Soil moisture controls on phenology and productivity in a semi-arid critical zone

Long-term species-level observations indicate the critical role of soil moisture in regulating China's grassland productivity relative to phenological and climatic factors

As a sensitive indicator of climate change and a key variable in ecosystem surface-atmosphere interaction, vegetation phenology, and the growing season length, as well as climatic factors (i.e., temperature, precipitation, and sunshine duration) are widely recognized as key factors influencing vegetation productivity. Recent studies have highlighted the importance of soil moisture in regulating grassland productivity. However, the relative importance of phenology, climatic factors, and soil moisture to plant species-level productivity across China's grasslands remains poorly understood. Here, we use nearly four decades (1981 to 2018) of in situ species-level observations from 17 stations distributed across grasslands in China to examine the key mechanisms that control grassland productivity. The results reveal that soil moisture is the strongest determinant of the interannual variability in grassland productivity. In contrast, the spring/autumn phenology, the length of vegetation growing season, and climate factors have relatively minor impacts. Generally, annual aboveground biomass increases by 3.9 to 25.3 g∙m2 (dry weight) with a 1 % increase in growing season mean soil moisture across the stations. Specifically, the sensitivity of productivity to moisture in wetter and colder environments (e.g., alpine meadows) is significantly higher than that in drier and warmer environments (e.g., temperate desert steppes). In contrast, the sensitivity to the precipitation of the latter is greater than the former. The effect of soil moisture is the most pronounced during summer. Dominant herb productivity is more sensitive to soil moisture than the others. Moreover, multivariate regression analyses show that the primary climatic factors and their attributions to variations in soil moisture differ among the stations, indicating the interaction between climate and soil moisture is very complex. Our study highlights the interspecific difference in the soil moisture dependence of grassland productivity and provides guidance to climate change impact assessments in grassland ecosystems.

Responses of phenology to preseason drought and soil temperature for different land cover types on the Mongolian Plateau

Drought and heat caused major disturbance in nature by interfering with plant phenology, and can also alter the vulnerability and resilience of terrestrial ecosystems. Existing research on the Mongolian Plateau has primarily focused on studying the response of the start (SOS) and end (EOS) of the growing season to drought and heat variations. However, there is still a lack of comprehensive understanding regarding the coupled effects of drought and heat on phenology across different land cover types. In this study, we retrieved SOS and EOS based on 34-year (1982-2015) normalized difference vegetation index (NDVI) dataset from Global Inventory Modeling and Mapping Studies (GIMMS). Results showed that grasslands and the Gobi-Desert show rapid advancement in SOS, and forests presented the slowest advancement in SOS, but SOS in croplands were delayed. EOS across four land cover types advanced, with the Gobi-Desert showed the highest rate of advancement and forests the lowest. Using the Palmer Drought Severity Index (PDSI) and soil temperature as the indicators of drought and thermal conditions, the responses of SOS and EOS to these two climate variables were evaluated. The advanced SOS driven by lower drought severity was detected in forests, grasslands, croplands and the Gobi-Desert. The dominant response of EOS to drought severity was positive in croplands, grasslands and forests, except for the Gobi-Desert, where drought severity had negative effects on EOS. Compared with the daily average soil temperature (STmean), the daily maximum soil temperature (STmax, daytime), and the daily minimum soil temperature (STmin, nighttime), the daily diurnal soil temperature range (DSTR, where DSTR = STmax - STmin) between night and day were the most suitable indicators for assessing the response of SOS and EOS to soil temperature. Strong negative correlation between SOS and the preseason DSTR was pronounced in all land cover types on the Mongolian Plateau. However, EOS was negatively correlated with the preseason DSTR only in the Gobi-Desert. Last but not least, normalized sensitivity assessments reveal that the negative impacts of DSTR on SOS and EOS were the main controlling factors on the Mongolian Plateau phenology, followed by the couple negative effects of drought severity and DSTR.

Unraveling the impact of wildfires on permafrost ecosystems: Vulnerability, implications, and management strategies

Permafrost regions play an important role in global carbon and nitrogen cycling, storing enormous amounts of organic carbon and preserving a delicate balance of nutrient dynamics. However, the increasing frequency and severity of wildfires in these regions pose significant challenges to the stability of these ecosystems. This review examines the effects of fire on chemical, biological, and physical properties of permafrost regions. The physical, chemical, and pedological properties of frozen soil are impacted by fires, leading to changes in soil structure, porosity, and hydrological functioning. The combustion of organic matter during fires releases carbon and nitrogen, contributing to greenhouse gas emissions and nutrient loss. Understanding the interactions between fire severity, ecosystem processes, and the implications for permafrost regions is crucial for predicting the impacts of wildfires and developing effective strategies for ecosystem protection and agricultural productivity in frozen soils. By synthesizing available knowledge and research findings, this review enhances our understanding of fire severity's implications for permafrost ecosystems and offers insights into effective fire management strategies.

