Mud, algae or seagrass: An assessment of remote sensing techniques for mapping inter-tidal seagrass cover and composition in turbid tropical environments

Large areas of tropical sub- and inter-tidal seagrass beds occur in highly turbid environments and cannot be mapped through the water column. The purpose of this project was to determine if and how airborne and satellite imaging systems could be used to map inter-tidal seagrass properties along the wet-tropics coast in north Queensland, Australia. The work aimed to: (1) identify the minimum level of seagrass foliage cover that could be detected from airborne and satellite imagery; and (2) define the minimum detectable differences in seagrass foliage cover in exposed intertidal seagrass beds. High resolution spectral-reflectance data (2040 bands, 350 – 2500nm) were collected over 40cm diameter plots from 240 sites on Magnetic Island, Pallarenda Beach and Green Island in North Queensland at spring low tides in April 2006. The seagrass species sampled were: Thalassia hemprechii, Halophila ovalis, Halodule uninerivs; Syringodium isoetifolium, Cymodocea serrulata, and Cymodoea rotundata. Digital photos were captured for each plot and used to derive estimates of seagrass species cover, epiphytic growth, micro- and macro-algal cover, and substrate colour. Sediment samples were also collected and analysed to measure the concentration of Chlorophyll-a associated with benthic micro-algae. The field reflectance spectra were analysed in combination with their corresponding seagrass species foliage cover levels to establish the minimum foliage projective cover required for each seagrass to be significantly different from bare substrate and substrate with algal cover. This analysis was repeated with reflectance spectra resampled to the bandpass functions of Quickbird, Ikonos, SPOT 5 and Landsat 7 ETM. Preliminary results indicate that conservative minimum detectable seagrass cover levels across most the species sampled were between 30%- 35% on dark substrates. Further analysis of these results will be conducted to determine their separability and satellite images and to assess the effects epiphytes and algal cover.

Families 'at risk' and the family nurse partnership:the intrusion of risk into social exclusion policy

This article considers why the family nurse partnership (FNP) has been promoted as a means of tackling social exclusion in the UK. The FNP consists in a programme of visits by nurses to low-income first-time mothers, both while the mothers are pregnant and for the first two years following birth. The FNP is focused on both teaching parenthood and encouraging mothers back into education and/or into employment. Although the FNP marks a considerable discontinuity with previous approaches to family health, it is congruent with an emerging new approach to social exclusion. This new approach maintains that the most important task of social policy is to identify quickly the most 'at-risk' households, individuals and children so that interventions can be targeted more effectively at those 'at risk', either to themselves or to others. The article illustrates this new approach by analysing a succession of reports by the Social Exclusion Unit. It indicates that there is a considerable amount of ambiguity about the relationship between specific risk-factors and being 'at risk of social exclusion'. Nonetheless, this new approach helps to explain why British policy-makers may have chosen to promote the new FNP now. © 2009 Cambridge University Press.

On Handling Replay Attacks in Intrusion Detection Systems

We propose a method for detecting and analyzing the so-called replay attacks in intrusion detection systems, when an intruder contributes a small amount of hostile actions to a recorded session of a legitimate user or process, and replays this session back to the system. The proposed approach can be applied if an automata-based model is used to describe behavior of active entities in a computer system.

Classification Trees as a Technique for Creating Anomaly-Based Intrusion Detection Systems

Intrusion detection is a critical component of security information systems. The intrusion detection process attempts to detect malicious attacks by examining various data collected during processes on the protected system. This paper examines the anomaly-based intrusion detection based on sequences of system calls. The point is to construct a model that describes normal or acceptable system activity using the classification trees approach. The created database is utilized as a basis for distinguishing the intrusive activity from the legal one using string metric algorithms. The major results of the implemented simulation experiments are presented and discussed as well.

