Validating remotely sensed land surface phenology with leaf out records from a citizen science network

Purdy, Logan M.; Sang, Zihaohan; Beaubien, Elisabeth; Hamann, Andreas

doi:10.1016/j.jag.2022.103148

Cited by 6 publications

(4 citation statements)

References 48 publications

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“…The relatively short time series (21 years) captured substantial interannual variation, but did not allow for robust analysis. While there are other phenology datasets available, we opted for the MODIS‐derived MCDQ12 in spite of its limited time span because of its relatively high degree of accuracy in the boreal biome, based on a comparison with field observations (Purdy et al, 2023). No such field verification was performed on the NDSI measurements used to quantify snow melt cover, but a comparison with independently collected Landsat data shows a strong concordance (98.4%) between the two products (Rittger et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Broadleaf tree phenology and springtime wildfire occurrence in boreal Canada

Parisien

Barber

Flannigan

et al. 2023

Global Change Biology

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Although broadleaf tree species of the boreal biome have a lower flammability compared to conifers, there is a period following snow melt and prior to leaf flush (i.e., greenup), termed the “spring window” by fire managers, when these forests are relatively conducive to wildfire ignition and spread. The goal of this study was to characterize the duration, timing, and fire proneness of the spring window across boreal Canada and assess the link between these phenological variables and the incidence of springtime wildfires. We used remotely sensed snow cover and greenup data to identify the annual spring window for five boreal ecozones from 2001 to 2021 and then compared seasonality of wildfire starts (by cause) and fire‐conducive weather in relation to this window, averaged over the 21‐year period. We conducted a path analysis to concomitantly evaluate the influence of the spring window's duration, the timing of greenup, and fire‐conducive weather on the annual number and the seasonality of spring wildfires. Results show that the characteristics of spring windows vary substantially from year to year and among geographic zones, with the interior west of Canada having the longest and most fire‐conducive spread window and, accordingly, the greatest springtime wildfire activity. We also provide support for the belief that springtime weather generally promotes wind‐driven, rather than drought‐driven wildfires. The path analyses show idiosyncratic behavior among ecozones, but, in general, the seasonality of the wildfire season is mainly driven by the timing of the greenup, whereas the number of spring wildfires mostly responds to the duration of the spring window and the frequency of fire‐conducive weather. The results of this study allows us to better understand and anticipate the biome‐wide changes projected for the northern forests of North America.

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Section: Discussionmentioning

confidence: 99%

Broadleaf tree phenology and springtime wildfire occurrence in boreal Canada

Parisien

Barber

Flannigan

et al. 2023

Global Change Biology

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“…Even if there is only one growing season, the variation between the two peaks can be reflected in the fluctuation of the EOS. To date, the dataset has been used to study phenological changes on a global scale [41][42][43], and has shown a high correlation with ground observation data in Alberta [44]. For comparison with this data, we utilized the phenological measurement data from Fujian Province in the earlier literature [45].…”

Section: Phenological Datamentioning

confidence: 99%

“…changes on a global scale [41][42][43], and has shown a high correlation with ground observation data in Alberta [44]. For comparison with this data, we utilized the phenological measurement data from Fujian Province in the earlier literature [45].…”

Section: Thematic Datamentioning

confidence: 99%

Analysis of Factors Driving Subtropical Forest Phenology Differentiation, Considering Temperature and Precipitation Time-Lag Effects: A Case Study of Fujian Province

