Academic Publications

@article{viswanathan_state_2025,
	title = {State of {India}'s {Birds} 2023: {A} framework to leverage semi-structured citizen science for bird conservation},
	volume = {16},
	copyright = {All rights reserved},
	issn = {2150-8925},
	shorttitle = {State of {India}'s {Birds} 2023},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ecs2.70290},
	doi = {10.1002/ecs2.70290},
	abstract = {Birds and their habitats are threatened with extinction around the world. Regional assessments of the “State of Birds” are a vital means to prioritize data-driven conservation action by informing national and global policy. Such evaluations have traditionally relied on data derived from extensive, long-term, standardized surveys that require significant resources, limiting their feasibility to a few regions in the world. In the absence of such “structured” long-term datasets, “semi-structured” datasets have recently emerged as a promising alternative in other regions around the world. Semi-structured data are generated and uploaded by birdwatchers to citizen science platforms such as eBird. Such data contain inherent biases because birdwatchers are not required to adhere to a fixed protocol. An evaluation of the status of birds from semi-structured data is therefore a difficult task that requires careful curation of data and the use of robust statistical methods to reduce errors and biases. In this article, we present a methodology that was developed for this purpose and was applied to produce the comprehensive State of India's Birds (SoIB) 2023 report. SoIB 2023 assessed the status of 942 bird species in India by evaluating each species based on three metrics: (1) long-term change, (2) current annual trend, and (3) distribution range size. We found evidence that 204 species have declined in the long term and that 142 species are in current decline. Birds that have vertebrate or invertebrate diets have declined most rapidly in the long term, whereas those that feed on fruits and nectar have been stable. Birds that require grasslands have declined more rapidly than those that require other habitats, indicating that grasslands are an important ecosystem to prioritize conservation in India. We classify 178 species as high conservation priority and present and discuss important insights about India's birds that can guide research and conservation action in the region. We hope that the detailed methodology described here can act as a blueprint to produce State of Birds assessments from semi-structured citizen science datasets and springboard conservation action in many other regions where structured data are lacking but strong communities of birdwatchers exist.},
	language = {en},
	number = {7},
	urldate = {2025-07-18},
	journal = {Ecosphere},
	author = {Viswanathan, Ashwin and Thrikkadeeri, Karthik and Koulgi, Pradeep and Praveen, J. and Deomurari, Arpit and Jha, Ashish and Warudkar, Ashwin and Suryawanshi, Kulbhushansingh and Madhusudan, M. D. and Kaushik, Monica and Goyal, Naman and Jayapal, Rajah and Quader, Suhel and Dutta, Sutirtha and Menon, Tarun and Ramachandran, Vivek},
	month = jul,
	year = {2025},
	pages = {e70290},
}

Birds and their habitats are threatened with extinction around the world. Regional assessments of the “State of Birds” are a vital means to prioritize data-driven conservation action by informing national and global policy. Such evaluations have traditionally relied on data derived from extensive, long-term, standardized surveys that require significant resources, limiting their feasibility to a few regions in the world. In the absence of such “structured” long-term datasets, “semi-structured” datasets have recently emerged as a promising alternative in other regions around the world. Semi-structured data are generated and uploaded by birdwatchers to citizen science platforms such as eBird. Such data contain inherent biases because birdwatchers are not required to adhere to a fixed protocol. An evaluation of the status of birds from semi-structured data is therefore a difficult task that requires careful curation of data and the use of robust statistical methods to reduce errors and biases. In this article, we present a methodology that was developed for this purpose and was applied to produce the comprehensive State of India's Birds (SoIB) 2023 report. SoIB 2023 assessed the status of 942 bird species in India by evaluating each species based on three metrics: (1) long-term change, (2) current annual trend, and (3) distribution range size. We found evidence that 204 species have declined in the long term and that 142 species are in current decline. Birds that have vertebrate or invertebrate diets have declined most rapidly in the long term, whereas those that feed on fruits and nectar have been stable. Birds that require grasslands have declined more rapidly than those that require other habitats, indicating that grasslands are an important ecosystem to prioritize conservation in India. We classify 178 species as high conservation priority and present and discuss important insights about India's birds that can guide research and conservation action in the region. We hope that the detailed methodology described here can act as a blueprint to produce State of Birds assessments from semi-structured citizen science datasets and springboard conservation action in many other regions where structured data are lacking but strong communities of birdwatchers exist.

