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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. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is one of the most important areas for the study of the carbon budgets of terrestrial ecosystems. However, the estimation of the net ecosystem productivity (NEP) remains uncertain in this region due to its complex topographic properties and climatic conditions. Using CO2-eddy-covariance-flux data from 1982 to 2018 at 18 sites distributed around the TP grassland, we analyzed the spatial–temporal patterns of the grassland NEP and its driving factors from 1982 to 2018 using a random forest (RF) model. Our results showed that the RF model captured the size of the carbon sink (R2 = 0.65, p < 0.05) between the observed and simulated values for the validation samples. During the observation period, the grassland acted as a carbon sink of 26.2 Tg C yr−1 and increased significantly, by 0.4 g C m−2 yr−1. On a regional scale, the annual NEP gradually increased from the northwest to the southeast, and a similar pattern was also observed in the long-term trends. Furthermore, the moisture conditions, such as the specific humidity and precipitation, were proven to be the main driving factors of the carbon flux in the southeastern areas, while the temperature predominantly controlled the carbon flux in the northwest. Our results emphasize the net carbon sink of the TP and provide a reliable way to upscale NEP from sites. [ABSTRACT FROM AUTHOR]

Global greening and its eco-environmental outcomes are getting mounting international focus. The important contribution of China to the global greening is highly appreciated. However, the basic driving forces are still elusive. The Loess Plateau (LP) and Three-River Source Region (TRSR) were chased as study areas in Northern China. The prior one represents the region experiencing intensive human interventions from ecological engineering projects, while the latter is a typical region that is experiencing faster climate change. Hypothesized to be driven by a disproportionate rate of human activities and climates, also being regions of typical large-scale ecological engineering projects, the study goal is to identify the actual driving forces on vegetation dynamics in these two regions. Trend analysis, correlation analysis, and residual trend-based method (RESTREND) were utilized to understand the relationships between climate variability, human activities, and vegetation dynamics. The spatiotemporal variations of vegetation from 1982 to 2019 were evaluated and the respective impacts of climatic and anthropogenic factors on vegetation dynamics were disentangled. Indicating apparent vegetation restoration in LP and TRSR, the results depict that annual LAI has remarkably increased during the 38 years. Temperature and precipitation promoted vegetation growth, whereas the solar radiation and vapor pressure deficit hampered it. After implementing the ecological engineering projects, the primary climatic factor changed from temperature to precipitation. Meanwhile, human activities act as the major driving factor in vegetation greening in the entire study area, with a contribution rate exceeding 70%. This information highlights that ecological engineering can significantly reduce the risks of ecosystem degradation and effectively restore vegetation, especially in ecologically sensitive and vulnerable areas. [ABSTRACT FROM AUTHOR]

It is hard for current time series reconstruction methods to achieve the balance of high-precision time series reconstruction and explanation of the model mechanism. The goal of this paper is to improve the reconstruction accuracy with a well-explained time series model. Thus, we developed a function-based model, the CCTM (Continuous Change Tracker Model) model, that can achieve high precision in time series reconstruction by tracking the time series variation rate. The goal of this paper is to provide a new solution for high-precision time series reconstruction and related applications. To test the reconstruction effects, the model was applied to four types of datasets: normalized difference vegetation index (NDVI), gross primary productivity (GPP), leaf area index (LAI), and MODIS surface reflectance (MSR). Several new observations are as follows. First, the CCTM model is well explained and based on the second-order derivative theorem, which divides the yearly time series into four variation types including uniform variations, decelerated variations, accelerated variations, and short-periodical variations, and each variation type is represented by a designed function. Second, the CCTM model provides much better reconstruction results than the Harmonic model on the NDVI, GPP, MSR, and LAI datasets for the seasonal segment reconstruction. The combined use of the Savitzky–Golay filter and the CCTM model is better than the combinations of the Savitzky–Golay filter with other models. Third, the Harmonic model has the best trend-fitting ability on the yearly time series dataset, with the highest R-Square and the lowest RMSE among the four function fitting models. However, with seasonal piecewise fitting, the four models all achieved high accuracy, and the CCTM performs the best. Fourth, the CCTM model should also be applied to time series image compression, two compression patterns with 24 coefficients and 6 coefficients respectively are proposed. The daily MSR dataset can achieve a compression ratio of 15 by using the 6-coefficients method. Finally, the CCTM model also has the potential to be applied to change detection, trend analysis, and phenology and seasonal characteristics extractions. [ABSTRACT FROM AUTHOR]

Forest height inversion with Polarimetric SAR Interferometry (PolInSAR) has become a research hotspot in the field of radar remote sensing. In this paper, we systematically studied a modified two-step, three-stage inversion simulating the L-band (L = 23 cm) full-polarization interferometric SAR data with an average forest height of 18 m using ESA PolSARpro-SIM software. We applied this method to E-SAR L-band single-baseline full PolInSAR data in 2003. In the first step, we modified the three-stage inversion algorithm based on phase diversity (PD)/maximum coherence difference (MCD) coherence optimization methods, corresponding to PD, MCD, respectively. In the second step, we introduced the coherence amplitude inversion term and modified the fixed weight to the variable of ε times the ground scattering ratio, which improved the accuracy of forest height inversion. The mean of forest height inversion by the HV method was the lowest (15.83 m) and the RMSE was the largest (4.80 m). The PD method was superior to the HV method with RMSE (4.60 m). The MCD method was slightly better than using the PD method with the smallest RMSE (4.43 m). After adding the coherence amplitude term, the RMSE was improved by 0.15 m, 0.14 m, and 0.08 m, respectively. The smallest RMSE was obtained by MCD, followed by the PD and HV methods. Although the robustness of the forest height inversion algorithm was reduced, the underestimation was improved and the RMSE was reduced. Due to the complexity of the real SAR E-SAR L-band single-baseline full PolInSAR data and the small sample sizes, the three-stage inversion methods based on coherent optimization were lower than the three-stage in-version method. After introducing the coherent magnitude term, the overestimation of the forest height was significantly weakened in HVWeight, PDweight, and MCDWeight, and PDWeight was optimal. The modified two-step, three-stage inversion algorithm had significant effects in alleviating forest height underestimation and overestimation, improving the accuracy of forest height inversion, and laying a foundation for the upcoming L-band SAR satellite generation, new SAR and LIDAR systems combined with RPAs (remotely piloted aircrafts)/UAVs (unmanned aerial vehicles) for small areas mapping initiatives, and promoting the depth and breadth of the SAR applications of the new SAR system. [ABSTRACT FROM AUTHOR]

