Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
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, 2024, Vol. 21, No. 2, pp. 196-211

Relationships between soil-forming factors and organic carbon stocks in forest soils of Karelia and the Karelian Isthmus using thematic satellite products

А.N. Narykova 1 , A.D. Nikitina 1 , A.S. Plotnikova 1 , M.A. Danilova 1 , N.E. Shevchenko 1 
1 Center for Forest Ecology and Productivity RAS, Moscow, Russia
Accepted: 15.03.2024
DOI: 10.21046/2070-7401-2024-21-2-196-211
This study examines relationships between soil-forming factors and soil organic carbon content, carbon stocks, carbon to nitrogen ratio (C:N) in the forests of Karelia and the Karelian Isthmus. Sample selection and chemical analysis of soils are conducted as part of the field-based program ICP Forest (International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests). Factors are represented as spatial variables obtained from thematic satellite products. Spatial variables are derived from the following geospatial data sources: digital elevation model ArcticDEM, global climate database WorldClim, satellite data MODIS (Moderate Resolution Imaging Spectroradiometer) Terra Snow Cover Daily Global, atmospheric reanalysis ERA5-Land (the fifth generation of European Reanalysis), vegetation map of Northwestern Russia, and geobotanical field-work data from the ICP Forests dataset. The most significant correlations between soil characteristics and soil forming factors occur with the following climate variables: annual mean temperature, precipitation of the coldest quarter, and annual precipitation. A stronger correlation occurs between soil characteristics and snow depth from the atmospheric reanalysis ERA5-Land than with MODIS snow cover data. The relationship between topography variables and soil characteristics is non-significant, presumably due to the sampling design and the minor elevation variations in the research area. The results indicate significant differences between vegetation variables and the C:N ratio in the forest floor. Carbon stocks vary considerably among the different vegetation types of ICP Forests data in the soil layer. Comparisons of autapomorphous and semihydromorphous forest soils do not reveal any differences in soil characteristics. The correlation analysis results are compared with findings from similar studies performed in other climatic conditions.
Keywords: satellite data, correlation analysis, Spearman’s correlation coefficient, Kruskal-Wallis method, soil organic carbon content and carbon stocks, C:N ratio
Full text

References:

  1. Akkumulyatsiya ugleroda v lesnykh pochvakh i suktsessionnyi status lesov (Carbon accumulation in forest soils and the successive status of forests), N. V. Lukina (ed.), Moscow: Tovarishchestvo nauchnykh izdanii KMK, 2018, 232 p. (in Russian).
  2. Bakhmet O. N., Carbon deposits in soils of pine and spruce forests of Karelia, Contemporary Problems of Ecology, 2018, Vol. 11, No. 7, pp. 697–703, DOI: 10.1134/S199542551807003X.
  3. Bakhmet O. N., Fedorets N. G., Kryshen’ A. M., Investigations within the international program ICP Forests in Karelia, Trudy Karelskogo nauchnogo tsentra, 2011, No. 2, pp. 133–139 (in Russian).
  4. Bienkovski P., Titlyanova A. A., Shibareva C. V., Transformation processes in the litter of boreal forests, Sibirskii ekologicheskii zhurnal, 2003, No. 6, pp. 707–712 (in Russian).
  5. Volkov A. D., Tipy lesa Karelii (Forest types of Karelia), Petrozavodsk: Karelian Research Center RAS, 2008, 192 p. (in Russian).
  6. Gavrilyuk E. A., Kuznetsova A. I., Gornov A. V., Geospatial modeling of nitrogen and carbon content and stock in the forest litter horizons based on Sentinel-2 multi-seasonal satellite imagery, Eurasian Soil Science, 2021, Vol. 54, No. 2, pp. 176–188, DOI: 10.1134/S1064229321020046.
  7. Gopp N. V., Meshalkina Yu. V., Narykova A. N. et al., Mapping of soil organic carbon content and stock at the regional and local levels: the analysis of modern methodological approaches, Forest Science Issues, 2023, Vol. 6, No. 1, Article 120, 59 p. (in Russian), DOI 10.31509/2658-607x-202361-120.
  8. Doronina A. Yu., Sosudistye rasteniya Karel’skogo peresheika (Leningradskaya oblast’) (Vascular plants of Karelian Isthmus (Leningrad region)), Moscow: Tovarishchestvo nauchnykh izdanii KMK, 2007, 574 p. (in Russian).
