Flowering Phenology Research Articles

Flowering effort and reproductive phenology of intertidal colonizing Zostera marina

The seagrass Zostera marina can inhabit the intertidal where the variable environmental conditions mean that the seagrass meadows are frequently in a continuous state of colonization, influencing, among others, their phenology and flowering effort. This could be especially notable in the southern limits of the species' distribution, where light exposure and temperature reach extreme values during the warmer seasons. In this study, we evaluate the flowering effort, phenology, photophysiology and vegetative development of recent colonizing Z. marina patches inhabiting the intertidal of a lagoon located near its southern limit of distribution, in the Ria de Aveiro (Portugal). To evaluate the effects of low tide exposure, tidepool and emerged seagrass patches were selected. Results showed short-lived differences in the phenology of the flowering of the patches and in their vegetative development, but in general, the photosynthetic activity, timing of flowering, densities of spathes and flowering shoots were similar in emerged and tidepool patches throughout the entire reproductive period (from June to August). The spathes per flowering shoot and the spathe and flowering shoot densities per unit of area of the colonizing patches were comparable to that obtained in other perennial intertidal meadows of this species and its timing was adjusted to that which occurred in areas of similar latitudes, ending when the temperature exceeded 25 °C. These results imply that intertidal colonizing Z. marina patches can flowering similarly to perennial meadows, regardless of whether or not they are submerged in pools at low tide, which implies a great adaptability of the species to intertidal areas. However, to fully understand the reproductive capacity of Z. marina in the Ria de Aveiro, future studies should determine the capacity of these flowers to form mature seeds, as well as their ability to germinate naturally in the area.

Spatial isolation impacts pollinator visitation and reproductive success of a threatened self-incompatible Mediterranean tree

Pollination service is crucial to achieve successful plant sexual reproduction and long-term population persistence. This pollination service can be affected by plant conspecific density and also by intrinsic features of individuals related to their flowering phenology and floral display. However, studies examining intrinsic and extrinsic traits on pollinator visitation and reproductive success of Mediterranean trees with limited reproduction are still scarce. We analyzed the effects of plant isolation, flowering phenology, flower weight and tree size on flower visitation probability, flowering patch visitation probability, fruit set and crop size. To this end, we intensively monitored pollinator visitation and fruit production of 67 (in 2019) and 73 (in 2020) Pyrus bourgaeana Decne trees within a threatened Mediterranean population. Our results revealed that isolated individuals received more pollinators than those on conspecific aggregations, suggesting intraspecific competition for pollinators in dense flowering neighborhoods. However, fruit set was higher in trees close to flowering conspecifics despite having fewer visits from pollinators, suggesting pollen limitation but not pollinator limitation in spatially isolated trees. Interestingly, we found increased crop sizes in spatially isolated trees which could be related to reduced intraspecific competition for resources in low-density neighborhoods (water, nutrients) and/or to higher reproductive investment (i.e. higher flower production). Overall, our results indicated pollen but not pollinator limitation in spatially isolated trees. Under this scenario of sexual reproduction mediated by pollinators, our findings stress the relevance of individuals' spatial distribution for self-incompatible trees exhibiting low individuals’ densities.

Disorder or a new order: How climate change affects phenological variability.

Advancing spring phenology is a well documented consequence of anthropogenic climate change, but it is not well understood how climate change will affect the variability of phenology year to year. Species' phenological timings reflect the adaptation to a broad suite of abiotic needs (e.g., thermal energy) and biotic interactions (e.g., predation and pollination), and changes in patterns of variability may disrupt those adaptations and interactions. Here, we present a geographically and taxonomically broad analysis of phenological shifts, temperature sensitivity, and changes in interannual variability encompassing nearly 10,000 long-term phenology time series representing more than 1000 species across much of the Northern Hemisphere. We show that the timings of leaf-out, flowering, insect first-occurrence, and bird arrival were the most sensitive to temperature variation and have advanced at the fastest pace for early-season species in colder and less seasonal regions. We did not find evidence for changing variability in warmer years in any phenophase groups, although leaf-out and flower phenology have become moderately but significantly less variable over time. Our findings suggest that climate change has not to this point fundamentally altered the patterns of interannual phenological variability.

