Emerging opportunities and challenges in phenology: a review

Long-term trends in global flowering phenology

Flowering phenology is an indicator of the impact of climate change on natural systems. Anthropogenic climate change has progressed over more than two centuries, but ecological studies are mostly short in comparison. Here we harness the large-scale digitization of herbaria specimens to investigate temporal trends in flowering phenology at a global scale. We trained a convolutional neural network model to classify images of angiosperm herbarium specimens as being in flower or not in flower. This model was used to infer flowering across 8 million specimens spanning a century and global scales. We investigated temporal trends in mean flowering date and flowering season duration within ecoregions. We found high diversity of temporal trends in flowering seasonality across ecoregions with a median absolute shift of 2.5 d per decade in flowering date and 1.4 d per decade in flowering season duration. Variability in temporal trends in phenology was higher at low latitudes than at high latitudes. Our study demonstrates the value of digitized herbarium specimens for understanding natural dynamics in a time of change. The higher variability in phenological trends at low latitudes likely reflects the effects of a combination of shifts in temperature and precipitation seasonality, together with lower photoperiodic constraints to flowering.

Digital Repeat Photography Application for Flowering Stage Classification of Selected Woody Plants

Digital repeat photography is currently applied mainly in geophysical studies of ecosystems. However, its role as a tool that can be utilized in conventional phenology, tracking a plant's seasonal developmental cycle, is growing. This study's main goal was to develop an easy-to-reproduce, single-camera-based novel approach to determine the flowering phases of 12 woody plants of various deciduous species. Field observations served as binary class calibration datasets (flowering and non-flowering stages). All the image RGB parameters, designated for each plant separately, were used as plant features for the models' parametrization. The training data were subjected to various transformations to achieve the best classifications using the weighted k-nearest neighbors algorithm. The developed models enabled the flowering classifications at the 0, 1, 2, 3, and 5 onset day shift (absolute values) for 2, 3, 3, 2, and 2 plants, respectively. For 9 plants, the presented method enabled the flowering duration estimation, which is a valuable yet rarely used parameter in conventional phenological studies. We found the presented method suitable for various plants, despite their petal color and flower size, until there is a considerable change in the crown color during the flowering stage.

The Relationship Between Phenological Characteristics and Life Forms Within Temperate Semi-Natural Grassland Ecosystems in the Central Himalaya Region of India

The seasonal phenological segregation observed among various species within a plant community can be interpreted as a form of niche differentiation that facilitates the coexistence of these species. In the present study, life forms and phenological attributes of dominant plant species in temperate semi-natural grasslands of Central Himalaya, India, were assessed between January 2022 and December 2022. This study was carried out in three sites in different forest zones, viz. oak, cypress and pine. In each site, plots measuring 0.5 hectares were established and phenological assessments were conducted within each of these plots. A total of 50, 36, and 49 herbaceous species were identified in the grasslands of oak, cypress and pine zones, respectively, with these species categorized into five distinct life form classes. In the grasslands of both oak and pine zones, hemicryptophytes emerged as the predominant life form, whereas in the cypress zone grasslands, it was found that chamaephytes take precedence. The differences observed in the classifications of life forms can be ascribed to the geographical distribution and the biotic interactions present in these sites. The three grasslands exhibit comparable climatic conditions and day lengths, resulting in no significant variations in soil temperature, light intensity or overall climatic factors. The majority of species commenced their flowering phase during the monsoon season, attributed to the favorable conditions characterized by warm, humid weather and adequate soil moisture. Various phenological events, including germination, growth, and senescence, are significantly affected by weather and climate, and their timing subsequently influences ecosystem processes in a reciprocal manner. This study provides valuable foundational data for ecological and environmental research, aiding in the comparison and distinction of plant compositions across the Himalayas and its ecosystems.

Phenological Shifts Since 1830 in 29 Native Plant Species of California and Their Responses to Historical Climate Change

Climate change is affecting Mediterranean climate regions, such as California. Retrospective phenological studies are a useful tool to track biological response to these impacts through the use of herbarium-preserved specimens. We used data from more than 12,000 herbarium specimens of 29 dominant native plant species that are characteristic of 12 broadly distributed vegetation types to investigate phenological patterns in response to climate change. We analyzed the trends of four phenophases: preflowering (FBF), flowering (F), fruiting (FS) and growth (DVG), over time (from 1830 to 2023) and through changes in climate variables (from 1896 to 2023). We also examined these trends within California's 10 ecoregions. Among the four phenophases, the strongest response was found in the timing of flowering, which showed an advance in 28 species. Furthermore, 21 species showed sequencing in the advance of two or more phenophases. We highlight the advances found over temperature variables: 10 in FBF, 28 in F, 17 in FS and 18 in DVG. Diverse and less-consistent results were found for water-related variables with 15 species advancing and 11 delaying various phenophases in response to decreasing precipitation and increasing evapotranspiration. Jepson ecoregions displayed a more pronounced advance in F related to time and mean annual temperature in the three of the southern regions compared to the northern ones. This study underscores the role of temperature in driving phenological change, demonstrating how rising temperatures have predominantly advanced phenophase timing. These findings highlight potential threats, including risks of climatic, ecological, and biological imbalances.

A General Model for the Seasonal to Decadal Dynamics of Leaf Area

Leaf phenology, represented at the ecosystem scale by the seasonal dynamics of leaf area index (LAI), is a key control on the exchanges of CO2, energy, and water between the land and atmosphere. Robust simulation of leaf phenology is thus important for both dynamic global vegetation models (DGVMs) and land-surface representations in climate and Earth System models. There is no general agreement on how leaf phenology should be modeled. However, a recent theoretical advance posits a universal relationship between the time course of "steady-state" gross primary production (GPP) and LAI-that is, the mutually consistent LAI and GPP that would pertain if weather conditions were held constant. This theory embodies the concept that leaves should be displayed when their presence is most beneficial to plants, combined with the reciprocal relationship of LAI and GPP via (a) the Beer's law dependence of GPP on LAI, and (b) the requirement for GPP to support the allocation of carbon to leaves. Here we develop a global prognostic LAI model, combining this theoretical approach with a parameter-sparse terrestrial GPP model (the P model) that achieves a good fit to GPP derived from flux towers in all biomes and a scheme based on the P model that predicts seasonal maximum LAI as the lesser of an energy-limited rate (maximizing GPP) and a water-limited rate (maximizing the use of available precipitation). The exponential moving average method is used to represent the time lag between leaf allocation and modeled steady-state LAI. The model captures satellite-derived LAI dynamics across biomes at both site and global levels. Since this model outperforms the 15 DGVMs used in the TRENDY project, it could provide a basis for improved representation of leaf-area dynamics in vegetation and climate models.

