Advertisement

Assessment of Forest Species Diversity in Sariska Tiger Reserve, Rajasthan, India

  • Pavan Kumar
  • Haroon Sajjad
  • Sufia Rehman
  • Purva Jain
Chapter

Abstract

This study makes an attempt to assess tree species diversity in Sariska Tiger Reserve (STR), Rajasthan, India, using Sentinel-2A data. We collected tree samples from ten plots in STR through random variable probability selection method. A total of 62 different species and 584 individual trees were selected from the plots using a principal coordinates of neighborhood matrices (PCNM). Four ecological indicator indices, namely, Margalef index (SR), Simpson’s diversity (D) index, Shannon-Wiener index (H′), and Pielou’s index (J), were utilized for measuring species diversity. Results revealed that Simpson’s diversity (D) index was more suited for determining species diversity, while Shannon-Wiener index (H/) was found to be the best index for assessing species richness. The methodology used in this study can help forest managers, environmentalist, and conservationist for formulating policies for management of forest ecosystem at various scales. This approach will be instructive in examining varied tree species and their richness with Simpson’s diversity (D) index and Shannon-Wiener index (H/).

Keywords

Species diversity Species richness Simpson’s diversity index Shannon-Wiener index Sariska Tiger Reserve 

References

  1. Balvanera P, Lott E, Segura G, Siebe C, Islas A (2002) Patterns of β-diversity in a Mexican tropical dry forest. J Veg Sci 13:145–158CrossRefGoogle Scholar
  2. Bettinger P, Tang M (2015) Tree-level harvest optimization for structure-based forest management based on the species mingling index. Forests 6:1121–1144CrossRefGoogle Scholar
  3. Bock M, Rossner G, Wissen M, Remm K, Langanke T, Lang S, Klug H, Blaschke T, Vrscaj B (2005) Spatial indicators for nature conservation from European to local scale. Ecol Indic 5:322–338CrossRefGoogle Scholar
  4. Bray JR, Curtis JT (1957) An ordination of the upland forest communities of southern Wisconsin. Ecol Monogr 27(4):325–349CrossRefGoogle Scholar
  5. Chiarucci A, Bonini I (2005) Quantitative floristics as a tool for the assessment of plant diversity in Tuscan forests. For Ecol Manag 212:160–170CrossRefGoogle Scholar
  6. Chust G, Chave J, Condit R, Aguilar S, Lao S, Pérez R (2006) Determinants and spatial modeling of tree beta-diversity in a tropical forest landscape in Panama. J Veg Sci 17:83–92Google Scholar
  7. Dale MRT, Fortin MJ (2002) Spatial autocorrelation and statistical tests in ecology. Ecoscience 9:162–167CrossRefGoogle Scholar
  8. D’Alessandro L, Fattorini L (2002) Resampling estimators of species richness from presence–absence data: why they don’t work. Metro 61:5–19Google Scholar
  9. Fahrig L (2003) Effects of habitat fragmentation on biodiversity. Annu Rev Ecol Evol Syst 34:487–515CrossRefGoogle Scholar
  10. Fairbanks HK, McGwire KC (2004) Patterns of floristic richness in vegetation communities of California: regional scale analysis with multi-temporal NDVI. Glob Ecol Biogeogr 13:221–235CrossRefGoogle Scholar
  11. Ferretti M, Chiarucci A (2003) Design concepts adopted in long-term forest monitoring programs in Europe-problems for the future? Sci Total Environ 310:171–178CrossRefGoogle Scholar
  12. Fearnside PM, Laurance WF (2004) Tropical deforestation and greenhouse gas emissions. Ecol Appl 14:982–986CrossRefGoogle Scholar
  13. Feilhauer H, Schmidtlein S (2009) Mapping continuous fields of forest alpha and beta diversity. Appl Veg Sci 12:429–439CrossRefGoogle Scholar
