Vol. 39, issue 03, article # 11

Skorokhodov A. V., Zhuravleva T. B. Photosynthetic activity of various vegetation types in southern Western Siberia and its relationship with environmental parameters based on reanalysis and satellite data. // Optika Atmosfery i Okeana. 2026. V. 39. No. 03. P. 266–276. DOI: 10.15372/AOO20260311 [in Russian].
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Abstract:

Solar-induced fluorescence is an indicator of plant photosynthetic activity that shows promise for monitoring ecosystem productivity on a global scale. The paper presents estimates of the photosynthetic activity for the main phytocenoses of southern Western Siberia (grasslands, deciduous and light coniferous forests, croplands and wetlands) based on TROPOMI satellite data for the period 2018–2024. Using ERA5-Land reanalysis data and products obtained from MODIS and CERES sensor measurements, we investigated the correlations between solar-induced fluorescence and key environmental temperature and moisture parameters, vegetation indices, and photosynthetically active radiation, as well as directly between these features themselves (spatial resolution – 0.05°, temporal resolution – 1 month). The presented results describe the specifics of these relationships both for the main phytocenoses of the entire target region and their latitudinal variability for grasslands and deciduous forests.

Keywords:

solar-induced fluorescence, temperature-moisture parameters, vegetation index, photosynthetically active radiation, correlation analysis, TROPOMI, ERA5-Land, MODIS, CERES

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References:

1. IPCC: Summary for policymakers // Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press, 2021. P. 1–41.
2. Fedorov B.G. Vybrosy uglekislogo gaza: uglerodnyi balans Rossii // Problemy prognozirovaniya. 2014. N 1. P. 63–77.
3. Monitoring potokov parnikovykh gazov v prirodnykh ekosistemakh // pod red. D.G. Zamolodchikova, D.V. Karelina, M.L. Gitarskogo, V.G. Blinova. Saratov: Amirit, 2017. 280 p.
4. Otsenka potokov parnikovykh gazov v ekosistemakh regionov Rossiiskoi Federatsii // otv. red. A.A. Romanovskaya. M.: IGKE, Print, 2023. 343 p.
5. Glagolev M.V. K metodu «obratnoi zadachi» dlya opredeleniya poverkhnostnoi plotnosti potoka gaza iz pochvy // Dinamika okruzhayushchei sredy i global'nye izmeneniya klimata. 2010. V. 1, N 1. P. 17–36.
6. Nicolini G., Fratini G., Avilov V., Kurbatova J.A., Vasenev I., Valentini R. Performance of eddy-covariance measurements in fetch-limited applications // Theor. Appl. Climatol. 2015. V. 127. P. 829–840. DOI: 10.1007/s00704-015-1673-x.
7. Burba G.G., Kurbatova Yu.A., Kuricheva O.A., Avilov V.K., Mamkin V.V. Metod turbulentnykh pul'satsii: Kratkoe prakticheskoe rukovodstvo. M.: IPEE im. A.N. Severtsova RAN, 2016. 223 p.
8. Korneev D.Yu. Informatsionnye vozmozhnosti metoda induktsii fluorestsentsii khlorofilla. Kiev: Al'terpres, 2002. 188 p.
9. Baldocchi D.D., Falge E., Gu L., Olson R., Hollinger D.Y., Running S.W., Anthoni P., Bernhofer Ch., Davis K.J., Evans R., Fuentes J., Goldstein A., Katul G., Law B.E., Lee X., Malhi Y., Meyers T.P., Munger J.W., Oechel W.C., Paw U.K.T., Pilegaard K., Schmid H.P., Valentini R., Verma S., Vesala T., Wilson K.B., Wofsy S.C. FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities // Bull. Am. Meteorol. Soc. 2001. V. 82. P. 2415–2434. DOI: 10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2.
