Abteilung Biogeochemie der Agrarökosysteme

[["dc.bibliographiccitation.artnumber","806146"],["dc.bibliographiccitation.journal","Frontiers in Agronomy"],["dc.bibliographiccitation.volume","3"],["dc.contributor.affiliation","Nazari, Meisam; 1Division of Biogeochemistry of Agroecosystems, Georg-August University of Göttingen, Göttingen, Germany"],["dc.contributor.affiliation","Mirgol, Behnam; 2Center for Agroecology, Water and Resilience, Coventry University, Coventry, United Kingdom"],["dc.contributor.affiliation","Salehi, Hamid; 3Department of Water Engineering, Tarbiat Modares University, Tehran, Iran"],["dc.contributor.author","Nazari, Meisam"],["dc.contributor.author","Mirgol, Behnam"],["dc.contributor.author","Salehi, Hamid"],["dc.date.accessioned","2022-07-13T07:38:01Z"],["dc.date.available","2022-07-13T07:38:01Z"],["dc.date.issued","2021"],["dc.date.updated","2022-09-04T22:36:08Z"],["dc.description.abstract","This is the first large-scale study to assess the climate change impact on the grain yield of rainfed wheat for three provinces of contrasting climatic conditions (temperate, cold semi-arid, and hot arid) in Iran. Five integrative climate change scenarios including +0.5°C temperature plus−5% precipitation, +1°C plus−10%, +1.5°C plus−15%, +2°C plus−20%, and +2.5°C plus−25% were used and evaluated. Nitrogen fertilizer and shifting planting dates were tested for their suitability as adaptive strategies for rainfed wheat against the changing climate. The climate change scenarios reduced the grain yield by −6.9 to −44.8% in the temperate province Mazandaran and by −7.3 to −54.4% in the hot arid province Khuzestan but increased it by +16.7% in the cold semi-arid province Eastern Azarbaijan. The additional application of +15, +30, +45, and +60 kg ha−1 nitrogen fertilizer as urea at sowing could not, in most cases, compensate for the grain yield reductions under the climate change scenarios. Instead, late planting dates in November, December, and January enhanced the grain yield by +6 to +70.6% in Mazandaran under all climate change scenarios and by +94 to +271% in Khuzestan under all climate change scenarios except under the scenario +2.5°C temperature plus−25% precipitation which led to a grain yield reduction of −85.5%. It is concluded that rainfed wheat production in regions with cold climates can benefit from the climate change, but it can be impaired in temperate regions and especially in vulnerable hot regions like Khuzestan. Shifting planting date can be regarded as an efficient yield-compensating and environmentally friendly adaptive strategy of rainfed wheat against the climate change in temperate and hot arid regions."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.3389/fagro.2021.806146"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112481"],["dc.language.iso","en"],["dc.relation.eissn","2673-3218"],["dc.relation.issn","2673-3218"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Climate Change Impact Assessment and Adaptation Strategies for Rainfed Wheat in Contrasting Climatic Regions of Iran"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Frontiers in Forests and Global Change"],["dc.bibliographiccitation.volume","4"],["dc.contributor.affiliation","Nazari, Meisam; 1Division of Biogeochemistry of Agroecosystems, Georg-August University of Göttingen, Göttingen, Germany"],["dc.contributor.affiliation","Eteghadipour, Mohammad; 2Department of Water and Soil, Faculty of Agricultural Engineering, Shahrood University of Technology, Shahrood, Iran"],["dc.contributor.affiliation","Zarebanadkouki, Mohsen; 3Chair of Soil Physics, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, Bayreuth, Germany"],["dc.contributor.affiliation","Ghorbani, Mohammad; 4Department of Agroecosystems, Faculty of Agriculture, University of South Bohemia, České Budějovice, Czechia"],["dc.contributor.affiliation","Dippold, Michaela A.; 1Division of Biogeochemistry of Agroecosystems, Georg-August University of Göttingen, Göttingen, Germany"],["dc.contributor.affiliation","Bilyera, Nataliya; 5Department of Soil and Plant Microbiome, Institute of Phytopathology, Christian-Albrechts-University of Kiel, Kiel, Germany"],["dc.contributor.affiliation","Zamanian, Kazem; 7Soil Science of Temperate Ecosystems, University of Göttingen, Göttingen, Germany"],["dc.contributor.author","Eteghadipour, Mohammad"],["dc.contributor.author","Zarebanadkouki, Mohsen"],["dc.contributor.author","Ghorbani, Mohammad"],["dc.contributor.author","Dippold, Michaela A."],["dc.contributor.author","Bilyera, Nataliya"],["dc.contributor.author","Zamanian, Kazem"],["dc.contributor.author","Nazari, Meisam"],["dc.date.accessioned","2022-01-11T14:06:13Z"],["dc.date.available","2022-01-11T14:06:13Z"],["dc.date.issued","2021"],["dc.date.updated","2022-09-04T22:22:13Z"],["dc.description.abstract","Soil compaction associated with mechanized wood harvesting can long-lastingly disturb forest soils, ecosystem function, and productivity. Sustainable forest management requires precise and deep knowledge of logging operation impacts on forest soils, which can be attained by meta-analysis studies covering representative forest datasets. We performed a meta-analysis on the impact of logging-associated compaction on forest soils microbial biomass carbon (MBC), bulk density, total porosity, and saturated hydraulic