A planning and decision-making framework for ecological restoration

A broad and objective perspective of ecological and socioenomic knowledge is required to underlie a scientific approach to the problems of terrestrial restoration ecology. Uncertainty associated with limited scientific knowledge highlights the crucial importance of the interaction between science and policy in weighing ecological restoration alternatives in relation to other management options. In this paper, we provide a pragmatic definition for restoration ecology that is suitable for extensive terrestrial applications and present a decision framework to help organize and clarify different phases of the decision process as it is related to ecological restoration. We argue that restoration planning should include a wider spectrum of participants and decisions than have traditionally been employed.     

MATHEMATICAL MODELS: PLANNING TOOLS FOR THE GREAT LAKES1

The Great Lakes Basin Commission has initiated a Framework Study to assess the present and projected water- and related land-resource problems and demands in the Great Lakes Basin. Poorly defined objectives; incomplete and inconsistent data arrays; unknown air, biota, water, and sediment interactions; and multiple planning considerations for interconnected, large lake systems hinder objective planning. To incorporate mathematical modeling as a planning tool for the Great Lakes, a two-phase program, comprising a feasibility and design study followed by contracted and in-house modeling, data assembly, and plan development, has been initiated. The models will be used to identify sensitivities of the lakes to planning and management alternatives, insufficiencies in the data base, and inadequately understood ecosystem interactions. For the first time objective testing of resource-utilization plans to identify potential conflicts will provide a rational and cost-effective approach to Great Lakes management. Because disciplines will be interrelated, the long-term effects of planning alternatives and their impacts on neighboring lakes and states can be evaluated. Testing of the consequences of environmental accidents and increased pollution levels can be evaluated, and risks to the resource determined. Examples are cited to demonstrate the use of such planning tools.     

Seasonality of spawning by tropical anguillid eels around Sulawesi Island, Indonesia

Remarkably little is known about the life histories of the many tropical anguillid eels distributed across the Indo-Pacific region, and since the Danish expedition to study eels in the region in 1928 and 1929, research on these eels has only begun again in recent years. Sampling for anguillid leptocephali in the Indonesian Seas has been carried out recently to learn about the spawning ecology and larval distributions of tropical eels there. The leptocephali of Anguilla marmorata, Anguilla bicolor pacifica, Anguilla borneensis, Anguilla interioris, and Anguilla celebesensis were collected around Sulawesi Island both in May 2001 and October of 2002. The development of genetic identification techniques has enabled these leptocephali to be identified to species, and their distributions and sizes during different seasons indicated that there are differing life history patterns among sympatric species in the region. A. celebesensis was found to have been spawning in Tomini Bay of northeastern Sulawesi Island in March and April 2001, but apparently, no spawning had occurred in the late summer and fall of 2002. Studies on anguillid glass eels have suggested that tropical anguillids may spawn throughout much of year, but our research on leptocephali in Tomini Bay and data on the downstream migration of tropical anguillids in the major tributary to Tomini Bay indicate that A. celebesensis may have a distinct seasonal pattern of spawning possibly related to the regional monsoon cycles. This is the first evidence of seasonality of spawning in tropical anguillid eels whose life histories are only just beginning to be revealed.     

Two-dimensional numerical and eco-toxicological modeling of chemical spills

The effects of chemical spills on aquatic nontarget organisms were evaluated in this study. Based on a review of three types of current eco-toxicological models of chemicals, i.e., ACQUATOX model of the US-EPA, Hudson River Model of PCBs, and critical body residual (CBR) model and dynamic energy budget (DEBtox) model, this paper presents an uncoupled numerical ecotoxicological model. The transport and transformation of spilled chemicals were simulated by a chemical transport model (including flow and sediment transport), and the mortalities of an organism caused by the chemicals were simulated by the extended threshold damage model, separately. Due to extreme scarcity of data, this model was applied to two hypothetical cases of chemical spills happening upstream of a lake. Theoretical analysis and simulated results indicated that this model is capable of reasonably predicting the acute effects of chemical spills on aquatic ecosystems or organism killings.     

Automated detection of frog calls and choruses by pulse repetition rate

Anurans (frogs and toads) are among the most globally threatened taxonomic groups. Successful conservation of anurans will rely on improved data on the status and changes in local populations, particularly for rare and threatened species. Automated sensors, such as acoustic recorders, have the potential to provide such data by massively increasing the spatial and temporal scale of population sampling efforts. Analyzing such data sets will require robust and efficient tools that can automatically identify the presence of a species in audio recordings. Like bats and birds, many anuran species produce distinct vocalizations that can be captured by autonomous acoustic recorders and represent excellent candidates for automated recognition. However, in contrast to birds and bats, effective automated acoustic recognition tools for anurans are not yet widely available. An effective automated call-recognition method for anurans must be robust to the challenges of real-world field data and should not require extensive labeled data sets. We devised a vocalization identification tool that classifies anuran vocalizations in audio recordings based on their periodic structure: the repeat interval-based bioacoustic identification tool (RIBBIT). We applied RIBBIT to field recordings to study the boreal chorus frog (Pseudacris maculata) of temperate North American grasslands and the critically endangered variable harlequin frog (Atelopus varius) of tropical Central American rainforests. The tool accurately identified boreal chorus frogs, even when they vocalized in heavily overlapping choruses and identified variable harlequin frog vocalizations at a field site where it had been very rarely encountered in visual surveys. Using a few simple parameters, RIBBIT can detect any vocalization with a periodic structure, including those of many anurans, insects, birds, and mammals. We provide open-source implementations of RIBBIT in Python and R to support its use for other taxa and communities.     

