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Propastin, Pavel A.
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Propastin, Pavel A.
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Propastin, Pavel A.
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Propastin, P. A.
Propastin, Pavel
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2012Journal Article [["dc.bibliographiccitation.artnumber","582159"],["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.journal","Journal of Sensors"],["dc.bibliographiccitation.lastpage","11"],["dc.bibliographiccitation.volume","2012"],["dc.contributor.author","Kappas, Martin W."],["dc.contributor.author","Propastin, Pavel A."],["dc.date.accessioned","2018-11-07T09:16:17Z"],["dc.date.accessioned","2020-05-08T09:43:33Z"],["dc.date.available","2018-11-07T09:16:17Z"],["dc.date.available","2020-05-08T09:43:33Z"],["dc.date.issued","2012"],["dc.description.abstract","Leaf area index (LAI) is a key biophysical variable for environmental process modelling. Remotely sensed data have become the primary source for estimation of LAI at the scales from local to global. A summary of existing LAI data sets and a discussion of their appropriateness for the formerly Soviet Central Asia, especially Kazakhstan, which is known for its huge grassland area (about 2 million km(2)), are valuable for environmental modelling in this region. The paper gives a brief review of existing global LAI products, such as AVHRR LAI, MODIS LAI, and SPOT-VEGETATION LAI, and shows that validation of these products in Kazakhstan as well as in other countries of the formerly Soviet Central Asia has not been carried out yet. Apart from the global LAI products, there are just a few data sets retrieved by remote sensing methods at subregional and regional scales in Kazakhstan. More research activities are needed to focus on the validation of the available global LAI products over the formerly Soviet Central Asia and developing new LAI data sets suitable for application in environmental modelling at different scales in this region."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2011"],["dc.identifier.doi","10.1155/2012/582159"],["dc.identifier.isi","000208865000030"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7593"],["dc.identifier.scopus","2-s2.0-84861049895"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/27904"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/64966"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-84861049895&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.eissn","1687-7268"],["dc.relation.issn","1687-725X"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Review of Available Products of Leaf Area Index and Their Suitability over the Formerly Soviet Central Asia"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI WOS2009Journal Article [["dc.bibliographiccitation.firstpage","159"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.lastpage","183"],["dc.bibliographiccitation.volume","1"],["dc.contributor.author","Propastin, Pavel A."],["dc.contributor.author","Kappas, Martin"],["dc.date.accessioned","2018-11-07T11:25:29Z"],["dc.date.accessioned","2020-05-08T08:40:17Z"],["dc.date.available","2018-11-07T11:25:29Z"],["dc.date.available","2020-05-08T08:40:17Z"],["dc.date.issued","2009"],["dc.description.abstract","Carbon sequestration was estimated in a semi-arid grassland region in Central Kazakhstan using an approach that integrates remote sensing, field measurements and meteorological data. Carbon fluxes for each pixel of 1 x 1 km were calculated as a product of photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (fPAR), the light use efficiency (LUE) and ecosystem respiration (R-e). The PAR is obtained from a mathematical model incorporating Earth-Sun distance, solar inclination, solar elevation angle, geographical position and cloudiness information of localities. The fPAR was measured in field using hemispherical photography and was extrapolated to each pixel by combination with the Normalized Difference Vegetation Index (NDVI) obtained by the Vegetation instrument on board the Satellite Pour l'Observation de la Terra (SPOT) satellite. Gross Primary Production (GPP) of the aboveground and belowground vegetation of 14 sites along a 230 km west-east transect within the study region were determined at the peak of growing season in different land cover types and linearly related to the amount of PAR absorbed by vegetation (APAR). The product of this relationship is LUE = 0.61 and 0.97 g C/MJ APAR for short