Field Ecology
Designing, carrying out and analyzing field studies, following one invented prairie pothole grazing study: questions, hypotheses and causal inference, replication, blocking, pseudoreplication, BACI designs and simulation-based power analysis, research permits, IACUC animal care, tribal research partnerships and the CARE principles, field safety and biosecurity, sampling designs, quadrats, transects and plotless methods, distance sampling, mark–recapture, removal, occupancy, spatial capture–recapture and eDNA, species accumulation, Chao2 and beta diversity, vegetation, soil, water and microclimate measurements, GPS telemetry, home ranges and resource selection, spatial autocorrelation, landscape metrics, GIS and NDVI, GLMs, mixed models and ordination, and a capstone on long-term monitoring, open data and a field study proposal, with seeded Python examples throughout.
BIOL-430 Year 4 3 credits 12 lessons · 5 h 11 min
Offered by HSM University · Biology
This is the American version of this course. See the Canadian version.
What you'll learn
- Turn an observed ecological pattern into a specific, answerable field question with competing hypotheses, distinguishing predictions and a justified scale of study.
- Design field studies and experiments with correct experimental units, replication, controls, randomization and blocking, avoid pseudoreplication, and use BACI designs and simulation-based power analysis.
- Plan fieldwork that meets permit, animal care, Indigenous partnership and data governance requirements in Canada or the United States, with a field safety plan and biosecurity protocol.
- Choose and apply simple random, stratified, systematic, cluster and adaptive sampling designs, allocate effort among strata, and select quadrat, transect and plotless methods suited to the organism.
- Estimate density from quadrat counts and from line- and point-transect distance sampling, diagnose clumping and correct counts for imperfect detection.
- Estimate abundance and detection probability with mark–recapture, removal, occupancy, N-mixture, spatial capture–recapture, camera trap and eDNA methods, and evaluate their assumptions.
- Measure field biodiversity with accumulation curves, incidence-based estimators, beta diversity partitions, functional and phylogenetic measures, bioacoustics and community science data.
- Measure vegetation structure, cover, woody basal area, soils, water, microclimate and phenology with standard, repeatable methods and calibrated observers.
- Analyze telemetry data to estimate home ranges, habitat selection and movement behavior, and handle capture, welfare and location data responsibly.
- Quantify spatial autocorrelation and scale, compute landscape metrics, work correctly with coordinate systems and use remote sensing indices such as NDVI with field validation.
- Prepare tidy, documented data and analyze field data with generalized linear models, mixed models, model selection and ordination.
- Design long-term monitoring with adequate power, link it to adaptive management, share data following FAIR and Indigenous data principles, and write a complete field study proposal.
Course content
12 lessons · 5 h 11 min total · final exam
- 1 Asking ecological questions in the field 28 min · quiz
- 2 Designing field studies and experiments 27 min · quiz
- 3 Planning fieldwork: permits, ethics, safety and Indigenous partnerships 27 min · quiz
- 4 Sampling designs 26 min · quiz
- 5 Estimating abundance I: plots, transects and distance sampling 24 min · quiz
- 6 Estimating abundance II: mark–recapture, removal and detection 25 min · quiz
- 7 Measuring biodiversity in the field 24 min · quiz
- 8 Vegetation, habitat and environmental measurements 25 min · quiz
- 9 Animal movement and telemetry 25 min · quiz
- 10 Spatial ecology, GIS and remote sensing 26 min · quiz
- 11 Analyzing field data: GLMs, mixed models and ordination 28 min · quiz
- 12 Capstone: long-term monitoring, open data and a field study proposal 26 min · quiz
- E Final exam 20 questions
Requirements
Recommended background. You can start any course at any time.
Description
Designing, carrying out and analyzing field studies, following one invented prairie pothole grazing study: questions, hypotheses and causal inference, replication, blocking, pseudoreplication, BACI designs and simulation-based power analysis, research permits, IACUC animal care, tribal research partnerships and the CARE principles, field safety and biosecurity, sampling designs, quadrats, transects and plotless methods, distance sampling, mark–recapture, removal, occupancy, spatial capture–recapture and eDNA, species accumulation, Chao2 and beta diversity, vegetation, soil, water and microclimate measurements, GPS telemetry, home ranges and resource selection, spatial autocorrelation, landscape metrics, GIS and NDVI, GLMs, mixed models and ordination, and a capstone on long-term monitoring, open data and a field study proposal, with seeded Python examples throughout.
Part of the Science stream, typically taken in year 4.