Spring 2027

Decision Methods for Natural Resource Managers

Decision Methods for Natural Resource Managers applies quantitative methods like optimization and simulation to managing natural resources, especially forests.

offering recorded3 credits
Recorded instructors · Spring 2027 Jennifer Raynor3.7/5

Summary

1 / 3

Recent recorded grades — Spring 2008: 3.11 GPA, 45.5% A/AB (n=22 letter grades); Spring 2026: 3.42 GPA, 76.9% A/AB (n=13 letter grades).

What you’ll be able to do

  • Quantify the timber and non-timber values of forest resources

  • Describe and apply financial decision criteria to evaluate forest investments

  • Explain how optimal rotation ages are determined and what factors affect this calculation

  • Create harvest scheduling models and apply them to diverse landowner objectives

  • Apply knowledge of mathematical models and financial theory to determine optimal rotation age for a given species and communicate findings in written and verbal formats

Source: UW Guide 1 UW Guide 2

Grade history

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average GPA
letter grades
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AB
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All recorded terms · compare terms & instructors

Prerequisites

Course map

MATH 112, 114, or 171 or placement into MATH 211 or 221. Not open to students with credit for A A E 652 prior to Fall 2025.

AAE/F&WECOL 430

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027
Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 5.00/5 from 1 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

RMP profile ↗ · All captured review dates; profile matched by name.

Recent recorded grades — Spring 2026: 3.42 GPA, 76.9% A/AB (n=13 letter grades).

Historical instructors & teaching patterns

JENNIFER RAYNOR is recorded teaching in Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

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

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 150
LEC 001Classroom Instruction0 / 150

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

Meeting source records

Student experience

the class

Recent recorded grades — Spring 2008: 3.11 GPA, 45.5% A/AB (n=22 letter grades); Spring 2026: 3.42 GPA, 76.9% A/AB (n=13 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Determining optimal rotation ages and the factors affecting these calculations.
  • Quantifying timber and non-timber values of forest resources.
  • Optimization and simulation techniques for natural resource management.

Skills

  • Apply quantitative methods, including optimization and simulation, to manage natural resources.
  • Create and apply harvest scheduling models to diverse landowner objectives.
  • Use financial decision criteria to evaluate forest investments.

Grades

Latest available · Spring 2026— 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 Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

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.

Selected offering source records
AAE/F&WECOL 430 · Spring 2027

Decision Methods for Natural Resource Managers

Recorded 2026-10-14
AAE/F&WECOL 430 · Spring 2027

Decision Methods for Natural Resource Managers

Recorded 2026-10-14
Raw records
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Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
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