Herbicides: A new threat to the Great Barrier Reef

The runoff of pesticides (insecticides, herbicides and fungicides) from agricultural lands is a key concern for the health of the iconic Great Barrier Reef, Australia. Relatively low levels of herbicide residues can reduce the productivity of marine plants and corals. However, the risk of these residues to Great Barrier Reef ecosystems has been poorly quantified due to a lack of large-scale datasets. Here we present results of a study tracing pesticide residues from rivers and creeks in three catchment regions to the adjacent marine environment. Several pesticides (mainly herbicides) were detected in both freshwater and coastal marine waters and were attributed to specific land uses in the catchment. Elevated herbicide concentrations were particularly associated with sugar cane cultivation in the adjacent catchment. We demonstrate that herbicides reach the Great Barrier Reef lagoon and may disturb sensitive marine ecosystems already affected by other pressures such as climate change.     

An animal movement model incorporating home range and habitat selection

Wildlife biologists are often interested in how an animal uses space and the habitat resources within that space. We propose a single model that estimates an animal’s home range and habitat selection parameters within that range while accounting for the inherent autocorrelation in frequently sampled telemetry data. The model is applied to brown bear telemetry data in southeast Alaska. This article is based on a portion of this author’s Ph.D. dissertation completed in 2003 at the University of Iowa.     

Environmental biotechnology: A bioremediation perspective

The term environmental biotechnology has a certain air of modernity when in fact it has a long history of use, if one considers the underlying principles and not the appellation. However, as part of its complex meaning, there is a dynamic new definition and purpose in this discipline with regard to bioremediation. The ability to probe the environment at the molecular level with exquisite methods, to create a new awareness of fundamental biological processes therein, has created an important new paradigm in remediation engineering design and management. Further, biological lines of evidence made extremely robust through the merger of biotechnology and environmental science are poised to be incorporated into the very fabric of site evaluation and disposition at the regulatory level. At the operational level, the field of environmental biotechnology is driven by the “omics,” the common suffix for disciplines like genomics, proteomics, and metabolomics. An introduction to these elements of the process is followed by a review of how they are being used right now in a commercial framework, with the understanding that the entire process is still in the formative stages of its vast potential. © 2005 Wiley Periodicals, Inc.     

Preconception and preimplantation diagnosis for cystic fibrosis

Preimplantation diagnosis provides couples at high genetic risk the possibility of avoiding genetic disease without the need for prenatal diagnosis and selective abortion of the affected pregnancy. Following extensive background work on the reliability of genetic diagnosis in a single cell, we offered on a research basis preimplantation diagnosis to five couples at risk for offspring with the delta-F508 mutation (the major mutation causing cystic fibrosis). There was no detrimental effect from polar body removal on either fertilization or preimplantation development. Genetic analysis, undertaken in 22 polar bodies and 15 corresponding blastomeres, identified 21 embryos of which ten were transferred.     

Forecasting extinction risk with nonstationary matrix models.

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.     

A review of the military approach to urban environmental deterioration in Nigeria

The concern of this paper is a review of the urban environmental degradation and the current approach by the military (environmental task force) in solving the problem. It is based on the experience of a few states in Nigeria. The paper proposes a comprehensive urban planning approach which should be integrated with an awareness campaign.     

EXPERIMENTAL VERIFICATION OF MULTICOMPONENT GROUND WATER CONTAMINATION PREDICTIONS1

ABSTRACT: Recent advances in mass transport modeling have made possible computation of the theoretical consequences of intricate multicomponent species interactions during ground water contamination events. Predictions such as strong chromatographic effects and induced downstream precipitations may have considerable impact on environmental analysis and regulation. Results of laboratory attempts to verify theoretical multicomponent transport predictions are discussed. Evidence presented here indicates that natural variability of soil properties make such verifications difficult. Although species interactions are easily confirmed, dramatic effects often exist only within small mathematical windows in strongly variable coefficient sets. Currently, the ability to generate multicomponent predictions apparently exceeds the ability to quantify the necessary, presumably deterministic, information required for real soils.     

Organic compounds and trace metals of anthropogenic origin in sediments from Montego Bay,Jamaica: assessment of sources and distribution pathways

Surface sediments throughout Montego Bay, Jamaica were collected in 1995 and analyzed for their trace metal and trace organic contaminant content. A variety of trace metals, petroleum hydrocarbons, polycyclic aromatic hydrocarbons, coprostanol as well as chlorinated hydrocarbons such as pesticides and polychlorinated biphenyls were detected and provide evidence for several anthropogenic inputs to the bay. Two main sources of these chemicals are the Montego River and the North Gully, the latter being more significant. Particle-associated pollutants were found to be distributed along the Montego River plume, as well as being transported by the prevailing water currents to the South-Western sections of the bay, probably through re-suspension of enriched fine sediments from the North Gully outfall area.