Improved Modeling of Vegetation Phenology Using Soil Enthalpy

Many vegetation phenological models predominantly rely on temperature, overlooking the critical roles of water availability and soil characteristics. This limitation significantly impacts the accuracy of phenological projections, particularly in water-limited ecosystems. We proposed a new approach incorporating soil enthalpy-a comprehensive metric integrating soil moisture, temperature, and texture-to improve phenological modeling. Using an extensive dataset combining FLUXNET observations, solar-induced fluorescence (SIF), and meteorological data across the Northern Hemisphere (NH), we analyzed the relationship between soil enthalpy and vegetation phenology from 2001 to 2020. Our analysis revealed significant temporal trends in soil enthalpy that corresponded with changes in leaf onset date (LOD) and leaf senescence date (LSD). We developed and validated a new soil enthalpy-based model with optimized parameters. The soil enthalpy-based model showed particularly strong performance in autumn phenology, improving LSD simulation accuracy by at least 15% across all vegetation types. For shrub and grassland ecosystems, LOD projections improved by more than 12% compared to the temperature-based model. Future scenario analysis using CMIP6 data (2020-2054) revealed that the temperature-based model consistently projects earlier LOD and later LSD compared to the soil enthalpy-based model, suggesting potential overestimation of growing season length in previous studies. This study establishes soil enthalpy as a valuable metric for phenological modeling and highlights the importance of incorporating both water availability and soil characteristics for more accurate predictions of vegetation phenology under changing climatic conditions.

Landscape-level variation in spring leaf phenology is driven by precipitation seasonality in the Mexican red oak Quercus castanea

Water availability is one of the essential factors that determine the distribution of plant species, as well as their ecological strategies. The study of leaf phenology, in conjunction with other leaf traits of an ecological nature, such as functional traits, makes it possible to determine the life history strategies of plant species and their variation along environmental gradients, which in turn influences the demographic rates of populations. In the present study, we analysed the effect of water availability at the landscape scale on spring leaf phenology and foliar traits such as leaf mass per area (LMA) and leaf thickness (LT) in the oak species Quercus castanea from a tropical latitude in central-western Mexico. Six sites were selected in the Cuitzeo basin, Michoacán, across a water availability gradient, ranging from 766 mm to 1145 mm of mean annual precipitation. Leaf samples were collected from 10 adult trees at each site and LT and LMA were estimated. Leaf phenology was monitored for each tree every two weeks between March and July for two consecutive years, 2021 and 2022, alongside soil moisture measurements. Temperature and precipitation variables for the two study years were obtained from meteorological stations and long-term bioclimatic variables from the Worldclim database. Significant spatial and temporal variation in leaf phenology was observed. Earlier leaf development and shorter development times were observed with increased soil moisture in March and April, and with higher precipitation in October of the previous year. Also, sites with long-term higher precipitation seasonality and with lower precipitation of the warmest quarter showed longer development times. A positive association between development times and leaf thickness was also observed. Quercus castanea shows a brevideciduous leaf phenology but with significant variation among populations, reflecting spatiotemporal mosaics of environmental and genetic variation and in covariation with leaf functional traits such as leaf thickness.

Cross-continental comparison of plant reproductive phenology shows high intraspecific variation in temperature sensitivity

The success of plant species under climate change will be determined, in part, by their phenological responses to temperature. Despite the growing need to forecast such outcomes across entire species ranges, it remains unclear how phenological sensitivity to temperature might vary across individuals of the same species. In this study, we harnessed community science data to document intraspecific patterns in phenological temperature sensitivity across the multicontinental range of six herbaceous plant species. Using linear models, we correlated georeferenced temperature data with 23 220 plant phenological records from iNaturalist to generate spatially explicit estimates of phenological temperature sensitivity across the shared range of species. We additionally evaluated the geographic association between local historic climate conditions (i.e. mean annual temperature [MAT] and interannual variability in temperature) and the temperature sensitivity of plants. We found that plant temperature sensitivity varied substantially at both the interspecific and intraspecific levels, demonstrating that phenological responses to climate change have the potential to vary both within and among species. Additionally, we provide evidence for a strong geographic association between plant temperature sensitivity and local historic climate conditions. Plants were more sensitive to temperature in hotter climates (i.e. regions with high MAT), but only in regions with high interannual temperature variability. In regions with low interannual temperature variability, plants displayed universally weak sensitivity to temperature, regardless of baseline annual temperature. This evidence suggests that pheno-climatic forecasts may be improved by accounting for intraspecific variation in phenological temperature sensitivity. Broad climatic factors such as MAT and interannual temperature variability likely serve as useful predictors for estimating temperature sensitivity across species' ranges.

Long-term data reveal widespread phenological change across major US estuarine food webs

Climate change is shifting the timing of organismal life-history events. Although consequential food-web mismatches can emerge if predators and prey shift at different rates, research on phenological shifts has traditionally focused on single trophic levels. Here, we analysed >2000 long-term, monthly time series of phytoplankton, zooplankton, and fish abundance or biomass for the San Francisco, Chesapeake, and Massachusetts bays. Phenological shifts occurred in over a quarter (28%) of the combined series across all three estuaries. However, phenological trends for many taxa (ca. 29-68%) did not track the changing environment. While planktonic taxa largely advanced their phenologies, fishes displayed broad patterns of both advanced and delayed timing of peak abundance. Overall, these divergent patterns illustrate the potential for climate-driven trophic mismatches. Our results suggest that even if signatures of global climate change differ locally, widespread phenological change has the potential to disrupt estuarine food webs.

Warm Spring Days are Related to Shorter Durations of Reproductive Phenophases for Understory Forest Herbs

As plants continue to respond to global warming with phenological shifts, our understanding of the importance of short-lived heat events and seasonal weather cues has lagged relative to our understanding of plant responses to broad shifts in mean climate conditions. Here, we explore the importance of warmer-than-average days in driving shifts in phenophase duration for spring-flowering woodland herbs across one growing season. We harnessed the combined power of community science and public gardens, engaging more than 30 volunteers to monitor shifts in phenology (documenting movement from one phenophase to the next) for 198 individual plants of 14 species twice per week for the 2023 growing season (March-October) across five botanic gardens in the midwestern and southeastern US. Gardens included the Holden Arboretum, Kirtland, OH; Dawes Arboretum, Newark, OH; Chicago Botanic Garden, Glencoe, IL; Missouri Botanical Garden, St. Louis, MO; and Huntsville Botanical Garden, Huntsville, AL. We tested: (1) that higher-than-average daily temperatures (deviation from 30-year historical mean daily temperatures for each location) would be related to truncated phenophase durations; and (2) that phenophase durations would vary among species. Our findings support both hypotheses. We documented significant inverse relationships between positive deviations in daily temperature from historic means (e.g., warmer-than-average days) and durations of three reproductive phenophases: "First Bud," "First Ripe Fruit," and "Early Fruiting." Similar (non-significant) trends were noted for several other early-season phenophases. Additionally, significant differences in mean phenophase durations were detected among the different species, although these differences were inconsistent across plant parts (vegetative, flowering, and fruiting). Results underscore the potential sensitivity of understory herb reproductive phenophases to warmer-than-average daily temperatures early in the growing season, contributing to our understanding of phenological responses to short-term heat events and seasonal weather cues.