@article{thrikkadeeri_birdwatchers_2024,
	title = {Birdwatchers piecing together \textit{{Locustella}} jigsaw: {Insights} into the wintering distribution of the cryptic {West} {Himalayan} {Bush} {Warbler} \textit{{Locustella} kashmirensis}},
	volume = {20},
	shorttitle = {Birdwatchers piecing together {Locustella} jigsaw},
	abstract = {New records of West Himalayan Bush Warbler (Himalayan Grasshopper Warbler) Locustella kashmirensis are collated to present an up to date picture of the species' breeding, migratory and wintering ranges. Well-documented breeding records of WHBW have all been from alpine habitats with short scrub, grassy or herbaceous vegetation. Data presented in this article suggest that 38 out of the 51 breeding season records (13 June–27 September) are from open habitats above 3,000 m asl, such as alpine meadows in the western and central Himalaya. Notably, 18 of these 38 observations are within a 7 km aerial distance from the closest glacier, and three are within a kilometre . The absence of more observations at similar altitudes is possibly because meadows and other open habitats close to glaciers are difficult for birders to access.The observations reported here, particularly the southern-most records in both Uttar Pradesh and West Bengal, now confirm that WHBW can show long-distance migratory behaviour, much like the closely related SBWA which typically winters further east of Uttar Pradesh. The winter (i.e., non-breeding) distribution spans much of northern India and the Ganga and Brahmaputra plains. It winters as far west as Pong Lake, Himachal Pradesh and as far south-west as Gurugram, Haryana, and south of River Ganga in Aligarh, Uttar Pradesh; Prayagraj, Uttar Pradesh and as far south-east as West Bengal and Bangladesh; and as far east as eastern Assam.},
	number = {3},
	journal = {Indian BIRDS},
	author = {Thrikkadeeri, Karthik and Sheth, Chintan and Himanshu, C. and Sharma, Virag and Arora, Gunjan and Sarkar, Kaushik and Rodrigues, Maxim and Allport, Gary and Biswas, Sandeep and Das, Sandip and Mitra, Rajdeep and Shivkar, Adesh and Panwar, Rajesh and Kumar, Prashant and Chitragupta, Prakash and Pratim, Manash and Lawrence, Able and Islam, Rofikul and Nanda, Kavi and Borah, Jugal and Menezes, Mark and Saikia, Shyamal and Gala, Mittal and Devi, Subhadra and Baig, Anas and Gupta, Manas and Hegde, Arun and Banerjee, Chaiti and Sarkar, Swarup and Basak, Sayanta and Chowdhury, Samarendra and Bhattacharjee, Prasenjit and Bera, Anish and Akhter, Samim and Majumder, Santanab and Kundu, Niladri and Maity, Sayandeep and Dev, Rakesh Singha and Pal, Aritra and Das, Debasis and Shome, Sudipto and Aon, Soumya and Shome, Kallol and Majumder, Amitabha and Naskar, Anindya and Nilsen, Jan-Erik and Gogoi, Runap and Basumatary, Rustom and Singh, Anand and Abhinav, C. and Viswanathan, Ashwin},
	month = sep,
	year = {2024},
	pages = {70--79},
}

New records of West Himalayan Bush Warbler (Himalayan Grasshopper Warbler) Locustella kashmirensis are collated to present an up to date picture of the species' breeding, migratory and wintering ranges. Well-documented breeding records of WHBW have all been from alpine habitats with short scrub, grassy or herbaceous vegetation. Data presented in this article suggest that 38 out of the 51 breeding season records (13 June–27 September) are from open habitats above 3,000 m asl, such as alpine meadows in the western and central Himalaya. Notably, 18 of these 38 observations are within a 7 km aerial distance from the closest glacier, and three are within a kilometre . The absence of more observations at similar altitudes is possibly because meadows and other open habitats close to glaciers are difficult for birders to access.The observations reported here, particularly the southern-most records in both Uttar Pradesh and West Bengal, now confirm that WHBW can show long-distance migratory behaviour, much like the closely related SBWA which typically winters further east of Uttar Pradesh. The winter (i.e., non-breeding) distribution spans much of northern India and the Ganga and Brahmaputra plains. It winters as far west as Pong Lake, Himachal Pradesh and as far south-west as Gurugram, Haryana, and south of River Ganga in Aligarh, Uttar Pradesh; Prayagraj, Uttar Pradesh and as far south-east as West Bengal and Bangladesh; and as far east as eastern Assam.

