Modeling greenup date of dominant grass species in the Inner Mongolian Grassland using air temperature and precipitation data

Divergent response of grassland aboveground net primary productivity and precipitation utilization efficiency to altered precipitation patterns by process-based model

The functioning of ecosystem services in water-limited grassland ecosystems is significantly influenced by precipitation characteristics. This study aims to quantitatively assess the impact of different precipitation scenarios on grassland productivity using the APSIM model. Historical weather data from 1968 to 2017 and observational data from three types of steppes (meadow, typical, and desert steppe) in Inner Mongolia Autonomous Region from 2004 to 2010 were collected to determine key crop variety parameters for the APSIM model. The effects of annual precipitation, seasonal precipitation, and inter-growing season precipitation variability on aboveground net primary production (ANPP) and precipitation utilization efficiency (PUE) in different types of steppes were investigated by scenario simulation by validated model. The simulated ANPP shows distinctive responses to the changed rainfall characteristics, where the influence of precipitation decreasing is more evident than precipitation increasing by the same precipitation change. Regarding steppe types, the typical steppe responded more strongly to increased precipitation, while decreased precipitation led to higher decline in ANPP for desert steppe. Precipitation during growing seasons caused more significant change than dormancy seasons regarding ANPP, however, PUE show the opposite trend, indicating the contribution of unit level precipitation changes to productivity is significant during dormancy seasons. The effect of changing precipitation during middle growing season outweighed that of late growing season and early growing season, and the positive effect of increasing precipitation were more pronounced in typical steppe and desert steppe if facing early growing season precipitation increase in the future. The research results provide a theoretical basis and technical support for optimizing grassland production management.

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.

Spatiotemporal variation of autumn phenology responses to preseason drought and temperature in alpine and temperate grasslands in China

We investigate the spatiotemporal patterns and environmental controls of the end of the vegetation growing season (EOS) in autumn across the alpine and temperate grasslands of China from 2001 through 2020, focusing on whether the EOS is likely a "dryness effect" due to drought or a "coolness effect" caused by cold temperature in autumn. The results show that the EOS date is earlier (∼6 days earlier on average) in alpine grasslands than in temperate grasslands. During 2001-2020, a slight non-significant delay of 1.0 day/decade is observed for the regional averaged EOS, which is mostly induced by the delayed EOS in 64.4 % of the study region. Preseason temperature (1-2 months before the EOS) exerts a positive control on the EOS in most of the alpine grasslands and some regions of the eastern part of the temperate grasslands, while drought with a mean length of 3.2 months before the EOS exerts positive effects on the EOS in the central, southwestern, and western parts of the temperate grasslands and in the northeastern part of the alpine grasslands. The positive effects of temperature and drought are very likely phenomena reflecting that the EOS is the "coolness effect" associated with lower temperatures in autumn and the "dryness effect" due to drought, especially meteorological drought without consideration of soil moisture, in late summer and/or early autumn, respectively. Our findings are supported by an analysis of the spatial patterns of the cold degree days (CDD) and EOS sensitivity to the CDD. However, the negative effects of drought are also found in eastern temperate grasslands, likely caused by decreased temperature accompanied by increased moisture. The results presented here highlight the importance of incorporating the impacts of droughts on EOS variability, as well as their interactive effects with temperature, into current vegetation autumn phenology models for grasslands.

Species differences in the green-up date of typical vegetation in Inner Mongolia and climate-driven mechanism based on process-based phenology models

