Changes In Phenology Research Articles

Remotely sensed and ground measurements reveal intraspecific differences in early season needle unfolding and senescence, but lack of variability in litter flammability of Pinus halepensis

Pinus halepensis Mill. is a conifer typical of Mediterranean pinewoods adapted to drought and fire. Although the timing of seasonal events in P. halepensis is strongly associated with these stressors and other environmental factors, needle phenology and litter flammability are insufficiently characterized at the intraspecific level. These traits can be informative of the existence of locally adapted populations across the species’ distribution range, and remote sensing approaches are promising tools to infer phenological changes in forest trees. In this study, we investigated intraspecific differentiation of P. halepensis related to needle phenology at the onset of the fire season (May-June) through vegetation indexes (VIs) obtained from unmanned aerial vehicles. We collected drone images using multispectral and RGB sensors for 56 adult populations of P. halepensis categorized into five ecotypes growing in two common gardens located in Spain under contrasting conditions (dry-continental versus wet-coastal). In the dry trial, we additionally monitored the temporal variation of RGB-derived indexes using two flights spaced over a one-month period. We also performed four consecutive ground measurements of needle pigments and fuel moisture content and obtained litter flammability traits for a subset of populations. Most in situ measurements and flammability traits did not show population differentiation. Regarding RGB-derived VIs, we did not detect obvious temporal patterns which differed among populations. However, we observed greener canopies in June than in May, which are indicative of the pace of current-year needle development. We also deduced an earlier phenology (i.e., earlier current-year needle unfolding) in the dry-continental trial. Ecotypic differentiation was found for some vegetation indexes related to needle unfolding (i.e., TCARI/OSAVI) and old needle senescence (i.e., PRSI). These differences were generally consistent across trials and time, and fundamentally indicated that sub-humid ecotypes typical of the eastern Mediterranean showed earlier needle unfolding and old needle senescence than semiarid ecotypes thriving in western continental Mediterranean areas. The intraspecific divergence observed in early season phenology is potentially related to the existence of contrasting life-history strategies present at the intraspecific level for the species. In particular, some semi-arid ecotypes, which are known to optimize the trade-off between carbon gain and water loss, exhibited an early old needle senescence (high likelihood of crown fire development) coupled with a late needle unfolding (conservative water use). These results indicate a possible trade-off between drought and fire resistance for the species, which suggest the importance of considering the intraspecific characteristics of Aleppo pine in forest management actions.

Farmers’ Perceptions of Climate Change and Its Socio-Ecological Consequences in Bhutan’s Biological Corridor Network

Sandwiched between two highly populated countries in the world, Bhutan is not an exception to the impacts of climate change. In the dearth of comprehensive climate data and limited research endeavors, Bhutan’s 69% of the total population, depending on agriculture and livestock farming, is apparently vulnerable to climate change adversities. Notably, those dwelling within the precincts of the Biological Corridors (BCs), recognized as custodians and conservation partners, have been relatively neglected in aspects of climate change impact studies. In the year 2019, our pioneering study in the northern biological corridors of Bhutan aimed to (i) comprehend people’s sensitivity to climate change; (ii) discern people’s perceptions on the severity of climate change impacts on livelihood, natural resources, and wildlife patterns; and (iii) help formulate appropriate strategies and policy transformation in climate adaptation interventions. We conducted a semi-structured questionnaire survey, applying random sampling (n = 136) of 435 households from western, central, and eastern Bhutan. Study revealed that farmers’ sensitivity and perception of the impact of climate change vary spatiotemporally, demographically, and occupationally. Not more than 76.7% of respondents noticed the changing climate patterns over the last ten years, while landless households (3%) noticed no discernible impacts. A rise in temperature is the most sensitive variable reported, followed by erratic precipitation, a change in plant phenology, and a shift in wildlife occupancy patterns. A total of 48% of respondents reported drought, scanty rain, floods, and diseases that moderately affected agriculture crops and livestock, while 42% of respondents perceive that climate change is a driving factor for human–wildlife conflict because of increasing wild animal movement towards their region. About 51% of respondents indicated adopting new adaptation strategies, which involved transitioning to different cattle breeds and altering agricultural cropping patterns and crop varieties. We recommend political support for inducing climate-smart agriculture and livestock practices. Urgent research is recommended for the shift of habitats and wildlife due to climate change to better understand and help formulate pragmatic climate adaptation measures in the face of rising human–wildlife conflict.