@article{thrikkadeeri_despite_2024,
	title = {Despite short-lived changes, {COVID}-19 pandemic had minimal large-scale impact on citizen science participation in {India}},
	volume = {126},
	copyright = {All rights reserved},
	issn = {0010-5422},
	url = {https://doi.org/10.1093/ornithapp/duae024},
	doi = {10.1093/ornithapp/duae024},
	abstract = {Many parts of the world lack the large and coordinated volunteer networks required for systematic monitoring of bird populations. In these regions, citizen science programs offer an alternative with their semi-structured data, but the utility of these data is contingent on how, where, and how comparably birdwatchers watch birds, year on year. Trends inferred from the data can be confounded during years when birdwatchers may behave differently, such as during the COVID-19 pandemic. We wanted to ascertain how the data uploaded from India to one such citizen science platform, eBird, were impacted by this deadly global pandemic. To understand whether eBird data from the pandemic years in India are comparable to data from adjacent years, we explored several characteristics of the data, such as how often people watched birds in groups or at public locations, at multiple spatial and temporal scales. We found that the volume of data generated increased during the pandemic years 2020–2021 compared to 2019. Data characteristics changed largely only during the peak pandemic months (April–May 2020 and April–May 2021) associated with high fatality rates and strict lockdowns. These changes in data characteristics (e.g., greater site fidelity and less group birding) were possibly due to the decreased human mobility and social interaction in these periods. The data from the remainder of these restrictive years remained similar to those of the adjacent years, thereby reducing the impact of the aberrant peak months on any annual inference. Our findings show that birdwatchers in India as contributors to citizen science rapidly returned to their pre-pandemic behavior, and that the effects of the pandemic on birdwatching effort and birdwatcher behavior are scale- and context-dependent. In summary, eBird data from the pandemic years in India remain useful for abundance trend estimation and similar large-scale applications, but will benefit from preliminary data quality checks when utilized at a fine scale.},
	number = {4},
	urldate = {2024-06-22},
	journal = {Ornithological Applications},
	author = {Thrikkadeeri, Karthik and Viswanathan, Ashwin},
	month = jun,
	year = {2024},
	pages = {duae024},
}

Many parts of the world lack the large and coordinated volunteer networks required for systematic monitoring of bird populations. In these regions, citizen science programs offer an alternative with their semi-structured data, but the utility of these data is contingent on how, where, and how comparably birdwatchers watch birds, year on year. Trends inferred from the data can be confounded during years when birdwatchers may behave differently, such as during the COVID-19 pandemic. We wanted to ascertain how the data uploaded from India to one such citizen science platform, eBird, were impacted by this deadly global pandemic. To understand whether eBird data from the pandemic years in India are comparable to data from adjacent years, we explored several characteristics of the data, such as how often people watched birds in groups or at public locations, at multiple spatial and temporal scales. We found that the volume of data generated increased during the pandemic years 2020–2021 compared to 2019. Data characteristics changed largely only during the peak pandemic months (April–May 2020 and April–May 2021) associated with high fatality rates and strict lockdowns. These changes in data characteristics (e.g., greater site fidelity and less group birding) were possibly due to the decreased human mobility and social interaction in these periods. The data from the remainder of these restrictive years remained similar to those of the adjacent years, thereby reducing the impact of the aberrant peak months on any annual inference. Our findings show that birdwatchers in India as contributors to citizen science rapidly returned to their pre-pandemic behavior, and that the effects of the pandemic on birdwatching effort and birdwatcher behavior are scale- and context-dependent. In summary, eBird data from the pandemic years in India remain useful for abundance trend estimation and similar large-scale applications, but will benefit from preliminary data quality checks when utilized at a fine scale.

