Preliminary comparison of natural versus model-predicted recovery of vessel-generated seagrass injuries in Florida Keys National Marine Sanctuary

Each year, more than 500 motorized vessel groundings cause widespread damage to seagrasses in Florida Keys National Marine Sanctuary (FKNMS). Under Section 312 of the National Marine Sanctuaries Act (NMSA), any party responsible for the loss, injury, or destruction of any Sanctuary resource, including seagrass, is liable to the United States for response costs and resulting damages. As part of the damage assessment process, a cellular automata model is utilized to forecast seagrass recovery rates. Field validation of these forecasts was accomplished by comparing model-predicted percent recovery to that which was observed to be occurring naturally for 30 documented vessel grounding sites. Model recovery forecasts for both Thalassia testudinum and Syringodium filiforme exceeded natural recovery estimates for 93.1% and 89.5% of the sites, respectively. For Halodule wrightii, the number of over- and under-predictions by the model was similar. However, where under-estimation occurred, it was often severe, reflecting the well-known extraordinary growth potential of this opportunistic species. These preliminary findings indicate that the recovery model is consistently generous to Responsible Parties in that the model forecasts a much faster recovery than was observed to occur naturally, particularly for T. testudinum, the dominant seagrass species in the region and the species most often affected. Environmental setting (i.e., location, wave exposure) influences local seagrass landscape pattern and may also play a role in the recovery dynamics for a particular injury site. An examination of the relationship between selected environmental factors and injury recovery dynamics is currently underway. (PDF file contains 20 pages.)

Invasionsoft: a web-enabled tool for invasive species colonization predictions

Predicting and averting the spread of invasive species is a core focus of resource managers in all ecosystems. Patterns of invasion are difficult to forecast, compounded by a lack of user-friendly species distribution model (SDM) tools to help managers focus control efforts. This paper presents a web-based cellular automata hybrid modeling tool developed to study the invasion pattern of lionfish (Pterois volitans/miles) in the western Atlantic and is a natural extension our previous lionfish study. Our goal is to make publically available this hybrid SDM tool and demonstrate both a test case (P. volitans/miles) and a use case (Caulerpa taxifolia). The software derived from the model, titled Invasionsoft, is unique in its ability to examine multiple default or user-defined parameters, their relation to invasion patterns, and is presented in a rich web browser-based GUI with integrated results viewer. The beta version is not species-specific and includes a default parameter set that is tailored to the marine habitat. Invasionsoft is provided as copyright protected freeware at http://www.invasionsoft.com.

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