Ecology and Resilient Infrastructure

Korean Society of Ecology and Infrastructure Engineering (응용생태공학회)
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Analysis of Phenological Changes by Phenocams on Some Major Species Distributed in Wetland and Forest Ecosystems in Korea

Phenocam을 활용한 국내 습지 및 산림생태계 대표 수종의 계절적 변화 분석

  • Minki Hong (Ecological Observation Team on Climate Change, National Institute of Ecology) ;
  • Hyohyemi Lee (Ecological Observation Team on Climate Change, National Institute of Ecology) ;
  • Jeong-Soo Park (Ecological Observation Team on Climate Change, National Institute of Ecology)
  • 홍민기 (국립생태원 기후생태관측팀) ;
  • 이효혜미 (국립생태원 기후생태관측팀) ;
  • 박정수 (국립생태원 기후생태관측팀)
  • Received : 2023.11.29
  • Accepted : 2023.12.18
  • Published : 2023.12.31
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Abstract

As climate change intensifies, the importance of studying plant phenology has increased, leading to a surge in research employing automated video recording devices like Phenocams. In this study, using the Phenocams operated by the National Institute of Ecology, we examined the trends in plant phenological changes across diverse ecosystem types in South Korea and analyzed their correlations with climate factors. The patterns of plant phenological changes varied by region and tree species. Pinus thunbergii and Pinus densiflora typically show an overall increase in their growth period, positively correlating with temperatures and precipitation during winter. However, uniquely, for Abies koreana on Hallasan Mt., a higher amount of precipitation in August leads to an earlier end of season (eos), and the correlation analysis with the recent phenomenon of dying A. Koreana seems necessary. beyond the analysis, solutions for handling missing data issues during the data collection process were proposed. Furthermore, to expand future research scope and encompass diverse ecosystem types, a suggestion to combine Phenocam research with satellite observations was presented.

기후변화가 심화됨에 따라 식물계절연구의 중요도가 증가하고 있으며 자동영상촬영장치 (피노캠, Phenocam)을 활용한 연구방법이 급부상하고 있다. 본 연구에서는 국립생태원에서 운영하는 피노캠을 활용하여 국내 주요 생태계 유형에 대한 식물계절 변화의 경향을 확인하고 기후요인과의 상관관계를 분석했다. 식물계절의 변화 양상은 지역 및 수종별로 다르게 나타났다. 곰솔 및 소나무림은 전체 생장 기간이 증가하는 경향을 보이며 주로 겨울철 기온과 강수량과 양의 상관관계를 보였으나, 한라산 구상나무는 8월 강수량이 많을수록 생장종료일이 빨라졌으며 최근 발생하는 구상나무 고사 현상과의 연관성 분석이 추후 필요할 것으로 보인다. 분석 결과에서 더 나아가 데이터 수집 과정에서 발생할 수 있는 결측치 문제 등에 대한 해결책을 제시하였으며, 향후 연구 범위를 확장하고 다양한 생태계 유형을 반영하기 위해 피노캠 연구와 위성 관측을 결합하는 방안을 제안하였다.

Keywords

Acknowledgement

본 연구는 국립생태원 "2023년 국가 장기생태연구 (NIE-고유연구(B)-2023-02)" 의 연구비 지원 하에 수행되었습니다.

