
Spatiotemporal characteristics and influencing factors of vegetation water use efficiency on the Tibetan Plateau in 2001-2020
HE Chenyang, WANG Yanjiao, YAN Feng, LU Qi
Journal of Geographical Sciences ›› 2025, Vol. 35 ›› Issue (1) : 39-64.
Spatiotemporal characteristics and influencing factors of vegetation water use efficiency on the Tibetan Plateau in 2001-2020
Water use efficiency (WUE), as a pivotal indicator of the coupling degree within the carbon-water cycle of ecosystems, holds considerable importance in assessment of the carbon-water balance within terrestrial ecosystems. However, in the context of global warming, WUE evolution and its primary drivers on the Tibetan Plateau remain unclear. This study employed the ensemble empirical mode decomposition method and the random forest algorithm to decipher the nonlinear trends and drivers of WUE on the Tibetan Plateau in 2001- 2020. Results indicated an annual mean WUE of 0.8088 gC/mm∙m2 across the plateau, with a spatial gradient reflecting decrease from the southeast toward the northwest. Areas manifesting monotonous trends of increase or decrease in WUE accounted for 23.64% and 9.69% of the total, respectively. Remarkably, 66.67% of the region exhibited trend reversals, i.e., 39.94% of the area of the Tibetan Plateau showed transition from a trend of increase to a trend of decrease, and 26.73% of the area demonstrated a shift from a trend of decrease to a trend of increase. Environmental factors accounted for 70.79% of the variability in WUE. The leaf area index and temperature served as the major driving forces of WUE variation.
water use efficiency / spatiotemporal characteristic / influencing factor / Tibetan Plateau {{custom_keyword}} /
Table 1 Proportions of EEMD trends in water use efficiency for different vegetation types |
Types | In to In | De to De | De to In | In to De |
---|---|---|---|---|
Desert | 44.32 | 3.36 | 26.43 | 25.89 |
Grassland | 32.74 | 7.44 | 19.68 | 40.14 |
Cultivation | 29.29 | 8.93 | 28.49 | 33.28 |
Forest | 21.10 | 8.59 | 48.07 | 22.23 |
Meadow | 20.25 | 11.27 | 22.28 | 46.20 |
Shrubs | 18.41 | 10.75 | 34.14 | 36.69 |
Swamp | 17.65 | 10.12 | 23.90 | 48.33 |
Alpine | 20.03 | 9.95 | 29.10 | 40.91 |
[1] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[2] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[3] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[4] |
With the development of rapid measurement techniques, stable oxygen isotope analysis of plant tissue is poised to become an important tool in plant physiological, ecological, paleoclimatic and forensic studies. Recent advances in mechanistic understanding have led to the improvement of process-based models that accurately predict variability in the oxygen isotope composition of plant organic material (δO). δO has been shown to reflect the isotope composition of soil water, evaporative enrichment in transpiring leaves, and isotopic exchange between oxygen atoms in organic molecules and local water in the cells in which organic molecules are formed. This review presents current theoretical models describing the influences on δO, using recently published experimental work to outline strengths and weaknesses in the models. The potential and realised applications of the technique are described.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[5] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[6] |
The world's forests influence climate through physical, chemical, and biological processes that affect planetary energetics, the hydrologic cycle, and atmospheric composition. These complex and nonlinear forest-atmosphere interactions can dampen or amplify anthropogenic climate change. Tropical, temperate, and boreal reforestation and afforestation attenuate global warming through carbon sequestration. Biogeophysical feedbacks can enhance or diminish this negative climate forcing. Tropical forests mitigate warming through evaporative cooling, but the low albedo of boreal forests is a positive climate forcing. The evaporative effect of temperate forests is unclear. The net climate forcing from these and other processes is not known. Forests are under tremendous pressure from global change. Interdisciplinary science that integrates knowledge of the many interacting climate services of forests with the impacts of global change is necessary to identify and understand as yet unexplored feedbacks in the Earth system and the potential of forests to mitigate climate change.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[7] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[8] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[9] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[10] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[11] |
Carbon use efficiency (CUE), one of the most important eco-physiological parameters, represents the capacity of plants to transform carbon into new biomass. Understanding the variations and controls of CUE is crucial for regional carbon assessment. Here, we used 15-years of continuous remote sensing data to examine the variations of CUE across broad geographic and climatic gradients in China. The results showed that the vegetation CUE was averaged to 0.54 ± 0.11 with minor interannual variation. However, the CUE greatly varied with geographic gradients and ecosystem types. Forests have a lower CUE than grasslands and croplands. Evergreen needleleaf forests have a higher CUE than other forest types. Climate factors (mean annual temperature (MAT), precipitation (MAP) and the index of water availability (IWA)) dominantly regulated the spatial variations of CUE. The CUE exhibited a linear decrease with enhanced MAT and MAP and a parabolic response to the IWA. Furthermore, the responses of CUE to environmental change varied with individual ecosystem type. In contrast, precipitation exerted strong control on CUE in grassland, while in forest and cropland, the CUE was mainly controlled by the available water. This study identifies the variations and response of CUE to environmental drivers in China, which will be valuable for the regional assessment of carbon cycling dynamics under future climate change.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[12] |
Copernicus Climate Change Service, 2019. ERA5-Land monthly averaged data from 2001 to present. ECMWF(2019) [2023-08-12].