  14. Foody GM, Cutler MEJ (2006) Mapping the species richness and composition of tropical forests from remotely sensed data with neural networks. Ecol Model 195:37–42CrossRefGoogle Scholar
  15. Gallardo-Cruz JA, Pérez-García EA, Meave JA (2009) β-Diversity and vegetation structure as influenced by slope aspect and altitude in a seasonally dry tropical landscape. Landsc Ecol 24:473–482CrossRefGoogle Scholar
  16. Gallardo-Cruz JA, Meave JA, Pérez-García EA, Hernández-Stefanoni JL (2010) Spatial structure of plant communities in a complex tropical landscape: implications for alpha and beta diversity. Commun Ecol 11:202–210CrossRefGoogle Scholar
  17. Gibbs HK, Brown S, Niles JO, Foley JA (2007) Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environ Res Lett 2(4):045023CrossRefGoogle Scholar
  18. Gillespie TW, Foody GM, Rocchini D, Giorgi AP, Saatchi S (2008) Measuring and modelling biodiversity from space. Prog Phys Geogr 32:203–221CrossRefGoogle Scholar
  19. Haralick RM, Shanmugam K, Dinstein I (1973) Textural features for image classification. IEEE Trans Syst Man Cybern SMC-3:610–621CrossRefGoogle Scholar
  20. He KS, Zhang J, Zhang Q (2009) Linking variability in species composition and MODIS NDVI based on beta diversity measurements. Acta Oecol 35:14–21CrossRefGoogle Scholar
  21. Hernandez-Stefanoni JL, Ponce-Hernandez R (2004) Mapping the spatial distribution of plant diversity indices in a tropical forest using multi-spectral satellite image classification and field measurements. Biodivers Conserv 13(14):2599–2621Google Scholar
  22. Hernández-Stefanoni JL, Gallardo-Cruz JA, Meave JA, Dupuy JM (2011) Combining geostatistical models and remotely sensed data to improve tropical plant richness mapping. Ecol Indic 11:1046–1056CrossRefGoogle Scholar
  23. Jain P, Ahmed R, Sajjad H (2016) Assessing and monitoring forest health using a forest fragmentation approach in Sariska Tiger Reserve, India. J Geogr 70(5):306–315CrossRefGoogle Scholar
  24. Jain P, Sajjad H (2016a) Analysis of willingness for relocation of the local communities living in the critical Tiger habitat of the Sariska Tiger Reserve, India. Local Environ 21(11):1409–1419CrossRefGoogle Scholar
  25. Jain P, Sajjad H (2016b) Household dependency on forest resources in the Sariska Tiger Reserve (STR), India: implications for management. J Sustain For 35(1):60–74CrossRefGoogle Scholar
  26. Jones MM, Tuomisto H, Borcard D, Legendre P, Clark DB, Olivas PC (2008) Explaining variation in tropical plant community composition: influence of environmental and spatial data quality. Oecologia 155:593–604CrossRefGoogle Scholar
  27. Kalkhan MA, Stafford EJ, Stohlgren TJ (2007) Rapid plant diversity assessment using a pixel nested plot design: a case study in beaver meadows, Rocky Mountain National Park, Colorado, USA. Divers Distrib 13(4):379–388CrossRefGoogle Scholar
  28. Kark S, Levin N, Phinn S (2008) Global environmental priorities: making sense of remote sensing: reply to TREE letter: satellites miss environmental priorities by Loarie et al. (2007). Trends Ecol Evol 23:181–182CrossRefGoogle Scholar
  29. Kirby KJ, Thomas RC (2000) Changes in the ground flora in Wytham woods, southern England from 1974 to 1991: implications for nature conservation. J Veg Sci 11:871–880CrossRefGoogle Scholar
  30. Koellner T, Hersperger AM, Wohlgemuth T (2004) Rarefaction method for assessing plant species diversity on a regional scale. Ecography 27:532–544CrossRefGoogle Scholar