The impacts of aridification on land surface phenological changes in the farming-pastoral ecotone of northern China based on the climatic zoning method

The impacts of aridification on land surface phenological changes in the farming-pastoral ecotone of northern China based on the climatic zoning method

Differential effects of climatic and non-climatic factors on the distribution of vegetation phenology trends on the Tibetan plateau

The study of vegetation phenology changes is important because it is a sensitive indicator of climate change, affecting the exchange of carbon, energy and water fluxes between the land and the atmosphere. Previous studies have focused on the effects of climatic factors among environmental factors on vegetation phenology, thus the effects of non-climatic factors among environmental factors have not been well quantified. This study endeavors to scrutinize the spatiotemporal inconsistency in the start-of-season (SOS) and the end-of-season (EOS) on the Tibetan Plateau (TP) and to quantify the effects of environmental factors on phenology. To this end, the Moderate-resolution Imaging Spectroradiomater (MODIS) Normalized Difference Vegetation Index (NDVI) data from 2001 to 2018 and four common used methods were employed to extract SOS and EOS, and the site data was used to select the most appropriate phenology results. The Geodetector model was used to assess and measure the explanatory power of different environmental factors. The research results indicate that temperature exerts a more substantial impact on phenology than precipitation on TP. non-climatic factors such as longitude, latitude, and elevation are more influential in determining the distribution of phenological trends than climatic factors. Among these non-climatic factors, latitude has the most prominent effect on the trends of SOS. Furthermore, non-climatic factors exhibit a stronger effect on SOS, whereas EOS is more susceptible to climatic factors and less influenced by non-climatic factors. These discoveries bear great significance in comprehending the intricate outcomes of regional changes on vegetation phenology and enhancing phenology models.

INTRAGRO: A machine learning approach to predict future growth of trees under climate change.

The escalating impact of climate change on global terrestrial ecosystems demands a robust prediction of the trees' growth patterns and physiological adaptation for sustainable forestry and successful conservation efforts. Understanding these dynamics at an intra-annual resolution can offer deeper insights into tree responses under various future climate scenarios. However, the existing approaches to infer cambial or leaf phenological change are mainly focused on certain climatic zones (such as higher latitudes) or species with foliage discolouration during the fall season. In this study, we demonstrated a novel approach (INTRAGRO) to combine intra-annual circumference records generated by dendrometers coupled to the output of climate models to predict future tree growth at intra-annual resolution using a series of supervised and unsupervised machine learning algorithms. INTRAGRO performed well using our dataset, that is dendrometer data of P. roxburghii Sarg. from the subtropical mid-elevation belt of Nepal, with robust test statistics. Our growth prediction shows enhanced tree growth at our study site for the middle and end of the 21st century. This result is remarkable since the predicted growing season by INTRAGRO is expected to shorten due to changes in seasonal precipitation. INTRAGRO's key advantage is the opportunity to analyse changes in trees' intra-annual growth dynamics on a global scale, regardless of the investigated tree species, regional climate and geographical conditions. Such information is important to assess tree species' growth performance and physiological adaptation to growing season change under different climate scenarios.

Effects of Climate Change and Urbanization on Vegetation Phenology in the Bucharest Metropolitan Area

