Acoustic Ecology

Research in acoustic ecology at the School of Informatics examines biodiversity patterns and ecosystem health through the analysis of environmental soundscapes. Using passive acoustic monitoring, vocalisations of indicator species—particularly birds—are recorded across diverse habitats and analysed using ecoacoustic indices and computational methods. Studies across ecosystems in Kerala demonstrate how acoustic metrics can reveal variations in biodiversity, habitat quality, and ecological disturbances such as anthropogenic noise and extreme events. This work supports scalable, non-invasive approaches for biodiversity monitoring and conservation planning.

Key Papers

1. Rajan, S. C., M, V., Mitra, A., N P, S., K, A., Pillai, M. S., & R, J. (2024). Threshold of anthropogenic sound levels within protected landscapes in Kerala, India, for avian habitat quality and conservation. Scientific Reports, 14(1).
2. C Rajan, S., Dominic, L., M, V., K, A., NP, S., & R, J. (2022a). Surrogacy of post natural disaster acoustic indices for biodiversity assessment. Environmental Challenges, 6, 100420.
3. Rajan, S. C., Athira, K., Jaishanker, R., Sooraj, N. P., & Sarojkumar, V. (2018). Rapid assessment of biodiversity using acoustic indices. Biodiversity and Conservation, 28(8–9), 2371–2383.

Floral Radiometry

Research in floral radiometry at the School of Informatics focuses on the quantitative characterization of floral colour using spectral reflectance measurements (300–700 nm). The work analyses floral colour from both human and pollinator visual perspectives to better understand plant–pollinator communication. This research has led to the proposal of the chromatic exclusivity hypothesis, explaining how floral colours occupy distinct regions in colour space to enhance pollinator discrimination. By integrating plant science, colour science, and ecological informatics, the work advances the study of floral signal evolution and pollination ecology, with links to hyperspectral remote sensing. The team also works on coral and foliar radiometry to characterize the spectra of marine and terrestrial biological systems.

Key Papers

1. Athira, Kakkara, Jaishanker, R. N., C. Rajan, S., & Dadhwal, V. K. (2023). Remote Sensing of Flowers. Ecological Informatics, 78, 102369.
2. Sooraj, N. P., Jaishanker, R., Athira, K., Sajeev, C. R., Lijimol, D., Saroj, K. V., Ammini, J., Pillai, M. S., & Dadhwal, V. K. (2019). Comparative study on the floral spectral reflectance of invasive and non-invasive plants. Ecological Informatics, 53, 100990.
3. Athira, K., Sooraj, N. P., Jaishanker, R., Saroj Kumar, V., Sajeev, C. R., Pillai, M. S., Govind, A., Ramarao, N., & Dadhwal, V. K. (2019). Chromatic exclusivity hypothesis and the physical basis of floral color. Ecological Informatics, 49, 40–44.
4. Athira, K., Sooraj, N. P., Jaishanker, R., Saroj Kumar, V., Sajeev, C. R., Pillai, M. S., Govind, A., & Dadhwal, V. K. (2019). Quantitative representation of floral colors. Color Research & Application, 44(3), 426–432.

Coupled Human – Environment System

Research on Coupled Human–Environment Systems (CHES) at the School of Informatics examines the interactions between human social systems and natural environmental systems as interconnected components of a single dynamic system. This research focuses on understanding the reciprocal and bidirectional relationships between human activities and ecological processes, and how these interactions generate feedback mechanisms that influence both environmental conditions and human decision-making. By integrating ecological data, computational approaches, and environmental informatics, the work seeks to better understand the complex dynamics linking society and the environment. Such insights are important for addressing environmental challenges and supporting pathways toward sustainable development and environmental management.

Morphometry

Research on morphometry at the School of Informatics focuses on the quantitative analysis of biological forms and structural traits, particularly leaf morphology. The work uses digital image analysis, morphometric methods, and computational tools to characterize variation in leaf size, forms, and structural features across species and environments. It also includes leaf venation network analysis to understand vascular organization and function. These morphological traits help link leaf structure with plant physiological performance and climate adaptation, contributing to functional trait analysis, biodiversity research, and ecological monitoring.

