Modeling the Potential Spread of the Recently Identified Non-Native Panther Grouper (Chromileptes altivelis)in the Atlantic Using a Cellular Automaton Approach

The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species

A geological overview of Florida

(PDF contains 80 pages.)

The A Posteriori Aspects of Estuarine Modeling

This exercise is the application of an analytical method for systematically modeling ecosystems data to observations made on a naturally eutrophic, mesohaline planktonic microcosm. The theory and experimental design are briefly outlined and the particular steps in the acutal modeling process follow. Then there is a discussion as to how the whole endeavor can be refined to culminate in models with predictive capabilities. (PDF has 16 pages.)

Modeling the Chesapeake Bay and Tributaries: a synopsis

The last decade has seen the development and application of a spectrum of physical and numerical hydrographic models of the Chesapeake Bay and its tributaries. The success of the James River Hydraulic Model has initiated the construction of an estuarine hydraulic model of the entire Chesapeake System. Numerical analogues for hydrographic behavior and contaminant dispersion in one-, two-, and three dimensional model estuaries exist for various regions of the Bay. From an engineering viewpoint, one dimensional models are sufficiently advanced to be routinely employed in aiding management decisions. Bay investigators are playing leading roles in the development of two- and three-dimensional models of estuarine flows.

A geological survey of Panama (1913)

The general plan of the surrey comprises a systematic study of the physiography, stratigraphy and structural geology, geologic history, geologic correlation, mineral resources (including coal, oil, and other fields), petrography and paleontology of the Canal Zone, and of as much of the adjacent areas of the Isthmian region as is feasible.

The Empirical Modeling of an Ecosystem

The authors have endeavored to create a verified a-posteriori model of a planktonic ecosystem. Verification of an empirically derived set of first-order, quadratic differential equations proved elusive due to the sensitivity of the model system to changes in initial conditions. Efforts to verify a similarly derived set of linear differential equations were more encouraging, yielding reasonable behavior for half of the ten ecosystem compartments modeled. The well-behaved species models gave indications as to the rate-controlling processes in the ecosystem.

Modeling Environmental Stress

The word stress when applied to ecosystems is ambiguous. Stress may be low-level, with accompanying near-linear strain, or it may be of finite magnitude, with nonlinear response and possible disintegration of the system. Since there are practically no widely accepted definitions of ecosystem strain, classification of models of stressed systems is tenuous. Despite appearances, most ecosystem models seem to fall into the low-level linear response category. Although they sometimes simulate systems behavior well, they do not provide necessary and sufficient information about sudden structural changes nor structure after transition. Dynamic models of finiteamplitude response to stress are rare because of analytical difficulties. Some idea as to future transition states can be obtained by regarding the behavior of unperturbed functions under limiting strain conditions. Preliminary work shows that, since community variables do respond in a coherent manner to stress, macroscopic analyses of stressed ecosystems offer possible alternatives to compartmental models.

Estuaries

In the following an attempt is made to outline the specific problems of modelling of estuaries as characterized by the discharge of fresh water into a partially enclosed sea water body. The hydrodynamical regime and exchange mechanisms encountered in estuaries lead to specific chemical, biological and geological processes requiring specially adapted models.

Establishing National Ocean Service Priorities for Estuarine, Coastal, and Ocean Modeling: Capabilities, Gaps, and Preliminary Prioritization Factors

This report was developed to help establish National Ocean Service priorities and chart new directions for research and development of models for estuarine, coastal and ocean ecosystems based on user-driven requirements and supportive of sound coastal management, stewardship, and an ecosystem approach to management. (PDF contains 63 pages)

Stormwater runoff - modeling impacts of urbanization and climate change

Development pressure throughout the coastal areas of the United States continues to build, particularly in the southeast (Allen and Lu 2003, Crossett et al. 2004). It is well known that development alters watershed hydrology: as land becomes covered with surfaces impervious to rain, water is redirected from groundwater recharge and evapotranspiration to stormwater runoff, and as the area of impervious cover increases, so does the volume and rate of runoff (Schueler 1994, Corbett et al. 1997). Pollutants accumulate on impervious surfaces, and the increased runoff with urbanization is a leading cause of nonpoint source pollution (USEPA 2002). Sediment, chemicals, bacteria, viruses, and other pollutants are carried into receiving water bodies, resulting in degraded water quality (Holland et al. 2004, Sanger et al. 2008). (PDF contains 5 pages)

Panel discussion: U.S. EPA using modeling and ecosystem services to enhance coastal decision making

This panel will discuss the research being conducted, and the models being used in three current coastal EPA studies being conducted on ecosystem services in Tampa Bay, the Chesapeake Bay and the Coastal Carolinas. These studies are intended to provide a broader and more comprehensive approach to policy and decision-making affecting coastal ecosystems as well as provide an account of valued services that have heretofore been largely unrecognized. Interim research products, including updated and integrated spatial data, models and model frameworks, and interactive decision support systems will be demonstrated to engage potential users and to elicit feedback. It is anticipated that the near-term impact of the projects will be to increase the awareness by coastal communities and coastal managers of the implications of their actions and to foster partnerships for ecosystem services research and applications. (PDF contains 4 pages)

