|
|
Chaitra, A.; Upgupta, S.; Bhatta, L. D.; Mathangi, J.; Anitha, D. S.; Sindhu, K.; Kumar, V.; Agrawal, N. K.; Murthy, M. S. R.; Qamar, F.; Murthy, I. K.; Sharma, J.; Chaturvedi, R. K.; Bala, G.; Ravindranath, N. H.
The impacts of climate change in terms of forest vegetation shifts and Net Primary Productivity (NPP) changes are assessed for Brahmaputra, Koshi and Indus river basins for the mid (2021-2050) and long (2071-2100) terms for RCP4
.5 and RCP8.5 scenarios. Two Dynamical Global Vegetation Models (DGVMs), Integrated BIosphere Simulator (IBIS) and (Lund Postdam and Jena (LPJ), have been used for this purpose. The DGVMs are driven by the ensemble mean climate projections from 5 climate models that contributed to the CMIP5 data base. While both DGVMs project vegetation shifts in the forest areas of the basins, there are large differences in vegetation shifts projected by IBIS and LPJ. This may be attributed to differing representation of land surface processes and to differences in the number of vegetation types (Plant Functional Types) defined and simulated in the two models. However, there is some agreement in NPP changes as projected by both IBIS and LPJ, with IBIS mostly projecting a larger increase in NPP for the future scenarios. Despite the uncertainties with respect to climate change projections at river basin level and the differing impact assessments from different DGVMs, it is necessary to assess the “vulnerability” of the forest ecosystems and forest dependent communities to current climate risks and future climate change and to develop and implement resilience or adaptation measures. Assessment of the “vulnerability” and designing of the adaptation strategies could be undertaken for all the forested grids where both IBIS and LPJ project vegetation shifts
Read More
|
|
|
Karki, S.; Pforte, B.; Karky, B. S.; Statz, J.; Dangi, R. B.; Khanal, D. R.; Chand, N. B.; Poudel, M.; Maraseni, T.; Cadman, T.; Lopez, F.; Delma, S.; Wangchuk, S.; Norbu, L.; Oo, T. N.; Rawat, V. R. S.; Singh, T. P.; Sharma, J. V.; Windhorst, K.
REDD+ Initiative has prepared a UNFCCC submission report “The Development of REDD+ Safeguards in the Hindu Kush Himalaya: Recent Experiences and Processes” to demonstrate that the participating HKH countries are committed to developing REDD+ safeguards
. This document illustrates the ongoing progress made on integrating safeguard in REDD+ programme in the HKH countries that are in their REDD readiness phase. This report synthesizes the overall progress of National Safeguard System, by analyzing gaps and common challenges to implement REDD+ safeguards in Bhutan, India, Myanmar and Nepal and recommends the way forward. This report, prepared through series of regional level South-South learning workshops in 2015 and 2016, is a testament of how the HKH countries are trying to comply with the UNFCCC guidelines by engaging in the development of National Safeguard System
Read More
|
|
|
Roy, P. S.; Behera, M. D.; Murthy, M. S. R.; Roy, A.; Singh, S.; Kushwaha, S. P. S.; Jha, C. S.; Sudhakar, S.; Joshi, P. K.; Reddy, C. S.; Gupta, S.; Pujar, G.; Dutt, C. B. S.; Srivastava, V. K.; Porwal, M. C.; Tripathi, P.; Singh, J. S.; Chitale, V.; Skidmore, A. K.; Rajshekhar, G.; Kushwaha, D.; Karnataka, H.; Saran, S.; Giriraj, A.; Padalia, H.; Kale, M.; Nandy, S.; Jeganathan, C.; Singh, C. P.; Biradar, C. M.; Pattanaik, C.; Singh, D. K.; Devagiri, G. M.; Talukdar, G.; Panigrahy, R. K.; Singh, H.; Sharma, J. R.; Haridasan, K.; Trivedi, S.; Singh, K. P.; Kannan, L.; Daniel, M.; Misra, M. K.; Niphadkar, M.; Nagbhatla, N.; Prasad, N.; Tripathi, O. P.; Prasad, P. R. C.; Dash, P.; Qureshi, Q.; Tripathi, S. K.; Ramesh, B. R.; Gowda, B.; Tomar, S.; Romshoo, S.; Giriraj, S.; Ravan, S. A.; Behera, S. K.; Paul, S.; Das, A. K.; Ranganath, B. K.; Singh, T. P.; Sahu, T. R.; Shankar, U.; Menon, A. R. R.; Srivastava, G.; Neeti; Sharma, S.; Mohapatra, U. B.; Peddi, A.; Rashid, H.; Salroo, I.; Krishna, P. H.; Hajra, P. K.; Vergheese, A. O.; Matin, S.; Chaudhary, S. A.; Ghosh, S.; Lakshmi, U.; Rawat, D.; Ambastha, K.; Kalpana, P.; Devi, B. S. S.; Gowda, B.; Sharma, K. C.; Mukharjee, P.; Sharma, A.; Davidar, P.; Raju, R. R. V.; Ketewa, S. S.; Kant, S.; Raju, V. S.; Uniyal, B. P.; Debnath, B.; Rout, D. K.; Thapa, R.; Joseph, S.; Chhetri, P.; Ramchandran, R.
