Phenological Shifts Research Articles

Climate variability links to changes in Rioja wine (Spain).

This study investigates the impact of regional climate changes on the production, quality, chemical composition, and phenological patterns of Rioja wine in Spain from 1993 to 2017. Data from DOCa Rioja and the Marqués de Riscal winery were analyzed in conjunction with meteorological and remote sensing data to provide a comprehensive evaluation. The findings reveal an increase in alcohol content and pH, coupled with a decrease in acidity, correlative to phenological shifts such as earlier grape ripening and reduced leaf canopy. Additionally, a thorough examination of monthly climate anomalies highlights the significance of May in determining harvest outcomes, influenced by the Eastern Atlantic (EA) mode of low-frequency variability. The potential connection between springtime weather conditions and tropical climate variability is also explored.

Intra‐ and inter‐specific variability in the temporal trends of butterfly phenology in the Northern Alps

Abstract Large‐scale declines in insect abundances and richness due to climate and land‐use change have been well documented during the past years. These changes are accompanied by shifts in insect phenology towards earlier appearance in spring and prolonged activity periods in late summer and autumn. The magnitude of these responses to climate change might be masked by intra‐ and inter‐specific variability in phenology and trait expression. Here, we used a large data set of museum records of butterflies from the northern Austrian Alps (380 m to >3000 m asl) and ask to which degree does intra‐ and inter‐specific variability in spring and autumn activity and in the numbers of generations affect the temporal trends in phenology during the last 30 years? For the 17 most abundant species, we found phenological variability to strongly differ among species, local habitats and study years. Ubiquitous mobile species were significantly more variable than habitat specialist and sedentary species. Intra‐specific variability was highest in ubiquitous habitat generalist species and increased during the study period. As consequence, seasonal appearance and composition of local butterfly communities are now less predictable than decades ago. It remains unclear whether this trend causes a rewiring of pollinator food webs.

Interdisciplinary Perspectives on Forest Ecosystems and Climate Interplay: A Review

This review comprehensively examines the multifunctional role of forest ecosystems in climate regulation and the consequential impacts of climate change on these critical biomes. A systematic approach was employed, utilizing extensive bibliometric analysis and synthesis of recent literature from databases such as Web of Science, ScienceDirect, and Google Scholar. Key ecological functions of forests, including carbon sequestration, albedo modulation, evapotranspiration, and cloud formation, were scrutinized to elucidate their contributions to the global carbon cycle and local/regional climate dynamics. The analysis highlights significant phenological shifts, species migrations, and increased vulnerabilities to pests, diseases, and fire disturbances as primary indicators of climate-induced ecological changes. Furthermore, the study explores the intricate feedback loops that exacerbate deforestation and alterations in forest structure and function. Predictive models incorporating various climate scenarios are discussed, emphasizing their importance in developing adaptive management strategies for forest conservation. The findings underscore the necessity for interdisciplinary approaches and stakeholder engagement to formulate effective strategies for mitigating climate change impacts and enhancing forest ecosystem resilience. This review advances the field of ecology by providing critical insights into the interplay between forest ecosystems and climate dynamics, offering a foundation for future research and policy development.

High voltinism, late-emerging butterflies are sensitive to interannual variation in spring temperature in North Carolina.

Climate change has been repeatedly linked to phenological shifts in many taxa, but the factors that drive variation in phenological sensitivity remain unclear. For example, relatively little is known about phenological responses in areas that have not exhibited a consistent warming trend, making it difficult to project phenological responses in response to future climate scenarios for these regions. We used an extensive community science dataset to examine changes in the adult flight onset dates of 38 butterfly species with interannual variation in spring temperatures in the Piedmont region of North Carolina, a region that did not experience a significant overall warming trend in the second half of the 20th century. We also explored whether voltinism, overwintering stage, and mean adult flight onset dates explain interspecific variation in phenological sensitivity to spring temperature. We found that 12 out of 38 species exhibited a significant advance in adult flight onset dates with higher spring temperatures. In comparison, none of the 38 species exhibited a significant advance with year. There was a significant interaction between mean onset flight date and voltinism, such that late-emerging, multivoltine species tended to be the most sensitive to spring temperature changes. We did not observe a significant correlation between phenological sensitivity and the overwintering stage. These results suggest that butterfly arrival dates may shift as temperatures are projected to rise in the southeastern United States, with late-emerging, multivoltine species potentially exhibiting the greatest shifts in adult flight onset dates.