grassland and steppe, respectively. The R-e is estimated using complex models driven by climatic data. Growing season carbon sequestration was calculated for the modelling year of 2004. Overall, the short grassland was a net carbon sink, whereas the steppe was carbon neutral. The evaluation of the modelled carbon sequestration against independent reference data sets proved high accuracy of the estimations."],["dc.identifier.doi","10.3390/rs1030159"],["dc.identifier.isi","000208400500003"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8263"],["dc.identifier.scopus","2-s2.0-79952038615"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/56630"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/64956"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-79952038615&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","2072-4292"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Modeling Net Ecosystem Exchange for Grassland in Central Kazakhstan by Combining Remote Sensing and Field Data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI WOS2012Journal Article [["dc.bibliographiccitation.firstpage","220"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.lastpage","246"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Propastin, Pavel A."],["dc.contributor.author","Kappas, Martin"],["dc.date.accessioned","2018-11-07T09:15:01Z"],["dc.date.accessioned","2020-05-11T09:20:50Z"],["dc.date.available","2018-11-07T09:15:01Z"],["dc.date.available","2020-05-11T09:20:50Z"],["dc.date.issued","2012"],["dc.description.abstract","A new multi-decade national-wide coarse-resolution data set of leaf area index (LAI) over the Republic of Kazakhstan has been developed based on data from the Advanced Very High Resolution Radiometer (AVHRR) and in situ measurements of vegetation structure. The Kazakhstan-wide LAI product has been retrieved using an algorithm based on a physical radiative transfer model establishing a relationship between LAI and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation at the per-pixel scale. The results revealed high consistencies between the produced AVHRR LAI data set and ground truth information and the 30-m resolution Landsat ETM+ LAI estimated using the similar algorithm. Differences in LAI between the AVHRR-based product and the Landsat ETM+-based product are lower than 0.4 LAI units in terms of RMSE. The produced Kazakhstan-wide LAI was also compared with the global 8-km AVHRR LAI (LAI_PAL_BU_V3) and 1-km MODIS LAI (MOD15A2 LAI) products. Results show remarkable consistency of the spatial distribution and temporal dynamics between the new LAI product and both examined global LAI products. However, the results also revealed several discrepancies in LAI estimates when comparing the global and the Kazakhstan-wide products. The discrepancies in LAI estimates were outlined and discussed."],["dc.identifier.doi","10.3390/rs4010220"],["dc.identifier.isi","000306755900012"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8252"],["dc.identifier.scopus","2-s2.0-84857933030"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/64981"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/27571"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-84857933030&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","2072-4292"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Retrieval of Coarse-Resolution Leaf Area Index over the Republic of Kazakhstan Using NOAA AVHRR Satellite Data and Ground Measurements"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI WOS2009Journal Article Research Paper [["dc.bibliographiccitation.firstpage","6612"],["dc.bibliographiccitation.issue","24"],["dc.bibliographiccitation.journal","Journal of Climate"],["dc.bibliographiccitation.lastpage","6623"],["dc.bibliographiccitation.volume","22"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Propastin, Pavel A."],["dc.contributor.author","Kappas, Martin W."],["dc.contributor.author","Panferov, Oleg I."],["dc.date.accessioned","2018-11-07T11:21:33Z"],["dc.date.accessioned","2020-05-08T08:40:09Z"],["dc.date.available","2018-11-07T11:21:33Z"],["dc.date.available","2020-05-08T08:40:09Z"],["dc.date.issued","2009"],["dc.description.abstract","The present study is based on the assumption that vegetation in Indonesia is significantly affected by climate anomalies that are related to El Nino-Southern Oscillation (ENSO) warm phases (El Nino) during the past decades. The analysis builds upon a monthly time series from the normalized difference vegetation index (NDVI) gridded