“Green pointillism”: detecting the within-population variability of budburst in temperate deciduous trees with phenological cameras

Delpierre, Nicolas; Soudani, Kamel; Berveiller, Daniel; Dufrêne, Éric; Hmimina, Gabriel; Vincent, Gaëlle

doi:10.1007/s00484-019-01855-2

Cited by 16 publications

(16 citation statements)

References 44 publications

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“…One way to proceed is to systematize ground observation campaigns at sites equipped with phenological cameras (e.g. Delpierre et al., 2020; Keenan et al., 2014). Train observers and inter‐calibrate them.…”

Section: Discussionmentioning

confidence: 99%

Higher sample sizes and observer inter‐calibration are needed for reliable scoring of leaf phenology in trees

Chuine

Denéchère

et al. 2021

Journal of Ecology

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Reliable phenological observations are needed to quantify the impact of climate change on tree phenology. Ground observations remain a prime source of phenological data, but their accuracy and precision have not been systematically quantified. The high subjectivity of ground phenological observations affects their accuracy, and the high within‐population variability of tree phenology affects their precision. The magnitude of those effects is unknown to date. We first explored the inter‐observer variability in the timing of bud development and leaf senescence in trees using a unique dataset of seven observer inter‐calibration sessions. Then, using tree phenological data collected in three European forests (n = 2,346 observations for budburst, n = 539 for leaf senescence), we quantified how the ‘observer uncertainty’ (accuracy of the observations) and the ‘population sampling uncertainty’ (precision of the observations) combine to affect the estimates of the budburst and the leaf senescence dates. The median observer uncertainty was 8 days for budburst (BBCH = 7) and 15 days for leaf senescence (BBCH = 95). As expected, the population sampling uncertainty decreased with increasing sample size, and was about 6 days for budburst and 10 days for leaf senescence for a sample of 10 individuals monitored per population (corresponding to the median sample size in the phenological literature). As a whole, the overall uncertainty of phenological observations could reach up to 2 weeks for budburst and 1 month for leaf senescence. Synthesis. This paper quantifies for the first time the accuracy and precision of ground phenological observations in forest trees and as such offers tables to estimate the uncertainty of phenological data. We show that reliable estimates of budburst and leaf senescence require three times (n = 30) to two times (n = 20) larger sample sizes as compared to sample sizes usually considered in phenological studies. We further call for an increased effort of observer inter‐calibration, required to increase the accuracy of phenological observations. These recommendations reduce the uncertainty of phenological data, thereby improving the estimation of phenological trends over time, the response of phenology to temperature or the inference of phenological model parameters.

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Section: Discussionmentioning

confidence: 99%

Higher sample sizes and observer inter‐calibration are needed for reliable scoring of leaf phenology in trees

Chuine

Denéchère

et al. 2021

Journal of Ecology

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“…A description of field phenological data is given in Denéchère et al (2019), Delpierre et al (2020) and Soudani et al (2020). Briefly, phenological observations were conducted according to two complementary sampling protocols.…”

Section: Methodsmentioning

confidence: 99%

Potential of Synthetic Aperture Radar Sentinel-1 time series for the monitoring of phenological cycles in a deciduous forest

Soudani

Delpierre

Berveiller

et al. 2021

Preprint

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Annual time-series of the two satellites C-band SAR (Synthetic Aperture Radar) Sentinel-1 A and B data over five years were used to characterize the phenological cycle of a temperate deciduous forest. Six phenological markers of the start, middle and end of budburst and leaf expansion stage in spring and the leaf senescence in autumn were extracted from time-series of the ratio (VV/VH) of backscattering at co-polarization VV (vertical-vertical) and at cross polarization VH (vertical-horizontal). These markers were compared to field phenological observations, and to phenological dates derived from various proxies (Normalized Difference Vegetation Index NDVI time-series from Sentinel-2 A and B images, in situ NDVI measurements, Leaf Area Index LAI and litterfall temporal dynamics). We observe a decrease in the backscattering coefficient (σ0) at VH cross polarization during the leaf development and expansion phase in spring and an increase during the senescence phase, contrary to what is usually observed on various types of crops. In vertical polarization, σ0VV shows very little variation throughout the year. S-1 time series of VV/VH ratio provides a good description of the seasonal vegetation cycle allowing the estimation of spring and autumn phenological markers. Estimates provided by VV/VH of budburst dates differ by approximately 8 days on average from phenological observations. During senescence phase, estimates are positively shifted (later) and deviate by about 20 days from phenological observations of leaf senescence while the differences are of the order of 2 to 4 days between the phenological observations and estimates based on in situ NDVI and LAI time-series, respectively. A deviation of about 7 days, comparable to that observed during budburst, is obtained between the estimates of senescence from S-1 and those determined from the in situ monitoring of litterfall. While in spring, leaf emergence and expansion described by LAI or NDVI explains the increase of VV/VH (or the decrease of σ0VH), during senescence, S-1 VV/VH is decorrelated from LAI or NDVI and is better explained by litterfall temporal dynamics. This behavior resulted in a hysteresis phenomenon observed on the relationships between VV/VH and NDVI or LAI. For the same LAI or NDVI, the response of VV/VH is different depending on the phenological phase considered. This study shows the high potential offered by Sentinel-1 SAR C-band time series for the detection of forest phenology for the first time, thus overcoming the limitations caused by cloud cover in optical remote sensing of vegetation phenology.

