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Ganeshaiah, K. N.
- Ecological Amplitude and Regeneration of Medicinally Important Threatened Trees in the Central Western Ghats
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Indian Forester, Vol 130, No 11 (2004), Pagination: 1330-1338Abstract
The central part of the Western Ghats (i.e. Uttara Kannada District of Karnataka) was surveyed for tree species and regeneration using belt transects. Medicinally important trees were more in disturbed evergreen forests while undisturbed evergreen forests had proportionately more threatened species. Out of total 19 species of medicinally important threatened trees recorded , only Knema attenuata , Garcinia gummigutta and Artocarpus hirsutus showed a wider ecological amplitude with presence in disturbed and undisturbed evergreen forests. All other species were either confined to undisturbed forests or were rare in both types. Most of the threatened medicinal trees showed decrease in abundance in the disturbed evergreen forests. Species for which seeds or fruits are extracted like Myristica malabarica , Garcinia sp. , Hydnocarpus pentandra etc. there was a lack of adequate regeneration compared to density of trees and are at double disadvantage of habitat loss and regeneration loss.- Molecular Analysis of Semecarpus kathalekanensis (Anacardiaceae) - a Newly Described Species from the Myristica Swamps of Western Ghats, India
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Indian Forester, Vol 130, No 1 (2004), Pagination: 101-104Abstract
No abstract- Tree Species Composition in Koyna Wildlife Sanctuary, Northern Western Ghats of India
Abstract Views :241 |
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Affiliations
1 Research and Action in Natural Wealth Administration, 16, Swastishree Society, Ganesh Nagar, Pune 411 052, IN
2 Team Members, Western Ghats Bioresource Mapping Project of Department of Biotechnology, IN
1 Research and Action in Natural Wealth Administration, 16, Swastishree Society, Ganesh Nagar, Pune 411 052, IN
2 Team Members, Western Ghats Bioresource Mapping Project of Department of Biotechnology, IN
Source
Current Science, Vol 108, No 9 (2015), Pagination: 1688-1693Abstract
We established belt transects of 1000 m &3#215; 5 m in Koyna Wildlife Sanctuary at 12 different localities, to study tree species diversity. A total of 4296 individuals of girth at breast height (GBH) ≥15 cm were enumer-ated belonging to 108 species. A subtype of Memecylon-Syzygium-Olea was identified based on dominance from the area previously ascribed to Memecylon-Syzygium-Actinodaphne floristic series. Out of 41 fam-ilies, Melastomataceae, Myrtaceae and Moraceae were found to be dominant families according to the Family Importance Value. Shannon index (H') ranged from 1.5 to 3.03. Taxonomic diversity measured for each sampled locality using normalized simple Avalanche index showed variation between 0.104 and 1.00 and positive correlation with H'. Rarity score for identify-ing unique tree species composition correlated posi-tively with simple avalanche index. Evergreen forest of Navja and Ozarade together showed highest popula-tion of IUCN-listed tree species. This study shall pave the way for the subsequent ecological research in this area which has recently been declared as a World Natural Heritage Site by UNESCO.Keywords
Koyna Wildlife Sanctuary, Memecylon-syzygium-olea, Rarity Score, Simple Avalanche Index.- Feeling the ‘Pulses’ for the Second Green Revolution
Abstract Views :273 |
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1 School of Ecology and Conservation, UAS, GKVK, Bengaluru 560 065, IN
1 School of Ecology and Conservation, UAS, GKVK, Bengaluru 560 065, IN
Source
Current Science, Vol 111, No 6 (2016), Pagination: 959-960Abstract
During the last few decades there has been a frustrating call, rather a cry, for a repeat of the green revolution that our country experienced between 1960s and 1980s. It is widely acknowledged by experts that this cry emerges due to two related problems; first, the green revolution that accelerated the food production of the country lost its steam within a couple of decades and second, the tools, techniques and wherewithal used during this first phase of green revolution were no more sufficient to keep the steam on. Clearly, if we do not address these problems immediately and fail to re-accelerate the pace of green revolution, the increasing gap between the demand for, and production of food grains would begin to haunt our country again. In other words the country is looking towards another revolution - aptly termed as second green revolution. While efforts are on to prepare the ground for this second phase, or for an 'Ever Green Revolution', it would be wise to introspect the reasons for the deceleration of the first phase.- What Should Drive the Idea of Conservation:Emotions or Economics?