Two-dimensional numerical and eco-toxicological modeling of chemical spills

The effects of chemical spills on aquatic nontarget organisms were evaluated in this study. Based on a review of three types of current eco-toxicological models of chemicals, i.e., ACQUATOX model of the US-EPA, Hudson River Model of PCBs, and critical body residual (CBR) model and dynamic energy budget (DEBtox) model, this paper presents an uncoupled numerical ecotoxicological model. The transport and transformation of spilled chemicals were simulated by a chemical transport model (including flow and sediment transport), and the mortalities of an organism caused by the chemicals were simulated by the extended threshold damage model, separately. Due to extreme scarcity of data, this model was applied to two hypothetical cases of chemical spills happening upstream of a lake. Theoretical analysis and simulated results indicated that this model is capable of reasonably predicting the acute effects of chemical spills on aquatic ecosystems or organism killings.     

Oceanic variability and coastal topography shape genetic structure in a long-dispersing sea urchin

Understanding the scale of marine population connectivity is critical for the conservation and sustainable management of marine resources. For many marine species adults are benthic and relatively immobile, so patterns of larval dispersal and recruitment provide the key to understanding marine population connectivity. Contrary to previous expectations, recent studies have often detected unexpectedly low dispersal and fine-scale population structure in the sea, leading to a paradigm shift in how marine systems are viewed. Nonetheless, the link between fine-scale marine population structure and the underlying physical and biological processes has not been made. Here we show that patterns of genetic structure and population connectivity in the broadcast-spawning and long-distance dispersing sea urchin Centrostephanus rodgersii are influenced by physical oceanographic and geographic variables. Despite weak genetic differentiation and no isolation-by-distance over thousands of kilometers among samples from eastern Australia and northern New Zealand, fine-scale genetic structure was associated with sea surface temperature (SST) variability and geography along the southeastern Australian coast. The zone of high SST variability is characterized by periodic shedding of eddies from the East Australian Current, and we suggest that ocean current circulation may, through its influence on larval transport and recruitment, interact with the genetic consequences of large variance in individual reproductive success to generate patterns of fine-scale patchy genetic structure. If proven consistent across species, our findings suggest that the optimal scale for fisheries management and reserve design should vary among localities in relation to regional oceanographic variability and coastal geography.     

Bioaccumulation of platinum group metals on some fish species ( Oreochromis niloticus,Penaeus laspisulcates,Scylla serrate,Galaxias brevipinnis and Mollusc ) in the Pra estuary of Ghana

Catalytic converters have been designed to solve the problem of pollution from automobiles. However, recent studies have shown that the platinum group metals (PGMs) that are used in the design are being deposited alongside highways. The objective of this study was to measure the levels of PGMs that bioaccumulate in Oreochromis niloticus, Penaeus laspisulcates, Scylla serrate, Galaxias brevipinnis and Mollusc in the river Pra estuary along a major highway in Ghana. Chemical analysis using neutron activation analysis showed accumulation of the PGMs in all the biota species analysed. The S. serrate and mollusc showed higher accumulation than the other species. The mollusc and the other fish species in the estuary are consumed in Ghana, and therefore there is the need to educate the population on the effect of the PGMs on their health.     

ExSys-LOPA for the chemical process industry

The chemical process industries are characterized by the use, processing, and storage of large amounts of dangerous chemical substances and/or energy. Among different missions of chemical plants there are two very important ones, which: 1. provide a safe work environment, 2. fully protect the environment. These important missions can be achieved only by design of adequate safeguards for identified process hazards. Layer of Protection Analysis (LOPA) can successfully answer this question. This technique is a simplified process of quantitative risk assessment, using the order of magnitude categories for initiating cause frequency, consequence severity, and the likelihood of failure of independent protection layers to analyze and assess the risk of particular accident scenarios. LOPA requires application of qualitative hazard evaluation methods to identify accident scenarios, including initiating causes and appropriate safeguards. This can be well fulfilled, e.g., by HAZOP Studies or What-If Analysis. However, those techniques require extensive experience, efforts by teams of experts as well as significant time commitments, especially for complex chemical process units. In order to simplify that process, this paper presents another strategy that is a combination of an expert system for accident scenario identification with subsequent application of LOPA. The concept is called ExSys-LOPA, which employs, prepared in advance, values from engineering databases for identification of loss events specific to the selected target process and subsequently a accident scenario barrier model developed as an input for LOPA. Such consistent rules for the identification of accident scenarios to be analyzed can facilitate and expedite the analysis and thereby incorporate many more scenarios and analyze those for adequacy of the safeguards. An associated computer program is under development. The proposed technique supports and extends the Layer of Protection Analysis application, especially for safety assurance assessment of risk-based determination for the process industries. A case study concerning HF alkylation plant illustrates the proposed method.     

An approach to solve the facility layout problem based on the worst-case scenario

A new approach to determine the optimal distribution of process facilities is presented in this paper. The formulation considers a set of facilities already installed in a given land and a new set of facilities to be accommodated within the same land. In addition, it is considered that a set of facilities either installed or to be laid out presents the possibility of toxic release. Based on previous analysis, the worst-case scenario implies calm wind and stable atmospheric condition. Since these conditions tend to exist during several days of the year, the proposed model is formulated assuming these deterministic values for wind and atmospheric conditions. The final model is formulated as a disjunctive model that is converted into a mixed-integer non-linear program (MINLP) via the convex-hull method. The model is then solved with local and global optimizers in the GAMS package. Using the current approach based on minimum distances for a particular case study results in a distribution with a very high risk whereas the optimal results using this proposed approach indicate large separations between releasing facilities and the inhabited facilities due to the high toxicity of the released material. More elaboration will be aggregated into the developed model to include prevention and mitigation systems to produce more compact but optimal and safe layouts.