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Revised Universal Soil Loss Equation (RUSLE) model coupled with transport limited sediment delivery (TLSD) function was used to predict the longtime average annual soil loss, and to identify the critical erosion-/deposition-prone areas in a tropical mountain river basin, viz
., Muthirapuzha River Basin (MRB; area = 271.75 km2), in the southern Western Ghats, India. Mean gross soil erosion in MRB is 14.36 t ha−1 yr−1, whereas mean net soil erosion (i.e., gross erosion–deposition) is only 3.60 t ha−1 yr−1 (i.e., roughly 25% of the gross erosion). Majority of the basin area (∼86%) experiences only slight erosion (=8564
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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
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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
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The paper evaluates sensitivity of various spaceborne digital elevation models (DEMs), viz
., Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mapping Mission (SRTM) and Global Multi-resolution Terrain Elevation Data 2010 (GMTED), in comparison with the DEM (TOPO) derived from contour data of 20 m interval of Survey of India topographic sheets of 1: 50,000 scale. Several topographic attributes, such as elevation (above mean sea level), relative relief, slope, aspect, curvature, slope-length and -steepness (LS) factor, terrain ruggedness index (TRI), topographic wetness index (TWI), hypsometric integral (Ihyp) and drainage network attributes (stream number and stream length) of two tropical mountain river basins, viz., Muthirapuzha River Basin and Pambar River Basin are compared to evaluate the variations. Though the basins are comparable in extent, they differ in respect of terrain characteristics and climate. The results suggest that ASTER and SRTM provide equally reliable representation of topography portrayed by TOPO and the topographic attributes extracted from the spaceborne DEMs are in agreement with those derived from TOPO. Despite the coarser resolution, SRTM shows relatively higher vertical accuracy (RMSE = 23 and 20 m respectively in MRB and PRB) compared to ASTER (RMSE = 33 and 24 m) and GMTED (RMSE = 59 and 48 m). Vertical accuracy of all the spaceborne DEMs is influenced by relief of the terrain as well as type of vegetation. Further, GMTED shows significant deviation for most of the attributes, indicating its inability for mountain-river-basin-scale studies
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Laurance, W. F.; Carolina Useche, D.; Rendeiro, J.; Kalka, M.; Bradshaw, C. J. A.; Sloan, S. P.; Laurance, S. G.; Campbell, M.; Abernethy, K.; Alvarez, P.; Arroyo-Rodriguez, V.; Ashton, P.; Benitez-Malvido, J.; Blom, A.; Bobo, K. S.; Cannon, C. H.; Cao, M.; Carroll, R.; Chapman, C.; Coates, R.; Cords, M.; Danielsen, F.; De Dijn, B.; Dinerstein, E.; Donnelly, M. A.; Edwards, D.; Edwards, F.; Farwig, N.; Fashing, P.; Forget, P.-M.; Foster, M.; Gale, G.; Harris, D.; Harrison, R.; Hart, J.; Karpanty, S.; John Kress, W.; Krishnaswamy, J.; Logsdon, W.; Lovett, J.; Magnusson, W.; Maisels, F.; Marshall, A. R.; McClearn, D.; Mudappa, D.; Nielsen, M. R.; Pearson, R.; Pitman, N.; van der Ploeg, J.; Plumptre, A.; Poulsen, J.; Quesada, M.; Rainey, H.; Robinson, D.; Roetgers, C.; Rovero, F.; Scatena, F.; Schulze, C.; Sheil, D.; Struhsaker, T.; Terborgh, J.; Thomas, D.; Timm, R.; Nicolas Urbina-Cardona, J.; Vasudevan, K.; Joseph Wright, S.; Carlos Arias-G, J.; Arroyo, L.; Ashton, M.; Auzel, P.; Babaasa, D.; Babweteera, F.; Baker, P.; Banki, O.; Bass, M.; Bila-Isia, I.; Blake, S.; Brockelman, W.; Brokaw, N.; Bruhl, C. A.; Bunyavejchewin, S.; Chao, J.