The linkage between functional traits and drone-derived phenology of 74 Northern Hemisphere tree species

Tree phenology is a major component of the global carbon and water cycle, serving as a fingerprint of climate change, and exhibiting significant variability both within and between species. In the emerging field of drone monitoring, it remains unclear whether this phenological variability can be effectively captured across numerous tree species. Additionally, the drivers behind interspecific variations in the phenology of deciduous trees are poorly understood, although they may be linked to plant functional traits. In this study, we derived the start of season (SOS), end of season (EOS), and length of season (LOS) for 3099 individuals from 74 deciduous tree species of the Northern Hemisphere at a unique study site in southeast Germany using drone imagery. We validated these phenological metrics with in-situ data and analyzed the interspecific variability in terms of plant functional traits. The drone-derived SOS and EOS showed high agreement with ground observations of leaf unfolding (R2 = 0.49) and leaf discoloration (R2 = 0.79), indicating that this methodology robustly captures phenology at the individual level with low temporal and human effort. Both intra- and interspecific phenological variability were high in spring and autumn, leading to differences in the LOS of up to two months under almost identical environmental conditions. Functional traits such as seed dry mass, chromosome number, and continent of origin played significant roles in explaining interspecific phenological differences in SOS, EOS, and LOS, respectively. In total, 55 %, 39 %, and 45 % of interspecific variation in SOS, EOS, and LOS could be explained by the Boosted Regression Tree (BRT) models based on functional traits. Our findings encourage new research avenues in tree phenology and advance our understanding of the growth strategies of key tree species in the Northern Hemisphere.

Assessment of Phenological Dynamics of Different Vegetation Types and Their Environmental Drivers with Near-Surface Remote Sensing: A Case Study on the Loess Plateau of China

Plant phenology is an important indicator of the impact of climate change on ecosystems. We have continuously monitored vegetation phenology using near-surface remote sensing, i.e., the PhenoCam in a gully region of the Loess Plateau of China from March 2020 to November 2022. In each image, three regions of interest (ROIs) were selected to represent different types of vegetation (scrub, arbor, and grassland), and five vegetation indexes were calculated within each ROI. The results showed that the green chromatic coordinate (GCC), excess green index (ExG), and vegetation contrast index (VCI) all well-captured seasonal changes in vegetation greenness. The PhenoCam captured seasonal trajectories of different vegetation that reflect differences in vegetation growth. Such differences may be influenced by external abiotic environmental factors. We analyzed the nonlinear response of the GCC series to environmental variables with the generalized additive model (GAM). Our results suggested that soil temperature was an important driver affecting plant phenology in the Loess gully region, especially the scrub showed a significant nonlinear response to soil temperature change. Since in situ phenology monitoring experiments of the small-scale on the Loess Plateau are still relatively rare, our work provides a reference for further understanding of vegetation phenological variations and ecosystem functions on the Loess Plateau.

Using citizen science data for predicting the timing of ecological phenomena across regions

The scarcity of long-term observational data has limited the use of statistical or machine-learning techniques for predicting intraannual ecological variation. However, time-stamped citizen-science observation records, supported by media data such as photographs, are increasingly available. In the present article, we present a novel framework based on the concept of relative phenological niche, using machine-learning algorithms to model observation records as a temporal sample of environmental conditions in which the represented ecological phenomenon occurs. Our approach accurately predicts the temporal dynamics of ecological events across large geographical scales and is robust to temporal bias in recording effort. These results highlight the vast potential of citizen-science observation data to predict ecological phenomena across space, including in near real time. The framework is also easily applicable for ecologists and practitioners already using machine-learning and statistics-based predictive approaches.

Voltinism of a solitary bee was influenced by temperature but not provision size

Changes in the timing and duration of life cycles are distinctive fingerprints of environmental change. Yet, the biotic and abiotic cues underpinning phenology and voltinism, i.e., number of generations per year, are poorly understood. Here, I experimentally test how temperature and provision size influence voltinism and survival to emergence in a solitary bee Colletes validus, and how temperature influences voltinism in the brood parasite Tricrania sanguinipennis. Within the same population, univoltine individuals emerge after 1 year (1-year form), whereas semivoltine individuals enter prolonged dormancy and emerge after 2 years (2-year form). I reared field-collected bees under 2 × 2 factorial experiments with cool (18.5 °C ± 0.5 °C) vs. warm (24 °C ± 0.5 °C) temperature treatments (bees and beetles) and no supplement vs. supplemental food treatments (+ 20% ± 5% pollen provision by mass); beetles were reared under temperature treatments only. Cool temperatures consistently increased the proportion of 2-year bees regardless of provision size, a finding that was consistent with three years of field observations. There was a demographic cost to prolonged dormancy in that both 1- and 2-year bees survived to emergence as adults, but survival of 2-year bees was approximately 50% lower than 1-year bees. Two-year beetles were produced under cooler temperatures, but unlike bees, beetles had nearly perfect survival to emergence in all treatments. This experiment advances our mechanistic understanding of the environmental drivers of voltinism in diverse insect taxa and underscores the importance of considering cryptic life stages when interpreting responses to environmental change.

Multispecies deep learning using citizen science data produces more informative plant community models

In the age of big data, scientific progress is fundamentally limited by our capacity to extract critical information. Here, we map fine-grained spatiotemporal distributions for thousands of species, using deep neural networks (DNNs) and ubiquitous citizen science data. Based on 6.7 M observations, we jointly model the distributions of 2477 plant species and species aggregates across Switzerland with an ensemble of DNNs built with different cost functions. We find that, compared to commonly-used approaches, multispecies DNNs predict species distributions and especially community composition more accurately. Moreover, their design allows investigation of understudied aspects of ecology. Including seasonal variations of observation probability explicitly allows approximating flowering phenology; reweighting predictions to mirror cover-abundance allows mapping potentially canopy-dominant tree species nationwide; and projecting DNNs into the future allows assessing how distributions, phenology, and dominance may change. Given their skill and their versatility, multispecies DNNs can refine our understanding of the distribution of plants and well-sampled taxa in general.

Projections of the start of the airborne pollen season in Barcelona (NE Iberian Peninsula) over the 21st century

The effects of global warming are numerous and recent studies reveal that they can affect the timing of pollination. Temperature is the meteorological variable that presents a clearer relationship with the start of the pollination season of most of the observed airborne pollen taxa. In Catalonia, in the last fifty years, the average annual air temperature has increased by +0.23 °C/decade, and the local warming has been slightly higher than the one on a global scale. Projections point to an increase in temperature in the coming decades, which would be more marked towards the middle of the century. To analyse the effect of the increase in temperature due to global warming on the starting date of pollen season in Barcelona, a forecasting model has been applied to a set of projected future temperatures estimated by the European RESCCUE project. This model, largely used in the literature, is based on determining the thermal needs of the plant for the pollen season to begin. The model calibration to obtain the initial parameters has been made by using 20 years of pollen data (2000-2019), and the model effectiveness has subsequently been tested through an internal evaluation over the period of the calibration and an external evaluation on 4 years not included in the calibration (2020-2023). The mean bias error in the internal calibration ranged between -0.4 and - 0.6 days, and between +0.5 and - 8.3 in the external one, depending on the taxon. The results of the application of the model to the temperature projections over the 21st century point to a progressive advancement in the pollination dates of several pollen types abundant in the city, allergenic most of them. These advances ranged, at the end of the century, between 15 and 27 days, depending on the climate model, for the scenario of the highest concentrations (RCP8.5) and between 7 and 12 days for the emissions stabilization scenario (RCP4.5).

Why do avian responses to change in Arctic green-up vary?

