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Votre recherche

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L’interface de recherche est composée de trois sections : Rechercher, Explorer et Résultats. Celles-ci sont décrites en détail ci-dessous.

Vous pouvez lancer une recherche aussi bien à partir de la section Rechercher qu’à partir de la section Explorer.

Rechercher

Cette section affiche vos critères de recherche courants et vous permet de soumettre des mots-clés à chercher dans la bibliographie.

  • Chaque nouvelle soumission ajoute les mots-clés saisis à la liste des critères de recherche.
  • Pour lancer une nouvelle recherche plutôt qu’ajouter des mots-clés à la recherche courante, utilisez le bouton Réinitialiser la recherche, puis entrez vos mots-clés.
  • Pour remplacer un mot-clé déjà soumis, veuillez d’abord le retirer en décochant sa case à cocher, puis soumettre un nouveau mot-clé.
  • Vous pouvez contrôler la portée de votre recherche en choisissant où chercher. Les options sont :
    • Partout : repère vos mots-clés dans tous les champs des références bibliographiques ainsi que dans le contenu textuel des documents disponibles.
    • Dans les auteurs ou contributeurs : repère vos mots-clés dans les noms d’auteurs ou de contributeurs.
    • Dans les titres : repère vos mots-clés dans les titres.
    • Dans tous les champs : repère vos mots-clés dans tous les champs des notices bibliographiques.
    • Dans les documents : repère vos mots-clés dans le contenu textuel des documents disponibles.
  • Vous pouvez utiliser les opérateurs booléens avec vos mots-clés :
    • ET : repère les références qui contiennent tous les termes fournis. Ceci est la relation par défaut entre les termes séparés d’un espace. Par exemple, a b est équivalent à a ET b.
    • OU : repère les références qui contiennent n’importe lequel des termes fournis. Par exemple, a OU b.
    • SAUF : exclut les références qui contiennent le terme fourni. Par exemple, SAUF a.
    • Les opérateurs booléens doivent être saisis en MAJUSCULES.
  • Vous pouvez faire des groupements logiques (avec les parenthèses) pour éviter les ambiguïtés lors de la combinaison de plusieurs opérateurs booléens. Par exemple, (a OU b) ET c.
  • Vous pouvez demander une séquence exacte de mots (avec les guillemets droits), par exemple "a b c". Par défaut la différence entre les positions des mots est de 1, ce qui signifie qu’une référence sera repérée si elle contient les mots et qu’ils sont consécutifs. Une distance maximale différente peut être fournie (avec le tilde), par exemple "a b"~2 permet jusqu’à un terme entre a et b, ce qui signifie que la séquence a c b pourrait être repérée aussi bien que a b.
  • Vous pouvez préciser que certains termes sont plus importants que d’autres (avec l’accent circonflexe). Par exemple, a^2 b c^0.5 indique que a est deux fois plus important que b dans le calcul de pertinence des résultats, tandis que c est de moitié moins important. Ce type de facteur peut être appliqué à un groupement logique, par exemple (a b)^3 c.
  • La recherche par mots-clés est insensible à la casse et les accents et la ponctuation sont ignorés.
  • Les terminaisons des mots sont amputées pour la plupart des champs, tels le titre, le résumé et les notes. L’amputation des terminaisons vous évite d’avoir à prévoir toutes les formes possibles d’un mot dans vos recherches. Ainsi, les termes municipal, municipale et municipaux, par exemple, donneront tous le même résultat. L’amputation des terminaisons n’est pas appliquée au texte des champs de noms, tels auteurs/contributeurs, éditeur, publication.

Explorer

Cette section vous permet d’explorer les catégories associées aux références.