@article{schille_decomposing_2024,
	title = {Decomposing drivers in avian insectivory: {Large}-scale effects of climate, habitat and bird diversity},
	volume = {51},
	copyright = {© 2024 John Wiley \& Sons Ltd.},
	issn = {1365-2699},
	shorttitle = {Decomposing drivers in avian insectivory},
	url = {https://doi.org/10.1111/jbi.14808},
	doi = {10.1111/jbi.14808},
	abstract = {Aim Climate is a major driver of large-scale variability in biodiversity, as a likely result of more intense biotic interactions under warmer conditions. This idea fuelled decades of research on plant-herbivore interactions, but much less is known about higher-level trophic interactions. We addressed this research gap by characterizing both bird diversity and avian predation along a climatic gradient at the European scale. Location Europe. Taxon Insectivorous birds and pedunculate oaks. Methods We deployed plasticine caterpillars in 138 oak trees in 47 sites along a 19° latitudinal gradient in Europe to quantify bird insectivory through predation attempts. In addition, we used passive acoustic monitoring to (i) characterize the acoustic diversity of surrounding soundscapes; (ii) approximate bird abundance and activity through passive acoustic recordings; and (iii) infer both taxonomic and functional diversity of insectivorous birds from recordings. Results The functional diversity of insectivorous birds increased with warmer climates. Bird predation increased with forest cover and bird acoustic activity but decreased with mean annual temperature and functional richness of insectivorous birds. Contrary to our predictions, climatic clines in bird predation attempts were not directly mediated by changes in insectivorous bird diversity or acoustic activity, but climate and habitat still had independent effects on predation attempts. Main Conclusions Our study supports the hypothesis of an increase in the diversity of insectivorous birds towards warmer climates but refutes the idea that an increase in diversity would lead to more predation and advocates for better accounting for activity and abundance of insectivorous birds when studying the large-scale variation in insect-tree interactions.},
	language = {en},
	number = {6},
	urldate = {2024-02-20},
	journal = {Journal of Biogeography},
	author = {Schillé, Laura and Valdés-Correcher, Elena and Archaux, Frédéric and Bălăcenoiu, Flavius and Bjørn, Mona Chor and Bogdziewicz, Michal and Boivin, Thomas and Branco, Manuela and Damestoy, Thomas and de Groot, Maarten and Dobrosavljević, Jovan and Duduman, Mihai-Leonard and Dulaurent, Anne-Maïmiti and Green, Samantha and Grünwald, Jan and Eötvös, Csaba Béla and Faticov, Maria and Fernandez-Conradi, Pilar and Flury, Elisabeth and Funosas, David and Galmán, Andrea and Gossner, Martin M. and Gripenberg, Sofia and Grosu, Lucian and Hagge, Jonas and Hampe, Arndt and Harvey, Deborah and Houston, Rick and Isenmann, Rita and Kavčič, Andreja and Kozlov, Mikhail V. and Lanta, Vojtech and Le Tilly, Bénédicte and Lopez-Vaamonde, Carlos and Mallick, Soumen and Mäntylä, Elina and Mårell, Anders and Milanović, Slobodan and Molnár, Márton and Moreira, Xoaquín and Moser, Valentin and Mrazova, Anna and Musolin, Dmitrii L. and Perot, Thomas and Piotti, Andrea and Popova, Anna V. and Prinzing, Andreas and Pukinskaya, Ludmila and Sallé, Aurélien and Sam, Katerina and Sedikhin, Nickolay V. and Shabarova, Tanja and Tack, Ayco J. M. and Thomas, Rebecca and Thrikkadeeri, Karthik and Toma, Dragoș and Vaicaityte, Grete and van Halder, Inge and Varela, Zulema and Barbaro, Luc and Castagneyrol, Bastien},
	month = feb,
	year = {2024},
}

Aim Climate is a major driver of large-scale variability in biodiversity, as a likely result of more intense biotic interactions under warmer conditions. This idea fuelled decades of research on plant-herbivore interactions, but much less is known about higher-level trophic interactions. We addressed this research gap by characterizing both bird diversity and avian predation along a climatic gradient at the European scale. Location Europe. Taxon Insectivorous birds and pedunculate oaks. Methods We deployed plasticine caterpillars in 138 oak trees in 47 sites along a 19° latitudinal gradient in Europe to quantify bird insectivory through predation attempts. In addition, we used passive acoustic monitoring to (i) characterize the acoustic diversity of surrounding soundscapes; (ii) approximate bird abundance and activity through passive acoustic recordings; and (iii) infer both taxonomic and functional diversity of insectivorous birds from recordings. Results The functional diversity of insectivorous birds increased with warmer climates. Bird predation increased with forest cover and bird acoustic activity but decreased with mean annual temperature and functional richness of insectivorous birds. Contrary to our predictions, climatic clines in bird predation attempts were not directly mediated by changes in insectivorous bird diversity or acoustic activity, but climate and habitat still had independent effects on predation attempts. Main Conclusions Our study supports the hypothesis of an increase in the diversity of insectivorous birds towards warmer climates but refutes the idea that an increase in diversity would lead to more predation and advocates for better accounting for activity and abundance of insectivorous birds when studying the large-scale variation in insect-tree interactions.