10. Kuricheva O.A., Avilov V.K., Varlagin A.V., Gitarskii M.L., Dmitrichenko A.A., Dyukarev E.A., Zagirova S.V., Zamolodchikov D.G., Zyryanov V.I., Karelin D.V., Karsanaev S.V., Kurganova I.N., Lapshina E.D., Maksimov A.P., Maksimov T.X., Mamkin V.V., Marunich A.S., Miglovets M.N., Mikhailov O.A., Panov A.V., Prokushkin A.S., Sidenko N.V., Shilkin A.V., Kurbatova Yu.A. Monitoring ekosistemnykh potokov parnikovykh gazov na territorii Rossii: set' RuFlux // Izv. RAN. Ser. Geograficheskaya. 2023. V. 87, N 4. P. 512–535. DOI: 10.31857/S2587556623040052.
11. Frankenberg C., Berry J. Solar-induced chlorophyll fluorescence: Origins, relation to photosynthesis and retrieval // Comp. Remote Sens. 2018. V. 3. P. 143–162. DOI: 10.1016/B978-0-12-409548-9.10632-3.
12. Köehler P., Frankenberg C., Magney T.S., Guanter L., Joiner J., Landgraf J. Global retrievals of solar induced chlorophyll fluorescence with TROPOMI: First results and intersensor comparisomn to OCO-2 // Geophys. Res. Lett. 2018. V. 5. P. 10546–10463. DOI: 10.1029/2018GL079031.
13. Duveiller G., Filipponi F., Walther S., Köhler P., Frankenberg C., Guanter L., Cescatti A. A spatially downscaled sun-induced fluorescence global product for enhanced monitoring of vegetation productivity // Earth Syst. Sci. Data. 2020. V. 12. P. 1101–1116. DOI: 10.5194/essd-12-1101-2020.
14. Li X., Xiao J. TROPOMI observations allow for robust exploration of the relationship between solar-induced chlorophyll fluorescence and terrestrial gross primary production // Remote Sens. Environ. 2022. V. 268. Art. 112748. DOI: 10.1016/j.rse.2021.112748.
15. Anav A., Friedlingstein P., Beer C., Ciais Ph., Harper A., Jones Ch., Murray-Tortarolo G., Papale D., Parazoo N.C., Peylin Ph., Piao S., Sitch S., Viovy N., Wiltshire A., Zhao M. Spatiotemporal patterns of terrestrial gross primary production: A review // Rev. Geophys. 2015. V. 53, N 3. P. 785–818. DOI: 10.1002/2015RG000483.
16. Li X., Xiao J., He B. Chlorophyll fluorescence observed by OCO-2 is strongly related to gross primary productivity estimated from flux towers in temperate forests // Remote Sens. of Environ. 2018. V. 204. P. 659–671. DOI: 10.1016/j.rse.2017.09.034.
17. Wang M., Zhang L. Synchronous changes of GPP and solar-induced chlorophyll fluorescence in a subtropical evergreen coniferous forest // Plants. 2023. V. 12, N 11. Art. 2224. DOI: 10.3390/plants12112224.
18. Turner A.J., Köhler P., Magney T.S., Frankenberg C., Fung I., Cohen R.C. Extreme events driving year-to-year differences in gross primary productivity across the US // Biogeosciences. 2021. V. 18. P. 6579–6588. DOI: 10.5194/bg-18-6579-2021.
19. Wang Y., Liu J., Wennberg P.L., He L., Bonal D., Köhler P., Frankenberg C., Sitch S.P., Friedlingstein P. Elucidating climatic drivers of photosynthesis by tropical forests // Global Change Biology. 2023. V. 29, N 17. P. 4811–4825. DOI: 10.1111/gcb.16837.
20. Kim J.E, Wang J.A., Li Y., Czimczik C.I., Randerson J.T. Wildfire-induced increases in photosynthesis in boreal forest ecosystems of North America // Glob. Chang. Biol. 2024. V. 30, N 1. DOI: 10.1111/gcb.17151.
21. Guanter L., Bacour C., Schneider A., Aben I., van Kempen T.A., Maignan F., Retscher C., Köhler P., Frankenberg C., Joiner J., Zhang Y. The TROPOSIF global sun-induced fluorescence dataset from the Sentinel-5P TROPOMI mission // Earth Syst. Sci. Data. 2021. V. 13. P. 5423–5440. DOI: 10.5194/essd-13-5423-202.
