Dr Ben Longstaff

Abstract: In an effort to better portray changing health conditions in Chesapeake Bay and support restoration efforts, a Bay Health Index (BHI) was developed to assess the ecological effects of nutrient and sediment loading on 15 regions of the estuary. Three water quality and three biological measures were combined to formulate the BHI. Water quality measures of chlorophyll-a, dissolved oxygen, and Secchi depth were averaged to create the Water Quality Index (WQI), and biological measures of the phytoplankton and benthic indices of biotic integrity (P-IBI and B-IBI, respectively) and the area of submerged aquatic vegetation (SAV) were averaged to create the Biotic Index (BI). The WQI and BI were subsequently averaged to give a BHI value representing ecological conditions over the growing season (i.e., March-October). Lower chlorophyll-a concentrations, higher dissolved oxygen concentrations, deeper Secchi depths, higher phytoplankton and benthic indices relative to ecological health-based thresholds, and more extensive SAV area relative to restoration goal areas, characterized the least-impaired regions. The WQI, P-BI and BHI were significantly correlated with (1) regional river flow (r = -0.64, -0.57 and -0.49, respectively; p < 0.01), (2) nitrogen (N), phosphorus (P) and sediment loads (all positively correlated with flow), and (3) the sum of developed and agricultural land use (highest annual r(2) = 0.86, 0.71 and 0.68, respectively) in most reporting regions, indicating that the BHI is strongly regulated by nutrient and sediment loads from these land uses. The BHI uses ecological health-based thresholds that give an accurate representation of the health conditions in Chesapeake Bay and was the basis for an annual, publicly released environmental report card that debuted in 2007.

Abstract: Nitrogen loading to aquatic ecosystems from sewage is recognised worldwide as a growing problem. The use of nitrogen stable isotopes as a means of discerning sewage nitrogen in the environment has been used annually by the Ecosystem Health Monitoring Program in Moreton Bay (Australia) since 1997 when the technique was first developed. This (“sewage plume mapping”) technique, which measures the δ¹⁵N isotopic signature of the red macroalga Catenella nipae after incubation in situ, has demonstrated a large reduction in the magnitude and spatial extent of sewage nitrogen within Moreton Bay over the past 5 years. This observed reduction coincides with considerable upgrades to the nitrogen removal efficacy at several sewage treatment plants within the region. This paper describes the observed changes and evaluates whether they can be attributed to the treatment upgrades. (c) 2004 Published by Elsevier Ltd.

Abstract: An extensive and diverse assemblage of seagrass habitats exists along the tropical and subtropical coastline of north east Australia and the associated Great Barrier Reef. In their natural state, these habitats are characterised by very low nutrient concentrations and are primarily nitrogen limited. Summer rainfall and tropical storms/cyclones lead to large flows of sediment-laden fresh water. Macro grazers, dugongs (Dugong dugon) and green sea turtles (Chelonia mydas) are an important feature in structuring tropical Australian seagrass communities. In general, all seagrass habitats in north east Australia are influenced by high disturbance and are both spatially and temporally variable. This paper classifies the diversity into four habitat types and proposes the main limiting factor for each habitat. The major processes that categorise each habitat are described and significant threats or gaps in understanding are identified. Four broad categories of seagrass habitat are defined as \'River estuaries\', \'Coastal\', \'Deep water\' and \'Reef\', and the dominant controlling factors are terrigenous runoff, physical disturbance, low light and low nutrients, respectively. Generic concepts of seagrass ecology and habitat function have often been found inappropriate to the diverse range of seagrass habitats in north east Australian waters. The classification and models developed here explain differences in habitats by identifying ecological functions and potential response to impacts in each habitat. This understanding will help to better focus seagrass management and research in tropical habitats.

