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dc.contributor.authorJoy, Michael Kevin
dc.date.accessioned2010-11-28T20:39:02Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2010-11-28T20:39:02Z
dc.date.issued2003
dc.identifier.urihttp://hdl.handle.net/10179/1921
dc.descriptionThis thesis consists of chapters that were published as articles. Joy, MK; Death, RG. (2004). Application of the index of biotic integrity methodology to New Zealand freshwater fish communities ENVIRONMENTAL MANAGEMENT, 34 (3): 415-428 The original publication is available at www.springerlink.com http://www.springerlink.com/content/1v8255xcemx5tfnk/ Joy, MK; Death, RG (2004). Predictive modelling and spatial mapping of freshwater fish and decapod assemblages using GIS and neural networks. FRESHWATER BIOLOGY, 49 (8): 1036-1052 The definitive version is available at www3.interscience.wiley.com http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2427.2004.01248.x/abstract Joy, MK; Death, RG (2003). Assessing biological integrity using freshwater fish and decapod habitat selection functions ENVIRONMENTAL MANAGEMENT, 32 (6): 747-759 The original publication is available at www.springerlink.com http://www.springerlink.com/content/w1wca0vf0ljab705/ Joy, MK; Death, RG. (2003). Biological assessment of rivers in the Manawatu-Wanganui region of New Zealand using a predictive macroinvertebrate model. NEW ZEALAND JOURNAL OF MARINE AND FRESHWATER RESEARCH, 37 (2): 367-379 Published version is available at http://www.royalsociety.org.nz/publications/journals/nzjm/2003/034/ Joy, MK; Death, RG. (2002). Predictive modelling of freshwater fish as a biomonitoring tool in New Zealand. FRESHWATER BIOLOGY, 47 (11): 2261-2275. The definitive version is available at www3.interscience.wiley.com http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2427.2004.01248.x/abstracten_US
dc.description.abstractA suite of new regional and national lotic freshwater bioassessment tools were developed for New Zealand. This work permits the inclusion of freshwater fish in bioassessment, a component of the fauna previously largely ignored. The multivariate predictive models developed gave a number of advantages over the existing albeit overextended single-index approach (the macroinvertebrate community index) used by regional authorities. To acquire the data for constructing the models more than 500 sites were sampled over three North Island regions. The sites were selected to represent least impacted conditions known as reference sites so that the biotic communities sampled would representing the best attainable or the goal for resource managers. Models were constructed to predict the biota representing best available conditions based on the non human influenced physicochemical variables defining the sites. The predicted and observed assemblages were then compared using an observed over expected ratio (O/E) so that scores less than 1 represent less [i.e. fewer] species observed than expected. This (O/E) ratio is more than simply the assessment of species richness, as only those species predicted are included in the ratio. Reference site multivariate predictive models using fish and macroinvertebrate assemblage groups were developed for bioassessment in the Manawatu-Wanganui Region. Two reference site multivariate predictive models using individual fish and decapod species were developed for the Auckland region. The first used traditional linear discriminant function analysis and the second used artificial neural networks (ANNs). A model to predict the spatial occurrence of fish and decapods was developed for fish in the Wellington Region using Geographic Information Systems (GIS) and ANNs. The remotely sensed data was available for all rivers in the region so the predictions could be extended over the entire stream network to produce a fish map. Finally an index of biotic integrity (IBI) using fish was developed for the entire country and evaluated using remotely assessed environmental data. Exhaustive evaluations of predictions from all the models confirmed their credibility as a biomonitoring.en_US
dc.language.isoenen_US
dc.publisherMassey Universityen_US
dc.rightsThe Authoren_US
dc.subjectFreshwater biological assessmenten_US
dc.subjectFreshwater ecologyen_US
dc.subject.otherFields of Research::270000 Biological Sciences::270700 Ecology and Evolution::270701 Freshwater ecologyen_US
dc.titleThe development of predictive models to enhance biological assessment of riverine systems in New Zealand : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Ecology at Massey University, Palmerston North, New Zealanden_US
dc.typeThesisen_US
thesis.degree.disciplineEcologyen_US
thesis.degree.grantorMassey Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophy (Ph.D.)en_US


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