Species distribution modelling
Occurrence records and environmental layers are combined to estimate where a species can occur, with sampling bias corrected, absence data used where they exist and uncertainty mapped beside the prediction.
The Global Centre for Risk and Innovation (GCRI)
Ecology is the core science of this platform: it explains how species, populations and ecosystems respond to pressure, which changes matter for ecosystem function, and how losses become changes in the services people depend on. Field survey design and long-term monitoring give the evidence that every model is checked against.
GCRI · Established · service level R0
Ecology is the science of how organisms interact with each other and their environment. Here it explains how species, populations and ecosystems respond to pressure and how losses change the services people rely on. Field survey design and long-term monitoring, now including environmental DNA and acoustic surveys, give the evidence every model is checked against.
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 biodiversity and nature, climate and hazards and oceans and coasts, 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.
Occurrence records and environmental layers are combined to estimate where a species can occur, with sampling bias corrected, absence data used where they exist and uncertainty mapped beside the prediction.
Repeated counts are modelled to separate trend from observation error, and viability analysis estimates how extinction risk changes under alternative management or habitat loss.
Water, soil or air samples are sequenced and sound recorders deployed to detect species that are hard to see, with detection probability estimated from replicate samples.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Species distribution model | A model relating species records to environmental variables to predict where a species can occur. |
| Population viability analysis | Estimating a population's risk of decline or extinction over time from its size, trend and variability. |
| Environmental DNA | Genetic material shed by organisms into water, soil or air, sampled to detect species without seeing them. |
Mountain ranges, deserts, wetlands, glaciers and reefs, and how remote each division is from large cities, shown for the Nordic and Baltic region as an example geography for this subject.
Data from the source register feeds the methods; calibration and an independent test gate the estimate and its limits; the decision stays with the competent authority.
Fig. 01Nodes carry their type, metrics and state; connectors show what feeds what; the gates are the validation steps; the timeline is one application. Design of the method's use, not a record of a run.
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 |
|---|---|---|
| GBIF and OBIS occurrence records | Distribution modelling and gap analysis | OBSERVED |
| IUCN Red List assessments and range maps | Threat status and ranges | OFFICIAL |
| Standardised monitoring schemes | Population trends | OBSERVED |
| Environmental DNA sequence data | Species detection | OBSERVED |
| Long Term Ecological Research site data | Ecosystem processes and change | OBSERVED |
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 |
|---|---|
| Independent survey validation | Distribution models are tested against survey data not used in fitting, held out in spatially separate blocks |
| Detection and observer effects | Occupancy and abundance models account for imperfect detection and changing observer effort |
| Taxonomic verification | Identifications are checked against reference collections and a taxonomic backbone before analysis |
| Sampling bias assessment | Record density is compared with access and effort so that gaps are not read as absence |
Ecosystems show nonlinear responses and thresholds that are hard to anticipate from past data. Sampling is uneven across regions and taxa.
Biodiversity Nexus stewards ecology and biodiversity science for the Consortium and reviews how it is applied across platforms.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.