Stakeholder tools
Research applications
Decision-support tools that translate the research into interactive platforms for conservation managers, wildlife ecologists and game planners — each one runs in your browser.
IIASA postdoctoral research
Scandinavian Species Distribution Models
Grid-level density and habitat projections for moose (Alces alces), roe deer (Capreolus capreolus) and grey wolf (Canis lupus) across 374 Scandinavian grid cells under five IPCC Shared Socioeconomic Pathways — designed for foresters, game hunters and wildlife managers.
The tool couples hierarchical and stacked species distribution models — integrating climate, vegetation and land-cover predictors — with ODE-based wolf–ungulate trophic interaction layers (Guisan & Thuiller, 2005; Chapron et al., 2016). The map slider restricts projections to 2025–2060, while per-grid time series retain the full 1999–2060 record so stakeholders can read projections against baseline variability. The application runs entirely in the browser via stlite; no install is required.
- Species
- Moose · Roe deer · Wolf
- Scenarios
- SSP1-1.9 · 1-2.6 · 2-4.5 · 3-7.0 · 5-8.5
- Map window
- 2025–2060
- Time series
- 1999–2060
- Extent
- 374 grid cells
- Approach
- Hierarchical ML SDMs + ODE
- Runtime
- In-browser (stlite / Pyodide)
- Users
- Foresters · hunters · managers
- Repository
- Wolf-model
IIASA postdoctoral research
Forage Energy Meta-Database
A curated, interactive meta-database of plant metabolizable energy content, digestibility and Jacobs' D foraging preference indices for boreal ungulates — enabling quantitative habitat management and population energy-budget parameterisation.
The application synthesises Menke energy coefficients with Jacobs' D preference indices to compute preference-weighted metabolizable energy (ep) for each plant species. Use the Database tab to browse and filter records, the Calculator to compute energy budgets, and the Contribute tab to submit new data.
- Records
- 72 plant–species–season entries
- Species
- Moose · Roe deer · Red deer
- Seasons
- Spring · Summer · Autumn · Winter
- Variables
- ME · Jacobs' D · ep · confidence
- Tabs
- Database · Calculator · Contribute · About
- Use case
- Wildlife management · population modelling
- Repository
- Forage-energy-content-meta-database
Frontiers in Applied Mathematics & Statistics (2026)
AlderIPM-Sim — Alnus eco-epidemic IPM simulator
A browser-based decision-support tool for managing alder leaf beetle (Agelastica alni) outbreaks in European black alder (Alnus glutinosa) forests. It couples a within-season four-state ODE system with an annual discrete map, adds parasitoid biocontrol by Meigenia mutabilis and generalist predation by passerine birds, and lets managers predict regime shifts, detect early-warning signals, fit field data and compare integrated pest-management strategies.
The within-season module integrates a four-state ODE (susceptible larvae S, parasitised larvae I, adult parasitoids F, cumulative defoliation D) with fourth-order Runge–Kutta over the ~50-day larval vulnerability window; a Holling type II functional response governs parasitism. An annual discrete map then handles between-year beetle reproduction (Beverton–Holt), parasitoid overwinter survival, and canopy feedback (K = K0·exp(−φD)). Companion Python (pip install "git+...#subdirectory=alder-ipm-sim-py") and R (remotes::install_github) packages share the same model, parameter names and outputs, so any browser session reproduces verbatim in code.
- System
- A. glutinosa · A. alni · M. mutabilis · passerines
- Model
- Within-season ODE + annual Beverton–Holt map
- States
- S · I · F · D (RK4, ~50-day window)
- Features
- Simulation · equilibrium · bifurcation · fitting · early warnings · control
- Analyses
- LHS-PRCC · basin stability · resistance & resilience
- Early warnings
- Variance · autocorrelation · spectral reddening · Kendall τ
- Runtime
- In-browser (Plotly.js + Leaflet)
- Packages
- Python 3 + R, same model and outputs
- Repository
- AlderIPM-Sim
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Cite: Ghosh, S., & Singh, S. (2026). Adaptive stability of the Black alder ecoepidemic system: integrated intervention alone prevents regime shift under phenological variability. Frontiers in Applied Mathematics and Statistics, 12, 1831903. https://doi.org/10.3389/fams.2026.1831903