Aim: Ecosystem carbon use efficiency (CUEe) is a core parameter of ecosystem process models, but its relationships with climate are still uncertain, especially for ecosystems with harsh environments. Large inconsistencies in climate impacts on the CUEe have been reported among various spatial scales. The goal of this study was to examine whether warming promotes or restricts the CUEe and whether the CUEe responds to a warming gradient in a linear or nonlinear manner. Location: Tibetan Plateau. Time period: 2000–2018. Major taxa studied: Alpine grassland ecosystem. Methods: We integrated multiple‐source data of carbon fluxes and CUEe, including warming experiments at a site scale, eddy covariance observations at a landscape scale and synthesized warming experiments and ecosystem process models at a regional scale. Next, we deployed a statistical model to examine the warming impacts on the CUEe across scales; the effects of biotic and abiotic factors on the CUEe and its components were summarized based on the results of standardized major axis tests and routines, structural equation modelling and nonlinear models. Results: This study reported a suppressive warming impact on the CUEe, which followed a nonlinear curve with severe inhibition in the high‐level warming treatment. With a warming threshold of 1.5–2.0°C, CUEe response patterns transitioned from no change to a significant decrease. The restriction effects can be ascribed to the joint adverse and asymmetric effects of warming on CUEe components under multiple‐level warming. Warming‐modified relationships among CUEe components and the nonlinear effects of biotic and abiotic factors led to the nonlinear responses of CUEe to warming. Main conclusions: This study revealed suppressive and nonlinear effects of warming on the CUEe, including especially dramatic CUEe decreases with high‐level warming. These findings are critical for optimizing model parameters and improving predictions of the carbon sequestration capacity of alpine grasslands. [ABSTRACT FROM AUTHOR]

Summary: Global environmental change is altering the Earth's ecosystems. However, much research has focused on ecosystem‐level responses, and we know substantially less about community‐level responses to global change stressors.Here we conducted a 6‐yr field experiment in a high‐altitude (4600 m asl) alpine grassland on the Tibetan Plateau to explore the effects of nitrogen (N) addition and rising atmospheric CO2 concentration on plant communities.Our results showed that N and CO2 enrichment had synergistic effects on alpine grassland communities. Adding nitrogen or CO2 alone did not alter total community biomass, species diversity or community composition, whereas adding both resources together increased community biomass, reduced species diversity and altered community composition. The observed decline in species diversity under simultaneous N and CO2 enrichment was associated with greater community biomass and lower soil water content, and driven by the loss of species characterised simultaneously by tall stature and small specific leaf area.Our findings point to the co‐limitation of alpine plant community biomass and structure by nitrogen and CO2, emphasising the need for future studies to consider multiple aspects of global environmental change together to gain a more complete understanding of their ecological consequences. [ABSTRACT FROM AUTHOR]

Climate change is known to affect many facets of the Earth's ecosystems. However, little is known about its impacts on phylogenetic and functional properties of ecological communities.Here we studied the responses of plant communities in an alpine grassland on the Tibetan Plateau to environmental warming across taxonomic, phylogenetic and functional levels in a 6‐year multiple‐level warming experiment.While low‐level warming did not alter either plant species richness or phylogenetic/functional community structure, high‐level warming significantly decreased species richness. Higher level warming more strongly reduced soil moisture and caused stronger environmental filtering, consequently changing species composition and community structure. At the plant functional trait level, high‐level warming promoted species turnover through altering the effects of traits such as plant height on species extinction and SLA on species colonization. As a result, high‐, but not low‐level warming drove phylogenetic/functional community structure from overdispersion to randomness, by filtering out species that were functionally dissimilar and distantly related to the resident species.Synthesis. Our study provides evidence that the responses of plant phylogenetic and functional community structure to low warming differ from those in the future scenarios of increasing temperature. Importantly, the extinction of species that was functionally dissimilar and distantly related to the resident species contributed to alterations in plant community structure under high warming. Our study underscores the need to incorporate the phylogenetic and functional perspectives to gain a more complete understanding of community responses to climate warming. [ABSTRACT FROM AUTHOR]