Being an essential issue in global warming, the response of urban vegetation to climate change and urbanization has become an increasing concern at both the local and global levels. This study aims to investigate the effect of the urban environment on vegetation phenology for the Bucharest metropolitan area in Romania and to identify the potential climate drivers that influence key phenology in the urban environment. In this study, we comprehensively analyzed the response of urban vegetation phenology shifts due to climate variability and urbanization in the Bucharest metropolitan area from a spatiotemporal perspective during the 2002- 2022 period. Through synergy use of time series of the main climate variables, Air temperature -AT, land surface temperature (LST), and biophysical variables derived from MODIS Terra/Aqua satellite and in-situ data, this study developed a complex statistical and spatial regression analysis. Green space was measured with satellite-derived vegetation indicators Normalized Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI), Net Primary Production (NPP) data, which captures the combined availability of urban parks, street trees, forest, and periurban agricultural areas. Leaf Area Index (LAI) and Photosynthetically active radiation (FPAR) indicators have been used to characterize the effects of meteorological parameters and urbanization impacts on vegetation phenology and their changes. The results show that the response of vegetation phenology to urbanization level and climate parameters variability has a distinct spatiotemporal difference across the urban/periurban gradient. The findings of this study show that the land surface temperature anomalies associated with urbanization-induced climate warming, especially during strong summer heat waves and under urban heat islands alter urban vegetation biophysical properties, directly impacting its phenology shifts. At the metropolitan scale, the urban thermal environment directly impacts vegetation phenology patterns. The quantitative findings of this study are of great importance for understanding the complex impacts of urbanization and climate changes on vegetation phenology and for developing models to predict vegetation phenological changes under future urbanization.

The impact of vegetation phenology changes on the relationship between climate and net primary productivity in Yunnan, China, under global warming.

Climate influences net primary productivity (NPP) either directly or indirectly via phenology. Therefore, clarifying the indirect effects of climate on NPP through phenology is of utmost importance. However, the underlying mechanisms by which phenology indirectly affects NPP are unknown and poorly studied. Based on different structural equation models, this study analyzed the influence of phenology on the relationship between climate and NPP, and the results were as follows: (1) Temperature and solar radiation directly affect the end and beginning of the growing season, respectively, while precipitation indirectly affects the beginning of the growing season. (2) Spring phenology mainly affects the relationship between subsequent precipitation and net primary productivity, while autumn phenology mainly affects the relationship between temperature and net primary productivity. (3) Solar radiation is the most important direct influence factor on phenology and NPP, and the relationship between it and NPP is hardly disturbed by vegetation phenology. This research holds significant scientific and applied values in enhancing our understanding of the effects of global warming, forecasting ecosystem responses in the future, and formulating adaptation strategies.

The phenological response of European vegetation to urbanisation is mediated by macrobioclimatic factors

Plant phenology is a crucial component of ecosystem functioning and is affected by multiple elements of global change; we therefore need to quantify the current phenological changes associated to human activities and understand their impacts on ecosystems. Urbanisation and the intensification of anthropogenic activities alter meteorological conditions and cause phenological changes in urban vegetation worldwide. We used remote sensing data to evaluate the phenological response (start of season date SOS, length of season LOS and end of season date EOS) of five main vegetation types (evergreen forests, deciduous forests, mixed forests, sparse woody vegetation and grasslands) to urbanisation in the 69 most populated pan-European metropolitan areas (i.e., those that include cities with a population over 450,000 inhabitants) for the period 2002–2021. In general, SOS advanced and LOS increased with urbanisation intensity across European metropolitan areas. We found that macrobioclimatic factors strongly determined the strength and direction of the phenological response to urbanisation intensity. The greatest advances in SOS with increasing urbanisation were registered in metropolitan areas in the Mediterranean region, where there was also more uncertainty in this relationship. The EOS advanced with urbanisation in metropolitan areas in the Mediterranean macrobioclimate, whereas in areas with higher precipitation during summer the opposite trend was observed suggesting water availability mediates the response between urbanisation and autumn phenophases. Our results suggest that macrobioclimatic constraints operating at the continental scale are crucial to understand the relationship between plant phenology and urbanisation intensity.

The effect of seasonality and weather conditions on human perception of the urban–rural transitional landscape

Landscape perception research into the impact of seasonally changing landscape characteristics with the simultaneous influence of the weather are rare. Therefore, eye-tracking metrics were calculated (fixation and saccades) for the whole tested landscape, while its areas of interest (AOIs) were established based on clustering methods. Moreover, the gaze pattern was analysed using the Voronoi cells method. To identify significant differences in landscape perception according to various weather and seasonality, nonparametric tests were applied. The significant influence of weather/seasonality and their synergistic influence is noticed. The results indicate a rather complex influence of the types of weather in warmer and cooler seasons. Regardless of the weather type, seasonal changes cause greater visual span and shorter fixations in the warmer season. The fixations and saccades are shorter in the warmer season in two AOI’s during positive weather, but are longer in negative weather during the colder season in most AOI’s. The main reasons for the influence of weather and seasonality on the visual perception include seasonal changes in the landscape, resulting in the appearance of the landscape from more urban to natural and vice versa (phenological changes) as well as lighting changes (due to seasonality and type of weather).

