Using Habitat Quality and Diversity Measures to Assess Conservation Priorities for Sites in the Ukrainian Carpathians

  • Alex MkrtchianEmail author
Part of the Environmental Science and Engineering book series (ESE)


The chapter investigates the possibilities and advantages of using habitat quality and diversity measures in the design of ecological networks in the Ukrainian Carpathians. It was shown that habitat diversity could be indicated by the measures of topographic variance. The latter correlate well with some characteristics connected with ecological as well as socioeconomic factors determining land suitability for conservation. The received measure of topographic variation correlates significantly with the abundance of rare and endangered plant species entered into the Ukrainian Red Book. The correlation of this abundance with the Normalized Difference Vegetation Index (NDVI) values is not as pronounced and is highly dependent on local conditions. An attempt was made to arrive at an integral measure of the appropriateness for assigning protected status, using easily obtained remote sensing and elevation data.


Normalize Difference Vegetation Index Protected Status Ecological Network Universal Transverse Mercator Protected Area Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Alpin P (2007) On scales and dynamics of observing the environment. Int J Remote Sens 27(11):2123–2140Google Scholar
  2. Austin MP, Smith TM (1989) A new model for the continuum concept. Vegetatio 83:35–47CrossRefGoogle Scholar
  3. Bawa K, Rose J, Ganeshaiah KN, Barve N, Kiran MC, Umashaanker R (2002) Assessing biodiversity from space: an example from the Western Ghats. India Conserv Ecol 6(2):7Google Scholar
  4. Blöschl G (1995) Scale issues in hydrological modelling: a review. Hydrol Process 9(3–4):251–290CrossRefGoogle Scholar
  5. Brusak V, Bezushko A, Voznyi Y, Zinko Y, Feldbaba-Klushyna L, Masikevych Y, Matveyev S, Movchan Y, Popovych S, Prychodko M (2006) Skhema ecomerezhi Ukrajinskyh Karpat (natsionalnyj riven’). Living Ukraine 9(10):8–9Google Scholar
  6. Clark WC (1985) Scales of climate impacts. Clim Chang 7:5–27CrossRefGoogle Scholar
  7. Danell K, Lundberg P, Niemela P (1996) Species richness in mammalian herbivores: patterns in the boreal zone. Ecography 19(4):404–409CrossRefGoogle Scholar
  8. Deodatus FD, Protsenko L (eds) (2010) Creation of ecological corridors in Ukraine. A manual on stakeholder involvement and landscape-ecological modelling to connect protected areas, based on a pilot in the Carpathians. State Agency for Protected Areas of the Ministry of Environmental Protection of Ukraine, Altenburg and Wymenga Ecological Consultants, InterEcoCentre, KyivGoogle Scholar
  9. Frank A, Karn J (2003) Vegetation indices, CO2 flux, and biomass for Northern Plains grasslands. J Range Manag 56:382–387CrossRefGoogle Scholar
  10. Glenn EP, Huete AR, Nagler PL, Nelson SG (2008) Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: what vegetation indices can and cannot tell us about the landscape. Sens 8(4):2136–2160CrossRefGoogle Scholar
  11. Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135:147–186CrossRefGoogle Scholar
  12. Herenchuk K (ed) (1968) Pryroda Ukrajinskyh Karpat. Lviv University, LvivGoogle Scholar
  13. Hofer G, Wagner H, Herzog F, Edwards PG (2008) Effects of topographic variability on the scaling of plant species richness in gradient dominated landscapes. Ecography 31(1):131–139CrossRefGoogle Scholar
  14. Jarvis A, Reuter HI, Nelson A, Guevara E (2008) Hole-filled seamless SRTM data V4. International centre for tropical agriculture (CIAT). Accessed 31 Oct 2010
  15. Karr JR, Roth RR (1971) Vegetation structure and avian diversity in several new world areas. Am Nat 105:423–435CrossRefGoogle Scholar
  16. Levin SA (1992) The problem of pattern and scale in ecology. Ecol 73:1943–1983CrossRefGoogle Scholar
  17. MacArthur RH (1964) Environmental factors affecting bird species diversity. Am Nat 98:387–397CrossRefGoogle Scholar
  18. Margalef R (1968) Perspectives in ecological theory. Chicago University Press, ChicagoGoogle Scholar
  19. McGarigal K, Marks B (1994) Fragstats: spatial pattern analysis program for quantifying landscape structure. Reference manual, CorvallisGoogle Scholar
  20. Ministry for environmental protection of Ukraine (1996) Ukrainian red book, 2nd edn. Accessed 31 Oct 2010
  21. Montgomery D, Foufoula-Georgiou E (1993) Channel network source representation for digital elevation models. Water Resour Res 29(12):3925–3934CrossRefGoogle Scholar
  22. NASA Landsat Program (2009) Landsat 7 ETM+ scene L71185026_02620070522, Geo-cover. USGS, Sioux FallsGoogle Scholar
  23. Oindo BO, de By RA, Skidmore AK (2000) Interannual variability of NDVI and bird species diversity in Kenya. Int J Appl Earth Obs Geoinf 2(3–4):172–180CrossRefGoogle Scholar
  24. Owen JG (1989) Patterns of herpetofaumal species richness: relation to temperature, precipitation, and variance in elevation. J Biogeogr 16(2):141–150CrossRefGoogle Scholar
  25. Pianka ER (1966) Latitudinal gradients in species diversity: a review of concepts. Am Nat 100:33–46CrossRefGoogle Scholar
  26. Podolsky R (1994) Ecological hot spots. A method for estimating biodiversity directly from digital Earth imagery. Earth Obs Mag 30–36Google Scholar
  27. Prince SD (1991) Satellite remote sensing of primary production. Int J Remote Sens 12:1301–1311CrossRefGoogle Scholar
  28. Purvis A, Hector A (2000) Getting the measure of biodiversity. Nature 405:212–219CrossRefGoogle Scholar
  29. Richerson PJ, Lum K (1980) Patterns of plant species diversity in California: relation to weather and topography. Am Nat 116(14):504–536CrossRefGoogle Scholar
  30. Rouse JW, Haas RH, Schell JA, Deering DW (1973) Monitoring vegetation systems in the Great Plains with ERTS. In: Third ERTS Symposium, 10–14 December 1973, Greenbelt, MD. NASA, Washington, DC. SP-351(I), pp 309–317Google Scholar
  31. Running S, Nemani R, Heinsch F, Zhao M, Reeves M, Hashimoto H (2004) A continuous satellite-derived measure of global primary production. Biosci 54:547–560CrossRefGoogle Scholar
  32. Sheliag-Sosonko Y (1999) Rozbudova ecomerezhi Ukrajiny. Phytosociocenter, KyivGoogle Scholar
  33. 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, Nov 10–14, 2003, Honolulu, Hawaii. International Center for Remote Sensing of Environment, Tucson, AZGoogle Scholar
  34. Tang Z, Wang Z, Zheng C, Fang J (2006) Biodiversity in China’s mountains. Front Ecol Environ 4(7):347–352CrossRefGoogle Scholar
  35. Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3(4):385–397CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Ivan Franko National University of LvivLvivUkraine

Personalised recommendations