• Discrepancies exist with different data in phenology extractions. • High temporal resolution data has higher accuracies in capturing SOS. • Double logistic method can minimize the extraction difference. The vegetation phenology is a commonly used indicator signaling vegetation responses to global changes. Monitoring vegetation phenology at a regional and global scale needs to rely to remote sensing data, for which multiple sources of datasets and extraction methods have been developed. To be efficient, remote sensing data with coarse temporal resolution is conventionally preferred in exploring vegetation phenology patterns at the continental or global scale. As fine temporal resolution data is increasingly available, effects of their temporal resolution on our analysis are still elusive. In this study, we applied several commonly utilized vegetation phenology extraction methods on two different temporal resolution MODIS NDVI data and compared their performances on the Tibetan Plateau (TP). The results showed there were certain discrepancies in the magnitude, trends and spatial patterns of extracted phenological parameters between the two datasets and among the different extraction methods. Generally, the phenological parameters derived from fine temporal resolution NDVI (MOD09A1) displayed later start of growing season (SOS), earlier end of growing season (EOS), shorter length of growing season (LOS), and were more accurate in capturing vegetation SOS compared with the coarse temporal resolution NDVI data (MOD13A2). The double logistic method can minimize the differences of extracted SOS or EOS between the two temporal resolution datasets. The findings of this study would improve accuracies of applying remote sensing data on monitoring vegetation dynamics and advance our understanding on vegetation responses to climate changes. [ABSTRACT FROM AUTHOR]

Effects of climate warming and changing precipitation on ecosystem carbon fluxes have been intensively studied. However, how they co‐regulate carbon fluxes is still elusive for some understudied ecosystems. To fill the gap, we examined net ecosystem productivity (NEP), gross ecosystem productivity (GEP,) and ecosystem respiration (ER) responses to multilevel of temperature increments (control, warming 1, warming 2, warming 3, warming 4) in three contrasting hydrological growing seasons in a typical semiarid alpine meadow. We found that carbon fluxes responded to precipitation variations more strongly in low‐level warming treatments than in high‐level ones. The distinct responses were attributable to different soil water conditions and community composition under low‐level and high‐level warming during the three growing seasons. In addition, carbon fluxes were much more sensitive to decreased than to increased precipitation in low‐level warming treatments, but not in high‐level ones. At a regional scale, this negative asymmetry was further corroborated. This study reveals that future precipitation changes, particularly decreased precipitation would induce significant change in carbon fluxes, and the effect magnitude is regulated by climate warming size. [ABSTRACT FROM AUTHOR]

As the recent global warming hiatus and the warming on high elevations are attracting worldwide attention, this study examined the robustness of the warming slowdown over the Tibetan plateau (TP) and its related driving forces. By integrating multiple-source data from 1982 to 2015 and using trend analysis, we found that the mean temperature (Tmean), maximum temperature (Tmax) and minimum temperature (Tmin) showed a slowdown of the warming trend around 1998, during the period of the global warming hiatus. This was found over both the growing season (GS) and non-growing season (NGS) and suggested a robust warming hiatus over the TP. Due to the differences in trends of Tmax and Tmin, the trend of diurnal temperature range (DTR) also shifted after 1998, especially during the GS temperature. The warming rate was spatially heterogeneous. The northern TP (NTP) experienced more warming than the southern TP (STP) in all seasons from 1982 to 1998, while the pattern was reversed in the period from 1998 to 2015. Water vapour was found to be the main driving force for the trend in Tmean and Tmin by influencing downward long wave radiation. Sunshine duration was the main driving force behind the trend in Tmax and DTR through a change in downward shortwave radiation that altered the energy source of daytime temperature. Water vapour was the major driving force for temperature change over the NTP, while over the STP, sunshine duration dominated the temperature trend. [ABSTRACT FROM AUTHOR]

The relationships between cover and AGB for the dominant and widely distributed alpine grasslands on the northern Tibetan Plateau is still not fully examined. The objectives of this study are to answer the following question: (1) How does aboveground biomass (AGB) of alpine grassland relate to plant cover at different spatial scales? (2) What are the major biotic and abiotic factors influencing on AGB-cover relationship? A community survey (species, cover, height, and abundance) was conducted within 1 m × 1 m plots in 70 sites along a precipitation gradient of 50-600 m. Ordinary linear regression was employed to examine AGB-cover relationships of both community and species levels at regional scale of entire grassland and landscape scale of alpine meadow, alpine steppe, and desert steppe. Hierarchical partitioning was employed to estimate independent contributions of biotic and abiotic factors to AGB and cover at both scales. Partial correlation analyses were used to discriminate the effects of biotic and abiotic factors on AGB-cover relationships at two spatial scales. AGB and community cover both exponentially increased along the precipitation gradient. At community level, AGB was positively and linearly correlated with cover for all grasslands except for alpine meadow. AGB was also linearly correlated with cover of species level at both regional and landscape scales. Contributions of biotic and abiotic factors to the relationship between AGB and cover significantly depended on spatial scales. Cover of cushions, forbs, legumes and sedges, species richness, MAP, and soil bulk density were important factors that influenced the AGB-cover relationship at either regional or landscape scale. This study indicated generally positive and linear relationships between AGB and cover are at both regional and landscape scales. Spatial scale may affect ranges of cover and modify the contribution of cover to AGB. AGB-cover relationships were influenced mainly by species composition of different functional groups. Therefore, in deriving AGB patterns at different spatial scales, community composition should be considered to obtain acceptable accuracy. [ABSTRACT FROM AUTHOR]