  • Les catégories peuvent servir à affiner votre recherche. Cochez une catégorie pour l’ajouter à vos critères de recherche. Les résultats seront alors restreints aux références qui sont associées à cette catégorie.
  • Dé-cochez une catégorie pour la retirer de vos critères de recherche et élargir votre recherche.
  • Les nombres affichés à côté des catégories indiquent combien de références sont associées à chaque catégorie considérant les résultats de recherche courants. Ces nombres varieront en fonction de vos critères de recherche, de manière à toujours décrire le jeu de résultats courant. De même, des catégories et des facettes entières pourront disparaître lorsque les résultats de recherche ne contiennent aucune référence leur étant associées.
  • Une icône de flèche () apparaissant à côté d’une catégorie indique que des sous-catégories sont disponibles. Vous pouvez appuyer sur l’icône pour faire afficher la liste de ces catégories plus spécifiques. Par la suite, vous pouvez appuyer à nouveau pour masquer la liste. L’action d’afficher ou de masquer les sous-catégories ne modifie pas vos critères de recherche; ceci vous permet de rapidement explorer l’arborescence des catégories, si désiré.

Résultats

Cette section présente les résultats de recherche. Si aucun critère de recherche n’a été fourni, elle montre toute la bibliographie (jusqu’à 20 références par page).

  • Chaque référence de la liste des résultats est un hyperlien vers sa notice bibliographique complète. À partir de la notice, vous pouvez continuer à explorer les résultats de recherche en naviguant vers les notices précédentes ou suivantes de vos résultats de recherche, ou encore retourner à la liste des résultats.
  • Des hyperliens supplémentaires, tels que Consulter le document ou Consulter sur [nom d’un site web], peuvent apparaître sous un résultat de recherche. Ces liens vous fournissent un accès rapide à la ressource, des liens que vous trouverez également dans la notice bibliographique.
  • Le bouton Résumés vous permet d’activer ou de désactiver l’affichage des résumés dans la liste des résultats de recherche. Toutefois, activer l’affichage des résumés n’aura aucun effet sur les résultats pour lesquels aucun résumé n’est disponible.
  • Diverses options sont fournies pour permettre de contrôler l’ordonnancement les résultats de recherche. L’une d’elles est l’option de tri par Pertinence, qui classe les résultats du plus pertinent au moins pertinent. Le score utilisé à cette fin prend en compte la fréquence des mots ainsi que les champs dans lesquels ils apparaissent. Par exemple, si un terme recherché apparaît fréquemment dans une référence ou est l’un d’un très petit nombre de termes utilisé dans cette référence, cette référence aura probablement un score plus élevé qu’une autre où le terme apparaît moins fréquemment ou qui contient un très grand nombre de mots. De même, le score sera plus élevé si un terme est rare dans l’ensemble de la bibliographie que s’il est très commun. De plus, si un terme de recherche apparaît par exemple dans le titre d’une référence, le score de cette référence sera plus élevé que s’il apparaissait dans un champ moins important tel le résumé.
  • Le tri par Pertinence n’est disponible qu’après avoir soumis des mots-clés par le biais de la section Rechercher.
  • Les catégories sélectionnées dans la section Explorer n’ont aucun effet sur le tri par pertinence. Elles ne font que filtrer la liste des résultats.
Dans les auteurs ou contributeurs
  • "Peng, Changhui"

Résultats 425 ressources

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Résumés
  • Wang, T., Deng, Z., Xie, Y., Wang, B., Wu, S., Li, F., Wang, W., Zou, Y., Li, X., Hou, Z., Zeng, J., Wang, M., & Peng, C. (2023). Time-lag effects of flood stimulation on methane emissions in the Dongting Lake floodplain, China. Agricultural and Forest Meteorology, 341, 109677. https://doi.org/10.1016/j.agrformet.2023.109677
    Consulter sur linkinghub.elsevier.com
  • Wu, X., Liu, H., Li, X., Piao, S., Ciais, P., Guo, W., Yin, Y., Poulter, B., Peng, C., Viovy, N., Vuichard, N., Wang, P., & Huang, Y. (2017). Higher temperature variability reduces temperature sensitivity of vegetation growth in Northern Hemisphere. Geophysical Research Letters, 44(12), 6173–6181. https://doi.org/10.1002/2017GL073285

