Cumulative effects in assessment
Ecological baselines and landscape models show how several projects together affect a habitat or species, which a single project assessment would miss.
GRF · Climate and Nature Governance
Ecology and biodiversity science for climate and nature governance
Ecology explains how ecosystems function, change and respond to pressure. In nature governance it gives the evidence behind protected-area design, impact assessment, restoration targets and nature-related disclosure, and it shows where thresholds and cumulative effects make permit-by-permit decisions unreliable.
01Register
Key facts.
Method recordSTEM method
- MethodEcology and biodiversity science
- StewardBiodiversity Nexus
- Applied inClimate and Nature Governance
- Data4 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What ecology and biodiversity science does here.
Ecology studies the interactions among organisms and between organisms and their environment, from populations to ecosystems. It explains how biodiversity loss and ecosystem change alter services such as pollination, water regulation and disease control. In climate and hazards, biodiversity and nature, water and food and agriculture, ecological assessment identifies dependencies of agriculture, water and health on natural systems. It supports nature-related disclosure and the evaluation of tipping-point risks. The canonical description is on the STEM Commons.
Protected-area representativeness
Ecoregion and species range data test whether a protected-area network covers the range of ecosystems, beyond its total area.
Restoration monitoring
Indicators of vegetation structure, species composition and function are tracked against reference sites to judge whether restoration meets its stated objectives.
03Geography
Habitat condition in the Andes.
Land cover, vegetation, plant growth and population density over the Andes, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 4
Habitat condition, for this page
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- MODIS Terra EVI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite index; clouds leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 250 m grid
- Uncertainty
- Satellite vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest 8-day period GIBS publishes)
- Source
- MODIS Aqua GPP (MYD17) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- 8-day; Satellite-driven model; latest 8-day period GIBS publishes
- Newest at build
- 2026-09-30
- Resolution
- about 500 m grid
- Uncertainty
- Model estimate of carbon taken up by plants over the 8-day period shown; an indicator of growth, not harvest or production.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds and overpass timing leave gaps)
- Source
- VIIRS NOAA-20 375 m (FIRMS) (NASA LANCE FIRMS)
- Provider
- NASA LANCE FIRMS
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds and overpass timing leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 500 m grid
- Uncertainty
- Satellite hot-spot detections for the day shown, including gas flares and industrial heat; not a confirmed fire, an incident report or a warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Habitat condition, framed on the Andes.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERT · U.S. Geological SurveySources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Optional layers (7 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
- Gross primary production, 8-day total: MODIS Aqua GPP (MYD17), NASA LP DAAC · 30 Sep 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
04Data
What the method consumes.
Datasets and records used by ecology and biodiversity science on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| IUCN Red List assessments | Species extinction risk | ESTIMATED |
| World Database on Protected Areas | Coverage and design | Published statistics |
| GBIF species occurrence records | Species distributions | OBSERVED |
| IPBES assessments | Drivers and trends | REPORTED |
05Monitor
Field sampling.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Field sampling
Climate and nature governance · Ecology and biodiversity science · Run R-9951
Three sites overdueGRF · Climate and Nature Governance
Sampling sites
red: result above guideline
Latest results
| S-59 | Basin | 3.3 | 9 | Below |
| S-37 | Entities | 4.3 | 8 | Near |
| S-19 | Implementation | 6.3 | 9 | Near |
| S-25 | Adaptation | 11.1 | 10 | Below |
Trend at selected site
06Validation
How results are checked.
Predictions are compared with independent survey data and long-term monitoring sites. Experimental manipulations and natural experiments test causal mechanisms.
| Check | How it is done |
|---|---|
| Baseline quality | Assessments state the age, method and coverage of ecological baselines |
| Reference conditions | Restoration and condition measures are compared with documented reference sites |
| Sampling bias | Occurrence data are checked for collection bias before mapping distributions |
Ecosystems show nonlinear responses and thresholds that are hard to anticipate from past data. Sampling is uneven across regions and taxa.
07Policy scenarios
Compare instruments: rules, incentives and information.
Three families of instruments side by side against the baseline, each with its own lag and adoption speed, under the coverage and compliance you set; effect sizes are teaching values to replace with evidence. Scenario: named assumptions about the future, not a forecast. The map on this page shows The Andes; the model itself is not tied to a place.