22. Muñoz-Sabater J., Dutra E., Agustí-Panareda A., Albergel C., Arduini G., Balsamo G., Boussetta S., Choulga M., Harrigan S., Hersbach H., Martens B., Miralles D.G., Piles M., Rodríguez-Fernández N.J., Zsoter E., Buontempo C., Thépaut J.-N. ERA5-Land: A state-of-the-art global reanalysis dataset for land applications // Earth Syst. Sci. Data. 2021. V. 13. P. 4349–4383. DOI: 10.5194/essd-13-4349-2021.
23. VEGA-Science: Unikal'nyi instrument nauchnogo analiza dannykh sputnikovykh nablyudenii. URL: http://sci-vega.ru (data obrashcheniya: 25.04.2025).
24. Santoro M., Kirches G., Wevers J., Boettcher M., Brockmann C., Lamarche C. Land cover CCI. Productuser Guide. Version 2. Belgium: UCL-Geomatics, 2012. 105 p.
25. Li X., Xiao Global J.A. 0.05-Degree product of solar-induced chlorophyll fluorescence derived from OCO-2, MODIS, and reanalysis data // Remote Sens. 2019. V. 11. P. 517. DOI: 10.3390/rs11050517.
26. WMO-LCDNV. URL: https://wmolcdnv.ecmwf.int (last access: 01.09.2025).
27. Liu R., Zhang X., Wang W., Wang Y., Liu H., Ma M., Tang G. Global-scale ERA5 product precipitation and temperature evaluation // Ecol. Indic. 2024. V. 166, N 112481. DOI: 10.1016/j.ecolind.2024.112481.
28. Chen X., Su Z., Ma Y., Cleverly J., Liddell M. An accurate estimate of monthly mean land surface temperatures from MODIS clear-sky retrievals // J. Hydrometeor. 2017. V. 18. P. 2827–2847. DOI: 10.1175/JHM-D-17-0009.1.
29. MODIS Land. Status for: Vegetation Indices (MOD13). URL: https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MOD13 (last access: 25.04.2025).
30. Pu J., Yan K., Roy S., Zhu Z., Rautiainen M., Knyazikhin Y., Myneni R.B. Sensor-independent LAI/FPAR CDR: Reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022 // Earth Syst. Sci. Data. 2024. V. 16. P. 15–34. DOI: 10.5194/essd-16-15-2024.
31. Rutan D.A., Kato S., Doelling D.R., Rose F.G., Nguyen L.T., Caldwell T.E., Loeb N.G. CERES synoptic product: Methodology and validation of surface radiant flux // J. Atmos. Ocean. Technol. 2017. V. 32. P. 1121–1143. DOI: 10.1175/JTECH-D-14-00165.1.
32. QA4SM – Quality Assurance Service for Satellite Soil Moisture Data. URL: https://qa4sm.eu/ui/ home (last access: 25.04.2015).
33. OGIMET: Professional information about meteorological conditions in the world. URL: http://www.ogimet.com/home.phtml.en (last access: 25.04.2025).
34. Bai G., Lerebourg C., Clerici M., Gobron N., Muller J.-P., Song R., Dash J., Brown L., Morris H., Lopez-Baeza E., Albero E., Ghent D., Dodd E. GBOV (Ground-Based Observation for Validation): A Copernicus service for validation of land products // IEEE International Geoscience and Remote Sensing Symposium. Malaysia, Kuala Lumpur: IEEE, 2022. P. 4304–4307. DOI: 10.1109/IGARSS46834.2022.9883162.
35. Augustine J.A., De Luisi J.J., Long C.N. SURFRAD – A national surface radiation budget network for atmospheric research // Bull. Am. Meterol. Soc. 2000. V. 81, N 10. P. 2341–2358. DOI: 10.1175/1520-0477(2000) 081<2341:SANSRB>2.3.CO;2.