Key Papers

1. Muraleedharan, V., Rajan, S. C., N P, S., V, S. K., & R, J. (2026). A comprehensive tree leaf image dataset for Morphometric Studies. Environmental Research Communications, 8(1), 014501.
2. Muraleedharan, V., Rajan, S. C., & R, J. (2024). Geometric entropy of plant leaves: A measure of morphological complexity. PLOS ONE, 19(1). https://doi.org/10.1371/journal.pone.0293596
3. Muraleedharan, V., Rajan, S. C., & R, J. (2023). Determining the limits of traditional box-counting fractal analysis in leaf complexity studies. Flora, 304, 152300.
4. Vishnu, M., & Jaishanker, R. (2023). Fractal-thermodynamic system analogy and complexity of plant leaves. Environmental Research Communications, 5(5), 055013.

Biodiversity and conservation

Research at the School of Informatics in this area focuses on understanding biodiversity patterns, ecosystem processes, and vegetation dynamics using machine learning and remote sensing approaches. The work integrates satellite data, field observations, and computational methods to analyse spatial and temporal changes in vegetation and habitats across landscapes. Machine learning models are applied to support species distribution analysis, habitat characterization, and ecological pattern detection. These approaches contribute to monitoring ecosystem changes, assessing habitat quality, and supporting biodiversity conservation and landscape-level environmental management.

Key Papers

1. Jaishanker, R., Vishnu, M., Sajeev, C. R., Sooraj, N. P., Athira, K., Sarojkumar, V., Lijimol, D., Subin, J. M., Anjaly, U., & Dadhwal, V. K. (2021). Biodiversity Clock and conservation triangle: Integrative platform for biodiversity monitoring, evaluation, and preemptive conservation intervention. Environmental and Sustainability Indicators, 11, 100137.
2. Sabu, M. M., Pasha, S. V., Reddy, C. S., Singh, R., & Jaishanker, R. (2021). The effectiveness of tiger conservation landscapes in decreasing deforestation in South Asia: A Remote Sensing-based study. Spatial Information Research, 30(1), 63–75.
3. Reddy, C. S., Unnikrishnan, A., Asra, M., Maya Manikandan, T., & Jaishanker, R. (2019). Spatial conservation prioritisation of threatened forest ecosystems in Myanmar. Journal of the Indian Society of Remote Sensing, 47(10), 1737–1749.
4. Athira, K., Reddy, C. S., Saranya, K. R., Joseph, S., & Jaishanker, R. (2017). Habitat monitoring and conservation prioritisation of protected areas in Western Ghats, Kerala, India. Environmental Monitoring and Assessment, 189(6).

Human Wildlife Conflict

Research on human–wildlife conflict at the School of Informatics examines interactions between human communities and wildlife that lead to ecological and socio-economic challenges. The work integrates traditional ecological knowledge, sensor-based monitoring systems, and spatial ecological data, supported by artificial intelligence and machine learning, to analyse patterns of wildlife movement and conflict across landscapes. This integrative approach enables improved monitoring, early detection of wildlife presence, and the development of data-driven strategies for conflict mitigation, supporting human–wildlife coexistence and biodiversity conservation.

Members

• Jaishanker R (Principal Investigator)
• Sooraj N P (Assistant Professor and Chair)
• Athira K (Assistant Professor)
• Vishnu M (Technical Assistant)
• Arjun C P (PhD Student)
• Anjaly Unnikrishnan (PhD Student)
• Aleesha Fathima S L (PhD Student)
• Anoop A S (PhD Student)
• Arun S (PhD Student)
• Minu Merin Sabu (PhD Student)
• Sadhvi Kwatra (PhD Student)
• Chaitali S More (PhD Student)

e-mail: ecologicalinformatics@duk.ac.in