Water quality assessment of Portuguese streams: Regional or national predictive models?

Feio, Maria João; Norris, Richard H.; Graça, Manuel A. S.; Nichols, Susan J.

doi:10.1016/j.ecolind.2008.09.012

Cited by 35 publications

(23 citation statements)

References 30 publications

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“…Moreover, the statistical power needed to detect overall biological impacts, based on the O/E for the number of taxa, is similar for P c up to 70% (CLARKE and MURPHY, 2006). Several posterior predictive models also utilize this approach (e.g., FEIO et al, 2009;POQUET et al, 2009).…”

Section: The First Steps Of the Predictive Modeling: The River Invertmentioning

confidence: 98%

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Predictive Models for Freshwater Biological Assessment: Statistical Approaches, Biological Elements and the Iberian Peninsula Experience: A Review

Feio

Poquet

2011

International Review of Hydrobiology

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In the last three decades, predictive models have been developed and applied worldwide for freshwater bioassessment. They consist of statistical tools that follow the concept of the Reference Condition Approach. Composed of several sequential steps, these assessment tools assess the deviation of given site assemblages from the expected biological condition in the absence of human disturbance. The most common approaches (RIVPACS/AUSRIVAS and BEAST) are based on a posteriori classifications that use the biological composition of a community to classify reference sites in groups, and afterwards to establish which environmental features best discriminate the biological groups obtained. Here, we review the predictive modeling procedures used in freshwaters bioassessment (RIVPACS/AUSRIVAS, BEAST, ANNA, Artificial Neural Networks, Bayesian Belief Networks and others) as well as the biological elements to which they have been applied.We also review the Spanish and Portuguese experiences in the development and application of predictive models, with particular attention to regional environmental conditions, the different modeling approaches, and the available implementation tools. Moreover, and considering the natural continuity within the Iberian Peninsula (which include several transnational rivers), we discuss the possibilities of the development of common predictive models across the region, considering all factors that may influence their performance, such as the target scale used to develop the models (regional or peninsular); common reference criteria; sampling and sorting procedures; the taxonomic resolution used in the models; the temporal variability (mainly in the Iberian Mediterranean region); and the biological elements to consider. We concluded that there are good technical conditions for the implementations of a common predictive approach throughout the Iberian Peninsula, which should allow a global biological assessment of streams with different biological elements and seasons that could be used by water managers in the context of the Water Framework Directive.

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Section: The First Steps Of the Predictive Modeling: The River Invertmentioning

confidence: 98%

“…The North model includes six biological distinct groups (64% correct classifications) while four groups composed the South model. All the communities are described in FEIO et al (2009).…”

Section: The Iberian Peninsula Experiencementioning

confidence: 99%

Predictive Models for Freshwater Biological Assessment: Statistical Approaches, Biological Elements and the Iberian Peninsula Experience: A Review

Feio

Poquet

2011

International Review of Hydrobiology

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“…For example, Sanchez et al [69] studied the importance of urban and Hawkins and Yuan [83] studied the influence of agricultural areas where human interventions are generally expanded until the edge of the streams. However, many studies included the information of local land use but did not specifically assess its potential effects on the water quality [78,82] or did not find its importance on the ecological water quality after analyses [79]. Table 3.…”

Section: Local or Riparian Land-use Scalementioning

confidence: 99%

“…Due to their relative simplicity, they have been often used in ecological water quality studies. For example, Carlisle and Meador [76] used multiple discriminant analysis, Feio et al [79] used multi-dimensional scaling and stepwise multiple discriminant function analysis, and Mantyka-Pringle et al [67] used principal components analysis. Some disadvantages of these techniques are that the outputs can be difficult to interpret and that associations among variables and distribution patterns do not inherently imply causality [118].…”

Section: Type Of Models # Of Studies Referencesmentioning

confidence: 99%

Ecological Models to Infer the Quantitative Relationship between Land Use and the Aquatic Macroinvertebrate Community

Damanik-Ambarita

Everaert

Goethals

2018

Water

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Land-use changes influence the ecological water quality. In spite of this knowledge, land-use information is often missing in ecological water quality studies. Therefore, in the present research, we selected 39 peer-reviewed model-based scientific papers that study the relationship between land use and aquatic macroinvertebrates. From the selected papers, we found that certain water bodies responded more to local land use, while other water bodies were more likely to be affected by catchment land use. Hence, combined land-use information from both the local scale and the catchment scale will provide a better understanding of the impact of land-use changes on the ecological water quality. To gain this knowledge, efforts need to be taken to acquire land-use information from field observations and remote sensing or a geographic information system (GIS) data source. Furthermore, we concluded on the benefits of using models to better understand the relationship between the ecological water quality and environmental variables. Depending on the aim of the study and the nature of the data, researchers can select the most suitable model to ensure fast analysis.

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“…Predictive models, although conceptually simple, are a powerful statistical tool developed for the assessment of rivers at various scales (from site-specific to a national scale) and coastal waters which are gaining prevalence in global assessment schemes , Feio et al 2009). Once operational, these tools are of value to water users, allowing them to make informed choices about behaviours to reduce exposure risk (Boehm et al 2007).…”

Section: Mathematical Modelingmentioning

confidence: 99%

Animal Waste, Water Quality and Human Health

Dufour¹,

Bartram²,

Bos³

et al. 2013

wio

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The excreta (faeces and urine) of mammals and birds are widespread across planet Earth and frequently contaminate water that is used for bathing and recreation, that is treated and distributed for human consumption, and that is used to irrigate crops.The risk that such contamination represents to human health is inadequately understood. It is widely assumed that faeces of animals represents a lesser risk to human health than human faeces of because of the 'species barrier' and especially the species-specificity of most viruses. This book points to a rational and systematic way of assessing the risks and to cost-effective approaches to manage them. The information presented is expected to have important consequences for prioritisation of preventive and remedial interventions.

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Water quality assessment of Portuguese streams: Regional or national predictive models?

Cited by 35 publications

References 30 publications

Predictive Models for Freshwater Biological Assessment: Statistical Approaches, Biological Elements and the Iberian Peninsula Experience: A Review

Predictive Models for Freshwater Biological Assessment: Statistical Approaches, Biological Elements and the Iberian Peninsula Experience: A Review

Ecological Models to Infer the Quantitative Relationship between Land Use and the Aquatic Macroinvertebrate Community

Animal Waste, Water Quality and Human Health

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