Phytoplankton as indicators of global warming?

AbstractTerrestrial plants are sensitive indicators of global warming because their annual cycles of growth and senescence are changing as warming proceeds. Single celled algae are distinct life forms capable of population bursts in any season, so there is uncertainty about phytoplankton phenology as a comparable indicator of global warming. We analyzed 4+ decades of monthly chlorophyll a measurements at two sites in San Francisco Bay and found abrupt shifts during summer months leading to a 48‐day advance in the annual pattern of chlorophyll‐a accumulation at one site and a 36‐day delay at the other. These large phenological changes were not associated with changing temperature, but they were associated with changes in top–down control by bivalve filter feeders as biological communities were restructured by (1) introduction of a non‐native clam, and (2) a shift in atmospheric forcing of the NE Pacific. This study illustrates that changes in phytoplankton phenology are not necessarily responses to or indicators of global warming. However, they can be indicators of human disturbances and natural climate oscillations having effects large enough to mask the effect of climate warming.

Shifts in intra-annual growth dynamics drive a decline in productivity of temperate trees in Central European forest under warmer climate

Climate change shifts tree growth phenology and dynamics in temperate forests. However, there is still little information on how warming climate changes intra-annual growth patterns and how these changes affect the productivity and carbon uptake of temperate trees. To address this knowledge gap, we used high-precision growth data from automatic dendrometers to quantify the impacts of unusually warm weather in 2022 (hot year) on growth phenology, dynamics and aboveground biomass (AGB) production in eight common temperate species (both conifers and broadleaved) in the Czech Republic. Mixed-effect models were used to investigate inter-annual changes in the start, end, and length of the growing season and intra-annual growth dynamics. We also modelled how changes in growth phenology, growth rates, and tree size affected yearly AGB production of individual trees. In the hot year, the growth started 5 days earlier, peaked 22 days earlier and ended 20 days earlier than in the climatically normal year, resulting in a shorter growing season with fewer growing days. AGB production decreased 36 % in the hot year, mainly due to fewer growing days and lower maximum growth rates, but with significant variation among tested species. The decline in AGB production in the hot year was most significant in the most productive species, which were also the species with the greatest reduction in the number of growing days. Tree size strongly enhanced AGB production, but its effect did not change with climate variation. Our findings suggest that climate change is likely to advance but also shorten the growing season of temperate trees, resulting in lower biomass production and carbon uptake. The results also indicate that the fast-growing and highly productive temperate tree species will have their growth reduced most by climate change, which will increasingly limit their high carbon sequestration potential.

Mapping oak wilt disease from space using land surface phenology

Protecting the future of forests relies on our ability to observe changes in forest health. Thus, developing tools for sensing diseases in a timely fashion is critical for managing threats at broad scales. Oak wilt —a disease caused by a pathogenic fungus (Bretziella fagacearum)— is threatening oaks, killing thousands yearly while negatively impacting the ecosystem services they provide. Here we propose a novel workflow for mapping oak wilt by targeting temporal disease progression through symptoms using land surface phenology (LSP) from spaceborne observations. By doing so, we hypothesize that phenological changes in pigments and photosynthetic activity of trees affected by oak wilt can be tracked using LSP metrics derived from the Chlorophyll/Carotenoid Index (CCI). We used dense time-series observations from Sentinel-2 to create Analysis Ready Data across Minnesota and Wisconsin and to derive three LSP metrics: the value of CCI at the start and end of the growing season, and the coefficient of variation of the CCI during the growing season. We integrate high-resolution airborne imagery in multiple locations to select pixels (n = 3872) from the most common oak tree health conditions: healthy, symptomatic for oak wilt, and dead. These pixels were used to train an iterative Partial Least Square Discriminant (PLSD) model and derive the probability of an oak tree (i.e., pixel) in one of these conditions and the associated uncertainty. We assessed these models spatially and temporally on testing datasets revealing that it is feasible to discriminate among the three health conditions with overall accuracy between 80 and 82%. Within conditions, our models suggest that spatial variations among three CCI-derived LSP metrics can identify healthy (Area Under the Curve (AUC) = 0.98), symptomatic (AUC = 0.89), and dead (AUC = 0.94) oak trees with low false positive rates. The model performance was robust across different years as well. The predictive maps were used to guide local stakeholders to locate disease hotspots for ground verification and subsequent decision-making for treatment. Our results highlight the capabilities of LSP metrics from dense spaceborne observations to map diseases and to monitor large-scale change in biodiversity.