Climate‐associated variation in the within‐season dynamics of juvenile ticks in California

AbstractChanging climate has driven shifts in species phenology, influencing a range of ecological interactions from plant–pollinator to consumer–resource. Phenological changes in host–parasite systems have implications for pathogen transmission dynamics. The seasonal timing, or phenology, of peak larval and nymphal tick abundance is an important driver of tick‐borne pathogen prevalence through its effect on cohort‐to‐cohort transmission. Tick phenology is tightly linked to climatic factors such as temperature and humidity. Thus, variation in climate within and across regions could lead to differences in phenological patterns. These differences may explain regional variation in tick‐borne pathogen prevalence of the Lyme disease‐causing Borrelia bacteria in vector populations in the United States. For example, one factor thought to contribute to high Lyme disease prevalence in ticks in the eastern United States is the asynchronous phenology of ticks there, where potentially infected nymphal ticks emerge earlier in the season than uninfected larval ticks. This allows the infected nymphal ticks to transmit the pathogen to hosts that are subsequently fed upon by the next generation of larval ticks. In contrast, in the western United States where Lyme disease prevalence is generally much lower, tick phenology is thought to be more synchronous with uninfected larvae emerging slightly before, or at the same time as, potentially infected nymphs, reducing horizontal transmission potential. Sampling larval and nymphal ticks, and their host‐feeding phenology, both across large spatial gradients and through time, is challenging, which hampers attempts to conduct detailed studies of phenology to link it with pathogen prevalence. In this study, we demonstrate through intensive within‐season sampling that the relative abundance and seasonality of larval and nymphal ticks are highly variable along a latitudinal gradient and likely reflect the variable climate in the far western United States with potential consequences for pathogen transmission. We find that feeding patterns were variable and synchronous feeding of juvenile ticks on key blood meal hosts was associated with mean temperature. By characterizing within‐season phenological patterns of the Lyme disease vector throughout a climatically heterogeneous region, we can begin to identify areas with high potential for tick‐borne disease risk and underlying mechanisms at a finer scale.

Trends in Vegetation Seasonality in the Iberian Peninsula: Spatiotemporal Analysis Using AVHRR-NDVI Data (1982–2023)

Vegetation seasonality is a critical indicator of ecological responses to global climate change, especially in the Iberian Peninsula, where the intersection of human activity and climate variability amplifies these effects. Understanding these changes is vital for adopting ecogeographical sustainability and developing effective climate adaptation strategies. This study examines trends in vegetation seasonality in the Iberian Peninsula from 1982 to 2023, based on weekly AVHRR NDVI data (2184 images). By integrating Seasonal Trend Analysis (STA) with Robust Trend Analysis (RTA)—including the Theil–Sen (TS) slope estimator, the Contextual Mann–Kendall (CMK) test (α = 0.05), and false discovery rate (FDR) control—we identified significant phenological shifts and widespread vegetation greening. The results reveal a regional response to global patterns of climate change, with 94.2% of the study area exhibiting significant trends, particularly in the Mediterranean ecoregion, where earlier growing seasons are becoming increasingly common. These shifts highlight the urgent need for sustainable land and resource management in the face of accelerating global change. Our findings provide critical insights into the ecological dynamics of the Iberian Peninsula, offering a robust foundation for formulating policies that promote environmental sustainability and enhance resilience to climate change.

A robust method for mapping soybean by phenological aligning of Sentinel-2 time series

Soybean is an important crop for food and animal feed. Production and area both continue to increase and expand into new areas and countries. Spatially explicit information on soybean cultivation is essential to crop monitoring, production estimation, and national accounting systems. However, its cultivation in diverse climate conditions, landscapes, and agricultural systems poses challenges to accurately map soybean across different regions and years. We propose an innovative soybean mapping method combining phenological alignment with machine learning (named here RF-DTW), which can be applied to diverse geographies and years by aligning phenological shifts and using distinctive features from Sentinel-2 time-series. The method first uses the dynamic time warping (DTW) algorithm to align the growing season between pixels across different sites. Then, based on the harmonized time-series, a set of distinctive features was identified and used to build random forest (RF) models to classify soybean across ten globally distributed sites and multiple years. Results show that the green chlorophyll vegetation index (GCVI), greenness and water content composite index (GWCCI), normalized difference senescent vegetation index (NDSVI), red edge position (REP), and short-wave infrared bands are important inputs for distinguishing soybean from other crops. Spectral-phenological features, particularly the curve slope metrics of GCVI and GWCCI during the peak to late growing season, rank as the most important features for mapping soybean. RF-DTW demonstrates good generalizability across ten study sites, achieving an overall accuracy (OA) of 0.92 and an F1-score of 0.84. F1-scores for eight out of ten sites ranged between 0.82 and 0.98, outperforming a benchmark method, although they were lower (F1-score < 0.60) for the two sites in Sub-Saharan Africa. Additionally, RF-DTW performs robustly when transferred to untrained regions and years, with most cases showing an F1-score higher than 0.70. Our proposed method, as a combination of phenological alignment and machine learning, can be used to map soybean accurately and efficiently across different regions and years, to provide crucial information for understanding the rapid dynamics of soybean cultivation and its global-scale impacts.

