Regional processes in mangrove ecosystems: spatial scaling relationships, biomass, and turnover rates following catastrophic disturbance

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.

Surface mean flow and turbulence structure in tropical cyclone winds

Hurricanes are one of the deadliest and costliest natural hazards affecting the Gulf coast and Atlantic coast areas of the United States. An effective way to minimize hurricane damage is to strengthen structures and buildings. The investigation of surface level hurricane wind behavior and the resultant wind loads on structures is aimed at providing structural engineers with information on hurricane wind characteristics required for the design of safe structures. Information on mean wind profiles, gust factors, turbulence intensity, integral scale, and turbulence spectra and co-spectra is essential for developing realistic models of wind pressure and wind loads on structures. The research performed for this study was motivated by the fact that considerably fewer data and validated models are available for tropical than for extratropical storms. ^ Using the surface wind measurements collected by the Florida Coastal Monitoring Program (FCMP) during hurricane passages over coastal areas, this study presents comparisons of surface roughness length estimates obtained by using several estimation methods, and estimates of the mean wind and turbulence structure of hurricane winds over coastal areas under neutral stratification conditions. In addition, a program has been developed and tested to systematically analyze Wall of Wind (WoW) data, that will make it possible to perform analyses of baseline characteristics of flow obtained in the WoW. This program can be used in future research to compare WoW data with FCMP data, as gust and turbulence generator systems and other flow management devices will be used to create WoW flows that match as closely as possible real hurricane wind conditions. ^ Hurricanes are defined as tropical cyclones for which the maximum 1-minute sustained surface wind speeds exceed 74 mph. FCMP data include data for tropical cyclones with lower sustained speeds. However, for the winds analyzed in this study the speeds were sufficiently high to assure that neutral stratification prevailed. This assures that the characteristics of those winds are similar to those prevailing in hurricanes. For this reason in this study the terms tropical cyclones and hurricanes are used interchangeably. ^

Spatial scale and abundance patterns of large fish communities in freshwater marshes of the Florida Everglades

Anthropogenic habitat alterations and water-management practices have imposed an artificial spatial scale onto the once contiguous freshwater marshes of the Florida Everglades. To gain insight into how these changes may affect biotic communities, we examined whether variation in the abundance and community structure of large fishes (SL . 8 cm) in Everglades marshes varied more at regional or intraregional scales, and whether this variation was related to hydroperiod, water depth, floating mat volume, and vegetation density. From October 1997 to October 2002, we used an airboat electrofisher to sample large fishes at sites within three regions of the Everglades. Each of these regions is subject to unique watermanagement schedules. Dry-down events (water depth , 10 cm) occurred at several sites during spring in 1999, 2000, 2001, and 2002. The 2001 dry-down event was the most severe and widespread. Abundance of several fishes decreased significantly through time, and the number of days post-dry-down covaried significantly with abundance for several species. Processes operating at the regional scale appear to play important roles in regulating large fishes. The most pronounced patterns in abundance and community structure occurred at the regional scale, and the effect size for region was greater than the effect size for sites nested within region for abundance of all species combined, all predators combined, and each of the seven most abundant species. Non-metric multi-dimensional scaling revealed distinct groupings of sites corresponding to the three regions. We also found significant variation in community structure through time that correlated with the number of days post-dry-down. Our results suggest that hydroperiod and water management at the regional scale influence large fish communities of Everglades marshes.

Population structure of spotted sunfish (Lepomis punctatus) in the Florida Everglades as revealed by DNA microsatellite analysis

Genetic diversity can be used to describe patterns of gene flow within and between local and regional populations. The Florida Everglades experiences seasonal fluctuations in water level that can influence local population extinction and recolonization dynamics. In addition, this expansive wetland has been divided into water management regions by canals and levees. These combined factors can affect genetic diversity and population structure of aquatic organisms in the Everglades. We analyzed allelic variation at six DNA microsatellite loci to examine the population structure of spotted sunfish (Lepomis punctatus) from the Everglades. We tested the hypothesis that recurrent local extinction and recent regional divisions have had an effect on patterns of genetic diversity. No marked differences were observed in comparisons of the heterozygosity values of sites within and among water management units. No evidence of isolation by distance was detected in a gene flow and distance correlation between subpopulations. Confidence intervals for the estimated F-statistic values crossed zero, indicating that there was no significant genetic difference between subpopulations within a region or between regions. Notably, the genetic variation among subpopulations in a water conservation area was greater than variation among regions (Fsp>FPT). These data indicate that the spatial scale of recolonization following local extinction appears to be most important within water management units.