As the world's highest and largest plateau, the Qinghai-Xizang Plateau has experienced a greater warming than the Northern Hemisphere and global averages. This warming has been reported to exhibit an elevation-dependent pattern. However, the finding involved plenty of uncertainties caused by the spatially limited datasets and complex topography. Here, we explored an approach integrating satellite-derived LST data and ground records to generate a spatially continuous air temperature dataset for the plateau grasslands from 2003 to 2012, and then examined influences of elevation/topography on temperature change trends. The derived temperature dataset was validated to be closely correlated with field-station records. Based on the derived spatially continuous temperature datasets, we found an opposite change trend of annually average temperature between Qinghai and Xizang Province. The contrasted trend was obvious in daytime and more so in summer season. By analyzing the temperature trend in relation to elevation, we found an enhanced temperature change trend in higher elevation than in lower elevation for autumn nights and winter temperatures, while the temperature change trends for other seasons were more evident in lower elevation areas. The varying temperature change trends as regulated by elevation implies that temperate grasslands have experienced a more rapid temperature change than alpine grasslands during the past decade. [ABSTRACT FROM AUTHOR]

Aim Carbon use efficiency [net primary production ( NPP)/gross primary production ( GPP) ratio] is a parameter related to the allocation of photosynthesized products by plants and is commonly used in many biogeochemical cycling models. But how this parameter changes with climates is still unknown. Faced by an aggravated global warming, there is a heightened necessity in unravelling the dependence of the NPP/ GPP ratio on climates. The objective of this study was to examine how ongoing climate change is regulating global patterns of change in the NPP/ GPP ratio. The study finding would elucidate whether the global vegetation ecosystem is becoming more or less efficient in terms of carbon storage under climatic fluctuation. Location The global planetary ecosystem. Methods The annual NPP/ GPP ratio of the global terrestrial ecosystem was calculated over a 10-year period based on Moderate Resolution Imaging Spectroradiometer data and an ecosystem productivity model. The temporal dynamics of the global NPP/ GPP ratio and their dependence on climate were investigated. Results The global NPP/ GPP ratio exhibited a decreasing trend from 2000 to 2009 due to decreasing NPP and stable GPP over this period. The temporal dynamics of the NPP/ GPP ratio were strongly controlled by temperature and precipitation. Increased temperature lowered the NPP/ GPP ratio, and increased precipitation led to a higher NPP/ GPP ratio. Conclusions The NPP/ GPP ratio exhibits a clear temporal pattern associated with climatic fluctuations at a global scale. The associations of the NPP/ GPP ratio with climatic variability challenge the conventional assumption that the NPP/ GPP ratio should be consistent independent of environmental conditions. More importantly, the findings of this study have fundamental significance for our understanding of ongoing global climatic change. In regions and time periods experiencing drought or increased temperatures, plant ecosystems would suffer a higher ecosystem respiration cost and their net productivity would shrink. [ABSTRACT FROM AUTHOR]

Aim To test two predictions of the phylogenetic niche conservatism hypothesis for the latitudinal diversity gradient: (1) species in colder regions tend to be more phylogenetically related to each other (i.e. greater phylogenetic clustering) than those in warmer regions, and (2) clades are younger in colder regions. Location North America. Methods Correlation analysis was used to relate richness, mean clade age and phylogenetic relatedness (measured as phylogenetic species variability and net relatedness index) of angiosperm trees in 1175 regional assemblages (each with 12100 km2) to latitude and minimum temperature. The analysis was conducted for North America north of Mexico as a whole as well as for each of the three longitudinal bands (eastern, central and western) of North America. Results Species richness and mean clade age are negatively correlated with latitude and positively correlated with minimum temperature. Tree species in regional assemblages tend to be more phylogenetically related (clustered) in regions at higher latitudes with lower temperatures. Main conclusions The results of this study support two of the major predictions of the phylogenetic niche conservatism hypothesis for the latitudinal diversity gradient: species tend to be more phylogenetically clustered and ages of clades tend to be younger in colder regions, compared with those in warmer regions. [ABSTRACT FROM AUTHOR]

• Temporal change in relationship between NDVI and diurnal temperature was explored. • R NDVI-TMX and R NDVI-TMN showed distinct variations between mid- and high latitudes. • Weakening effect of TMX on vegetation growth was more apparent than that of TMN. • TRENDY models didn't capture dynamic relation of vegetation growth to TMX or TMN. Global warming has boosted vegetation growth to a large extent, but this stimulation effect has significantly weakened in recent years. Among the set of possible driving forces, the asymmetric daytime and nighttime warming effect has been largely neglected. To improve our understanding on the relationship between vegetation growth and global warming, this study tries to attribute the respective effects of daytime and nighttime temperature on vegetation growth and reveal their temporal trends in the extratropical Northern Hemisphere (30–90 °N). The results showed there had been significant warming trends in growing season maximum (TMX, 0.37 °C per decade) and minimum temperatures (TMN, 0.38 °C per decade) during 1982–2015, especially in high latitudes of the NH. Under the asymmetric diurnal warming, the effects of TMX and TMN on normalized difference vegetation index (NDVI) exhibited distinct temporal variations between mid- (<55 °N) and high latitudes (>55 °N). The positive correlation between NDVI and TMX (R NDVI-TMX) weakened in high latitudes, as well as the negative correlation between NDVI and TMN (R NDVI-TMN). However, the R NDVI-TMX and R NDVI-TMN changed little in mid-latitudes. Moreover, the weakening effect of TMX on NDVI was more apparent than that of TMN in high latitudes. The area with significantly (p < 0.1) positive R NDVI-TMX and significantly (p < 0.1) negative R NDVI-TMN both shrank from 1982–1998 to 1999–2015, with prior (15.97%) twice the latter one (7.09%) in shrunk area in high latitudes. With regard to vegetation type, decline in area with significantly (p < 0.1) positive R NDVI-TMX and negative R NDVI-TMN was extremely obvious in savannas, deciduous broadleaf forests and deciduous needleleaf forests. Besides, we also disclosed the poor performance of ecosystem process models in capturing the dynamic relationship between vegetation growth and diurnal temperature, which might be caused by their totally relying on diurnal mean temperature, instead of daytime and nighttime temperature, in forcing the models. This study can further advance our understandings on ecosystem responses to climate warming, and efficiently improve performance of ecosystem models. [ABSTRACT FROM AUTHOR]

