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Guidelines for Plant Phenological Observations
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... Phenological monitoring was carried out visually every other day on all plants. A system of digital messages was used, which were converted into days of the year (DOYs) according to Koch et al. [19] via software, where DOY 1 represents January 1, and so on. For uniform coding of blooming phenophases, the extended general BBCH scale [20] and the percentage of open flowers [21] were used, where: BF indicates the beginning of flowering (the day when more than 10% of flowers on most of the canopy or a larger number of inflorescences are open), FF indicates full flowering (the day when more than 50% of flowers are open), and EF indicates the end of flowering (the day when fewer than 20% of inflorescences are present). ...
... Multivariate cluster analysis indicates the separation of globe flowering ash genotypes into two subclusters ( Figure 10). The majority of genotypes are grouped in the first subcluster, while the second subcluster includes genotypes 19,40,35,42,27,38,41,28,36,39, and 34. The first subcluster comprises four subgroups with genotypes having similar values of morphological characteristics of the inflorescences. ...
Climate change increasingly impacts urban dendroflora, affecting plant physiology and phenological phases. This paper investigates the impact of changing climatic conditions on the blooming of Fraxinus ornus ‘Globosa’, a decorative form of ash that is a significant component of green infrastructure in Novi Sad, Serbia. The research, conducted over 15 years on 42 individuals in a linear planting near a large river, analyzed temperature and precipitation effects on blooming times and inflorescence characteristics The results indicate changes in the timing of blooming, earlier than recorded in the literature, suggesting that temperature variations and changes in climatic conditions have significantly influenced the phenological phases of the selected clones of globe flowering ash. Additionally, the studied individuals showed exceptional adaptation to climate change and are not considered vulnerable. This study confirmed that this cultivar of flowering ash in urban environments is a key link in the green infrastructure of cities, functioning as green corridors along river flows as a nature-based solution. The studied cultivar is an important element of cultural heritage, contributing to the recreational potential of the linear composition of the promenade, especially during the flowering phenophase, when, in addition to its aesthetic values, it has psychological effects on users of the space, offering a calming influence due to its regular canopy and planting rhythm. Additionally, this cultivar provides important ecological functions, such as offering pollen for pollinators, thereby significantly contributing to the implementation of ecosystem services.
... Compared to analyses of current data, however, the use of phenological data from historical publications has become more complex. This complexity comes from how the data is presented in historical publications (e.g., yearbooks, monthly or weekly climate reviews and/or bulletins; Koch et al. 2007) and how it may differ in composition from those initially made by the volunteers. ...
... Our examples of data editing originate from historical scientific publications. Similar sources of historical phenological data, i.e., yearbooks, monthly climate reviews and/ or weekly bulletins of the national or local institutes, have been previously highlighted by Koch et al. (2007) and more recently detailed by Ovaskainen et al. (2020) and Kalvāne et al. (2021). Apart from scientific reports, phenological observations can be collected from newspaper articles where seasonal plant development and events may have been highlighted frequently in the past (Aono and Saito 2010;Moreno et al. 2016;Fitchett and Raik 2021). ...
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.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00114-023-01861-w.
... For most phenological observations, plant populations were visited twice or three times per week in the best-case scenario (Kaspar et al., 2015). However, a daily resolution is recommended for increasing precision in phenological records (Koch et al., 2009). The phenological stage BBCH 60 reflects the first flowers that open in a plant population but, in some cases, these dates may not be fully representative of the average flowering onset of a certain population. ...
Global temperatures are increasing due to human-driven climate change, with notable implications for the flowering phenology of many forest tree species. Modelling the thermal requirements of these species is critical for projecting the impacts of climate change on forests and for developing appropriate adaptation strategies. Fitting models to phenological observations requires long time series of data, but such data are scarce. Researchers would benefit from combining databases from different locations to fit a single model. The aims of this study are to model the thermal requirements for flowering of the most relevant angiosperm tree species in central Europe and to determine if the accuracy of the models can be improved by limiting the geographic spread of the calibration data. To this end, we fitted the PhenoFlex phenology modelling framework using various subsets of records from the Pan-European Phenology database, which were paired with local temperature data. We used all available data for five species (Acer platanoides, Alnus glutinosa, Betula pendula, Corylus avellana and Fraxinus excelsior) to fit general thermal requirement models. We also fitted models using subsets of the dataset, limiting the calibration sets to data from climatically homogeneous regions and different geographical extents. The general models had average mean absolute errors of 8.51-15.15 days, indicating that they are effective in forecasting flowering onset for central Europe. Predictions did not improve when fitting models with data from temperature-homogeneous areas or from within small geographical extents. These findings suggest that fitting several models to cover parts of an extensive region does not necessarily perform better than fitting a single model for the whole region. This implies that including data from different locations within central Europe when calibrating models would increase the size of calibration datasets without causing a significant increase in model errors. This may help alleviate problems of data scarcity.