Different species within the same community may exhibit distinct phenological responses to climate change, so it is necessary to study species differences in the green-up date among abundant species within a wide area, and a suitable phenology model should be introduced to explain the associated climate-driven mechanism. Although various models have been developed, very few studies have aimed to compare their efficiency and robustness, and the relative contributions of climate driving factors have not been sufficiently examined. We analyzed phenology data for 12 species across 17 stations in Inner Mongolia and found that essential spatiotemporal and interspecies differences existed in the green-up date. Five process-based models were established for each species and their performance was comprehensively evaluated. The two-phase models (sequential model, parallel model, unified model and unified model combined with precipitation driving) generally performed better than the one-phase model (thermal time model), and the model considering precipitation performed the best, which indicates that it is necessary to introduce the chilling effect and precipitation driving effect to improve the model accuracy in arid environments. We proposed a method to estimate the contribution rates of various climate driving factors, and significant differences in the relative demand for the various climate driving factors among different species were clearly revealed. The results indicated that for natural vegetation in Inner Mongolia, the need for the chilling and temperature driving is relatively high, and the precipitation driving is very important for herbaceous vegetation, which leads to considerable spatial and interspecies differences in green-up date. We demonstrated the feasibility of quantitatively evaluating the contributions of different climate driving factors with a process-based model, and the contradiction in phenological changes among different studies may eventually be clarified.

Satellite-Based Monitoring on Green-Up Date for Optimizing the Rest-Grazing Period in Xilin Gol Grassland

Ecological degradation has occurred in global grasslands and has impaired their ecosystem services severely, so ecological conservation of grasslands should be focused more on the effectiveness of management measures. The green-up process decides the year-round forage yield and ecological conditions of grasslands. Adopting rest-grazing during the green-up process can guarantee a successful green-up, thus realizing more economic benefits without grassland degradation. Therefore, studies should pay more attention to whether the green-up process is really covered by the rest-grazing period or not. We analyze the spatiotemporal variations and the stability of the annual green-up date in Xilin Gol Grassland from 2000 to 2018 based on MODIS time series images and compare the green-up date with the rest-grazing period to assess the effectiveness of the rest-grazing policy. The results show that the green-up date of Xilin Gol Grassland had advanced 15 days on average because of the increasing trend of both temperature and precipitation during 2000~2018. The green-up date is mostly 120~130 d in the east, about 10 days earlier than the west (130~140 d) and 20 days earlier than in the central areas (140~150 d), also because of the spatial variations of temperature and precipitation. The coefficient of variation (CV) of the green-up date showed a significant negative correlation with precipitation, so the green-up date is more unstable in the arid areas. The rest-grazing period started more than 45 days earlier than the green-up date and failed to cover it in several years, which occurred more frequently in southern counties. The average green-up date appeared after rest-grazing started in over 98% of areas, and the time gap is 15~45 days in 88% of areas, which not only could not avoid grassland degradation effectively but also increased herdsmen’s life burden. This study aims to accurately grasp the temporal and spatial variations of the green-up date in order to provide references for adjusting a more proper rest-grazing period, thus promoting ecological conservation and sustainable development of animal husbandry.

Spatial Difference between Temperature and Snowfall Driven Spring Phenology of Alpine Grassland Land Surface Based on Process-Based Modeling on the Qinghai–Tibet Plateau

As a sensitive indicator for climate change, the spring phenology of alpine grassland on the Qinghai–Tibet Plateau (QTP) has received extensive concern over past decade. It has been demonstrated that temperature and precipitation/snowfall play an important role in driving the green-up in alpine grassland. However, the spatial differences in the temperature and snowfall driven mechanism of alpine grassland green-up onset are still not clear. This manuscript establishes a set of process-based models to investigate the climate variables driving spring phenology and their spatial differences. Specifically, using 500 m three-day composite MODIS NDVI datasets from 2000 to 2015, we first estimated the land surface green-up onset (LSGO) of alpine grassland in the QTP. Further, combining with daily air temperature and precipitation datasets from 2000 to 2015, we built up process-based models for LSGO in 86 meteorological stations in the QTP. The optimum models of the stations separating climate drivers spatially suggest that LSGO in grassland is: (1) controlled by temperature in the north, west and south of the QTP, where the precipitation during late winter and spring is less than 20 mm; (2) driven by the combination of temperature and precipitation in the middle, east and southwest regions with higher precipitation and (3) more likely controlled by both temperature and precipitation in snowfall dominant regions, since the snow-melting process has negative effects on the air temperature. The result dictates that snowfall and rainfall should be concerned separately in the improvement of the spring phenology model of the alpine grassland ecosystem.