data from the Advanced Very High Resolution Radiometer (AVHRR) and two ENSO proxies, namely, sea surface temperature anomalies (SSTa) and Southern Oscillation index (SOI), and aims at the analysis of the spatially explicit dimension of ENSO impact on vegetation on the Indonesian archipelago. A time series correlation analysis between NDVI anomalies and ENSO proxies for the most recent ENSO warm events (1982-2006) showed that, in general, anomalies in vegetation productivity over Indonesia can be related to an anomalous increase of SST in the eastern equatorial Pacific and to decreases in SOI, respectively. The net effect of these variations is a significant decrease in NDVI values throughout the affected areas during the ENSO warm phases. The 1982/83 ENSO warm episode was rather short but-in terms of ENSO indices-the most extreme one within the study period. The 1997/98 El Nino lasted longer but was weaker. Both events had significant impact on vegetation in terms of negative NDVI anomalies. Compared to these two major warm events, the other investigated events (1987/88, 1991/92, 1994/95, and 2002/03) had no significant effect on vegetation in the investigated region. The land cover-type specific sensitivity of vegetation to ENSO anomalies revealed thresholds of vegetation response to ENSO warm events. The results for the 1997/98 ENSO warm event confirm the hypothesis that the vulnerability of vegetated tropical land surfaces to drought conditions is considerably affected by land use intensity. In particular, it could be shown that natural forest areas are more resistant to drought stress than degraded forest areas or cropland. Comparing the spatially explicit patterns of El Nino-related vegetation variation during the major El Nino phases, the spatial distribution of affected areas reveals distinct core regions of ENSO drought impact on vegetation for Indonesia that coincide with forest conversion and agricultural intensification hot spots."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft (DFG) [SFB-552]"],["dc.identifier.doi","10.1175/2009JCLI2460.1"],["dc.identifier.isi","000273359000007"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/5931"],["dc.identifier.scopus","2-s2.0-77649334436"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/55798"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-77649334436&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.eissn","1520-0442"],["dc.relation.issn","0894-8755"],["dc.relation.orgunit","Abteilung Bioklimatologie"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Spatial patterns of NDVI variation over Indonesia and their relationship to ENSO warm events during the period 1982-2006"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI WOS2015Journal Article Research Paper [["dc.bibliographiccitation.firstpage","6655"],["dc.bibliographiccitation.issue","22"],["dc.bibliographiccitation.journal","Biogeosciences"],["dc.bibliographiccitation.lastpage","6667"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Olchev, A."],["dc.contributor.author","Ibrom, A."],["dc.contributor.author","Panferov, O."],["dc.contributor.author","Gushchina, D."],["dc.contributor.author","Kreilein, H."],["dc.contributor.author","Popov, V."],["dc.contributor.author","Propastin, P."],["dc.contributor.author","June, T."],["dc.contributor.author","Rauf, A."],["dc.contributor.author","Gravenhorst, G."],["dc.contributor.author","Knohl, A."],["dc.date.accessioned","2017-09-07T11:49:05Z"],["dc.date.available","2017-09-07T11:49:05Z"],["dc.date.issued","2015"],["dc.description.abstract","The possible impact of El Niño–Southern Oscillation (ENSO) events on the main components of CO2 and H2O fluxes between the tropical rainforest and the atmosphere is investigated. The fluxes were continuously measured in an old-growth mountainous tropical rainforest in Central Sulawesi in Indonesia using the eddy covariance method for the period from January 2004 to June 2008. During this period, two episodes of El Niño and one episode of La Niña were observed. All these ENSO episodes had moderate intensity and were of the central Pacific type. The temporal variability analysis of the main meteorological parameters and components of CO2 and H2O exchange showed a high sensitivity of evapotranspiration (ET) and gross primary production (GPP) of the tropical rainforest to meteorological variations caused by both El Niño and La Niña episodes. Incoming solar radiation is the main governing factor that is responsible for ET and GPP variability. Ecosystem respiration (RE) dynamics depend mainly on the air temperature changes and are almost insensitive to ENSO. Changes in precipitation due to moderate ENSO events did not have any notable effect on ET and GPP, mainly because of sufficient soil moisture conditions even in periods of an anomalous reduction in precipitation in the region."],["dc.identifier.doi","10.5194/bg-12-6655-2015"],["dc.identifier.gro","3147096"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/4815"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation","SFB 990 | A | A03: Untersuchung von Land-Atmosphäre Austauschprozesse in Landnutzungsänderungs-Systemen"],["dc.relation.issn","1726-4189"],["dc.relation.orgunit","Abteilung Bioklimatologie"],["dc.rights","CC BY 3.0"],["dc.subject.gro","sfb990_journalarticles"],["dc.title","Response of CO2 and H2O fluxes in a mountainous tropical rainforest in equatorial Indonesia to El Niño events"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI2015Journal Article [["dc.bibliographiccitation.firstpage","4405"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Biogeosciences Discussions"],["dc.bibliographiccitation.lastpage","4431"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Olchev, A."],["dc.contributor.author","Ibrom, A."],["dc.contributor.author","Panferov, O."],["dc.contributor.author","Gushchina, D."],["dc.contributor.author","Propastin, P."],["dc.contributor.author","Kreilein, H."],["dc.contributor.author","June, T."],["dc.contributor.author","Rauf, A."],["dc.contributor.author","Gravenhorst, G."],["dc.contributor.author","Knohl, A."],["dc.date.accessioned","2019-07-09T11:42:04Z"],["dc.date.available","2019-07-09T11:42:04Z"],["dc.date.issued","2015"],["dc.description.abstract","The possible impact of El Niño–Southern Oscillation (ENSO) events on the main components of CO2 and H2O fluxes between the tropical rainforest and the atmosphere is investigated. The fluxes were continuously measured in an old-growth mountainous tropical rainforest in Central Sulawesi in Indonesia using the eddy covariance method for the period from January 2004 to June 2008. During this period, two episodes of El Niño and one episode of La Niña were observed. All these ENSO episodes had moderate intensity and were of the central Pacific type. The temporal variability analysis of the main meteorological parameters and components of CO2 and H2O exchange showed a high sensitivity of evapotranspiration (ET) and gross primary production (GPP) of the tropical rainforest to meteorological variations caused by both El Niño and La Niña episodes. Incoming solar radiation is the main governing factor that is responsible for ET and GPP variability. Ecosystem respiration (RE) dynamics depend mainly on the air temperature changes and are almost insensitive to ENSO. Changes in precipitation due to moderate ENSO events did not have any notable effect on ET and GPP, mainly because of sufficient soil moisture conditions even in periods of an anomalous reduction in precipitation in the region."],["dc.description.sponsorship","Open-Access Publikationsfonds 2015"],["dc.identifier.doi","10.5194/bgd-12-4405-2015"],["dc.identifier.fs","616105"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12761"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/58580"],["dc.language.iso","en"],["dc.relation.issn","1810-6285"],["dc.rights.access","openAccess"],["dc.title","Response of CO2 and H2O fluxes of a mountainous tropical rain forest in equatorial Indonesia to El Niño events"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]Details DOI2015Journal Article [["dc.bibliographiccitation.firstpage","3760"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.lastpage","3782"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Kappas, Martin W."],["dc.contributor.author","Propastin, Pavel A."],["dc.contributor.author","Degener, Jan F."],["dc.contributor.author","Renchin, Tsolmon"],["dc.date.accessioned","2018-11-07T09:58:51Z"],["dc.date.accessioned","2020-05-08T08:40:25Z"],["dc.date.available","2018-11-07T09:58:51Z"],["dc.date.available","2020-05-08T08:40:25Z"],["dc.date.issued","2015"],["dc.description.abstract","Long-term global datasets of the Leaf Area Index (LAI) are important for monitoring global vegetation dynamics and are an important input for Earth system models (ESM). The comparison of long-term datasets is based on two recently available datasets both derived from AVHRR (Advanced Very High Resolution Radiometer) time series. The LAI3g dataset is developed from the new improved third