    Abstract Interannual air temperature variability has changed over some regions in Northern Hemisphere (NH), accompanying with climate warming. However, whether and to what extent it regulates the interannual sensitivity of vegetation growth to temperature variability (i.e., interannual temperature sensitivity)—one central issue in understanding and predicting the responses of vegetation growth to changing climate—still remains poorly quantified and understood. Here we quantify the relationships between the interannual temperature sensitivity of mean growing‐season (April–October) normalized difference vegetation index (NDVI) and ecosystem model simulations of gross primary productivity (GPP), and variability in mean growing‐season temperature for forest, shrub, and grass over NH. We find that higher interannual variability in mean growing‐season temperature leads to consistent decrease in interannual temperature sensitivity of mean growing‐season NDVI among all vegetation types but not in model simulations of GPP. Drier condition associates with ~130 ± 150% further decrease in interannual temperature sensitivity of mean growing‐season NDVI by temperature variability in forest and shrub. These results illustrate that varying temperature variability can significantly regulate the interannual temperature sensitivity of vegetation growth over NH, interacted with drought variability and nonlinear responses of photosynthesis to temperature. Our findings call for an improved characterization of the nonlinear effects of temperature variability on vegetation growth within global ecosystem models. , Key Points It shows consistent decrease in temperature sensitivity of vegetation growth by temperature variability for all vegetation types Larger decrease in temperature sensitivity of vegetation growth by temperature variability is found in forest and shrub in dry regions Drier condition adds further decrease in temperature sensitivity of vegetation growth by temperature variability for forest and shrub in dry regions

    Consulter sur agupubs.onlinelibrary.wiley.com
  • Jiang, X., Chen, H., Peng, C., Li, Y., He, Y., Chen, D., Lin, M., Hu, J., Ma, T., Liu, L., Liu, X., Xia, M., & Liu, Y. (2016). Soil Carbon Dioxide Fluxes from Three Forest Types of the Tropical Montane Rainforest on Hainan Island, China. Water, Air, & Soil Pollution, 227(6), 213. https://doi.org/10.1007/s11270-016-2904-1
    Consulter sur link.springer.com
  • Wang, M., Yang, G., Gao, Y., Chen, H., Wu, N., Peng, C., Zhu, Q., Zhu, D., Wu, J., He, Y., Tian, J., Zhao, X., & Zhang, Y. (2015). Higher recent peat C accumulation than that during the Holocene on the Zoige Plateau. Quaternary Science Reviews, 114, 116–125. https://doi.org/10.1016/j.quascirev.2015.01.025
    Consulter sur linkinghub.elsevier.com
  • Wang, Y., Chen, H., Zhu, Q., Peng, C., Wu, N., Yang, G., Zhu, D., Tian, J., Tian, L., Kang, X., He, Y., Gao, Y., & Zhao, X. (2014). Soil methane uptake by grasslands and forests in China. Soil Biology and Biochemistry, 74, 70–81. https://doi.org/10.1016/j.soilbio.2014.02.023
    Consulter sur linkinghub.elsevier.com
  • Jin, J., Xiang, W., Zeng, Y., Ouyang, S., Zhou, X., Hu, Y., Zhao, Z., Chen, L., Lei, P., Deng, X., Wang, H., Liu, S., & Peng, C. (2022). Stand carbon storage and net primary production in China’s subtropical secondary forests are predicted to increase by 2060. Carbon Balance and Management, 17(1), 6. https://doi.org/10.1186/s13021-022-00204-y

    Abstract Background Forest ecosystems play an important role in carbon sequestration, climate change mitigation, and achieving China's target to become carbon (C) neutral by 2060. However, changes in C storage and net primary production (NPP) in natural secondary forests stemming from tree growth and future climate change have not yet been investigated in subtropical areas in China. Here, we used data from 290 inventory plots in four secondary forests [evergreen broad-leaved forest (EBF), deciduous and evergreen broad-leaved mixed forest (DEF), deciduous broad-leaved forest (DBF), and coniferous and broad-leaved mixed forest (CDF)] at different restoration stages and run a hybrid model (TRIPLEX 1.6) to predict changes in stand carbon storage and NPP under two future climate change scenarios (RCP4.5 and RCP8.5). Results The runs of the hybrid model calibrated and validated by using the data from the inventory plots suggest significant increase in the carbon storage by 2060 under the current climate conditions, and even higher increase under the RCP4.5 and RCP8.5 climate change scenarios. In contrast to the carbon storage, the simulated EBF and DEF NPP declines slightly over the period from 2014 to 2060. Conclusions The obtained results lead to conclusion that proper management of China’s subtropical secondary forests could be considered as one of the steps towards achieving China’s target to become carbon neutral by 2060.