A process-based model reveals the restoration gap of degraded grasslands in Inner Mongolian steppe

Due to the influence of climate change and extensive grazing, a large proportion of steppe grassland has been degraded worldwide. The Chinese government initiated a series of grassland restoration programs to reverse the degradation. However, the limiting factors and the restoration potential remain unknown. Here we present a process-based model to assess the restoration gap (RG) defined as maximum biomass differences between non-degraded and degraded grasslands with different degrees of soil and vegetation degradation. The process-based model Agricultural Production Systems Simulator (APSIM) was evaluated utilizing observation data from both typical and meadow steppes under natural conditions in terms of phenology, dynamics of above-ground biomass and soil water content. Scenario analysis and sensitivity analysis were subsequently performed to address the RG and controlling factors during 1969-2018. The results showed that the calibrated model performed well with r > 0.75 and model efficiency factor EF > 0.5 for all the simulation components. According to our model results, the RG was larger in typical steppe compared to that of meadow steppe and it increased with increasing soil and/or vegetation degradation, to ~60% under extremely degraded scenarios. Both soil and vegetation degradation led to reduced water use efficiency, with an elevated proportion of soil evaporation to evapotranspiration (Es/ET), however, the limiting factor for RG varied. The degradation of soil water holding capacity contributed more to RG regardless of climate conditions for typical steppe in all years and for meadow steppe in dry years. In wet years the importance of vegetation coverage reduction increased for RG in meadow steppe, where the relative importance of vegetation coverage (valued at 62.8%) was 25.6% higher than that of soil degradation. Our results demonstrated the importance of considering climate variations when developing protection and restoration programs for grassland ecosystems.

Impacts of preseason drought on vegetation spring phenology across the Northeast China Transect

Vegetation phenology is undergoing profound changes in response to the recent increases in the intensity and frequency of drought events. However, the mechanisms by which drought affects the start of the growing season (SGS) are poorly understood particularly in arid and semi-arid regions. Here, we identified varying degrees of preseason drought events and analyzed the sensitivity of the SGS to preseason drought across the Northeast China Transect (NECT). Our results showed that drought caused a delayed SGS in grassland ecosystems, but an advanced SGS within forest ecosystems. These contrasting responses to preseason drought reflected different adaptive strategies between vegetation types. The SGS was shown to be highly sensitive to short timescales drought (1-3 months) in semi-arid grasslands where annual precipitation is 200-300 mm (i.e. SAGE_200-300). Biomes within this region were found to be most vulnerable out of all the ecosystems to drought. Given the frequent nature of droughts in the mid-latitudes, a drought early warning system was recommended accompanied by improved modeling of how the SGS will be affected by intensified drought under future climate change.

Why don't phenophase dates in the current year affect the same phenophase dates in the following year?

Examining whether a phenophase occurrence date in the current year affects the same phenophase occurrence date in the following year is crucial for developing cross-year phenological prediction models. Here, we carried out correlation analyses between leaf unfolding start (LUS)/leaf fall end (LFE) dates in the current and following years for four dominant tree species in temperate northern China from 1981 to 2012. Then, we calculated the recurrence intervals of LUS and LFE between two adjacent years for each species. Moreover, we investigated temperature effects on LUS/LFE dates, growing season and non-growing season lengths. Results show that correlation coefficients between LUS/LFE dates in the current and following years are nonsignificant at most stations. The recurrence interval of a phenophase has slight interannual variation and correlates significantly (and negatively) with the phenophase occurrence date of the current year. Further analyses indicate that LUS dates correlate significantly (and negatively) with spring mean temperatures, while LFE dates correlate significantly (and positively) with autumn mean temperatures, but negatively with growing season mean temperatures. In addition, spring mean temperatures can influence growing season length by controlling LUS date but cannot influence the following non-growing season length. Similarly, autumn mean temperatures and growing season mean temperatures can influence the subsequent non-growing season length but cannot influence the growing season length of the following year. Our study highlights that recurrence interval and time restrictions in the effects of seasonal temperatures on phenophase dates are the main environmental causes of nonsignificant correlations between phenophase occurrence dates in the current and following years.