Shifts bidirectional dependency between vegetation greening and soil moisture over the past four decades in China

Soil moisture (SM) has changed significantly over the past 40 years in China, while NDVI has varied dramatically, leading to increasing regional conflict between vegetation growth and water resource use. Quantifying the bidirectional dependency between SM and NDVI is essential for understanding the balance between land vegetation and water resources. However, few studies have reported their mutual feedback and spatiotemporal bidirectional dependency. This paper aims to reveal the bidirectional dependency between SM and NDVI using Granger causality test to show spatiotemporal tendency coupling patterns through trend coupling analysis, wavelet transform, and lag correlation. The Results indicated that a coupling relationship existed between SM and NDVI over most of China. The unidirectional Granger effect between SM on NDVI was 58 %, the unidirectional Granger effect of NDVI on SM was 26 %, and the bidirectional Granger relationship between SM and NDVI was 16 %. The Granger relationship is different for different soil layers or land cover types. SM and NDVI increased together in 36 % of the land cover areas, but SM increased and NDVI decreased in 12 %, and the SM decreased and NDVI increased in 27 %. The trend coupling between SM and NDVI has spatial heterogeneity. There is no change rule of coupling relationship with drought variation, but SM and NDVI increased together with more overlapping ecological restoration projects. SM decreased with the increase of NDVI from 1982 to 2010 but has reversed since 2011. NDVI and SM co-increased significantly with the implementation of ecological restoration projects during 2011-2022. The coupling relationship has a time lag effect of 1-3 months, and the time lag of NDVI to SM of deep soil layers mainly occurred in Southern China. This study illustrated the coupling framework and feedback analysis between SM and vegetation greening, which is helpful for the scientific implementing ecological restoration projects and the management of ecosystem carbon and water cycles.

Nitrogen transfer between plant species with different temporal N-demand

Phenological segregation among species in a community is assumed to promote coexistence, as using resources at different times reduces competition. However, other unexplored nonalternative mechanisms can also result in a similar outcome. This study first tests whether plants can redistribute nitrogen (N) among them based on their nutritional temporal demand (i.e. phenology). Field 15 N labelling experiments showed that 15 N is transferred between neighbour plants, mainly from low N-demand (late flowering species, not reproducing yet) to high N-demand plants (early flowering species, currently flowering-fruiting). This can reduce species' dependence on pulses of water availability, and avoid soil N loss through leaching, having relevant implications in the structuring of plant communities and ecosystem functioning. Considering that species phenological segregation is a pervasive pattern in plant communities, this can be a so far unnoticed, but widely spread, ecological process that can predict N fluxes among species in natural communities, and therefore impact our current understanding of community ecology and ecosystem functioning.

Enhanced dominance of soil moisture stress on vegetation growth in Eurasian drylands

Despite the mounting attention being paid to vegetation growth and their driving forces for water-limited ecosystems, the relative contributions of atmospheric and soil moisture dryness stress on vegetation growth are an ongoing debate. Here we comprehensively compare the impacts of high vapor pressure deficit (VPD) and low soil water content (SWC) on vegetation growth in Eurasian drylands during 1982-2014. The analysis indicates a gradual decoupling between atmospheric dryness and soil dryness over this period, as the former has expanded faster than the latter. Moreover, the VPD-SWC relation and VPD-greenness relation are both non-linear, while the SWC-greenness relation is near-linear. The loosened coupling between VPD and SWC, the non-linear correlations among VPD-SWC-greenness and the expanded area extent in which SWC acts as the dominant stress factor all provide compelling evidence that SWC is a more influential stressor than VPD on vegetation growth in Eurasian drylands. In addition, a set of 11 Earth system models projected a continuously growing constraint of SWC stress on vegetation growth towards 2100. Our results are vital to dryland ecosystems management and drought mitigation in Eurasia.

Increased precipitation leads to earlier green-up and later senescence in Tibetan alpine grassland regardless of warming

It is debatable whether warming or increased precipitation primarily drives the changes of spring and autumn phenology in alpine grasslands at high elevations like the Tibetan Plateau. We aim to test the hypothesis that increased precipitation and soil moisture rather than warming significantly advance spring green-up dates (GUD) of dominant species in a semiarid alpine grassland, while both increases of temperature and precipitation delay their autumn senescence dates (SD). We conducted a 2-year manipulative experiment with infrared warming (ambient, +2 °C) and precipitation increase for each of rainfall events (ambient, +15 %, +30 %) during the growing season in a Tibetan alpine grassland. GUD and SD of three dominant species and the relevant soil temperature (ST) and moisture (SM) were observed. Rainy season onset as well as Pre-GUD or Pre-SD (30 days before GUD or SD) mean air-temperature (T_-30d) and precipitation (P_-30d) and relevant soil temperature (ST_-30d) and moisture (SM_-30d) were calculated for each experimental treatment. GUD dates of the three dominant species were advanced by increased precipitation rather than by warming, which showed a robust positive correlation with rainy season onset. SD dates were independently delayed by both increases of temperature and precipitation. There was no interactive effect of warming and increased precipitation on GUD and SD across species and years. In general, GUD had a significant negative correlation with Pre-GUD P_-30d (SM_-30d) but not with Pre-GUD T_-30d (ST_-30d), while SD showed a significant positive correlation with Pre-SD T_-30d and P_-30d or Pre-SD ST_-30d and SM_-30d. Our data support the hypothesis, indicating that spring and autumn phenology of monsoon-adapted alpine vegetation are more sensitive to precipitation change than to warming. The prolonged growing season length under increased temperature and precipitation is more depended on the delay of autumn senescence than the advance of spring green-up.

Climate extremes drive the phenology of a dominant species in meadow steppe under gradual warming

Plant phenology in terrestrial ecosystems, especially in the Northern Hemisphere, is expected to change owing to the projected increasing frequency and intensity of climate extremes in the context of global warming. Although such changes under mean climate change have been extensively reported in the literature, little is known about the impacts of climate extremes. In this study, climatic changes and their effects on plant phenology were characterized using long-term climatic and phenological data from the start and end of the growing season (SOS and EOS, respectively) from 2005 to 2020 for Stipa baicalensis, a dominant species in a temperate meadow steppe. The results showed that the temperature, including the mean and minimum temperatures, and extreme warm indices significantly increased; however, annual precipitation, and the frequency of extreme cold and precipitation events decreased. The SOS of S. baicalensis was initially earlier and later, whereas the EOS trended to be delayed. However, the growing season (LOS) was slightly prolonged. Compared with the indices under mean temperature, the pre-season (before SOS or EOS) minimum temperature dominantly affected SOS and EOS, whereas the mean and extreme precipitation slightly affected them. Furthermore, the findings showed that plant phenology responded to extreme temperatures quicker and stronger than mean temperatures. This study provides insight into how key extreme climatic factors could affect plant phenophases and improve and refine the phenological model. This could also be useful in enhancing grassland ecosystem management and sustainable development.

