16 resultados para Tongues of fire

em Digital Commons at Florida International University


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Recent research makes clear that much of the Everglade’s flora and fauna have evolved to tolerate or require frequent fires. Nevertheless, restoration of the Everglades has thus far been conceptualized as primarily a water reallocation project. These two forces are directly linked by the influence of water flows on fire fuel moisture content, and are indirectly linked through a series of complex feedback loops. This interaction is made more complex by the alteration and compartmentalization of current water flows and fire regimes, the lack of communication between water and fire management agencies, and the already imperiled state of many local species. It is unlikely, therefore, that restoring water flows will automatically restore the appropriate fire regimes, leaving the prospect of successful restoration in some doubt. The decline of the Cape Sable seaside sparrow, and its potential for recovery, illustrates the complexity of the situation.

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While the existence of black carbon as part of dissolved organic matter (DOM) has been confirmed, quantitative determinations of dissolved black carbon (DBC) in freshwater ecosystem and information on factors controlling its concentration are scarce. In this study, stream surface water samples from a series of watersheds subject to different burn frequencies in Konza Prairie (Kansas, USA) were collected in order to determine if recent fire history has a noticeable effect on DBC concentration. The DBC levels detected ranged from 0.04 to 0.11 mg L−1, accounting for ca. 3.32 ± 0.51% of dissolved organic carbon (DOC). No correlation was found between DBC concentration and neither fire frequency nor time since last burn. We suggest that limited DBC flux is related to high burning efficiency, possibly greater export during periods of high discharge and/or the continuous export of DBC over long time scales. A linear correlation between DOC and DBC concentrations was observed, suggesting the export mechanisms determining DOC and DBC concentrations are likely coupled. The potential influence of fire history was less than the influence of other factors controlling the DOC and DBC dynamics in this ecosystem. Assuming similar conditions and processes apply in grasslands elsewhere, extrapolation to a global scale would suggest a global grasslands flux of DBC on the order of 0.14 Mt carbon year−1.

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Within the marl prairie grasslands of the Florida Everglades, USA, the combined effects of fire and flooding usually lead to very significant changes in tree island structure and composition. Depending on fire severity and post-fire hydroperiod, these effects vary spatially and temporally throughout the landscape, creating a patchy post-fire mosaic of tree islands with different successional states. Through the use of the Normalized Difference Vegetation Index (NDVI) and three predictor variables (marsh water table elevation at the time of fire, post-fire hydroperiod, and tree island size), along with logistic regression analysis, we examined the probability of tree island burning and recovering following the Mustang Corner Fire (May to June 2008) in Everglades National Park. Our data show that hydrologic conditions during and after fire, which are under varying degrees of management control, can lead to tree island contraction or loss. More specifically, the elevation of the marsh water table at the time of the fire appears to be the most important parameter determining the severity of fire in marl prairie tree islands. Furthermore, in the post-fire recovery phase, both tree island size and hydroperiod during the first year after the fire played important roles in determining the probability of tree island recovery, contraction, or loss.

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The Chihuahua desert is one of the most biologically diverse ecosystems in the world, but suffers serious degradation because of changes in fire regimes resulting in large catastrophic fires. My study was conducted in the Sierra La Mojonera (SLM) natural protected area in Mexico. The purpose of this study was to implement the use of FARSITE fire modeling as a fire management tool to develop an integrated fire management plan at SLM. Firebreaks proved to detain 100% of wildfire outbreaks. The rosetophilous scrub experienced the fastest rate of fire spread and lowland creosote bush scrub experienced the slowest rate of fire spread. March experienced the fastest rate of fire spread, while September experienced the slowest rate of fire spread. The results of my study provide a tool for wildfire management through the use geospatial technologies and, in particular, FARSITE fire modeling in SLM and Mexico.

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The pine rocklands of South Florida, characterized by a rich herbaceous flora with many narrowly endemic taxa beneath an overstory of south Florida slash pine (Pinus elliottii var. densa), are found in three areas: the Miami Rock Ridge of southeastern peninsular Florida, the Lower Florida Keys, and slightly elevated portions of the southern Big Cypress National Preserve. Fire is an important element in these ecosystems, since in its absence the pine canopy is likely to be replaced by dense hardwoods, resulting in loss of the characteristic pineland herb flora. Prescribed fire has been used in Florida Keys pine forests since the creation of the National Key Deer Refuge (NKDR), with the primary aim of reducing fuels. Because fire can also be an effective tool in shaping ecological communities, we conducted a 4-year research study which explored a range of fire management options in NKDR. The intent of the study was to provide the Fish and Wildlife Service and other land managers with information regarding when and where to burn in order to perpetuate these unique forests.