Machine learning methods for efficient and automated in situ monitoring of peach flowering phenology

Accurate knowledge of peach flowering phenology is essential for scheduling precise irrigation and managing artificial pollination for breeding. However, in situ monitoring of peach flowering phenology is laborious and challenging. This study divided peach flowering phenology into eight stages covering inflorescence emergence and flowering using BBCH scales. Web-connected recording cameras and weather stations automatically-collected flower images and meteorological data from three peach cultivars. Daily variables, including area proportion of specific color ranges in the images, temperature, illuminance and heat/chilling requirement data were applied for training and testing four machine learning models: random forest (RF), support vector machine (SVM), naïve Bayes (NB), and k-Nearest Neighbors (KNN). Grid tuning and 10-fold cross-validations were conducted on these models to determine the optimal method for identifying peach flowering phenological stages. The RF model obtained highest optimal F1 score of 98.82 % (harmonic average of model accuracy and recall) among the models on the testing set. The area proportion of specific color ranges in the real-time images are essential for model performance. Heat requirement data (biological growth time and growing degree days) can improve the overall accuracy. The classification accuracy at different BBCH phenological stages of the three cultivars is acceptable for real-time monitoring of peach flowering phenology. These are applicable for peach breeding, heat stress management, and irrigation scheduling. The RF model also shows acceptable accuracy with flower images and public meteorological data input, which reveals the extendibility for phenology monitoring of other trees or crops.

Herbarium Specimens May Provide Biased Flowering Phenology Estimates for Dioecious Species

Premise of research. Measuring phenology from herbarium specimens has become a widely used, powerful method for investigating the effects of climate change on plants across space, time, and phylogeny. However, it is not known whether and how biases in plant collecting might affect conclusions, particularly for dioecious species.Methodology. We examined the effects of spring temperature and latitude on the flowering phenology of male and female blunt-lobed spicebush (Lindera obtusiloba Blume) plants from across East Asia using 88 herbarium specimens and digitized photographs collected from 1918 to 2018.Pivotal results. Temperature and latitude did not affect the flowering phenology of either sex when analyzed separately. Surprisingly, however, female flowering plants were collected on average 25 d later than male plants. This difference is likely due to male plants being preferentially collected during the flowering season (with showy but more ephemeral flowers) and female plants being collected after the peak flowering season (with nonreceptive flowers persisting later into the season).Conclusions. Researchers investigating phenology using herbarium specimens need to be aware of possible collecting bias in dioecious species and species with persistent flowers. Herbarium collectors and photographers should sample both male and female plants.

The FloRes Database: A floral resources trait database for pollinator habitat-assessment generated by a multistep workflow.

The decline of pollinating insects in agricultural landscapes proceeds due to intensive land use and the associated loss of habitat and food sources. The feeding of those insects depends on the spatial and temporal distribution of nectar and pollen as food resource. Hence, to protect insect biodiversity, a spatio-temporal assessment of food quantity of their habitats is necessary. Therefore, sufficient data on traits of floral resources are required. As floral resources' traits of plants are important to quantify food availability, we present two databases, the FloRes Database (Floral Resources Database) and the raw database, from where FloRes was derived. Both databases contain the plant traits: (1) flowering period, (2) floral-unit density per day, (3) nectar volume per floral unit per day, (4) sugar content per floral unit, (5) sugar concentration in nectar, (6) pollen mass or volume per floral unit and per day, (7) protein content of pollen and (8) corolla depth. All traits were sampled from literature and online databases. The raw database consists of 702 specified plant species, 138 unspecified species 37 species (spec., sp), 22 species pluralis (spp) and, for 79, only the genus was identified) and two species complexes (agg.). Those 842 taxa belong to 488 genera and 102 families. Finally, only 27 taxa have a complete set of traits, too few for a sufficient assessment of spatio-temporal availability of floral food-resources.As information on floral resources is scattered throughout many publications with different units, we also present our multistep workflow implemented in five consecutive R-scripts. The multistep workflow standardises the trait units of the raw database to comparable entities with identical units and aggregates them on a reasonable taxonomic level into the second application database, the FloRes Database. Finally, the FloRes Database contains aggregated information of traits for 42 taxa and, when corolla depth is excluded, for 72 taxa.This is the first attempt to gather these eight traits from different literature sources into one database with a multistep workflow. The publication of the multistep workflow enables the users to extend the FloRes Database on their own demands with other literature data or newly-gathered data to improve quantification of food resources. Especially, the combination of pollen, nectar and the open flowers per square metre is, as far as we know, a novelty.The FloRes Database can be used to evaluate the quantity of food-resource habitats available for pollinators, for example, to compare seed mixtures of agri-environmental measures, such as flower strips, considering flower phenology on a daily basis.

