Stocktake Sale on now: wide range of books at up to 70% off!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Estimation of post-fire vegetation recovery in boreal forests using solar-induced chlorophyll fluorescence (SIF) data

Meng Guo A , Jing Li B D , Fangbing Yu A , Shuai Yin C , Shubo Huang A and Lixiang Wen A
+ Author Affiliations
- Author Affiliations

A Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.

B Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Science, Changchun 130102, China.

C Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba 3058506, Japan.

D Corresponding author. Email: lijingsara@iga.ac.cn

International Journal of Wildland Fire 30(5) 365-377 https://doi.org/10.1071/WF20162
Submitted: 5 October 2020  Accepted: 23 January 2021   Published: 11 February 2021

Abstract

The estimation of post-fire vegetation recovery is essential for forest management and wildfire policy-making. In the last few decades, vegetation indices have been widely used to monitor post-fire vegetation recovery by comparison with the pre-fire state. In this study, vegetation recovery is estimated using Solar-Induced chlorophyll Fluorescence (SIF), which is a by-product of photosynthesis and can reflect the physiological characteristics of a plant. We found that 20 years is insufficient for vegetation recovery, as the SIF within burned areas exhibited a significant increasing trend, which was most notable within the first 6 to 10 years after a wildfire. When comparing the SIF within and outside burned areas, we found that, during the first 3 to 6 years, SIF values outside burned areas were larger than that within burned areas; however, after ~6 years, the SIF within the burned areas exceeded that outside burned areas owing to the different carbon sequestration intensities of different vegetation recovery stages. Field photos of recovering vegetation were then compared with the Enhanced Vegetation Index (EVI) trend within the burned area, and it was found that, although the EVI reached pre-fire levels or stabilised, vegetation recovery was continuing.

Keywords: boreal forest, fire CCI, forest fire, MODIS EVI, post-fire vegetation recovery, SIF.


References

Baker NR (2008) Chlorophyll fluorescence: a probe of photosynthesis in vivo. Annual Review of Plant Biology 59, 89–113.
Chlorophyll fluorescence: a probe of photosynthesis in vivo.Crossref | GoogleScholarGoogle Scholar | 18444897PubMed |

Boucher D, Gauthier S, Thiffault N, Marchand W, Girardin M, Urli M (2020) How climate change might affect tree regeneration following fire at northern latitudes: a review. New Forests 51, 543–571.
How climate change might affect tree regeneration following fire at northern latitudes: a review.Crossref | GoogleScholarGoogle Scholar |

Brando PM, Oliveria-Santos C, Rocha W, Cury R, Coe MT (2016) Effects of experimental fuel additions on fire intensity and severity: unexpected carbon resilience of a neotropical forest. Global Change Biology 22, 2516–2525.
Effects of experimental fuel additions on fire intensity and severity: unexpected carbon resilience of a neotropical forest.Crossref | GoogleScholarGoogle Scholar | 26750627PubMed |

Brando P, Macedo M, Silvério D, Rattis L, Paolucci L, Alencar A, Coe M, Amorim C (2020) Amazon wildfires: Scenes from a foreseeable disaster. Flora 268, 151609
Amazon wildfires: Scenes from a foreseeable disaster.Crossref | GoogleScholarGoogle Scholar |

Chuvieco E, Yue C, Heil A, Mouillot F, Alonso-Canas I, Padilla M, Pereira JM, Oom D, Tansey K (2016) A new global burned area product for climate assessment of fire impacts. Global Ecology and Biogeography 25, 619–629.
A new global burned area product for climate assessment of fire impacts.Crossref | GoogleScholarGoogle Scholar |

Chuvieco E, Lizundia-Loiola J, Pettinari ML, Ramo R, Plummer SE (2018) Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies. Earth System Science Data 10, 2015–2031.
Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies.Crossref | GoogleScholarGoogle Scholar |

Collins L, McCarthy G, Mellor A, Newell G, Smith L (2020) Training data requirements for fire severity mapping using Landsat imagery and random forest. Remote Sensing of Environment 245, 111839
Training data requirements for fire severity mapping using Landsat imagery and random forest.Crossref | GoogleScholarGoogle Scholar |

Cuevas-Gonzalez M, Gerard F, Balzter H, Riaño D (2009) Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices. Global Change Biology 15, 561–577.
Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices.Crossref | GoogleScholarGoogle Scholar |