  31. Kumar P, Kumar D, Mandal VP, Pandey PC, Rani M, Tomar V (2012) Settlement risk zone recognition using high resolution satellite data in Jharia coal field, Dhanbad, India. Life Sci J 9(1s):1–6Google Scholar
  32. Kumar P, Sharma LK, Pandey PC, Sinha S, Nathawat MS (2013a) Geospatial strategy for tropical forest-wildlife reserve biomass estimation. 6(2):917–923CrossRefGoogle Scholar
  33. Kumar P, Singh BK, Rani M (2013b) An efficient hybrid classification approach for land use/land cover analysis in a semi-desert area using ETM+ and LISS-III sensor. IEEE Sensors J 13(6):2161–2165CrossRefGoogle Scholar
  34. Kumar P, Pandey PC, Kumar V, Singh BK, Tomar V, Rani M (2014) Efficient recognition of forest species biodiversity by inventory based geospatial approach using LISS IV. IEEE Sensors J 13(6):2161–2165CrossRefGoogle Scholar
  35. Kumar P, Pandey PC, Kumar V, Singh BK, Tomar V, Rani M (2015) Efficient recognition of forest species biodiversity by inventory-based geospatial approach using LISS IV sensor. IEEE Sensors J 15(3):1884CrossRefGoogle Scholar
  36. Laurance WF (1991) Edge effects in tropical forest fragments: application of a model for the design of nature reserves. Biol Conserv 57:205–219CrossRefGoogle Scholar
  37. Le Quéré C, Peters GP, Andres RJ, Andrew RM, Boden T, Ciais P, Friedlingstein P, Houghton RA, Marland G, Moriarty R et al (2013) Global carbon budget 2013. Earth Syst Sci Data Discuss 6:689–760CrossRefGoogle Scholar
  38. Legendre P, Mi X, Ren H, Ma K, Yu M, Sun I-F, He F (2009) Partitioning beta diversity in a subtropical broad-leaved forest of China. Ecology 90:663–674CrossRefGoogle Scholar
  39. Lexerød NL, Eid T (2006) An evaluation of different diameter diversity indices based on criteria related to forest management planning. For Ecol Manag 222:17–28CrossRefGoogle Scholar
  40. Margalef FR (1958) Information theory in ecology. Int J Gen Syst 3:36–71Google Scholar
  41. Mejía-Domínguez NR, Meave JA, Díaz-Ávalos C (2012) Spatial structure of the abiotic environment and its association with sapling community structure and dynamics in a cloud forest. Int J Biometeorol 56(2):305–318CrossRefGoogle Scholar
  42. Morlon H, Chuyong G, Condit R, Hubbell S, Kenfack D, Thomas D, Valencia R, Green JL (2008) A general framework for the distance-decay of similarity in ecological communities. Ecol Lett 11:904–917CrossRefGoogle Scholar
  43. Nagendra H (2001) Using remote sensing to assess biodiversity. Int J Remote Sens 22:2377–2400CrossRefGoogle Scholar
  44. O’Hara K (2014) Multiaged silviculture: managing for complex forest stand structures. Oxford University Press, Oxford, p 17Google Scholar
  45. Oindo BO, Skidmore AK (2002) Interannual variability of NDVI and species richness in Kenya. Int J Remote Sens 23:285–298CrossRefGoogle Scholar
  46. Oindo BO, Skidmore AK (2010) Interannual variability of NDVI and species richness in Kenya, pp 285–298Google Scholar
  47. Oldeland J, Wesuls D, Rocchini D, Schmidt M, Jürgens N (2010a) Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity? Ecol Indic 10:390–396CrossRefGoogle Scholar
  48. Oldeland J, Wesuls D, Rocchini D, Schmidt M, Jürgens N (2010b) Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity? Ecol Indic 10:390–396CrossRefGoogle Scholar
  49. Ozdemir I, Karnieli A (2011) Predicting forest structural parameters using the image texture derived from worldview-2 multispectral imagery in a dryland forest, Israel. Int J Appl Earth Obs Geoinf 13:701–710CrossRefGoogle Scholar
  50. Palmer MW (1995) How should one count species? Nat Areas J 15:124–135Google Scholar
  51. Palmer MW (2005) Distance decay in an old-growth neotropical forest. J Veg Sci 16:161–166CrossRefGoogle Scholar