Multi-class detection of kiwifruit flower and its distribution identification in orchard based on YOLOv5l and Euclidean distance

Asynchrony of kiwifruit flowering time results in different flower phenological stages in canopy at the same time. Pollination quality of flowers is influenced by their phenological stages, while their distributions determine fruit distributions and influence kiwifruit quality and yield. Thus, it’s necessary to find suitable flowers to be pollinated based on flower phenology and its distribution. However, influences of flower phenology and flower distribution were not considered in most previous studies about robotic pollination of kiwifruit, where pollination of all open flowers was indiscriminate. Therefore, a method was proposed for multi-class detection of kiwifruit flower and its distribution identification in orchard, which was based on You Only Look Once version 5 large (YOLOv5l) and Euclidean distance. According to kiwifruit flower phenology, kiwifruit flowers were classified into 10 classes to find suitable flowers for pollination, while flower cluster and branch junction were divided into 4 classes for obtaining flower distributions. All classes were manually labeled by rectangular bounding boxes for training and testing. Considering high detection accuracy requirements with small model size, YOLOv5l was applied to do transfer learning for multi-class detection of kiwifruit flower. Then, pixels coordinate of multi-class objects and their corresponding Euclidean distances could be gained. Finally, flower distributions in canopy were obtained by matching method. Total mean Average Precision (mAP) was 91.60 % in YOLOv5l, while the mAP of multi-class flower (10 classes) was 93.23 %, which was 5.70 % higher than that of the other 4 classes. Matching accuracy (MA) of flowers matching flower clusters was up to 97.60 %. Moreover, MA of flower cluster matching branch junction (96.20 %) and total MA (93.30 %) increased by 1.20 % and 1.00 % based on improved matching method, respectively. Total processing speed of multi-class flower detection and its distribution identification was 112.46 ms per image including 15.50 ms for image detection by YOLOv5l. Results showed that multi-class kiwifruit flowers and relative flower distributions could be fast and accurately obtained for further selecting suitable flowers for robotic pollination.

Reproductive Biology of the Two Varieties of Anacyclus pyrethrum L.-Anacyclus pyrethrum var. pyrethrum (L.) Link and Anacyclus pyrethrum var. depressus (Ball.) Maire-An Endemic Endangered Species.

The reproductive system is essential for the structuring and transmission of genetic diversity. Understanding the reproductive biology of threatened endemic species is considered to be a crucial element for the implementation of effective conservation strategies. Given the lack of information and the insufficient state of knowledge on the reproductive system of Anacyclus pyrethrum L., a threatened medicinal species endemic to Morocco, we are the first to study the reproductive biology of two varieties of Anacyclus pyrethrum L.: Anacyclus pyrethrum var. pyrethrum (L.) Link and Anacyclus pyrethrum var. depressus (Ball.) Maire. The reproductive biology of the two varieties was examined in detail by studying the development of the inflorescence, phenology of flowering, breeding system, pollinators, production, and seed dispersal. The experimental results described in this work suggest that Anacyclus pyrethrum L. is a gynomonic species, with a mixed autogamy–allogamy reproductive regime with a high predominance of allogamy. It appears to be partially self-incompatible, with allogamy rates for Anacyclus pyrethrum var. depressus (Ball.) Maire and Anacyclus pyrethrum var. pyrethrum (L.) Link of 78.70% and 79.01%, respectively. It depends on pollination vectors to produce a large number of seeds. This study on the breeding system of Anacyclus pyrethrum L. provides a tool for developing management strategies and adequate conservation measures.

Agronomic evaluation of shade tolerance of 16 spring Camelina sativa (L.) Crantz genotypes under different artificial shade levels using a modified membership function.

