Forest ecosystem productivity and function is strongly influenced by the interaction between soil organisms and their resource use that can be impeded by an imbalance of ecological stoichiometry. Soil microorganisms are known to have an important role in biogeochemical cycling which is strongly influenced by ecological stoichiometry. However, there is limited understanding of how soil micro-food web respond to stoichiometric imbalances during forest restoration. Here, we investigated the effect of forest restoration on soil physio-chemical properties and the structure and function of soil micro-food web along a chronosequence of transformation stages: (i) early stage monoculture plantation of Chinese fir (Cunninghamia lanceolata) comprised of three age classes (5, 10 and 20 years); (ii) mid-stage conifer-broadleaved mixed forest; and (iii) late-stage mixed species broadleaved forest in south China. Results showed that forest restoration from C. lanceolata monocultures to mixed species broadleaved forest significantly increased soil organic carbon and total nitrogen. Soil bacteria, fungi, protists and nematodes abundance increased and the co-occurrence networks of soil biota became more complex and stable along the restoration chronosequence. In contrast, soil nitrogen and phosphorus limitations, particularly phosphorus limitation, increased along the chronosequence. In addition, soil exoenzyme activity suggested that the microbial investment in resource acquisition shifted from C-to nutrient-acquiring enzymes from the earlier to the later restoration stages. Availability of soil resources (e.g., dissolved organic carbon, ammonium, and available phosphate) appeared to have an important role in regulating soil food web composition, structure and stability during forest restoration. We conclude that nutrient limitation, particularly phosphorus limitation, likely has an important role in determining the stability of soil food webs during forest restoration. These findings contribute to our understanding of the relationships between soil nutrient limitation and soil micro-food web, and have implications for carbon sequestration through forest restoration and management in southern China.

Urbanization shows continuous expansion and development, ushering in the co-evolution of urban environments and vegetation over time. Recent remote sensing-based studies have discovered prevalent vegetation growth enhancement in urban environments. However, whether there is a temporal evolution of the growth enhancement remains unknown and unexplored. Here we expanded the existing framework for assessing the long-term impact of urbanization on veg-etation greenness (enhanced vegetation index, EVI) using long time series of remote sensing images and applied it in Changsha, the capital city of Hunan province in China. Results showed that vegetation growth experienced widespread enhancement from 2000 to 2017, and increased 1.8 times from 2000 to 2017, suggesting strong continuous adaptive capability of vegetation to urban conditions. Although the overall impact of urbanization was negative due to the re-placement of vegetated surfaces, the growth enhancement nevertheless offset or compensated the direct loss of vege-tated cover during urbanization in the magnitude of 28 % in 2000 to 44 % in 2017. Our study also revealed large spatial heterogeneity in vegetation growth response among various districts at different urbanization levels and found an emergent trend under the observed spatial heterogeneity toward an asymptotic maximum with urbanization, showing EVI converges to 0.22 in highly urbanized areas. We further found that the positive effect of urbanization on vegetation growth is a function of urbanization intensity and time, which implies that the effect of the urban environ-ment on vegetation can be simulated and predicted, and can be verified in more cities in the future. Our study is the first to successfully quantify long-term spatial patterns on the co-evolution of urbanization and vegetation, providing a new understanding of the continuous adaptive responses of vegetation growth to urbanization and shedding light on predicting biological responses to future environmental change.

Higher land surface temperature (LST) in cities than its surrounding areas presents a major sustainability challenge for cities. Adaptation and mitigation of the increased LST require in-depth understanding of the impacts of landscape features on LST. We studied the influences of different landscape features on LST in five large cities across China to investigate how the features of a specific urban landscape (endogenous features), and neighboring environments (exogenous features) impact its LST across a continuum of spatial scales. Surprisingly, results show that the influence of endogenous landscape features (E-endo) on LST can be described consistently across all cities as a nonlinear function of grain size (g(s)) and neighbor size (n(s)) (E-endo = beta n(s)g(s)(-0.5), where beta is a city-specific constant) while the influence of exogenous features (E-exo) depends only on neighbor size (n(s)) (E-exo = gamma-epsilon n(s)(0.5), where gamma and epsilon are city-specific constants). In addition, a simple relationship describing the relative strength of endogenous and exogenous impacts of landscape features on LST was found (E-endo > E-exo if ns > kg(s)(2/5), where k is a city-specific parameter; otherwise, E-endo < E-exo). Overall, vegetation alleviates 40%-60% of the warming effect of built-up while surface wetness intensifies or reduces it depending on climate conditions. This study reveals a set of unifying quantitative relationships that effectively describes landscape impacts on LST across cities, grain and neighbor sizes, which can be instrumental towards the design of sustainable cities to deal with increasing temperature. (C) 2021 Elsevier B.V. All rights reserved.

Through litter decomposition enormous amounts of carbon is emitted to the atmosphere. Numerous large-scale decomposition experiments have been conducted focusing on this fundamental soil process in order to understand the controls on the terrestrial carbon transfer to the atmosphere. However, previous studies were mostly based on site-specific litter and methodologies, adding major uncertainty to syntheses, comparisons and meta-analyses across different experiments and sites. In the TeaComposition initiative, the potential litter decomposition is investigated by using standardized substrates (Rooibos and Green tea) for comparison of litter mass loss at 336 sites (ranging from -9 to +26 degrees C MAT and from 60 to 3113 mm MAP) across different ecosystems. In this study we tested the effect of climate (temperature and moisture), litter type and land-use on early stage decomposition (3 months) across nine biomes. We show that litter quality was the predominant controlling factor in early stage litter decomposition, which explained about 65% of the variability in litter decomposition at a global scale. The effect of climate, on the other hand, was not litter specific and explained <0.5% of the variation for Green tea and 5% for Rooibos tea, and was of significance only under unfavorable decomposition conditions (i.e. xeric versus mesic environments). When the data were aggregated at the biome scale, climate played a significant role on decomposition of both litter types (explaining 64% of the variation for Green tea and 72% for Rooibos tea). No significant effect of land-use on early stage litter decomposition was noted within the temperate biome. Our results indicate that multiple drivers are affecting early stage litter mass loss with litter quality being dominant. In order to be able to quantify the relative importance of the different drivers over time, long-term studies combined with experimental trials are needed. (C) 2018 Elsevier B.V. All rights reserved.