Development of a mathematical and computer model to assess water quality impacts of hazardous compounds from minor gasoline spills in the inter-tidal zone of the Miami River, Florida

The objective of this study was to develop a model to predict transport and fate of gasoline components of environmental concern in the Miami River by mathematically simulating the movement of dissolved benzene, toluene, xylene (BTX), and methyl-tertiary-butyl ether (MTBE) occurring from minor gasoline spills in the inter-tidal zone of the river. Computer codes were based on mathematical algorithms that acknowledge the role of advective and dispersive physical phenomena along the river and prevailing phase transformations of BTX and MTBE. Phase transformations included volatilization and settling. ^ The model used a finite-difference scheme of steady-state conditions, with a set of numerical equations that was solved by two numerical methods: Gauss-Seidel and Jacobi iterations. A numerical validation process was conducted by comparing the results from both methods with analytical and numerical reference solutions. Since similar trends were achieved after the numerical validation process, it was concluded that the computer codes algorithmically were correct. The Gauss-Seidel iteration yielded at a faster convergence rate than the Jacobi iteration. Hence, the mathematical code was selected to further develop the computer program and software. The model was then analyzed for its sensitivity. It was found that the model was very sensitive to wind speed but not to sediment settling velocity. ^ A computer software was developed with the model code embedded. The software was provided with two major user-friendly visualized forms, one to interface with the database files and the other to execute and present the graphical and tabulated results. For all predicted concentrations of BTX and MTBE, the maximum concentrations were over an order of magnitude lower than current drinking water standards. It should be pointed out, however, that smaller concentrations than the latter reported standards and values, although not harmful to humans, may be very harmful to organisms of the trophic levels of the Miami River ecosystem and associated waters. This computer model can be used for the rapid assessment and management of the effects of minor gasoline spills on inter-tidal riverine water quality. ^

Ensemble fuzzy belief intrusion detection design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems: Implications for predictive uncertainty and data collection

Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. ^ The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. ^ The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection. ^

Adsorption and desorption of phosphate on limestone in experiments simulating seawater intrusion

This study investigates the potential release of from carbonate aquifers exposed to seawater intrusion. Adsorption and desorption of in the presence of deionized water (DIW) and seawater were conducted on a large block of Pleistocene age limestone to simulate the effects of seawater intrusion into a coastal carbonate aquifer at the laboratory scale. The limestone showed strong adsorption of in DIW, while adsorption was significantly less in the presence of seawater. Dissolution of CaCO3 was found to prevent adsorption at salinities less than 30 psu. Adsorption of was limited at higher salinities (30–33 psu), due to competition with ions for adsorption sites. At a salinity3 precipitated. Concentrations of between 2 and 5 μmol/L were released by desorption when the limestone was exposed to seawater. The results of this study suggest that as seawater intrudes into an originally freshwater coastal aquifer, adsorbed may be released into the groundwater. Consequently, adsorbed is expected to be released from coastal carbonate aquifers world-wide as sea level continues to rise exposing more of the freshwater aquifer to seawater.

A tidal creek water budget: Estimation of groundwater discharge and overland flow using hydrologic modeling in the Southern Everglades

Taylor Slough is one of the natural freshwater contributors to Florida Bay through a network of microtidal creeks crossing the Everglades Mangrove Ecotone Region (EMER). The EMER ecological function is critical since it mediates freshwater and nutrient inputs and controls the water quality in Eastern Florida Bay. Furthermore, this region is vulnerable to changing hydrodynamics and nutrient loadings as a result of upstream freshwater management practices proposed by the Comprehensive Everglades Restoration Program (CERP), currently the largest wetland restoration project in the USA. Despite the hydrological importance of Taylor Slough in the water budget of Florida Bay, there are no fine scale (∼1 km2) hydrodynamic models of this system that can be utilized as a tool to evaluate potential changes in water flow, salinity, and water quality. Taylor River is one of the major creeks draining Taylor Slough freshwater into Florida Bay. We performed a water budget analysis for the Taylor River area, based on long-term hydrologic data (1999–2007) and supplemented by hydrodynamic modeling using a MIKE FLOOD (DHI,http://dhigroup.com/) model to evaluate groundwater and overland water discharges. The seasonal hydrologic characteristics are very distinctive (average Taylor River wet vs. dry season outflow was 6 to 1 during 1999–2006) with a pronounced interannual variability of flow. The water budget shows a net dominance of through flow in the tidal mixing zone, while local precipitation and evapotranspiration play only a secondary role, at least in the wet season. During the dry season, the tidal flood reaches the upstream boundary of the study area during approximately 80 days per year on average. The groundwater field measurements indicate a mostly upwards-oriented leakage, which possibly equals the evapotranspiration term. The model results suggest a high importance of groundwater contribution to the water salinity in the EMER. The model performance is satisfactory during the dry season where surface flow in the area is confined to the Taylor River channel. The model also provided guidance on the importance of capturing the overland flow component, which enters the area as sheet flow during the rainy season. Overall, the modeling approach is suitable to reach better understanding of the water budget in the mangrove region. However, more detailed field data is needed to ascertain model predictions by further calibrating overland flow parameters.