References

  1. Ahn, U.S., Kim, D.S., Yun, Y.S., Ko, S.H., Kim, K.S. and Cho, I.S. 2019. The inference about the cause of death of Korean Fir in Mt. Halla through the analysis of spatial dying pattern - Proposing the possibility of excess soil moisture by climate changes -. Korean Journal of Agricultural and Forest Meteorology 21(1): 1-28. 
  2. Aono, Y. and Kazui, K. 2008. Phenological data series of cherry tree flowering in Kyoto, Japan, and its application to reconstruction of springtime temperatures since the 9th century. International Journal of Climatology 28: 905-914.  https://doi.org/10.1002/joc.1594
  3. Asse, D., Chuine, I., Vitasse, Y., Yoccoz, N.G., Delpierre, N., Badeau, V., Delestrade, A., and Randin, C.F. 2018. Warmer winters reduce the advance of tree spring phenology induced by warmer springs in the Alps. Agricultural and Forest Meteorology 252: 220-230.  https://doi.org/10.1016/j.agrformet.2018.01.030
  4. Brown, T.B., Hultine, K.R., Steltzer, H., Denny, E.G., Denslow, M.W., Granados, J., Henderson, S., Moore, D., Nagai, S., SanClement, M., Sanchez-Azofeifa, A., Sonnentag, O., Tazik, D., and Richardson, A.D. 2016. Using phenocams to monitor our changing Earth: toward a global phenocam network. Front Ecol Envrion 14(2): 84-93.  https://doi.org/10.1002/fee.1222
  5. Burke, M.W.V. and Rundquist, B.C. 2021. Scaling Phenocam GCC, NDVI, and EVI2 with Harmonized LandsatSentinel using Gaussian Processes. Agricultural and Forest Meteorology 300: 108316. 
  6. Cui, T., Martz, L., Lamb, E.G., Zhao, L., and Guo, X. 2019. Comparison of Grassland Phenology Derived from MODIS Satellite and PhenoCam Near-Surface Remote Sensing in North America. Canadian Journal of Remote Sensing 45(5): 707-722.  https://doi.org/10.1080/07038992.2019.1674643
  7. Duchenne, F., Thebault, E., Michez, D., Elias, M., Drake, M., Persson, M., Rousseau-Piot, J.S., Pollet, M., Vanor melingen, P., and Fontaine, C. 2020. Phenological shifts alter the seasonal structure of pollinator assemblages in Europe. Nature Ecology & Evolution 4: 115-121. 
  8. Estiarte, M. and Penuelas, J. 2015. Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency. Global Change Biology 21: 1005-1017.  https://doi.org/10.1111/gcb.12804
  9. Filippa, G., Cremonese, E., Migliavacca, M., Galvagno, M., Forkel, M., Wingate, L., Tomelleri, E., Morra di Cella, U., and Richardson, A.D. 2016a. Phenopix: A R package for image-based vegetation phenology. Agricultural and Forest Meteorology 220: 141-150.  https://doi.org/10.1016/j.agrformet.2016.01.006
  10. Filippa, G., Cremonese, E., Migliavacca, M., Richardson, A., Galvagno, M., and Forkel, M. 2016b. Phenopix: pixel based phenology.
  11. Gibson, D., Blomberg, E.J., and Sedinger, J.S. 2016. Evaluating vegetation effects on animal demographics: the role of plant phenology and sampling bias. Ecology and Evolution 6(11): 3621-3631.  https://doi.org/10.1002/ece3.2148
  12. Gordo, O. and Sanz, J.J. 2005. Phenology and climate change: a long-term study in a Mediterranean locality. Oecologia 146:484-495.  https://doi.org/10.1007/s00442-005-0240-z
  13. Han, S.H., Yun, C.W., and Lee, S. 2020. Phenophase Extraction from Repeat Digital Photography in the Northern Temperate Type Deciduous Broadleaf Forest. Journal of Korean Society of Forest Science 109(4): 361-370. 
  14. Khare, S., Deslauriers, A., Morin, H., Latifi, H., and Rossi, S. 2022. Comparing Time-Lapse PhenoCams with Satellite Observations across the Boreal Forest of Quebec, Canada. Remote Sensing 14(1): 100. 
  15. Kim, H., Hong, J., Kim, S.C., Oh, S.H., and Kim, J. 2011. Plant Phenology of Threatened species for Climate change in Sub-alpine zone of Korea - Especially on the Summit Area of Mt. Deogyusan -. Korean J. Plant Res. 24(5): 549-556.  https://doi.org/10.7732/kjpr.2011.24.5.549