Using historical General Land Office record as a reference, this study employed a landscape-scale disturbance and succession model to estimate the future cumulative effects of six alternative management plans on the tree species composition for various physiographic settings for the Mark Twain National Forest in Missouri. The results indicate that over a 200-year horizon, the relative abundance of black oak and pine species groups will decrease and the relative abundance of the white oak species group will increase, regardless of management strategy. General Land Office witness tree records provide a measure of tree species composition in the period from 1800 to 1850, prior to the large-scale influx of European settlers. Compared to the tree species composition described in the General Land Office records, the six contemporary management alternatives considered all would lead to a lower abundance of pine species, a higher abundance of red/black oak species, and a slightly higher abundance of white oak species after 200 years. Impacts of management on tree species composition varied with physiographic settings. The projected relative abundance of pine differed significantly across the five physiographic classes over the first 40 years of the simulation. In the medium term (simulation years 41–100) the projected relative pine abundance differed significantly among only four physiographic classes. In the long term (simulation years 100–200) the projected relative pine abundance differed for only one physiographic class. In contrast, differences among physiographic classes in the relative abundance of black oaks and white oaks increased over time. In general, the expected long-term differences in relative tree species abundance among six proposed alternative management plans are small compared to shifts in tree species composition that have occurred from 1850 to the present. [Copyright &y& Elsevier]

Abstract: Previous research addressing the unequal distribution of locally desirable land (LDL) has mainly ignored their associated environments (i.e., rural or urban). However, this study proposed a new framework that treats rural and urban regions separately. In rural areas, the LDLs included all public lands. In urbanized areas, the LDLs were defined as green open spaces. Potential inequities in the distribution of LDL were assessed with respect to socioeconomic characteristics of residents in the State of Georgia. Using US Census Bureau Data (2000), Census Block Groups (CBGs) adjacent to LDLs were compared to CBGs outside of LDLs on four socioeconomic variables (per capita income, occupation, education, and race) in urban, suburban and rural environments. Results showed that CBGs adjacent to LDLs were composed of statistically significant upper-class communities containing fewer blue-collar workers, more whites, and higher income and higher educated people in rural, suburban and urban areas. [Copyright &y& Elsevier]

• The first study to use high-resolution images to survey pika hole size and area. • The first study to explore pika hole distribution pattern at a landscape scale. • Effects of pika hole on plant growth in the surrounding varies with pika hole size. • Vegetation coverage affects pika hole density in alpine meadow. The pika (Ochotona curzoniae) hole is an important landscape feature in the Tibetan Plateau (TP) grasslands, and it indicates grassland degradation levels due to the destruction caused by pika burrowing activities on grasslands. However, no studies have ever explored landscape patterns of pika holes and their effects on adjacent vegetation coverage. Taking meadow grasslands in Northern Tibet as an example, this study gathered unmanned aerial vehicle (UAV) images and explored landscape patterns of pika holes and their effects on grass coverage in the surroundings. The performances of two classification methods, including the decision tree classification based on Fully Constrained Least Squares (FDC) and the object-oriented classification (OBC) were compared in recognizing sizes and shapes of pika holes. The results showed that: (1) The object-oriented classification exhibits higher classification accuracy in identifying pika holes. (2) The average size of pika holes in the study area is 0.01 m2 and they exhibit clustered distribution patterns. The average distance between any two nearest pika hole patches is 0.79 m. (3) It presents a significant quadratic relationship between the number of pika holes and grass coverage. (4) The average effective distance of pika holes on the surrounding grass coverage is 20 cm. The findings of this study can provide guidelines for pika control and improve grassland management on the TP. [ABSTRACT FROM AUTHOR]

Plant phenology, as an indicator of environmental variation and climate change impacts, has vital effects on ecosystem biogeochemical cycles. As another major land cover type, snow cover plays an important role in influencing on ecosystem geo-biophysical processes and water availability. For Tibetan Plateau, snow cover and the alpine vegetation are more sensitive to climate change than other regions in China. In situ and regional studies provide evidence for the warming effect on phenology in the plateau. However, the understanding of how seasonal dynamic of snow cover affect the phenology by modulating soil water availability or other environmental factors, are still very limited. In our research, we use a 16-year time-series cloud-free MODIS daily snow cover MODIS dataset to extract the FSCD(Freezing of Snow Cover Date),MSCD(Melt of Snow Cover Date) and SCD(Snow Cover Duration). We also extract the spring phenology based on three vegetation indexes (NDVI, NDPI and PPI) to eliminate the snow cover's contamination. An overall enhanced spring phenology as well as a shorter SCD are observed. Snow cover area exhibited two separate peaks during autumn and late winter over the plateau. MSCD and FSCD do not show significant trend during research period. Extended SCD regions mainly distributed in middle-east of the plateau, while shrunken SCD distributed in other regions of the plateau. For the semi-arid meadow region, the autumn SCD and slightly postponed FSCD have positive effect on advancing the spring phenology along with lag effects. For the arid steppe region, the slightly postponed MSCD and the shrunken SCD have negative effect on the non-significant delay of spring phenology. The non-growing season freezing degree days(FDD) also can modify the effect of MSCD, FSCD and SCD on the spring phenology. Overall, our results suggest that for the alpine vegetation in Tibetan Plateau show distinct react to the snow cover change in different seasons. In further studies, with these effect considered, the predictions on the Tibetan Plateau's spring phenology could be improved.keywords: alpine vegetation, snow cover, phenology,Tibetan Plateau [ABSTRACT FROM AUTHOR]

