Measures of nutrient processes as indicators of stream ecosystem health

To better understand how freshwater ecosystems respond to changes in catchment land-use, it is important to develop measures of ecological health that include aspects of both ecosystem structure and function. This study investigated measures of nutrient processes as potential indicators of stream ecosystem health across a land-use gradient from relatively undisturbed to highly modified. A total of seven indicators (potential denitrification; an index of denitrification potential relative to sediment organic matter; benthic algal growth on artificial substrates amended with (a) N only, (b) P only, and (c) N and P; and delta N-15 of aquatic plants and benthic sediment) were measured at 53 streams in southeast Queensland, Australia. The indicators were evaluated by their response to a defined gradient of agricultural land-use disturbance as well as practical aspects of using the indicators as part of a monitoring program. Regression models based on descriptors of the disturbance gradient explained a large proportion of the variation in six of the seven indicators. Denitrification index, algal growth in N amended substrate, and delta N-15 of aquatic plants demonstrated the best regression. However, the delta N-15 value of benthic sediment was found to be the best indicator overall for incorporation into a monitoring program, as samples were relatively easy to collect and process, and were successfully collected at more than 90% of the study sites

Statistics critical in securing our food supply

“World food security … is at its lowest in half a century,” wrote Julian Cribb FTSE, a wellknown consultant in science communication and founding editor of www.sciencealert. com.au in the lead article in the 2008 ATSE Focus magazine issue entitled “Food for the world: the nation’s challenge”. Food security continues to be a key national and international concern and it is pleasing to see this issue of Focus again exploring aspects of the topic with the aim of continuing to raise awareness of issues and influencing relevant policy decisions. Statistics (or statistical science, more broadly) has been critical to the information and decision-making value chain needed to optimise agriculture and the food supply chain. The key steps are most often addressed by multidisciplinary research groups including statisticians in collaboration with life and physical scientists, agri-industry personnel and other relevant stakeholders

Aspects of statistical design for monitoring waters of Port Curtis, Queensland

This report provides design input for an ecosystem health monitoring program that displays and highlights change in the ecological health of Port Curtis. Here, ecological health is defined in terms of the spatial distribution of processes, habitats and anthropogenic impact zones. Ecological health monitoring therefore requires a combined analysis of spatial extent and temporal persistence, with the latter used to detect trends and assess the condition of the port over time. After investigation of four data sets made available for statistical analysis, two main design aspects have been considered, 1) the optimal number of grabs for macrobenthos sampling and 2) spatial configuration of sampling stations via inference gained through interpolation of water quality parameters and contaminants throughout the port

Food price volatility and hunger alleviation - can Cannes work?

Recent years have seen global food prices rise and become more volatile. Price surges in 2008 and 2011 held devastating consequences for hundreds of millions of people and negatively impacted many more. Today one billion people are hungry. The issue is a high priority for many international agencies and national governments. At the Cannes Summit in November 2011, the G20 leaders agreed to implement five objectives aiming to mitigate food price volatility and protect vulnerable persons. To succeed, the global community must now translate these high level policy objectives into practical actions. In this paper, we describe challenges and unresolved dilemmas before the global community in implementing these five objectives. The paper describes recent food price volatility trends and an evaluation of possible causes. Special attention is given to climate change and water scarcity, which have the potential to impact food prices to a much greater extent in coming decades. We conclude the world needs an improved knowledge base and new analytical capabilities, developed in parallel with the implementation of practical policy actions, to manage food price volatility and reduce hunger and malnutrition. This requires major innovations and paradigm shifts by the global community

Water quality indices from unbalanced spatio-temporal monitoring designs

This chapter investigates a variety of water quality assessment tools for reservoirs with balanced/unbalanced monitoring designs and focuses on providing informative water quality assessments to ensure decision-makers are able to make risk-informed management decisions about reservoir health. In particular, two water quality assessment methods are described: non-compliance (probability of the number of times the indicator exceeds the recommended guideline) and amplitude (degree of departure from the guideline). Strengths and weaknesses of current and alternative water quality methods will be discussed. The proposed methodology is particularly applicable to unbalanced designs with/without missing values and reflects the general conditions and is not swayed too heavily by the occasional extreme value (very high or very low quality). To investigate the issues in greater detail, we use as a case study, a reservoir within South-East Queensland (SEQ), Australia. The purpose here is to obtain an annual score that reflected the overall water quality, temporally, spatially and across water quality indicators for each reservoir