    Consulter sur cbmjournal.biomedcentral.com
  • Zhang, K., Peng, C., Zhu, Q., Li, M., Yan, Z., Li, M., Yan, L., Zhang, X., Wang, J., Li, Y., Kang, E., Song, H., & Kang, X. (2022). Estimating natural nitrous oxide emissions from the Qinghai–Tibetan Plateau using a process-based model: Historical spatiotemporal patterns and future trends. Ecological Modelling, 466, 109902. https://doi.org/10.1016/j.ecolmodel.2022.109902
    Consulter sur linkinghub.elsevier.com
  • Ouyang, S., Xiang, W., Gou, M., Chen, L., Lei, P., Xiao, W., Deng, X., Zeng, L., Li, J., Zhang, T., Peng, C., & Forrester, D. I. (2021). Stability in subtropical forests: The role of tree species diversity, stand structure, environmental and socio‐economic conditions. Global Ecology and Biogeography, 30(2), 500–513. https://doi.org/10.1111/geb.13235

    Abstract Aim Tree species diversity can increase the stability of ecosystem productivity by increasing mean productivity and/or reducing the standard deviation in productivity. However, stand structure, environmental and socio‐economic conditions influence plant diversity and might strongly influence the relationships between diversity and stability in natural forest communities. The relative importance of these factors for community stability remains poorly understood in complex (species‐rich) subtropical forests. Location Subtropical area of southern China. Time period 1999–2014. Major taxa studied Forest trees. Methods We conducted bivariate analyses to examine the mechanisms (overyielding and species asynchrony) underlying the effects of diversity on stability. Multiple regression models were then used to determine the relative importance of tree species diversity, stand structure, socio‐economic factors and environmental conditions on stability. Structural equation modelling was used to disentangle how these variables directly and/or indirectly affect forest stability. Results Tree species richness exerted a positive effect on stability through overyielding and species asynchrony, and this effect was stronger in mountainous forests than in hilly forests. Species richness positively affected the mean productivity, whereas species asynchrony negatively affected the variability in productivity, hence increasing forest stability. Structural diversity also had a positive effect, whereas population density had a negative effect on stability. Precipitation variability and slope mainly had indirect influences on stability through their effects on tree species richness. Main conclusions Overall, tree species diversity governed stability; however, stand structure, socio‐economic conditions and environmental conditions also played an important role in shaping stability in these forests. Our work highlights the importance of regulating stand structure and socio‐economic factors in forest management and biodiversity conservation, to maintain and enhance their stability to provide ecosystem services in the face of unprecedented anthropogenic activities and global climate change.

    Consulter sur onlinelibrary.wiley.com
  • Yang, G., Tian, J., Chen, H., Jiang, L., Zhan, W., Hu, J., Zhu, E., Peng, C., Zhu, Q., Zhu, D., He, Y., Li, M., & Dong, F. (2019). Peatland degradation reduces methanogens and methane emissions from surface to deep soils. Ecological Indicators, 106, 105488. https://doi.org/10.1016/j.ecolind.2019.105488
    Consulter sur linkinghub.elsevier.com
  • He, Y., Guan, W., Xue, D., Liu, L., Peng, C., Liao, B., Hu, J., Zhu, Q., Yang, Y., Wang, X., Zhou, G., Wu, Z., & Chen, H. (2019). Comparison of methane emissions among invasive and native mangrove species in Dongzhaigang, Hainan Island. Science of The Total Environment, 697, 133945. https://doi.org/10.1016/j.scitotenv.2019.133945
    Consulter sur linkinghub.elsevier.com
  • Bell, F. W., Dacosta, J., Newmaster, S. G., Mallik, A., Hunt, S., Anand, M., Maloles, J., Peng, C., Parton, J., McLaughlin, J., Winters, J., Wester, M., & Shaw, M. (2017). The NEBIE plot network: Highlights of long-term scientific studies. The Forestry Chronicle, 93(02), 122–137. https://doi.org/10.5558/tfc2017-019

