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As a consequence of warming temperatures around the world, spring and autumn phenologies have been shifting, with corresponding changes in the length of the growing season. Our understanding of the spatial and interspecific variation of these changes, however, is limited. Not all species are responding similarly, and there is significant spatial variation in responses even within species. This spatial and interspecific variation complicates efforts to predict phenological responses to ongoing climate change, but must be incorporated in order to build reliable forecasts. Here, we use a long-term dataset (1953–2005) of plant phenological events in spring (flowering and leaf out) and autumn (leaf colouring and leaf fall) throughout Japan and South Korea to build forecasts that account for these sources of variability. Specifically, we used hierarchical models to incorporate the spatial variability in phenological responses to temperature to then forecast species' overall and site-specific responses to global warming. We found that for most species, spring phenology is advancing and autumn phenology is getting later, with the timing of events changing more quickly in autumn compared with the spring. Temporal trends and phenological responses to temperature in East Asia contrasted with results from comparable studies in Europe, where spring events are changing more rapidly than are autumn events. Our results emphasize the need to study multiple species at many sites to understand and forecast regional changes in phenology.

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an ‘extra’ day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.

CONTENTS: Summary 926 I. Introduction 927 II. What triggers a plant to leaf-out? 928 III. Variation in leaf-out among species 929 IV. Leaf-out and climate change 932 V. Conclusions 937 Acknowledgements 937 References 937 SUMMARY: Leafing-out of woody plants begins the growing season in temperate forests and is one of the most important drivers of ecosystem processes. There is substantial variation in the timing of leaf-out, both within and among species, but the leaf development of almost all temperate tree and shrub species is highly sensitive to temperature. As a result, leaf-out times of temperate forests are valuable for observing the effects of climate change. Analysis of phenology data from around the world indicates that leaf-out is generally earlier in warmer years than in cooler years and that the onset of leaf-out has advanced in many locations. Changes in the timing of leaf-out will affect carbon sequestration, plant-animal interactions, and other essential ecosystem processes. The development of remote sensing methods has expanded the scope of leaf-out monitoring from the level of an individual plant or forest to an entire region. Meanwhile, historical data have informed modeling and experimental studies addressing questions about leaf-out timing. For most species, onset of leaf-out will continue to advance, although advancement may be slowed for some species because of unmet chilling requirements. More information is needed to reduce the uncertainty in predicting the timing of future spring onset.

The paper analyses time series of thermal growing season (GS) start (GSS) and end dates (GSE) and length (GSL) in three cities representing urbanised areas of Central Europe (Kraków, Prague, Vienna) in the period 1792–2020. The classification of dates of growing season start and end, as well as length of the designated growing seasons, was conducted from climate data. An attempt was made to identify the dominant patterns of GS course, considering its start date, length, and end date collectively. In the period 1972–2020 in Central Europe, the growing season was prolonged, although the changes in particular stations selected for analysis occurred unevenly and simultaneously resulted from different causes. Three subperiods can be designated, differing in the intensity of changes in the start and end dates, as well as growing season length. The intensification of the rate of the occurring changes was recorded in all stations at the end of the twentieth and in the twenty-first century. There is a trend of decreasing frequency of short and abnormally short periods and more and more frequent occurrence of long and abnormally long seasons in the analysed multiannual period. Regardless of the differences between the stations in the designated GS types, the shortest of them were observed simultaneously at all three analysed stations in the period 1830–1860 and at the beginning of the twentieth century. The opposite type, representing the longest GS, is most abundant since the 1990s in Central Europe.

Climate change will increase both average temperatures and extreme summer temperatures. Analyses of the fitness consequences of climate change have generally omitted negative fitness and population declines associated with heat stress. Here, we examine how seasonal and interannual temperature variability will impact fitness shifts of ectotherms from the past (1961–1990) to future (2071–2100), by modelling thermal performance curves (TPCs) for insect species across latitudes. In temperate regions, climate change increased the length of the growing season (increasing fitness) and increased the frequency of heat stress (decreasing fitness). Consequently, species at mid‐latitudes (20–40°) showed pronounced but heterogeneous responses to climate change. Fitness decreases for these species were accompanied by greater interannual variation in fitness. An alternative TPC model and a larger data set gave qualitatively similar results. How close maximum summer temperatures are to the critical thermal maximum of a species – the thermal buffer – is a good predictor of the change in mean fitness expected under climate change. Thermal buffers will decrease to near or below zero by 2100 for many tropical and mid‐latitude species. Our forecasts suggest that mid‐latitude species will be particularly susceptible to heat stress associated with climate change due to temperature variation.

A large number of water- and climate-related applications, such as drought monitoring, are based on spaceborne-derived relationships between land surface temperature (LST) and the normalized difference vegetation index (NDVI). The majority of these applications rely on the existence of a negative slope between the two variables, as identified in site- and time-specific studies. The current paper investigates the generality of the LST-NDVI relationship over a wide range of moisture and climatic/radiation regimes encountered over the North American continent (up to 60°N) during the summer growing season (April-September). Information on LST and NDVI was obtained from long-term (21 years) datasets acquired with the Advanced Very High Resolution Radiometer (AVHRR). It was found that when water is the limiting factor for vegetation growth (the typical situation for low latitudes of the study area and during the midseason), the LST- NDVI correlation is negative. However, when energy is the limiting factor for vegetation growth (in higher latitudes and elevations, especially at the beginning of the growing season), a positive correlation exists between LST and NDVI. Multiple regression analysis revealed that during the beginning and the end of the growing season, solar radiation is the predominant factor driving the correlation between LST and NDVI, whereas other biophysical variables play a lesser role. Air temperature is the primary factor in midsummer. It is concluded that there is a need to use empirical LST-NDVI relationships with caution and to restrict their application to drought monitoring to areas and periods where negative correlations are observed, namely, to conditions when water-not energy-is the primary factor limiting vegetation growth.

Community ecologists have long recognized the importance of phenology (the timing of periodic life-history events) in structuring communities. Phenological differences between exotic and native species may contribute to the success of invaders, yet a general theory for how phenology may shape invasions has not been developed. Shifts toward longer growing seasons, tracked by plant and animal species worldwide, heighten the need for this analysis. The concurrent availability of extensive citizen-science and long-term datasets has created tremendous opportunities to test the relationship between phenology and invasion. Here, we (1) extend major theories within community and invasion biology to include phenology, (2) develop a predictive framework to test these theories, and (3) outline available data resources to test predictions. By creating an integrated framework, we show how new analyses of long-term datasets could advance the fields of community ecology and invasion biology, while developing novel strategies for invasive species management. Although we focus here on terrestrial plants, our framework has clear extensions to animal communities and aquatic ecosystems as well.

For accurate interpretation of oxygen isotopes in tree rings (δ¹⁸O), it is necessary to disentangle the mechanisms underlying the variations in the tree's internal water cycle and to understand the transfer of source versus leaf water δ¹⁸O to phloem sugars and stem wood. We studied the seasonal transfer of oxygen isotopes from precipitation and soil water through the xylem, needles and phloem to the tree rings of Larix decidua at two alpine sites in the Lötschental (Switzerland). Weekly resolved δ¹⁸O records of precipitation, soil water, xylem and needle water, phloem organic matter and tree rings were developed. Week‐to‐week variations in needle‐water ¹⁸O enrichment were strongly controlled by weather conditions during the growing season. These short‐term variations were, however, not significantly fingerprinted in tree‐ring δ¹⁸O. Instead, seasonal trends in tree‐ring δ¹⁸O predominantly mirrored trends in the source water, including recent precipitation and soil water pools. Modelling results support these findings: seasonal tree‐ring δ¹⁸O variations are captured best when the week‐to‐week variations of the leaf water signal are suppressed. Our results suggest that climate signals in tree‐ring δ¹⁸O variations should be strongest at temperate sites with humid conditions and precipitation maxima during the growing season.

The Earth is warming, especially in polar areas in which winter temperatures and precipitation are expected to increase. Despite a growing research focus on winter climatic change, the impacts on Arctic terrestrial ecosystems remain poorly understood. Snow acts as an insulator, and depth changes affect the enhancement of thermally dependent reactions, such as microbial activity, affecting soil nutrient composition, respiration, and winter gas efflux. Snow depth and spring temperatures influence snowmelt timing, determining the start of plant growth and forage availability. Delays in winter onset affect tundra carbon balance, faunal hibernation, and migration but are unlikely to lengthen the plant growing season. Mild periods in winter followed by a return to freezing have negative consequences for plants and invertebrates, and the resultant ice layers act as barriers to foraging, triggering starvation of herbivores and their predators. In summary, knock-on effects between seasons and trophic levels have important consequences for biological activity, diversity, and ecosystem function.

Although temperature is an important driver of seasonal changes in photosynthetic physiology, photoperiod also regulates leaf activity. Climate change will extend growing seasons if temperature cues predominate, but photoperiod-controlled species will show limited responsiveness to warming. We show that photoperiod explains more seasonal variation in photosynthetic activity across 23 tree species than temperature. Although leaves remain green, photosynthetic capacity peaks just after summer solstice and declines with decreasing photoperiod, before air temperatures peak. In support of these findings, saplings grown at constant temperature but exposed to an extended photoperiod maintained high photosynthetic capacity, but photosynthetic activity declined in saplings experiencing a naturally shortening photoperiod; leaves remained equally green in both treatments. Incorporating a photoperiodic correction of photosynthetic physiology into a global-scale terrestrial carbon-cycle model significantly improves predictions of seasonal atmospheric CO2 cycling, demonstrating the benefit of such a function in coupled climate system models. Accounting for photoperiod-induced seasonality in photosynthetic parameters reduces modeled global gross primary production 2.5% (∼4 PgC y–1), resulting in a >3% (∼2 PgC y–1) decrease of net primary production. Such a correction is also needed in models estimating current carbon uptake based on remotely sensed greenness. Photoperiod-associated declines in photosynthetic capacity could limit autumn carbon gain in forests, even if warming delays leaf senescence.