Camelina [Camelina sativa (L.) Crantz] is currently gaining considerable attention as a potential oilseed feedstock for biofuel, oil and feed source, and bioproducts. Studies have shown the potential of using camelina in an intercropping system. However, there are no camelina genotypes evaluated or bred for shade tolerance. The objective of this study was to evaluate and determine the shade tolerance of sixteen spring camelina genotypes (growth stage: BBCH 103; the plants with 4–5 leaves) for intercropping systems. In this study, we simulated three different shade levels, including low (LST), medium (MST), and high shade treatments (HST; 15, 25, and 50% reduction of natural light intensity, respectively), and evaluated the photosynthetic and physiological parameters, seed production, and seed quality. The mean chlorophyll pigments, including the total chlorophyll and chlorophyll a and b across the 16 genotypes increased as shade level increased, while the chlorophyll fluorescence parameter Fv/Fm, chlorophyll a/b, leaf area, the number of silicles and branches plant−1 decreased as shade level increased. The first day of anthesis and days of flowering duration of camelina treated with shade were significantly delayed and shortened, respectively, as shade increased. The shortened lifecycle and altered flowering phenology decreased camelina seed yield. Additionally, the shade under MST and HST reduced the seed oil content and unsaturated fatty acids, but not saturated fatty acids. The dendrograms constructed using the comprehensive tolerance membership values revealed that CamK9, CamC4, and ‘SO-40’ were the relatively shade-tolerant genotypes among the 16 camelina genotypes. These camelina genotypes can grow under the shade level up to a 25% reduction in natural light intensity producing a similar seed yield and seed oil quality, indicating the potential to intercrop with maize or other small grain crops. The present study provided the baseline information on the response of camelina genotypes to different shade levels, which would help in selecting or breeding shade-tolerant genotypes.

Citizen science helps predictions of climate change impact on flowering phenology: A study on Anemone nemorosa

Rapidly increasing resources of citizen science databases (CS) collecting information on species occurrence are increasingly useful as a data source for global biodiversity research. The photos attached to records allow to verify the species identification and identify its phenological phase. We assessed CS data's usefulness in large-scale phenological research on temperate forest understory species, using a common and widely distributed in Europe: Anemone nemorosa. We analyzed 9804 photos from CS databases. We found 177 15’ grid cells with ≥10 observations of flowering plants for bootstrap estimation of flowering onset and offset. We predicted flowering dates for the present and future climate according to Shared Socioeconomic Pathways averaged over four global circulation models for 2040–60 and 2060–80 across A. nemorosa natural range. The estimated magnitude of change in the flowering phenology for both future periods is comparable. The estimated flowering onset median was 24–41 days earlier while flowering offset median was 19–34 days earlier than predicted for the current climate. We estimated a flowering length median of up to 7 days longer than for current climatic conditions. The predicted changes in the phenology of flowering will not significantly change the duration of flowering but will accelerate onset of this phenophase by about one month. Our study showed that CS might provide a valuable dataset that allows for developing reliable models of plant phenology. It was possible due to a large sample size, resulting from species characteristics: flowering when wider audience is interested in searching spring indicators, easy identification and abundant occurrence. We demonstrated that using dataset of such spatiotemporal extent can cautiously be used for development of future predictions. Such approach allows for evaluating flowering phenology in the understory and to improve understanding the consequences of climate change for biodiversity and functioning of temperate ecosystems.

High Temperature and Elevated CO2 Modify Phenology and Growth in Pepper Plants

The aim of this study was to determine the effect of temperature and CO2 on seed emergence, seedling quality, and phenological stage of Capsicum chinense and Capsicum annum cultivated in four controlled growth chambers (C1: 30 °C and 400 μmol CO2 mol−1; C2: 40 °C and 1200 μmol CO2 mol−1; C3: 30 °C and 1200 μmol CO2 mol−1; C4: 40 °C and 400 μmol CO2 mol−1). Neither temperature nor elevated CO2 influenced seed emergence, although differences were observed in seedling mortality, with high temperature affecting seedling survival in both species; the mortality rate at 40 °C was 20 and 53% in C. annuum and 45 and 58% in C. chinense at 400 and 1200 μmol CO2 mol−1, respectively. Differences were also observed in growth parameters, where positive effects were observed on leaf area, which reached 45.9 cm2 in C. annuum and 23.9 cm2 in C. chinense with elevated CO2 at 30 °C, but negative effects were observed with high temperature. CO2 enrichment increased flower and fruit production per plant. However, high temperature delayed flower phenology, increased flower abortion and inhibited fruit set. Elevated CO2 counteracted the detrimental effects of high temperature on growth parameters and flower number, but this was not sufficient to prevent flower abortion and the detrimental morphological characteristics of fruit caused by a temperature of 40 °C.

