GLORIA

GEOMAR Library Ocean Research Information Access

Ihre E-Mail wurde erfolgreich gesendet. Bitte prüfen Sie Ihren Maileingang.

Leider ist ein Fehler beim E-Mail-Versand aufgetreten. Bitte versuchen Sie es erneut.

Vorgang fortführen?

Exportieren
Filter
  • MDPI AG  (6)
Materialart
Verlag/Herausgeber
  • MDPI AG  (6)
Sprache
Erscheinungszeitraum
  • 1
    In: Microorganisms, MDPI AG, Vol. 11, No. 5 ( 2023-04-25), p. 1114-
    Kurzfassung: The establishment of artificial grassland is crucial in restoring degraded grassland and resolving the forage–livestock conflict, and the application of organic fertilizer and complementary seeding of grass–legume mixture are effective methods to enhance grass growth in practice. However, its mechanism behind the underground is largely unclear. Here, by utilizing organic fertilizer in the alpine region of the Qinghai–Tibet Plateau, this study assessed the potential of grass–legume mixtures with and without the inoculation of Rhizobium for the restoration of degraded grassland. The results demonstrated that the application of organic fertilizer can increase the forage yield and soil nutrient contents of degraded grassland, and they were 0.59 times and 0.28 times higher than that of the control check (CK), respectively. The community composition and structure of soil bacteria and fungi were also changed by applying organic fertilizer. Based on this, the grass–legume mixture inoculated with Rhizobium can further increase the contribution of organic fertilizer to soil nutrients and thus enhance the restoration effects for degraded artificial grassland. Moreover, the application of organic fertilizer significantly increased the colonization of gramineous plant by native mycorrhizal fungi, which was ~1.5–2.0 times higher than CK. This study offers a basis for the application of organic fertilizer and grass–legume mixture in the ecological restoration of degraded grassland.
    Materialart: Online-Ressource
    ISSN: 2076-2607
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2720891-6
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    In: Microorganisms, MDPI AG, Vol. 10, No. 6 ( 2022-06-02), p. 1148-
    Kurzfassung: The effects of organic fertilizer application on the soil microbial community in grassland systems have been extensively studied. However, the effects of organic fertilizers on the structure of rhizosphere microbial communities are still limited. In this study, the diversity and composition of rhizosphere microbial communities of a gramineous grass Elymus nutans under organic fertilizer treatment were studied in an artificial pasture on Qinghai–Tibet Plateau. After a growing season, the application of organic fertilizer not only increased the height and biomass of Elymus nutans, but also changed the rhizosphere microbial compositions. In particular, organic fertilizer increased the diversity of rhizosphere bacterial community and inhibited the growth of pathogenic bacteria such as Acinetobacter, but the opposite trend was observed for the diversity of fungal community. The assembly process of fungal community was changed from a stochastic process to a deterministic process, indicating that selection was strengthened. Additionally, both the infection rate of arbuscular mycorrhizal fungi (AMF) toward host plants and the development of AMF-related structures were significantly increased after the application of organic fertilizer. Our study demonstrated that the addition of organic fertilizer to artificial pasture could improve the growth of grass through the alteration of the rhizosphere microbial communities. Organic fertilizer had a greater selectivity for the bacterial and the fungal communities that enhanced the niche filtration in this community, further benefiting the yield of forages.
    Materialart: Online-Ressource
    ISSN: 2076-2607
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2720891-6
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 3
    Online-Ressource
    Online-Ressource
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 19 ( 2022-10-06), p. 4966-
    In: Remote Sensing, MDPI AG, Vol. 14, No. 19 ( 2022-10-06), p. 4966-
    Kurzfassung: High-precision rainfall information is of great importance for the improvement of the accuracy of numerical weather prediction and the monitoring of floods and mudslides that affect human life. With the rapid development of satellite constellation networks, there is great potential for reconstructing high-precision rainfall fields in large areas by using widely distributed Earth–space link (ESL) networks. In this paper, we have carried out research on reconstructing high-precision rainfall fields using an ESL network with the compressed sensing (CS) method in the case of a sparse distribution of the ESLs. Firstly, ESL networks with different densities are designed using the K-means clustering algorithm. The real rainfall fields are then reconstructed using the designed ESL networks with CS, and the reconstructed results are compared with that of the inverse distance weighting (IDW) algorithm. The results show that the root mean square error (RMSE) and correlation coefficient (CC) of the reconstructed rainfall fields using the ESL network with CS are lower than 0.15 mm/h and higher than 0.999, respectively, when the density is 0.05 links per square kilometer, indicating that the ESL network with CS is capable of reconstructing the high-precision rainfall fields under sparse sampling. Additionally, the performance of reconstructing the rainfall fields using the ESL networks with CS is superior compared to the reconstructed results of the IDW algorithm.
    Materialart: Online-Ressource
    ISSN: 2072-4292
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2513863-7
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 4
    In: Agronomy, MDPI AG, Vol. 13, No. 2 ( 2023-02-07), p. 481-