... The extended BBCH scale (Meier, 1997) was used, and the following were determined: the day of the opening of the flower bud scales (BB, numerical code 01), the beginning of flowering (BF, numerical code 61) -the day when more than 10% of the flowers are open, full flowering (FF, numerical code 65) -the day when more than 50% of flowers are open and end of flowering (EF, numerical code 69) -day with less than 10% open flowers in the canopy. Based on the system of digital messages according to Koch et al. (2007), dates were converted to the day of the year (DOY). The specific DOY range is defined by the first (BF) and last observed date of flowering, which began in December 2022 and ended in April 2023. ...
... Thuật ngữ "sinh trưởng" được hiểu là sự tăng trưởng kích thước theo thời gian của cây trồng như chiều cao, đường kính, sinh khối và khối lượng [4]. Theo cách thủ công, sự phát triển của cây được mô tả theo quy mô tăng trưởng dựa vào thang đo do Viện Sinh học, Văn phòng Giống cây trồng và ngành Công nghiệp Hoá chất Liên bang Đức xây dựng gọi là BBCH (Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie) với các mã quy định riêng biệt [5] liên quan tới giai đoạn tăng trưởng của cây (từ BBCH 00 cho giai đoạn hạt khô cho đến BBCH 99 cho giai đoạn thu hoạch sản phẩm) giúp cho việc trao đổi thông tin thuận lợi hơn trong lĩnh vực khoa học kiểu hình cây giữa cộng đồng khoa học. Hình 1 thể hiện các giai đoạn phát triển của cây đậu với các giai đoạn được đánh dấu bằng thang đo BBCH [6]. ...
This study evaluate advancements in the application of deep learning and multi-wavelength imaging techniques for monitoring and phenotyping plant growth. With the rapid development of plant breeding technology, effectively integrating high-throughput phenotyping platforms, utilizing conventional imaging to tomographic imaging, which represent a significant step forward in researching complex traits related to plant growth and adaptability. Although deep learning methods have demonstrated breakthrough capabilities of image classification in various fields, their application in plant growth monitoring presents challenges such as the need for extensive data annotation and the ability to process spatial and temporal information simultaneously. This article emphasizes the necessity of developing new softwares and techniques to improve data interpretability and achieves results that align with plant physiological models. Progress in both deep learning and image techniques areas promises to provide more detailed insights into plant phenotypes, accelerate analysis, and enhance our understanding of plant development in diverse environments. This research not only reviews a new state-of-the-art deep learning and image techniques but also provides comments on the need for technology development and proposes future research directions.
... The knowledge of the onset for specific phenological stages in grapevine is advantageous as management and chemical practices can be applied at optimum times (Jones and Davis, 2000). Several methods for monitoring phenology are at the moment in use for agricultural purposes: (1) operator visual observations usually conducted on a plant-to-plant scale (Lancashire et al., 1991;Koch et al., 2009;Denny et al., 2014;Nordt et al., 2021), (2) drone or in-situ continuous measurements, which are Fig. 4. Example of phenotypic variation for dynamic quantum yield of photosystem II in dark adapted material (F v /F m ) for the bud-shoot of two contrasting varieties (Charodnnay, A and Merlot, B) at increasing GDD 6 and/or BBCH. Points are means over two-to-three years (n = 30-40) and error bars represent standard error of the mean (SEM). ...
Early budburst is becoming an increasingly challenging topic in viticulture. Anticipating vegetative resume results in an overall phenological advance, in potential higher risks of late frost and subsequent negative effects on berry quality and overall vine productivity. Phenotypic variation for date of budburst onset (BBCH07) is known in Vitis vinifera and potential exploitation of data regarding thermal requests to reach BBCH07 are critical in defining new avenues for viticulture. Nevertheless, reproducible methods are lacking in defining phenological progression in grapevine and further efforts are needed to standardize quantitative dataset associated with early growth stages appearance. In this work, a panel of twenty-one Vitis vinifera varieties grown in an experimental vineyard were assessed for early phenological onset (pre-to-post budburst) via visual observation, quantum yield of photosystem II in the dark adapted (F v /F m) bud section and growing degree days accumulation over three years. Further experiments were carried out under controlled environmental conditions to evaluate the effect of different simulated late frost on bud viability. Our data proposes F v /F m from bud section as a quantitative and reliable tool, although destructive following our pipeline, to monitor early phenological events in grapevine with significant non-linear associations of the F v /F m with growing degree days on base 6 • C (GDD 6) and phenology. We observed significant (p < 0.001) inter-varietal variation for thermal requests to reach budburst ranking from 140 to 260 GDD 6 although some varieties showed inconsistent data between years (i.e. a plastic response). Late frost damage was associated with phenological progression suggesting a linear and positive correlation between cold injury and de-acclimation from cold hardiness up until first leaf appearance. However, monitoring F v /F m in selected varieties provided evidence of varietal-specific response to late frost with e.g., Chardonnay and Gewürztraminer showing maintenance of photosystem II activity even at advanced phenological stages. This suggests the presence of preferable acclimation mechanisms to late frost in Vitis vinifera that will deserve further investigation. Our data provides a comprehensive analysis of early phenological events in grapevine, providing novel methods of assessment (F v /F m), varieties possessing escape strategies (i.e. large thermal accumulation to reach BBCH07) and varieties with putative late frost tolerance even after budburst. Overall, further work is ongoing to define the mechanisms underlying late frost tolerance per se and to identify novel varieties with preferable combination of traits.