generation Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) from AVHRR sensors and best-quality MODIS LAI data. The second long-term LAI dataset is based on the 8-km spatial resolution GIMMS-AVHRR data (Goettingen GIS & Remote Sensing, GGRS dataset). The GGRS-LAI product uses a satellite-based LAI. This algorithm uses a three-dimensional physical radiative transfer model, which establishes the relationship between LAI, vegetation fractional cover and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. The model incorporates a number of site-/region-specific parameters, including the vegetation architecture variables, such as leaf angle distribution, clumping index and light extinction coefficient. For the application of the model to Kazakhstan, the vegetation architecture variables were computed at the local (pixel) level based on extensive field surveys of the biophysical properties of vegetation in representative grassland areas of Kazakhstan. As a main result of our study, we could summarize that the differences between both products are most pronounced at the start and the end of the growing season. During the spring and autumn months, the LAI difference maps showed a considerable difference of LAI GGRS and LAI3g. LAI3g is characterized by a considerably earlier start and a later finish to the growing season than LAI GGRS. Moreover, LAI3g showed LAI > 0 during the winter months when any green vegetation is absent in all land covers of Kazakhstan. A direct cause for this could be a too high base level of the LAI3g during the leafless phase."],["dc.description.sponsorship","Open-Access Publikationsfonds 2015"],["dc.identifier.doi","10.3390/rs70403760"],["dc.identifier.isi","000354789300017"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11885"],["dc.identifier.scopus","2-s2.0-84937838132"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37454"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/64957"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-84937838132&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","2072-4292"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Inter-Comparison and Evaluation of the Global LAI Product (LAI3g) and the Regional LAI Product (GGRS-LAI) over the Area of Kazakhstan"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI WOS2017Journal Article [["dc.bibliographiccitation.artnumber","e0179875"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","PloS one"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Chen, Yizhao"],["dc.contributor.author","Li, Jianlong"],["dc.contributor.author","Ju, Weimin"],["dc.contributor.author","Ruan, Honghua"],["dc.contributor.author","Qin, Zhihao"],["dc.contributor.author","Huang, Yiye"],["dc.contributor.author","Jeelani, Nasreen"],["dc.contributor.author","Padarian, José"],["dc.contributor.author","Propastin, Pavel"],["dc.date.accessioned","2019-07-09T11:43:31Z"],["dc.date.available","2019-07-09T11:43:31Z"],["dc.date.issued","2017"],["dc.description.abstract","Water-use efficiency (WUE), defined as the ratio of net primary productivity (NPP) to evapotranspiration (ET), is an important indicator to represent the trade-off pattern between vegetation productivity and water consumption. Its dynamics under climate change are important to ecohydrology and ecosystem management, especially in the drylands. In this study, we modified and used a late version of Boreal Ecosystem Productivity Simulator (BEPS), to quantify the WUE in the typical dryland ecosystems, Temperate Eurasian Steppe (TES). The Aridity Index (AI) was used to specify the terrestrial water availability condition. The regional results showed that during the period of 1999-2008, the WUE has a clear decreasing trend in the spatial distribution from arid to humid areas. The highest annual average WUE was in dry and semi-humid sub-region (DSH) with 0.88 gC mm-1 and the lowest was in arid sub-region (AR) with 0.22 gC mm-1. A two-stage pattern of WUE was found in TES. That is, WUE would enhance with lower aridity stress, but decline under the humid environment. Over 65% of the region exhibited increasing WUE. This enhancement, however, could not indicate that the grasslands were getting better because the NPP even slightly decreased. It was mainly attributed to the reduction of ET over 70% of the region, which is closely related to the rainfall decrease. The results also suggested a similar negative spatial correlation between the WUE and the mean annual precipitation (MAP) at the driest and the most humid ends. This regional pattern reflected the