Abstract: Pulsed turbidity events caused by factors such as flooding rivers have the potential to seriously impact seagrass communities by depriving the plants of all available light. The effects of light deprivation was investigated on the survival, morphology and physiology of the tropical seagrasses Halodule pinifolia and Halophila ovalis growing in the South-East Gulf of Carpentaria, Australia, a region where pulsed flood events are common. Additionally, physiological:and morphological responses to light availability along natural gradients were examined. Responses to both experimental and natural light gradients were investigated for their potential use as indicators of impending seagrass loss during pulsed turbidity events. H. pinifolia was deprived of light for 80 days using in situ shade screens and the following parameters measured at three depths and under the shade screens: biomass, shoot density, canopy height, amino acid content, chlorophyll content, delta(13)C signature, %C and sugar concentration, The quantity of light was extremely variable, with mean daily irradiances between 9-12 mol photons m(-2) day(-1), and a range of 0.05-42 mol photons m(-2) day(-1) . H. pinifolia leaf amino acid content increased with increased water depth (from 8 to 18 mu mol g fresh wt.), chlorophyll a to b ratio decreased (from 2.4 to 2.1) and delta(13)C values became more negative (from -9 to -12). H. ovalis displayed little tolerance to light deprivation, with plant death occurring after 38 days in the dark. H. pinifolia showed a high degree of tolerance to light deprivation with no biomass loss before day 38 and complete die-off predicted after 100 days. Shoot density, biomass and canopy height all declined after 38 days. Physiological parameters that responded significantly to the light deprivation were the amino acids which increased (from 20 to 80 mu mol g fresh wt.), the chlorophyll 8 to b ratio which decreased (from 2.5 to 2.1) and the values which became more negative (from -9 to -10). Changes in leaf physiology (e.g. amino acid content, chlorophyll content and delta(13)C) occurred before morphological changes (e.g, biomass, shoot, density, canopy height) or die-off, and were thus considered to be potential indicators of impending seagrass die-off during light deprivation. In conclusion, only long duration (>38 days) pulsed turbidity events would have a detrimental impact on H. pinifolia growing in the Gulf of Carpentaria and that by assessing specific physiological responses, seagrass loss during pulsed turbidity events can predicted. (C) 1999 Elsevier Science B.V. All rights reserved.

Abstract: Vast areas of the globe's coastal zone have experienced significant declines in ecosystem health. Deteriorating water quality, loss and alteration of vital habitats, and reduced populations of fish and shellfish are some of the major changes recorded. Regardless of the differences between cultures, climate regions, and population pressures, integrated management and assessment is required to solve coastal environmental problems. Establishing and running an effective assessment program is a complex process that necessitates strategic collaboration and partnerships between many individuals and agencies. This book was written to make the process of running a coastal assessment program easier and the outcomes more effective. It provides a step‒by‒step approach from data collection and information management to synthesis and application and draws on the knowledge of a variety of coastal scientists and managers. The book is divided into four sections that represent the four major steps needed to apply data within an coastal assessment program: community engagement, community knowledge, environmental information, and data collection.

Abstract: Although spatial analysis is technically a component of statistical analysis and environmental modeling, the important role it plays, or should play, in coastal assessment programs warrants specific attention in its own separate chapter. This chapter provides some of the basic principles for producing effective maps through to the process of undertaking complex spatial analyses.

Abstract: As highlighted in the title of this chapter, the array of in situ instruments available for coastal monitoring is increasing rapidly—“the ever‒growing toolbox,”(Figure 12.1). This growth is driven in part by research and development into new or existing sensors, sensor platforms, data logging, and data telemetry. Because there are such rapid changes in the field of in situ monitoring, this chapter gives specific focus to many emerging technologies, such as nutrient analyzers and pathogen detectors. Although these examples have been included to illustrate the cutting edge of in situ monitoring, there are often inherent challenges of new instruments do not have a long history of use and application. Therefore, it must not be forgotten that there are many well established in situ instruments to consider ranging from the classic and very simple Secchi disc to more complex water quality probes. In situ monitoring in itself is a very large topic and is covered in more detail by many books.1 The purpose of this chapter, therefore, is to provide a brief discussion on why to use in situ monitoring, to identify what the most suitable situations and tools to use for in situ monitoring are, and to identify some of the associated challenges with in situ monitoring.

Abstract: This chapter continues the discussion of ecological indicators but with the specific application of producing ecological report cards. It explains the reasons for producing report cards, the steps to produce indicators based on ecological thresholds, and the process of combining indicators into overarching indices. Ecological report cards, like the indicators that they are based on, are one of the most important products for directing data collection and analysis.