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.

Male reproductive success is not strongly affected by phenological changes in mate availability in monoecious Sagittaria latifolia.

Many plants express their female and male sex roles at different times (dichogamy), with important consequences for mating. Dichogamy can yield mate limitation via biased floral sex ratios, particularly at the beginning and end of the flowering season when many plants simultaneously function as the same sex. This form of mate limitation should be reduced if plants adjust their allocations to female versus male sex functions in a manner that tracks seasonal variability in mating opportunities. For example, under protogyny (i.e. dichogamy with female function expressed first) plants with male-biased sex expression should have enhanced mating opportunities early in the flowering season as other plants begin to flower (in female sex phase). We quantified seasonal changes in sex allocation, patterns of mate availability and realized siring success in a population of protogynous Sagittaria latifolia. Our results were consistent with previous findings that seasonal changes in sex allocation should compensate for lost mating opportunities under the temporally variable mating environments caused by dichogamy. However, patterns of siring success in the population were inconsistent with this interpretation. We suggest that realized siring success might depend more strongly on spatial than on temporal aspects of mate availability.

Citizen science data reveal possible multi-decadal phenological changes in the arrival time of a migratory tropical seabird species at the breeding ground

Citizen science data reveal possible multi-decadal phenological changes in the arrival time of a migratory tropical seabird species at the breeding ground

Application of statistical models in the detection of grapevine phenology changes

In recent decades, there have been significant changes in temperature and precipitation, as well as in the occurrence of phenological stages of the grapevine in most wine-growing regions around the world. These changes are not the same for each variety, nor in all locations. Due to the vulnerability of the viticulture sector, including the possible losses in production in the current winegrowing areas, as well as the planting of vineyards in new areas, it is of great importance to examine the trends in the occurrence of individual stages and to link them as successfully as possible with changes in meteorological parameters. The simplest approach to this is using agrometeorological indices (e.g., Growing degree day, GDD) which can determine the possibility of growing a certain variety. There is also the possibility of developing and testing simple statistical phenological models that serve to predict the occurrence of phenological stages. Four such models were tested for the prediction of four phenological stages (budburst, flowering, veraison, and harvest) for four grape varieties ('Graševina', 'Chardonnay', 'Merlot', and 'Plavac mali') in Croatia. The first two models are commonly used GDD models with a temperature base of 10 °C or 5 °C, and thresholds necessary for phenological stage to start depending on variety or variety and location. The other two models are based on the determination of the best multi-linear regression using as predictors monthly and multi-month averages of minimum temperature, maximum temperature, mean temperature, and total precipitation. The increase in temperature index values from the 1990s to today is particularly significant. Statistical phenological models also proved to be a good indicator of the occurrence of individual phenological stages. GDD models proved to be somewhat better in prediction, GDD models that use a temperature of 5 °C as a base proved to be better for predicting budburst, those that use a base of 10 °C proved to be better for the other stages and particularly for flowering (with agreement index d up to 0.8 and root mean square error of prediction RMSE from 5 to 10 days). Linear regression that uses temperature as a predictor and the same equation regardless of location proved to be very good in predicting the harvest of autochthonous varieties ('Graševina' and 'Plavac mali') with low RMSE (up to 10 days). The presented results indicate that these models could be applied to future scenarios and with that help to make decisions in the wine sector in Croatia and worldwide.

