Comparison of budburst phenology trends and precision among participants in a citizen science program

The written history of plant phenology: shaping primary sources for secondary publications

Phenological research establishes the science of nature's natural calendar. This research, the monitoring and analysis of seasonal rhythms of plants and animals, is commonly based on citizen science data. Such data may be digitized from primary sources provided by the citizen scientist's original phenological diaries. Secondary data sources are formed by historical publications (for example, yearbooks and climate bulletins). While primary data has the advantage of first-hand notetaking, its digitization may, in practice, be time-consuming. Contrastingly, secondary data can contain well-organized typesetting, making digitization less labour-intensive. However, secondary data can be reshaped by the motivations of the historical actors who were collating the data. This study compared data from 1876-1894 gathered originally by citizen scientists (primary data) and the secondary data founded upon the previous primary data, later published by the Finnish Society of Sciences and Letters as a series of phenological yearbooks. In the secondary data, the recorded numbers of taxa and their phenological stages appeared to be fewer and phenological events standardized, with an increased prevalence of agricultural phenology (at the cost of autumn phenology). Moreover, it seems the secondary data had been screened for potential outliers. While secondary sources may provide current phenologists with coherent sets of relevant data, future users must be aware of potential data reshaping resulting from the preferences of historical actors. These actors may weigh and limit the original observations according to their own criteria and preferences.

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

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.

Phenological and elevational shifts of plants, animals and fungi under climate change in the European Alps

Mountain areas are biodiversity hotspots and provide a multitude of ecosystem services of irreplaceable socio-economic value. In the European Alps, air temperature has increased at a rate of about 0.36°C decade^-1 since 1970, leading to glacier retreat and significant snowpack reduction. Due to these rapid environmental changes, this mountainous region is undergoing marked changes in spring phenology and elevational distribution of animals, plants and fungi. Long-term monitoring in the European Alps offers an excellent natural laboratory to synthetize climate-related changes in spring phenology and elevational distribution for a large array of taxonomic groups. This review assesses the climatic changes that have occurred across the European Alps during recent decades, spring phenological changes and upslope shifts of plants, animals and fungi from evidence in published papers and previously unpublished data. Our review provides evidence that spring phenology has been shifting earlier during the past four decades and distribution ranges show an upwards trend for most of the taxonomic groups for which there are sufficient data. The first observed activity of reptiles and terrestrial insects (e.g. butterflies) in spring has shifted significantly earlier, at an average rate of -5.7 and -6.0 days decade^-1 , respectively. By contrast, the first observed spring activity of semi-aquatic insects (e.g. dragonflies and damselflies) and amphibians, as well as the singing activity or laying dates of resident birds, show smaller non-significant trends ranging from -1.0 to +1.3 days decade^-1 . Leaf-out and flowering of woody and herbaceous plants showed intermediate trends with mean values of -2.4 and -2.8 days decade^-1 , respectively. Regarding species distribution, plants, animals and fungi (N = 2133 species) shifted the elevation of maximum abundance (optimum elevation) upslope at a similar pace (on average between +18 and +25 m decade^-1 ) but with substantial differences among taxa. For example, the optimum elevation shifted upward by +36.2 m decade^-1 for terrestrial insects and +32.7 m decade^-1 for woody plants, whereas it was estimated to range between -1.0 and +11 m decade^-1 for semi-aquatic insects, ferns, birds and wood-decaying fungi. The upper range limit (leading edge) of most species also shifted upslope with a rate clearly higher for animals (from +47 to +91 m decade^-1 ) than for plants (from +17 to +40 m decade^-1 ), except for semi-aquatic insects (-4.7 m decade^-1 ). Although regional land-use changes could partly explain some trends, the consistent upward shift found in almost all taxa all over the Alps is likely reflecting the strong warming and the receding of snow cover that has taken place across the European Alps over recent decades. However, with the possible exception of terrestrial insects, the upward shift of organisms seems currently too slow to track the pace of isotherm shifts induced by climate warming, estimated at about +62 to +71 m decade^-1 since 1970. In the light of these results, species interactions are likely to change over multiple trophic levels through phenological and spatial mismatches. This nascent research field deserves greater attention to allow us to anticipate structural and functional changes better at the ecosystem level.