Towards simulation and emulation of large-scale computer networks

Developing analytical models that can accurately describe behaviors of Internet-scale networks is difficult. This is due, in part, to the heterogeneous structure, immense size and rapidly changing properties of today's networks. The lack of analytical models makes large-scale network simulation an indispensable tool for studying immense networks. However, large-scale network simulation has not been commonly used to study networks of Internet-scale. This can be attributed to three factors: 1) current large-scale network simulators are geared towards simulation research and not network research, 2) the memory required to execute an Internet-scale model is exorbitant, and 3) large-scale network models are difficult to validate. This dissertation tackles each of these problems. ^ First, this work presents a method for automatically enabling real-time interaction, monitoring, and control of large-scale network models. Network researchers need tools that allow them to focus on creating realistic models and conducting experiments. However, this should not increase the complexity of developing a large-scale network simulator. This work presents a systematic approach to separating the concerns of running large-scale network models on parallel computers and the user facing concerns of configuring and interacting with large-scale network models. ^ Second, this work deals with reducing memory consumption of network models. As network models become larger, so does the amount of memory needed to simulate them. This work presents a comprehensive approach to exploiting structural duplications in network models to dramatically reduce the memory required to execute large-scale network experiments. ^ Lastly, this work addresses the issue of validating large-scale simulations by integrating real protocols and applications into the simulation. With an emulation extension, a network simulator operating in real-time can run together with real-world distributed applications and services. As such, real-time network simulation not only alleviates the burden of developing separate models for applications in simulation, but as real systems are included in the network model, it also increases the confidence level of network simulation. This work presents a scalable and flexible framework to integrate real-world applications with real-time simulation.^

Spatiotemporal patterns in community structure of macroinvertebrates inhabiting calcareous periphyton mats

Calcareous floating periphyton mats in the southern Everglades provide habitat for a diverse macroinvertebrate community that has not been well characterized. Our study described this community in an oligotrophic marsh, compared it with the macroinvertebrate community associated with adjacent epiphytic algae attached to macrophytes in the water column, and detected spatial patterns in density and community structure. The floating periphyton mat (floating mat) and epiphytic algae in the water column (submerged epiphyton) were sampled at 4 sites (1 km apart) in northern Shark River Slough, Everglades National Park (ENP), in the early (July) and late (November) wet season. Two perpendicular 90-m transects were established at each site and 100 samples were taken in a nested design. Sites were located in wet-prairie spikerush-dominated sloughs with similar water depths and emergent macrophyte communities. Floating mats were sampled by taking cores (6-cm diameter) that were sorted under magnification to enumerate infauna retained on a 250-μm-mesh sieve and with a maximum dimension >1 mm. Our results showed that floating mats provide habitat for a macroinvertebrate community with higher densities (no. animals/g ash-free dry mass) of Hyalella azteca, Dasyhelea spp., and Cladocera, and lower densities of Chironomidae and Planorbella spp. than communities associated with submerged epiphyton. Densities of the most common taxa increased 3× to 15× from early to late wet season, and community differences between the 2 habitat types became more pronounced. Floating-mat coverage and estimated floating-mat biomass increased 20 to 30% and 30 to 110%, respectively, at most sites in the late wet season. Some intersite variation was observed in individual taxa, but no consistent spatial pattern in any taxon was detected at any scale (from 0.2 m to 3 km). Floating mats and their resident macroinvertebrate communities are important components in the Everglades food web. This community should be included in environmental monitoring programs because degradation and eventual loss of the calcareous periphyton mat is associated with P enrichment in this ecosystem.

Disturbance frequency and community structure in a twenty-five year intervention study

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.

Ecosystem structure, nutrient dynamics, and hydrologic relationships in tree islands of the southern Everglades, Florida, USA

Tree islands are an important structural component of many graminoid-dominated wetlands because they increase ecological complexity in the landscape. Tree island area has been drastically reduced with hydrologic modifications within the Everglades ecosystem, yet still little is known about the ecosystem ecology of Everglades tree islands. As part of an ongoing study to investigate the effects of hydrologic restoration on short hydroperiod marshes of the southern Everglades, we report an ecosystem characterization of seasonally flooded tree islands relative to locations described by variation in freshwater flow (i.e. locally enhanced freshwater flow by levee removal). We quantified: (1) forest structure, litterfall production, nutrient utilization, soil dynamics, and hydrologic properties of six tree islands and (2) soil and surface water physico-chemical properties of adjacent marshes. Tree islands efficiently utilized both phosphorus and nitrogen, but indices of nutrient-use efficiency indicated stronger P than N limitation. Tree islands were distinct in structure and biogeochemical properties from the surrounding marsh, maintaining higher organically bound P and N, but lower inorganic N. Annual variation resulting in increased hydroperiod and lower wet season water levels not only increased nitrogen use by tree species and decreased N:P values of the dominant plant species (Chrysobalanus icaco), but also increased soil pH and decreased soil temperature. When compared with other forested wetlands, these Everglades tree islands were among the most nutrient efficient, likely a function of nutrient immobilization in soils and the calcium carbonate bedrock. Tree islands of our study area are defined by: (1) unique biogeochemical properties when compared with adjacent short hydroperiod marshes and other forested wetlands and (2) an intricate relationship with marsh hydrology. As such, they may play an important and disproportionate role in nutrient and carbon cycling in Everglades wetlands. With the loss of tree islands that has occurred with the degradation of the Everglades system, these landscape processes may have been altered. With this baseline dataset, we have established a long-term ecosystem-scale experiment to follow the ecosystem trajectory of seasonally flooded tree islands in response to hydrologic restoration of the southern Everglades.

