A comparison of ground-based methods for obtaining large-scale, high-resolution data on the spring leaf phenology of temperate tree species

Smith, Alison M.; Ramsay, Paul M.

doi:10.1007/s00484-019-01839-2

Cited by 7 publications

(2 citation statements)

References 63 publications

(94 reference statements)

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“…Unsurprisingly, the CC and the interpolated DWD phenology of F. sylvatica largely match. Corresponding to literature findings (Ahrends et al., 2009; Smith & Ramsay, 2020) F. excelsior leaves out later than F. sylvatica .…”

Section: Discussionsupporting

confidence: 84%

“…The observation that indirect derivation methods are the first to indicate the start of spring phenology, compared to direct methods observing the trees themselves can therefore be primarily explained by the recording of the understory, which shows a clear drawback of the recording method. Unsurprisingly, the CC and the interpolated DWD phenology of F. sylvatica largely match.Corresponding to literature findings(Ahrends et al, 2009;Smith & Ramsay, 2020) F. excelsior leaves out later than F. sylvatica.Advancing trends of SOS in the Hainich National Park from 2000 to 2020 are predominantly in line with the current literature(Caparros-Santiago et al, 2021;Menzel et al, 2020;…”

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confidence: 82%

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Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues

Kloos,

Klosterhalfen,

Knohl

et al. 2024

Global Change Biology

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Leaf coloring and fall mark the end of the growing season (EOS), playing essential roles in nutrient cycling, resource allocation, ecological interactions, and as climate change indicators. However, understanding future changes in autumn phenology is challenging due to the multitude of likely environmental cues and substantial variations in timing caused by different derivation methods. Yet, it remains unclear whether these two factors are independent or if methodological uncertainties influence the environmental cues determined. We derived start of growing season (SOS) and EOS at a mixed beech forest in Central Germany for the period 2000–2020 based on four different derivation methods using a unique long‐term data set of in‐situ data, canopy imagery, eddy covariance measurements, and satellite remote sensing data and determined their influence on a predictor analysis of leaf senescence. Both SOS and EOS exhibited substantial ranges in mean onset dates (39.5 and 28.6 days, respectively) across the different methods, although inter‐annual variations and advancing SOS trends were similar across methods. Depending on the data, EOS trends were advanced or delayed, but inter‐annual patterns correlated well (mean r = .46). Overall, warm, dry, and less photosynthetically productive growing seasons were more likely to be associated with a delayed EOS, while colder, wetter, and more photosynthetically productive vegetation periods resulted in an earlier EOS. In addition, contrary to recent results, no clear influence of pre‐solstice vegetation activity on the timing of senescence was detected. However, most notable were the large differences in sign and strength of potential drivers both in the univariate and multivariate analyses when comparing derivation methodologies. The results suggest that an ensemble analysis of all available phenological data sources and derivation methods is needed for general statements on autumn phenology and its influencing variables and correct implementation of the senescence process in ecosystem models.

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Section: Discussionsupporting

confidence: 84%

supporting

confidence: 82%

Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues

Kloos,

Klosterhalfen,

Knohl

et al. 2024

Global Change Biology

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Unraveling the Tapestry of Plant Phenology in the Face of Climate Change and Environmental Stress

Gusain,

Chauhan,

Singh

et al. 2024

Urban Forests, Climate Change and Environmental Pollution

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A comparison of herbarium and citizen science phenology datasets for detecting response of flowering time to climate change in Denmark

2022

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Phenology has emerged as a key metric to measure how species respond to changes in climate. Innovative means have been developed to extend the temporal and spatial range of phenological data by obtaining data from herbarium specimens, citizen science programs, and biodiversity data repositories. These different data types have seldom been compared for their effectiveness in detecting environmental impacts on phenology. To address this, we compare three separate phenology datasets from Denmark: (i) herbarium specimen data spanning 145 years, (ii) data collected from a citizen science phenology program over a single year observing first flowering, and (iii) data derived from incidental biodiversity observations in iNaturalist over a single year. Each dataset includes flowering day of year observed for three common spring-flowering plant species: Allium ursinum (ramsons), Aesculus hippocastanum (horse chestnut), and Sambucus nigra (black elderberry). The incidental iNaturalist dataset provided the most extensive geographic coverage across Denmark and the largest sample size and recorded peak flowering in a way comparable to herbarium specimens. The directed citizen science dataset recorded much earlier flowering dates because the program objective was to report the first flowering, and so was less compared to the other two datasets. Herbarium data demonstrated the strongest effect of spring temperature on flowering in Denmark, possibly because it was the only dataset measuring temporal variation in phenology, while the other datasets measured spatial variation. Herbarium data predicted the mean flowering day of year recorded in our iNaturalist dataset for all three species. Combining herbarium data with iNaturalist data provides an even more effective method for detecting climatic effects on phenology. Phenology observations from directed and incidental citizen science initiatives will increase in value for climate change research in the coming years with the addition of data capturing the inter-annual variation in phenology.

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A comparison of ground-based methods for obtaining large-scale, high-resolution data on the spring leaf phenology of temperate tree species

Abstract: A comparison of ground-based methods for obtaining large-scale, high-resolution data on the spring leaf phenology of temperate tree species Smith, AM

Cited by 7 publications

References 63 publications

Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues

Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues

Unraveling the Tapestry of Plant Phenology in the Face of Climate Change and Environmental Stress

A comparison of herbarium and citizen science phenology datasets for detecting response of flowering time to climate change in Denmark

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