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Stakeholder Tools

Research Applications

Decision-support tools translating postdoctoral research into accessible, interactive platforms for conservation managers, wildlife ecologists, and game planners.

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.

3 species 5 IPCC SSPs Map 2025–2060 History 1999–2060 374 grid cells Machine-learning SDMs Predator–prey ODEs

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-browser via stlite; no install is required.

Open Application
SpeciesMoose · Roe Deer · Wolf
Climate scenariosSSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5
Map window2025–2060
Time-series window1999–2060 (historical + projection)
Spatial extent374 Scandinavian grid cells
Modelling approachHierarchical ML SDMs + ODE
RuntimeIn-browser (stlite / Pyodide)
Target usersForesters · Game hunters · Wildlife managers
GitHub repositoryWolf-model
Moose
Alces alcesWikimedia Commons, Public Domain
Roe deer
Capreolus capreolusWikimedia Commons, CC BY-SA
Grey wolf
Canis lupusWikimedia Commons, CC BY-SA
Scandinavian Species Distribution Models — v2.0
Moose · Roe Deer · Grey Wolf · Five IPCC SSPs · Map 2025–2060 · Time series 1999–2060
Live · In-browser
Open in full screen for the best experience — first load takes 20–40 seconds
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.

72 records 3 species 4 seasons ME (MJ/kg DM) Jacobs' D index Open contribution

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.

View Source on GitHub
Records72 plant–species–season entries
SpeciesMoose · Roe Deer · Red Deer
SeasonsSpring · Summer · Autumn · Winter
Key variablesME, Jacobs D, e_p, Confidence
Application tabsDatabase · Calculator · Contribute · About
Use caseWildlife management · Population modelling
GitHub repositoryForage-energy-content-meta-database
Moose
Alces alcesWikimedia Commons, Public Domain
Roe deer
Capreolus capreolusWikimedia Commons, CC BY-SA
Red deer
Cervus elaphusLuc Viatour, CC BY-SA 3.0
Forage Energy Database
Animal Forage Metabolizable Energy & Preference Index · 72 records · 3 species
Interactive · Open Access
Open in full screen for the best experience
Frontiers in Applied Mathematics & Statistics (2026)

AlderIPM-Sim — Alnus Ecoepidemic 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 4-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.

Within-season ODE + annual map 4 states (S · I · F · D) Meigenia biocontrol Regime-shift early warnings LHS-PRCC sensitivity Basin stability Python + R packages

The within-season module integrates a 4-state ODE (susceptible larvae S, parasitised larvae I, adult parasitoids F, cumulative defoliation D) with 4th-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.

Open Application Source code & packages
Target systemAlnus glutinosa · Agelastica alni · Meigenia mutabilis · passerines
ModelHybrid within-season ODE + annual Beverton-Holt map
State variablesS · I · F · D (RK4, ~50-day larval window)
Core featuresSimulation · Equilibrium · Bifurcation (1-D/2-D) · Fitting · Early warnings · Control
AnalysesLHS-PRCC sensitivity · Basin stability · Resistance & resilience
Early warningsVariance · Autocorrelation · Spectral reddening · Kendall τ
RuntimeIn-browser (Plotly.js + Leaflet); no install
Companion packagesPython 3 + R (same model, same outputs)
GitHub repositoryAlderIPM-Sim
Alnus glutinosa
Alnus glutinosaNikanos, Wikimedia Commons, CC BY-SA 2.5
Agelastica alni
Agelastica alniAndré Karwath, Wikimedia Commons, CC BY-SA 2.5
Tachinid fly
Meigenia mutabilis (Tachinidae)Muhammad Mahdi Karim, Wikimedia Commons, CC BY-SA 3.0
AlderIPM-Sim — Alnus Ecoepidemic IPM Simulator
Within-season ODE + annual map · Regime-shift early warnings · IPM control comparison · Python & R packages
Live · In-browser
Open in full screen for the best experience

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. doi:10.3389/fams.2026.1831903