Earlier leaf senescence dates are constrained by soil moisture

The unprecedented warming that has occurred in recent decades has led to later autumn leaf senescence dates (LSD) throughout the Northern Hemisphere. Yet, great uncertainties still exist regarding the strength of these delaying trends, especially in terms of how soil moisture affects them. Here we show that changes in soil moisture in 1982-2015 had a substantial impact on autumn LSD in one-fifth of the vegetated areas in the Northern Hemisphere (>30° N), and how it contributed more to LSD variability than either temperature, precipitation or radiation. We developed a new model based on soil-moisture-constrained cooling degree days (CDD_SM ) to characterize the effects of soil moisture on LSD and compared its performance with the CDD, Delpierre and spring-influenced autumn models. We show that the CDD_SM model with inputs of temperature and soil moisture outperformed the three other models for LSD modelling and had an overall higher correlation coefficient (R), a lower root mean square error and lower Akaike information criterion (AIC) between observations and model predictions. These improvements were particularly evident in arid and semi-arid regions. We studied future LSD using the CDD_SM model under two scenarios (SSP126 and SSP585) and found that predicted LSD was 4.1 ± 1.4 days and 5.8 ± 2.8 days earlier under SSP126 and SSP585, respectively, than other models for the end of this century. Our study therefore reveals the importance of soil moisture in regulating autumn LSD and, in particular, highlights how coupling this effect with LSD models can improve simulations of the response of vegetation phenology to future climate change.

Important role of precipitation in controlling a more uniform spring phenology in the Qinba Mountains, China

Under global warming, the gradual pattern of spring phenology along elevation gradients (EG) has significantly changed. However, current knowledge on the phenomenon of a more uniform spring phenology is mainly focused on the effect of temperature and neglected precipitation. This study aimed to determine whether a more uniform spring phenology occurs along EG in the Qinba Mountains (QB) and explore the effect of precipitation on this pattern. We used Savitzky-Golay (S-G) filtering to extract the start of season (SOS) of the forest from the MODIS Enhanced Vegetation Index (EVI) during 2001-2018 and determined the main drivers of the SOS patterns along EG by partial correlation analyses. The SOS showed a more uniform trend along EG in the QB with a rate of 0.26 ± 0.01 days 100 m^-1 per decade during 2001-2018, but there were differences around 2011. A delayed SOS at low elevations was possibly due to the reduced spring precipitation (SP) and spring temperature (ST) between 2001 and 2011. Additionally, an advanced SOS at high elevations may have been caused by the increased SP and reduced winter temperature (WT). These divergent trends contributed to a significant uniform trend of SOS with a rate of 0.85 ± 0.02 days 100 m^-1 per decade. Since 2011, significantly higher SP (especially at low elevations) and rising ST advanced the SOS, and the SOS at lower altitudes was more advanced than at higher altitudes, resulting in greater SOS differences along EG (0.54 ± 0.02 days 100 m^-1 per decade). The SP determined the direction of the uniform trend in SOS by controlling the SOS patterns at low elevations. A more uniform SOS may have important effects on local ecosystem stability. Our findings could provide a theoretical basis for establishing ecological restoration measures in areas experiencing similar trends.

Soil Moisture, Organic Carbon, and Nitrogen Content Prediction with Hyperspectral Data Using Regression Models

Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.

Influences of Seasonal Soil Moisture and Temperature on Vegetation Phenology in the Qilian Mountains

Vegetation phenology is a commonly used indicator of ecosystem responses to climate change and plays a vital role in ecosystem carbon and hydrological cycles. Previous studies have mostly focused on the response of vegetation phenology to temperature and precipitation. Soil moisture plays an important role in maintaining vegetation growth. However, our understanding of the influences of soil moisture dynamics on vegetation phenology is sparse. In this study, using a time series of the normalized difference vegetation index (NDVI) from the moderate resolution imaging spectroradiometer (MODIS) dataset (2001–2020), the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (LOS) in the Qilian Mountains (QLMs) were extracted. The spatiotemporal patterns of vegetation phenology (SOS, EOS, and LOS) were explored. The partial coefficient correlations between the SOS, EOS, and seasonal climatic factors (temperature, precipitation, and soil moisture) were analyzed. The results showed that the variation trends of vegetation phenology were not significant (p > 0.05) from 2001 to 2020, the SOS was advanced by 0.510 d/year, the EOS was delayed by 0.066 d/year, and the LOS was prolonged by 0.580 d/year. The EOS was significantly advanced and the LOS significantly shortened with increasing altitude. The seasonal temperature, precipitation, and soil moisture had spatiotemporal heterogeneous effects on the vegetation phenology. Overall, compared with temperature and soil moisture, precipitation had a weaker influence on the vegetation phenology in the QLMs. For different elevation zones, the temperature and soil moisture influenced the vegetation phenology in most areas of the QLMs, and spring temperature was the key driving factor influencing SOS; the autumn soil moisture and autumn temperature made the largest contributions to the variations in EOS at lower (<3500 m a.s.l.) and higher elevations (>3500 m a.s.l.), respectively. For different vegetation types, the spring temperature was the main factor influencing the SOS for broadleaf forests, needleleaf forests, shrublands, and meadows because of the relative lower soil moisture stress. The autumn soil moisture was the main factor influencing EOS for deserts because of the strong soil moisture stress. Our results demonstrate that the soil moisture strongly influences vegetation phenology, especially at lower elevations and water-limited areas. This study provides a scientific basis for better understanding the response of vegetation phenology to climate change in arid mountainous areas and suggests that the variation in soil moisture should be considered in future studies on the influence of climate warming and environmental effects on the phenology of water-limited areas.