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[13] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[14] |
Plant water-use efficiency (WUE) is expected to affect plant fitness and thus be under natural selection in arid habitats. Although many natural population studies have assessed plant WUE, only a few related WUE to fitness. The further determination of whether selection on WUE is direct or indirect through functionally related traits has yielded no consistent results. For natural populations of two desert annual sunflowers, Helianthus anomalus and H. deserticola, we used phenotypic selection analysis with vegetative biomass as the proxy for fitness to test (1) whether there was direct and indirect selection on WUE (carbon isotope ratio) and related traits (leaf N, area, succulence) and (2) whether direct selection was consistent with hypothesized drought/dehydration escape and avoidance strategies. There was direct selection for lower WUE in mesic and dry H. anomalus populations, consistent with dehydration escape, even though it is the longer lived of the two species. For mesic H. anomalus, direct selection favored lower WUE and higher N, suggesting that plants may be "wasting water" to increase N delivery via the transpiration stream. For the shorter lived H. deserticola in the direr habitat, there was indirect selection for lower WUE, inconsistent with drought escape. There was also direct selection for higher leaf N, succulence and leaf size. There was no direct selection for higher WUE consistent with dehydration avoidance in either species. Thus, in these natural populations of two desert dune species higher fitness was associated with some combination direct and indirect selection for lower WUE, higher leaf N and larger leaf size. Our understanding of the adaptive value of plant ecophysiological traits will benefit from further consideration of related traits such as leaf nitrogen and more tests in natural populations.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[15] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[16] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[17] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[18] |
Climate change is a major driver of vegetation activity, and thus their complex processes become a frontier and difficulty in global change research. To understand this relationship between climate change and vegetation activity, the spatial distribution and dynamic characteristics of the response of NDVI to climate change were investigated by the geographically weighted regression (GWR) model during 1982 to 2013 in China. This model was run based on the combined datasets of satellite vegetation index (NDVI) and climate observation (temperature and moisture) from meteorological stations nationwide. The results showed that the spatial non-stationary relationship between NDVI and surface temperature has appeared in China: the significant negative temperature-vegetation relationship was located in Northeast, Northwest and Southeast China, while the positive correlation was more concentrated from southwest to northeast. By comparing the normalized regression coefficients from GWR model for different climate factors, it presented the regions with moisture dominants for NDVI were in North China and the Tibetan Plateau, and the areas of temperature dominants were distributed in East, Central and Southwest China, where the annual mean maximum temperature accounted for the largest areas. In addition, regression coefficients from GWR model between NDVI dynamics and climate variability indicated that the higher warming rate could result in the weakened vegetation activity through some mechanisms such as enhanced drought, while the moisture variability could mediate the hydrothermal conditions for the variation of vegetation activity. When the increasing rate of photosynthesis exceeded that of respiration, the positive correlation between vegetation dynamics and climate variability was reflected. However, the continuous and dynamic process of vegetation activity response to climate change will be determined by spatially heterogeneous conditions in climate change and vegetation cover. Furthermore, the dynamic description of climate-induced vegetation activity from its rise to decline in different regions is expected to provide a scientific basis for initiating ecosystem-based adaptation strategies in response to global climate change. {{custom_citation.content}}
{{custom_citation.annotation}}
|
[19] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[20] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[21] |
Elucidating the distribution of the grazing pressure requires an understanding of the grazing activities. In this study, we analyzed the grazing behavior of yaks in Three-River- Source Region (TRSR) and identified the main factors influencing the distribution of grazing intensity (GI) using trajectory data and remote sensing datasets. Our results revealed that a semi-resident transhumance strategy is employed in this region. The average grazing time (GT) of four GPS collars over the year was 11.84 h/day (N6), 11.01 h/day (N11), 9.25 h/day (N18), and 11.61 h/day (N24). GT was generally higher in warm seasons (summer and autumn) than in cold seasons (spring and winter). The average daily moving speed was found to be closely related to the pasture size of different herders and the seasons. Geodetector analysis identified the distance to camp (DOC) as the most important single factor influencing the distribution of GI, explaining up to 52% of the GI variations. However, relying solely on this factor may not accurately depict the actual GI distribution. When pairwise factors interacted, the explanatory power of the model increased, ranging from 34.55% to 63.26%. Our study highlights the importance of considering multiple factors when predicting grazing intensity, as grazing activities tend to cluster near settlements, but other factors may also be influential. {{custom_citation.content}}
{{custom_citation.annotation}}
|
[22] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[23] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[24] |