Controls
- Baseline trend of the outcome
- 2.0% a year
- Coverage of the instrument
- 70%
- Compliance
- 75%
- Effect size, against the teaching value
- 100%
- Years ahead
- 20 years
Readouts
- Largest reduction at the horizon
- Regulation
- Its reduction against the baseline
- 21%
Numbers, methods and sources
| Year | Baseline | Regulation | Economic incentive | Information and capacity |
|---|---|---|---|---|
| 0 | 100.0 | 99.5 | 98.8 | 99.1 |
| 1 | 102.0 | 101.2 | 100.1 | 99.8 |
| 2 | 104.0 | 102.5 | 101.1 | 99.9 |
| 3 | 106.1 | 103.5 | 101.6 | 100.0 |
| 4 | 108.2 | 103.7 | 101.8 | 100.7 |
| 5 | 110.4 | 103.2 | 101.7 | 102.1 |
| 6 | 112.6 | 102.0 | 101.6 | 103.9 |
| 7 | 114.9 | 100.4 | 101.6 | 105.9 |
| 8 | 117.2 | 99.2 | 102.1 | 108.0 |
| 9 | 119.5 | 98.6 | 102.9 | 110.1 |
| 10 | 121.9 | 98.9 | 104.2 | 112.3 |
| 11 | 124.3 | 99.7 | 105.7 | 114.5 |
| 12 | 126.8 | 101.1 | 107.4 | 116.8 |
| 13 | 129.4 | 102.7 | 109.4 | 119.2 |
| 14 | 131.9 | 104.5 | 111.4 | 121.6 |
| 15 | 134.6 | 106.5 | 113.5 | 124.0 |
| 16 | 137.3 | 108.5 | 115.7 | 126.5 |
| 17 | 140.0 | 110.7 | 118.0 | 129.0 |
| 18 | 142.8 | 112.9 | 120.4 | 131.6 |
| 19 | 145.7 | 115.1 | 122.8 | 134.2 |
| 20 | 148.6 | 117.4 | 125.2 | 136.9 |
Methods
- Tools of government Hood (1983), The Tools of Government, Macmillan
- Carrots, sticks and sermons Bemelmans-Videc, Rist and Vedung (1998), Transaction
- Diffusion of innovations Rogers (2003), Diffusion of Innovations, Free Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Borders Natural Earth
- Cities Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Climate and Nature Governance in Foundry
- Tested at Climate and Nature Governance in Universe
- Codified in Climate and Earth Systems in Standards
- Published in Climate and Nature Governance in Reports
- Taught in Faculty of Earth and Environmental Sciences in Academy
08Connections
Topics that rely on this method.
09Implementation
From mandate to evaluation, by pillar.
The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Andes; the model itself is not tied to a place.
- Mandate and problem framing Competent authority (outside the programme)
A competent authority frames the problem and the mandate under its own rules. Howlett, Ramesh and Perl (2009) - Evidence and system model Foundry
The system is modelled with its feedbacks, data and stated limits. OECD (2014), principle 2 - Options appraised with scenarios Foundry
Instruments are compared under scenarios, with uncertainty shown. Hood (1983) - Exercise with stakeholders Universe
The options are tested in an exercise with those who would implement and bear them. OECD (2014), principle 3 - Standard or guidance drafted Nexus Standards
What works is codified as a standard or guidance, open to comment. Nexus Standards process - Decision by the authority Competent authority (outside the programme)
The authority decides, outside the programme, with the evidence on record. Howlett, Ramesh and Perl (2009) - Capacity and training Risk Academy
Those who implement are trained on the decided instrument and its data. Sendai Framework (2015), priority 2 - Monitoring and public report Reports
Indicators are published with sources, limits and corrections. OECD (2014), principle 5 - Evaluation and revision Nexus Standards
Results return to the standard and the model: the cycle closes. Howlett, Ramesh and Perl (2009)
Methods
- Policy cycle Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press
- Governance of critical risks OECD (2014), Recommendation of the Council on the Governance of Critical Risks
- Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Climate and Nature Governance in Foundry
- Tested at Climate and Nature Governance in Universe
- Codified in Climate and Earth Systems in Standards
- Published in Climate and Nature Governance in Reports
- Taught in Faculty of Earth and Environmental Sciences in Academy
10Stewardship
Who maintains the method.