Best environmental predictors of breeding phenology differ with elevation in a common woodland bird species

Temperatures in mountain areas are increasing at a higher rate than the Northern Hemisphere land average, but how fauna may respond, in particular in terms of phenology, remains poorly understood. The aim of this study was to assess how elevation could modify the relationships between climate variability (air temperature and snow melt-out date), the timing of plant phenology and egg-laying date of the coal tit (Periparus ater). We collected 9 years (2011-2019) of data on egg-laying date, spring air temperature, snow melt-out date, and larch budburst date at two elevations (~1,300 m and ~1,900 m asl) on a slope located in the Mont-Blanc Massif in the French Alps. We found that at low elevation, larch budburst date had a direct influence on egg-laying date, while at high-altitude snow melt-out date was the limiting factor. At both elevations, air temperature had a similar effect on egg-laying date, but was a poorer predictor than larch budburst or snowmelt date. Our results shed light on proximate drivers of breeding phenology responses to interannual climate variability in mountain areas and suggest that factors directly influencing species phenology vary at different elevations. Predicting the future responses of species in a climate change context will require testing the transferability of models and accounting for nonstationary relationships between environmental predictors and the timing of phenological events.

Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens—preserved plant material curated in natural history collections—but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth.

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

Phenological variation in spring leafing between and within species can determine plant responses to warmer winter and spring temperatures in the short term. Methods are needed for monitoring canopy development that can be replicated on a large-scale, while retaining fine-scale resolution at the level of individual trees. Citizen science has the potential to provide this, but a range of approaches exist in terms of the phenophase recorded (e.g. budburst or leaf expansion), how the phenophase is characterised (first events or intensity monitoring) and the portion of tree crown assessed and observation frequency. A comparison of spring budburst and leaf expansion of four tree species (Fraxinus excelsior, Fagus sylvatica, Quercus robur and Acer pseudoplatanus) was monitored in one woodland using (1) counts of expanded leaves on three crown sections, (2) percentage estimates of expanded leaves across the whole crown and (3) a greenness index from photography. Logistic growth models were applied to make comparisons. First-event dates were found to be misleading due to high variation in leaf development rates within and between species. Percentage estimates and counts produced similar estimates of leaf expansion timing and rate. The greenness index produced similar estimates of timing, but not rate, and was compromised by practicalities of photographing individual crowns in closed-canopy woodland. Citizen scientists could collect data across the period of spring leafing, with visual counts and/or estimates made every 3-4 days, subject to tests of reliability in pilot citizen science studies.

Daily Maximum Temperatures Induce Lagged Effects on Leaf Unfolding in Temperate Woody Species Across Large Elevational Gradients

The timing of leaf unfolding in temperate woody species is predominantly controlled by the seasonal course of temperature in late winter and early spring. However, quantifying lagged temperature effects on spring phenology is still challenging. Here, we aimed at investigating lagged and potentially non-linear effects of daily maximum temperatures on the probability of leaf unfolding in temperate woody species growing across large elevational gradients. We analyzed 5280 observations of leaf-out time of four tree species (European beech, horse chestnut, European larch, Norway spruce) and one shrub species (common hazel) that were recorded by volunteers over 40 years at 42 locations in Switzerland. We used a case-crossover sampling design to match leaf-out dates with control dates (i.e., dates before or after leaf-out), and analyzed these data with conditional logistic regression accounting for lagged temperature effects over 60 days. Multivariate meta-analyses were used to synthesize lagged temperature and elevational effects on leaf unfolding across multiple phenological stations. Temperature effects on the probability of leaf unfolding were largest at relatively short lags (i.e., within ca. 10 days) and decreased with increasing lags. Short- to mid-term effects (i.e., within ca. 10 to 20 days) were larger for late-leafing species known to be photoperiod-sensitive (beech, Norway spruce). Temperature effects increased for the broadleaved species (horse chestnut, hazel, beech) with decreasing elevation, particularly within ca. 10 to 40 days, i.e., leaf unfolding occurs more rapidly at low elevations for a given daily maximum temperature. Our novel findings provide evidence of cumulative and long-term temperature effects on leaf unfolding, whereby the efficiency of relatively high temperatures to trigger leaf-out becomes higher shortly before bud burst. These lagged associations between temperature and leaf unfolding improve our understanding of phenological responses across temperate woody species with differing ecological requirements that occur along elevational gradients.