Predicting the probability of avian reproductive success and its components at a nesting site
Ghosh, S., Banerjee, A., Mukhopadhyay, S., Bhattacharya, S., & Ray, S. (2022). Ecological Informatics, 72, 101841.
doi:10.1016/j.ecoinf.2022.101841Research output
Publications, by project
Computational methodologies validated and published in peer-reviewed ecological journals, following the TRACE framework for transparency and reproducibility.
Models are developed following the TRACE framework and validated against independent datasets. First-author papers provide reproducible code via GitHub. Twelve papers across seven projects; first-author entries are marked in red.
The Merops philippinus Project
Prey groups
- Odonata
- Hymenoptera
- Coleoptera
- Lepidoptera
- Diptera
Data sources
- Field survey
- Climate (IMD)
- Soil (NBSS)
- Remote sensing
Primary data types
- Nest counts
- Breeding success
- Insect traps
- Aquatic sampling
Variation in prey community determines nesting rates of Merops philippinus
Ghosh, S. (2022). NDC E-BIOS, 2, 63–70.
Is the primary helper always a key group for the dynamics of cooperative birds?
Ghosh, S., Al Basir, F., Chowdhury, G., Bhattacharya, S., & Ray, S. (2021). Ecological Modelling, 459, 109710.
doi:10.1016/j.ecolmodel.2021.109710Helminth molecular niche in the mammal body
Helminth species
Hymenolepis diminuta (tapeworm)
Bacterial strains
Lactobacillus taiwanensis S29
Lactiplantibacillus plantarum S27
Efficacy of Lactobacillus taiwanensis S29 and Lactiplantibacillus plantarum S27 against tapeworm infection in Swiss Albino rats
Mandal, S., Mondal, C., Ghosh, S., Saha, S., Ray, M. S., & Lyndem, L. M. (2024). Experimental Parasitology, 259, 108715.
doi:10.1016/j.exppara.2024.108715Hymenolepis diminuta reduce lactic acid bacterial load and induce dysbiosis in the early infection of the probiotic colonization of Swiss Albino rat
Mandal, S., Mondal, C., Mukherjee, T., Saha, S., Kundu, A., Ghosh, S., & Lyndem, L. M. (2022). Microorganisms, 10(12), 2328.
doi:10.3390/microorganisms10122328Growth model generalisation
Applied-mathematics project developing generalised growth-curve models, validated on biological systems.
Applied to
- Fish growth data
- Cancer cell proliferation assays
- Stem cell dynamics
- Moth cooperative behaviour
Moths exhibit strong memory among cooperative species of other taxonomic groups: An empirical study
Rana, S., Basu, A., Ghosh, S., & Bhattacharya, S. (2023). Ecological Modelling, 476, 110235.
doi:10.1016/j.ecolmodel.2022.110235A noble extended stochastic logistic model for cell proliferation with density-dependent parameters
Roy, T., Ghosh, S., Saha, B., & Bhattacharya, S. (2022). Scientific Reports, 12, 8998.
doi:10.1038/s41598-022-12719-yA new growth curve model portraying the stress response regulation of fish
Roy, T., Ghosh, S., & Bhattacharya, S. (2022). Ecological Modelling, 470, 109999.
doi:10.1016/j.ecolmodel.2022.109999On developing a mathematical model for self-inducing proliferation and its regulation
Roy, T., Ghosh, S., Kundu, S., & Bhattacharya, S. (2021). Bulletin of the Calcutta Mathematical Society, 113(4), 271–308.
Plankton community ecology of Bakreswar
Plankton groups
- Copepoda
- Cladocera
- Rotifera
- Protozoa
Traits considered
- Body size
- Feeding type
- Reproductive mode
- Seasonality
Zooplankton community of Bakreswar reservoir: Assessment and visualization of distribution pattern using self-organizing maps
Banerjee, A., Rakshit, N., Chakrabarty, M., Sinha, S., Ghosh, S., & Ray, S. (2022). Ecological Informatics, 72, 101837.
doi:10.1016/j.ecoinf.2022.101837Eco-epidemiology of canine distemper in the African wild dog
Investigation and control strategy for canine distemper disease on endangered wild dog species: A model-based approach
Reja, S., Ghosh, S., Ghosh, I., Paul, A., & Bhattacharya, S. (2022). SN Applied Sciences, 4, 176.
doi:10.1007/s42452-022-05053-5The Taiga Project — WP4: Wildlife module
Research tools and interactive applications developed under this project are on the Research Tools page.
Predicting future wolf density in Scandinavia under land-use and climate scenarios with an individual-based hybrid model
This study develops a hybrid grid-based demographic–spatial model to predict future grey wolf (Canis lupus) density across Scandinavia under projected land-use and climate scenarios. Following near-extinction in the 1960s, wolves have naturally recolonised the Scandinavian boreal forest, but understanding how many packs can coexist in human-dominated landscapes remains critical for balancing ecological benefits with social acceptance. The model integrates four coupled modules operating across spatial scales on a 50 × 50 km grid: (1) a Wolf Habitat Module that estimates prey availability from deer harvest data, vegetation, and land-use/land-cover, and combines it with climatic variables to produce a habitat suitability index; (2) a Wolf Pack Module that uses habitat suitability and prey availability to estimate recruitment via litter size and pup survival, yielding pack size and wolf density per grid cell; (3) a Wolf Dispersal Module that calculates yearling dispersal from each pack, routes dispersing wolves to suitable receiver grids based on habitat suitability, and estimates solitary wolf density available for new pack formation; and (4) a Wolf Territory Module that estimates territory size as a function of habitat suitability and calculates the number of packs each grid cell can support. The model is trained on long-term monitoring data from the SKANDULV programme (1999–2015) and validated against independent data (2016–2024). Predictions are generated under multiple SSP-RCP scenarios to test three hypotheses: that future forest-cover changes will increase average territory size, that warmer winters will shift territory concentration northward, and that overall wolf density will increase across Scandinavia.
Conceptual model structure
Optimal control theory on forest eco-epidemic system analyses
Focal system
- Alnus glutinosa
- Agelastica alni
- Meigenia mutabilis
- Passeriform birds
Methods
- Optimal control theory
- Eco-epidemic modelling
- Regime-shift analysis
- Hybrid seasonal–annual models
An interactive simulator of this system, AlderIPM-Sim, is on the Research Tools page.
Adaptive stability of the Black alder ecoepidemic system: integrated intervention alone prevents regime shift under phenological variability
Ghosh, S., & Singh, S. (2026). Frontiers in Applied Mathematics and Statistics, 12, 1831903.
doi:10.3389/fams.2026.1831903