Contrasting Effects of Temperature and Precipitation on Vegetation Greenness along Elevation Gradients of the Tibetan Plateau

The Tibetan Plateau (TP) is one of the most sensitive regions to global climate warming, not only at the inter-annual time scale but also at the altitudinal scale. We aim to investigate the contrasting effects of temperature and precipitation on vegetation greenness at different altitudes across the TP. In this study, interannual and elevational characteristics of the Normalized Difference Vegetation Index (NDVI), temperature, and precipitation were examined during the growing season from 1982 to 2015. We compared the elevational movement rates of the isolines of NDVI, temperature, and precipitation, and the sensitivities of elevational NDVI changes to temperature and precipitation. The results show that from 1982 to 2015, the elevational variation rate of isolines for NDVI mismatched with that for temperature and precipitation. The elevational movements of NDVI isolines were mostly controlled by precipitation at elevations below 2400 m and by the temperature at elevations above 2400 m. Precipitation appears to plays a role similar to temperature, and even a more effective role than the temperature at low elevations, in controlling elevational vegetation greenness changes at both spatial and interannual scales in the TP. This study highlights the regulation of temperature and precipitation on vegetation ecosystems along elevation gradients over the whole TP under global warming conditions.

Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

Both vegetation phenology and net primary productivity (NPP) are crucial topics under the background of global change, but the relationships between them are far from clear. In this study, we quantified the spatial-temporal vegetation start (SOS), end (EOS), and length (LOS) of the growing season and NPP for the temperate grasslands of China based on a 34-year time-series (1982–2015) normalized difference vegetation index (NDVI) derived from global inventory modeling and mapping studies (GIMMS) and meteorological data. Then, we demonstrated the relationships between NPP and phenology dynamics. The results showed that more than half of the grasslands experienced significant changes in their phenology and NPP. The rates of their changes exhibited spatial heterogeneity, but their phenological changes could be roughly divided into three different clustered trend regions, while NPP presented a polarized pattern that increased in the south and decreased in the north. Different trend zones’ analyses revealed that phenology trends accelerated after 1997, which was a turning point. Prolonged LOS did not necessarily increase the current year’s NPP. SOS correlated with the NPP most closely during the same year compared to EOS and LOS. Delayed SOS contributed to increasing the summer NPP, and vice versa. Thus, SOS could be a predictor for current year grass growth. In view of this result, we suggest that future studies should further explore the mechanisms of SOS and plant growth.

Photoperiod controls vegetation phenology across Africa

Vegetation phenology is driven by environmental factors such as photoperiod, precipitation, temperature, insolation, and nutrient availability. However, across Africa, there's ambiguity about these drivers, which can lead to uncertainty in the predictions of global warming impacts on terrestrial ecosystems and their representation in dynamic vegetation models. Using satellite data, we undertook a systematic analysis of the relationship between phenological parameters and these drivers. The analysis across different regions consistently revealed photoperiod as the dominant factor controlling the onset and end of vegetation growing season. Moreover, the results suggest that not one, but a combination of drivers control phenological events. Consequently, to enhance our predictions of climate change impacts, the role of photoperiod should be incorporated into vegetation-climate and ecosystem modelling. Furthermore, it is necessary to define clearly the responses of vegetation to interactions between a consistent photoperiod cue and inter-annual variation in other drivers, especially under a changing climate.