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“…For both manual field and visual observations, we considered leaf emergence to occur when most leaves had emerged entirely from bud scales such that leaf midribs were visible and leaf senescence to occur when most leaves had begun to show autumn colouration. Curve-estimated leaf emergence dates for the three (1) (Ahrends et al, 2008(Ahrends et al, , 2009Berra et al, 2016;Browning et al, 2017;Delpierre et al, 2020;Keenan et al, 2014;Klosterman et al, 2014;Klosterman & Richardson, 2017;Kosmala et al, 2016;Peltoniemi et al, 2018;Richardson, Hufkens, Milliman, Aubrecht, Chen, et al, 2018;Seyednasrollah et al, 2021;Wingate et al, 2015;Xie, Civco, & Silander Jr, 2018;Zhang et al, 2020).…”

Section: Acadian Phenocam Networkmentioning

confidence: 99%

“…(1) installation of grey non-reflective reference panels in the field of view of all cameras in 2020 onwards and normalization of vegetation G CC time series following Delpierre et al (2020) (Ahrends et al, 2009;Klosterman et al, 2014;Kosmala et al, 2016;Peltoniemi et al, 2018), and (5) comparison of leaf phenology derived from a Spypoint camera to that of a fixed white balance Brinno camera (https://brinno.com/pages/ produ ct-tlc20 0pro) at an external site. For both manual field and visual observations, we considered leaf emergence to occur when most leaves had emerged entirely from bud scales such that leaf midribs were visible and leaf senescence to occur when most leaves had begun to show autumn colouration.…”

Section: Acadian Phenocam Networkmentioning

confidence: 99%

Climate‐driven shifts in leaf senescence are greater for boreal species than temperate species in the Acadian Forest region in contrast to leaf emergence shifts

Spafford

MacDougall

Steenberg³

2023

Ecology and Evolution

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The Acadian Forest Region is a temperate‐boreal transitional zone in eastern North America which provides a unique opportunity for understanding the potential effects of climate change on both forest types. Leaf phenology, the timing of leaf life cycle changes, is an important indicator of the biological effects of climate change, which can be observed with stationary timelapse cameras known as phenocams. Using four growing seasons of observations for the species Acer rubrum (red maple), Betula papyrifera (paper/white birch) and Abies balsamea (balsam fir) from the Acadian Phenocam Network as well as multiple growing season observations from the North American PhenoCam Network we parameterized eight leaf emergence and six leaf senescence models for each species which span a range in process and driver representation. With climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) we simulated future leaf emergence, senescence and season length (senescence minus emergence) for these species at sites within the Acadian Phenocam Network. Model performances were similar across models and leaf emergence model RMSE ranged from about 1 to 2 weeks across species and models, while leaf senescence model RMSE ranged from about 2 to 4 weeks. The simulations suggest that by the late 21st century, leaf senescence may become continuously delayed for boreal species like Betula papyrifera and Abies balsamea, though remain relatively stable for temperate species like Acer rubrum. In contrast, the projected advancement in leaf emergence was similar across boreal and temperate species. This has important implications for carbon uptake, nutrient resorption, ecology and ecotourism for the Acadian Forest Region. More work is needed to improve predictions of leaf phenology for the Acadian Forest Region, especially with respect to senescence. Phenocams have the potential to rapidly advance process‐based model development and predictions of leaf phenology in the context of climate change.

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“Green pointillism”: detecting the within-population variability of budburst in temperate deciduous trees with phenological cameras

Cited by 16 publications

References 44 publications

Higher sample sizes and observer inter‐calibration are needed for reliable scoring of leaf phenology in trees

Higher sample sizes and observer inter‐calibration are needed for reliable scoring of leaf phenology in trees

Potential of Synthetic Aperture Radar Sentinel-1 time series for the monitoring of phenological cycles in a deciduous forest

Climate‐driven shifts in leaf senescence are greater for boreal species than temperate species in the Acadian Forest region in contrast to leaf emergence shifts

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