Anthropogenic environmental changes are influencing the structure and function of many ecological communities, but their underlying mechanisms are often poorly understood. We conducted a 7‐year field experiment to explore the ecological consequences of nitrogen (N) and phosphorous (P) enrichment in a high‐altitude Tibetan alpine grassland. We found that the enrichment of both N and P, but not either alone, increased plant above‐ and belowground biomass. In contrast, N, but not P, enrichment reduced species richness and altered plant phylogenetic diversity and structure. Whereas plant species loss and changes in phylogenetic structure were mainly driven by higher soil manganese levels under N addition, they were mainly driven by increased plant belowground biomass under the addition of both N and P. Our study highlights the resource co‐limitation of community biomass but not the structure of the study grassland, while also identifying soil metal toxicity and belowground competition as important mechanisms driving community changes following nutrient amendment. [ABSTRACT FROM AUTHOR]

Global warming exerts profound impacts on terrestrial carbon cycles and feedback to climates. Ecosystem respiration (ER) is one of the main components of biosphere CO2 fluxes. However, knowledge regarding how ER responds to warming is still lacking. In this study, a manipulative experiment with five simulated temperature increases (+0℃ [Control], +2.1℃ [warming 1, W1], +2.7℃ [warming 2, W2], +3.2℃ [warming 3, W3], +3.9℃ [warming 4, W4]) was conducted to investigate ER responses to warming in an alpine meadow on the Tibetan Plateau. The results showed that ER was suppressed by warming both in dry and wet years. The responses of ER to warming all followed a nonlinear pattern. The nonlinear processes can be divided into three stages, the quick‐response stage (W1), stable stage (W1–W3), and transition stage (W4). Compared with the nonlinear model, the linear model maximally overestimated the response ratios of ER to warming 2.2% and 3.2% in 2015 and 2016, respectively, and maximally underestimated the ratio 7.0% and 2.7%. The annual differences in ER responding to warming were mainly attributed to the distinct seasonal distribution of precipitation. Specially, we found that the abrupt shift response of ER to warming under W4 treatment in 2015, which might be regulated by the excitatory effect of precipitation after long‐term drought in the mid‐growing season. This study highlights the importance of the nonlinearity of warming effects on ER, which should be taken into the global‐C‐cycling models for better predicting future carbon–climate feedbacks. The responses of ER to warming all followed a nonlinear pattern. The nonlinear processes can be divided into three stages, the quick‐response stage (W1), stable stage (W1–W3), and transition stage (W4). The annual differences in ER responding to warming were mainly attributed to the distinct seasonal distribution of precipitation. Specially, we found that the distinct abrupt shift response of ER to warming under W4 treatment in 2015, which might be regulated by the excitatory effect of precipitation after long‐term drought in the mid‐growing season. [ABSTRACT FROM AUTHOR]

To explore grazing effects on carbon fluxes in alpine meadow ecosystems, we used a paired eddy-covariance (EC) system to measure carbon fluxes in adjacent fenced (FM) and grazed (GM) meadows on the Tibetan plateau. Gross primary productivity (GPP) and ecosystem respiration (Re) were greater at GM than FM for the first two years of fencing. In the third year, the productivity at FM increased to a level similar to the GM site. The higher productivity at GM was mainly caused by its higher photosynthetic capacity. Grazing exclusion did not increase carbon sequestration capacity for this alpine grassland system. The higher optimal photosynthetic temperature and the weakened ecosystem response to climatic factors at GM may help to facilitate the adaption of alpine meadow ecosystems to changing climate. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau has experienced higher-than-global-average climate warming in recent decades, resulting in many significant changes in ecosystem structure and function. Among them is albedo, which bridges the causes and consequences of land surface processes and climate. The plateau is covered by snow/ice and vegetation in the non-growing season (nGS) and growing season (GS), respectively. Based on the MODIS products, we investigated snow/ice cover and vegetation greenness in relation to the spatiotemporal changes of albedo on the Tibetan Plateau from 2000 through 2013. A synchronous relationship was found between the change in GSNDVI and GSalbedo over time and across the Tibetan landscapes. We found that the annual average albedo had a decreasing trend, but that the albedo had slightly increased during the nGS and decreased during the GS. Across the landscapes, the nGSalbedo fluctuated in a synchronous pattern with snow/ice cover. Temporally, monthly snow/ice coverage also had a high correspondence with albedo, except in April and October. We detected clear dependencies of albedo on elevation. With the rise in altitude, the nGSalbedo decreased below 4000 m, but increased for elevations of 4500–5500 m. Above 5500 m, the nGSalbedo decreased, which was in accordance with the decreased amount of snow/ice coverage and the increased soil moisture on the plateau. More importantly, the decreasing albedo in the most recent decade appeared to be caused primarily by lowered growing season albedo. [ABSTRACT FROM AUTHOR]