Global climate change has altered the timing of seasonal events (i.e., phenology) for a diverse range of biota. Within and among species, however, the degree to which alterations in phenology match climate variability differ substantially. To better understand factors driving these differences, we evaluated variation in timing of nesting of eight Arctic-breeding shorebird species at 18 sites over a 23-year period. We used the Normalized Difference Vegetation Index as a proxy to determine the start of spring (SOS) growing season and quantified relationships between SOS and nest initiation dates as a measure of phenological responsiveness. Among species, we tested four life history traits (migration distance, seasonal timing of breeding, female body mass, expected female reproductive effort) as species-level predictors of responsiveness. For one species (Semipalmated Sandpiper), we also evaluated whether responsiveness varied across sites. Although no species in our study completely tracked annual variation in SOS, phenological responses were strongest for Western Sandpipers, Pectoral Sandpipers, and Red Phalaropes. Migration distance was the strongest additional predictor of responsiveness, with longer-distance migrant species generally tracking variation in SOS more closely than species that migrate shorter distances. Semipalmated Sandpipers are a widely distributed species, but adjustments in timing of nesting relative to variability in SOS did not vary across sites, suggesting that different breeding populations of this species were equally responsive to climate cues despite differing migration strategies. Our results unexpectedly show that long-distance migrants are more sensitive to local environmental conditions, which may help them to adapt to ongoing changes in climate.

Exploring the role of biotic factors in regulating the spatial variability in land surface phenology across four temperate forest sites

Land surface phenology (LSP), the characterization of plant phenology with satellite data, is essential for understanding the effects of climate change on ecosystem functions. Considerable LSP variation is observed within local landscapes, and the role of biotic factors in regulating such variation remains underexplored. In this study, we selected four National Ecological Observatory Network terrestrial sites with minor topographic relief to investigate how biotic factors regulate intra-site LSP variability. We utilized plant functional type (PFT) maps, functional traits, and LSP data to assess the explanatory power of biotic factors for the start and end of season (SOS and EOS) variability. Our results indicate that PFTs alone explain only 0.8-23.4% of intra-site SOS and EOS variation, whereas including functional traits significantly improves explanatory power, with cross-validation correlations ranging from 0.50 to 0.85. While functional traits exhibited diverse effects on SOS and EOS across different sites, traits related to competitive ability and productivity were important for explaining both SOS and EOS variation at these sites. These findings reveal that plants exhibit diverse phenological responses to comparable environmental conditions, and functional traits significantly contribute to intra-site LSP variability, highlighting the importance of intrinsic biotic properties in regulating plant phenology.

Opportunistic plant observations reveal spatial and temporal gradients in phenology

Opportunistic plant records provide a rapidly growing source of spatiotemporal plant observation data. Here, we used such data to explore the question whether they can be used to detect changes in species phenologies. Examining 19 herbaceous and one woody plant species in two consecutive years across Europe, we observed significant shifts in their flowering phenology, being more pronounced for spring-flowering species (6-17 days) compared to summer-flowering species (1-6 days). Moreover, we show that these data are suitable to model large-scale relationships such as "Hopkins' bioclimatic law" which quantifies the phenological delay with increasing elevation, latitude, and longitude. Here, we observe spatial shifts, ranging from -5 to 50 days per 1000 m elevation to latitudinal shifts ranging from -1 to 4 days per degree northwards, and longitudinal shifts ranging from -1 to 1 day per degree eastwards, depending on the species. Our findings show that the increasing volume of purely opportunistic plant observation data already provides reliable phenological information, and therewith can be used to support global, high-resolution phenology monitoring in the face of ongoing climate change.

Critical role of water conditions in the responses of autumn phenology of marsh wetlands to climate change on the Tibetan Plateau

The Tibetan Plateau, housing 20% of China's wetlands, plays a vital role in the regional carbon cycle. Examining the phenological dynamics of wetland vegetation in response to climate change is crucial for understanding its impact on the ecosystem. Despite this importance, the specific effects of climate change on wetland vegetation phenology in this region remain uncertain. In this study, we investigated the influence of climate change on the end of the growing season (EOS) of marsh wetland vegetation across the Tibetan Plateau, utilizing satellite-derived Normalized Difference Vegetation Index (NDVI) data and observational climate data. We observed that the regionally averaged EOS of marsh vegetation across the Tibetan Plateau was significantly (p < .05) delayed by 4.10 days/decade from 2001 to 2020. Warming preseason temperatures were found to be the primary driver behind the delay in the EOS of marsh vegetation, whereas preseason cumulative precipitation showed no significant impact. Interestingly, the responses of EOS to climate change varied spatially across the plateau, indicating a regulatory role for hydrological conditions in marsh phenology. In the humid and cold central regions, preseason daytime warming significantly delayed the EOS. However, areas with lower soil moisture exhibited a weaker or reversed delay effect, suggesting complex interplays between temperature, soil moisture, and EOS. Notably, in the arid southwestern regions of the plateau, increased preseason rainfall directly delayed the EOS, while higher daytime temperatures advanced it. Our results emphasize the critical role of hydrological conditions, specifically soil moisture, in shaping marsh EOS responses in different regions. Our findings underscore the need to incorporate hydrological factors into terrestrial ecosystem models, particularly in cold and dry regions, for accurate predictions of marsh vegetation phenological responses to climate change. This understanding is vital for informed conservation and management strategies in the face of current and future climate challenges.

Effects of temperature and precipitation changes on shifts in breeding phenology of an endangered toad

In the last century, a plethora of species have shown rapid phenological changes in response to climate change. Among animals, amphibians exhibit some of the greatest responses since their activity strongly depends on temperature and rainfall regimes. These shifts in phenology can have negative consequences for amphibian fitness. Thus, understanding phenological changes in amphibians is pivotal to design conservation actions to mitigate climate change effects. We used data on Common Spadefoot Toad (Pelobates fuscus) reproductive migration to wetlands over a period of 8 years in Italy to (i) identify the factors related to breeding migrations, (ii) assess potential phenological shifts in the breeding period, and (iii) determine which climatic factors are related to the observed phenological shifts. Our results showed that toads migrate to spawning sites preferably in early spring, on rainy days with temperatures of 9-14 °C, and with high humidity. Furthermore, despite an increase in average temperature across the study period, we observed a delay in the start of breeding migrations of 12.4 days over 8 years. This counterintuitive pattern was the result of a succession of hot and dry years that occurred in the study area, highlighting that for ephemeral pond breeders, precipitation could have a larger impact than temperature on phenology. Our results belie the strong presumption that climate change will shift amphibian phenology toward an earlier breeding migration and underline the importance of closely investigating the environmental factors related to species phenology.

