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1.
PLoS One ; 10(1): e0116952, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-25574667

RESUMO

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.


Assuntos
Incêndios , Modelos Teóricos , Ecossistema , Florida , Pradaria , Umidade , Chuva , Estações do Ano , Temperatura
2.
Mar Pollut Bull ; 48(3-4): 359-70, 2004 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-14972589

RESUMO

In wetlands, oil spills may affect decomposition in soils, which controls organic matter accumulation, the primary contributor to positive elevation change. In this study we examined how oil from a spill affected organic matter decomposition in soils of a brackish intertidal marsh in Maryland. Decomposition was measured using the cellulose (cotton) strip technique. Cellulose decomposition was not affected by concentrations of different oil components (total hydrocarbons, total resolved hydrocarbons, and polycyclic aromatic hydrocarbons). Rather, other abiotic characteristics of the soil had strong effects on decomposition rates, including strong negative effects of soil depth and salinity, and a positive effect of pH. Measures of soil fertility (NH(4)-N and PO(4)-P) were not significantly related to cellulose decomposition. Thus, we conclude that decomposition was controlled more by naturally occurring environmental factors rather than by exposure to oil.


Assuntos
Celulose/metabolismo , Petróleo/metabolismo , Microbiologia do Solo , Poluentes do Solo/metabolismo , Acidentes , Ecossistema , Monitoramento Ambiental , Concentração de Íons de Hidrogênio , Maryland , Poluentes do Solo/análise , Abastecimento de Água
3.
PLoS One ; 8(9): e75946, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-24086670

RESUMO

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 (R (2) 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.


Assuntos
El Niño Oscilação Sul , Incêndios/estatística & dados numéricos , Modelos Teóricos , Chuva , Estações do Ano , Florida
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