Dr. Sinchan Ghosh
Applied Ecology · Wildlife Population Modelling

Research Tools

Field-ready models for the people who manage Scandinavian wildlife.

Interactive, evidence-based tools translating peer-reviewed population models into maps and scenarios that foresters, game hunters, and wildlife managers can read, query, and act on — no coding, no setup.

Open a tool How to read the outputs

Available tools

Each tool runs entirely in your browser. Data updates on release; the model version and last-updated date are shown on every tool page.

Live Scandinavia Wolf · Roe deer · Moose 1999–2060

Scandinavian Species Distribution Models

Explore grid-level density and habitat projections for wolves and their prey under historical conditions (1999–2015) and five IPCC SSP climate scenarios (2016–2060). Click any grid cell to see a full time series and scenario spread.

For foresters

Project ungulate browsing pressure on regeneration stands under different climate futures, by county and grid.

For game hunters

Compare roe deer and moose density trends in your management area; anticipate wolf territory presence decade by decade.

For wildlife managers

Assess pack size, territory number, and prey availability jointly — the variables that drive quota and depredation policy.

Open the tool → Methods & assumptions

Model version: v2.0 (updated predictions) · Coverage: Sweden & Norway grid (~50 km) · Scenarios: Historical, SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5

How to read the outputs

Scenarios, in plain terms

The Shared Socioeconomic Pathways (SSPs) describe plausible futures for emissions and land use, not forecasts. SSP1-2.6 reflects strong mitigation; SSP5-8.5 reflects a fossil-fuel-intensive path. Compare scenarios rather than trusting any single line (Riahi et al., 2017; IPCC AR6 WGI, 2021).

Density vs. habitat suitability

Density (D_roe, D_moose, Wolf Density) reflects expected animals per unit area. Habitat suitability (H) is a 0–1 index of environmental fit under climate and land-cover covariates, independent of current population. Use both together for management decisions.

Uncertainty

Projections carry structural, parameter, and scenario uncertainty. The scenario spread displayed in the time-series charts is the minimum uncertainty band; actual realisations may fall outside it. Treat grid-level numbers as directional, not precise counts (Araújo & Guisan, 2006).

Privacy & performance

Nothing you click leaves your browser. The tool loads the model outputs once, then runs locally using Pyodide/stlite. First load takes ~20–40 seconds on a typical connection; subsequent interactions are instant.

Methods, briefly

Species distribution and density surfaces are fitted from national monitoring data (Scandinavian wolf monitoring, moose and roe deer harvest statistics, and habitat covariates) and projected forward using ISIMIP-bias-corrected climate forcings for the five SSP pathways. The wolf sub-model couples pack size, territory number, and territory size to solitary-wolf dispersal, consistent with established Scandinavian wolf demography (Chapron et al., 2016; Wabakken et al., 2001). Prey densities are linked to climate-driven habitat suitability following Guisan & Thuiller (2005). Full methods and code are in the repository README and the forthcoming manuscript.

How to cite

If you use outputs from these tools in a report, plan, or publication, please cite:

Ghosh, S. (2026). Scandinavian Species Distribution Models v2.0 [Interactive research tool].
Wolf-model repository, IIASA postdoctoral research.
Retrieved from https://gsinchanpostdoc.github.io/Wolf-model/tools/scandinavian-sdm/