Spring 2027

Wildlife Management Techniques

Wildlife Management Techniques covers preparation of collections, analyses of food habits, sex and age determinations, censuses, trapping and banding, planting food and cover, and research techniques.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 5

Recent recorded grades — Fall 2023: 3.23 GPA, 65.7% A/AB (n=35 letter grades); Fall 2024: 3.55 GPA, 81.8% A/AB (n=33 letter grades); Fall 2025: 3.54 GPA, 78.4% A/AB (n=37 letter grades).

What you’ll be able to do

  • Identify and list various wildlife research techniques, such as GIS, GPS, animal capture, and tracking methods

  • Explain the principles and applications of different wildlife research techniques, including the use of trail cameras and habitat surveys

  • Use field equipment and techniques, such as radio-tracking and stable isotope analysis, in real-world wildlife research scenarios

  • Analyze data collected from field experiments, such as mark-recapture and occupancy models, to draw meaningful conclusions about wildlife populations and behaviors

  • Critically evaluate the effectiveness and limitations of various wildlife research techniques and methodologies discussed in the course

  • Design and propose a comprehensive wildlife research project, incorporating appropriate techniques and methodologies learned throughout the course

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

None

  • None
F&WECOL 561 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • None

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.

Meeting source records
Download part 1

Student experience

the class

Recent recorded grades — Fall 2023: 3.23 GPA, 65.7% A/AB (n=35 letter grades); Fall 2024: 3.55 GPA, 81.8% A/AB (n=33 letter grades); Fall 2025: 3.54 GPA, 78.4% A/AB (n=37 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Preparation of collections, analyses of food habits, sex and age determinations, censuses, trapping and banding, planting food and cover, and research techniques.
  • Wildlife research techniques including GIS, GPS, animal capture, and tracking methods.
  • Principles and applications of wildlife research techniques, including trail cameras and habitat surveys.
  • Field equipment and techniques such as radio-tracking and stable isotope analysis in real-world scenarios.
  • Data analysis from field experiments using mark-recapture and occupancy models for wildlife populations and behaviors.
  • Design and proposal of a comprehensive wildlife research project.

Skills

  • Preparing collections, analyzing food habits, determining sex and age, conducting censuses, trapping and banding, and planting food and cover.
  • Identifying and listing wildlife research techniques including GIS, GPS, animal capture, and tracking methods.
  • Explaining principles and applications of wildlife research techniques, including trail cameras and habitat surveys.
  • Using field equipment and techniques like radio-tracking and stable isotope analysis in real-world scenarios.
  • Analyzing data from field experiments using mark-recapture and occupancy models to draw conclusions about wildlife populations.
  • Critically evaluating the effectiveness and limitations of various wildlife research techniques and methodologies.
  • Designing and proposing a comprehensive wildlife research project incorporating appropriate techniques and methodologies.

Grades

Latest available · Fall 2025— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2025

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Fall 2025 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1316 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records

No offering records for the selected term.

Raw records 
[]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews

No records available.

Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "744071a83de2072ec3580c8190e2cd59c93189444724f9093f4377446895ac69",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}