Damgaard C (2019) A critique of the space-for-time substitution practice in community ecology. Trends in Ecology & Evolution 34, 416–421.
A critique of the space-for-time substitution practice in community ecology.Crossref | GoogleScholarGoogle Scholar |

Epting J, Verbyla D (2005) Landscape-level interactions of pre-fire vegetation, burn severity, and post-fire vegetation over a 16-year period in interior Alaska. Canadian Journal of Forest Research 35, 1367–1377.
Landscape-level interactions of pre-fire vegetation, burn severity, and post-fire vegetation over a 16-year period in interior Alaska.Crossref | GoogleScholarGoogle Scholar |

Fernandez-Manso A, Quintano C, Roberts DA (2016) Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems. Remote Sensing of Environment 184, 112–123.
Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems.Crossref | GoogleScholarGoogle Scholar |

Francos M, Pereira P, Alcañiz M, Úbeda X (2018) Post-wildfire management effects on short-term evolution of soil properties (Catalonia, Spain, SW Europe). The Science of the Total Environment 633, 285–292.
Post-wildfire management effects on short-term evolution of soil properties (Catalonia, Spain, SW Europe).Crossref | GoogleScholarGoogle Scholar | 29574372PubMed |

Frankenberg C, Butz A, Toon GC (2011) Disentangling chlorophyll fluorescence from atmospheric scattering effects in O2A-band spectra of reflected sun-light. Geophysical Research Letters 38, L03801
Disentangling chlorophyll fluorescence from atmospheric scattering effects in O2A-band spectra of reflected sun-light.Crossref | GoogleScholarGoogle Scholar |

Frankenberg C, O’Dell C, Berry J, Guanter L, Joiner J, Köhler P, Pollock R, Taylor TE (2014) Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2. Remote Sensing of Environment 147, 1–12.
Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2.Crossref | GoogleScholarGoogle Scholar |

Gao BC, Li RR (2000) Quantitative Improvement in the Estimates of NDVI Values from remotely sensed data by correcting thin cirrus scattering effects. Remote Sensing of Environment 74, 494–502.
Quantitative Improvement in the Estimates of NDVI Values from remotely sensed data by correcting thin cirrus scattering effects.Crossref | GoogleScholarGoogle Scholar |

Gitas I, Mitri G, Veraverbeke S, Polychronaki A (2012) Advances in remote sensing of post-fire vegetation recovery monitoring – A review. In ‘Remote sensing of biomass – Principles and applications’. (Ed. L Fatoyinbo) pp. 143–176. (IntechOpen Limited: London, UK)

Goetz S, Fiske G, Bunn A (2006) Using satellite time-series data sets to analyze fire disturbance and forest recovery across Canada. Remote Sensing of Environment 101, 352–365.
Using satellite time-series data sets to analyze fire disturbance and forest recovery across Canada.Crossref | GoogleScholarGoogle Scholar |

Guanter L, Frankenberg C, Dudhia A, Lewis PE, Gómez-Dans J, Kuze A, Suto H, Grainger RG (2012) Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements. Remote Sensing of Environment 121, 236–251.
Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements.Crossref | GoogleScholarGoogle Scholar |

Guanter L, Zhang Y, Jung M, Joiner J, Voigt M, Berry JA, Frankenberg C, Huete AR, Zarco-Tejada P, Lee JE, Moran MS, Ponce-Campos G, Beer C, Camps-Valls G, Buchmann N, Gianelle D, Klumpp K, Cescatti A, Baker JM, Griffis TJ (2014) Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proceedings of the National Academy of Sciences of the United States of America 111, E1327–E1333.
Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence.Crossref | GoogleScholarGoogle Scholar | 24706867PubMed |

Guo M, Li J, He H, Xu J, Jin Y (2018) Detecting global vegetation changes using Mann–Kendal (MK) trend test for 1982–2015 time period. Chinese Geographical Science 28, 907–919.
Detecting global vegetation changes using Mann–Kendal (MK) trend test for 1982–2015 time period.Crossref | GoogleScholarGoogle Scholar |

Guo M, Li J, Wen L, Huang S (2019) Estimation of CO2 emissions from wildfires using OCO-2 data. Atmosphere 10, 581
Estimation of CO2 emissions from wildfires using OCO-2 data.Crossref | GoogleScholarGoogle Scholar |

