ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 3, pp. 178-185

Dark conifer forests NDVI as a function of climate in the Volga basin

P.A. Shary 1 , L.S. Sharaya 2 
1 Institute of Physicochemical and Biological Problems in Soil Science RAS, Pushchino, Moscow Region, Russia
2 Institute of Ecology of the Volga Basin RAS, Togliatti, Russia
Accepted: 26.05.2022
DOI: 10.21046/2070-7401-2022-19-3-178-185
Vegetation index NDVI of dark-conifer forests for summer of 2005 is statistically compared with climate in the Volga basin. We separate two portions of the region that are represented by two samples each of 200 points (plots 1 km2): north-eastern (NE) and western (W) ones. Average winter temperature in W is 3.5 degrees greater than in NE. Two models of multiple regression are constructed that link NDVI with climate: for NE and for W. The relation of NDVI to winter or February temperature is positive in NE, but negative in W. The link of NDVI with precipitation in the cold period (November-March) is negative in NE and positive in W. We suggest that such non-linear behavior of dark-conifer forest NDVI for the whole region may be explained by both frost damages and known effects of winter drought. This was additionally strengthened by the influence of precipitation. Winter drought consists in that, at the end of winter, when roots are still frozen increasing transpiration results in water loss of branches and this leads to diminished NDVI later in summer.
Keywords: dark conifer forests, climate, winter drought, multiple regression
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References:

  1. Bartalev S. A., Egorov V. A., Zharko V. O., Loupian E. A., Plotnikov D. E., Khvostikov S. A., Shabanov N. V., Sputnikovoe kartografirovanie rastitel’nogo pokrova Rossii (Land cover mapping over Russia using satellite data), Moscow: IKI, 2016, 208 p. (in Russian).
  2. Walter H., Allgemeine Geobotanik, Stuttgart: Eugen Ulmer, 1979, 260 p.
  3. Gribova S. A., Isachenko T. I., Lavrenko E. M., Rastitel’nost’ evropeiskoi chasti SSSR (Vegetation of the European Part of the USSR), Leningrad: Nauka, 1980, 430 p. (in Russian).
  4. Shary P. A., Pinskii D. L., Statistical evaluation of the relationships between spatial variability in the organic carbon content in gray forest soils, soil density, concentrations of heavy metals, and topography, Eurasian Soil Science, 2013, Vol. 46, No. 11, pp. 1076–1087, DOI: 10.7868/S0032180X13090104.
  5. Shary P. A., Ivanova A. V., Sharaya L. S., Kostina N. V., Rozenberg G. S., Comparative analysis of the species richness of life forms of vascular plants in the Middle Volga, Contemporary Problems of Ecology, 2019, Vol. 12, pp. 310–320, DOI: 10.15372/SEJ20190402.
  6. Shary P. A., Sharaya L. S., Sidyakina L. V., The relation of forest NDVI to climate in Volga basin, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 4, pp. 154–163 (in Russian), DOI: 10.21046/2070-7401-2020-17-4-154-163.
  7. Shvidenko A. Z., Global changes and forest taxation, Lesnaya taksatsiya i lesoustroistvo, 2012, No. 1(47), pp. 52–75 (in Russian).
  8. Fisher J. I., Mustard J. F., Vadeboncoeur M. A., Green leaf phenology at Landsat resolution: scaling from the field to the satellite, Remote Sensing of Environment, 2006, Vol. 100, pp. 265–279, https://doi.org/10.1016/j.rse.2005.10.022.
  9. Hijmans R. J., Cameron S. E., Parra J. L., Jones P. J., Jarvis A., Very high resolution interpolated climate surfaces for global land areas, Intern. J. Climatology, 2005, Vol. 25, pp. 1965–1978, https://doi.org/10.1002/joc.1276.
  10. Hoylman Z. H., Jencso K. G., Hu J., Holden Z. A., Allred B., Dobrowski S., Robinson N., Martin J. T., Affleck D., Seielstad C., The topographic signature of ecosystem climate sensitivity in the western United States, Geophysical Research Letters, 2019, Vol. 46, pp. 14508–14520, https://doi.org/10.1029/2019GL085546.
  11. Hwang T., Song C., Vose J. M., Band L. E., Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index, Landscape Ecology, 2011, Vol. 26, pp. 541–556, https://doi.org/10.1007/s10980-011-9580-8.
  12. Lischke H., Guisan A., Fischlin A., Bugmann H., Vegetation responses to climate change in the Alps — Modeling studies, In: A View from the Alps: Regional Perspectives on Climate Change, Cebon P., Dahinden U., Davies H., Imboden D., Jaeger C. (eds.), Boston: MIT Press, 1998, Chapter 6, pp. 309–350.
  13. Montgomery D. C., Peck E. A., Introduction to Linear Regression Analysis, New York: John Wiley and Sons, 1982, 504 p.
  14. Moser D., Dullinger S., Englisch T., Niklfeld H., Plutzar C., Sauberer N., Zechmeister H. G., Grabherr G., Environmental determinants of vascular plant species richness in the Austrian Alps, J. Biogeography, 2005, Vol. 32, pp. 1117–1127, doi.org/10.1111/j.1365-2699.2005.01265.x.
  15. Richerson P. J., Lum K.-L., Patterns of plant species diversity in California: relation to weather and topography, The American Naturalist, 1980, Vol. 116, pp. 504–536.
  16. Rodriguez E., Morris C. S., Belz J. E., Chapin E. C., Martin J. M., Daffer W., Hensley S., An assessment of the SRTM topographic products, Technical Report JPL D-31639, Pasadena, CA, USA: Jet Propulsion Lab., 2005, 143 p.
  17. Wood J., Overview of software packages used in geomorphometry, In: Geomorphometry: Concepts, Software, Applications, Hengl T., Reuter H. I. (eds.), Ser. Developments in Soil Science, Vol. 33, Amsterdam, etc.: Elsevier, 2009, Chapter 10, pp. 257–267, doi.org/10.1016/S0166-2481(08)00010-X.
  18. Zhou L., Tucker C. J., Kaufmann R. K., Slayback D., Shabanov N. V., Myneni R. B., Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999, J. Geophysical Research, 2001, Vol. 106, pp. 20069–20083, https://doi.org/10.1029/2000JD000115.