Utilizing herbarium specimens to assist with the listing of rare plants

Funding for rare plant conservation is limited. In addition, many aspects of the biology and ecology of rare plants are unknown. Therefore, low-cost data generation approaches to fill these gaps should be pursued. Herbarium specimens can be used as a low-cost alternative to learn about the basic biology and ecology of rare plant species. The information provided on herbarium labels has dramatically increased in recent decades to include precise locality (i.e., latitude/longitude), exact dates, habitat, associated species, and substrate. In addition, herbarium specimens are being digitized and the resulting images and data are available via clearinghouses such as GBIF and SEINet. Already, herbarium specimens of rare plants have been used to develop habitat suitability models, predict range shifts, and assess changes in flower phenology due to climate change. Herbarium specimens can also provide a wealth of information about the reproductive biology and biotic interactions of rare plants. In this paper, we will demonstrate how this information can be accessed and present a practical application for using this information to populate an important federal listing document in the USA, Species Status Assessments (SSA). We will provide examples from the literature, as well as case studies from our own research, to demonstrate how this information can be collected from herbarium specimens and how and where to incorporate this information into SSAs. More generally, data gleaned from herbarium specimens can become part of a conservationist’s tool kit to further our knowledge of past, present, and future trends for rare plants. Additional knowledge of a species’ biology and ecology allows land managers and conservationists to make more informed decisions and allows for greater protection of listed species.

Droughts force temporal change and spatial migration of vegetation phenology in the northern Hemisphere

Ecosystems are exposed to continuous shifts in droughts. This shows up as a point on a pixel that moves continuously in a specific direction and angle (spatial migration) to preserve its original climate niche. We currently do not have a good understanding whether ecosystems exposed to droughts are more sensitive to droughts temporal trends or spatial migrations. Using dataset of vapor pressure deficit (VPD), total water storage anomaly (TWSA), and standardized soil moisture index (SSMI), we tested the spatiotemporal sensitivity of vegetation phenology to extreme droughts and compound extreme droughts, respectively. On the temporal scale, we found that the differences in the sensitivity of vegetation phenology to VPD, TWSA, and SSMI were mainly reflected in the lag time. Compared to normal years, however, the start of growing season (SOS) was advanced and the end of growing season (EOS) was delayed in most pixels even under extreme preseason droughts. Such results can be attributed to the extreme atmospheric driving forces. On the spatial scale, the spatial migration velocity of SOS and EOS was best correlated with the extreme atmospheric drought (r = 0.5, p < 0.01) and the extreme soil drought in the third layer (r = 0.43, p < 0.01), respectively. Compared to extreme droughts, however, the effects of compound extreme droughts on the spatial migration of vegetation phenology only produced weak negative feedback (|r| < 0.1, p < 0.01). This indicate that the velocity of vegetation phenology was consistent with the velocity of single extreme droughts. Our results emphasize the temporal sensitivity of droughts on vegetation phenology and the accompanying effects of extreme droughts on the spatial shifts in vegetation phenology.

Detection and attribution of the start of the growing season changes in the Northern Hemisphere

Global climate change has led to significant changes in land surface phenology. At present, research on the factors influencing the start of the growing season (SOS) mainly focuses on single factor effects, such as temperature and precipitation, ignoring the combined action of multiple factors. The impact of multiple factors on the spatial and temporal patterns of the SOS in the Northern Hemisphere is not clear, and it is necessary to combine multiple factors to quantify the degrees of influence of different factors on the SOS. Based on the GIMMS3g NDVI dataset, CRU climate data and other factor data, we used geographic detector model, random forest regression model, multiple linear regression, partial correlation analysis and Sen + Mann-Kendall trend analysis to explore the variation of the SOS in the Northern Hemisphere to reveal the main driving factors and impact threshold of 17 influencing factors on the SOS. The results showed that (1) during the past 34 years (1982–2015), the SOS in Europe and Asia mainly showed an advancing trend, whereas the SOS in North America mainly showed a delaying trend. (2) The SOS was mainly controlled by frost frequency, temperature and humidity. Increasing frost frequency inhibited the advancement of the SOS, and increasing temperature and humidity promoted the advancement of the SOS. (3) There were thresholds for the influences of the driving factors on the SOS. Outside the threshold ranges, the response mechanism of the SOS to driving factors changed. The results are important for understanding the response of the SOS to global climate change.

Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data

While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake.