Region-specific phenological sensitivities and rates of climate warming generate divergent temporal shifts in flowering date across a species' range

Incorporating plant phenological responses into species distribution models reduces estimates of future species loss and turnover

Anthropogenetic climate change has caused range shifts among many species. Species distribution models (SDMs) are used to predict how species ranges may change in the future. However, most SDMs rarely consider how climate-sensitive traits, such as phenology, which affect individuals' demography and fitness, may influence species' ranges. Using > 120 000 herbarium specimens representing 360 plant species distributed across the eastern United States, we developed a novel 'phenology-informed' SDM that integrates phenological responses to changing climates. We compared the ranges of each species forecast by the phenology-informed SDM with those from conventional SDMs. We further validated the modeling approach using hindcasting. When examining the range changes of all species, our phenology-informed SDMs forecast less species loss and turnover under climate change than conventional SDMs. These results suggest that dynamic phenological responses of species may help them adjust their ecological niches and persist in their habitats as the climate changes. Plant phenology can modulate species' responses to climate change, mitigating its negative effects on species persistence. Further application of our framework will contribute to a generalized understanding of how traits affect species distributions along environmental gradients and facilitate the use of trait-based SDMs across spatial and taxonomic scales.

Sex-dependent phenological responses to climate vary across species' ranges

Anthropogenic climate change has significantly altered the flowering times (i.e., phenology) of plants worldwide, affecting their reproduction, survival, and interactions. Recent studies utilizing herbarium specimens have uncovered significant intra- and inter-specific variation in flowering phenology and its response to changes in climate but have mostly been limited to animal-pollinated species. Thus, despite their economic and ecological importance, variation in phenological responses to climate remain largely unexplored among and within wind-pollinated dioecious species and across their sexes. Using both herbarium specimens and volunteer observations of cottonwood (Populus) species, we examined how phenological sensitivity to climate varies across species, their ranges, sexes, and phenophases. The timing of flowering varied significantly across and within species, as did their sensitivity to spring temperature. In particular, male flowering generally happened earlier in the season and was more sensitive to warming than female flowering. Further, the onset of flowering was more sensitive to changes in temperature than leaf out. Increased temporal gaps between male and female flowering time and between the first open flower date and leaf out date were predicted for the future under two climate change scenarios. These shifts will impact the efficacy of sexual reproduction and gene flow among species. Our study demonstrates significant inter- and intra-specific variation in phenology and its responses to environmental cues, across species' ranges, phenophases, and sex, in wind-pollinated species. These variations need to be considered to predict accurately the effects of climate change and assess their ecological and evolutionary consequences.

Complex climate-mediated effects of urbanization on plant reproductive phenology and frost risk

Urbanization can affect the timing of plant reproduction (i.e. flowering and fruiting) and associated ecosystem processes. However, our knowledge of how plant phenology responds to urbanization and its associated environmental changes is limited. Herbaria represent an important, but underutilized source of data for investigating this question. We harnessed phenological data from herbarium specimens representing 200 plant species collected across 120 yr from the eastern US to investigate the spatiotemporal effects of urbanization on flowering and fruiting phenology and frost risk (i.e. time between the last frost date and flowering). Effects of urbanization on plant reproductive phenology varied significantly in direction and magnitude across species ranges. Increased urbanization led to earlier flowering in colder and wetter regions and delayed fruiting in regions with wetter spring conditions. Frost risk was elevated with increased urbanization in regions with colder and wetter spring conditions. Our study demonstrates that predictions of phenological change and its associated impacts must account for both climatic and human effects, which are context dependent and do not necessarily coincide. We must move beyond phenological models that only incorporate temperature variables and consider multiple environmental factors and their interactions when estimating plant phenology, especially at larger spatial and taxonomic scales.