conductivity (K sat ) affected by two management factors (machine weight and passage frequency), two soil factors (texture and depth), and the time passed since the compaction event. Compaction significantly decreased soil MBC by −29.5% only in subsoils (>30 cm). Overall, compaction increased soil bulk density by 8.9% and reduced total porosity and K sat by −10.1 and −40.2%, respectively. The most striking finding of this meta-analysis is that the greatest disturbance to soil bulk density, total porosity, and K sat occurs after very frequent (>20) machine passages. This contradicts the existing claims that most damage to forest soils happens after a few machine passages. Furthermore, the analyzed physical variables did not recover to the normal level within a period of 3–6 years. Thus, altering these physical properties can disturb forest ecosystem function and productivity, because they play important roles in water and air supply as well as in biogeochemical cycling in forest ecosystems. To minimize the impact, we recommend the selection of suitable logging machines and decreasing the frequency of machine passages as well as logging out of rainy seasons especially in clayey soils. It is also very important to minimize total skid trail coverage for sustainable forest management."],["dc.description.abstract","Soil compaction associated with mechanized wood harvesting can long-lastingly disturb forest soils, ecosystem function, and productivity. Sustainable forest management requires precise and deep knowledge of logging operation impacts on forest soils, which can be attained by meta-analysis studies covering representative forest datasets. We performed a meta-analysis on the impact of logging-associated compaction on forest soils microbial biomass carbon (MBC), bulk density, total porosity, and saturated hydraulic conductivity (K sat ) affected by two management factors (machine weight and passage frequency), two soil factors (texture and depth), and the time passed since the compaction event. Compaction significantly decreased soil MBC by −29.5% only in subsoils (>30 cm). Overall, compaction increased soil bulk density by 8.9% and reduced total porosity and K sat by −10.1 and −40.2%, respectively. The most striking finding of this meta-analysis is that the greatest disturbance to soil bulk density, total porosity, and K sat occurs after very frequent (>20) machine passages. This contradicts the existing claims that most damage to forest soils happens after a few machine passages. Furthermore, the analyzed physical variables did not recover to the normal level within a period of 3–6 years. Thus, altering these physical properties can disturb forest ecosystem function and productivity, because they play important roles in water and air supply as well as in biogeochemical cycling in forest ecosystems. To minimize the impact, we recommend the selection of suitable logging machines and decreasing the frequency of machine passages as well as logging out of rainy seasons especially in clayey soils. It is also very important to minimize total skid trail coverage for sustainable forest management."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.3389/ffgc.2021.780074"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/97857"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-507"],["dc.relation.eissn","2624-893X"],["dc.relation.orgunit","Department für Nutzpflanzenwissenschaften"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Impacts of Logging-Associated Compaction on Forest Soils: A Meta-Analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","795287"],["dc.bibliographiccitation.journal","Frontiers in Environmental Science"],["dc.bibliographiccitation.volume","9"],["dc.contributor.affiliation","Salehi, Hamid; \r\n\r\n1\r\nDepartment of Water Engineering, Tarbiat Modares University, Tehran, Iran"],["dc.contributor.affiliation","Shamsoddini, Ali; \r\n\r\n2\r\nDepartment of Remote Sensing and GIS, Tarbiat Modares University, Tehran, Iran"],["dc.contributor.affiliation","Mirlatifi, Seyed Majid; \r\n\r\n1\r\nDepartment of Water Engineering, Tarbiat Modares University, Tehran, Iran"],["dc.contributor.affiliation","Mirgol, Behnam; \r\n\r\n3\r\nCenter for Agroecology, Water and Resilience, Coventry University, Coventry, United Kingdom"],["dc.contributor.affiliation","Nazari, Meisam; \r\n\r\n4\r\nDivision of Biogeochemistry of Agroecosystems, Georg-August University of Göttingen, Göttingen, Germany"],["dc.contributor.author","Salehi, Hamid"],["dc.contributor.author","Shamsoddini, Ali"],["dc.contributor.author","Mirlatifi, Seyed Majid"],["dc.contributor.author","Mirgol, Behnam"],["dc.contributor.author","Nazari, Meisam"],["dc.date.accessioned","2022-02-01T10:31:38Z"],["dc.date.available","2022-02-01T10:31:38Z"],["dc.date.issued","2021"],["dc.date.updated","2022-02-09T13:20:15Z"],["dc.description.abstract","Producing daily actual evapotranspiration (ET a ) maps with high spatial resolution has always been a challenge for remote sensing research. This study assessed the feasibility of producing daily ET a maps with a high spatial resolution (30 m) for the sugarcane farmlands of Amir Kabir Sugarcane Agro-industry (Khuzestan, Iran) using three different scenarios. In the first scenario, the reflectance bands of Landsat 8 were predicted from the moderate resolution imaging