Guo M, Li J, Huang S, Wen L (2020) Feasibility of using MODIS products to simulate Sun-Induced Chlorophyll Fluorescence (SIF) in boreal forests. Remote Sensing 12, 680
Feasibility of using MODIS products to simulate Sun-Induced Chlorophyll Fluorescence (SIF) in boreal forests.Crossref | GoogleScholarGoogle Scholar |

Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A, Thau D, Stehman SV, Goetz SJ, Loveland TR, Kommareddy A, Egorov A, Chini L, Justice CO, Townshend JRG (2013) High-resolution global maps of 21st-century forest cover change. Science 342, 850–853.
High-resolution global maps of 21st-century forest cover change.Crossref | GoogleScholarGoogle Scholar | 24233722PubMed |

Hu T, Hu H, Li F, Zhao B, Wu S, Zhu G, Sun L (2019) Long-term effects of post-fire restoration types on nitrogen mineralisation in a Dahurian larch (Larix gmelinii) forest in boreal China. The Science of the Total Environment 679, 237–247.
Long-term effects of post-fire restoration types on nitrogen mineralisation in a Dahurian larch (Larix gmelinii) forest in boreal China.Crossref | GoogleScholarGoogle Scholar | 31082597PubMed |

Kasischke E, French N (1997) Constraints on using AVHRR composite index imagery to study patterns of vegetation cover in boreal forests. International Journal of Remote Sensing 18, 2403–2426.
Constraints on using AVHRR composite index imagery to study patterns of vegetation cover in boreal forests.Crossref | GoogleScholarGoogle Scholar |

Knorre AA, Kirdyanov AV, Prokushkin AS, Krusic PJ, Büntgen U (2019) Tree ring-based reconstruction of the long-term influence of wildfires on permafrost active layer dynamics in central Siberia. The Science of the Total Environment 652, 314–319.
Tree ring-based reconstruction of the long-term influence of wildfires on permafrost active layer dynamics in central Siberia.Crossref | GoogleScholarGoogle Scholar | 30366332PubMed |

Köhler P, Guanter L, Kobayashi H, Walther S, Yang W (2018) Assessing the potential of sun-induced fluorescence and the canopy scattering coefficient to track large-scale vegetation dynamics in Amazon forests. Remote Sensing of Environment 204, 769–785.
Assessing the potential of sun-induced fluorescence and the canopy scattering coefficient to track large-scale vegetation dynamics in Amazon forests.Crossref | GoogleScholarGoogle Scholar |

Kong J-j, Yang J, Bai E (2018) Long-term effects of wildfire on available soil nutrient composition and stoichiometry in a Chinese boreal forest. The Science of the Total Environment 642, 1353–1361.
Long-term effects of wildfire on available soil nutrient composition and stoichiometry in a Chinese boreal forest.Crossref | GoogleScholarGoogle Scholar | 30045515PubMed |

Lee JE, Frankenberg C, van der Tol C, Berry JA, Guanter L, Boyce CK, Fisher JB, Morrow E, Worden JR, Asefi S, Badgley G, Saatchi S (2013) Forest productivity and water stress in Amazonia: Observations from GOSAT chlorophyll fluorescence. Proceedings of the Royal Society B: Biological Sciences 280, 20130171
Forest productivity and water stress in Amazonia: Observations from GOSAT chlorophyll fluorescence.Crossref | GoogleScholarGoogle Scholar | 23760636PubMed |

Li X, Xiao J (2019) A global, 0.05-degree product of Solar-Induced Chlorophyll Fluorescence derived from OCO-2, MODIS, and reanalysis data. Remote Sensing 11, 517
A global, 0.05-degree product of Solar-Induced Chlorophyll Fluorescence derived from OCO-2, MODIS, and reanalysis data.Crossref | GoogleScholarGoogle Scholar |

Li X, Xiao J, He B (2018a) Chlorophyll fluorescence observed by OCO-2 is strongly related to gross primary productivity estimated from flux towers in temperate forests. Remote Sensing of Environment 204, 659–671.
Chlorophyll fluorescence observed by OCO-2 is strongly related to gross primary productivity estimated from flux towers in temperate forests.Crossref | GoogleScholarGoogle Scholar |