  9. Zmirtovich I. V., Middle taiga of the Karelian Isthmus: zonal, intrazonal and extrazonal phenomena, Vestnik ekologii, lesovedeniya i landshaftovedeniya, 2011, No. 12, pp. 54–76 (in Russian).
  10. Ivanova E. A., Danilova M. A., Smirnov V. E., Ershov V. V., Comparative assessment of the rate of decomposition of plant litter in spruce and pine forests at the northern limit of distribution, Forest Science Issues, 2023, Vol. 6, No. 3, Article 132, (in Russian), DOI: 10.31509/2658-607x-202363-132.
  11. Kuznetsova A. I., Influence of vegetation on soil carbon stocks in forests (review), Forest Science Issues, 2021, Vol. 4, No. 4, pp. 41–54 (in Russian), DOI: 10.31509/2658-607x-2021-44-95.
  12. Kuznetsova A. I., Lukina N. V., Gornov A. V. et al., Carbon stock in sandy soils of pine forests in the west of Russia, Eurasian Soil Science, 2020, Vol. 53, No. 8, pp. 1056–1065, DOI: 10.1134/S1064229320080104.
  13. Lukina N. V., Kuznetsova A. I., Geras’kina A. P. et al., Unaccounted factors determining carbon stocks in forest soils, Meteorologiya i gidrologiya, 2022, No. 10, pp. 92–110 (in Russian), DOI: 10.52002/0130-2906-2022-10-92-110.
  14. Morozova R. M., Geographic patterns of soil cover formation in Karelia, Trudy Karelskogo nauchnogo tsentra RAN. Biogeografiya Karelii. Ser. Biologiya, 2012, No. 2, pp. 12–18 (in Russian).
  15. Nazarova L. E., Climate of the Republic of Karelia (Russia): air temperature, variability and changes, Geopolitika i ekogeodinamika regionov, 2014, Vol. 10, No. 1, pp. 746–749 (in Russian).
  16. Narykova A. N., Plotnikova A. S., The geospatial modeling results of carbon stocks in the forest litter of the Republic of Karelia and the Karelian Isthmus, Regional’nye problemy distantsionnogo zondirovaniya Zemli: materialy 10-i Mezhdunarodnoi nauchnoi konferentsii (Regional problems of remote sensing of the Earth: Proc. 10th Intern. Scientific Conf.), Krasnoyarsk: SFU, 2023, pp. 115–119 (in Russian).
  17. Perelman A. I., Geokhimiya landshafta (Landscape geochemistry), Moscow, 1975, 341 p. (in Russian).
  18. Pesyakova A. A., Feklistov P. A., The structure and stock of forest litter in pine forests of the northern taiga, Vestnik KrasGAU, 2017, No. 4, pp. 182–186 (in Russian).
  19. Polynov B. B., Geokhimicheskie landshafty (Geochemical landscapes), Moscow: Izd. AN SSSR, 1956, 751 p. (in Russian).
  20. Polyakova E. V., Kutinov Yu. G., Mineev A. L., Chistova Z. B., Analysis of the applicability of the ASTER GDEM v2 and ArcticDEM digital elevation models in research on Russia’s Arctic territories, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 7, pp. 117–127 (in Russian), DOI: 10.21046/2070-7401-2020-17-7-117-127.
  21. Pochvovedenie (Soil science), V. A. Kovda, B. G. Rozanov (eds.), Moscow: Vysshaya shkola, 1988, 400 p. (in Russian).
  22. Rozhkova A. N., The role of snow cover in the biochemical nitrogen cycle, Mezhdunarodnaya nauchno-prakticheskaya konferentsiya “Sovremennye tendentsii v nauchnom obespechenii agropromyshlennogo kompleksa” (Proc. Intern. Scientific and Practical Conf. “Modern trends in scientific support of the agro-industrial complex”), 2020, pp. 58–61 (in Russian).
  23. Ryzhova I. M., Podvezennaya M. A., Kirillova N. P., A comparative statistical analysis of the variability of carbon stock in automorphous and semihydromorphous soils of forest ecosystems in European Russia, Vestnik Moskovskogo universiteta. Seriya 17: Pochvovedenie, 2022, No. 2, pp. 20–27 (in Russian).
  24. Sin’kevich S. M., Bakhmet O. N., Ivanchikov A. A., The role of soils in the regional carbon balance in the pine forests of Karelia, Eurasian Soil Science, 2009, Vol. 42, No. 3, pp. 267–276, DOI: 10.1134/S106422930903003X.