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I investigated the phenology and breeding systems of two Florida endemic pawpaws, Asimina reticulata, widespread in peninsular Florida, and A. tetramera, a federally endangered species limited to two counties on the Atlantic Coastal Ridge. The purpose of this study was to determine if differences contribute to the rarity of Asimina tetramera compared with A. reticulata. The study was conducted in sand pine scrub sites with the largest populations of A. tetramera in the two counties. Flowering seasons differ for the two species. Both species are hermaphroditic and strongly protogynous. Pollination experiments show that neither species is autogamous and the primary breeding mechanism is outcrossing, although low levels of geitonogamous pollination occur in mature scrub habitats. High levels of inbreeding depression were noted in both species at both sites but inbreeding depression was relaxed the first year post-fire. Fruit set in mature habitats may be pollinator limited. ^ I studied insects associated with the flowers in sand pine scrub habitat in southeastern Florida from 1994–1996. The most commonly represented orders were Coleoptera (25 spp.), Lepidoptera. (3 spp.) and Hymenoptera. (3 spp.). All Coleoptera. were flower visitors; one species, Euphoria sepulchralis (Fabricius)(Scarabeaidae), visited flowers of the two Asimina species at both sites. Eurytides marcellus (Cramer) (Lepidoptera: Papilionidae) eggs and larvae were observed on both species of Asimina during each year of the study. ^ Resource management techniques were applied to a mature sand pine scrub community in Jonathan Dickinson State Park in southeastern Florida for the management of Asimina tetramera. Manipulations conducted in 1996 included combinations of fire and mechanical treatments. I measured effects of these treatments on flowering and fruit set on A. tetramera and found cutting and burning was most effective in increasing flowering, followed by burning. Mechanical cutting and mulching had no significant effect. ^

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Fire is a globally distributed disturbance that impacts terrestrial ecosystems and has been proposed to be a global “herbivore.” Fire, like herbivory, is a top-down driver that converts organic materials into inorganic products, alters community structure, and acts as an evolutionary agent. Though grazing and fire may have some comparable effects in grasslands, they do not have similar impacts on species composition and community structure. However, the concept of fire as a global herbivore implies that fire and herbivory may have similar effects on plant functional traits. Using 22 years of data from a mesic, native tallgrass prairie with a long evolutionary history of fire and grazing, we tested if trait composition between grazed and burned grassland communities would converge, and if the degree of convergence depended on fire frequency. Additionally, we tested if eliminating fire from frequently burned grasslands would result in a state similar to unburned grasslands, and if adding fire into a previously unburned grassland would cause composition to become more similar to that of frequently burned grasslands. We found that grazing and burning once every four years showed the most convergence in traits, suggesting that these communities operate under similar deterministic assembly rules and that fire and herbivory are similar disturbances to grasslands at the trait-group level of organization. Three years after reversal of the fire treatment we found that fire reversal had different effects depending on treatment. The formerly unburned community that was then burned annually became more similar to the annually burned community in trait composition suggesting that function may be rapidly restored if fire is reintroduced. Conversely, after fire was removed from the annually burned community trait composition developed along a unique trajectory indicating hysteresis, or a time lag for structure and function to return following a change in this disturbance regime. We conclude that functional traits and species-based metrics should be considered when determining and evaluating goals for fire management in mesic grassland ecosystems.

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This research first evaluated the effects of urban wildland interface on reproductive biology of the Big Pine Partridge Pea, Chamaecrista keyensis, an understory herb that is endemic to Big Pine Key, Florida. I found that C. keyensis was self-compatible, but depended on bees for seed set. Furthermore, individuals of C. keyensis in urban habitats suffered higher seed predation and therefore set fewer seeds than forest interior plants. ^ I then focused on the effects of fire at different times of the year, summer (wet) and winter (dry), on the population dynamics and population viability of C. keyensis. I found that C. keyensis population recovered faster after winter burns and early summer burns (May–June) than after late summer burns (July–September) due to better survival and seedling recruitment following former fires. Fire intensity had positive effects on reproduction of C. keyensis. In contrast, no significant fire intensity effects were found on survival, growth, and seedling recruitment. This indicated that better survival and seedling recruitment following winter and early summer burns (compared with late summer burns) were due to the reproductive phenology of the plant in relation to fires rather than differences in fire intensity. Deterministic population modeling showed that time since fire significantly affected the finite population growth rates (λ). Particularly, recently burned plots had the largest λ. In addition, effects of timing of fires on λ were most pronounced the year of burn, but not the subsequent years. The elasticity analyses suggested that maximizing survival is an effective way to minimize the reduction in finite population growth rate the year of burn. Early summer fires or dry-season fires may achieve this objective. Finally, stochastic simulations indicated that the C. keyensis population had lower extinction risk and population decline probability if burned in the winter than in the late summer. A fire frequency of approximately 7 years would create the lowest extinction probability for C. keyensis. A fire management regime including a wide range of burning seasons may be essential for the continued existence of C. keyensis and other endemic species of pine rockland on Big Pine Key. ^