36. Dorigo W.A., Wagner W., Hohensinn R., Hahn S., Paulik C., Xaver A., Gruber A., Drusch M., Mecklenburg S., van Oevelen P., Robock A., Jackson T. The International Soil Moisture Network: A data hosting facility for global in situ soil moisture measurements // Hydrol. Earth Syst. Sci. 2011. V. 15. P. 1675–698. DOI: 10.5194/hess-15-1675-2011.
37. Kuzhevskaya I.V., Gorbatenko V.P., Nosyreva O.V., Volkova M.A., Nechepurenko O.E., Chursin V.V., Chered'ko N.N. Agroklimaticheskie kharakteristiki zemel' sel'skokhozyaistvennogo naznacheniya na territorii Sibirskogo Federal'nogo okruga v usloviyakh izmeneniya klimata // Meteorol. i gidrol. 2023. N 10. P. 77–87. DOI: 10.52002/0130-2906-2023-10-77-87.
38. Abramova O.F., Ivanov A.E., Inkin A.N. Obzor algoritmov masshtabirovaniya rastrovoi grafiki // European Student Sci. J. 2016. N 2. P. 1–6.
39. Shekhar A., Chen J., Bhattacharjee S., Buras A., Castro A., Zang C., Rammig A. Capturing the impact of the 2018 European drought and heat across different vegetation types using OCO-2 solar-induced fluorescence // Remote Sens. 2020. V. 12, N 19. DOI: 10.3390/rs12193249.
40. Song A., Liang S., Li H., Yan B. Effects of biodiversity on functional stability of freshwater wetlands: A systematic review // Front. Microbiol. 2024. V. 15. DOI: 10.3389/fmicb.2024.1397683.
41. Kooistra L., Clevers J. Estimating potato leaf chlorophyll content using ratio vegetation indices // Remote Sens. Lett. 2016. V. 7, N 6. P. 611–620. DOI: 10.1080/2150704X.2016.1171925.
42. Liu J., Wennberg P.O., Parazoo N.C., Yin Y., Frankenberg C. Observational constraints on the response of high-latitude northern forests to warming // AGU Advances. 2020. V. 1, N 4. Art. e2020AV000228. DOI: 10.1029/2020AV000228.
43. Bachofen C., Poyatos R., Flo V., Martínez-Vilalta J., Mencuccini M., Granda V., Grossiord C. Stand structure of Central European forests matters more than climate for transpiration sensitivity to VPD // J. Appl. Ecol. 2023. V. 60. P. 886–897. DOI: 10.1111/1365-2664.14383.
44. Kopecký M., Hederová L., Macek M., Klinerová T., Wild J. Forest plant indicator values for moisture reflect atmospheric vapour pressure deficit rather than soil water content // New Phytol. 2024. V. 244. P. 1801–1811. DOI: 10.1111/nph.20068.
45. Otieno D., Lindner S., Muhr J., Broken W. Sensitivity of peatland herbaceous vegetation to vapor pressure deficit influences net ecosystem CO2 exchange // Wetlands. 2012. V. 32. P. 895–905. DOI: 10.1007/s13157-012-0322-8.
46. Horel A., Zsigmond T., Farkas C., Gelybó G., Tóth E., Kern A., Bakacsi Z. Climate change alters soil water dynamics under different land use types // Sustainability. 2022. V. 14, N 3908. DOI: 10.3390/su14073908.
47. Arkhangel'skaya T.A. Temperaturnyi rezhim kompleksnogo pochvennogo pokrova. M.: GEOS, 2012. 282 p.
48. Rahimi E., Dong P., Jung C. How do climate and latitude shape global tree canopy structure? // Forests. 2025. V. 16. Art. 432. DOI: 10.3390/f16030432.
49. Karta rastitel'nosti SSSR (dlya vysshikh uchebnykh zavedenii). Masshtab 1:4000000. M.: GUGK, 1990.
50. Informatsionnaya sistema «Pochvenno-geograficheskaya baza dannykh Rossii». URL: https://soil-db.ru (data obrashcheniya: 25.04.2025).