FLOWERING LOCUS C drives delayed flowering in Arabidopsis grown and selected at elevated CO 2

Altered flowering time at elevated [CO ₂ ] is well documented, although mechanisms are not well understood. An Arabidopsis genotype previously selected for high fitness at elevated [CO ₂ ] (SG) showed delayed flowering and larger size at flowering when grown at elevated (700 ppm) versus current (380 ppm) [CO ₂ ]. This response was correlated with prolonged expression of FLOWERING LOCUS C ( FLC ), a vernalization-responsive floral repressor gene. To determine if FLC directly delays flowering at elevated [CO ₂ ] in SG, we used vernalization (extended cold) to downregulate FLC expression. We hypothesized that vernalization would eliminate delayed flowering at elevated [CO ₂ ] through the direct reduction of FLC expression, eliminating differences in flowering time between current and elevated [CO ₂ ]. We found that with downregulation of FLC expression via vernalization, SG plants grown at elevated [CO ₂ ] no longer delayed flowering compared to current [CO ₂ ]. Thus, vernalization returned the earlier flowering phenotype, counteracting effects of elevated [CO ₂ ] on flowering. This study indicates that elevated [CO ₂ ] can delay flowering directly through FLC , and downregulation of FLC under elevated [CO ₂ ] reverses this effect. Moreover, this study demonstrates that increasing [CO ₂ ] may potentially drive major changes in development through FLC .

The ecological implications of intra- and inter-species variation in phenological sensitivity

Plant-pollinator mutualisms rely upon the synchrony of interacting taxa. Climate change can disrupt this synchrony as phenological responses to climate vary within and across species. However, intra- and interspecific variation in phenological responses is seldom considered simultaneously, limiting our understanding of climate change impacts on interactions among taxa across their ranges. We investigated how variation in phenological sensitivity to climate can alter ecological interactions simultaneously within and among species using natural history collections and citizen science data. We focus on a unique system, comprising a wide-ranged spring ephemeral with varying color morphs (Claytonia virginica) and its specialist bee pollinator (Andrena erigeniae). We found strongly opposing trends in the phenological sensitivities of plants vs their pollinators. Flowering phenology was more sensitive to temperature in warmer regions, whereas bee phenology was more responsive in colder regions. Phenological sensitivity varied across flower color morphs. Temporal synchrony between flowering and pollinator activity was predicted to change heterogeneously across the species' ranges in the future. Our work demonstrates the complexity and fragility of ecological interactions in time and the necessity of incorporating variation in phenological responses across multiple axes to understand how such interactions will change in the future.

Impact of ambient temperature, precipitation and seven years of experimental warming and nutrient addition on fruit production in an alpine heath and meadow community

Alpine and polar regions are predicted to be among the most vulnerable to changes in temperature, precipitation, and nutrient availability. We carried out a seven-year factorial experiment with warming and nutrient addition in two alpine vegetation communities. We analyzed the relationship between fruit production and monthly mean, maximum, and min temperatures during the fall of the pre-fruiting year, the fruiting summer, and the whole fruit production period, and measured the effects of precipitation and growing and thawing degree days (GDD & TDD) on fruit production. Nutrient addition (heath: 27.88 ± 3.19 fold change at the end of the experiment; meadow: 18.02 ± 4.07) and combined nutrient addition and warming (heath: 20.63 ± 29.34 fold change at the end of the experiment; meadow: 18.21 ± 16.28) increased total fruit production and fruit production of graminoids. Fruit production of evergreen and deciduous shrubs fluctuated among the treatments and years in both the heath and meadow. Pre-maximum temperatures had a negative effect on fruit production in both communities, while current year maximum temperatures had a positive impact on fruit production in the meadow. Pre-minimum, pre-mean, current mean, total minimum, and total mean temperatures were all positively correlated with fruit production in the meadow. The current year and total precipitation had a negative effect on the fruit production of deciduous shrubs in the heath. GDD had a positive effect on fruit production in both communities, while TDD only impacted fruit production in the meadow. Increased nutrient availability increased fruit production over time in the high alpine plant communities, while experimental warming had either no effect or a negative effect. Deciduous shrubs were the most sensitive to climate parameters in both communities, and the meadow was more sensitive than the heath. The difference in importance of TDD for fruit production may be due to differences in snow cover in the two communities.