Investigating elevational gradient of climate driving effects on cropland ecosystem net primary productivity (NPP) plays an important role in food security in alpine region. We simulated cropland NPP by coupling a remote sensing model with an ecosystem process model and explored elevational gradient of climate driving effects on it in an alpine region of the southwest China during 1981–2014. The results showed that cropland NPP increased significantly with a rate of 3.85 gC m−2 year−1 year−1 under significant increasing solar radiation and climate warming and drying, among which the increasing solar radiation was the main driving factor of the increasing NPP. The driving effect of climate warming on cropland NPP shifted from negative at low elevations to positive at high elevations, which was caused by the fragile ecosystem characteristics and frequent drought at low elevations and a higher temperature sensitivity of cropland ecosystem at high elevations. Different effects of climate warming on NPP change at different elevations caused different results when we analyzed the climate-driving effects on cropland NPP at different spatial scales. These results reminded us that we should take the elevational gradient of climate driving effects into account when we manage food security in the alpine region. [ABSTRACT FROM AUTHOR]

As a key biotic factor, phenology exerts fundamental influences on ecosystem carbon sequestration. However, whether spring phenology affects the subsequent seasonal ecosystem productivity and the underlying resource limitation mechanism remains unclear for the alpine grasslands of the Tibetan Plateau (TP). In this study, we investigated the direct and lagged seasonal responses of net primary productivity (NPP) to the beginning of growing season (BGS) along a precipitation gradient by integrating field observations, remote sensing monitoring and ecosystem model simulations. The results revealed distinct response patterns of seasonal NPP to BGS. Specifically, the BGS showed a significant and negative correlation with spring NPP (R = −0.73, p < 0.01), as evidenced by the direct boosting effects of earlier BGS on spring NPP. Moreover, spring NPP was more responsive to BGS in areas with more annual precipitation. The boosting effects of earlier BGS on NPP tended to weaken in summer compared with that in spring. Sequentially, BGS exhibited stronger positive correlation with autumn NPP in areas with less annual precipitation, which suggested the enhanced lagged suppressing effects of earlier spring phenology on ecosystem carbon assimilation during the later growing season under aggravated water stress. Overall, the strengthened NPP in spring was offset by its decrement in autumn, resulting in no obvious relationship between BGS and annual NPP (R = −0.34, p > 0.05) for the entire grasslands on the TP. The findings of this study imply that the lagged effects of phenology on the ecosystem productivity during the subsequent seasons should not be neglected in the future studies. [ABSTRACT FROM AUTHOR]

• Phenology length dominantly influences carbon sequestration in Xizang Plateau. • The dominant role of phenology length enhances along an elevational gradient. • The plateau may play an increasingly crucial role in mitigating future climate change. Interannual variations in terrestrial carbon sequestration are jointly controlled by vegetation phenology and physiological activity. However, it remains unclear how this joint control varies with elevation in alpine ecosystems. To explore the relationships among these factors in Xizang Plateau grassland during 1981–2014, we used the remotely sensed total enhanced vegetation index (EVI) during the growing season (EVI GST), growing season length (GSL), and maximum EVI during the growing season (EVI max) as indicators of annual carbon sequestration, phenology, and photosynthetic activity, respectively. Using these indicators, we investigated the effects of phenology and photosynthetic activity on annual carbon sequestration along an elevation gradient. We found that EVI GST increased, indicating an improvement in carbon sequestration, under prolonged GSL and enhanced EVI max. The trend of a prolonged GSL increased with elevation by 0.039 day year−1 per 1000 m (p < 0.001). The interannual variation in EVI GST was better explained by the interannual variation in GSL (standardized regression coefficient, SRC: 0.88; linear R2: 0.89; partial R2: 0.85) than by that in EVI max (SRC: 0.12; linear R2: 0.33; partial R2: 0.09). This stronger contribution of GSL than of EVI max became more pronounced with increasing elevation. The increase in GSL was more effective than the resistance of environmental constraints of the maximum photosynthetic activity on strengthening carbon sequestration under more extreme environments at higher elevations. These findings increase our understanding of phenological effects on carbon sequestration in alpine ecosystems. Given the projected climate warming and wetting in the future, our study suggests that carbon sequestration will increase due to climate-induced prolongation of GSL across Xizang Plateau grassland. The plateau may play an increasingly crucial role in mitigating future climate change. [ABSTRACT FROM AUTHOR]

Climate and evolutionary factors (e.g. diversification, time-for-speciation, niche conservatism) are both thought to be major drivers of species richness in regional assemblages. However, few studies have simultaneously investigated the relative effects of climate and evolutionary factors on species richness across a broad geographical extent. Here, we assess their relative effects on species richness of angiosperm trees across North America. Species richness of angiosperm trees in 1175 regional assemblages were related to climate and phylogenetic structure using a structural equation modeling (SEM) approach. Climate was quantified based on the mean temperature of the coldest month and mean annual precipitation. Evolutionary factors (time-for-speciation vs diversification) were inferred from phylogeny-based measures of mean root distance, phylogenetic species variability, and net relatedness index. We found that at the continental scale, species richness is correlated with temperature and precipitation with approximately similar strength. In the SEM with net relatedness index and phylogenetic species variability and with all the 1175 quadrats, the total direct effect size of phylogenetic structure on species richness is greater than the total direct effect size of climate on species richness by a factor of 3.7. The specific patterns of phylogenetic structure (i.e. greater phylogenetic distances in more species rich regions) are consistent with the idea that time and niche conservatism drive richness patterns in North American angiosperm trees. We conclude that angiosperm tree species richness in regional assemblages in North America is more strongly related to patterns of phylogenetic relatedness than to climatic variation. The results of the present study support the idea that climatic and evolutionary explanations for richness patterns are not in conflict, and that evolutionary processes explain both the relationship between climate and richness and substantial variation in richness that is independent of climate. [ABSTRACT FROM AUTHOR]

