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FISH 506E

A History of Fisheries

FISH 506E Credits: 3

This multi-disciplinary course examines the history of human fishing from ancient times in order to understand its impacts on natural ecosystems, biodiversity and human communities, drawing lessons for sustainability and future development. Focused on the development of fishing technology, the course is illustrated with many examples and case studies world-wide, and includes a historical review of BC fisheries. Some prior knowledge of fisheries and fishing gear (such as covered in FISH 520) will be useful and as part of the study of the origins of fishing technology, students may learn how to make a net (this will depend on help from Joe Bauer).

Tony Pitcher
Not offered in 2023/24

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FISH 506F / ANTH 461

Traditional Ecological Knowledge in Fisheries Management – Current Topics in Fisheries

FISH 506F / ANTH 461 Credits: 3

This course will focus on the role of traditional & local ecological knowledge in environmental assessment processes and in the development of resource management plans. Natural resource management approaches have long been critiqued for highlighting bio-economic features over cultural and social aspects of the human/environmental interface. Practitioners have come a long way over the past several decades and are now open to incorporating local systems of knowledge into management plans. The difficulty is how to do this.

Charles Menzies
Not offered in 2023/24

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FISH 506G / SPPG 544

Economic Foundations of Environmental Policies

FISH 506G / SPPG 544 Credits: 3

Environmental and natural resource economics: externalities, property rights, public goods, market failure, inter-generational trade-offs, and optimal extraction of biological and depletable resources. Environmental regulation, industrial competitiveness, and distribution of income and welfare.

Rashid Sumaila

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Section Activity Term Days Times Instructors

FISH 506H / STAT 547N

Statistics in Ecology and Marine Sciences

FISH 506H / STAT 547N Credits: 1.5

Data in ecology and marine sciences are frequently associated with large challenges. This class will introduce some of the challenges of using statistics to answer questions in ecology and marine sciences and the statistical tools developed to handle them. This course is a statistics class for graduate students in the Department of Statistics (STAT) and the Ocean and Fisheries Graduate program (OCF). This class is intended for students with good statistics background and some familiarity with R. The class is not recommended for students with little experience analyzing data and those with limited R programming skills.

Marie Auger-Méthé
Not offered in 2023/24

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FISH 506I

Co-Creating Aquatic Science

FISH 506I Credits: 3

This course, co-created with members of the Haida Nation, will train and empower the next generation of researchers seeking to co-create science for the betterment of aquatic systems. Co-Creating Aquatic Science is an interdisciplinary, multi-generational, and profoundly relational course. This course is presented ONLINE, with an in-person gathering. Enrolment in this course is selective, and class size is small.

Andrea Reid

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Section Activity Term Days Times Instructors

FISH 506J

Managing nature: the case of fisheries

FISH 506J Credits: 3

Course will be taught online, with part of the audience at UBC and part at Paris-Dauphine. It is projected that available technology will allow 7 sessions to be held in-person at UBC, with the Dauphine audience attending remotely, and 7 sessions to be held in-person at Dauphine, with the UBC audience attending remotely. If technology fails, 12 sessions will be held remotely at both sides, and 2 sessions will be held, in-person and separately, at each site.

Rashid Sumaila and Ivar Ekeland (Dauphine)

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Section Activity Term Days Times Instructors

FISH 506M

Effective scientific poster communication

FISH 506M Credits: 1

Most scientists, particularly in the early phases of their career, are expected to present the results of their research in the form of a conference poster. Yet unlike oral presentations, students receive little training on this mode of scientific communication. The course material will be conveyed through a series of weekly instructor and student-led seminars that include presentations and group discussion. This course is offered in-person only.

David Rosen

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FISH 506R

Fisheries and Population Modelling Methods Using R

FISH 506R Credits: 3

R (R Core Team 2019) is the most commonly used programming language for fisheries and ecological modeling and data analysis. Courses in ecology and statistics have become commonly taught with R as the statistical software of choice. R is used, among other things, for conventional statistical analyses, for plotting purposes, to code up computer simulation models representing fish, invertebrate and mammal population dynamics, and to manage implementations of Bayesian statistical packages such as WinBUGS, JAGS and STAN.

Murdoch McAllister
Not offered in 2023/24

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FISH 505

Quantitative Analysis of Fisheries 2

FISH 505 Credits: 3

This course examines advanced concepts and methods in fish population dynamics and stock assessment, with emphasis on design of harvest policies for sustainable fisheries. Through a mixture of lecture and tutorial sessions, students learn to apply the main methods used today for fisheries assessment, along with pitfalls and examples of where these methods have failed.

Murdoch McAllister
Not offered in 2023/24

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Section Activity Term Days Times Instructors

FISH 504

Quantitative Analysis of Fisheries 1

FISH 504 Credits: 3

This course provides an introduction to the quantitative theories of fishery dynamics, and the use of various types of analytical methods for fishery assessment. Lectures are supplemented with tutorial sessions, mainly using Microsoft Excel, where students first work on set problems in class, followed by extended analyses to consolidate understanding and familiarity with methods of analysis.

Murdoch McAllister

Sections (1)

Section Activity Term Days Times Instructors
001 Lecture 1 Murdoch McAllister