Using long-term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea-Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best-performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea, the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Recent evolution of flowering time across multiple European plant species correlates with changes in aridity

Ongoing global warming and increasing drought frequencies impact plant populations and potentially drive rapid evolutionary adaptations. Historical comparisons, where plants grown from seeds collected in the past are compared to plants grown from freshly collected seeds from populations of the same sites, are a powerful method to investigate recent evolutionary changes across many taxa. We used 21-38 years old seeds of 13 European plant species, stored in seed banks and originating from Mediterranean and temperate regions, together with recently collected seeds from the same sites for a greenhouse experiment to investigate shifts in flowering phenology as a potential result of adaptive evolution to changes in drought intensities over the last decades. We further used single nucleotide polymorphism (SNP) markers to quantify relatedness and levels of genetic variation. We found that, across species, current populations grew faster and advanced their flowering. These shifts were correlated with changes in aridity at the population origins, suggesting that increased drought induced evolution of earlier flowering, whereas decreased drought lead to weak or inverse shifts in flowering phenology. In five out of the 13 species, however, the SNP markers detected strong differences in genetic variation and relatedness between the past and current populations collected, indicating that other evolutionary processes may have contributed to changes in phenotypes. Our results suggest that changes in aridity may have influenced the evolutionary trajectories of many plant species in different regions of Europe, and that flowering phenology may be one of the key traits that is rapidly evolving.

Climate lags and genetics determine phenology in quaking aspen (Populus tremuloides)

Spatiotemporal patterns of phenology may be affected by mosaics of environmental and genetic variation. Environmental drivers may have temporally lagged impacts, but patterns and mechanisms remain poorly known. We combine multiple genomic, remotely sensed, and physically modeled datasets to determine the spatiotemporal patterns and drivers of canopy phenology in quaking aspen, a widespread clonal dioecious tree species with diploid and triploid cytotypes. We show that over 391 km² of southwestern Colorado: greenup date, greendown date, and growing season length vary by weeks and differ across sexes, cytotypes, and genotypes; phenology has high phenotypic plasticity and heritabilities of 31-61% (interquartile range); and snowmelt date, soil moisture, and air temperature predict phenology, at temporal lags of up to 3 yr. Our study shows that lagged environmental effects are needed to explain phenological variation and that the effect of cytotype on phenology is obscured by its correlation with topography. Phenological patterns are consistent with responses to multiyear accumulation of carbon deficit or hydraulic damage.

Advances in spring leaf phenology are mainly triggered by elevated temperature along the rural-urban gradient in Beijing, China

Urbanization-induced phenological changes have received considerable attention owing to their implications for determining urban ecosystem productivity and predicting the response of plants and ecosystem carbon cycles to future climate change. However, inconsistent rural-urban gradients in plant phenology remain, and phenological drivers other than temperature are poorly understood. In this study, we simultaneously observed the micro-climate and spring leaf phenology of seven woody plant species at 13 parks along a rural-urban gradient in Beijing, China. The minimum (T_min) and mean (T_mean) air temperature and the minimum (VPD_min) and mean (VPD_mean) vapor pressure deficit increased significantly along the rural-urban gradient, but the maximum air temperature (T_max) and maximum vapor pressure deficit (VPD_max) did not. All observed leaf phenological phases for the seven species were significantly advanced along the rural-urban gradient by 0.20 to 1.02 days/km. Advances in the occurrence of leaf phenological events were significantly correlated with increases in T_mean (accounting for 57-59% variation), T_min (21-26%), VPD_min (12-16%), and VPD_mean (3-5%), but not with changes in T_max or VPD_max. Advances in spring leaf phenology along the rural-urban gradient differed between non-native species and native species and between shrubs and trees. The reason may be mainly that the sensitivities of spring leaf phenology to micro-climate differ with species origin and growth form. This study highlights that urbanization-induced increases in T_mean and T_min are the major contributors to advances in spring leaf phenology along the rural-urban gradient, exerting less influence on native species than on non-native species.

Canopy composition drives variability in urban growing season length more than the heat island effect

The elevated heat of urban areas compared to their surroundings makes humid temperate cities a useful preview of future climate effects on natural forest phenology. The utility of this proxy rests on the expectation that trees in urban areas alter their phenology in response to warmer site conditions in spring and fall. However, it is possible that apparent lengthening of the growing season is instead governed by human-driven tree species selection and plant functional type (PFT; trees, shrubs, turfgrass) heterogeneity typical of managed landscapes. Without the use of highly spatially and temporally resolved remote sensing data, the roles of tree taxonomy and local site characteristics (e.g., impervious cover) in controlling phenology remain confounded. To understand the drivers of earlier start of season (SOS) and later end of season (EOS) among urban trees, we estimated individual tree phenology using >130 high-resolution satellite images per year (2018-2020) for ~10,000 species-labeled trees in Washington, DC. We found that species identity alone accounted for 4× more variability in the timing of SOS and EOS compared with a tree's planting location characteristics. Additionally, the urban mix of PFTs may be more responsible for apparent advances in SOS (by between 1.8 ± 1.3 and 3.5 ± 1.3 days) than heat per se. The results of this study caution against associating longer growing seasons in cities-observed in moderate to coarse resolution remote sensing imagery-to within-species phenological plasticity and demonstrate the power of high-resolution satellite data for tracking tree phenology in biodiverse environments.

Uses, Botanical Characteristics, and Phenological Development of Slender Nightshade (Solanum nigrescens Mart. and Gal.)

Slender nightshade (Solanum nigrescens Mart. and Gal.) is a perennial, herbaceous plant from the Solanaceae family, which is distributed in various environments. The aim of this study was to review the scientific literature and to establish slender nightshade plants under greenhouse conditions in order to record their phenological development. The specialized literature regarding the distribution, botanical characteristics, and uses of such species was analyzed. The phenological development was recorded based on the BBCH (Biologische Bundesanstalt, Bundessortenamt, Chemische Industrie) guide. Slender nightshade seeds were germinated under greenhouse conditions, then transferred to red porous volcano gravel locally known as tezontle in black polyethylene bags and watered with a Steiner nutrient solution. Changes in phenology were monitored and recorded from germination to the ripening of fruit and seeds. Slender nightshade has a wide distribution in Mexico and is used for medicinal and gastronomical purposes, as well as to control pathogens. The phenological development of slender nightshade has seven stages from germination to the ripening of fruit and seeds. Slender nightshade is a poorly studied plant with potential for human consumption. The phenological recording provides a tool for its management and further research as a crop.

Global warming is increasing the discrepancy between green (actual) and thermal (potential) seasons of temperate trees

Over the past decades, global warming has led to a lengthening of the time window during which temperatures remain favorable for carbon assimilation and tree growth, resulting in a lengthening of the green season. The extent to which forest green seasons have tracked the lengthening of this favorable period under climate warming, however, has not been quantified to date. Here, we used remote sensing data and long-term ground observations of leaf-out and coloration for six dominant species of European trees at 1773 sites, for a total of 6060 species-site combinations, during 1980-2016 and found that actual green season extensions (GS: 3.1 ± 0.1 day decade^-1 ) lag four times behind extensions of the potential thermal season (TS: 12.6 ± 0.1 day decade^-1 ). Similar but less pronounced differences were obtained using satellite-derived vegetation phenology observations, that is, a lengthening of 4.4 ± 0.13 and 7.5 ± 0.13 day decade^-1 for GS and TS, respectively. This difference was mainly driven by the larger advance in the onset of the thermal season compared to the actual advance of leaf-out dates (spring mismatch: 7.2 ± 0.1 day decade^-1 ), but to a less extent caused by a phenological mismatch between GS and TS in autumn (2.4 ± 0.1 day decade^-1 ). Our results showed that forest trees do not linearly track the new thermal window extension, indicating more complex interactions between winter and spring temperatures and photoperiod and a justification of demonstrating that using more sophisticated models that include the influence of chilling and photoperiod is needed to accurately predict spring phenological changes under warmer climate. They urge caution if such mechanisms are omitted to predict, for example, how vegetative health and growth, species distribution and crop yields will change in the future.