Differential changes in life cycle-event phenology provide a window into regional population declines

Climate change affects the phenology of annual life cycle events of organisms, such as reproduction and migration. Shifts in the timing of these events could have important population implications directly, or provide information about the mechanisms driving population trajectories, especially if they differ between life cycle event. We examine if such shifts occur in a declining migratory passerine bird (willow warbler, Phylloscopus trochilus), which exhibits latitudinally diverging population trajectories. We find evidence of phenological shifts in breeding initiation, breeding progression and moult that differ across geographic and spring temperature gradients. Moult initiation following warmer springs advances faster in the south than in the north, resulting in proportionally shorter breeding seasons, reflecting higher nest failure rates in the south and in warmer years. Tracking shifts in multiple life cycle events allowed us to identify points of failure in the breeding cycle in regions where the species has negative population trends, thereby demonstrating the utility of phenology analyses for illuminating mechanistic pathways underlying observed population trajectories.

Climate warming-driven phenological shifts are species-specific in woody plants: evidence from twig experiment in Kashmir Himalaya

Experimental evidences in support of climate warming-driven phenological shifts are still scarce, particularly from the developing world. Here, we investigated the effect of experimental warming on flowering phenology of selected woody plants in Kashmir Himalaya. We selected the twigs of four congeneric pairs of temperate woody species (Prunus, Populus, Ulmus, Viburnum)-typical spring-flowering plants in the region. Using randomised block design, we monitored these winter dormant twigs in controlled growth chambers to study the effect of different temperature regimes (9, 17, 20 and 23 °C) and species identity on the patterns of phenological shifts. We observed a significant phenological shift in all the species showing preponement in the first flower out and senescence phases ranging from 0.56 to 3.0 and 0.77 to 4.04 days per degree increase in temperature, respectively. The duration of flowering phase in all the species showed a corresponding decrease along the gradient of increasing temperature, which was more driven by preponement of the flower senescence than the start of flowering. The patterns of phenological shifts were highly species-specific, and the magnitude of these shifts significantly varied in all the four pairs of congeneric species despite their phylogenetic similarity. Our study provides experimental support to the previous long-term observation and herbarium-based studies showing that the patterns of phenological shifts in response to global climate warming are likely to vary between species, even those belonging to same evolutionary stock. Our findings highlight that a one-size-fits-all strategy to manage the likely impacts of climate warming-induced phenological shifts will seldom succeed, and should instead be designed for the specific phenological responses of species and regions.

Machine Learning Undercounts Reproductive Organs on Herbarium Specimens but Accurately Derives Their Quantitative Phenological Status: A Case Study of Streptanthus tortuosus

Machine learning (ML) can accelerate the extraction of phenological data from herbarium specimens; however, no studies have assessed whether ML-derived phenological data can be used reliably to evaluate ecological patterns. In this study, 709 herbarium specimens representing a widespread annual herb, Streptanthus tortuosus, were scored both manually by human observers and by a mask R-CNN object detection model to (1) evaluate the concordance between ML and manually-derived phenological data and (2) determine whether ML-derived data can be used to reliably assess phenological patterns. The ML model generally underestimated the number of reproductive structures present on each specimen; however, when these counts were used to provide a quantitative estimate of the phenological stage of plants on a given sheet (i.e., the phenological index or PI), the ML and manually-derived PI's were highly concordant. Moreover, herbarium specimen age had no effect on the estimated PI of a given sheet. Finally, including ML-derived PIs as predictor variables in phenological models produced estimates of the phenological sensitivity of this species to climate, temporal shifts in flowering time, and the rate of phenological progression that are indistinguishable from those produced by models based on data provided by human observers. This study demonstrates that phenological data extracted using machine learning can be used reliably to estimate the phenological stage of herbarium specimens and to detect phenological patterns.