Magnitude and determinants of plant root hydraulic redistribution: A global synthesis analysis

Plant root hydraulic redistribution (HR) has been widely recognized as a phenomenon that helps alleviate vegetation drought stress. However, a systematic assessment of the magnitude of HR and its drivers at the global scale are lacking. We collected 37 peer-reviewed papers (comprising 47 research sites) published in 1900-2018 and comprehensively analyzed the magnitude of HR and its underlying factors. We used a weighting method to analyze HR magnitude and its effect on plant transpiration. Machine learning algorithms (boosted regression trees) and structural equation modeling were used to determine the influence of each factor on HR magnitude. We found that the magnitude of HR was 0.249 mm H2O d-1 (95% CI, 0.113-0.384) and its contribution to plant transpiration was 27.4% (3-79%). HR varied significantly among different terrestrial biomes and mainly occurred in forests with drier conditions, such as temperate forest ecosystems (HR = 0.502 mm H2O d-1), where HR was significantly higher than in other ecosystems (p < 0.01). The magnitude of HR in angiosperms was significantly higher than that in gymnosperms (p < 0.05). The mean magnitude of HR first increased and then decreased with an increase in humidity index; conversely, the mean magnitude of HR decreased with an increase in water table depth. HR was significantly positively correlated with root length and transpiration. Plant characteristics and environmental factors jointly accounted for 61.0% of the variation in HR, and plant transpiration was the major factor that directly influenced HR (43.1% relative importance; p < 0.001), and soil texture was an important indirect driver of HR. Our synthesis offers a comprehensive perspective of how plant characteristics and environmental factors influence HR magnitude.

Impact of Snowpack on the Land Surface Phenology in the Tianshan Mountains, Central Asia

The accumulation and ablation processes of seasonal snow significantly affect the land surface phenology in a mountainous ecosystem. However, the ability of snow to regulate the alpine land surface phenology in the arid regions is not well described in the context of climate change. The impact of snowpack changes on land surface phenology and its driving factors were investigated in the Tianshan Mountains using the land surface phenology metrics derived from satellited products and a snow dataset from downscaled regional climate model simulations covering the period from 1983 to 2015. The results demonstrated that the annual mean start of growing season (SOS) and length of growing season (LOS) experienced a significant (p < 0.05) decrease and increase with a rate of −2.45 days/decade and 2.98 days/decade, respectively. The significantly advanced SOS and increased LOS were mainly seen in the Western Tianshan Mountains and Ili Valley regions with elevations from 2500 to 3500 m a.s.l and below 3000 m a.s.l, respectively. During the early spring, the significant decline in snow cover fraction (SCF) could advance the SOS. In contrast, snowmelt amount and annual maximum snow water equivalent (SWE) have an almost equally substantial positive correlation with annual maximum vegetation greenness. In particular, the SOS of grassland was the most sensitive to variations of snow cover fraction during early spring than that of other vegetation types, and their strong relationship was mainly located at elevations from 1500 to 2500 m a.s.l. Its greenness was significantly controlled by the annual maximum snow water equivalent in all elevation bands. Both decreased SCF and increased temperature in the early spring caused a significant advance of the SOS, consequently prolonging the LOS. Meanwhile, more SWE and snowmelt amount could significantly promote vegetation greenness by regulating the soil moisture. The results can improve the understanding of the snow ecosystem services in the alpine regions under climate change.

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

Characterising the Land Surface Phenology of Middle Eastern Countries Using Moderate Resolution Landsat Data

Global change impacts including climate change, increased CO2 and nitrogen deposition can be determined through a more precise characterisation of Land Surface Phenology (LSP) parameters. In addition, accurate estimation of LSP dates is being increasingly used in applications such as mapping vegetation types, yield forecasting, and irrigation management. However, there has not been any attempt to characterise Middle East vegetation phenology at the fine spatial resolution appropriate for such applications. Remote-sensing based approaches have proved to be a useful tool in such regions since access is restricted in some areas due to security issues and their inter-annual vegetation phenology parameters vary considerably because of high uncertainty in rainfall. This study aims to establish for the first time a comprehensive characterisation of the vegetation phenological characteristics of the major vegetation types in the Middle East at a fine spatial resolution of 30 m using Landsat Normalized Difference Vegetation Index (NDVI) time series data over a temporal range of 20 years (2000–2020). Overall, a progressive pattern in phenophases was observed from low to high latitude. The earliest start of the season was concentrated in the central and east of the region associated mainly with grassland and cultivated land, while the significantly delayed end of the season was mainly distributed in northern Turkey and Iran corresponding to the forest, resulting in the prolonged length of the season in the study area. There was a significant positive correlation between LSP parameters and latitude, which indicates a delay in the start of the season of 4.83 days (R2 = 0.86, p < 0.001) and a delay in the end of the season of 6.54 days (R2 = 0.83, p < 0.001) per degree of latitude increase. In addition, we have discussed the advantages of fine resolution LSP parameters over the available coarse datasets and showed how such outputs can improve many applications in the region. This study shows the potential of Landsat data to quantify the LSP of major land cover types in heterogeneous landscapes of the Middle East which enhances our understanding of the spatial-temporal dynamics of vegetation dynamics in arid and semi-arid settings in the world.