Ma,

Zhang,

Qin

et al. 2024

Forests

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Subtropical forest phenology differentiation is affected by temperature, precipitation, and topography. Understanding the primary contributing elements and their interactions with forest phenology can help people better comprehend the subtropical forest growth process and its response to climate. Meanwhile, the temporal and spatial variations of phenological rhythms are important indicators of climatic impacts on forests. Therefore, this study aimed to analyze both a total area and different forest growth environments within the whole (i.e., coastal site areas (II, IV) and inland site areas (I, III)) as to spatiotemporal patterns associated with subtropical forests in Fujian Province, which is located at the boundary between the middle and south subtropical zones. Considering the asymmetric effects of climate and forest growth, this study chose pre-seasonal and cumulative temperature and precipitation factors and utilized the GeoDetector model to analyze the dominant drivers and interactions within phenology differentiation in Fujian Province. The results show the following: (1) All of the phenological parameters were advanced or shortened over the 19-year observation period; those of shrubland and deciduous broadleaf forests fluctuated greatly, and their stability was poor. (2) The phenological parameters were more distinct at the borders of the site areas. Additionally, the dates associated with the end of the growth season (EOS) and the date-position of peak value (POP) in coastal areas (i.e., II and IV) were later than those in inland areas (i.e., I and III). Among the parameters, the length of the growth season (LOS) was most sensitive to altitude. (3) Precipitation was the main driving factor affecting the spatial heterogeneity of the start of the growth season (SOS) and the EOS. The relatively strong effects of preseason and current-month temperatures on the SOS may be influenced by the temperature threshold required to break bud dormancy, and the relationship between the SOS and temperature was related to the lag time and the length of accumulation. The EOS was susceptible to the hydrothermal conditions of the preseason accumulation, and the variation trend was negatively correlated with temperature and precipitation. Spatial attribution was used to analyze the attribution of phenology differentiation from the perspectives of different regions, thus revealing the relationships between forest phenology and meteorological time-lag effects, the result which can contribute to targeted guidance and support for scientific forest management.

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“…To find an appropriate reference data set for phenological comparisons with the Flora Incognita data, which encompasses the same spatial and temporal coverage, remains a challenge (Katal et al, 2023). One future validation avenue could explore the relationship between our macrophenological approach and the macrophenology derived from satellite observations, for example (Purdy et al, 2023;Studer et al, 2007;Tian et al, 2021;Zeng et al, 2020;Zhang et al, 2003).…”

Section: Validation and Biasmentioning

confidence: 99%

Macrophenological dynamics from citizen science plant occurrence data

Mora,

Rzanny,

Wäldchen

et al. 2024

Methods Ecol Evol

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Phenological shifts across plant species is a powerful indicator to quantify the effects of climate change. Today, mobile applications with automated species identification open new possibilities for phenological monitoring across space and time. Here, we introduce an innovative spatio‐temporal machine learning methodology that harnesses such crowd‐sourced data to quantify phenological dynamics across taxa, space and time. Our algorithm links individual phenological responses across thousands of species and geographical locations, using a similarity measure. The analysis draws on nearly ten million plant observations collected through the AI‐based plant identification app Flora Incognita in Germany from 2018 to 2021. Our method quantifies changes in synchronisation across the annual cycle. During the growing season, synchronised behaviour can be encoded by a few characteristic macrophenological patterns. Nonlinear spatio‐temporal changes of these patterns can be efficiently quantified using a data compressibility measure. Outside the growing season, the phenological synchronisation diminishes introducing noise into the patterns. Despite biases and uncertainties associated with crowd‐sourced data, for example due to human data collection behaviour, our study demonstrates the feasibility of deriving meaningful indicators for monitoring plant macrophenology from individual plant observations. As crowd‐sourced databases continue to expand, our approach holds promise to study climate‐induced phenological shifts and feedback loops.

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Validating remotely sensed land surface phenology with leaf out records from a citizen science network

Cited by 6 publications

References 48 publications

Broadleaf tree phenology and springtime wildfire occurrence in boreal Canada

Broadleaf tree phenology and springtime wildfire occurrence in boreal Canada

Analysis of Factors Driving Subtropical Forest Phenology Differentiation, Considering Temperature and Precipitation Time-Lag Effects: A Case Study of Fujian Province

Macrophenological dynamics from citizen science plant occurrence data

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