Efficient spatial models for predicting the occurrence of subarctic estuarine-associated fishes: implications for management-Reference-Cited by-同舟云学术

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Efficient spatial models for predicting the occurrence of subarctic estuarine-associated fishes: implications for management

Published:2015-11-26 Issue:6 Volume:22 Page:501-517
ISSN:0969-997X
Container-title:Fisheries Management and Ecology
language:en
Short-container-title:Fish Manag Ecol

Author:

Miller K. B.¹,Huettmann F.²,Norcross B. L.³

Affiliation:

1. Auke Bay Laboratories; Alaska Fisheries Science Center; National Marine Fisheries Service; NOAA; Juneau AK USA

2. EWHALE Lab; Institute of Arctic Biology; Biology & Wildlife Department; University of Alaska Fairbanks (UAF); Fairbanks AK USA

3. School of Fisheries and Ocean Sciences; University of Alaska Fairbanks; Fairbanks AK USA

Publisher

Wiley

Subject

Ecology,Aquatic Science

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/fme.12148/fullpdf

Reference74 articles.

1. Multi-scale fish-habitat associations and the use of habitat surrogates to predict the organization and abundance of deep-water fish assemblages;Anderson;Journal of Experimental Marine Biology and Ecology,2009

2. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling;Austin;Ecological Modelling,2002

3. Accounting for dispersal and biotic interactions to disentangle drivers of species distributions and their abundances;Boulangeat;Ecology Letters,2012

4. Random forests;Breiman;Machine Learning,2001

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4. Use of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook;Machine Learning for Ecology and Sustainable Natural Resource Management;2018

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