  16. Klost erman, S.T., Hufkens, K., Gray, J.M., Melaas, E., Sonnentag, O., Lavine, I., Mitchell, L., Norman, R., Friedl, M.A., and Richardson, A.D. 2014. Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery. Biogeosciences 11: 4305-4320.  https://doi.org/10.5194/bg-11-4305-2014
  17. Kramer, K., Leinonen, I., and Loustau, D. 2000. The importance of phenology for the evaluation of impact of climate change on growth of boreal, temperate and Mediterranean forests ecosystems: an overview. Int J Biometeorol 44: 67-75.  https://doi.org/10.1007/s004840000066
  18. National Institute of Ecology. 2022. Monitoring ecosystem response to climate change. National institute of Ecology. Seocheon, Korea. p. 452. (In Korean) 
  19. O'Leary, D.S., Kellermann, J.L., and Wayne, C. 2018. Snowmelt timing, phenology, and growing season length in conifer forests of Crater Lake National Park, USA. Int J Biometeorol 62: 273-285.  https://doi.org/10.1007/s00484-017-1449-3
  20. Oh, M., Kim, J., Lee, B., and Kim, T. 2022. Hydrometeorological Characteristics in Season and Solar Term According to RCP Climate Change Scenarios. Journal of Wetlands Research 24(4): p288-300. 
  21. Park, E., Lee, N., Kim, M., and Park, H.C. 2019. A Study on the Phenology of Quercus mongolica Using Vegetation Indices in Korea National Park. Proc. Korean Soc. Environ. Ecol. Con. 29(2), 195. 
  22. Piao, S., Liu, Q., Chen, A., Janssens, I.A., Fu, Y., Dai, J., Liu, L., Lian, X., Shen, M., and Zhu, X. 2019. Plant phenology and global climate change: Current progresses and challenges. Global Change Biology 25: 1922-1940.  https://doi.org/10.1111/gcb.14619
  23. R Core Team. 2023. R: A Language and Environment for Statistical Computing. R foundation for Statistical Computing, Vienna, Austria. 
  24. Ren, S., Qin, Q., and Ren, H. 2019. Contrasting wheat phenological responses to climate change in global scale. Science of the Total Environment 665: 620-631.  https://doi.org/10.1016/j.scitotenv.2019.01.394
  25. Schreiber, S.G., Ding, C., Hamann, A., Hacke, U.G., Thomas. B.R., and Brouard, J.S. 2013. Frost hardiness vs. growth performance in trembling aspen: an experimental test of assisted migration. Journal of Applied Ecology 50: 939-949.  https://doi.org/10.1111/1365-2664.12102
  26. Seyednasrollah, B., Young, A.M., Li, X., Milliman, T., Ault, T., Frolking, S., Friedl, M., and Richardson A. D. 2020. Sensitivity of Deciduous Forest Phenology to Environmental Drivers: Implications for Climate Change Impacts Across North America. Geophysical Research Letters 47: e2019GL086788. 
  27. Shim, K., Roh, K., So, K., Kim, G., Jeong, H., and Lee, D. 2010. Assessing Impacts of Global Warming on Rice Growth and Production in Korea. Climate Change Research 1(2): 121-131. 
  28. Song, J.H., Han, S.H., Lee, S.H., and Yun, C.W. 2019. Changes for Stand Structure of Abies koreana Forest at the Yeongsil Area of Mt. Hallasan for Six Years (from 2011 to 2017). Journal of Korean Society of Forest Science 108(1): 1-9. 
  29. Thapa, S., Garcia Millan, V.E., and Eklundh, L. 2021. Assessing Forest Phenology: A Multi-Scale Comparison of Near-Surface (UAV, Spectral Reflectance Sensor, PhenoCam) and Satellite (MODIS, Sentinel-2) Remote Sensing. Remote Sensing 13: 1597. 
  30. Tucker, C.J., Pinzon, J.E., Brown, M.E., Slayback, D.A., Pak, E.W., Mahoney, R., Vermote, E.F., and El Saleous, N. 2010. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing 26(20): 4485-4498.  https://doi.org/10.1080/01431160500168686
  31. Xie, Y., Wang, X., and Silander, J.A. 2015. Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts. PNAS 112(44): 13585-13590.  https://doi.org/10.1073/pnas.1509991112