Phylogeography reveals the origin of the two phenological forms of large blue, Phengaris arion (Lepidoptera: Lycaenidae)

Abstract Our main goal was to investigate the phylogeography of the butterfly Phengaris arion to reveal the evolutionary origin of its ‘spring’ and ‘summer’ forms. Molecular analyses based on highly variable microsatellites, together with Wolbachia screening, were carried out on 34 populations in Europe. We found three well-defined genetic lineages of different origins: the Apennine, the central and the eastern. The highly distinct Apennine lineage is limited by the Alps and evaluated as an Evolutionary Significant Unit (ESU). Therefore, the taxon name ligurica, described from the Ligurian coast (Italy), should not be applied to denote the ‘summer form’ of the Pannonian region. The central lineage is limited by the Carpathians and the most eastern ranges of the Alps, and lacks major range fluctuations related to glaciations, although there is evidence for extra-Mediterranean refugia in the Carpathian Basin. The eastern clade could have had refugia in central Asia. Our results exclude the potential allopatric origin of the ‘spring’ and ‘summer’ arion, and support the hypothesis that the existence of the two forms could be a result of local adaptation to the distinctive phenology of host plant flowering which is manifested in the genetic differences between them. Wolbachia infection has been ruled out as a driver of sympatric speciation in P. arion.

Flower colour and flowering phenology mediate plant–pollinator interaction assembly in a diverse co‐flowering community

Abstract Uncovering the role of competition and facilitation in community assembly is central for developing a predictive understanding of the forces that organize biodiversity. Standard trait‐based approaches however rely on detection of only one assembly mechanism (competition or facilitation) along a single trait even though pollinator‐mediated plant–plant interactions can be structured along multiple phenotypic, phenological and ecological traits. We evaluated plant species distribution along multiple phenotypic and ecological traits (flower colour, flowering time, pollinator sharing) and described an entire co‐flowering community as a set of modules with unique patterns of assembly, to test predictions regarding the relative contribution of competition and facilitation to the assembly of a diverse co‐flowering community. We show a modular pattern of flower colour assembly. Flower colour modules differ in their spectral reflectance patterns including colour hue and saturation. Within modules, however, species are differentially assembled along phenological and ecological traits (pollinator sharing) depending on the main pollinator group visiting plant species within each module. Results suggest different trait assembly patterns within individual trait‐modules in the same co‐flowering community and that different trait‐patterns can result from the same type of ecological interaction. This study reveals empirical evidence of community assembly along multiple axes of trait differentiation and raises caution when interpreting assembly patterns based on a single trait. Read the free Plain Language Summary for this article on the Journal blog.

Monitoring of cherry flowering phenology with Google Trends.

Google Trends (GT) is an online tool designed for searching for changes over time. We assessed its use for evaluating changes in the timing of cherry flowering phenology, which is of intense interest to Japanese people. We examined the relationship between time-series of relative search volume (RSV: relative change in search requests over time obtained from the GT access engine) and cherry flowering information published on websites (as ground truth) in relation to three famous ancient cherry trees. The time-series of RSV showed an annual bell-shaped seasonal variability, and the dates of the maximum RSV tended to correspond to the dates of full bloom. Our results suggest that GT allows monitoring of multiple famous cherry flowering sites where we cannot obtain long-term flowering data to evaluate the spatiotemporal variability of cherry flowering phenology.

Climate change is associated with increased allocation to potential outcrossing in a common mixed mating species.