@techreport{soib_state_2023,
	title = {State of {India}'s {Birds}, 2023: {Range}, trends, and conservation status},
	copyright = {All rights reserved},
	url = {https://zenodo.org/records/11124590},
	urldate = {2023-09-11},
	institution = {The SoIB Partnership},
	author = {{SoIB}},
	month = aug,
	year = {2023},
	doi = {10.5281/zenodo.11124590},
	pages = {119},
}

@article{praveen_kerala_2022,
	title = {Kerala {Bird} {Atlas} 2015–20: features, outcomes and implications of a citizen-science project},
	volume = {122},
	copyright = {All rights reserved},
	issn = {0011-3891},
	shorttitle = {Kerala {Bird} {Atlas} 2015–20},
	url = {https://www.currentscience.ac.in/Volumes/122/03/0298.pdf},
	doi = {10.18520/cs/v122/i3/298-309},
	abstract = {Citizen-science driven exercises (e.g. bird surveys) and online platforms (e.g. eBird) provide voluminous data on bird occurrence. However, the semi-structured nature of their data collection makes it difficult to compare bird distribution across space and time. Bird atlases are based on standardized surveys and describe the distribution of bird species over a predefined region and have fewer biases, and thus are better suited for use in research. The recently concluded Kerala Bird Atlas (henceforth KBA) is Asia’s largest bird atlas in terms of geographical extent, sampling effort and species coverage. The entire state of Kerala was systematically surveyed twice a year during 2015–20 and over 0.3 million records of 380 species from 25,000 checklists were aggregated. The dataset was filtered and various metrics were estimated. A total of 915 cells were laid out for systematic surveys, of which 888 were surveyed in either or both the seasons – dry season (January–March) and wet season (July–September); 27 cells could not be surveyed in either of the seasons due to logistical constraints. However, this variation in sampling effort had a minimal effect on survey completeness. The slope of the species accumulation curve suggested nearcomplete species sampling in over 70\% of the cells. After eliminating nocturnal and pelagic species, data from 361 species were analysed. Species count was higher in the dry season than in the wet season. Species richness (count) and evenness were higher in the northern and central districts than in the southern districts. High elevation regions of the southern Western Ghats were the largest contiguous areas lacking sufficient sampling. We found that most of the endemics were concentrated in the Western Ghats, but threatened species were as likely to occur along the coasts as in the Ghats. The KBA dataset is a valuable resource for testing various ecological hypotheses and suggesting science-backed conservation measures. KBA model could be replicated for similar atlases in other states or biogeographic regions of India.},
	language = {en},
	number = {3},
	urldate = {2023-08-15},
	journal = {Current Science},
	author = {Praveen, J. and Nameer, P. O. and Jha, Ashish and Aravind, Anish and Dilip, K. G. and Karuthedathu, Dipu and Tom, George and Mavelikara, Hari and Mannar, Harikumar and Palot, Jafer and Johnson, Jaichand and Jishnu, R. and Rodrigues, K. Maxim and Mujeeb, P. M. and Namassivayan, L. and Payyeri, Naveelal and Nesrudheen, P. P. and Narayanan, S. Prasanth and Prasanth, S. S. and Krishna, M. C. Prashantha and Praveen, E. S. and Velayudhan, Praveen and Reghuvaran, Premchand and Kidoor, Raju and Rathish, R. L. and Roshnath, R. and Sashikumar, C. and Meppayur, Satyan and Sivakumar, A. K. and Sreedevi, A. K. and Sreekumar, B. and Sreekumar, E. R. and Sumesh, P. B. and Venugopal, R. and Venugopal, Vinod and Vishnudas, C. K. and Kartha, Vishnupriyan and Puliyeri, Vivek and Quader, Suhel and Reddy, Abinand and Puthiyeri, Abdul Raheem and Riyas, K. Abdul