The Wayback Machine - https://web.archive.org/web/20260207132640/https://courses.cornell.edu/search/?P=NTRES%204100

Search Results

Search Results for "NTRES 4100"

NTRES 4100 - Advanced Conservation Biology (4 Credits)  
Crosslisted with ENTOM 4100, BIOCB 4100  
This course integrates technical approaches to biodiversity conservation, with a focus on biological analysis of species facing extinction risk. Students will learn quantitative tools for analyzing variation at genetic, population, and landscape levels. The curriculum covers stage-structured population dynamics, predation, gene flow, inbreeding, extinction processes, and harvesting effects. Analytical methods include population-projection models, perturbation analysis, metapopulation models, population viability analysis, and various genetic diversity assessments. Special attention is given to evaluating extinction risk in data-deficient species such as insects. By developing these quantitative skills, students will critically evaluate assumptions underlying conservation plans and assessments, including IUCN criteria and endangered species classification. The course is suitable for all biology and conservation-related majors.
Prerequisites: an ecology class such as: NTRES 3100, BIOEE 3610 or ENTOM 4550; a genetics class such as: BIOMG2800, NTRES 2830 DNA or ENTOM 4700; or permission of the instructor.  
Distribution Requirements: (BIO-AS), (BSC-AG, DLG-AG, MQL-AG)  
Exploratory Studies: (CU-SBY)
Last Four Terms Offered: Fall 2024, Fall 2023, Fall 2022, Fall 2021  
Learning Outcomes:
  • Apply ecological and genetic principles to analyze patterns of biodiversity and assess extinction risks for threatened species.
  • Conduct population viability analyses (PVA) to quantify extinction risk and evaluate conservation interventions.
  • Analyze genetic diversity metrics including heterozygosity, inbreeding coefficients, and effective population size to inform conservation breeding programs.
  • Evaluate challenges in assessing extinction risk for data-deficient species, with special emphasis on insects and other understudied taxa.
  • Demonstrate proficiency in computational tools (R and other software) for conservation data analysis.
  • Effectively communicate complex conservation analyses through scientific writing and data visualization.