  25. Sokhranenie tsennykh prirodnykh territorii Severo-Zapada Rossii. Analiz reprezentativnosti seti OOPT Arkhangel’skoi, Vologodskoi, Leningradskoi i Murmanskoi oblastei, Respubliki Karelii, Sankt-Peterburga (Mapping of High Conservation Value Areas in Northwestern Russia: Gap-Analysis of the Protected Areas Network in the Murmansk, Leningrad, Arkhangelsk, Vologda, and Karelia regions, and the city of Saint Petersburg), K. N. Kobyakova (ed.), Saint Petersburg, 2011, 506 p. (in Russian).
  26. Chernova O. V., Ryzhova I. M., Podvezennaya M. A., Assessment of Organic Carbon Pools in Forest Soils on a Regional Scale, Pochvovedenie, 2020, No. 3, pp. 340–350 (in Russian), DOI: 10.31857/S0032180X20030028.
  27. Chernova O. V., Golozubo O. M., Alyabina I. O., Shepashchenko D. G., Integrated Approach to Spatial Assessment of Soil Organic Carbon in Russian Federation, Eurasian Soil Science, 2021, Vol. 54, No. 3, pp. 325–336, DOI: 10.1134/S1064229321030042.
  28. Chestnykh O. V., Zamolodchikov D. G., Pochvennye kharakteristiki Severnoi Evrazii (Soil characteristics of Northern Eurasia), Certificate of state registration of data base No. 2018621164 (RU), Reg. 17.05.2018 (in Russian).
  29. Chestnykh O. V., Lyzhin V. A., Koksharova A. V., The carbon reserves in litters of forests in Russia, Lesovedenie, 2007, No. 6, pp. 114–121 (in Russian).
  30. Shary P. A., Sharaya L. S., Pastukhov A. V., Kaverin D. A., Spatial distribution of organic carbon in soils of Eastern European tundra and forest-tundra depending on climate and topography, Izvestiya RAN. Seriya Geograficheskaya, 2018, No. 5, pp. 39–48 (in Russian), DOI: 10.1134/S2587556618060146.
  31. Schepaschenko D. G., Shvidenko A. Z., Mukhortova L. V., Vedrova E. F., The pool of organic carbon in the soils of Russia, Eurasian Soil Science, 2013, Vol. 46, No. 2, pp. 107–116, DOI: 10.1134/S1064229313020129.
  32. Callesen I., Liski J., Raulund-Rasmussen K. et al., Soil carbon stores in Nordic well-drained forest soils — relationships with climate and texture class, Global Change Biology, 2003, Vol. 9, Issue 3, pp. 358–370, DOI: 10.1046/j.1365-2486.2003.00587.x.
  33. Duarte E., Zagal E., Barrera J. et al., Digital mapping of soil organic carbon stocks in the forest lands of Dominican Republic, European J. Remote Sensing, 2022, Vol. 55, No. 1, pp. 213–231, DOI: 10.1080/22797254.2022.2045226.
  34. Frank D. A., Pontes A. W., McFarlane K. J., Controls on soil organic carbon stocks and turnover among North American ecosystems, Ecosystems, 2012, Vol. 15, Issue 4, pp. 604–615, DOI: 10.1007/s10021-012-9534-2.
  35. Gomes L., Faria R., de Souza E. et al., Modelling and mapping soil organic carbon stocks in Brazil, Geoderma, 2019, Vol. 340, pp. 337–350, DOI: 10.1016/j.geoderma.2019.01.007.
  36. Gu J., Bol R., Sun Y., Zhang H., Soil carbon quantity and form are controlled predominantly by mean annual temperature along 4000 km North-South transect of Eastern China, Catena, 2022, Vol. 217, Issue 1–2, DOI: 10.1016/j.catena.2022.106498.
  37. Guo P.-T., Li M.-F., Luo W., Tang Q.-F., Liu Z.-W., Lin Z.-M., Digital mapping of soil organic matter for rubber plantation at regional scale: An application of random forest plus residuals kriging approach, Geoderma, 2015, Vol. 237–238, pp. 49–59, DOI: 10.1016/j.geoderma.2014.08.009.