Li X, Xiao J, He B, Altaf Arain M, Beringer J, Desai AR, Emmel C, Hollinger DY, Krasnova A, Mammarella I, Noe SM, Ortiz PS, Rey-Sanchez AC, Rocha AV, Varlagin A (2018b) Solar-induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO-2 and flux tower observations. Global Change Biology 24, 3990–4008.
Solar-induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO-2 and flux tower observations.Crossref | GoogleScholarGoogle Scholar | 29733483PubMed |

Lizundia-Loiola J, Otón G, Ramo R, Chuvieco E (2020) A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data. Remote Sensing of Environment 236, 111493
A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data.Crossref | GoogleScholarGoogle Scholar |

Ma J, Xiao X, Bu R, Doughty R, Hu Y, Chen B, Li X, Zhao B (2017) Application of the space-for-time substitution method in validating long-term biomass predictions of a forest landscape model. Environmental Modelling & Software 94, 127–139.
Application of the space-for-time substitution method in validating long-term biomass predictions of a forest landscape model.Crossref | GoogleScholarGoogle Scholar |

Meroni M, Rossini M, Guanter L, Alonso L, Rascher U, Colombo R, Moreno J (2009) Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications. Remote Sensing of Environment 113, 2037–2051.
Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications.Crossref | GoogleScholarGoogle Scholar |

Micallef A, Ribó M, Canals M, Puig P, Lastras G, Tubau X (2014) Space-for-time substitution and the evolution of a submarine canyon–channel system in a passive progradational margin. Geomorphology 221, 34–50.
Space-for-time substitution and the evolution of a submarine canyon–channel system in a passive progradational margin.Crossref | GoogleScholarGoogle Scholar |

Mitri GH, Gitas IZ (2013) Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery. International Journal of Applied Earth Observation and Geoinformation 20, 60–66.
Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery.Crossref | GoogleScholarGoogle Scholar |

Mohammed GH, Colombo R, Middleton EM, Rascher U, van der Tol C, Nedbal L, Goulas Y, Pérez-Priego O, Damm A, Meroni M, Joiner J, Cogliati S, Verhoef W, Malenovský Z, Gastellu-Etchegorry J-P, Miller JR, Guanter L, Moreno J, Moya I, Berry JA, Frankenberg C, Zarco-Tejada PJ (2019) Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress. Remote Sensing of Environment 231, 111177
Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.Crossref | GoogleScholarGoogle Scholar | 33414568PubMed |

Moradizadeh H, Heydari M, Omidipour R, Mezbani A, Prevosto B (2020) Ecological effects of fire severity and time since fire on the diversity partitioning, composition and niche apportionment models of post-fire understory vegetation in semi-arid oak forests of Western Iran. Ecological Engineering 143, 105694
Ecological effects of fire severity and time since fire on the diversity partitioning, composition and niche apportionment models of post-fire understory vegetation in semi-arid oak forests of Western Iran.Crossref | GoogleScholarGoogle Scholar |

Nepstad DC, Ssimo AV, Alencar A, Nobre C, Brooksk MCV (1999) Large-scale impoverishment of Amazonian forest by logging and fire. Nature 398, 505–508.
Large-scale impoverishment of Amazonian forest by logging and fire.Crossref | GoogleScholarGoogle Scholar |

Parazoo NC, Bowman K, Fisher JB, Frankenberg C, Jones DB, Cescatti A, Perez-Priego O, Wohlfahrt G, Montagnani L (2014) Terrestrial gross primary production inferred from satellite fluorescence and vegetation models. Global Change Biology 20, 3103–3121.
Terrestrial gross primary production inferred from satellite fluorescence and vegetation models.Crossref | GoogleScholarGoogle Scholar | 24909755PubMed |

Potapov P, Hansen MC, Stehman SV, Loveland TR, Pittman K (2008) Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss. Remote Sensing of Environment 112, 3708–3719.
Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss.Crossref | GoogleScholarGoogle Scholar |

Riaño D, Moreno-Ruiz J, Isidoro D, Ustin S (2007) Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA-NASA Pathfinder. Global Change Biology 13, 40–50.
Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA-NASA Pathfinder.Crossref | GoogleScholarGoogle Scholar |

Rossini M, Meroni M, Celesti M, Cogliati S, Julitta T, Panigada C, Rascher U, van der Tol C, Colombo R (2016) Analysis of red and far-red sun-induced chlorophyll fluorescence and their ratio in different canopies based on observed and modeled data. Remote Sensing 8, 412
Analysis of red and far-red sun-induced chlorophyll fluorescence and their ratio in different canopies based on observed and modeled data.Crossref | GoogleScholarGoogle Scholar |