Prediction of vegetation phenology with atmospheric reanalysis over semiarid grasslands in Inner Mongolia

Vegetation phenology is a sensitive indicator of climate change and vegetation growth. In the present study, two phenological phases with respect to vegetation growth at the initial and mature stages, namely, the start of the season (SOS) and the peak of the season (POS), were estimated from a satellite-derived normalized difference vegetation index (NDVI) dataset over a long-term period of 32 years (1983 to 2014) and used to explore their responses to atmospheric variables, including air temperature, precipitation, solar radiation, wind speed and soil moisture. First, the forward feature selection method was used to determine whether each independent variable was linear or nonlinear to the SOS and POS. In addition, a generalized additive model (GAM) was used to analyze the correlation between the phenological phases and each independent variable at different temporal scales. The results show that soil moisture and precipitation are linearly correlated with the SOS, whereas the other variables are nonlinearly correlated. Meanwhile, soil moisture, wind speed and solar radiation are found to be nonlinearly correlated with the POS. However, air temperature and precipitation reveal a significant negative correlation with the POS. Furthermore, it was concluded that the aforementioned independent variables from the previous year could contribute to approximately 63%-85% of the SOS variations in the present year, whereas the atmospheric variables from April to June could contribute to approximately 70%-85% of the POS variations in the same year. Finally, the SOS and POS predicted by the GAM exhibit significant agreement with those derived from the satellite NDVI dataset, with the root mean square error of approximately 3 to 5 days.

Factors dominating the horizontal and vertical variability of soil water vary with climate and plant type in loess deposits

Identifying the variability and predominant factors affecting soil water (SW) is essential in regions with thick vadose zones and deep-rooted plants. This information is needed to clarify the balance between water availability and plant water demand. We collected 9263 soil samples from 128 profiles of 7-25 m deep soil under different climates (arid, semiarid and subhumid), soil textures and plant types (shallow or deep roots) in China's Loess Plateau. The factors dominating the horizontal and vertical variability of SW were identified using a multimodel inference approach and stepwise regression analysis. Horizontally, the mean water content and storage increased while the water deficits decreased from the northwest to the southeast. Vertically, mean water content and storage are highest in the relatively stable layer, followed by rapidly changing layers and active layers. Plant age and soil clay content dominate the horizontally varied SW, while plant age and normalized difference vegetation index (NDVI) dominate the vertical variability of SW. However, the dominant factors appeared to differ with climate and plant type. It was determined that for climate, soil clay content and plant age in arid regions, precipitation and plant age in semiarid regions, NDVI and plant age in subhumid regions were important factors. For plants, the dominant factors are NDVI and precipitation under shallow-rooted plants; however, NDVI and plant age were dominant under deep-rooted plants. The dominance of plant age highlighted the impact of vegetation patterns on SW, especially for deep-rooted plants, which should be taken into account when managing water resources and ecosystem rehabilitation in degraded regions.

Precipitation Dominates the Relative Contributions of Climate Factors to Grasslands Spring Phenology on the Tibetan Plateau

Temperature and precipitation are the primary regulators of vegetation phenology in temperate zones. However, the relative contributions of each factor and their underlying combined effect on vegetation phenology are much less clear, especially for the grassland of the Tibetan Plateau To quantify the contribution of each factor and the potential interactions, we conducted redundancy analysis for grasslands spring phenology on the Tibetan Plateau during 2000–2017. Generally, the individual contribution of temperature and precipitation to grasslands spring phenology (the start of growing season (SOS)) was lower, despite a higher correlation coefficient, which further implied that these factors interact to affect the SOS. The contributions of temperature and precipitation to the grasslands spring phenology varied across space on the Tibetan Plateau, and these spatial heterogeneities can be mainly explained by the spatial gradient of long-term average precipitation during spring over 2000–2017. Specifically, the SOS for meadow was dominated by the mean temperature in spring (Tspring) in the eastern wetter ecoregion, with an individual contribution of 24.16% (p < 0.05), while it was strongly negatively correlated with the accumulated precipitation in spring (Pspring) in the western drier ecoregion. Spatially, a 10 mm increase in long-term average precipitation in spring resulted in an increase in the contribution of Tspring of 2.0% (p < 0.1) for meadow, while it caused a decrease in the contribution of Pspring of −0.3% (p < 0.05). Similarly, a higher contribution of Pspring for steppe was found in drier ecoregions. A spatial decrease in precipitation of 10 mm increased the contribution of Pspring of 1.4% (p < 0.05). Considering these impacts of precipitation on the relative contribution of warming and precipitation to the SOS, projected climate change would have a stronger impact on advancing SOS in a relatively moist environment compared to that of drier areas. Hence, these quantitative interactions and contributions must be included in current ecosystem models, mostly driven by indicators with the direct and the overall effect in response to projected climate warming.

Living on the edge: A continental-scale assessment of forest vulnerability to drought

Globally, forests are facing an increasing risk of mass tree mortality events associated with extreme droughts and higher temperatures. Hydraulic dysfunction is considered a key mechanism of drought-triggered dieback. By leveraging the climate breadth of the Australian landscape and a national network of research sites (Terrestrial Ecosystem Research Network), we conducted a continental-scale study of physiological and hydraulic traits of 33 native tree species from contrasting environments to disentangle the complexities of plant response to drought across communities. We found strong relationships between key plant hydraulic traits and site aridity. Leaf turgor loss point and xylem embolism resistance were correlated with minimum water potential experienced by each species. Across the data set, there was a strong coordination between hydraulic traits, including those linked to hydraulic safety, stomatal regulation and the cost of carbon investment into woody tissue. These results illustrate that aridity has acted as a strong selective pressure, shaping hydraulic traits of tree species across the Australian landscape. Hydraulic safety margins were constrained across sites, with species from wetter sites tending to have smaller safety margin compared with species at drier sites, suggesting trees are operating close to their hydraulic thresholds and forest biomes across the spectrum may be susceptible to shifts in climate that result in the intensification of drought.

Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.

Impacts of soil water stress on the acclimated stomatal limitation of photosynthesis: Insights from stable carbon isotope data

Atmospheric aridity and drought both influence physiological function in plant leaves, but their relative contributions to changes in the ratio of leaf internal to ambient partial pressure of CO₂ (χ) - an index of adjustments in both stomatal conductance and photosynthetic rate to environmental conditions - are difficult to disentangle. Many stomatal models predicting χ include the influence of only one of these drivers. In particular, the least-cost optimality hypothesis considers the effect of atmospheric demand for water on χ but does not predict how soils with reduced water further influence χ, potentially leading to an overestimation of χ under dry conditions. Here, we use a large network of stable carbon isotope measurements in C₃ woody plants to examine the acclimated response of χ to soil water stress. We estimate the ratio of cost factors for carboxylation and transpiration (β) expected from the theory to explain the variance in the data, and investigate the responses of β (and thus χ) to soil water content and suction across seed plant groups, leaf phenological types and regions. Overall, β decreases linearly with soil drying, implying that the cost of water transport along the soil-plant-atmosphere continuum increases as water available in the soil decreases. However, despite contrasting hydraulic strategies, the stomatal responses of angiosperms and gymnosperms to soil water tend to converge, consistent with the optimality theory. The prediction of β as a simple, empirical function of soil water significantly improves χ predictions by up to 6.3 ± 2.3% (mean ± SD of adjusted-R² ) over 1980-2018 and results in a reduction of around 2% of mean χ values across the globe. Our results highlight the importance of soil water status on stomatal functions and plant water-use efficiency, and suggest the implementation of trait-based hydraulic functions into the model to account for soil water stress.

Water Addition Prolonged the Length of the Growing Season of the Desert Shrub Nitraria tangutorum in a Temperate Desert

Climate models often predict that more extreme precipitation events will occur in arid and semiarid regions, where plant phenology is particularly sensitive to precipitation changes. To understand how increases in precipitation affect plant phenology, this study conducted a manipulative field experiment in a desert ecosystem of northwest China. In this study, a long-term in situ water addition experiment was conducted in a temperate desert in northwestern China. The following five treatments were used: natural rain plus an additional 0, 25, 50, 75, and 100% of the local mean annual precipitation. A series of phenological events, including leaf unfolding (onset, 30%, 50%, and end of leaf unfolding), cessation of new branch elongation (30, 50, and 90%), and leaf coloration (80% of leaves turned yellow), of the locally dominant shrub Nitraria tangutorum were observed from 2012 to 2018. The results showed that on average, over the seven-year-study and in all treatments water addition treatments advanced the spring phenology (30% of leaf unfolding) by 1.29-3.00 days, but delayed the autumn phenology (80% of leaves turned yellow) by 1.18-11.82 days. Therefore, the length of the growing season was prolonged by 2.11-13.68 days, and autumn phenology contributed more than spring phenology. In addition, water addition treatments delayed the cessation of new branch elongation (90%) by 5.82-12.61 days, and nonlinear relationships were found between the leaves yellowing (80% of leaves) and the amount of watering. Linear relationships were found between the cessation of new branch elongation (90%), the length of the growing season, and amount of water addition. The two response patterns to water increase indicated that predictions of phenological events in the future should not be based on one trend only.

Water-use efficiency in a semi-arid woodland with high rainfall variability

As the ratio of carbon uptake to water use by vegetation, water-use efficiency (WUE) is a key ecosystem property linking global carbon and water cycles. It can be estimated in several ways, but it is currently unclear how different measures of WUE relate, and how well they each capture variation in WUE with soil moisture availability. We evaluated WUE in an Acacia-dominated woodland ecosystem of central Australia at various spatial and temporal scales using stable carbon isotope analysis, leaf gas exchange and eddy covariance (EC) fluxes. Semi-arid Australia has a highly variable rainfall pattern, making it an ideal system to study how WUE varies with water availability. We normalized our measures of WUE across a range of vapour pressure deficits using g₁ , which is a parameter derived from an optimal stomatal conductance model and which is inversely related to WUE. Continuous measures of whole-ecosystem g₁ obtained from EC data were elevated in the 3 days following rain, indicating a strong effect of soil evaporation. Once these values were removed, a close relationship of g₁ with soil moisture content was observed. Leaf-scale values of g₁ derived from gas exchange were in close agreement with ecosystem-scale values. In contrast, values of g₁ obtained from stable isotopes did not vary with soil moisture availability, potentially indicating remobilization of stored carbon during dry periods. Our comprehensive comparison of alternative measures of WUE shows the importance of stomatal control of fluxes in this highly variable rainfall climate and demonstrates the ability of these different measures to quantify this effect. Our study provides the empirical evidence required to better predict the dynamic carbon-water relations in semi-arid Australian ecosystems.

Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability

Dryland regions cover >40% of the Earth's land surface, making these ecosystems the largest biome in the world. Ecosystems in these areas play an important role in determining the interannual variability of the global terrestrial carbon sink. Examining carbon fluxes of various types of dryland ecosystems and their responses to climatic variability is essential for improving projections of the carbon cycle in these regions. In this study, we made use of observations from a regional flux tower observation network in a typical arid endorheic basin, the Heihe river basin (HRB). As a representative area of both the arid region of China and the entire region of central Asia, the HRB includes the main ecosystems in arid regions. We compared the spatial variations of carbon fluxes of five terrestrial ecosystems (i.e., grassland, cropland, desert, wetland, and forest ecosystems) and explored the responses of ecosystem carbon fluxes to climatic factors across different ecosystems. We found that our region exhibits a carbon sink ranging from 85.9 to 508.7 gC/m²/yr for different ecosystems, and the water availability is critical to the spatial variability of carbon fluxes in arid regions. Carbon fluxes across all sites exhibited weak correlations with temperature and precipitation. Marked differences in precipitation effects were observed between the sites within oases and those outside of oases. Irrigation and groundwater recharge were of great importance to the variations in carbon fluxes for the sites within oases. Evapotranspiration (ET) exhibited strong relationships with carbon fluxes, indicating that ET was a better metric of soil water availability than was precipitation in driving the spatial variability of carbon fluxes in arid regions. This study has implications for better understanding the carbon budget of terrestrial ecosystems and informing ecological management in dryland regions.

Evaluating the Effectiveness of Using Vegetation Indices Based on Red-Edge Reflectance from Sentinel-2 to Estimate Gross Primary Productivity

Gross primary productivity (GPP) is the most important component of terrestrial carbon flux. Red-edge (680–780 nm) reflectance is sensitive to leaf chlorophyll content, which is directly correlated with photosynthesis as the pigment pool, and it has the potential to improve GPP estimation. The European Space Agency (ESA) Sentinel-2A and B satellites provide red-edge bands at 20-m spatial resolution on a five-day revisit period, which can be used for global estimation of GPP. Previous studies focused mostly on improving cropland GPP estimation using red-edge bands. In this study, we firstly evaluated the relationship between eight vegetation indices (VIs) retrieved from Sentinel-2 imagery in association with incident photosynthetic active radiation (PARin) and carbon flux tower GPP (GPPEC) across three forest and two grassland sites in Australia. We derived a time series of five red-edge VIs and three non-red-edge VIs over the CO2 flux tower footprints at 16-day time intervals and compared both temporal and spatial variations. The results showed that the relationship between the red-edge index (CIr, ρ 783 ρ 705 − 1 ) multiplied by PARin and GPPEC had the highest correlation (R2 = 0.77, root-mean-square error (RMSE) = 0.81 gC∙m−2∙day−1) at the two grassland sites. The CIr also showed consistency (rRMSE defined as RMSE/mean GPP, lower than 0.25) across forest and grassland sites. The high spatial resolution of the Sentinel-2 data provided more detailed information to adequately characterize the GPP variance at spatially heterogeneous areas. The high revisit period of Sentinel-2 exhibited temporal variance in GPP at the grassland sites; however, at forest sites, the flux-tower-based GPP variance could not be fully tracked by the limited satellite images. These results suggest that the high-spatial-resolution red-edge index from Sentinel-2 can improve large-scale spatio-temporal GPP assessments.

A New Wetness Index to Evaluate the Soil Water Availability Influence on Gross Primary Production of European Forests

Rising temperature, drought and more-frequent extreme climatic events have been predicted for the next decades in many regions around the globe. In this framework, soil water availability plays a pivotal role in affecting vegetation productivity, especially in arid or semi-arid environments. However, direct measurements of soil moisture are scarce, and modeling estimations are still subject to biases. Further investigation on the effect of soil moisture on plant productivity is required. This study aims at analyzing spatio-temporal variations of a modified temperature vegetation wetness index (mTVWI), a proxy of soil moisture, and evaluating its effect on gross primary production (GPP) in forests. The study was carried out in Europe on 19 representative tree species during the 2000–2010 time period. Results outline a north–south gradient of mTVWI with minimum values (low soil water availability) in Southern Europe and maximum values (high soil water availability) in Northeastern Europe. A low soil water availability negatively affected GPP from 20 to 80%, as a function of site location, tree species, and weather conditions. Such a wetness index improves our understanding of water stress impacts, which is crucial for predicting the response of forest carbon cycling to drought and aridity.

Can UAV-Based Infrared Thermography Be Used to Study Plant-Parasite Interactions between Mistletoe and Eucalypt Trees?

Some of the remnants of the Cumberland Plain woodland, an endangered dry sclerophyllous forest type of New South Wales, Australia, host large populations of mistletoe. In this study, the extent of mistletoe infection was investigated based on a forest inventory. We found that the mistletoe infection rate was relatively high, with 69% of the Eucalyptus fibrosa and 75% of the E. moluccana trees being infected. Next, to study the potential consequences of the infection for the trees, canopy temperatures of mistletoe plants and of infected and uninfected trees were analyzed using thermal imagery acquired during 10 flights with an unmanned aerial vehicle (UAV) in two consecutive summer seasons. Throughout all flight campaigns, mistletoe canopy temperature was 0.3–2 K lower than the temperature of the eucalypt canopy it was growing in, suggesting higher transpiration rates. Differences in canopy temperature between infected eucalypt foliage and mistletoe were particularly large when incoming radiation peaked. In these conditions, eucalypt foliage from infected trees also had significantly higher canopy temperatures (and likely lower transpiration rates) compared to that of uninfected trees of the same species. The study demonstrates the potential of using UAV-based infrared thermography for studying plant-water relations of mistletoe and its hosts.