Biodiversity Nexus stewards ecology and biodiversity science for the Consortium and reviews how it is applied across platforms.
11Twin and cascade simulator
Exercise the cascade with the people who decide.
Assembled from the Nexus Standards area profile Biodiversity and nature risk standards: the hazards it names, the systems and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position. To model a place of your own choosing, open the full System Builder.
Hazards
- Deforestation
- Biodiversity loss (set off downstream)
- Soil erosion (set off downstream)
- Land-system change boundary transgression (set off downstream)
- Amazon rainforest dieback (set off downstream)
- Slope slide (set off downstream)
- Flash flood (set off downstream)
- Zoonotic spillover event (set off downstream)
- Wildfire (set off downstream)
- Emerging arbovirus outbreak (set off downstream)
- Malaria resurgence (set off downstream)
Systems and couplings
- Biodiversity and nature risk standards
- Climate risk standards Feedback
- Health risk standards Cascade
- Food and agriculture risk standards Dependency
- Environmental degradation hazard standards Shared hazard records
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-3bDataset and product metadata profile (STAC, DCAT, PROV-O)NS-5Figure, map and visualisation standard (with the UI/UX kit)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-N5Biodiversity and nature risk and resilienceNRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H27Hazard family: Biodiversity and species stress (NHS-1 eco.species)NRS-H26Hazard family: Land and wetland degradation (NHS-1 eco.land)NRS-H28Hazard family: Climate-state shifts (NHS-1 eco.climate-state)NRS-H64Hazard family: Ecosystem regime shifts (NHS-1 eco.regime-shift)
Observation
- GBIF occurrence API and downloads (listed for reference)
- World Database on Protected and Conserved Areas (listed for reference)
- Global Forest Watch tree cover loss (Hansen/UMD) and alerts (listed for reference)
- ESA WorldCover 10 m land cover (listed for reference)
- Copernicus Land Monitoring Service products (listed for reference)
- Red List Index
- Forest area as a proportion of total land area
- Proportion of important sites for terrestrial and freshwater biodiversity covered by protected areas
Example geography
- Pacific Island states: 150 hexagonal cells
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
12Connected
Where this page leads across the Consortium.
13Sector signature
Who a decision on ecology and biodiversity science for climate and nature governance reaches.
The sectors a policy on ecology and biodiversity science for climate and nature governance has to coordinate: a choice in one ministry lands in the others.
Select corners · hover lines6 / 15 relations
Signature
Biodiversity and its partners
Biodiversity gives pollination and soils to food (0.6), watershed regulation to water (0.5) and zoonotic spillover and medicines to health (0.4).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Food → Biodiversity · land conversion0.6
- Water → Food · irrigation0.8
- Water → Biodiversity · environmental flows0.6
- Food → Health · nutrition0.7
14Questions
Questions and answers.
What are the limits of ecology and biodiversity science in this field?
Ecosystems show nonlinear responses and thresholds that are hard to anticipate from past data. Sampling is uneven across regions and taxa.
How are results checked?
Predictions are compared with independent survey data and long-term monitoring sites. Experimental manipulations and natural experiments test causal mechanisms.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
15Instruments and commitments
Instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Mandates and agreements over time
The agreements that set mandates and commitments on ecology and biodiversity science for climate and nature governance, from adoption to their current horizon.
- 1992UNFCCC and Convention on Biological DiversityUnited Nations
- 2015Sendai Framework for Disaster Risk ReductionUNDRR
- 20152030 Agenda and the Sustainable Development GoalsUnited Nations
- 2015Paris AgreementUNFCCC
- 2022Kunming-Montreal Global Biodiversity FrameworkCBD
- 2023First global stocktake under the Paris AgreementUNFCCC
- 2030Horizon of the 2030 Agenda and the Sendai FrameworkUnited Nations
Sendai Framework for Disaster Risk Reduction · UNDRRParis Agreement · UNFCCC2030 Agenda and the Sustainable Development Goals · United NationsInternational Health Regulations · WHO
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