Abstract Views :237 |
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Authors
Affiliations
1 School of Ecology and Conservation, University of Agricultural Sciences, GKVK Campus, Bengaluru-560 065, IN
1 School of Ecology and Conservation, University of Agricultural Sciences, GKVK Campus, Bengaluru-560 065, IN
Source
Current Science, Vol 113, No 06 (2017), Pagination: 1011-1012Abstract
Towards the end of June 2015, along the borders of the Hwange National Park in Zimbabwe, a lion named Cecil was hit by an arrow shot by Dr Walter Palmer, a rich US dentist and a habitual wild-game hunter. Not satisfied merely by injuring the lion, the dentist tracked it incessantly for almost the next 40 h, and on 1 July 2015, he shot it down with his rifle.- B. G. L. Swamy (1918–1980):A One-Man Institution
Abstract Views :264 |
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Authors
Affiliations
1 DST Centre for Policy Research, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016, IN
2 School of Ecology and Conservation, University of Agricultural Sciences, GKVK, Bengaluru 560 065, IN
1 DST Centre for Policy Research, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016, IN
2 School of Ecology and Conservation, University of Agricultural Sciences, GKVK, Bengaluru 560 065, IN
Source
Current Science, Vol 115, No 11 (2018), Pagination: 2168-2171Abstract
B. G. L. Swamy was an internationally acknowledged botanist, researcher, teacher, thinker, art historian, painter, cartoonist, music aficionado and above all, a gifted Kannada writer. Hence it is no exaggeration to say that he was less an individual and more a one-man institution. In this, the year of his birth centenary, we offer tribute to this truly multi-faceted personality of the last century who straddled the worlds of arts, sci-ence and literature.References
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- Radhakrishna, B. P., B. G. L. Swamy: Jeevanachitra Mattu Sādhane (in Kan-nada), Geological Society of India, Ban-galore, 2008.
- Ganeshaiah, K. N., Bhanu Prabha, Sun-day supplement of Kannada Prabha, 11 February 2018.
- Swamy, B. G. L., Kāleju Ranga (in Kan-nada), Manohara Granthamāla, Dhara-war, 1975, pp. 1–2.
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- The Plant List considers Sarcandra irvingbaileyi Swamy as an unresolved name; http://www.theplantlist.org/tpl1.1/record/kew-2484652 (accessed on 15 Oc-tober 2018; https://indiabiodiversity.org/biodiv/species/show/250088). The India Biodiversity Portal considers this name as a synonym of Sarcandra chloranthoides Gardn. (accessed on 20 October 2018).
