activities since annual rainfall was not significantly different pre- and post-restoration. Cattle grazing did not have a negative or positive effect on the success of restoration, nor did we detect any positive effect of grazing on the success of restoration. Overall, our study shows that hydrological restoration can enhance wetland hydroperiod, water depth and wetland vegetation, but more resources should be allocated to short- and long-term monitoring of the restoration success., Competing Interests: The authors received funding form The Mosaic Company (www.mosaicco.com/). This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development, or marketed products to declare.

Ecological sampling can be labor intensive, and logistically impractical in certain environments. We optimize line intercept sampling and compare estimation methods for assessing feral swine damage within fragile wetland ecosystems in Florida. Sensitive wetland sites, and the swine damage within them, were mapped using GPS technology. Evenly spaced parallel transect lines were simulated across a digital map of each site. The length of each transect and total swine damage under each transect were measured and percent swine damage within each site was estimated by two methods. The total length method (TLM) combined all transects as a single long transect, dividing the sum of all damage lengths across all transects by the combined length of all transect lines. The equal weight method (EWM) calculated the damage proportion for each transect line and averaged these proportions across all transects. Estimation was evaluated using transect spacings of 1, 3, 5, 10, 15, and 20 m. Based on relative root mean squared error and relative bias measures, the TLM produced higher quality estimates than EWM at all transect spacings. Estimation quality decreased as transect spacing increased, especially for TLM. Estimation quality also increased as the true proportion of swine damage increased. Diminishing improvements in estimation quality as transect spacings decreased suggested 5 m as an optimal tradeoff between estimation quality and labor. An inter-transect spacing of 5 m with TLM estimation appeared an optimal starting point when designing a plan for estimating swine damage, with practical, logistical, economic considerations determining final design details.