NCEA Level 2 Education for Sustainability cheat sheet

Sustainable development (Brundtland, 1987): meeting present needs without compromising the ability of future generations to meet theirs.

Three pillars / triple bottom line: environmental, social, economic - sustainability requires all three, not just environmental protection.

Weak sustainability: natural capital is substitutable by human-made capital. Strong sustainability: some natural capital is critical and non-substitutable.

Carrying capacity: the maximum population or load an ecosystem can support indefinitely without degradation.

Ecological footprint measures demand on biologically productive land and water in global hectares (gha); biocapacity is supply. Footprint > biocapacity = ecological deficit.

Earth Overshoot Day marks the date when humanity's annual demand exceeds what ecosystems regenerate that year.

Planetary boundaries: nine Earth-system processes (e.g. climate change, biodiversity loss, nitrogen cycle) with thresholds defining a safe operating space.

Precautionary principle: where serious or irreversible harm is possible, lack of full certainty is not grounds for postponing cost-effective measures.

Polluter pays principle: the party causing pollution bears the cost of managing it, not the community or environment.

Interdependence: a change in one system produces flow-on effects in the others; analyse chains of cause and effect rather than isolated impacts.

Environmental degradation usually hits social and economic wellbeing unevenly - lower-income groups and minorities often bear more cost (environmental justice).

Ecosystem services: provisioning (food, water, timber), regulating (climate, pollination, water purification), cultural (recreation, identity), supporting (soil formation, nutrient cycling).

Externalities are costs or benefits not reflected in market price - e.g. carbon emissions, water pollution - and are a key cause of market failure in sustainability.

Linear economy (take–make–dispose) vs circular economy (design out waste, keep materials in use, regenerate natural systems).

Social licence to operate: community acceptance a business needs; loss of it can halt operations regardless of legal compliance.

Cultural values and practices shape resource use - loss of language and traditional knowledge often accompanies loss of biodiversity and land.

Tragedy of the commons: shared, unregulated resources can be over-exploited; Ostrom showed community rules and boundaries can prevent this.

Mātauranga Māori is a body of knowledge, values and practices developed by Māori over generations, transmitted orally and through practice; it is not a subset of Western science.

Kaitiakitanga: the obligation of guardianship and care for the environment, held by tangata whenua; it is a responsibility, not optional stewardship.

Mauri: life force or vitality present in people, land, water and ecosystems; damaging mauri is a cultural harm, not only a physical one.

Whakapapa connects people to ancestors, land and species, grounding identity and relationships with place.

Tapu and rāhui are customary restrictions that can function as conservation tools (e.g. temporary harvest bans after a death or to protect a resource).

Te Tiriti o Waitangi / Treaty of Waitangi: partnership, participation and protection principles; iwi/hapū participation in resource management is a legal and ethical expectation.

Mātauranga and science are complementary knowledge systems; best practice is genuine co-management with shared authority, not consultation after decisions are made.

Different cultural perspectives (Pacific, Asian, European, indigenous) produce different priorities - e.g. collectivist vs individualist views of resource use - and these shape acceptable solutions.

Cultural sustainability includes language, customs, and access to traditional sites and resources; it is a pillar in its own right, not a subset of social.

Issue vs problem: an issue is contested and involves differing values and stakeholders; a problem has an agreed solution path.

Cause–effect chain: direct cause → underlying cause → root cause. Root causes are often economic incentives, policy gaps or values, not individual behaviour.

Stakeholder analysis: identify who is affected, who has power, who has knowledge, and whose interests conflict.

A good inquiry question is specific, place-based, measurable and answerable with available data.

Primary data: surveys, interviews, field measurement, observation. Secondary data: council reports, statistics, scientific papers, iwi records.

Reliability: repeatable methods, sufficient sample size, consistent measurement. Validity: the data actually measures the factor claimed.

Bias sources: leading survey questions, small or non-representative samples, selective use of evidence, and single-source reliance.

Environmental impact indicators include water quality (e.g. E. coli, nitrate), biodiversity counts, soil erosion, air quality, and greenhouse gas emissions.

Systems mapping (e.g. causal loop diagrams) reveals feedback loops - reinforcing loops amplify change, balancing loops resist it.

Action types: personal (behaviour change), collective (school/community projects), civic (submissions, petitions, voting), and entrepreneurial (social enterprise).

Effective action targets causes, not just symptoms - a beach clean-up addresses symptoms; a product redesign or bylaw addresses causes.

SMART goals: specific, measurable, achievable, relevant, time-bound; without a baseline you cannot show change.

Evaluation needs indicators measured before and after, plus a comparison or control where possible.

Outcome types: direct outputs (trees planted, kg recycled), outcomes (change in behaviour or state), and impacts (longer-term environmental/social change).

Unintended consequences must be checked - e.g. a plastic-bag ban increasing paper-bag use with higher carbon footprint.

Attribution problem: other factors (weather, policy, season) may explain observed change; state this limitation explicitly.

Success criteria should include participation and equity, not only environmental metrics - who was involved and who benefited.

Reflection on what would be done differently is part of evaluation; evidence of monitoring matters more than claims of success.

Scenarios are plausible, not predictions: explore at least three - business-as-usual, sustainable transition, and a disruptive/regenerative future.

Backcasting: define a desired future state, then work backwards to identify the steps needed now. Contrast with forecasting from current trends.

Precautionary approach vs cost–benefit: weigh irreversible risks more heavily than reversible ones.

Intergenerational equity: decisions are judged by their effect on future generations, who have no voice in present decisions.

Time horizons matter - short electoral and business cycles often conflict with long ecological timescales; policy design can correct this.

Trade-offs and synergies: list who gains and who loses from each option; sustainability decisions usually involve distributional choices.

Adaptive management: act, monitor, learn, adjust - treat decisions as experiments where uncertainty is high.

Resilience vs efficiency: highly optimised systems can be brittle; diversity and redundancy increase the capacity to absorb shocks.

Decision tools: multi-criteria analysis, life-cycle assessment, and stakeholder deliberation each make values and weightings explicit.

Issue vs problem: an issue is contested and involves differing values and stakeholders; a problem has an agreed solution path.

Cause–effect chain: direct cause → underlying cause → root cause. Root causes are often economic incentives, policy gaps or values, not individual behaviour.

Stakeholder analysis: identify who is affected, who has power, who has knowledge, and whose interests conflict.

A good inquiry question is specific, place-based, measurable and answerable with available data.

Primary data: surveys, interviews, field measurement, observation. Secondary data: council reports, statistics, scientific papers, iwi records.

Reliability: repeatable methods, sufficient sample size, consistent measurement. Validity: the data actually measures the factor claimed.

Bias sources: leading survey questions, small or non-representative samples, selective use of evidence, and single-source reliance.

Environmental impact indicators include water quality (e.g. E. coli, nitrate), biodiversity counts, soil erosion, air quality, and greenhouse gas emissions.

Systems mapping (e.g. causal loop diagrams) reveals feedback loops - reinforcing loops amplify change, balancing loops resist it.