PremiseAlthough the balance between cross‐ and self‐fertilization is driven by the environment, no long‐term study has documented whether anthropogenic climate change is affecting reproductive strategy allocation in species with mixed mating systems. Here, we test whether the common blue violet (Viola sororia; Violaceae) has altered relative allocation to the production of potentially outcrossing flowers as the climate has changed throughout the 20th century.MethodsUsing herbarium records spanning from 1875 to 2015 from the central United States, we quantified production of obligately selfing cleistogamous (CL) flowers and potentially outcrossing chasmogamous (CH) flowers by V. sororia, coupled these records with historic temperature and precipitation data, and tested whether changes to the proportion of CL flowers correlate with temporal climate trends.ResultsWe find that V. sororia progressively produced lower proportions of CL flowers across the past century and in environments with lower mean annual temperature and higher total annual precipitation. We also find that both CL and CH flower phenology has advanced across this time period.ConclusionsOur results suggest that V. sororia has responded to lower temperatures and greater water availability by shifting reproductive strategy allocation away from selfing and toward potential outcrossing. This provides the first long‐term study of how climate change may affect relative allocation to potential outcrossing in species with mixed mating systems. By revealing that CL flowering is associated with low water availability and high temperature, our results suggest the production of obligately selfing flowers is favored in water limited environments.

Automated identification of diverse Neotropical pollen samples using convolutional neural networks

Abstract Pollen is used to investigate a diverse range of ecological problems, from identifying plant–pollinator relationships to tracking flowering phenology. Pollen types are identified according to a set of distinctive morphological characters which are understood to capture taxonomic differences and phylogenetic relationships among taxa. However, categorizing morphological variation among hyperdiverse pollen samples represents a challenge even for an expert analyst. We present an automated workflow for pollen analysis, from the automated scanning of pollen sample slides to the automated detection and identification of pollen taxa using convolutional neural networks (CNNs). We analysed aerial pollen samples from lowland Panama and used a microscope slide scanner to capture three‐dimensional representations of 150 sample slides. These pollen sample images were annotated by an expert using a virtual microscope. Metadata were digitally recorded for ~100 pollen grains per slide, including location, identification and the analyst's confidence of the given identification. We used these annotated images to train and test our detection and classification CNN models. Our approach is two‐part. We first compared three methods for training CNN models to detect pollen grains on a palynological slide. We next investigated approaches to training CNN models for pollen identification. Because the diversity of pollen taxa in environmental and palaeontological samples follows a long‐tailed distribution, we experimented with methods for addressing imbalanced representation using our most abundant 46 taxa. We found that properly weighting pollen taxa in our training objective functions yielded improved accuracy for individual taxa. Our average accuracy for the 46‐way classification problem was 82.3%. We achieved 89.5% accuracy for our 25 most abundant taxa. Pollen represents a challenging visual classification problem that can serve as a model for other areas of biology that rely on visual identification. Our results add to the body of research demonstrating the potential for a fully automated pollen classification system for environmental and palaeontological samples. Slide imaging, pollen detection and specimen identification can be automated to produce a streamlined workflow.

Spatial and Temporal Distribution Characteristics of Flower-Viewing Tourism and Its Influencing Factors in China

Despite the rapid development of flower-viewing tourism in China in recent years, there is almost no systematic research on it. Therefore, this study analyzes the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China using the spatial statistical analysis methods and the geographic detector method. The study uses the Point-of-Interest data of flower-viewing tourist attractions from networks such as Qunar and Ctrip, the flower observation data from China Phenological Observation Network, Chinese network news, and Weibo, and the statistical data from yearbooks. The results are as follows: 1) The spatial attribution type of flower-viewing tourism in China is aggregated into areas, including two high-density aggregated areas, three medium-density aggregated areas, and one general-density aggregated area. Furthermore, five major types of flower-viewing tourist attractions have formed several aggregated areas. 2) The time of flower viewing in China starts from about February and lasts about eight months till October each year. Florescence and flowering time of different ornamental flowers in different regions are different. 3) The spatial and temporal distribution characteristics of flower-viewing tourism in China are mainly affected by ornamental flower phenology, spatial distribution characteristics of flower-viewing resources, regional permanent population size, youth population size, female population size, regional GDP, and added value of the tertiary sector. These conclusions clarify the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China. They could provide a scientific basis and useful reference for the coordination and sustainable development of regional flower-viewing tourism in China.