Phenological response of plants of different biomorphs to climate change in Western Siberia

The results of a phenology study of 78 species of perennial plants from biomorphological groups of chamaephytes, hemicryptophytes and geophytes over a 20-year period (1996—2015) are discussed. Against the background of air temperature and precipitation changes of the warm season in Novosibirsk, the timing shift in phenological events have been analyzed using calculated linear trends. It is found that the trends for species groups are multidirectional and vary significantly in magnitude. At the same time, most of the shifts in phenology are due not to trends, but to the interannual variability of climatic indicators.

Selection and adaptation to weed management methods: implications for non-chemical and integrated weed management approaches.

Herbicide-resistant weeds are a growing global concern, threatening food security. Non-chemical weed management approaches are becoming increasingly important. Furthermore, the adoption of non-conventional agricultural practices is on the rise, with regenerative farming practices aimed at rebuilding soil organic matter, restoring biodiversity, and reducing chemical use gaining traction. Consequently, non-chemical weed management methods are seen as essential solutions. However, excessive reliance on these methods may inadvertently lead to weed selection and adaptation, reducing their effectiveness. Here, we explore the mechanisms driving changes in efficacy due to selectivity and adaptation to non-chemical weed management practices. Additionally, we discuss potential integrated weed management (IWM) strategies that combine chemical and non-chemical methods to mitigate the risks of weed adaptation. This study highlights the role of evolutionary processes in shaping weed adaptation to non-chemical weed management methods and underscores the need to understand these processes to develop IWM approaches that remain effective over time. Monitoring phenological shifts and adaptations in the field should be a key component of decision support systems, tailored to the unique conditions of each site. Furthermore, a deeper understanding of weed adaptation mechanisms can enhance the efficacy of IWM strategies and help delay the inevitable adaptation to these control methods. © 2024 Society of Chemical Industry.

Arctic amplification causes earlier onset of seasonal tree growth in northeastern Siberia

Abstract Although recent warming affects the high-northern latitudes at an unprecedented rate, little is known about its impact on boreal forests because in situ observations from remote ecosystems in Siberia are sparse. Here, we analyze the radial growth and climate sensitivity of 54 Cajander larches (Larix cajanderi Mayr.) from three sites across the northern treeline ecotone within the Omoloy river basin in northeastern Siberia. Three independent tree-ring width chronologies span 279–499 years and exhibit distinct summer temperature signals. These records further reveal evidence for sufficiently earlier onsets of growing seasons since the middle of the 20th century. This phenological shift coincides with rapidly increasing May temperatures and associated earlier snowmelt. Our findings reinforce the importance of high-precision ground measurements from remote regions in Siberia to better understand how warming-induced changes in the functioning and productivity of the boreal forest influence carbon, nutrient, and water cycle dynamics.

Influence of Vegetation Phenology on the Temporal Effect of Crop Fractional Vegetation Cover Derived from Moderate-Resolution Imaging Spectroradiometer Nadir Bidirectional Reflectance Distribution Function–Adjusted Reflectance