Physiological acclimation and genotypic adaptation to prevailing temperatures may influence forest responses to future climatic warming. We examined photosynthetic and respiratory responses of sugar maple (Acer saccharum Marsh.) from two portions of the species' range for evidence of both phenomena in a laboratory study with seedlings. A field study was also conducted to assess the impacts of temperature acclimation on saplings subjected to an imposed temperature manipulation (4 degrees C above ambient temperature). The two seedling populations exhibited more evidence of physiological acclimation to warming than of ecotypic adaptation, although respiration was less sensitive to short-term warming in the southern population than in the northern population. In both seedling populations, thermal compensation increased photosynthesis by 14% and decreased respiration by 10% in the warm-acclimated groups. Saplings growing in open-top field chambers at ambient temperature and 4 degrees C above ambient temperature showed evidence of temperature acclimation, but photosynthesis did not increase in response to the 4 degrees C warming. On the contrary, photosynthetic rates measured at the prevailing chamber temperature throughout three growing seasons were similar, or lower (12% lower on average) in saplings maintained at 4 degrees C above ambient temperature compared with saplings maintained at ambient temperature. However, the long-term photosynthetic temperature optimum for saplings in the field experiment was higher than it was for seedlings in either the 27 or the 31 degrees C growth chamber. Respiratory acclimation was also evident in the saplings in the field chambers. Saplings had similar rates of respiration in both temperature treatments, and respiration showed little dependence on prevailing temperature during the growing season. We conclude that photosynthesis and respiration in sugar maple have the potential for physiological acclimation to temperature, but exhibit a low degree of genetic adaptation. Some of the potential for acclimation to a 4 degrees C increase above a background of naturally fluctuating temperatures may be offset by differences in water relations, and, in the long term, may be obscured by the inherent variability in rates under field conditions. Nevertheless, physiologically based models should incorporate seasonal acclimation to temperature and permit ecotypic differences to influence model outcomes for those species with high genetic differentiation between regions.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[25] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[26] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[27] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[28] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[29] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[30] |
Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m(-2) mm(-1) yr(-1) under the single effect of rising CO2 ('CO2 '), climate change ('CLIM') and nitrogen deposition ('NDEP'), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (-0.0005 g C m(-2) mm(-1) yr(-1) ), which differs from process-model (0.0064 g C m(-2) mm(-1) yr(-1) ) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt, GPP×VPD/TR) in response to rising CO2, climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon-water interactions over terrestrial ecosystems under global change. © 2015 John Wiley & Sons Ltd.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[31] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[32] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[33] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[34] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[35] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[36] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[37] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[38] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[39] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[40] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[41] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[42] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[43] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[44] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[45] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[46] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[47] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[48] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[49] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[50] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[51] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[52] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[53] |
Recent climatic changes have enhanced plant growth in northern mid-latitudes and high latitudes. However, a comprehensive analysis of the impact of global climatic changes on vegetation productivity has not before been expressed in the context of variable limiting factors to plant growth. We present a global investigation of vegetation responses to climatic changes by analyzing 18 years (1982 to 1999) of both climatic data and satellite observations of vegetation activity. Our results indicate that global changes in climate have eased several critical climatic constraints to plant growth, such that net primary production increased 6% (3.4 petagrams of carbon over 18 years) globally. The largest increase was in tropical ecosystems. Amazon rain forests accounted for 42% of the global increase in net primary production, owing mainly to decreased cloud cover and the resulting increase in solar radiation.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[54] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[55] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[56] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[57] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[58] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[59] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[60] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[61] |