Quantifying the importance of day length in process-based models for the prediction of temperate spring flowering phenology

Owing to climate change and frequent extreme weather events, changes in spring flowering phenology have been observed in temperate forests. The flowering time response to climate change is divergent among species and is difficult to predict due to the complexity of flowering mechanisms. To compare the effects of spring warming, winter chilling, and day length on spring flowering time, we evaluated eight process-based models (two types of forcing models, two types of chilling-forcing models, and four models with the effect of day length added to the aforementioned four models). We used flowering data of seven temperate species (Cornus officinalis, Rhododendron mucronulatum, Forsythia koreana, Prunus yedoensis, Rhododendron yedoense f. poukhanense, Rhododendron schlippenbachii, and Robinia pseudoacacia) observed in nine different arboretums in South Korea over 9 years. Generally, the forcing model performed better than the sequential chilling-forcing model, regardless of the species. The performance gap between the models was reduced when day length term was included in model, but the chilling-forcing model did not outperform the forcing model. The effect of day length on flowering time differed depending on the species. Prunus yedoensis, which had a particularly low warming sensitivity compared to other species, was more dependent on day length than other species. On the other hand, day length had little effect on the flowering time of Robinia pseudoacacia and Cornus officinalis, mostly found in the early successional stage. These findings imply that the effect of chilling on flowering time would be minor for the seven species inhabiting the warm-temperate forest, and the effect of day length on flowering time was species-specific and dependent on species' temperature (warming) sensitivity and life strategy. In the future warm climate, the flowering time of day length sensitive species would not advance significantly, which may result in a phenological mismatch and endanger their life.

Greater responses of flower phenology ofKobresia pygmaeacommunity to precipitation addition than to constant and stepwise warming

AbstractThere is a debate about unmatched results between manipulative warming using constant warming rates every year (CW) and long-term observations warming affect temperature sensitivity of flowering phenology. This may be because long-term observations represent the actual yearly increase in temperature (i.e. a yearly stepwise warming rate per year, SW) which would differ from CW and their effects would be regulated by precipitation alteration. We conducted a warming experiment with CW (temperature increase by +1 °C and sustained this elevated temperature for the duration of the study) and SW (temperature increase by + 0.25 °C progressively each year) with precipitation addition in an alpine grassland for four years. Our results showed that neither warming rate affected community flowering phenology. However, precipitation addition advanced onsets of flowering for early-spring flowering (ESF) and mid-summer flowering (MSF) groups, and advanced the end date of flowering for ESF but delayed it for the MSF group. Therefore, flowering duration remained stable for the ESF group and prolonged for the MSF group, and further prolonging the flowering duration of the community. There were no interactions between warming rates and precipitation addition on the community’s flowering phenology. A severe drought in a year significantly decreased the maximal number of community flowers in the following year. Therefore, a change in precipitation has a greater effect than warming on the community flowering phenology in the semi-arid alpine grassland.

Increased Coastal Nutrient Loading Enhances Reproductive Intensity of Zostera marina: Implications for Seagrass Meadow Resilience

Because sexual reproduction is essential for the establishment and persistence of seagrass meadows, flowering intensity is an important trait that influences the resilience and stability of seagrass populations. Although the effects of excessive coastal nutrient loading on seagrass vegetative growth have been extensively documented, the effects on seagrass reproductive phenology and intensity remain unclear. To examine the reproductive responses of seagrass populations to increased coastal nutrient loading, the flowering phenology and intensity of Zostera marina were compared between sites with high-nutrient, low-light conditions (Deukryang Bay and Dongdae Bay) and low-nutrient, high-light conditions (Koje Bay) on the southern coast of Korea. Nutrient contents of the above- and below-ground tissues of Z. marina reflected in situ nutrient and light availability at the study sites. Reproductive shoot density and biomass, as well as flowering frequency and reproductive effort, were much higher (1.5–4.6-fold) at the high-nutrient, low-light study sites of Deukryang Bay and Dongdae Bay than at the low-nutrient, high-light site of Koje Bay. Consequently, potential seed production was higher in Deukryang Bay and Dongdae Bay than in Koje Bay. Chronic high-nutrient and low-light conditions significantly increased the reproductive intensity of Z. marina, supporting the persistence and resilience of Z. marina populations. The results of this study could provide insights into the conservation and management of seagrass meadows under increased coastal nutrient loading.