Shi L, Dech JP, Liu H, Zhao P, Zhou M (2019) Post‐fire vegetation recovery at forest sites is affected by permafrost degradation in the Da Xing’an Mountains of northern China. Journal of Vegetation Science 30, 940–949.
Post‐fire vegetation recovery at forest sites is affected by permafrost degradation in the Da Xing’an Mountains of northern China.Crossref | GoogleScholarGoogle Scholar |

Tang JW, Korner C, Muraoka H, Piao SL, Shen MG, Thackeray SJ, Yang X (2016) Emerging opportunities and challenges in phenology: a review. Ecosphere 7, e01436
Emerging opportunities and challenges in phenology: a review.Crossref | GoogleScholarGoogle Scholar |

Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8, 127–150.
Red and photographic infrared linear combinations for monitoring vegetation.Crossref | GoogleScholarGoogle Scholar |

van Leeuwen WJD, Casady GM, Neary DG, Bautista S, Alloza JA, Carmel Y, Wittenberg L, Malkinson D, Orr BJ (2010) Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel. International Journal of Wildland Fire 19, 75–93.
Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel.Crossref | GoogleScholarGoogle Scholar |

Vanderhoof M, Burt C, Hawbaker T (2018) Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA. International Journal of Wildland Fire 27, 699–713.
Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA.Crossref | GoogleScholarGoogle Scholar |

Veraverbeke S, Gitas I, Katagis T, Polychronaki A, Somers B, Goossens R (2012) Assessing post-fire vegetation recovery using red–near infrared vegetation indices: Accounting for background and vegetation variability. ISPRS Journal of Photogrammetry and Remote Sensing 68, 28–39.
Assessing post-fire vegetation recovery using red–near infrared vegetation indices: Accounting for background and vegetation variability.Crossref | GoogleScholarGoogle Scholar |

Viana-Soto A, Aguado I, Salas J, García M (2020) Identifying post-fire recovery trajectories and driving factors using landsat time series in fire-prone Mediterranean pine forests. Remote Sensing 12, 1499
Identifying post-fire recovery trajectories and driving factors using landsat time series in fire-prone Mediterranean pine forests.Crossref | GoogleScholarGoogle Scholar |

Xiao J, Chevallier F, Gomez C, Guanter L, Hicke JA, Huete AR, Ichii K, Ni W, Pang Y, Rahman AF, Sun G, Yuan W, Zhang L, Zhang X (2019) Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years. Remote Sensing of Environment 233, 111383
Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years.Crossref | GoogleScholarGoogle Scholar |

Yamada Y, Ohkubo T, Shimizu K (2020) Causal analysis of accuracy obtained using high-resolution global forest change data to identify forest loss in small forest plots. Remote Sensing 12, 2489
Causal analysis of accuracy obtained using high-resolution global forest change data to identify forest loss in small forest plots.Crossref | GoogleScholarGoogle Scholar |

Yi K, Hiroshi T, Zhang J, Guo M, Wang X, Zhong G (2013) Long-term satellite detection of post-fire vegetation trends in boreal forests of China. Remote Sensing 5, 6938–6957.
Long-term satellite detection of post-fire vegetation trends in boreal forests of China.Crossref | GoogleScholarGoogle Scholar |

Yu L, Wen J, Chang CY, Frankenberg C, Sun Y (2019) High‐resolution global contiguous SIF of OCO‐2. Geophysical Research Letters 46, 1449–1458.
High‐resolution global contiguous SIF of OCO‐2.Crossref | GoogleScholarGoogle Scholar |

Zarco-Tejada PJ, Morales A, Testi L, Villalobos FJ (2013) Spatio-temporal patterns of chlorophyll fluorescence and physiological and structural indices acquired from hyperspectral imagery as compared with carbon fluxes measured with eddy covariance. Remote Sensing of Environment 133, 102–115.
Spatio-temporal patterns of chlorophyll fluorescence and physiological and structural indices acquired from hyperspectral imagery as compared with carbon fluxes measured with eddy covariance.Crossref | GoogleScholarGoogle Scholar |

Zhang Y, Joiner J, Alemohammad SH, Zhou S, Gentine P (2018) A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks. Biogeosciences 15, 5779–5800.
A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks.Crossref | GoogleScholarGoogle Scholar |