Moderate-Resolution Imaging Spectroradiometer (MODIS) Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) products are being increasingly used for the quantitative remote sensing of vegetation. However, the assumption underlying the MODIS NBAR product’s inversion model—that surface anisotropy remains unchanged over the 16-day retrieval period—may be unreliable, especially since the canopy structure of vegetation undergoes stark changes at the start of season (SOS) and the end of season (EOS). Therefore, to investigate the MODIS NBAR product’s temporal effect on the quantitative remote sensing of crops at different stages of the growing seasons, this study selected typical phenological parameters, namely SOS, EOS, and the intervening stable growth of season (SGOS). The PROBA-V bioGEOphysical product Version 3 (GEOV3) Fractional Vegetation Cover (FVC) served as verification data, and the Pearson correlation coefficient (PCC) was used to compare and analyze the retrieval accuracy of FVC derived from the MODIS NBAR product and MODIS Surface Reflectance product. The Anisotropic Flat Index (AFX) was further employed to explore the influence of vegetation type and mixed pixel distribution characteristics on the BRDF shape under different stages of the growing seasons and different FVC; that was then combined with an NDVI spatial distribution map to assess the feasibility of using the reflectance of other characteristic directions besides NBAR for FVC correction. The results revealed the following: (1) Generally, at the SOSs and EOSs, the differences in PCCs before vs. after the NBAR correction mainly ranged from 0 to 0.1. This implies that the accuracy of FVC derived from MODIS NBAR is lower than that derived from MODIS Surface Reflectance. Conversely, during the SGOSs, the differences in PCCs before vs. after the NBAR correction ranged between –0.2 and 0, suggesting the accuracy of FVC derived from MODIS NBAR surpasses that derived from MODIS Surface Reflectance. (2) As vegetation phenology shifts, the ensuing differences in NDVI patterning and AFX can offer auxiliary information for enhanced vegetation classification and interpretation of mixed pixel distribution characteristics, which, when combined with NDVI at characteristic directional reflectance, could enable the accurate retrieval of FVC. Our results provide data support for the BRDF correction timescale effect of various stages of the growing seasons, highlighting the potential importance of considering how they differentially influence the temporal effect of NBAR corrections prior to monitoring vegetation when using the MODIS NBAR product.

Defining algal bloom phenology in Lake Erie

Elucidating the impact of global climate change on aquatic ecosystems, particularly through phenological shifts in primary producers, is critical for understanding ecological resilience. Here, we focus on the phenological shifts in chlorophyll as a proxy for algae biomass and primary production in aquatic ecosystems, specifically in Lake Erie as well as concentrations of the toxin microcystin. By tracking temporal changes in each, we identified key phenological phases important to estimate duration, magnitude, and intensity of harmful algal blooms (HABs). Determining which influential biotic and abiotic factors such as temperature, wind speed, nutrient availability, and climate change is most important, is a long-term management need for Lake Erie, which can be explored using our methodology. Our novel statistical framework employing Bayesian generalized additive mixed models described seasonal chlorophyll and particulate microcystin concentration from Lake Erie and our simple geometric method identified the start, peak, and end of algal blooms. This research enhances our understanding of the ecological effects of nutrient pollution on aquatic ecosystems and provides a repeatable method for determining phenological events without the need for user defined cutoffs which aids in the management and mitigation of HABs, safeguarding water quality in regions dependent on lakes for drinking water.

Climate-Smart Invasive Species Management for 21st Century Global Change Challenges.

Addressing the global challenges of climate change and biotic invasions requires understanding their interactions and implications for natural resource management. To facilitate and support invasive species management in a changing climate, we review how climate change and invasions interact to impact the planning, action, and outcomes of invasive species management. Climate change is facilitating the introduction of new potential invasive species and altering pathways of introduction and spread, with implications for which species natural resource managers need to assess, monitor, and target. Climate-driven shifts in invasive species phenology require more flexible management timelines. Climate change may reduce the efficacy and feasibility of current treatment methods and make native ecosystems more vulnerable to invasion. Additionally, disturbance caused by extreme climate events can compound the spread and impacts of biological invasions, making invasive species management a necessary part of extreme event preparation and response planning. As a solution to these challenges, we propose climate-smart invasive species management, which we define as the approaches that managers and decision-makers can take to address the interactive effects of climate change and invasions. Climate-smart invasive species management includes considering potential shifts in species ranges, abundances, and impacts to inform monitoring, treatment, and policies to prevent new invasive species. Climate-smart management may also involve adjusting the timing and type of treatment to maintain efficacy, promoting resilient ecosystems through climate-smart restoration, and considering the effects of climate change when setting management goals. Explicitly considering the interactions of climate change and biological invasions within organizational decision-making and policy can lead to more effective management and promote more resilient landscapes.

Climate change reduces the tension of conflicting selection pressures on breeding date in a passerine bird.