    Kurzfassung: It has been widely recognized that organic fertilizer (OF) application under monoculture and continuous cropping can change the microbial community and increase forage biomass in the Qinghai–Tibet Plateau. However, as a commonly used grassland planting pattern, the way in which grass–legume mixtures respond to OF application remains unclear. To clarify application effects of organic fertilizer in the grass–legume mixtures, we conducted a field experiment at the Qinghai–Tibet Plateau and collected the rhizospheric and bulk soils to reveal their microbial community by using high-throughput sequencing and molecular ecological networks. It was found that OF application changed the microbial community and increased the forage biomass under monoculture. However, in grass–legume mixtures, we found that OF application did not promote the increase of forage (Gramineae) biomass (Student t-test: p 〉 0.05). By analyzing both prokaryote and fungal communities, it was found that OF application had a greater impact on bulk soil microorganisms than on those of the rhizosphere in grass–legume mixtures. Co-occurrence network analysis showed that the rhizosphere and bulk soil networks of grass–legume mixtures were significantly more vulnerable under OF treatment (vulnerability of prokaryotes in grass: 0.1222; vulnerability of prokaryotes in legumes: 0.1730; fungal vulnerability in grass: 0.0116; fungal vulnerability in legumes: 0.0223) than non-OF treatment (vulnerability of prokaryotes in grass: 0.1015; vulnerability of prokaryotes in legumes: 0.1337; fungal vulnerability in grass: 0.0046; fungal vulnerability in legumes: 0.0126), which indicated that OF application did not provide favorable conditions for microbial interactions in grass–legume mixtures. In addition, structural equation modeling showed that OF application had some significant negative impacts on soil physicochemical properties and the robustness of the prokaryote community. The robustness of fungi had a significant negative (p 〈 0.001) impact on forage biomass, but OF application had no significant (p 〉 0.05) direct impact on the forage biomass, which indicated that the OF did not promote forage biomass in grass–legume mixtures. These results suggest that the application of organic fertilizer is unnecessary for grass–legume mixtures, because it does not promote the interactions between rhizospheric microbes and forage.
    Materialart: Online-Ressource
    ISSN: 2073-4395
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2607043-1
    SSG: 23
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 5
    In: Agronomy, MDPI AG, Vol. 12, No. 7 ( 2022-07-21), p. 1722-
    Kurzfassung: Chemical fertilizers are gradually being replaced with new biological fertilizers, which can improve the soil and soil microorganisms. In this experiment, leguminous forage (Medicago sativa cv. Beilin 201) was used as the research object. By measuring alfalfa root systems and soil properties and using high-throughput sequencing technology, we investigated the effect of biological (rhizobial) fertilizer at different concentrations on soil fertility and alfalfa rhizosphere microbiota in alpine grasslands. The results demonstrated that the treatment with biofertilizer significantly reduced total nitrogen (TN) and total organic carbon (TOC) content in soils, increased root densities, and significantly increased the number of root nodules in alfalfa. There were differences in the response of rhizosphere microorganisms to different concentrations of biofertilizer, and the treatment with biofertilizer led to pronounced changes in the microbial community structure. The abundance of beneficial bacteria such as Rhizobium, Arthrobacter, and Pseudomonas was significantly increased. The Pearson correlation analysis showed that soil moisture and soil conductivity were significantly positively correlated with the observed richness of rhizosphere microbiota (p 〈 0.05). Meanwhile, Actinobacteria showed a significantly positive correlation with nitrate, TOC, and TN (p 〈 0.01). These results indicated that biofertilizers enhanced soil fertility and altered the rhizosphere microbiota of alfalfa in alpine grassland.
    Materialart: Online-Ressource
    ISSN: 2073-4395
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2607043-1
    SSG: 23
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 6
    Online-Ressource
    Online-Ressource
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 9 ( 2022-05-06), p. 2220-
    In: Remote Sensing, MDPI AG, Vol. 14, No. 9 ( 2022-05-06), p. 2220-
    Kurzfassung: High-precision retrieval of rainfall over large areas is of great importance for the research of atmospheric detection and the social life. With the rapid development of communication satellite constellations and 5G communication networks, the use of widely distributed networks of earth–space links (ESLs) and horizontal microwave links (HMLs) to retrieve rainfall over large areas has great potential for obtaining high-precision rainfall fields and complementing traditional instruments of rainfall measurement. In this paper, we carry out the research of combining multiple ESLs with HMLs to retrieve rainfall fields. Firstly, a rainfall detection network for retrieving rainfall fields is built based on the atmospheric propagation model of ESL and HML. Then, the ordinary Kriging interpolation (OK) and radial basis function (RBF) neural network are applied to the reconstruction of rainfall fields. Finally, the performance of the joint network of ESLs and HMLs to retrieve rainfall fields in the area is validated. The results show that the joint network of ESLs and HMLs based on OK algorithm and RBF neural network is capable of retrieving the distribution of rain rates in different rain cells with high accuracy, and the root mean square error (RMSE) of retrieving the rain rates of real rainfall fields is lower than 0.56 mm/h, and the correlation coefficient (CC) is higher than 0.996. In addition, the CC for retrieving stratiform rainfall and convective rainfall by the joint network of ESLs and HMLs is higher than 0.949, indicating that the characteristics of the two different types of rainfall events can be accurately monitored.
    Materialart: Online-Ressource
    ISSN: 2072-4292
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2513863-7
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
Schließen ⊗
Diese Webseite nutzt Cookies und das Analyse-Tool Matomo. Weitere Informationen finden Sie hier...