Variations in Soil Water Content, Infiltration and Potential Recharge at Three Sites in a Mediterranean Mountainous Region of Baja California, Mexico

In this research, we examined temporal variations in soil water content (θ), infiltration patterns, and potential recharge at three sites with different mountain block positions in a semiarid Mediterranean climate in Baja California, Mexico: two located on opposing aspects (south- (SFS) and north-facing slopes (NFS)) and one located in a flat valley. At each site, we measured daily θ between 0.1 and 1 m depths from May 2014 to September 2016 in four hydrological seasons: wet season (winter), dry season (summer) and two transition seasons. The temporal evolution of θ and soil water storage (SWS) shows a strong variability that is associated mainly with high precipitation (P) pulses and soil profile depth at hillslope sites. Results shows that during high-intensity P events sites with opposing aspects reveal an increase of θ at the soil–bedrock interface suggesting lateral subsurface fluxes, while vertical soil infiltration decreases noticeably, signifying the production of surface runoff. We found that the dry soil conditions are reset annually at hillslope sites, and water is not available until the next wet season. Potential recharge occurred only in the winter season with P events greater than 50 mm/month at the SFS site and greater than 120 mm/month at the NFS site, indicating that soil depth and lack of vegetation cover play a critical role in the transport water towards the soil–bedrock interface. We also calculate that, on average, around 9.5% (~34.5 mm) of the accumulated precipitation may contribute to the recharge of the aquifer at the hillslope sites. Information about θ in a mountain block is essential for describing the dynamics and movement of water into the thin soil profile and its relation to potential groundwater recharge.

Finite analytic method for modeling variably saturated flows

This paper develops a finite analytic method (FAM) for solving the two-dimensional Richards' equation. The FAM incorporates the analytic solution in local elements to formulate the algebraic representation of the partial differential equation of unsaturated flow so as to effectively control both numerical oscillation and dispersion. The FAM model is then verified using four examples, in which the numerical solutions are compared with analytical solutions, solutions from VSAFT2, and observational data from a field experiment. These numerical experiments show that the method is not only accurate but also efficient, when compared with other numerical methods.

Differences in osmotic adjustment, foliar abscisic acid dynamics, and stomatal regulation between an isohydric and anisohydric woody angiosperm during drought

Species are often classified along a continuum from isohydric to anisohydric, with isohydric species exhibiting tighter regulation of leaf water potential through stomatal closure in response to drought. We investigated plasticity in stomatal regulation in an isohydric (Eucalyptus camaldulensis) and an anisohydric (Acacia aptaneura) angiosperm species subject to repeated drying cycles. We also assessed foliar abscisic acid (ABA) content dynamics, aboveground/belowground biomass allocation and nonstructural carbohydrates. The anisohydric species exhibited large plasticity in the turgor loss point (Ψ_TLP ), with plants subject to repeated drying exhibiting lower Ψ_TLP and correspondingly larger stomatal conductance at low water potential, compared to plants not previously exposed to drought. The anisohydric species exhibited a switch from ABA to water potential-driven stomatal closure during drought, a response previously only reported for anisohydric gymnosperms. The isohydric species showed little osmotic adjustment, with no evidence of switching to water potential-driven stomatal closure, but did exhibit increased root:shoot ratios. There were no differences in carbohydrate depletion between species. We conclude that a large range in Ψ_TLP and biphasic ABA dynamics are indicative of anisohydric species, and these traits are associated with exposure to low minimum foliar water potential, dense sapwood and large resistance to xylem embolism.

Divergence in plant water-use strategies in semiarid woody species

Partitioning of water resources amongst plant species within a single climate envelope is possible if the species differ in key hydraulic traits. We examined 11 bivariate trait relationships across nine woody species found in the Ti-Tree basin of central Australia. We found that species with limited access to soil moisture, evidenced by low pre-dawn leaf water potential, displayed anisohydric behaviour (e.g. large seasonal fluctuations in minimum leaf water potential), had greater sapwood density and lower osmotic potential at full turgor. Osmotic potential at full turgor was positively correlated with the leaf water potential at turgor loss, which was, in turn, positively correlated with the water potential at incipient stomatal closure. We also observed divergent behaviour in two species of Mulga, a complex of closely related Acacia species which range from tall shrubs to low trees and dominate large areas of arid and semiarid Australia. These Mulga species had much lower minimum leaf water potentials and lower specific leaf area compared with the other seven species. Finally, one species, Hakea macrocarpa A.Cunn ex.R.Br., had traits that may allow it to tolerate seasonal dryness (through possession of small specific leaf area and cavitation resistant xylem) despite exhibiting cellular water relations that were similar to groundwater-dependent species. We conclude that traits related to water transport and leaf water status differ across species that experience differences in soil water availability and that this enables a diversity of species to exist in this low rainfall environment.

Variation in photosynthetic traits related to access to water in semiarid Australian woody species

Low soil water content can limit photosynthesis by reducing stomatal conductance. Here, we explore relationships among traits pertaining to carbon uptake and pre-dawn leaf water potential (as an index of soil water availability) across eight species found in semiarid central Australia. We found that as pre-dawn leaf water potential declined, stomatal limitations to photosynthesis increased, as did foliar nitrogen, which enhanced photosynthesis. Nitrogen-fixing Acacia species had higher foliar nitrogen concentrations compared with non-nitrogen fixing species, although there was considerable variability of traits within the Acacia genus. From principal component analysis we found that the most dissimilar species was Acacia aptaneura Maslin&J.E.Reid compared with both Eucalyptus camaldulensis Dehnh. and Corymbia opaca. (D.J.Carr & S.G.M.Carr)K.D.Hill&L.A.S.Johnson, having both the largest foliar N content, equal largest leaf mass per area and experiencing the lowest pre-dawn water potential of all species. A. aptaneura has shallow roots and grows above a hardpan that excludes access to groundwater, in contrast to E. camaldulensis and C. opaca, which are known to access groundwater. We conclude that ecohydrological niche separation is an important factor driving the variability of within-biome traits related to carbon gain. These observations have important implications for global vegetation models, which are parameterised with many of the traits measured here, but are often limited by data availability.