spectroradiometer (MODIS) imagery using the spatial and temporal adaptive reflectance fusion model (STARFM) algorithm. Also, the thermal bands of Landsat 8 were predicted by the spatiotemporal adaptive data fusion algorithm for temperature mapping (SADFAT). Then, ET a amounts were calculated employing such bands and the surface energy balance algorithm for land (SEBAL). In the second scenario, the input data needed by SEBAL were downscaled using the MODIS images and different methods. Then, using the downscaled data and SEBAL, daily ET a amounts with a spatial resolution of 30 m were calculated. In the third scenario, ET a data acquired by MODIS were downscaled to the scale of Landsat 8. In the second and third scenarios, downscaling of the data was carried out by the ratio, regression, and neural networks methods with two different approaches. In the first approach, the Landsat image on day 1 and the relationship between the two MODIS images on day 1 and the other days were used. In the second approach, the simulated image on the previous day and the relationship between the two consecutive images of MODIS were used. Comparing the simulated ET a amounts with the ET a amounts derived from Landsat 8, the first scenario had the best result with an RMSE (root mean square error) of 0.68 mm day −1 . The neural networks method used in the third scenario with the second approach had the worst result with an RMSE of 2.25 mm day −1 , which was however a better result than the ET a amounts derived from MODIS with an RMSE of 3.19 mm day −1 . The method developed in this study offers an efficient and inexpensive way to produce daily ET a maps with a high spatial resolution. Furthermore, we suggest that STARFM and SADFAT algorithms have acceptable accuracies in the simulation of reflectance and thermal bands of Landsat 8 images for homogeneous areas."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.3389/fenvs.2021.795287"],["dc.identifier.eissn","2296-665X"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/98911"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-517"],["dc.relation.eissn","2296-665X"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Spatial and Temporal Resolution Improvement of Actual Evapotranspiration Maps Using Landsat and MODIS Data Fusion"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Plant and Soil"],["dc.contributor.author","Nazari, Meisam"],["dc.contributor.author","Bilyera, Nataliya"],["dc.contributor.author","Banfield, Callum C."],["dc.contributor.author","Mason-Jones, Kyle"],["dc.contributor.author","Zarebanadkouki, Mohsen"],["dc.contributor.author","Munene, Rosepiah"],["dc.contributor.author","Dippold, Michaela A."],["dc.date.accessioned","2022-10-04T10:21:19Z"],["dc.date.available","2022-10-04T10:21:19Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract\n \n Aims\n This study investigated the influence of climate and soil on the exudation rate and polysaccharide composition of aerial nodal root mucilage from drought-resistant and drought-susceptible maize varieties.\n \n \n Methods\n Two maize varieties were grown in two different soils (sandy-clay loam Acrisol and loam Luvisol) under simulated climatic conditions of their agroecological zones of origin in Kenya and Germany. The exudation rate of mucilage from the aerial nodal roots was quantified as dry weight per root tip per day and the mucilage was characterized for its polysaccharide composition.\n \n \n Results\n On average, the mucilage exudation rate was 35.8% higher under the Kenyan semi-arid tropical than under the German humid temperate climatic conditions. However, cultivation in the loam Luvisol soil from Germany led to 73.7% higher mucilage exudation rate than cultivation in the sandy-clay loam Acrisol soil from Kenya, plausibly due to its higher microbial biomass and nutrient availability. The drought-resistant Kenyan maize variety exuded 58.2% more mucilage than the drought-susceptible German variety. On average, mucilage polysaccharides were composed of 40.6% galactose, 26.2% fucose, 13.1% mannose, 11% arabinose, 3.5% glucose, 3.2% xylose, 1.3% glucuronic acid, and 1% an unknown uronic acid. Overall, significantly higher proportions of the uronic acids were found in the mucilage of the plants grown in the Kenyan sandy-clay loam soil and under the Kenyan semi-arid tropical climatic conditions.\n \n \n Conclusions\n Maize is able to enhance its mucilage exudation rate under warm climatic conditions and in soils of high microbial activity to mitigate water stress and support the rhizosphere microbiome, respectively.\n \n \n Graphical abstract"],["dc.description.sponsorship"," Deutsche Bundesstiftung Umwelt http://dx.doi.org/10.13039/100007636"],["dc.description.sponsorship"," Robert Bosch Stiftung http://dx.doi.org/10.13039/501100001646"],["dc.description.sponsorship"," Georg-August-Universität Göttingen 501100003385"],["dc.identifier.doi","10.1007/s11104-022-05669-x"],["dc.identifier.pii","5669"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/114379"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-600"],["dc.relation.eissn","1573-5036"],["dc.relation.issn","0032-079X"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Soil, climate, and variety impact on quantity and quality of maize root mucilage exudation"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]