    The NEBIE plot network is a stand-scale, multi-agency research project designed to compare the ecological effects of a range of silvicultural treatments in northern temperate and boreal forest regions of Ontario, Canada. While research on silviculture intensities has been previously conducted, the NEBIE plot network is at a larger scale, and covers a wider range of intensities in a variety of northern temperate and boreal forest types. Details about experimental design, treatment designs and research sites, are presented in a companion paper which is published in this edition of The Forestry Chronicle. The operational scale of treatment plots allow for assessment of a variety of forest values. We used a criteria and indicator approach to organize long-term research studies on the network sites, with the goal of providing scientific findings that would inform forest policy. Pre-treatment, and 2-, 5-, and 10-year post-harvesting data have been collected. These initial data add to existing information on the effects of intensification of silviculture on biological diversity, forest productivity, ecosystem health and vitality, soil and water resources, contribution of enhanced forest management global carbon cycles, and long-term multiple socio-economic benefits of northern forests.

    Consulter sur pubs.cif-ifc.org
  • Wei, H., Peng, C., Yang, B., Song, H., Li, Q., Jiang, L., Wei, G., Wang, K., Wang, H., Liu, S., Liu, X., Chen, D., Li, Y., & Wang, M. (2018). Contrasting Soil Bacterial Community, Diversity, and Function in Two Forests in China. Frontiers in Microbiology, 9, 1693. https://doi.org/10.3389/fmicb.2018.01693
    Consulter sur www.frontiersin.org
  • Yang, H., Detto, M., Liu, S., Yuan, W., Hsieh, C.-I., Wang, X., Chen, R., Chen, H., Peng, C., Jiang, X., Li, Y., Xu, H., Liu, W., & Yang, Q. (2017). Effects of canopy gaps on N 2 O fluxes in a tropical montane rainforest in Hainan of China. Ecological Engineering, 105, 325–334. https://doi.org/10.1016/j.ecoleng.2017.04.042
    Consulter sur linkinghub.elsevier.com
  • Zhan, W., Yang, Z., Liu, J., Chen, H., Yang, G., Zhu, E., Hu, J., Jiang, L., Liu, L., Zhu, D., He, Y., Zhao, C., Xue, D., & Peng, C. (2021). Effect of Grazing Intensities on Soil N2O Emissions from an Alpine Meadow of Zoige Plateau in China. Atmosphere, 12(5), 541. https://doi.org/10.3390/atmos12050541

    The alpine meadow of Zoige Plateau plays a key role in local livestock production of cattle and sheep. However, it remains unclear how animal grazing or its intensity affect nitrous oxide (N2O) emissions, and the main driving factors. A grazing experiment including four grazing intensities (G0, G0.7, G1.2, G1.6 yak ha−1) was conducted between January 2013 and December 2014 to evaluate the soil nitrous oxide (N2O) fluxes under different grazing intensities in an alpine meadow on the eastern Qinghai–Tibet Plateau of China. The N2O fluxes were examined with gas collected by the static chamber method and by chromatographic concentration analysis. N2O emissions in the growing seasons (from May to September) were lower than that in non-growing seasons (from October to April) in 2013, 1.94 ± 0.30 to 3.37 ± 0.56 kg N2O ha−1 yr−1. Annual mean N2O emission rates were calculated as 1.17 ± 0.50 kg N2O ha−1 yr−1 in non-grazing land (G0) and 1.94 ± 0.23 kg N2O ha−1 yr−1 in the grazing land (G0.7, G1.2, and G1.6). The annual mean N2O flux showed no significant differences between grazing treatments in 2013. However, there were significantly greater fluxes from the G0.7 treatment than from the G1.6 treatment in 2014, especially in the growing season. Over the two years, the soil N2O emission rate was significantly negatively correlated with soil water-filled pore space (WFPS) and dissolved organic carbon (DOC) content as well as positively correlated with soil available phosphorus (P). No relationship was observed between soil N2O emission rate and temperature or rainfall. Our results showed that the meadow soils acted as a source of N2O for most periods and turned into a weak sink of N2O later during the sampling period. Our results highlight the importance of proper grazing intensity in reducing N2O emissions from alpine meadow. The interaction between grazing intensity and N2O emissions should be of more concern during future management of pastures in Zoige Plateau.