A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented
. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (Error! Hyperlink reference not valid. Typ
Read More
|
|
|
Roy, P. S.; Behera, M. D.; Murthy, M. S. R.; Roy, A.; Singh, S.; Kushwaha, S. P. S.; Jha, C. S.; Sudhakar, S.; Joshi, P. K.; Reddy, C. S.; Gupta, S.; Pujar, G.; Dutt, C. B. S.; Srivastava, V. K.; Porwal, M. C.; Tripathi, P.; Singh, J. S.; Chitale, V.; Skidmore, A. K.; Rajshekhar, G.; Kushwaha, D.; Karnataka, H.; Saran, S.; Giriraj, A.; Padalia, H.; Kale, M.; Nandy, S.; Jeganathan, C.; Singh, C. P.; Biradar, C. M.; Pattanaik, C.; Singh, D. K.; Devagiri, G. M.; Talukdar, G.; Panigrahy, R. K.; Singh, H.; Sharma, J. R.; Haridasan, K.; Trivedi, S.; Singh, K. P.; Kannan, L.; Daniel, M.; Misra, M. K.; Niphadkar, M.; Nagbhatla, N.; Prasad, N.; Tripathi, O. P.; Prasad, P. R. C.; Dash, P.; Qureshi, Q.; Tripathi, S. K.; Ramesh, B. R.; Gowda, B.; Tomar, S.; Romshoo, S.; Giriraj, S.; Ravan, S. A.; Behera, S. K.; Paul, S.; Das, A. K.; Ranganath, B. K.; Singh, T. P.; Sahu, T. R.; Shankar, U.; Menon, A. R. R.; Srivastava, G.; Neeti; Sharma, S.; Mohapatra, U. B.; Peddi, A.; Rashid, H.; Salroo, I.; Krishna, P. H.; Hajra, P. K.; Vergheese, A. O.; Matin, S.; Chaudhary, S. A.; Ghosh, S.; Lakshmi, U.; Rawat, D.; Ambastha, K.; Kalpana, P.; Devi, B. S. S.; Gowda, B.; Sharma, K. C.; Mukharjee, P.; Sharma, A.; Davidar, P.; Raju, R. R. V.; Ketewa, S. S.; Kant, S.; Raju, V. S.; Uniyal, B. P.; Debnath, B.; Rout, D. K.; Thapa, R.; Joseph, S.; Chhetri, P.; Ramchandran, R.
A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented
. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (Error! Hyperlink reference not valid. Typ
Read More
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Pulse production in India is characterised by diversity of crops and their regional specificity based on adaptation to prevailing agroclimatic conditions
. Pulses as a group can utilise limited soil moisture and nutrients more efficiently than cereal crops and for that reason farmers have chosen them to grow under highly adverse conditions. The process of differential resource allocation to pulse crops operates at agro-ecological niche allocation and at individual farmers level, out of necessity, and not out of choice or preference. At present more than 92 per cent of the area under pulses is confined to unirrigated areas, and in future the bulk of pulse production will continue to come from unirrigated areas. Therefore, any plan for increasing pulse production in the country should be based on a long-term approach for improved productivity of these crops under rainfed farming conditions rather than on the use of high inputs. Crop productivity comparisons made under unirrigated conditions between pulses and cereals do not support the general belief that pulses suffer from inherent low productivity. Rather the low productivity of pulses is due to the low input conditions associated with the complex socio-economic and agroclimatic problems of rainfed agriculture. Long neglect of rainfed areas has resulted in poor institutional development and, therefore, there is considerable lag in developing strong traditions of scientific thinking and research, and training of scientists to work in these areas. This para deals in detail with agroclimatic, socio-economic and biological constraints of pulse production and gaps in transfer of technology in rainfed areas
Read More
|
email alert
or subscribe to the 
RSS feed.
