21 resultados para Uncertainty and disturbance


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In August 1997, a large aggregation of the common sea urchin, Lytechinus variegatus, was discovered moving southward through a lush and productive seagrass monoculture of Syringodium filiforme in the Florida Keys, FL. Sea urchin densities at the grazing front were greater than 300 individuals m−2 which resulted in the overgrazing of seagrasses and a complete denuding of all vegetation from this area. The steady rate of the grazing front migration permitted the estimation of the time since disturbance for any point behind this grazing front allowing the use of a chronosequence approach to investigate the processes early on in succession of these communities. In May 1999, six north-south parallel transects were established across the disturbed seagrass communities and into the undisturbed areas south of the grazing front. Based on the measured rates of the migration of the grazing front, we grouped 60 sites into five categories (disturbed, recently grazed, active grazing front, stressed and undisturbed). The large scale loss of seagrass biomass initiated community-wide cascading effects that significantly altered resource regimes and species diversity. The loss of the seagrass canopy and subsequent death and decay of the below-ground biomass resulted in a de-stabilization of the sediments. As the sediments were eroded into the water column, turbidity significantly increased, reducing light availability and significantly reducing the sediment nitrogen pool and depleting the seed bank. The portion of the chronosequence that has had the longest period of recovery now consists of a mixed community of seagrass and macroalgae, as remnant survivors and quick colonizers coexist and jointly take advantage of the open space.

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Refuge habitats increase survival rate and recovery time of populations experiencing environmental disturbance, but limits on the ability of refuges to buffer communities are poorly understood. We hypothesized that importance of refuges in preventing population declines and alteration in community structure has a non-linear relationship with severity of disturbance. In the Florida Everglades, alligator ponds are used as refuge habitat by fishes during seasonal drying of marsh habitats. Using an 11-year record of hydrological conditions and fish abundance in 10 marshes and 34 alligator ponds from two regions of the Everglades, we sought to characterize patterns of refuge use and temporal dynamics of fish abundance and community structure across changing intensity, duration, and frequency of drought disturbance. Abundance in alligator ponds was positively related to refuge size, distance from alternative refugia (e.g. canals), and abundance in surrounding marsh prior to hydrologic disturbance. Variables negatively related to abundance in alligator ponds included water level in surrounding marsh and abundance of disturbance-tolerant species. Refuge community structure did not differ between regions because the same subset of species in both regions used alligator ponds during droughts. When time between disturbances was short, fish abundance declined in marshes, and in the region with the most spatially extensive pattern of disturbance, community structure was altered in both marshes and alligator ponds because of an increased proportion of species more resistant to disturbance. These changes in community structure were associated with increases in both duration and frequency of hydrologic disturbance. Use of refuge habitat had a modal relationship with severity of disturbance regime. Spatial patterns of response suggest that decline in refuge use was because of decreased effectiveness of refuge habitat in reducing mortality and providing sufficient time for recovery for fish communities experiencing reduced time between disturbance events.

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Models of community regulation commonly incorporate gradients of disturbance inversely related to the role of biotic interactions in regulating intermediate trophic levels. Higher trophic-level organisms are predicted to be more strongly limited by intermediate levels of disturbance than are the organisms they consume. We used a manipulation of the frequency of hydrological disturbance in an intervention analysis to examine its effects on small-fish communities in the Everglades, USA. From 1978 to 2002, we monitored fishes at one long-hydroperiod (average 350 days) and at one short-hydroperiod (average 259 days; monitoring started here in 1985) site. At a third site, managers intervened in 1985 to diminish the frequency and duration of marsh drying. By the late 1990s, the successional dynamics of density and relative abundance at the intervention site converged on those of the long-hydroperiod site. Community change was manifested over 3 to 5 years following a dry-down if a site remained inundated; the number of days since the most recent drying event and length of the preceding dry period were useful for predicting population dynamics. Community dissimilarity was positively correlated with the time since last dry. Community dynamics resulted from change in the relative abundance of three groups of species linked by life-history responses to drought. Drought frequency and intensity covaried in response to hydrological manipulation at the landscape scale; community-level successional dynamics converged on a relatively small range of species compositions when drought return-time extended beyond 4 years. The density of small fishes increased with diminution of drought frequency, consistent with disturbance-limited community structure; less-frequent drying than experienced in this study (i.e., longer return times) yields predator-dominated regulation of small-fish communities in some parts of the Everglades.

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Physiological processes and local-scale structural dynamics of mangroves are relatively well studied. Regional-scale processes, however, are not as well understood. Here we provide long-term data on trends in structure and forest turnover at a large scale, following hurricane damage in mangrove ecosystems of South Florida, U.S.A. Twelve mangrove vegetation plots were monitored at periodic intervals, between October 1992 and March 2005. Mangrove forests of this region are defined by a −1.5 scaling relationship between mean stem diameter and stem density, mirroring self-thinning theory for mono-specific stands. This relationship is reflected in tree size frequency scaling exponents which, through time, have exhibited trends toward a community average that is indicative of full spatial resource utilization. These trends, together with an asymptotic standing biomass accumulation, indicate that coastal mangrove ecosystems do adhere to size-structured organizing principles as described for upland tree communities. Regenerative dynamics are different between areas inside and outside of the primary wind-path of Hurricane Andrew which occurred in 1992. Forest dynamic turnover rates, however, are steady through time. This suggests that ecological, more-so than structural factors, control forest productivity. In agreement, the relative mean rate of biomass growth exhibits an inverse relationship with the seasonal range of porewater salinities. The ecosystem average in forest scaling relationships may provide a useful investigative tool of mangrove community biomass relationships, as well as offer a robust indicator of general ecosystem health for use in mangrove forest ecosystem management and restoration.

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Understanding who evacuates and who does not has been one of the cornerstones of research on the pre-impact phase of both natural and technological hazards. Its history is rich in descriptive illustrations focusing on lists of characteristics of those who flee to safety. Early models of evacuation focused almost exclusively on the relationship between whether warnings were heard and ultimately believed and evacuation behavior. How people came to believe these warnings and even how they interpreted the warnings were not incorporated. In fact, the individual seemed almost removed from the picture with analysis focusing exclusively on external measures. ^ This study built and tested a more comprehensive model of evacuation that centers on the decision-making process, rather than decision outcomes. The model focused on three important factors that alter and shape the evacuation decision-making landscape. These factors are: individual level indicators which exist independently of the hazard itself and act as cultural lenses through which information is heard, processed and interpreted; hazard specific variables that directly relate to the specific hazard threat; and risk perception. The ultimate goal is to determine what factors influence the evacuation decision-making process. Using data collected for 1998's Hurricane Georges, logistic regression models were used to evaluate how well the three main factors help our understanding of how individuals come to their decisions to either flee to safety during a hurricane or remain in their homes. ^ The results of the logistic regression were significant emphasizing that the three broad types of factors tested in the model influence the decision making process. Conclusions drawn from the data analysis focus on how decision-making frames are different for those who can be designated “evacuators” and for those in evacuation zones. ^

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Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.