Inner Mongolian grassland plant phenological changes and their climatic drivers

Global warming is widely believed to extend the length of plant growing season (LOS) through advancing the start (SOS) and delaying the end (EOS) of plant growing season. However, divergent directions of phenological changes under current climate warming have been frequently reported but poorly understood. Here we collate the long-term filed phenological and climatic records at 8 sites in Inner Mongolian grassland to assess how climate changes regulate the phenological variations with divergent directions and magnitudes in this region. We found that the spring climatic changes (e.g., changes in air temperature and precipitation during March and April) correlate well with variations in SOS. However, our in situ observations show divergent changes in SOS across space, which can be attributed to the generally insignificant changes of climates during the preseasons of SOS. The climate warming prior to the end of plant growing season (EOS) was generally significant at most sites. Nevertheless, the effects of such warming on changes in EOS were possibly overshadowed by the impacts of precipitation in this arid/semi-arid region. As a result, the temporal variations in EOS distribute divergent directions and magnitudes across space and species. Using climate attributes during the preseason of EOS alone can hardly explain changes in EOS. Alternatively, by introducing changes in SOS as an additional driving factor, variations in EOS can be well represented. We therefore infer that plant phenologies can divergently response to current global warming (depending on the seasonal patterns of warming). Moreover, other influential factors such as precipitation and the interactions between the timings of different phenological stages are also needed in predicting the phenological dynamics.

Spring- and fall-flowering species show diverging phenological responses to climate in the Southeast USA

Plant phenological shifts (e.g., earlier flowering dates) are known consequences of climate change that may alter ecosystem functioning, productivity, and ecological interactions across trophic levels. Temperate, subalpine, and alpine regions have largely experienced advancement of spring phenology with climate warming, but the effects of climate change in warm, humid regions and on autumn phenology are less well understood. In this study, nearly 10,000 digitized herbarium specimen records were used to examine the phenological sensitivities of fall- and spring-flowering asteraceous plants to temperature and precipitation in the US Southeastern Coastal Plain. Climate data reveal warming trends in this already warm climate, and spring- and fall-flowering species responded differently to this change. Spring-flowering species flowered earlier at a rate of 1.8-2.3 days per 1 °C increase in spring temperature, showing remarkable congruence with studies of northern temperate species. Fall-flowering species flowered slightly earlier with warmer spring temperatures, but flowering was significantly later with warmer summer temperatures at a rate of 0.8-1.2 days per 1 °C. Spring-flowering species exhibited slightly later flowering times with increased spring precipitation. Fall phenology was less clearly influenced by precipitation. These results suggest that even warm, humid regions may experience phenological shifts and thus be susceptible to potentially detrimental effects such as plant-pollinator asynchrony.

Variability of bio-climatology indicators in the Southwest China under climate warming during 1961-2015

Southwest China (SWC), characterized by complex climate, undulating topography, intertwined mountains and basins, and diverse ecosystem, is a global hotspot in biodiversity. SWC also is sensitive to climate change, the effects of which can be expressed through alterations in bio-climatology indicators. In this study, we investigated the trends of the key bio-climatology indicators, including mean temperature of the warmest month (TWM), mean temperature of the coldest month (TCM), accumulated temperature above 5 °C (AT₅) and 10 °C (AT₁₀), number of days with daily mean temperature above 5 °C (DT₅) and 10 °C (DT₁₀), annual precipitation (P), precipitation days (DP), and moisture index (MI). The 105 meteorological stations data from 1961 to 2015 were selected to examine the trend of these indexes in SWC. The results suggested that TWM and TCM both experienced a significant upward trend, with the more pronounced increase in TCM than that in TWM. TWM increased by 0.011 °C year^-1 and TCM increased by 0.025 °C year^-1. AT₅, AT₁₀, DT₅, and DT₁₀ also exhibited increasing trend, with AT₁₀ > AT₅ and DT₁₀ > DT₅, and the trend in DT was found to be less significant than that in AT. The increment of AT₅, AT₁₀, DT₅, and DT₁₀ were 6.452 °C year^-1, 7.158 °C year^-1, 0.164 days year^-1, and 0.263 days year^-1, respectively. P, DP, and MI showed a downward trend, among which DP experienced a significant decrease with - 1.018 days year^-1. In general, SWC tends to be drier and warmer, which may alter the structure and function of the local ecosystem, further then affect the role as a global diversity hotspot.

