Conservation Ethnobiology Field School 2012

Environmental Monitoring

Objectives

The collection of environmental data is not an end in itself. It must always be viewed in the context of helping understand a particular problem.

Questions Link

The primary concerns involve the following attributes:

Determining the spatial and temporal context.
Obtaining and viewing data at an appropriate resolution.
Knowing the accuracy of the data, especially when there is interpolation.
Displaying data in ways that support interpretation.
Combining data from a variety of sources.

Note that this football does not support climate specialists or people working on ecophysiology problems. Those are more specialized concerns.

Temporal Context

Where possible, the measurements are related to the following parameters.

Rainfall (daily)
Fog/Clouds (daily)
Snow (daily)
Temperature (hourly)
Humidity (hourly)
Wind speed (hourly, integrated from shorter period)
Solar Radiation (hourly, integrated from shorter period)
Stream or River flow (e.g., gauge height; daily/weekly)
Flooding (annual; start, duration, extent)
Fires (annual; season)

Spatial Context

Maps with the following information

Data recording sites
Prominent cultural features (e.g., cities, villages, special facilities)
Vegetation (e.g., vegetation cover map)
Soils
Streams and rivers
Flood inundation
Tsunami inundation
Historical fires
Transportation routes
Land use (e.g., crops, ownership, protection)
Cultural areas (e.g., parks, sacred areas)
Sociological (e.g., dominant ethnic group, tribe)

Extreme (Rare Episodic) Event Context

Tsunami inundation
Hurricane/Cyclone risk
Earthquakes
Landslides
Extensive Fires
Extreme Flooding

Data Display and Integration

Temperature and rainfall as Climate Diagrams

Wind as a Rose Diagram

Temperature Bar Charts of daily High, Low and Median

Temperature as a monthly distribution Map

Humidity Bar Charts of daily High, Low and Median

Rainfall as a daily total Bar Chart

Rainfall as a seasonal accumulation Bar Chart

Rainfall as a monthly distribution Map

Light as a spatial distribution Map

Data Sources

External Sources

Climate Summaries and Current Weather (temperature, rainfall)
Hydrology,
Extreme Events: Hurricanes/Cyclones, Floods, Tsunamis
Land Use & Vegetation (including conservation areas)

Local Sources

Skills

Data measurement
Data collection (external sources)
Data display & interpretation
Data analysis (statistics)

Hardware

Software

Literature

Skill/Behavioral Levels

Novice

Makes a few spot measurements if directed to do so.
Relies on equipment provided by other people.
Trusts the values produced by the equipment.
Does not calibrate equipment.
Transfers data well after the measurements have been taken.
Makes no efforts to integrate the data with other sources.
Does not participate in the analysis of the data.

Advanced Beginner

Conducts some searching for existing data before making any measurements.
Helps arrange to have the proper equipment available.
Tests the equipment before it is deployed.
Transfers the data soon after it is collected.
Analyzes the data superficially, usually long after all data are collected.
Uses an experimental design provided by other people.
Does not put the data into an historical or temporal context.

Competent

Promptly backs up the data and begins the analyses.
Uses a variety of data analysis techniques to assess and portray the temporal and spatial attributes of the data.
Interprets the data in the context of other studies.
Selects, calibrates and tests all of the equipment.
Properly stores equipment between uses.

Proficient

Prepares the data analysis workflow well ahead of time.
Quickly notes unexpected data values so these can be handled appropriately.
Creates qualitative categories for the measurements and applies these to the data.

Expert

Some Resources

Climate Diagrams

Last Updated: September 23, 2011.

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