Phenological physiology: seasonal patterns of plant stress tolerance in a changing climate

The physiological challenges posed by climate change for seasonal, perennial plants include increased risk of heat waves, postbudbreak freezing ('false springs'), and droughts. Although considerable physiological work has shown that the traits conferring tolerance to these stressors - thermotolerance, cold hardiness, and water deficit stress, respectively - are not static in time, they are frequently treated as such. In this review, I synthesize the recent literature on predictable seasonal - and therefore, phenological - patterns of acclimation and deacclimation to heat, cold, and water-deficit stress in perennials, focusing on woody plants native to temperate climates. I highlight promising, high-throughput techniques for quantifying thermotolerance, cold hardiness, and drought tolerance. For each of these forms of stress tolerance, I summarize the current balance of evidence regarding temporal patterns over the course of a year and suggest a characteristic temporal scale in these responses to environmental stress. In doing so, I offer a synthetic framework of 'phenological physiology', in which understanding and leveraging seasonally recurring (phenological) patterns of physiological stress acclimation can facilitate climate change adaptation and mitigation.

A century of climate warming results in growing season extension: Delayed autumn leaf phenology in north central North America

Shifts in the timing of key leaf phenological events including budburst, foliage coloration, and leaf fall have been observed worldwide and are consistent with climate warming. Quantifying changes in growing season length (GSL) because of shifts in both spring and autumn leaf phenology is crucial for modeling annual net ecosystem carbon uptake. However, a lack of long-term autumn phenology datasets has prevented assessment of these growing season level changes. We investigated shifts in growing season length, budburst, foliage coloration, and leaf fall over the past century in seven native hardwood species using a historic leaf phenology dataset collected in Wauseon, OH from 1883-1912 paired with contemporary observations. Using long-term meteorological data, we investigated temperature and precipitation trends over 130 years. Finally, we correlated spring and fall phenophases with monthly temperature and precipitation variables from the twelve months preceding that phenophase using historical meteorological data. We found significant extension of growing season length over the past century in five of the seven study species (ANOVA, p < 0.05) which resulted primarily from delayed foliage coloration rather than from earlier budburst in contrast to the few other studies assessing total GSL change. Our results suggest that most of the leaf phenological studies that investigate only budburst are disregarding crucial information about the end of the growing season that is essential for accurately predicting the effects of climate change in mixed-species temperate deciduous forests.

Fuzzy clustering for the within-season estimation of cotton phenology

Crop phenology is crucial information for crop yield estimation and agricultural management. Traditionally, phenology has been observed from the ground; however Earth observation, weather and soil data have been used to capture the physiological growth of crops. In this work, we propose a new approach for the within-season phenology estimation for cotton at the field level. For this, we exploit a variety of Earth observation vegetation indices (derived from Sentinel-2) and numerical simulations of atmospheric and soil parameters. Our method is unsupervised to address the ever-present problem of sparse and scarce ground truth data that makes most supervised alternatives impractical in real-world scenarios. We applied fuzzy c-means clustering to identify the principal phenological stages of cotton and then used the cluster membership weights to further predict the transitional phases between adjacent stages. In order to evaluate our models, we collected 1,285 crop growth ground observations in Orchomenos, Greece. We introduced a new collection protocol, assigning up to two phenology labels that represent the primary and secondary growth stage in the field and thus indicate when stages are transitioning. Our model was tested against a baseline model that allowed to isolate the random agreement and evaluate its true competence. The results showed that our model considerably outperforms the baseline one, which is promising considering the unsupervised nature of the approach. The limitations and the relevant future work are thoroughly discussed. The ground observations are formatted in an ready-to-use dataset and will be available at https://github.com/Agri-Hub/cotton-phenology-dataset upon publication.

Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications

Vegetation phenology has been viewed as the nature's calendar and an integrative indicator of plant-climate interactions. The correct representation of vegetation phenology is important for models to accurately simulate the exchange of carbon, water, and energy between the vegetated land surface and the atmosphere. Remote sensing has advanced the monitoring of vegetation phenology by providing spatially and temporally continuous data that together with conventional ground observations offers a unique contribution to our knowledge about the environmental impact on ecosystems as well as the ecological adaptations and feedback to global climate change. Land surface phenology (LSP) is defined as the use of satellites to monitor seasonal dynamics in vegetated land surfaces and to estimate phenological transition dates. LSP, as an interdisciplinary subject among remote sensing, ecology, and biometeorology, has undergone rapid development over the past few decades. Recent advances in sensor technologies, as well as data fusion techniques, have enabled novel phenology retrieval algorithms that refine phenology details at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. As such, here we summarize the recent advances in LSP and the associated opportunities for science applications. We focus on the remaining challenges, promising techniques, and emerging topics that together we believe will truly form the very frontier of the global LSP research field.

Continued spring phenological advance under global warming hiatus over the Pan-Third Pole

The global surface temperature has witnessed a warming hiatus in the first decade of this century, but how this slowing down of warming will impact spring phenology over Pan-Third Pole remains unclear. Here, we combined multiple satellite-derived vegetation indices with eddy covariance datasets to evaluate the spatiotemporal changes in spring phenological changes over the Pan-Third Pole. We found that the spring phenology over Pan-Third Pole continues to advance at the rate of 4.8 days decade^-1 during the warming hiatus period, which is contrasted to a non-significant change over the northern hemisphere. Such a significant and continued advance in spring phenology was mainly attributed to an increase in preseason minimum temperature and water availability. Moreover, there is an overall increasing importance of precipitation on changes in spring phenology during the last four decades. We further demonstrated that this increasingly negative correlation was also found across more than two-thirds of the dryland region, tentatively suggesting that spring phenological changes might shift from temperature to precipitation-controlled over the Pan-Third Pole in a warmer world.

Citizen science and expert opinion working together to understand the impacts of climate change

In the absence of historical information on phenology available in Australia, expert opinion was used for selecting indicator species that would be suitable for monitoring phenology on a continental scale as part of ClimateWatch-a citizen science program. Jacaranda mimosifolia being the most frequently observed species was used in this study to test expert opinion and the adequacy of citizen science records in detecting the influence of climatic conditions on this species' flowering phenology. Generalised Additive Models for Location Scale and Shape were used to explore the occurrence and intensity of flowering of Jacaranda in relation to rainfall, temperature, and sun exposure. Jacaranda flowering onset was influenced by winter cold exposure, while flowering intensity was related to increasing sun exposure as spring progresses, and both were influenced by the conditions for flowering in the former flowering seasons (i.e., sun exposure and highest temperatures reached, respectively). Our models provide the first attempt to describe the climate drivers for Jacaranda mimosifolia flowering in the southern hemisphere and identify where climatic changes will most likely alter this tree's phenology in Australia and benefit or challenge its reproductive ability. They also support the choice of species for citizen science programs based on expert opinion.