... To study and systematically collect detailed information about phenological events at the level of individual species, phenological networks such as the European Phenology Network (EPN) (van Vliet et al., 2003), the International Phenological Garden network (IPG) (Renner and Chmielewski, 2022), the USA National Phenology Network (USA-NPN) (National Phenology Network, 2022) or the PhenObs network (Nordt et al., 2021), have been established. Usually, the phenophases recorded by them are leafout, bud break, initial growth for annual plants, expansion of leaves, first flowering day, appearance of fruits, senescence, and leaf abscission (Koch et al., 2007;Morisette et al., 2009;Denny et al., 2014;Berra and Gaulton, 2021;Nordt et al., 2021). ...
Plant phenology plays a vital role in assessing climate change. To monitor this, individual plants are traditionally visited and observed by trained volunteers organized in national or international networks - in Germany, for example, by the German Weather Service, DWD. However, their number of observers is continuously decreasing. In this study, we explore the feasibility of using opportunistically captured plant observations, collected via the plant identification app Flora Incognita to determine the onset of flowering and, based on that, create interpolation maps comparable to those of the DWD. Therefore, the opportunistic observations of 17 species collected in 2020 and 2021 were assigned to “Flora Incognita stations” based on location and altitude in order to mimic the network of stations forming the data basis for the interpolation conducted by the DWD. From the distribution of observations, the percentile representing onset of flowering date was calculated using a parametric bootstrapping approach and then interpolated following the same process as applied by the DWD. Our results show that for frequently observed, herbaceous and conspicuous species, the patterns of onset of flowering were similar and comparable between both data sources. We argue that a prominent flowering stage is crucial for accurately determining the onset of flowering from opportunistic plant observations, and we discuss additional factors, such as species distribution, location bias and societal events contributing to the differences among species and phenology data. In conclusion, our study demonstrates that the phenological monitoring of certain species can benefit from incorporating opportunistic plant observations. Furthermore, we highlight the potential to expand the taxonomic range of monitored species for phenological stage assessment through opportunistic plant observation data.
... In agricultural production, sowing and transplanting periods, disease and insect pest control, irrigation, nutrient management and harvest time are based on the phenological phases of plants (Koch et al., 2007). The phenological study is an essential condition for higher yield and better medicinal material quality. ...
Astragalus membranaceus var. mongholicus (Astragalus) is a perennial medicinal plant belonging to Leguminosae. Its main agronomic and industrial interest is the accumulation of astragaloside IV and calycosin‐7‐O‐β‐D‐glucoside in roots, two components that play crucial pharmacological roles in the finished pharmaceutical products. Phenological research is a prerequisite for improving the yield quality of cultivated medicinal plants. However, there are no standardized phenological studies on Astragalus. To expand phenotyping knowledge on this medicinal plant, researchers and breeders need a universal scale to describe the development of this plant. This study aims to define the phenological growth stages of Astragalus, based on the existing Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale to provide a standard scale for Astragalus, and grown under temperate conditions of production and climate, proposes a disease and pest control reference. This study was conducted in Inner Mongolia, North China. The existing BBCH scale with a three‐digit code was used to define Astragalus's phenological growth codes, supplemented with pictures. Phenological observations were performed twice monthly, based on the developmental stages. The chronology and duration of each stage were also observed and described according to the accumulation of degree days during the growing season. Based on the data obtained, the influence of the average temperature and GDD on the phenophases was evaluated. The phenological description is divided into two principal growth stages: five for vegetative growth (perennating bud, leaf development, formation of branches, main stem elongation and root development), four for reproductive growth (reproductive organ development, flowering, fruit development and fruit maturation), and one for senescence according to the BBCH scale. Seventy secondary growth stages were described within the 10 principal growth stages. Under each secondary growth stage, six mesostages are also taken into account, which contains the distinct patterns of the phenological characteristics in Astragalus varieties and the process of transplanting seedlings. A practical management program for disease and pest control was also proposed by using the BBCH code and the phenological data proposed in this work. Our study presents the first BBCH scale established for Astragalus cultivated in temperate conditions and a chronology of phenological stages based on the accumulation of thermal time, through growing degree day calculation. This work provides a general tool that can be widely used by researchers, breeders, and manufacturers of medicinal materials leading to better agricultural production and scientific communication.