    Consulter sur www.mdpi.com
  • Wu, H., Xiang, W., Ouyang, S., Forrester, D. I., Zhou, B., Chen, L., Ge, T., Lei, P., Chen, L., Zeng, Y., Song, X., Peñuelas, J., & Peng, C. (2019). Linkage between tree species richness and soil microbial diversity improves phosphorus bioavailability. Functional Ecology, 33(8), 1549–1560. https://doi.org/10.1111/1365-2435.13355

    Abstract Increased availability of soil phosphorus (P) has recently been recognised as an underlying driving factor for the positive relationship between plant diversity and ecosystem function. The effects of plant diversity on the bioavailable forms of P involved in biologically mediated rhizospheric processes and how the link between plant and soil microbial diversity facilitates soil P bioavailability, however, remain poorly understood. This study quantified four forms of bioavailable P (CaCl 2 ‐P, citric‐P, enzyme‐P and HCl‐P) in mature subtropical forests using a novel biologically based approach, which emulates how rhizospheric processes influence the release and supply of available P. Soil microbial diversity was measured by Illumina high‐throughput sequencing. Our results suggest that tree species richness significantly affects soil microbial diversity ( p  < 0.05), increases litter decomposition, fine‐root biomass and length and soil organic carbon and thus increases the four forms of bioavailable P. A structural equation model that links plants, soil microbes and P forms indicated that soil bacterial and fungal diversity play dominant roles in mediating the effects of tree species richness on soil P bioavailability. An increase in the biodiversity of plants, soil bacteria and fungi could maintain soil P bioavailability and alleviate soil P limitations. Our results imply that biodiversity strengthens plant and soil feedback and increases P recycling. A plain language summary is available for this article.

    Consulter sur besjournals.onlinelibrary.wiley.com
  • Zhu, Q., Chen, H., Peng, C., Liu, J., Piao, S., He, J.-S., Wang, S., Zhao, X., Zhang, J., Fang, X., Jin, J., Yang, Q.-E., Ren, L., & Wang, Y. (2023). An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau. Nature Communications, 14(1), 6406. https://doi.org/10.1038/s41467-023-42099-4

    Abstract Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO 2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

    Consulter sur www.nature.com
  • Chen, H., Yin, K., Wang, H., Zhong, S., Wu, N., Shi, F., Zhu, D., Zhu, Q., Wang, W., Ma, Z., Fang, X., Li, W., Zhao, P., & Peng, C. (2011). Detecting One-Hundred-Year Environmental Changes in Western China Using Seven-Year Repeat Photography. PLoS ONE, 6(9), e25008. https://doi.org/10.1371/journal.pone.0025008
    Consulter sur dx.plos.org
  • Ouyang, S., Xiang, W., Wang, X., Xiao, W., Chen, L., Li, S., Sun, H., Deng, X., Forrester, D. I., Zeng, L., Lei, P., Lei, X., Gou, M., & Peng, C. (2019). Effects of stand age, richness and density on productivity in subtropical forests in China. Journal of Ecology, 107(5), 2266–2277. https://doi.org/10.1111/1365-2745.13194

    Abstract Forest productivity may be determined not only by biodiversity but also by environmental factors and stand structure attributes. However, the relative importance of these factors in determining productivity is still controversial for subtropical forests. Based on a large dataset from 600 permanent forest inventory plots across subtropical China, we examined the relationship between biodiversity and forest productivity and tested whether stand structural attributes (stand density in terms of trees per ha, age and tree size) and environmental factors (climate and site conditions) had larger effects on productivity. Furthermore, we quantified the relative importance of environmental factors, stand structure and diversity in determining forest productivity. Diversity, together with stand structure and site conditions, regulated the variability in forest productivity. The relationship between diversity and forest productivity did not vary along environmental gradients. Stand density and age were more important modulators of forest productivity than diversity. Synthesis . Diversity had significant and positive effects on productivity in species‐rich subtropical forests, but the effects of stand density and age were also important. Our work highlights that while biodiversity conservation is often important, the regulation of stand structure can be even more important to maintain high productivity in subtropical forests.