Rainfall Variability and Tidal Inundation Influences on Mangrove Greenness in Karimunjawa National Park, Indonesia

Mangroves, which are vulnerable to natural threats and human activities on small islands in the tropics, play an essential role as carbon sinks, helping to mitigate climate change. In this study, we discussed the effect of natural factors on mangrove sustainability by analyzing the impact of rainfall, land surface temperature (LST), and tidal inundation on the greenness of mangroves in Karimunjawa National Park (KNP), Indonesia. We used Sentinel-2 image data to obtain the normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) during the dry season to determine the effect of inundation on mangrove greenness and soil moisture. The tidal inundation area was calculated using topographic data from the KNP and tidal observations from the area adjacent to it. Unmanned autonomous vehicles and topographic data were used to estimate mangrove canopy height. We also calculated mangrove greenness phenology and compared it to rainfall from satellite data from 2019–2021. Results show that the intertidal area is dominated by taller mangroves and has higher NDVI and NDMI values than non-intertidal areas. We also observed that mangroves in intertidal areas are mostly evergreen, and optimum greenness in KNP occurs from February to October, with maximum greenness in July. Cross-correlation analysis suggests that high rainfall affects NDVI, with peak greenness occurring three months after high rainfall. The LST and NDVI cross-correlation showed no time lag. This suggests that LST was not the main factor controlling mangrove greenness, suggesting tides and rainfall influence mangrove greenness. The mangroves are also vulnerable to climate variability and change, which limits rainfall. However, sea-level rise due to climate change might positively impact mangrove greenness.

Spring and Autumn Phenology in Sessile Oak (Quercus petraea) Near the Eastern Limit of Its Distribution Range

Due to the visible and predictable influence of climate change on species’ spatial distributions, the conservation of marginal peripheral populations has become topical in forestry research. This study aimed to assess the spring (budburst, leaf development, and flowering) and autumn (leaf senescence) phenology of sessile oak (Quercus petraea), a species widespread across European forests close to its ranges’ eastern limit. This study was performed in Romania between spring 2017 and 2020, and it included a transect with three low-altitude populations, a reference population from its inner range, and a sessile oak comparative trial. The temperature was recorded to relate changes to phenophase dynamics. We identified small variations between the reference and peripheral populations associated with climatic conditions. In the peripheral populations, budburst timing had day-of-year (DOY) values <100, suggesting that sessile oak may be more susceptible to late spring frost. Furthermore, we found spring phenophase timing to be more constant than autumn senescence. Moreover, budburst in the sessile oak comparative trial had obvious longitudinal tendencies, with an east to west delay of 0.5–1.4 days per degree. In addition, budburst timing influenced leaf development and flowering, but not the onset of leaf senescence. These findings improve our understanding of the relationship between spring and autumn phenophase dynamics and enhance conservation strategies regarding sessile oak genetic resources.

Forest wildflowers bloom earlier as Europe warms: lessons from herbaria and spatial modelling

Today plants often flower earlier due to climate warming. Herbarium specimens are excellent witnesses of such long-term changes. However, the magnitude of phenological shifts may vary geographically, and the data are often clustered. Therefore, large-scale analyses of herbarium data are prone to pseudoreplication and geographical biases. We studied over 6000 herbarium specimens of 20 spring-flowering forest understory herbs from Europe to understand how their phenology had changed during the last century. We estimated phenology trends with or without taking spatial autocorrelation into account. On average plants now flowered over 6 d earlier than at the beginning of the last century. These changes were strongly associated with warmer spring temperatures. Flowering time advanced 3.6 d per 1°C warming. Spatial modelling showed that, in some parts of Europe, plants flowered earlier or later than expected. Without accounting for this, the estimates of phenological shifts were biased and model fits were poor. Our study indicates that forest wildflowers in Europe strongly advanced their phenology in response to climate change. However, these phenological shifts differ geographically. This shows that it is crucial to combine the analysis of herbarium data with spatial modelling when testing for long-term phenology trends across large spatial scales.

Warming-induced increase in carbon uptake is linked to earlier spring phenology in temperate and boreal forests

Under global warming, advances in spring phenology due to rising temperatures have been widely reported. However, the physiological mechanisms underlying the advancement in spring phenology still remain poorly understood. Here, we investigated the effect of temperature during the previous growing season on spring phenology of current year based on the start of season extracted from multiple long-term and large-scale phenological datasets between 1951 and 2018. Our findings indicate that warmer temperatures during previous growing season are linked to earlier spring phenology of current year in temperate and boreal forests. Correspondingly, we observed an earlier spring phenology with the increase in photosynthesis of the previous growing season. These findings suggest that the observed warming-induced earlier spring phenology is driven by increased photosynthetic carbon assimilation in the previous growing season. Therefore, the vital role of warming-induced changes in carbon assimilation should be considered to accurately project spring phenology and carbon cycling in forest ecosystems under future climate warming.

The mechanisms underlying plant phenological shifts are debated. Here, based on phenological observations and ecosystem flux and climate data, Gu and colleagues provide evidence that warming-enhanced photosynthesis in a growing season contributes to earlier spring phenology in the following year in temperate and boreal forests.

Phenological Response of Flood Plain Forest Ecosystem Species to Climate Change during 1961–2021

The present study analyses 61 years of phenological observations (1961–2021) of five herb, five shrub, four tree, and one bird species representing the prevalent spring species of floodplain forest ecosystems in the Czech Republic, central Europe. The in situ observations were conducted at the Vranovice site (48°48′ N, 16°46′ E, 170 m above mean sea level) representing the Plaček’ forest National Reserve. The observed plants and bird species showed statistically significant (p < 0.05) shifts in phenological terms to an earlier date of the year, but the rate of the shift among the observed species differed. The most progressive shifts were detected for the herbs (14 days), followed by the shrubs (13 days), trees (9 days), and finally by the bird species (8 days). All the phenophases were significantly correlated with the daily maximum temperature (r = 0.72–0.91). The results also showed a decline in the correlation for species among the phenophases of the herbs and trees. The phenophases that were highly correlated in the past were less correlated and had higher variability in the last decades. We conclude that the phenological response of the ecosystem to warming in the spring resulted in higher variability and a lower correlation among the observed phenophases mainly caused by the most expressive phenological shifts of the early herbs.

Soft coral reproductive phenology along a depth gradient: Can "going deeper" provide a viable refuge?

Many species across a wide range of taxa and habitats display phenological shifts and differences in response to both environmental gradients and climate change. Moreover, the wide‐scale decline of numerous ecosystems is leading to increasing efforts to identify zones that might serve as natural refuges from various disturbances, including ocean warming. One such refuge was suggested to be that of the deep coral reefs, but whether depth can provide coral populations with a viable and reproductive refuge remains unclear. Given the global coral‐reef degradation and the key role that corals play as ecosystem engineers, their reproductive ecology has been widely studied. A particular knowledge gap nonetheless exists regarding coral reproductive phenology along a depth gradient. Filling in this gap may uncover the environmental cues that regulate coral reproduction, leading to better predictions of population connectivity, and their possible responses to climate change and other environmental changes. Here, using long‐term in situ observations of the soft coral Rhytisma fulvum's reproductive activity along its entire depth range (0–45 m), we examined the relationship among several environmental factors and the coral's reproductive phenology and activity over five successive annual breeding seasons. Compared with the shallow depths, a lower number of reproducing colonies was found in habitats deeper than 30 m, highlighting possible constraints on coral reproduction at the deeper end of their range. Our results further revealed that an increase in seawater temperature over 1–2‐day intervals during the breeding season correlated with the onset of reproductive activity along the depth gradient, leading to different reproductive periodicities in different depths. These differences suggest that differential temperature regimes and reproductive timing across depth may create intraspecific temporal reproductive segregation, possibly reducing connectivity among populations along a depth gradient. Moreover, we found high variability among years in both the timing of breeding activities and in the level of reproductive synchrony among corals from different depths. Overall, our study questions whether depth can provide a long‐term and viable refuge for corals in the face of global environmental changes.