Drivers of Decadal-Scale Change in Southern Everglades Wetland Macrophyte Communities of the Coastal Ecotone

Understanding the relationships between hydrology and salinity and plant community structure and production is critical to allow predictions of wetland responses to altered water management, changing precipitation patterns and rising sea-level. We addressed how salinity, water depth, hydroperiod, canal inflows, and local precipitation control marsh macrophyte aboveground net primary production (ANPP) and structure in the coastal ecotone of the southern Everglades. We contrasted responses in two watersheds - Taylor Slough (TS) and C-111 - systems that have and will continue to experience changes in water management. Based on long-term trajectories in plant responses, we found continued evidence of increasing water levels and length of inundation in the C-111 watershed south of the C-111 canal. We also found strong differentiation among sites in upper TS that was dependent on hydrology. Finally, salinity, local precipitation and freshwater discharge from upstream explained over 80 % of the variance in Cladium ANPP at a brackish water site in TS. Moreover, our study showed that, while highly managed, the TS and C-111 watersheds maintain legacies in spatial pattern that would facilitate hydrologic restoration. Based on the trajectories in Cladium and Eleocharis, shifts in plant community structure could occur within 5–10 years of sustained water management change.

Metacommunity Structure Along Resource and Disturbance Gradients in Everglades Wetlands

We evaluated metacommunity hypotheses of landscape arrangement (indicative of dispersal limitation) and environmental gradients (hydroperiod and nutrients) in structuring macroinvertebrate and fish communities in the southern Everglades. We used samples collected at sites from the eastern boundary of the southern Everglades and from Shark River Slough, to evaluate the role of these factors in metacommunity structure. We used eigenfunction spatial analysis to model community structure among sites and distance-based redundancy analysis to partition the variability in communities between spatial and environmental filters. For most animal communities, hydrological parameters had a greater influence on structure than nutrient enrichment, however both had large effects. The influence of spatial effects indicative of dispersal limitation was weak and only periphyton infauna appeared to be limited by regional dispersal. At the landscape scale, communities were well-mixed, but strongly influenced by hydrology. Local-scale species dominance was influenced by water-permanence and nutrient enrichment. Nutrient enrichment is limited to water inflow points associated with canals, which may explain its impact in this data set. Hydroperiod and nutrient enrichment are controlled by water managers; our analysis indicates that the decisions they make have strong effects on the communities at the base of the Everglades food web.

Background traffic modeling for large-scale network simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

Surface Mean Flow and Turbulence Structure in Tropical Cyclone Winds

Hurricanes are one of the deadliest and costliest natural hazards affecting the Gulf coast and Atlantic coast areas of the United States. An effective way to minimize hurricane damage is to strengthen structures and buildings. The investigation of surface level hurricane wind behavior and the resultant wind loads on structures is aimed at providing structural engineers with information on hurricane wind characteristics required for the design of safe structures. Information on mean wind profiles, gust factors, turbulence intensity, integral scale, and turbulence spectra and co-spectra is essential for developing realistic models of wind pressure and wind loads on structures. The research performed for this study was motivated by the fact that considerably fewer data and validated models are available for tropical than for extratropical storms. Using the surface wind measurements collected by the Florida Coastal Monitoring Program (FCMP) during hurricane passages over coastal areas, this study presents comparisons of surface roughness length estimates obtained by using several estimation methods, and estimates of the mean wind and turbulence structure of hurricane winds over coastal areas under neutral stratification conditions. In addition, a program has been developed and tested to systematically analyze Wall of Wind (WoW) data, that will make it possible to perform analyses of baseline characteristics of flow obtained in the WoW. This program can be used in future research to compare WoW data with FCMP data, as gust and turbulence generator systems and other flow management devices will be used to create WoW flows that match as closely as possible real hurricane wind conditions. Hurricanes are defined as tropical cyclones for which the maximum 1-minute sustained surface wind speeds exceed 74 mph. FCMP data include data for tropical cyclones with lower sustained speeds. However, for the winds analyzed in this study the speeds were sufficiently high to assure that neutral stratification prevailed. This assures that the characteristics of those winds are similar to those prevailing in hurricanes. For this reason in this study the terms tropical cyclones and hurricanes are used interchangeably.

Background Traffic Modeling for Large-Scale Network Simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.