4. Indicators for sustainable development Flashcards

1
Q

What is the difference between an indicator an index?

A

Indicators measure a single topic.

An index merges multiple indicators.

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1
Q

Describe the two ways of measuring sustainable development.

A
  1. Summarize everything in an aggregated index. E.g. human development index, combining many indicators.; Happy Planet Index.
  2. Not striving to tell everything but creating an Indicator collection. E.g.: Sustainable Development Goals.
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2
Q

Name 1 strength and 1 weakness of indices.

A

Strengths

  • Single number
  • Easy to communicate

Weaknesses

  • Too simplistic and one dimensional: averages out (if one thing gets better, and one things gets worse, there would be no change)
  • Might have missing data and more incomplete
  • Calculation methods might be arbitrary (e.g. with normalisation)
  • You need to decide what is more important, and weighs more
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3
Q

Name 1 strength and 1 weakness of indicator collections

A

Strengths

  • Multi dimensional, holistic (can show nuances and trade offs)
  • No calculation errors

Weaknesses

  • Difficult to communicate, too much information
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4
Q

What does an indicator do?

A
  • Simplify complicated problems
  • Give insight in such problems
  • Quantify important underlying goals
  • Enable to support decision
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5
Q

What are two weaknesses of the Red List Index?

A
  • There might be differences in species distribution and vulnerable to presence/absence and monitoring;
  • Doesn’t account for invasive species that might have a detrimental impact
  • Monitoring might be costly despite working with volunteers
  • Doesn’t show drivers.
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6
Q

Describe 1 strength and 1 weakness of MSA.

A

Weakness:

  • Hard to decide baseline scenario
  • Strongly aggregates biodiversity data and pressures, giving all an equal weight

Strengths:

  • Gives info about ecosystem as a whole + interaction between species
  • Spatially explicit
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7
Q

Name three characteristics of a good indicator

A

A good indicator is:

  • Measurable
  • Comparable over time, space, etc.
  • Represents what you are trying to measure
  • Robust
  • Complete; helps capturing full system
  • Reproducible (for this it should be well documented and transparent)
  • Data should not be expensive
  • Sensitive to change
  • Easy to understand
  • Should be inclusive
  • Data should be collected and shared ethically
  • Should support decision making
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8
Q

What is the EU framework for measuring indicator quality?

A
  • Relevant; linked to the objectives
  • Accepted: by staff, stakeholders, scientists
  • Credible: unambiguous and easy to interpret
  • Easy to monitor
  • Robust against manipulation and error
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