Quantifying phenological diversity: a framework based on Hill numbers theory

Background

Despite the great concern triggered by the environmental crisis worldwide, the loss of temporal key functions and processes involved in biodiversity maintenance has received little attention. Species are restricted in their life cycles by environmental variables because of their physiological and behavioral properties; thus, the timing and duration of species' presence and their activities vary greatly between species within a community. Despite the ecological relevance of such variation, there is currently no measure that summarizes the key temporal aspects of biological diversity and allows comparisons of community phenological patterns. Here, we propose a measure that synthesizes variability of phenological patterns using the Hill numbers-based attribute diversity framework.

Methods

We constructed a new phenological diversity measure based on the aforementioned framework through pairwise overlapping distances, which was supplemented with wavelet analysis. The Hill numbers approach was chosen as an adequate way to define a set of diversity values of different order q, a parameter that determines the sensitivity of the diversity measure to abundance. Wavelet transform analysis was used to model continuous variables from incomplete data sets for different phenophases. The new measure, which we call Phenological Hill numbers (PD), considers the decouplings of phenophases through an overlapping area value between pairs of species within the community. PD was first tested through simulations with varying overlap in phenophase magnitude and intensity and varying number of species, and then by using one real data set.

Results

PD maintains the diversity patterns of order q as in any other diversity measure encompassed by the Hill numbers framework. Minimum PD values in the simulated data sets reflect a lack of differentiation in the phenological curves of the community over time; by contrast, the maximum PD values reflected the most diverse simulations in which phenological curves were equally distributed over time. PD values were consistent with the homogeneous distribution of the intensity and concurrence of phenophases over time, both in the simulated and the real data set.

Discussion

PD provides an efficient, readily interpretable and comparable measure that summarizes the variety of phenological patterns observed in ecological communities. PD retains the diversity patterns of order q characteristic of all diversity measures encompassed by the distance-based Hill numbers framework. In addition, wavelet transform analysis proved useful for constructing a continuous phenological curve. This methodological approach to quantify phenological diversity produces simple and intuitive values for the examination of phenological diversity and can be widely applied to any taxon or community's phenological traits.

Consistent temperature-dependent patterns of leaf lifespan across spatial and temporal gradients for deciduous trees in Europe

Temperature affects leaf lifespan (LL) across either space or time, driving long-term adaptation and short-term thermal acclimation, respectively. However, a comprehensive understanding of the phenomenon and the underlying phenological mechanisms remain poorly understood. The present study investigated the relationship between LL and temperature in six common deciduous trees across both spatial and temporal gradients, then explained the LL variation patterns based on phenological shifts. Using long-term (1971-2000) phenological records of six deciduous tree species at 54 sites across central Europe, we analyzed spatial and temporal variations of LL and leaf phenology along temperature gradients. We assessed the relative contribution of phenological shifts to LL variations by comparing absolute changes in leaf-out and leaf fall. We reported positive LL-temperature relationships across all observations along both spatial (+3.32 days/°C) and temporal (+4.43 days/°C) gradients. The paired t-test of the six deciduous tree species showed no significant difference in regression slopes of LL- temperature between the two gradients (t = -1.50, df = 5, P = 0.194). Prolonged LL can be explained mainly by earlier leaf-out induced by warmer temperatures both spatially (-3.22 days/°C) and temporally (-4.08 days/°C). The converging temperature-dependent patterns of LL across time and space indicate that short-term thermal acclimation keeps pace with long-term genetic adaptation for deciduous trees in Europe. Earlier leaf-out is the key force shaping the LL-temperature relationship. These results provide insights for predicting future vegetation dynamics under global warming.

No evidence for a negative effect of growing season photosynthesis on leaf senescence timing

The length of the growing season has a large influence on the carbon, water, and energy fluxes of global terrestrial ecosystems. While there has been mounting evidence of an advanced start of the growing season mostly due to elevated spring air temperatures, the mechanisms that control the end of the growing season (EOS) in most ecosystems remain relatively less well understood. Recently, a strong lagged control of EOS by growing season photosynthesis has been proposed, suggesting that more productive growing seasons lead to an earlier EOS. However, this relationship has not been extensively tested with in-situ observations across a variety of ecosystems. Here, we use observations from 40 eddy-covariance flux tower sites in temperate and boreal ecosystems in the northern hemisphere with more than 10 years of observations (594 site-years), ground observations of phenology, satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), and three leaf senescence models to test the extent of a relationship between growing season photosynthesis and end of season senescence. The results suggest that there is no significant negative relationship between growing season photosynthesis and observed leaf senescence, flux-inferred EOS estimates, or remotely sensed phenological metrics, in most ecosystems. On the contrary, while we found negative effects of summer air temperatures and autumn vapor pressure deficit on EOS, more productive growing seasons were typically related to a later, not earlier, EOS. Our results challenge recent reports of carry-over effects of photosynthesis on EOS timing, and suggest those results may not hold over a large range of ecosystems.

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.

Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology

Detecting crop phenology with satellite time series is important to characterize agroecosystem energy-water-carbon fluxes, manage farming practices, and predict crop yields. Despite the advances in satellite-based crop phenological retrievals, interpreting those retrieval characteristics in the context of on-the-ground crop phenological events remains a long-standing hurdle. Over the recent years, the emergence of near-surface phenology cameras (e.g., PhenoCams), along with the satellite imagery of both high spatial and temporal resolutions (e.g., PlanetScope imagery), has largely facilitated direct comparisons of retrieved characteristics to visually observed crop stages for phenological interpretation and validation. The goal of this study is to systematically assess near-surface PhenoCams and high-resolution PlanetScope time series in reconciling sensor- and ground-based crop phenological characterizations. With two critical crop stages (i.e., crop emergence and maturity stages) as an example, we retrieved diverse phenological characteristics from both PhenoCam and PlanetScope imagery for a range of agricultural sites across the United States. The results showed that the curvature-based Greenup and Gu-based Upturn estimates showed good congruence with the visually observed crop emergence stage (RMSE about 1 week, bias about 0–9 days, and R square about 0.65–0.75). The threshold- and derivative-based End of greenness falling Season (i.e., EOS) estimates reconciled well with visual crop maturity observations (RMSE about 5–10 days, bias about 0–8 days, and R square about 0.6–0.75). The concordance among PlanetScope, PhenoCam, and visual phenology demonstrated the potential to interpret the fine-scale sensor-derived phenological characteristics in the context of physiologically well-characterized crop phenological events, which paved the way to develop formal protocols for bridging ground-satellite phenological characterization.