Summertime Influences of Tidal Energy Advection on the Surface Energy Balance in a Mangrove Forest

Mangrove forests are ecosystems susceptible to changing water levels and temperatures due to climate change as well as perturbations resulting from tropical storms. Numerical models can be used to project mangrove forest responses to regional and global environmental changes, and the reliability of these models depends on surface energy balance closure. However, for tidal ecosystems, the surface energy balance is complex because the energy transport associated with tidal activity remains poorly understood. This study aimed to quantify impacts of tidal flows on energy dynamics within a mangrove ecosystem. To address the research objective, an intensive 10-day study was conducted in a mangrove forest located along the Shark River in the Everglades National Park, FL, USA. Forest–atmosphere turbulent exchanges of energy were quantified with an eddy covariance system installed on a 30-m-tall flux tower. Energy transport associated with tidal activity was calculated based on a coupled mass and energy balance approach. The mass balance included tidal flows and accumulation of water on the forest floor. The energy balance included temporal changes in enthalpy, resulting from tidal flows and temperature changes in the water column. By serving as a net sink or a source of available energy, flood waters reduced the impact of high radiational loads on the mangrove forest. Also, the regression slope of available energy versus sink terms increased from 0.730 to 0.754 and from 0.798 to 0.857, including total enthalpy change in the water column in the surface energy balance for 30-min periods and daily daytime sums, respectively. Results indicated that tidal inundation provides an important mechanism for heat removal and that tidal exchange should be considered in surface energy budgets of coastal ecosystems. Results also demonstrated the importance of including tidal energy advection in mangrove biophysical models that are used for predicting ecosystem response to changing climate and regional freshwater management practices.

Biogeochemical Effects of Simulated Sea Level Rise on Carbon Loss in an Everglades Mangrove Peat Soil

Saltwater intrusion and inundation can affect soil microbial activity, which regulates the carbon (C) balance in mangroves and helps to determine if these coastal forests can keep pace with sea level rise (SLR). This study evaluated the effects of increased salinity (+15 ppt), increased inundation (−8 cm), and their combination, on soil organic C loss from a mangrove peat soil (Everglades, Florida, USA) under simulated tides. Soil respiration (CO2 flux), methane (CH4) flux, dissolved organic carbon (DOC) production, and porewater nutrient concentrations were quantified. Soil respiration was the major pathway of soil organic C loss (94–98%) and was approximately 90% higher in the control water level than the inundated treatment under elevated salinity. Respiration rate increased with water temperature, but depended upon salinity and tidal range. CH4 flux was minimal, while porewater DOC increased with a concomitant, significant decline in soil bulk density under increased inundation. Porewater ammonium increased (73%) with inundation and soluble reactive phosphorus increased (32%) with salinity. Overall, the decline in soil organic C mineralization from combined saltwater intrusion and prolonged inundation was not significant, but results suggest SLR could increase this soil’s susceptibility to peat collapse and accelerate nutrient and DOC export to adjacent Florida Bay.