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- Identification of Indian Butterflies and Moths with Deep Convolutional Neural Networks x
Abstract Views :225 |
PDF Views:87
Authors
Affiliations
1 Independent Researcher, Bengaluru 560 024, IN
2 Department of Forestry and Environment Science, University of Agricultural Sciences, GKVK Campus, Bengaluru 500 065, IN
3 Department of Entomology, University of Agricultural Sciences, GKVK Campus, Bengaluru 500 065, IN
4 School of Ecology and Conservation, IN
1 Independent Researcher, Bengaluru 560 024, IN
2 Department of Forestry and Environment Science, University of Agricultural Sciences, GKVK Campus, Bengaluru 500 065, IN
3 Department of Entomology, University of Agricultural Sciences, GKVK Campus, Bengaluru 500 065, IN
4 School of Ecology and Conservation, IN
Source
Current Science, Vol 118, No 9 (2020), Pagination: 1456-1462Abstract
This paper reports our efforts to use artificial intelligence based on deep convolutional neural network (CNN) as a tool to identify Indian butterflies and moths. We compiled a dataset of over 170,000 images for 800 Indian butterfly species and 500 Indian moth species from diverse sources. We adopted the Effi-cientNet-B6 architecture for our CNN model, with about 44 million learnable parameters. We trained an ensemble of 5 such models on different subsets of the images in our data, employing artificial image augmentation techniques and transfer learning. This ensemble achieved a balanced top-1 accuracy of 86.5%, top-3 accuracy of 94.7%, and top-5 accuracy of 96.4% on the 1300 species, and a mean F1score of 0.867. Thus, our efforts demonstrate artificial intelligence can be effectively used for identifying these biological species that would substantially enhance the work efficiency of field level biologists in several spheres of investigations.Keywords
Artificial Intelligence, Butterfly Identification, Convolutional Neural Network, Moth Identification.References
- Gerven, M. V., Computational foundations of natural intelligence. In Artificial Neural Networks as Models of Neural Information Processing, 2017, vol. 11, 112, pp. 7–30.
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- Csáji, B. C., Approximation with Artificial Neural Networks. M Sc thesis submitted to the Faculty of Sciences, Eötvös Loránd University, Hungary, 2001.
- Ruder, S., An overview of gradient descent optimization algorithms, 2016, vol. 9; arXiv:1609.04747 [cs].
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- Ioffe, S. and Szegedy, C., Batch normalization: accelerating deep network training by reducing internal covariate shift. In Proceedings of the 32nd International Conference on Machine Learning, Lille, France, 2015, vol. 37.
- He, K., Zhang, X., Ren, S. and Sun, J., Delving deep into rectifiers: surpassing human-level performance on imagenet classification. In Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV), Washington, USA, 2015.
- Xie, Q., Luong, M.-T., Hovy, E. and Le, Q. V., Self-training with Noisy Student improves ImageNet classification, 2020; arXiv:abs/1911.04252.
- Russakovsky, O. et al., ImageNet large scale visual recognition challenge. Int. J. Comput. Vision, 2015, 115(12), 211–252.
- Schroff, F., Kalenichenko, D. and Philbin, J., FaceNet: a unified embedding for face recognition and clustering. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, USA, 2015.
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- Chang, Q., Qu, H., Wu, P. and Yi, J., Fine-Grained Butterfly and Moth Classification Using Deep Convolutional Neural Networks, Machine Learning course project report, submitted to the Department of Computer Science, Rutgers University, 2017; https:// pdfs.seman-ticscholar.org/4cf2/045b811c9e0807f9c94fc991566a6f5adbf4.pdf
- Poremski, A., Introducing LepSnap, 7, 2017; https://medium.com/@andrporemski/introducing-lepsnap-ff356c4c9da6(accessed on December 2018).
- Indian Bioresource Information Network; http://www.ibin.gov.in (accessed in 2019).
- Krause, J. et al., The unreasonable effectiveness of noisy data for fine-grained recognition. In Computer Vision – ECCV 2016(eds Leibe, B. et al.), Springer International Publishing, Cham, Switzerland, 2016, vol. 9907, pp. 301–320.
- Tan, M. and Le, Q. V., EfficientNet: rethinking model scaling for convolutional neural networks. InInternational Conference on Machine Learning (ICML), Long Beach, California, 2019.
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- How Justified is IPR towards ‘Life’?
Abstract Views :246 |
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Authors
Affiliations
1 School of Ecology and Conservation, University of Agricultural Sciences, GKVK, Bengaluru 560 065, IN
1 School of Ecology and Conservation, University of Agricultural Sciences, GKVK, Bengaluru 560 065, IN
Source
Current Science, Vol 119, No 5 (2020), Pagination: 731-732Abstract
No Abstract.- Are we creating an unsustainable State of Fear?
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Authors
Affiliations
1 University of Agricultural Sciences, Bengaluru 560 064, India, IN
1 University of Agricultural Sciences, Bengaluru 560 064, India, IN