Spatial prediction on a river network

This article develops methods for spatially predicting daily change of dissolved oxygen (Dochange) at both sampled locations (134 freshwater sites in 2002 and 2003) and other locations of interest throughout a river network in South East Queensland, Australia. In order to deal with the relative sparseness of the monitoring locations in comparison to the number of locations where one might want to make predictions, we make a classification of the river and stream locations. We then implement optimal spatial prediction (ordinary and constrained kriging) from geostatistics. Because of their directed-tree structure, rivers and streams offer special challenges. A complete approach to spatial prediction on a river network is given, with special attention paid to environmental exceedances. The methodology is used to produce a map of Dochange predictions for 2003. Dochange is one of the variables measured as part of the Ecosystem Health Monitoring Program conducted within the Moreton Bay Waterways and Catchments Partnership

Water quality indices from unbalanced spatio-temoral monitoring designs

This chapter investigates a variety of water quality assessment tools for reservoirs with balanced/unbalanced monitoring designs and focuses on providing informative water quality assessments to ensure decision-makers are able to make risk-informed management decisions about reservoir health. In particular, two water quality assessment methods are described: non-compliance (probability of the number of times the indicator exceeds the recommended guideline) and amplitude (degree of departure from the guideline). Strengths and weaknesses of current and alternative water quality methods will be discussed. The proposed methodology is particularly applicable to unbalanced designs with/without missing values and reflects the general conditions and is not swayed too heavily by the occasional extreme value (very high or very low quality). To investigate the issues in greater detail, we use as a case study, a reservoir within South-East Queensland (SEQ), Australia. The purpose here is to obtain an annual score that reflected the overall water quality, temporally, spatially and across water quality indicators for each reservoir

Taxonomic resolution and quantification of freshwater macroinvertebrate samples from an Australian dryland river : The benefits and costs of using species abundance data

In studies using macroinvertebrates as indicators for monitoring rivers and streams, species level identifications in comparison with lower resolution identifications can have greater information content and result in more reliable site classifications and better capacity to discriminate between sites, yet many such programmes identify specimens to the resolution of family rather than species. This is often because it is cheaper to obtain family level data than species level data. Choice of appropriate taxonomic resolution is a compromise between the cost of obtaining data at high taxonomic resolutions and the loss of information at lower resolutions. Optimum taxonomic resolution should be determined by the information required to address programme objectives. Costs saved in identifying macroinvertebrates to family level may not be justified if family level data can not give the answers required and expending the extra cost to obtain species level data may not be warranted if cheaper family level data retains sufficient information to meet objectives. We investigated the influence of taxonomic resolution and sample quantification (abundance vs. presence/absence) on the representation of aquatic macroinvertebrate species assemblage patterns and species richness estimates. The study was conducted in a physically harsh dryland river system (Condamine-Balonne River system, located in south-western Queensland, Australia), characterised by low macroinvertebrate diversity. Our 29 study sites covered a wide geographic range and a diversity of lotic conditions and this was reflected by differences between sites in macroinvertebrate assemblage composition and richness. The usefulness of expending the extra cost necessary to identify macroinvertebrates to species was quantified via the benefits this higher resolution data offered in its capacity to discriminate between sites and give accurate estimates of site species richness. We found that very little information (<6%) was lost by identifying taxa to family (or genus), as opposed to species, and that quantifying the abundance of taxa provided greater resolution for pattern interpretation than simply noting their presence/absence. Species richness was very well represented by genus, family and order richness, so that each of these could be used as surrogates of species richness if, for example, surveying to identify diversity hot-spots. It is suggested that sharing of common ecological responses among species within higher taxonomic units is the most plausible mechanism for the results. Based on a cost/benefit analysis, family level abundance data is recommended as the best resolution for resolving patterns in macroinvertebrate assemblages in this system. The relevance of these findings are discussed in the context of other low diversity, harsh, dryland river systems