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The pine rocklands of South Florida are characterized by an herbaceous flora with many narrowly endemic taxa, a diverse shrub layer containing several palms and numerous tropical hardwoods, and an overstory of south Florida slash pine (Pinus elliottii var. densa). Fire has been considered as an important environmental factor for these ecosystems, since in the absence of fire these pine forests are replaced by dense hardwood communities, resulting in loss of the characteristic pineland herb flora. Hence, in the Florida Keys pine forests, prescribed fire has been used since the creation of the National Key Deer Refuge. However, such prescribed burns were conducted in the Refuge mainly for fuel reduction, without much consideration of ecological factors. The USGS and Florida International University conducted a research study for four years, from 1998 to 2001, the objective of which was to document the response of pine rockland vegetation to a range of fire management options and to provide Fish and Wildlife Service and other land managers with information useful in deciding when and where to burn to perpetuate these unique pine forests. This study is described in detail in Snyder et al. (2005).

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Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

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This document summarizes the activities that were accomplished in FY 2009 on the research project “Cape Sable seaside sparrow habitat – Vegetation Monitoring”, a collaborative effort among the US Army Corps of Engineers, Florida International University, and the US Geological Survey. The major activities in 2009 included field work, data analysis and presentations. The results of 2009 field work were presented at the 4th International Congress of Fire Ecology and Management, Savannah, GA from November 30 to Dec 5, 2009 and at the Cape Sable seaside sparrow (CSSS) Fire Meeting, held at the Krome Center, Homestead, FL on December 8, 2009. Field sampling was conducted between March 23 and June 3, 2009, during which we resurveyed 234 sites: 191 Census sites, 3 sites on Transect B, 7 sites on Transect D, and 33 sites on Transect F. The number of sites sampled in 2009 was higher than in any previous year, primarily because a large number of sites burned in Mustang Corner fire and three other wild fires in 2008 were included in 2009 sampling. At all sites surveyed in 2009, we recorded structural and compositional vegetation parameters following the methods used in previous years (2003-2008) and tagged shrubs and trees (woody plants > 1 m) present in the 5 x 60 m plots. In addition, for the first time, we measured height of sawgrass (Cladium jamaicense) stubble in the compositional plots at the sites that were burned in 2008. Field data were entered by field crews, and were thoroughly checked by Jay Sah (Co-PI) to ensure that the data were complete, correct, and compliant with sampling methodologies. The data are stored under a project folder on a shared network drive maintained by the Southeast Environmental Research Center (SERC) at FIU. The shared network drive is backed up daily.

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Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as f-test is performed during each node’s split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

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The purpose of this research was to study interfering products in fire debris analysis, including their identification and characterization. Different substrates were classified, burned, extracted and analyzed in order to identify all the interfering products that they may release. It has been shown that these products come from three different sources: substrate background products, pyrolysis products and possibly combustion products. Different parameters in the creation of these products were evaluated such as the extinguishment process as well as the weathering of the sample prior to the analysis. It has been shown that the presence of these products is not always constant and thus, makes it difficult to extrapolate data to similar cases. Furthermore, some of these products are similar to the ones found in ignitable liquids. Finally, it shows one more time how important it is to collect and analyze control samples in fire debris analysis. ^

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Fire, which affects community structure and composition at all trophic levels, is an integral component of the Everglades ecosystem (Wade et al. 1980; Lockwood et al. 2003). Without fire, the Everglades as we know it today would be a much different place. This is particularly true for the short-hydroperiod marl prairies that predominate on the eastern and western flanks of Shark River Slough, Everglades National Park (Figure 1). In general, fire in a tropical or sub-tropical grassland community favors the dominance of C4 grasses over C3 species (Roscoe et al. 2000; Briggs et al. 2005). Within this pyrogenic graminoid community also, periodic natural fires, together with suitable hydrologic regime, maintain and advance the dominance of C4 vs C3 graminoids (Sah et al. 2008), and suppress the encroachment of woody stems (Hanan et al. 2009; Hanan et al. unpublished manuscript) originating from the tree islands that, in places, dominate the landscape within this community. However, fires, under drought conditions and elevated fuel loads, can spread quickly throughout the landscape, oxidizing organic soils, both in the prairie and in the tree islands, and, in the process, lead to shifts in vegetation composition. This is particularly true when a fire immediately precedes a flood event (Herndon et al. 1991; Lodge 2005; Sah et al. 2010), or if so much soil is consumed during the fire that the hydrologic regime is permanently altered as a result of a decrease in elevation (Zaffke 1983).