    Consulter sur besjournals.onlinelibrary.wiley.com
  • Bai, J., Zong, M., Li, S., Li, H., Duan, C., Feng, Y., Peng, C., Zhang, X., Sun, D., Lin, C., Shi, Y., Zheng, G., Wang, H., Liu, D., Li, F., & Huang, W. (2021). Nitrogen, water content, phosphorus and active iron jointly regulate soil organic carbon in tropical acid red soil forest. European Journal of Soil Science, 72(1), 446–459. https://doi.org/10.1111/ejss.12966

    Abstract Increasing forest soil organic carbon (SOC) storage is important for reducing carbon dioxide (CO 2 ) emissions from terrestrial ecosystems and mitigating global climate change. Although the effects of altitude, temperature and rainfall on organic carbon have been studied extensively, it is difficult to increase SOC storage by changing these factors in actual forest management. This study determined the SOC, soil physical and chemical properties, nutrient elements, heavy metal elements, soil minerals and microbial biomass in the 0–140‐cm soil layer of the monsoon broad‐leaved forest in the acid red soil region of southwestern China by stratification. We tried to identify the soil factors affecting the SOC storage of the forest in the acid red soil region and determine the weights of the factors affecting the SOC, with the aim of improving the SOC retention capacity in forest management by changing the main soil factors affecting SOC storage. The results showed that the soil factors affecting the forest SOC storage in this area are total nitrogen (N, 22.7%) > soil water content (19.9%) > active iron (including poorly crystalline iron, Fe o , 15.5%) > pH (9.5%) > phosphorus (P, 9.4%) > aluminium (Al, 8.9%) > silicon (Si, 7.1%) > sulphur (S, 6.8%). Of these factors, N, the water content, Fe o , and P are practical factors for forest management, whereas the pH, Al, Si and S are not. SOC was significantly positively correlated with the soil N concentration, water content, active iron content and P concentration ( p  < .05). In acidic red soil areas, with active iron as the highlight, N, soil water content, phosphorus and active iron jointly regulate the forest SOC storage capacity. Consequently, in actual forest management, any measures to promote soil N and water content and to activate inactive iron can enhance the storage of SOC, as appropriate input of N and P fertiliser and irrigation in dry years and the dry season. Highlights The soil environmental factors affecting SOC storage in forest soil are quantified Activation of inactive iron helps SOC storage in forest soil Irrigation and N and P input are effective for helping SOC storage in forest soil N, WC, P and Fe o jointly regulate SOC in tropical acid red soil forest

    Consulter sur bsssjournals.onlinelibrary.wiley.com
  • Chang, J., Ge, Y., Wu, Z., Du, Y., Pan, K., Yang, G., Ren, Y., Heino, M. P., Mao, F., Cheong, K. H., Qu, Z., Fan, X., Min, Y., Peng, C., & Meyerson, L. A. (2021). Modern cities modelled as “super‐cells” rather than multicellular organisms: Implications for industry, goods and services. BioEssays, 43(7), 2100041. https://doi.org/10.1002/bies.202100041

    Abstract The structure and “metabolism” (movement and conversion of goods and energy) of urban areas has caused cities to be identified as “super‐organisms”, placed between ecosystems and the biosphere, in the hierarchy of living systems. Yet most such analogies are weak, and render the super‐organism model ineffective for sustainable development of cities. Via a cluster analysis of 15 shared traits of the hierarchical living system, we found that industrialized cities are more similar to eukaryotic cells than to multicellular organisms; enclosed systems, such as factories and greenhouses, paralleling organelles in eukaryotic cells. We further developed a “super‐cell” industrialized city model: a “eukarcity” with citynucleus (urban area) as a regulating centre, and organaras (enclosed systems, which provide the majority of goods and services) as the functional components, and cityplasm (natural ecosystems and farmlands) as the matrix. This model may improve the vitality and sustainability of cities through planning and management.

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