... Rhythms of growth and development of peonies were studied by the phenological observation technique developed earlier [28,29]. For convenience, start dates of the main plant phenophases are presented in phenospectra. ...
Paeonia obovata and Paeonia oreogeton belong to the monotypic family Paeoniaceae. Both are popular as ornamental plants. P. obovata and P. oreogeton have been introduced into Novosibirsk Oblast (Western Siberia) from Primorye (Far East). The aim of the study was to assess their adaptability as well as the effect of seasonal developmental stages on the accumulation of secondary metabolites and reserve substances in the leaves and rhizomes under the conditions of Akademgorodok (Novosibirsk, Russia). According to long-term data (15 years), P. obovata and P. oreogeton complete the entire growth cycle here, including flowering and fruiting. Both species exhibited abundant flowering, but in the first 3 years, P. oreogeton did not bloom; yet under the microclimatic conditions specifically selected for this species (a more shaded area), it started to bloom and fruit yearly. A biochemical analysis (by spectrometric method) of P. obovata and P. oreogeton grown in Akademgorodok showed that the leaves accumulate higher concentrations of flavonols (P. obovata: 1.77%), tannins (P. oreogeton: 16.42%), ascorbic acid (P. oreogeton: 155.2 mg/100 g), and sugars (P. obovata: 20.85%) as compared to the roots. Peony rhizomes contain higher concentrations of protopectins (P. oreogeton: 13.03%), saponins (P. obovata: 21.06%), and starch (P. obovata: 30.20%) than the leaves do. These data can help to increase the levels of these natural compounds in these species. Further investigation into the dynamics of accumulation of biologically active substances in the organs of peonies will help to identify introduced plant species having high biochemical potential for the pharmaceutical industry.
Within the last decade the study of phenology has taken on a new legitimacy in the area of climate change research. A growing literature reveals that a change in the timing of natural events is occurring in a wide range of locations and affecting a wide range of species. Changes in spring have been those most commonly reported, with the emphasis on an advance in spring linked to an increase in temperature. Detection of change in autumn is hampered by a smaller pool of available data, events that are harder to define (such as leaf coloration), and various influencing environmental factors triggering autumnal phases. Despite this, the general pattern may be towards a delay in autumn. Plant, animal and abiotic responses, especially in spring, are quite similar. Thus, it would appear that winter is being squeezed at both ends, and this effect, of increasing the growing season, should become more pronounced in the face of predicted global warming. Copyright © 2002 Royal Meteorological Society.
The pulse of life with the seasons is a classic theme of biology, equally cap turing every man's curiosity about early and late milestones of every year's cycle and the critical physiologist's inquiry into life's subtle signals and responses. Natural historians of ancient and renaissance time as well as today have charted the commonsense facts behind inspired traditions of poetry and practical rules for growing food and fiber. This volume brings together several ways of organizing the basic principles of phenology. These find order in the otherwise overwhelming mass of detail that captures our fleeting attention, like the daily newspaper, and then tends to fade into the overstuffed archives of history. Is this order so obvious and understandable that there is no longer any scien tific challenge to "phenology" as a tradition? Or does apparent simplicity mask a complex and ultimately baffling obstacle to the understanding of seasonality in even those few indicator plants and animals we know best, not to men tion the less known species or races making up the rest of each major land scape unit or ecosystem? Denying both these hasty opinions, we think that this volume well illustrates a range of questions and answers-from soundly established (but not trivial) doctrine to exciting inquiry about how ecosystems are organized.
This Working Group II volume brings us completely up-to-date on the
vulnerability of socio-economic and natural systems to climate change.
This paper presents the reconstructed severity of winter seasons in the northern Baltic Sea on the basis of historical time series of ice break-up at the port of Riga (1529-1990). The winter seasons are classified as mild, average severe. Results of statistical analysis of time series of the date of ice break-up arranged according to the severity of winter seasons are given. A decreasing trend of about 2.0 d century(-1) for the time series of ice break-up dates for severe winters is detected with statistical significance at the 99.9% level; for the mild and average winter seasons the trends are statistically insignificant.