Unpredictably fluctuating environments create complex selective landscapes that shape the distribution of key life history traits. Identifying the mechanisms behind dynamic patterns of selection is difficult, yet essential for predicting responses to climate change. We combine long-term measures with field manipulation of natural selection on breeding date in a wild bird to investigate whether highly variable spring cold snaps drive fluctuating selection. We show that variation in cold snap intensity leads to fluctuating selection on breeding date-in weak cold snap years, selection was consistently negative; however, in strong cold snap years, its direction reversed. These patterns were mirrored in a field experiment; nests that were food supplemented during cold snaps avoided cold snap mortality leading earlier breeders to have higher fitness. In contrast, in the non-supplemented group earlier breeders had higher cold snap nest mortality and selection was positive. Using nearly a century of climate data, we show that cold snaps are becoming less frequent and paradoxically occurring later which should allow earlier breeders to avoid them, potentially releasing conflicting selection pressures and facilitating a rapid phenological shift. Thus, rather than constraining a species' ability to adapt, climate change can enable a rapid shift to a new phenotypic optimum.

Assessing the phenology and reproductive output of loggerhead turtles in relation to climatic variables at Patara Beach, Türkiye

AbstractLoggerhead turtles (Caretta caretta), being ectothermic organisms, could be especially susceptible to climate change effects, and may exhibit climate‐related variation in their reproductive behaviours such as phenology, annual nest numbers, clutch size, hatching success, incubation period and sex ratio. This study investigated the reproductive phenology and outputs of loggerhead turtles and their relationships with climatic variables over a 5‐year period (2019–2023) at Patara Beach, Türkiye. We found significant fluctuations in atmospheric temperature, sea surface temperature and relative humidity, and that female turtle emergences on Patara Beach could temporarily adjust their phenology in response to these minor environmental changes. We highlight the importance of understanding the impacts of phenological shifts on the ability to satisfy the conditions over the nesting season that determine reproductive output. Our statistical analyses also showed that increasing sea water temperatures and atmospheric temperatures, as well as decreasing precipitation and relative humidity, had direct and/or indirect effects on the nesting phenology and reproductive output of loggerhead turtles. The findings from this study indicate that atmospheric temperature significantly affected incubation period, hatching success rate, the number of dead embryos and the number of empty eggshells. Additionally, relative humidity had a significant impact on the incubation period and the number of empty eggshells. In this context, rising temperatures led to drier nest conditions, decreased incubation periods and increased nest temperatures, resulting in higher proportions of female offspring. In conclusion, there are still gaps in our understanding of the effects of climate change on the reproductive biology of loggerhead turtles, and more studies are needed at both the Mediterranean and global scales to better understand these effects.

Shifts in Plant Phenology and Its Responses to Climate Warming in Three Temperate Cities of China during 1963–2020

The advance of spring phenology and the delay of autumn phenology caused by global warming have been documented by many studies. However, most research has focused on natural areas, with limited studies conducted on phenological observations in urban environments. Here, we selected the first flowering date (FFD), first leaf date (FLD), and leaf coloring date (LCD) at three sites (Beijing, Harbin, and Mudanjiang) from the China Phenological Observation Network. We analyzed the phenological changes of 84 species between 1963–1991 and 1992–2020 to examine their response to urban warming. We then quantified the correlations and regressions between phenological events and preseason temperature. The results show the following: (1) Among the three sites, the mean FFD and FLD were earliest in Beijing, while the mean LCD occurred earliest in Harbin and latest in Beijing. (2) FFD and FLD exhibited a significant trend towards earlier occurrences at all three sites, while LCD showed a significant delay trend except for the Mudanjiang site. Specifically, at the Beijing, Harbin, and Mudanjiang sites, the mean FFD advanced by 8.32 days, 6.11 days, and 2.60 days in the latter period (p &lt; 0.05), whereas the mean FLD advanced by 11.30 days, 7.21 days, and 5.02 days (p &lt; 0.05), respectively. (3) In Beijing, Harbin, and Mudanjiang, both FFD and FLD were significantly negatively correlated with preseason temperature. However, no consistent relationship was observed between LCD and preseason temperature. These results enhance our understanding of the response of plant phenology to urban warming.