  38. Hall D. K., Riggs G. A., Salomonson V. V., MODIS/Terra Snow Cover 5-Min L2 Swath 500 m, NASA National Snow and Ice Data Center Distributed Active Archive Center, 2006, https://nsidc.org/data/modis/data_summaries.
  39. Hateffard F., Dolati P., Heidari A., Zolfaghari A., Assessing the performance of decision tree and neural network models in mapping soil properties, J. Mountain Science, 2019, Vol. 16, Issue 8, pp. 1833–1847, DOI: 10.1007/s11629-019-5409-8.
  40. Hijmans R. J., Cameron S. E., Parra J. L. et al., Very High Resolution Interpolated Climate Surfaces for Global Land Areas, Intern. J. Climatology, 2005, Vol. 25, pp. 1965–1978, DOI: 10.1002/joc.1276.
  41. Hounkpatin K., Stendahl J., Lundblad M., Karltun E., Predicting the spatial distribution of soil organic carbon stock in Swedish forests using a group of covariates and site-specific data, Soil, 2021, Vol. 7, Issue 2, pp. 377–398, DOI: 10.5194/soil-7-377-2021.
  42. Kruskal W. H., Wallis W. A., Use of ranks in one-criterion variance analysis, J. American Statistical Association, 1952, Vol. 47, No. 260, pp. 583–621.
  43. Landolt E., Baumler B., Erhardt A. et al., Flora indicativa — Okologische Zeigerwerte und biologische Kennzeichen zur Flora der Schweiz und der Alpen, 2010, 378 p., DOI: 10.2307/27896667.
  44. McBratney A. B., Santos M. L., Minasny B., On digital soil mapping, Geoderma, 2003, Vol. 117, Issues 1–2, pp. 3–52, DOI: 10.1016/S0016-7061(03)00223-4.
  45. Porter C., Morin P., Howat I. et al., ArcticDEM, Version 3, Harvard Dataverse, 2018, Vol. 1, DOI: 10.7910/DVN/OHHUKH.
  46. Spearman C., The proof and measurement of association between two things, American J. Psychology, 1904, Vol. 15, Issue 1, pp. 72–101, DOI: 10.2307/1412159.
  47. Strand L. T., Callesen I., Dalsgaard L., Wit H. A., Carbon and nitrogen stocks in Norwegian forest soils — The importance of soil formation, climate, and vegetation type for organic matter accumulation, Canadian J. Forest Research, 2016, Vol. 46, pp. 1–15, DOI: 10.1139/cjfr-2015-0467.
  48. Venter Z., Hawkins H., Cramer M., Mills A., Mapping soil organic carbon stocks and trends with satellite-driven high resolution maps over South Africa, Science of the Total Environment, 2021, Vol. 771, pp. 1–14, DOI: 10.1016/j.scitotenv.2021.145384.
  49. Wang B., Waters C., Orgill S. et al., High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia, Science of the Total Environment, 2018, Vol. 630, pp. 367–378, DOI: 10.1016/j.scitotenv.2018.02.204.
  50. Wang S., Xu L., Zhuang Q., He N., Investigating the spatio-temporal variability of soil organic carbon stocks in different ecosystems of China, Science of the Total Environment, 2021, Vol. 758, pp. 1–10, DOI: 10.1016/j.scitotenv.2020.143644.
  51. Wiesmeier M., Urbanski L., Hobley E. et al., Soil organic carbon storage as a key function of soils — A review of drivers and indicators at various scales, Geoderma, 2019, Vol. 333, pp. 149–162, DOI: 10.1016/j.geoderma.2018.07.026.
  52. Wipf S., Stoeckli V., Bebi P., Winter climate change in alpine tundra: plant responses to changes in snow depth and snowmelt timing, Climatic Change, 2009, Vol. 94, pp. 105–121, DOI: 10.1007/s10584-009-9546-x.
  53. Zhang Z., Zhang H., Xu E., Enhancing the digital mapping accuracy of farmland soil organic carbon in arid areas using agricultural land use history, J. Cleaner Production, 2022, Vol. 334, pp. 1–11, DOI: 10.1016/j.jclepro.2021.130232.
  54. Zhou T., Geng Y., Ji C. et al., Prediction of soil organic carbon and the C:N ratio on a national scale using machine learning and satellite data: A comparison between Sentinel-2, Sentinel-3 and Landsat-8 images, Science of the Total Environment, 2021, Vol. 755, pp. 1–16, DOI: 10.1016/j.scitotenv.2020.14266.