and Abhijith, R. S. and Surendran, Abhijith and Sunil, Abhin M. and Chandran, Abhinand and Abhirami, C. and Jayakumar, Abhirami M. and Peter, Abhishek Sebastian and Muhammed, N. V. Afreed and Katakath, Afthab Faisal and Ajai, P. and Raju, Aju K. and Akhil, P. M. and Akhil, U. S. and Amal, U. S. and Menon, Anamika and Ansari, Anas Ibinu and Aneesh, K. S. and Aneesh, S. and Hari, C. Anjana and Anjitha, R. and Raj, P. N. Anoop and John, Anu and Varma, Anuradha and Anushreedha, S. S. and Aravind, C. K. and Ramachandran, Arjun and Arun, B. and George, Arun and Gopi, Arun P. and Varghese, Arun and Vinod, Arya and Shaji, Ashley and Raj, V. M. Ashok and Viswanathan, Ashwin and Mohammed, Aslam and Aswin, A. and Aswin, K. S. and Ali, A. Azhar and Balaji, P. B. and Paul, M. Bibin and Shree, J. Chaithra and Venkatraman, Chandrasekaran and Charutha, K. and Jose, Clareena T. and Jose, Clince P. and Singh, Dalip and Sanghamithra, Devika and Sikarwar, Digvijay Singh and Murukesh, Divin and Divin, V. and Arief, Fauzia and Mandal, Jaydev and Sarlin, P. J. and Nafar, A. Adil and Bachan, K. H. Amitha and Rejitha, V. and Dev, R. S. Vishnu and Rowther, B. Elias and Raja, Firosh and Iyer, Geetha and George, Ginu and Gireesan, T. U. and Mohan, P. K. Girish and Dsouza, Glen Preetesh and Govind, G. and Greeshma, P. and Prasad, P. M. Hari and Hariharan, T. V. and Harith, A. and Harith, C. and Hemanth, B. and Mohamed, Ijaas and David, J. Patrick and Jain, P. K. and Jameela, P. and Jayakrishnan, G. and Jishnu, K. and Jismi, M. O. and Johnson, Jithin and Soniya, C. Joel and Babu, Jose Rani and Roy, Joseph and Nelson, Jyothish and Krishnan, M. Jyothi and Bhandary, K. Pranav and Jamaludheen, K. M. and Ravi, Kavingal and Thrikkadeeri, Karthik and Nair, Kausthubh K. and Kiran, B. S. and Kumar, Kiran S. and Raj, D. Kishore and Panaganti, Kishore Kumar and Moorthy, M. Krishna and Murthy, R. Krishna and Krishnanunni, M. R. and Prabhakaran, Latha and Lathika, K. K. and Abraham, Libin and Narayanan, G. Hari and Panigrahi, Madhumita and Manav, S. and Karingamadathil, Manoj and Manoj, T. R. and Thomas, Manu and Manuel, P. P. and Varghese, Mebin George and Chandran, P. Megha and Sulaiman, M. Mohammad and Madathil, Mohammed Ashif and Hirash, V. K. Mohammed and Ramees, K. Mohammed and Thirunnavaya, M. Sadique and Niyas, A. P. Muhammed and Muhasin, C. T. and Kizhakkemadham, Mukundan and Azeez, Naseerudheen Abdul and Nikhil, P. V. and Niranjana, C. and Mundekad, Nisha and Mohan, Nithin and Pavithra, A. and Viswanathan, Poornima and Pramod, P. and Prakash, G. and Prasath, S. and Prakash, Prasoon and Preethi, N. and Rajeevan, Rahul and Rajaguru, M. and Rajarajan, V. and Sankaran, Raju and Ratheesh, K. and Crasta, Rayan Pradeep and Mohan, Remya and Renju, Anon and Koshy, Robin C. and Rai, Rohan and Tom, Roshin and Chandran, Sachin and Sachinkrishna, M. V. and Ali, M. V. Saeed Anvar and Siril, Sajitha and Bharadwaj, D. D. Samarth and George, Samuel and Morris, Sancia and Augustine, Sandeep and Das, Sandeep K. and Morris, Sandie and Sandra, P. R. and Sanuraj, T. K. and Sawant, Saurabh and Morris, Savio and Selvaganesh, K. and Shahil, K. and Shahina, N. N. and Valasy, Shahul and Siji, P. K. and Joseph, Siju and Sivashankar, R. and Karim, Siyad A. and Mohan, Sreehari K. and Pillai, Sreehari M. and Sowmiya, M. Sri and Srinila, K. T. and Subin, K. S. and Sujith, V. G. and Sukumaran, Suryamol and Syamili, M. S. and Menon, Tarun and Praveen, Tejas and Thilak, S. A. and Antony, Tony and Ullas, U. R and Sivaji, Vinod Ooralath and Narayanan, Vishnu and Sreejith, M. Vishnu and Chandran, A. Vivek and Sudhakaran, Vivek and Vridhi, R. and Humam, Wahiba Irshad and Uchummal, Yadukrishna J. and Yathumon, M. A.},
	month = feb,
	year = {2022},
	pages = {298},
}