Aim To understand: (1) how temperature, precipitation and stand age control the above-ground biomass carbon density ( BCDa) of mature forests and its macroecology patterns across latitudes; (2) the age threshold for old-growth forests at a global scale. Location Global forests. Methods We compiled a database (897 sites) of mature forests between 80 and 1200 years old. The site data include latitude, longitude, mean annual temperature, mean annual precipitation, forest type, stand age, BCDa, living biomass (above- and below-ground biomass) carbon density and total (living plus dead) biomass carbon density. Based on the site data, we performed regression analyses to show how BCDa changes with climate and forest stand age. Results At a global scale, the highest BCDa of mature forests occurred mainly in the mid-latitude regions where mean annual temperatures were 8-10 °C and mean annual precipitation was between 1000 and 2500 mm. The average BCDa of forests in the stand age class of 450-500 years was higher than those in the other stand age classes. For forests between 80 and 450 years old, which form the majority of mature forests, carbon accumulation was faster in dead biomass than in living biomass. Main conclusions The highest BCDa of mature forests is located in mid-latitude regions with cool temperatures and moderate precipitation. The age threshold for old-growth forests at a global scale should be 450-500 years, which is much older than the previously documented age of 100-200 years. This older age threshold for old-growth forests is probably one of the primary reasons why recent works have concluded that old-growth forests are still carbon sinks. [ABSTRACT FROM AUTHOR]

Although forest landscape models (FLMs) have benefited greatly from ongoing advances of computer technology and software engineering, computing capacity remains a bottleneck in the design and development of FLMs. Computer memory overhead and run time efficiency are primary limiting factors when applying forest landscape models to simulate large landscapes with fine spatial resolutions and great vegetation detail. We introduce LANDIS PRO 6.0, a landscape model that simulates forest succession and disturbances on a wide range of spatial and temporal scales. LANDIS PRO 6.0 improves on existing forest landscape models with two new data structures and algorithms (hash table and run-length compression). The innovative computer design enables LANDIS PRO 6.0 to simulate very large (>108 ha) landscapes with a 30-m spatial resolution, which to our knowledge no other raster forest landscape models can do. We demonstrate model behavior and performance through application to five nested forest landscapes with varying sizes (from 1 million to 100 million 0.09-ha cells) in the southern Missouri Ozarks. The simulation results showed significant and variable effects of changing spatial extent on simulated forest succession patterns. Results highlighted the utility of a model like LANDIS PRO 6.0 that is capable of efficiently simulating large landscapes and scaling up forest landscape processes to a common regional scale of analysis. The programming methodology presented here may significantly advance the development of next generation of forest landscape models. [Copyright &y& Elsevier]

The Tibetan Plateau (TP), known as "The Roof of World", has expansive alpine grasslands and is a hotspot for climate change studies. However, cropland expansion and increasing anthropogenic activities have been poorly documented, let alone the effects of agricultural activities on food security and environmental change in the TP. The existing cropland mapping products do not depict the spatiotemporal characteristics of the TP due to low accuracies and inconsistent cropland distribution, which is affected by complicated topography and impedes our understanding of cropland expansion and its associated environmental impacts. One of the biggest challenges of cropland mapping in the TP is the diverse crop phenology across a wide range of elevations. To decrease the classification errors due to elevational differences in crop phenology, we developed two pixel- and phenology-based algorithms to map croplands using Landsat imagery and the Google Earth Engine platform along the Brahmaputra River and its two tributaries (BRTT) in the Tibet Autonomous Region, also known as the granary of TP, in 2015–2019. Our first phenology-based cropland mapping algorithm (PCM1) used different thresholds of land surface water index (LSWI) by considering varied crop phenology along different elevations. The second algorithm (PCM2) further offsets the phenological discrepancy along elevational gradients by considering the length and peak of the growing season. We found that PCM2 had a higher accuracy with fewer images compared with PCM1. The number of images for PCM2 was 279 less than PCM1, and the Matthews correlation coefficient for PCM2 was 0.036 higher than PCM1. We also found that the cropland area in BRTT was estimated to be 1979 ± 52 km2 in the late 2010s. Croplands were mainly distributed in the BRTT basins with elevations of 3800–4000 m asl. Our phenology-based methods were effective for mapping croplands in mountainous areas. The spatially explicit information on cropland area and distribution in the TP aid future research into the effects of cropland expansion on food security and environmental change in the TP. [ABSTRACT FROM AUTHOR]

Coastal wetlands provide essential ecosystem services and are closely related to human welfare. However, they can experience substantial degradation, especially in regions in which there is intense human activity. To control these increasingly severe problems and to develop corresponding management policies in coastal wetlands, it is critical to accurately map coastal wetlands. Although remote sensing is the most efficient way to monitor coastal wetlands at a regional scale, it traditionally involves a large amount of work, high cost, and low spatial resolution when mapping coastal wetlands at a large scale. In this study, we developed a workflow for rapidly mapping coastal wetlands at a 10 m spatial resolution, based on the recently emergent Google Earth Engine platform, using a machine learning algorithm, open-access Synthetic Aperture Radar (SAR) and optical images from the Sentinel satellites, and two terrain indices. We then generated a coastal wetland map of the Bohai Rim (BRCW10) based on the workflow. It has a producer accuracy of 82.7%, according to validation using 150 wetland samples. The BRCW10 data reflected finer information when compared to wetland maps derived from two sets of global high-spatial-resolution land cover data, due to the fusion of multiple data sources. The study highlights the benefits of simultaneously merging SAR and optical remote sensing images when mapping coastal wetlands. [ABSTRACT FROM AUTHOR]