Records from Neotropical non-breeding grounds reveal shifts in bird migration phenology over six decades

Changes in the migration phenology of birds linked to global change are extensively documented. Longitudinal studies from temperate breeding grounds have mostly shown earlier arrivals in the spring and a variety of patterns during fall migration,1,2 yet no studies have addressed whether and how migration phenology has changed using data from the tropical non-breeding grounds. Understanding whether changes in migratory phenology are also evident in non-breeding sites is essential to determining the underlying causes of patterns documented in breeding areas. Using data from historical scientific collections and modern repositories of community science records, we assessed changes in the migration phenology of 12 Nearctic-Neotropical long-distance migratory birds in Colombia over six decades. We also explored whether shared breeding and non-breeding climatic niches explained variation in the phenological patterns observed among species. All species showed shifts in spring (range -37 to 9days from peak passage date) or fall (range -26 to 36days) migration, but patterns differed among species in ways partly attributable to shared breeding or wintering climatic niches. Our results, although not yet broadly generalizable, suggest that birds use cues to time their migration at their non-breeding grounds, which are most likely different to those they use on their breeding grounds. To better understand the effects of global change on biodiversity, exploring the underlying drivers of phenological changes with further research integrating more long-term datasets available through scientific collections and community science platforms should be a priority.

Advances in breeding phenology outpace latitudinal and elevational shifts for North American birds tracking temperature.

Terrestrial species can respond to a warming climate in multiple ways, including shifting in space (via latitude or elevation) and time (via phenology). Evidence for such shifts is often assessed independent of other temperature-tracking mechanisms; critically, no study has compared shifts across all three spatiotemporal dimensions. Here we used two continental-scale monitoring databases to estimate trends in the breeding latitude (311 species), elevation (251 species) and phenology (111 species) of North American landbirds over 27 years, with a shared pool of 102 species. We measured the magnitude of shifts and compared them relative to average regional warming (that is, shift ratios). Species shifted poleward (1.1 km per year, mean shift ratio 11%) and to higher elevations (1.2 m per year, mean shift ratio 17%), while also shifting their breeding phenology earlier (0.08 days per year, mean shift ratio 28%). These general trends belied substantial variation among species, with some species shifting faster than climate, whereas others shifted more slowly or in the opposite direction. Across the three dimensions (n = 102), birds cumulatively tracked temperature at 33% of current warming rates, 64% of which was driven by advances in breeding phenology as opposed to geographical shifts. A narrow focus on spatial dimensions of climate tracking may underestimate the responses of birds to climate change; phenological shifts may offer an alternative for birds-and probably other organisms-to conserve their thermal niche in a warming world.

Phenological Shifts in Lake Ice Cover Across the Northern Hemisphere: A Glimpse Into the Past, Present, and the Future of Lake Ice Phenology

AbstractLong‐term ice phenology records quantify the effects of climate change on Northern Hemisphere lakes. This study uses lake ice phenological records across a gradient of lake sizes (0.1–31,967.8 km2 in lake surface area) obtained from community science networks. We compiled in situ ice phenological records for 2,499 lakes across 15 countries for an average of 30 years. These data revealed that for the last 50 years (1971–2020), the annual mean duration of lake ice cover decreased at a rate of 9 days per decade, with a regime shift in lake ice phenology in the late 1980s. We projected that at the end of the century (2070–2099), ice duration will decrease by an average of 10 days when compared to the historical time period (1971–2000) for the shared socioeconomic pathway (SSP) 1–2.6 climate scenario (SSP126), 23 days for SSP370, and 28 days for the SSP585. Impending human development can enhance or attenuate lake ice loss, as adaptation strategies can accelerate fossil fuel use, result in conflict, or seek strategies apart from fossil fuel development. These future pathways have critical implications for the future preservation of lake ice cover.

Climate change increases flowering duration, driving phenological reassembly and elevated co-flowering richness.

Changes to flowering phenology are a key response of plants to climate change. However, we know little about how these changes alter temporal patterns of reproductive overlap (i.e. phenological reassembly). We combined long-term field (1937-2012) and herbarium records (1850-2017) of 68 species in a flowering plant community in central North America and used a novel application of Bayesian quantile regression to estimate changes to flowering season length, altered richness and composition of co-flowering assemblages, and whether phenological shifts exhibit seasonal trends. Across the past century, phenological shifts increased species' flowering durations by 11.5 d on average, which resulted in 94% of species experiencing greater flowering overlap at the community level. Increases to co-flowering were particularly pronounced in autumn, driven by a greater tendency of late season species to shift the ending of flowering later and to increase flowering duration. Our results demonstrate that species-level phenological shifts can result in considerable phenological reassembly and highlight changes to flowering duration as a prominent, yet underappreciated, effect of climate change. The emergence of an autumn co-flowering mode emphasizes that these effects may be season-dependent.