Phenological responses of Icelandic subarctic grasslands to short-term and long-term natural soil warming

The phenology of vegetation, particularly the length of the growing season (LOS; i.e., the period from greenup to senescence), is highly sensitive to climate change, which could imply potent feedbacks to the climate system, for example, by altering the ecosystem carbon (C) balance. In recent decades, the largest extensions of LOS have been reported at high northern latitudes, but further warming-induced LOS extensions may be constrained by too short photoperiod or unfulfilled chilling requirements. Here, we studied subarctic grasslands, which cover a vast area and contain large C stocks, but for which LOS changes under further warming are highly uncertain. We measured LOS extensions of Icelandic subarctic grasslands along natural geothermal soil warming gradients of different age (short term, where the measurements started after 5 years of warming and long term, i.e., warmed since ≥50 years) using ground-level measurements of normalized difference vegetation index. We found that LOS linearly extended with on average 2.1 days per °C soil warming up to the highest soil warming levels (ca. +10°C) and that LOS had the potential to extend at least 1 month. This indicates that the warming impact on LOS in these subarctic grasslands will likely not saturate in the near future. A similar response to short- and long-term warming indicated a strong physiological control of the phenological response of the subarctic grasslands to warming and suggested that genetic adaptations and community changes were likely of minor importance. We conclude that the warming-driven extension of the LOSs of these subarctic grasslands did not saturate up to +10°C warming, and hence that growing seasons of high-latitude grasslands are likely to continue lengthening with future warming (unless genetic adaptations or species shifts do occur). This persistence of the warming-induced extension of LOS has important implications for the C-sink potential of subarctic grasslands under climate change.

The rise of phenology with climate change: an evaluation of IJB publications

In recent decades, phenology has become an important tool by which to measure both the impact of climate change on ecosystems and the feedback of ecosystems to the climate system. However, there has been little attempt to date to systematically quantify the increase in the number of scientific publications with a focus on phenology and climate change. In order to partially address this issue, we examined the number of articles (original papers, reviews and short communications) containing the terms 'phenology' and 'climate change' in the title, abstract or keywords, published in the International Journal of Biometeorology in the 60 years since its inception in 1957. We manually inspected all issues prior to 1987 for the search terms and subsequently used the search facility on the Web of Science online database. The overall number of articles published per decade remained relatively constant (255-378) but rose rapidly to 1053 in the most recent decade (2007-2016), accompanied by an increase (41-172) in the number of articles containing the search terms. A number of factors may have contributed to this rise, including the recognition of the value of phenology as an indicator of climate change and the initiation in 2010 of a series of conferences focusing on phenology which subsequently led to two special issues of the journal. The word 'phenology' was in use from the first issue, whereas 'climate change' only emerged in 1987 and peaked in 2014. New technologies such as satellite remote sensing and the internet led to an expansion of and greater access to a growing reservoir of phenological information. The application of phenological data included determining the impact of warming of phenophases, predicting wine quality and the pollen season, demonstrating the potential for mismatch to occur and both reconstructing and forecasting climate. Even though this analysis was limited to one journal, it is likely to be indicative of a similar trend across other scientific publications.

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

Five years of phenological monitoring in a mountain grassland: inter-annual patterns and evaluation of the sampling protocol

The increasingly important effect of climate change and extremes on alpine phenology highlights the need to establish accurate monitoring methods to track inter-annual variation (IAV) and long-term trends in plant phenology. We evaluated four different indices of phenological development (two for plant productivity, i.e., green biomass and leaf area index; two for plant greenness, i.e., greenness from visual inspection and from digital images) from a 5-year monitoring of ecosystem phenology, here defined as the seasonal development of the grassland canopy, in a subalpine grassland site (NW Alps). Our aim was to establish an effective observation strategy that enables the detection of shifts in grassland phenology in response to climate trends and meteorological extremes. The seasonal development of the vegetation at this site appears strongly controlled by snowmelt mostly in its first stages and to a lesser extent in the overall development trajectory. All indices were able to detect an anomalous beginning of the growing season in 2011 due to an exceptionally early snowmelt, whereas only some of them revealed a later beginning of the growing season in 2013 due to a late snowmelt. A method is developed to derive the number of samples that maximise the trade-off between sampling effort and accuracy in IAV detection in the context of long-term phenology monitoring programmes. Results show that spring phenology requires a smaller number of samples than autumn phenology to track a given target of IAV. Additionally, productivity indices (leaf area index and green biomass) have a higher sampling requirement than greenness derived from visual estimation and from the analysis of digital images. Of the latter two, the analysis of digital images stands out as the more effective, rapid and objective method to detect IAV in vegetation development.

