Continuing
Education Courses
If you plan to attend any of theses
courses, you must sign-up when you register for the meeting. Course registration deadline is
Information-Theoretic Approaches to Empirical Science
Basic/Intermediate
GIS Techniques for Fisheries Biologists
Advanced
GIS Techniques for Fisheries Biologists
Introduction
to Sturgeon Research Techniques
Mapping
Aquatic Habitat of Inland Freshwater Systems using Side-Scan Sonar
Introduction to Programming in R for Fisheries
Scientists
Natural
Channel Design: Instream Structures for Habitat Enhancement
Introduction
to Instream Habitat Modeling using MesoHABSIM
Choosing the Appropriate
Biotelemetry Technology for Aquatic Research
2008 Continuing
Education Courses
The Continuing
Education Committee (
Instructor: Dirk
Miller, 307-777-4556, Dirk.Miller@wgf.state.wy.us
CEUs:
N/A
Date/Time: Sunday,
August 17,
Tuition:
Are you currently an officer of an
Issues to be addressed include:
Basic/Intermediate
Instructor: Joanna Whittier, 785-532-6634;
whittier@ksu.edu
CEUs: 0.8
Date/Time: Saturday, August 16,
Tuition: Student $125, Member $220,
Non-member $250
This course will provide an overview and review of basic
skills with a focus on
Advanced
Instructor: Joanna Whittier,
785-532-6634; whittier@ksu.edu
CEUs: 0.8
Date/Time: Sunday, August 17,
Tuition: Student $150, Member $220,
Non-member $270
For those who are comfortable in their basic skills in
Introduction to Sturgeon
Research Techniques
Instructors: Kim Damon-Randall, 978-281-9300 ext. 6535
Kimberly.Damon-Randall@noaa.gov
Tom
Savoy, Jerre Mohler, Dewayne Fox, Christian Hager and Doug Peterson
NOAA
Fisheries Service and Atlantic States Marine Fisheries Commission
CEUs: N/A
Date/Time: Sunday, August 17,
Tuition: Student $100, Member $150,
Non-member $170
In general, there
is a lack of information available on many aspects of the life history of several
North American sturgeon species. Often, this information is imperative to
determining appropriate recovery actions for the species, some of which may be
listed under the U.S. Endangered Species Act and/or the Canadian Species at
Risk Act. Consequently, it is necessary to conduct research on these fish in a
manner that minimizes adverse impacts to the fish while ensuring that the
crucial information on abundance and life history characteristics is obtained.
Much has been learned in recent years regarding appropriate sampling techniques
for many sturgeon species. This workshop will provide an opportunity to conduct
various procedures such as laparoscopies, necropsies, surgical implantation of
tags, gastric lavage, blood and tissue collection, ageing, and other research
techniques on sturgeon under the tutelage of experienced researchers. Training
on these techniques for Atlantic sturgeon has been identified as a need by the
Atlantic States Marine Fisheries Commission’s Atlantic Sturgeon Technical
Committee and NOAA’s National Marine Fisheries Service. This course is
appropriate for new sturgeon researchers as well as a refresher for existing
fisheries professionals.
Mapping Aquatic
Habitat of Inland Freshwater Systems
Using Side-Scan
Sonar
Instructors: Adam J. Kaeser, 229-430-4256, adam.kaeser@dnr.state.ga.us
CEUs: n/a
Date/Time: Sunday, August 17,
Tuition: Student $50, Member $100,
Non-member $150
Session I Introduction to side scan sonar, mission
planning and image interpretation
Session II The mission process (capturing and working
with sonar data) Session
Session IV Habitat assessment and mapping applications
A need exists within the natural
resource community for an inexpensive and rapid technique for mapping and
quantifying benthic habitat features of navigable waterways to facilitate
research and management of aquatic fauna and their environments at the
landscape level. Unlike more expensive side scan sonar devices, the
recently-released Humminbird® side imaging system employs
a transducer that can be mounted directly to a small boat thus enabling the
survey of previously inaccessible waterways that include shallow, rocky
areas. We have developed a novel
technique utilizing ArcGIS to merge and transform images to match the actual
configuration of the underwater landscape. The end product is a
Target Audience: This workshop provides a timely introduction to the use of side scan
sonar in inland freshwater systems, and is geared toward all natural resource
professionals interested in sonar mapping of aquatic habitat.
Background Required: Some familiarity with
Introduction to Programming in R for Fisheries Scientists
Instructors: Elise Zipkin, 301-497-5810, ezipkin@usgs.gov, Patuxent
Wildlife Research Center, USGS.
Cheryl
Murphy, camurphy@msu.edu, Department of
Fisheries and Wildlife,
CEUs: 0.7
Date/Time: Sunday,
August 17,
Tuition: Student
$75, Member $125, Non-member $175
The language R is a powerful open-source mathematical and
statistical
software program (available for free at: http://www.r-project.org/).
The
program R is becoming increasingly popular among ecological and fisheries
scientists because of (1) the extensive number of built in tools that can
be used for data analysis and modeling and (2) the ability to easily create
one's own scripting programs. The goals of this workshop are to teach the
basics for getting started in R (and using a command line interface) as
well as to introduce participants to the capabilities of this powerful
programming package. Specifically, participants will learn how to enter and
import data into R; perform interactive computations and use built-in
functions; plot data and develop graphic capabilities; perform simple
statistical analyses; and become familiar with how to find help for future
questions with R. Examples will focus on current issues in fisheries
science such as estimating stock-recruitment relationships, fitting
length-at-age data to a von Bertalanffy growth model,
projecting population
trends, etc. We assume that participants have no prior experience with R.
Natural Channel
Design: Instream Structures for Habitat
Enhancement
Instructors: John Parish, 905-877-9531; jparish@parishgeomorphic.com Wolfgang Wolter,
519-886-2160; wwolter@tsh.ca
Ontario
Chapter in conjunction with Parish Geomorphic Ltd. and
CEUs: 0.6
Date/Time: Sunday August 17,
Tuition: Student $75, Member $125,
Non-member $175
A case study will be presented that encompasses topics
presented earlier in the session such as the physical, biological and technical
aspects of structure design. Material will be presented in lecture format with
encouragement of participation from students.
Topics include:
Introduction to
Instream Habitat Modeling using MesoHABSIM
Instructor: Piotr
Parasiewicz, 413-687-4740, Piotr@rushingrivers.org
Rushing Rivers Institute
CEUs: 1.2
Date/Time: Saturday, August 16,
Sunday,
August 17,
Includes
3 hours of field work.
Tuition: Student $150, Member $220,
Non-member $270
River
restoration planning demands tools capable of quantifying the consequences of
flow and channel modification at various temporal and spatial scales. The
Rushing Rivers Institute focuses on developing an efficient habitat assessment
approach to analyze functional relationships between river biota and their
physical environment at the watershed scale. A recently developed habitat
modeling approach, called MesoHABSIM, and its associated software, SimStream,
is experiencing growing popularity in river restoration and management planning
throughout the
Key Outcomes: The objective of
this course is to introduce the participants to the process of a new,
groundbreaking method in instream habitat modeling. After completed, course participants will
have knowledge of habitat modeling techniques and a good understanding of the
principles and processes involved in the MesoHABSIM approach. It will help them
to utilize the approach and/or its components for the benefit of riverine
fisheries restoration and management.
Target audience: Researchers, fisheries
professionals and managers of any level who want to get the general knowledge
about this technique and may consider applying it in their profession.
Information-Theoretic Approaches to Empirical Science
Instructor: David
R. Anderson, quietanderson@yahoo.com
CEUs: N/A
Date/Time: Sunday,
August 17,
Tuition: Student
$150, Member $165, Non-member $200
Tuition fee includes a new
textbook: Anderson,
D. R. 2008. Model based inference in the
life sciences: a primer on evidence. Springer,
This course is a
1-day
overview of a new science paradigm based on Information Theory. Kullback-Leibler
information is the basis for model selection using Akaike’s
Information Criterion (AIC). The course
deals with science philosophy, as much as data analysis and model
selection. The focus is on quantitative evidence for multiple science
hypotheses. This general approach
includes ranking the science hypotheses; examination of the probability of
hypothesis j, given the data; and
evidence ratios. Once these concepts
have been presented, the discussion shifts to making formal inference from all
the hypotheses and their models (multimodel
inference). Additional details can be
viewed at http://aicanderson2.home.comcast.net.
Key Outcomes: Attendees will have a good overview of these
new approaches and many people will be able to perform analyses with their own
data. The computations required are
quite simple once the parameter estimates have been obtained for each model.
Target Audience: Graduate students, post-docs, faculty, and
research people in various agencies and institutes. People involved in research and science where
their work involves hypothesizing and modelling and their inferences are model
based will gain from this material.
Background Required: Attendees should have a decent background in
statistical principles and modelling (this is NOT a modelling course). The course focuses on science, science
philosophy, information and evidence.
The amount of mathematics or statistics presented in the course is
relatively meager; however, without a good
understanding of linear and nonlinear regression, least squares and maximum
likelihood estimation, one will struggle to understand some of the material to
be presented.
Why Take This Course? A substantial paradigm shift is occurring in
our science and resource management. The
past century relied on null hypothesis testing, asymptotic distributions of the
test statistic, P-values and a ruling
concerning “significant” or “not significant.”
Under this analysis paradigm a test statistic (T) is computed from the data.
The P-value is the focus of
the analysis and is the Prob{T or more
extreme, given the null hypothesis].
With this definition in mind, we can abbreviate slightly. Prob(X|Ho), where it is understood that X represents the data or more extreme (unobserved) data.
The null hypothesis (Ho) takes
centre stage but is often trivial or even silly. The alternative hypothesis (HA) is not the subject of the
test; “support” for the alternative occurs only if the P-value (for the null hypothesis) is low, (often <0.05). Support for the alternative hypothesis comes
by default and only when the Prob{data|Ho}
is low.
The proper interpretation of the P-value
is quite strained: this might explain why so many people erroneously pretend it
means something quite different (i.e., the probability that the null hypothesis
is true). This is not what is meant by a
P-value.
These traditional methods are being replaced by “information-theoretic”
methods (and to a lesser extent, at least at this time, by a variety of
Bayesian methods). These approaches
focus on an a priori set of plausible
science hypotheses,
H1,
H2, …, HR .
Evidence for or against members of this set of “multiple working
hypotheses” consists of a set of probabilities.
Specifically, Prob{H1, H2, …, HR , given the
data} or Prob(Hj|X}. These probabilities are direct evidence, where evidence = information =
-entropy.
Simple evidence ratios allow a measure of the formal strength of
evidence for any two science hypotheses.
Note the radical difference in the probability statements (above) stemming
from either a P-value or the
probability of hypothesis j. Statistical inference should be about models
and parameters, conditional on the data, however, P-values are probability statements
about the data, conditional on the null hypothesis.
These new approaches (including Bayesian methods) allow statistical
inference to be based on all (or some) of the models in the a priori
set, leading to a robust class of methods termed “multimodel
inference.” That is, the inference is
based on all the models in the set.
Alternative science hypotheses take centre stage in these approaches and
will require much more attention than in the past century (where one started
with an alternative and the null was merely “nothing” or the naïve position:
thus, little science thinking was called for).
The set of science hypotheses “evolves” through time as implausible
hypotheses are eventually dropped from consideration, new hypotheses are added,
and existing hypotheses are further refined.
Rapid progress in the theoretical or applied sciences can be realized as
this set evolves, based on careful inferences from new data. This is an exciting time to be in science or
science-based management. There are
important philosophies involved here: these approaches go well beyond methods
for just “data analysis.”
Choosing the Appropriate Biotelemetry Technology
for Aquatic Research
Instructor: Mitchell
M. Sisak, (905) 836-6680; mitch.sisak@lotek.com
Lotek
Wireless Inc.
CEUs: 0.8
Date/Time: Sunday,
August 17,
Tuition: Student
$60, member $80, Non-member $100
The field of
microelectronics has seen an explosive growth over the last decade. With this
growth in electronics comes an attendant increase in the variety of
technologies being applied to the field of wildlife telemetry. Faced with the
ever-widening range of technologies available to remotely monitor animal
movement and behavior, researchers tasked with selecting an appropriate
technology often find themselves with too many choices and too few tools with
which to make an informed decision. This often results in the selection of
inappropriate technology or its misuse. In other instances, lack of knowledge
of the existence of a particular technology results in the erroneous decision
not to pursue a particular study as it is deemed technically unfeasible. A
further benefit common to most evolving telemetry technologies is the promise
of increased data volume but an unfortunate impact is the increased time required
for data verification, reduction, and analysis. Once again, new tools and
techniques are available to assist with data analysis, but many are not
commonly employed by the telemetry community. This course will present
researchers and their managers with an overview of the technologies currently
available, as well as technologies under development which show promise in the
field of aquatic research.