Watershed monitoring and the TMDL modeling to assess bacterial loading in estuarine environments to improve management

Shellfish bed closures along the North Carolina coast have increased over the years seemingly concurrent with increases in population (Mallin 2000). More and faster flowing storm water has come to mean more bacteria, and fecal indicator bacterial (FIB) standards for shellfish harvesting are often exceeded when no source of contamination is readily apparent (Kator and Rhodes, 1994). Could management reduce bacterial loads if the source of the bacteria where known? Several potentially useful methods for differentiating human versus animal pollution sources have emerged including Ribotyping and Multiple Antibiotic Resistance (MAR) (US EPA, 2005). Total Maximum Daily Load (TMDL) studies on bacterial sources have been conducted for streams in NC mountain and Piedmont areas (U.S. EPA, 1991 and 2005) and are likely to be mandated for coastal waters. TMDL analysis estimates allowable pollutant loads and allocates them to known sources so management actions may be taken to restore water to its intended uses (U.S. EPA, 1991 and 2005). This project sought first to quantify and compare fecal contamination levels for three different types of land use on the coast, and second, to apply MAR and ribotyping techniques and assess their effectiveness for indentifying bacterial sources. Third, results from these studies would be applied to one watershed to develop a case study coastal TMDL. All three watershed study areas are within Carteret County, North Carolina. Jumping Run Creek and Pettiford Creek are within the White Oak River Basin management unit whereas the South River falls within the Neuse River Basin. Jumping Run Creek watershed encompasses approximately 320 ha. Its watershed was a dense, coastal pocosin on sandy, relic dune ridges, but current land uses are primarily medium density residential. Pettiford Creek is in the Croatan National Forest, is 1133 ha. and is basically undeveloped. The third study area is on Open Grounds Farm in the South River watershed. Half of the 630 ha. watershed is under cultivation with most under active water control (flashboard risers). The remaining portion is forested silviculture.(PDF contains 4 pages)

On distribution of pollen in lakes. [Translation from: Palynology in geological research in the Baltic Soviet Republics p113-119. Vilnius, 1973.]

Systematic investigations of the distribution of pollen in stationary water bodies until now have hardly been conducted. For clarification of the problem of how the pollen of different plants which falls into a lake is deposited in relation to its physical properties, the character of the lake, wind currents and other factors, pollen analyses were carried out of surface samples of the bottom sediments of 13 Lithuanian lakes. Lakes were selected of different sizes (areas from 2333 ha. to 8 ha.) and different depths, not uniformly overgrown, situated in different physico-geographic regions of Lithuania. As a result of the investigation, it was established that in the surface layer of the sediments of the lakes of Lithuania pollen of woody species predominates.

Age validation, growth, mortality, and demographic modeling of spotted gully shark (Triakis megalopterus) from the southeast coast of South Africa

This study documents validation of vertebral band-pair formation in spotted gully shark (Triakis megalopterus) with the use of fluorochrome injection and tagging of captive and wild sharks over a 21-year period. Growth and mortality rates of T. megalopterus were also estimated and a demographic analysis of the species was conducted. Of the 23 OTC (oxytetracycline) -marked vertebrae examined (12 from captive and 11 from wild sharks), seven vertebrae (three from captive and four from wild sharks) exhibited chelation of the OTC and fluoresced under ultraviolet light. It was concluded that a single opaque and translucent band pair was deposited annually up to at least 25 years of age, the maximum age recorded. Reader precision was assessed by using an index of average percent error calculated at 5%. No significant differences were found between male and female growth patterns (P>0.05), and von Bertalanffy growth model parameters for combined sexes were estimated to be L∞=1711.07 mm TL, k=0.11/yr and t0=–2.43 yr (n=86). Natural mortality was estimated at 0.17/yr. Age at maturity was estimated at 11 years for males and 15 years for females. Results of the demographic analysis showed that the population, in the absence of fishing mortality, was stable and not significantly different from zero and particularly sensitive to overfishing. At the current age at first capture and natural mortality rate, the fishing mortality rate required to result in negative population growth was low at F>0.004/ yr. Elasticity analysis revealed that juvenile survival was the principal factor in explaining variability in population growth rate.

A modeling approach to identify optimal habitat and suitable fishing grounds for neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean

We developed a habitat suitability index (HSI) model to understand and identify the optimal habitat and potential fishing grounds for neon f lying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Remote sensing data, including sea surface temperature, sea surface salinity, sea surface height, and chlorophyll-a concentrations, as well as fishery data from Chinese mainland squid f leets in the main fishing ground (150–165°E longitude) from August to October, from 1999 to 2004, were used. The HSI model was validated by using fishery data from 2005. The arithmetic mean modeling with three of the environmental variables—sea surface temperature, sea surface height anomaly, and chlorophyll- a concentrations—was defined as the most parsimonious HSI model. In 2005, monthly HSI values >0.6 coincided with productive fishing grounds and high fishing effort from August to October. This result implies that the model can reliably predict potential f ishing grounds for O. bartramii. Because spatially explicit fisheries and environmental data are becoming readily available, it is feasible to develop a dynamic, near real-time habitat model for improving the process of identifying potential fishing areas for and optimal habitats of neon flying squid.