Temperature and snowfall trigger alpine vegetation green-up on the world's roof

Rapid temperature increase and its impacts on alpine ecosystems in the Qinghai-Tibetan Plateau, the world's highest and largest plateau, are a matter of global concern. Satellite observations have revealed distinctly different trend changes and contradicting temperature responses of vegetation green-up dates, leading to broad debate about the Plateau's spring phenology and its climatic attribution. Large uncertainties in remote-sensing estimates of phenology significantly limit efforts to predict the impacts of climate change on vegetation growth and carbon balance in the Qinghai-Tibetan Plateau, which are further exacerbated by a lack of detailed ground observation calibration. Here, we revealed the spatiotemporal variations and climate drivers of ground-based herbaceous plant green-up dates using 72 green-up datasets for 22 herbaceous plant species at 23 phenological stations, and corresponding daily mean air temperature and daily precipitation data from 19 climate stations across eastern and southern parts of the Qinghai-Tibetan Plateau from 1981 to 2011. Results show that neither the continuously advancing trend from 1982 to 2011, nor a turning point in the mid to late 1990s as reported by remote-sensing studies can be verified by most of the green-up time series, and no robust evidence for a warmer winter-induced later green-up dates can be detected. Thus, chilling requirements may not be an important driver influencing green-up responses to spring warming. Moreover, temperature-only control of green-up dates appears mainly at stations with relatively scarce preseason snowfall and lower elevation, while coupled temperature and precipitation controls of green-up dates occur mostly at stations with relatively abundant preseason snowfall and higher elevation. The diversified interactions between snowfall and temperature during late winter to early spring likely determine the spatiotemporal variations of green-up dates. Therefore, prediction of vegetation growth and carbon balance responses to global climate change on the world's roof should integrate both temperature and snowfall variations.

Precipitation impacts on vegetation spring phenology on the Tibetan Plateau

The ongoing changes in vegetation spring phenology in temperate/cold regions are widely attributed to temperature. However, in arid/semiarid ecosystems, the correlation between spring temperature and phenology is much less clear. We test the hypothesis that precipitation plays an important role in the temperature dependency of phenology in arid/semiarid regions. We therefore investigated the influence of preseason precipitation on satellite-derived estimates of starting date of vegetation growing season (SOS) across the Tibetan Plateau (TP). We observed two clear patterns linking precipitation to SOS. First, SOS is more sensitive to interannual variations in preseason precipitation in more arid than in wetter areas. Spatially, an increase in long-term averaged preseason precipitation of 10 mm corresponds to a decrease in the precipitation sensitivity of SOS by about 0.01 day mm(-1) . Second, SOS is more sensitive to variations in preseason temperature in wetter than in dryer areas of the plateau. A spatial increase in precipitation of 10 mm corresponds to an increase in temperature sensitivity of SOS of 0.25 day °C(-1) (0.25 day SOS advance per 1 °C temperature increase). Those two patterns indicate both direct and indirect impacts of precipitation on SOS on TP. This study suggests a balance between maximizing benefit from the limiting climatic resource and minimizing the risk imposed by other factors. In wetter areas, the lower risk of drought allows greater temperature sensitivity of SOS to maximize the thermal benefit, which is further supported by the weaker interannual partial correlation between growing degree days and preseason precipitation. In more arid areas, maximizing the benefit of water requires greater sensitivity of SOS to precipitation, with reduced sensitivity to temperature. This study highlights the impacts of precipitation on SOS in a large cold and arid/semiarid region and suggests that influences of water should be included in SOS module of terrestrial ecosystem models for drylands.