-T.; Chave, J.; Chellam, R.; Clark, C. J.; Clavijo, J.; Congdon, R.; Corlett, R.; Dattaraja, H. S.; Dave, C.; Davies, G.; de Mello Beisiegel, B.; Nazare Paes da Silva, R. d.; Di Fiore, A.; Diesmos, A.; Dirzo, R.; Doran-Sheehy, D.; Eaton, M.; Emmons, L.; Estrada, A.; Ewango, C.; Fedigan, L.; Feer, F.; Fruth, B.; Giacalone Willis, J.; Goodale, U.; Goodman, S.; Guix, J. C.; Guthiga, P.; Haber, W.; Hamer, K.; Herbinger, I.; Hill, J.; Huang, Z.; Fang Sun, I.; Ickes, K.; Itoh, A.; Ivanauskas, N.; Jackes, B.; Janovec, J.; Janzen, D.; Jiangming, M.; Jin, C.; Jones, T.; Justiniano, H.; Kalko, E.; Kasangaki, A.; Killeen, T.; King, H.-b.; Klop, E.; Knott, C.; Kone, I.; Kudavidanage, E.; Lahoz da Silva Ribeiro, J.; Lattke, J.; Laval, R.; Lawton, R.; Leal, M.; Leighton, M.; Lentino, M.; Leonel, C.; Lindsell, J.; Ling-Ling, L.; Eduard Linsenmair, K.; Losos, E.; Lugo, A.; Lwanga, J.; Mack, A. L.; Martins, M.; Scott McGraw, W.; McNab, R.; Montag, L.; Myers Thompson, J.; Nabe-Nielsen, J.; Nakagawa, M.; Nepal, S.; Norconk, M.; Novotny, V.; O'Donnell, S.; Opiang, M.; Ouboter, P.; Parker, K.; Parthasarathy, N.; Pisciotta, K.; Prawiradilaga, D.; Pringle, C.; Rajathurai, S.; Reichard, U.; Reinartz, G.; Renton, K.; Reynolds, G.; Reynolds, V.; Riley, E.; Rodel, M.-O.; Rothman, J.; Round, P.; Sakai, S.; Sanaiotti, T.; Savini, T.; Schaab, G.; Seidensticker, J.; Siaka, A.; Silman, M. R.; Smith, T. B.; Almeida, S. S. d.; Sodhi, N.; Stanford, C.; Stewart, K.; Stokes, E.; Stoner, K. E.; Sukumar, R.; Surbeck, M.; Tobler, M.; Tscharntke, T.; Turkalo, A.; Umapathy, G.; van Weerd, M.; Vega Rivera, J.; Venkataraman, M.; Venn, L.; Verea, C.; Volkmer de Castilho, C.; Waltert, M.; Wang, B.; Watts, D.; Weber, W.; West, P.; Whitacre, D.; Whitney, K.; Wilkie, D.; Williams, S.; Wright, D. D.; Wright, P.; Xiankai, L.; Yonzon, P.; Zamzani, F.
The rapid disruption of tropical forests probably imperils global biodiversity more than any other contemporary phenomenon
. With deforestation advancing quickly, protected areas are increasingly becoming final refuges for threatened species and natural ecosystem processes. However, many protected areas in the tropics are themselves vulnerable to human encroachment and other environmental stresses. As pressures mount, it is vital to know whether existing reserves can sustain their biodiversity. A critical constraint in addressing this question has been that data describing a broad array of biodiversity groups have been unavailable for a sufficiently large and representative sample of reserves. Here we present a uniquely comprehensive data set on changes over the past 20 to 30 years in 31 functional groups of species and 21 potential drivers of environmental change, for 60 protected areas stratified across the world’s major tropical regions. Our analysis reveals great variation in reserve ‘health’: about half of all reserves have been effective or performed passably, but the rest are experiencing an erosion of biodiversity that is often alarmingly widespread taxonomically and functionally. Habitat disruption, hunting and forest-product exploitation were the strongest predictors of declining reserve health. Crucially, environmental changes immediately outside reserves seemed nearly as important as those inside in determining their ecological fate, with changes inside reserves strongly mirroring those occurring around them. These findings suggest that tropical protected areas are often intimately linked ecologically to their surrounding habitats, and that a failure to stem broad-scale loss and degradation of such habitats could sharply increase the likelihood of serious biodiversity declines
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