Water quality monitoring: A combined approach to investigate gradients of change in the Great Barrier Reef, Australia

For the managers of a region as large as the Great Barrier Reef, it is a challenge to develop a cost effective monitoring program, with appropriate temporal and spatial resolution to detect changes in water quality. The current study compares water quality data (phytoplankton abundance and water clarity) from remote sensing with field sampling (continuous underway profiles of water quality and fixed site sampling) at different spatial scales in the Great Barrier Reef north of Mackay (20 degrees S). Five transects (20-30 km long) were conducted from clean oceanic water to the turbid waters adjacent to the mainland. The different data sources demonstrated high correlations when compared on a similar spatial scale (18 fixed sites). However, each data source also contributed unique information that could not be obtained by the other techniques. A combination of remote sensing, underway sampling and fixed stations will deliver the best spatial and temporal monitoring of water quality in the Great Barrier Reef. (c) 2004 Elsevier Ltd. All rights reserved.

Effects of hatchery shading and nest depth on the development and quality of Chelonia mydas hatchlings: implications for hatchery management in Peninsular, Malaysia

One of the decisions made by hatchery managers around the world is what degree of shading and nest depth are required to maximise the production of high-quality hatchlings at optimal sex ratios. The primary objectives of this study were to determine the effects of (1) hatchery shading and nest depth on nest temperatures and emergence lag, and (2) nest temperatures and nest depth on hatchling sex ratio and quality. In 2001, 26 Chelonia mydas clutches from Ma'Daerah beach, Terengganu, Malaysia, were relocated alternatively at depths of 50 cm and 75 cm into a 70%-shaded and a 100%-shaded hatchery. Data loggers were placed into the centre of each relocated clutch to record the temperature every hour over the course of incubation. When the hatchlings emerged, a sample of the clutch was run, measured and weighed and a separate sample was examined histologically for sex characteristics. Nest temperatures ranged between 28 degrees C and 30 degrees C and generally showed increases over the second half of incubation due to metabolic heating of the clutch. There was no significant correlation found between nest temperature and any of the hatchling parameters measured. Hatchlings from 75-cm-deep nests had a longer emergence lag (46.4 (+/- 10.2) h) than hatchlings from 50-cm-deep nests. Hatch and emergence success were similar to those of natural populations and hatchling sex ratios were male dominant, with an average of 72% males. There was a poor correlation between mean middle-third incubation temperatures and sex ratio. Hatchlings from 75-cm-deep nests had similar running speeds but lower condition index than their conspecifics from 50-cm-deep nests.

Data quality initiatives - striving for continuous improvements

Although managers consider accurate, timely, and relevant information as critical to the quality of their decisions, evidence of large variations in data quality abounds. Over a period of twelve months, the action research project reported herein attempted to investigate and track data quality initiatives undertaken by the participating organisation. The investigation focused on two types of errors: transaction input errors and processing errors. Whenever the action research initiative identified non-trivial errors, the participating organisation introduced actions to correct the errors and prevent similar errors in the future. Data quality metrics were taken quarterly to measure improvements resulting from the activities undertaken during the action research project. The action research project results indicated that for a mission-critical database to ensure and maintain data quality, commitment to continuous data quality improvement is necessary. Also, communication among all stakeholders is required to ensure common understanding of data quality improvement goals. The action research project found that to further substantially improve data quality, structural changes within the organisation and to the information systems are sometimes necessary. The major goal of the action research study is to increase the level of data quality awareness within all organisations and to motivate them to examine the importance of achieving and maintaining high-quality data.