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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 <jats:italic>a posteriori<\/jats:italic> 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.<\/jats:p><jats:p>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. (\u00a9 2011 WILEY\u2010VCH Verlag GmbH &amp; Co. KGaA, Weinheim)<\/jats:p>","DOI":"10.1002\/iroh.201111376","type":"journal-article","created":{"date-parts":[[2011,9,13]],"date-time":"2011-09-13T08:41:41Z","timestamp":1315903301000},"page":"321-346","source":"Crossref","is-referenced-by-count":32,"title":["Predictive Models for Freshwater Biological Assessment: Statistical Approaches, Biological Elements and the Iberian Peninsula Experience: A Review"],"prefix":"10.1002","volume":"96","author":[{"given":"Maria Joao","family":"Feio","sequence":"first","affiliation":[]},{"given":"Jos\u00e9 Manuel","family":"Poquet","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2011,9,13]]},"reference":[{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1051\/limn\/2004016"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0048-9697(03)00433-9"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2010.06.006"},{"key":"e_1_2_1_5_1","unstructured":"Alba\u2010Tercedor J.andA. 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