  52. Palmer MW, Earls P, Hoagland BW, White PS, Wohlgemuth T (2002) Quantitative tools for perfecting species lists. Environmetrics 13:121–137CrossRefGoogle Scholar
  53. Palmer MW, McGlinn DJ, Birrer S (2008) Artifacts and artifictions in biodiversity research. Folia Geobot 43:245–257CrossRefGoogle Scholar
  54. Pérez-García EA, Sevilha AC, Meave JA, Scariot A (2009) Floristic differentiation in limestone outcrops of southern Mexico and Central Brazil: a beta diversity approach. Bol Soc Bot Méx 84:45–58Google Scholar
  55. Pommerening A (2002) Approaches to quantifying forest structures. Forestry 75:305–324CrossRefGoogle Scholar
  56. Rocchini D (2007) Effects of spatial and spectral resolution in estimating ecosystem α-diversity by satellite imagery Remote Sens Environ 111:423–434CrossRefGoogle Scholar
  57. Rocchini D, Andreini Butini S, Chiarucci A (2005) Maximizing plant species inventory efficiency by means of remotely sensed spectral distances. Glob Ecol Biogeogr 14:431–437CrossRefGoogle Scholar
  58. Rocchini D, Nagendra H, Ghate R, Cade BS (2009) Spectral distance decay: assessing species beta-diversity by quantile regression. Photogramm Eng Remote Sens 75:1225–1230CrossRefGoogle Scholar
  59. Rocchini D, Hortal J, Lengyel S, Lobo JM, Jiménez-Valverde A, Ricotta C, Bacaro G, Chiarucci A (2011) Accounting for uncertainty when mapping species distributions: the need for maps of ignorance. Prog Phys Geogr 35:211–226CrossRefGoogle Scholar
  60. Shannon CE, Weaver W (1949) The mathematical theory of communication. The University of Illinois Press, Urbana, pp 1–117Google Scholar
  61. Simpson EH (1949) Measurement of diversity. Nature 163(4148):688–688CrossRefGoogle Scholar
  62. Skidmore AK, Oindo BO, Said MY (2003) Biodiversity assessment by remote sensing. In: Proceedings of the 30th international symposium on remote sensing of the environment: information for risk management and sustainable development, November 10–14, 2003, Honolulu, Hawaii, 4pGoogle Scholar
  63. St-Louis V, Pidgeon AM, Clayton MK, Locke BA, Bash D, Radeloff VC (2009) Satellite image texture and a vegetation index predict avian biodiversity in the Chihuahuan Desert of New Mexico. Ecography 32:468–480CrossRefGoogle Scholar
  64. Thomson A, Calvin K, Chini L, Hurtt G, Edmonds J, Ben Bond-Lamberty B, Frolking S, Wise MA, Janetos AC (2010) Climate mitigation and the future of tropical landscapes. Proc Natl Acad Sci U S A 107:19633–19638CrossRefGoogle Scholar
  65. Tomar V, Kumar P, Rani M, Gupta G, Singh J (2013) A satellite-based biodiversity dynamics capability in tropical forest. Electron J Geotech Eng 18(Bund. F):1171–1180Google Scholar
  66. Turner W, Spector S, Gardiner N, Fladeland M, Sterling E, Steiniger M (2003) Remote sensing for biodiversity science and conservation. Trends Ecol Evol 18:306–314CrossRefGoogle Scholar
  67. Ulanowicz RE (2001) Information theory in ecology. Comput Chem 25(4):393–399CrossRefGoogle Scholar
  68. Whittaker RH (1972) Evolution and measurement of species diversity. Taxon 21:213–251CrossRefGoogle Scholar
  69. Wilson SD (2000) Heterogeneity, diversity and scale in plant communities. In: Hutchings MJ, John EA, Stewart AJA (eds) The ecological consequences of environmental heterogeneity. Blackwell Science, Oxford, pp 53–69Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Pavan Kumar
    • 1
  • Haroon Sajjad
    • 1
  • Sufia Rehman
    • 1
  • Purva Jain
    • 1
  1. 1.Department of GeographyJamia Millia IslamiaNew DelhiIndia

Personalised recommendations