Background Deep roots are a common trait among a wide range of plant species and biomes, and are pivotal to the very existence of ecosystem services such as pedogenesis, groundwater and streamflow regulation, soil carbon sequestration and moisture content in the lower troposphere. Notwithstanding the growing realization of the functional significance of deep roots across disciplines such as soil science, agronomy, hydrology, ecophysiology or climatology, research efforts allocated to the study of deep roots remain incommensurate with those devoted to shallow roots. This is due in part to the fact that, despite technological advances, observing and measuring deep roots remains challenging. Scope Here, other reasons that explain why there are still so many fundamental unresolved questions related to deep roots are discussed. These include the fact that a number of hypotheses and models that are widely considered as verified and sufficiently robust are only partly supported by data. Evidence has accumulated that deep rooting could be a more widespread and important trait among plants than usually considered based on the share of biomass that it represents. Examples that indicate that plant roots have different structures and play different roles with respect to major biochemical cycles depending on their position within the soil profile are also examined and discussed. Conclusions Current knowledge gaps are identified and new lines of research for improving our understanding of the processes that drive deep root growth and functioning are proposed. This ultimately leads to a reflection on an alternative paradigm that could be used in the future as a unifying framework to describe and analyse deep rooting. Despite the many hurdles that pave the way to a practical understanding of deep rooting functions, it is anticipated that, in the relatively near future, increased knowledge about the deep rooting traits of a variety of plants and crops will have direct and tangible influence on how we manage natural and cultivated ecosystems.© The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[62] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[63] |
In this study, the interplay between ecosystem services and human well-being in Seni district, which is a pastoral region of Nagqu city on the Qinghai-Tibet Plateau, is investigated. Employing the improved InVEST model, CASA model, coupling coordination model, and hierarchical clustering method, we analyze the spatiotemporal patterns of ecosystem services, the levels of resident well-being levels, and the interrelationships between these factors over the period from 2000 to 2018. Our findings reveal significant changes in six ecosystem services, with water production decreasing by 7.1% and carbon sequestration and soil conservation services increasing by approximately 6.3% and 14.6%, respectively. Both the habitat quality and landscape recreation services remained stable. Spatially, the towns in the eastern and southern areas exhibited higher water production and soil conservation services, while those in the central area exhibited greater carbon sequestration services. The coupling and coordination relationship between ecosystem services and human well-being improved significantly over the study period, evolving from low-level coupling to coordinated coupling. Hierarchical clustering was used to classify the 12 town-level units into five categories. Low subjective well-being townships had lower livestock breeding services, while high subjective well-being townships had higher supply, regulation, and support ecosystem services. Good transportation conditions were associated with higher subjective well-being in townships with low supply services. We recommend addressing the identified transportation disparities and enhancing key regulatory and livestock breeding services to promote regional sustainability and improve the quality of life for Seni district residents, thus catering to the diverse needs of both herdsmen and citizens. {{custom_citation.content}}
{{custom_citation.annotation}}
|
[64] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[65] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[66] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[67] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[68] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[69] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[70] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[71] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[72] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[73] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[74] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[75] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[76] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[77] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[78] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[79] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[80] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[81] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[82] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[83] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[84] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[85] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[86] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[87] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[88] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[89] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[90] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[91] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[92] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[93] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[94] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[95] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[96] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[97] |
Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system and provision of ecosystem services(1,2). Yet how global vegetation is responding to the changing environment is not well established. Here we use three long-term satellite leaf area index (LAI) records and ten global ecosystem models to investigate four key drivers of LAI trends during 1982-2009. We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models suggest that CO2 fertilization effects explain 70% of the observed greening trend, followed by nitrogen deposition (9%), climate change (8%) and land cover change (LCC) (4%). CO2 fertilization effects explain most of the greening trends in the tropics, whereas climate change resulted in greening of the high latitudes and the Tibetan Plateau. LCC contributed most to the regional greening observed in southeast China and the eastern United States. The regional effects of unexplained factors suggest that the next generation of ecosystem models will need to explore the impacts of forest demography, differences in regional management intensities for cropland and pastures, and other emerging productivity constraints such as phosphorus availability.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
{{custom_ref.label}} |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
/
〈 |
|
〉 |