Citizen-science driven exercises (e.g. bird surveys) and online platforms (e.g. eBird) provide voluminous data on bird occurrence. However, the semi-structured nature of their data collection makes it difficult to compare bird distribution across space and time. Bird atlases are based on standardized surveys and describe the distribution of bird species over a predefined region and have fewer biases, and thus are better suited for use in research. The recently concluded Kerala Bird Atlas (henceforth KBA) is Asia’s largest bird atlas in terms of geographical extent, sampling effort and species coverage. The entire state of Kerala was systematically surveyed twice a year during 2015–20 and over 0.3 million records of 380 species from 25,000 checklists were aggregated. The dataset was filtered and various metrics were estimated. A total of 915 cells were laid out for systematic surveys, of which 888 were surveyed in either or both the seasons – dry season (January–March) and wet season (July–September); 27 cells could not be surveyed in either of the seasons due to logistical constraints. However, this variation in sampling effort had a minimal effect on survey completeness. The slope of the species accumulation curve suggested nearcomplete species sampling in over 70% of the cells. After eliminating nocturnal and pelagic species, data from 361 species were analysed. Species count was higher in the dry season than in the wet season. Species richness (count) and evenness were higher in the northern and central districts than in the southern districts. High elevation regions of the southern Western Ghats were the largest contiguous areas lacking sufficient sampling. We found that most of the endemics were concentrated in the Western Ghats, but threatened species were as likely to occur along the coasts as in the Ghats. The KBA dataset is a valuable resource for testing various ecological hypotheses and suggesting science-backed conservation measures. KBA model could be replicated for similar atlases in other states or biogeographic regions of India.

@mastersthesis{thrikkadeeri_habitat_2021,
	address = {České Budějovice, Czech Republic},
	title = {Habitat selection in post-breeding temperate forest birds},
	copyright = {Bez omezení},
	url = {https://dspace.jcu.cz/handle/20.500.14390/44891},
	abstract = {Habitat selection of forest birds in Branišovský les, České Budějovice, Czech Republic was studied by observing habitat preferences in the non-breeding season and exploring possible shifts in preferences due to the changing seasons. Patterns of habitat selection were analysed at multiple levels: considering all bird species as well as comparing between two feeding guilds. Preferences were also studied by specifically monitoring predation rates by birds on artificial caterpillars and exploring changes with habitat and season.},
	language = {eng},
	urldate = {2024-06-22},
	school = {Jihočeská Univerzita},
	author = {Thrikkadeeri, Karthik},
	month = jun,
	year = {2021},
}

Habitat selection of forest birds in Branišovský les, České Budějovice, Czech Republic was studied by observing habitat preferences in the non-breeding season and exploring possible shifts in preferences due to the changing seasons. Patterns of habitat selection were analysed at multiple levels: considering all bird species as well as comparing between two feeding guilds. Preferences were also studied by specifically monitoring predation rates by birds on artificial caterpillars and exploring changes with habitat and season.

@book{antony_butterflies_2018,
	title = {Butterflies {Of} {Christ} {University} {Main} {Campus}- {A} {Pictorial} {Guide}},
	volume = {1},
	copyright = {All rights reserved},
	isbn = {978-93-82305-98-9},
	author = {Antony, P. U. and Singh, Rachit Pratap and Chanda, Ritobroto and Jayanth, Arpitha and Anand, Aljo and Thrikkadeeri, Karthik and Das, Priyanka and Menon, Arjun S. and Swathi, H. A. and Wilson, Sheenu and Asher, Minoti and Buddh, Shyamsunder},
	month = jan,
	year = {2018},
}