different roles of water in regulating the terrestrial ecosystems under different aridity levels. This study could facilitate the understanding of the interactions between terrestrial carbon and water cycles, and thus contribute to a sustainable management of nature resources in the dryland ecosystems."],["dc.identifier.doi","10.1371/journal.pone.0179875"],["dc.identifier.pmid","28686667"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14550"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/58901"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1932-6203"],["dc.relation.orgunit","Fakultät für Geowissenschaften und Geographie"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.subject.ddc","550"],["dc.title","Quantitative assessments of water-use efficiency in Temperate Eurasian Steppe along an aridity gradient."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI PMID PMC2013Journal Article [["dc.bibliographiccitation.artnumber","075094"],["dc.bibliographiccitation.journal","Journal of Applied Remote Sensing"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Propastin, Pavel A."],["dc.date.accessioned","2018-11-07T09:20:00Z"],["dc.date.available","2018-11-07T09:20:00Z"],["dc.date.issued","2013"],["dc.description.abstract","The study investigates the overall vulnerability of vegetation in the River Ili delta (Lake Balkhash, Southern Kazakhstan) to locust hazards using correlation between the normalized difference vegetation index data from advanced very high resolution radiometer and the TOPEX/POSEIDON/JASON-1 satellite altimetry derived water level of Lake Balkhash. The study develops a new monitoring and evaluation system to detect the annual vegetated areas infested by locusts and to quantify the overall recurrence of locust damage in these areas throughout the period 1992 to 2006. The monitoring system-based annual estimations of locust-affected areas were validated against ground survey data. The validation reveals a good correspondence of the estimations with the information from ground truth. The results of the overall vulnerability assessment showed that, for the River Ili delta vegetative land, similar to 17% of the total area was characterized by moderate and high vulnerability of vegetation to locust hazards, whereas similar to 3% showed low vulnerability. Most parts of the Ili delta area are not sensitive to locust hazard. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI."],["dc.identifier.doi","10.1117/1.JRS.7.075094"],["dc.identifier.isi","000324092600001"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/9298"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/28771"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Spie-soc Photo-optical Instrumentation Engineers"],["dc.relation.issn","1931-3195"],["dc.rights","CC BY 3.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/3.0"],["dc.title","Satellite-based monitoring system for assessment of vegetation vulnerability to locust hazard in the River Ili delta (Lake Balkhash, Kazakhstan)"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI WOS2017Journal Article [["dc.bibliographiccitation.artnumber","115005"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","Environmental Research Letters"],["dc.bibliographiccitation.volume","12"],["dc.contributor.affiliation","Chen, Yizhao;"],["dc.contributor.affiliation","Ju, Weimin;"],["dc.contributor.affiliation","Groisman, Pavel;"],["dc.contributor.affiliation","Li, Jianlong;"],["dc.contributor.affiliation","Propastin, Pavel;"],["dc.contributor.affiliation","Xu, Xia;"],["dc.contributor.affiliation","Zhou, Wei;"],["dc.contributor.affiliation","Ruan, Honghua;"],["dc.contributor.author","Chen, Yizhao"],["dc.contributor.author","Ju, Weimin"],["dc.contributor.author","Groisman, Pavel"],["dc.contributor.author","Li, Jianlong"],["dc.contributor.author","Propastin, Pavel"],["dc.contributor.author","Xu, Xia"],["dc.contributor.author","Zhou, Wei"],["dc.contributor.author","Ruan, Honghua"],["dc.date.accessioned","2019-07-09T11:44:46Z"],["dc.date.available","2019-07-09T11:44:46Z"],["dc.date.issued","2017"],["dc.date.updated","2022-02-09T13:19:03Z"],["dc.description.abstract","The temperate Eurasian steppe (TES) is a region where various environmental, social, and economic stresses converge. Multiple types of disturbance exist widely across the landscape, and heavily influence carbon cycling in this region. However, a current quantitative assessment of the impact of disturbances on carbon sequestration is largely lacking. In this study, we combined the boreal ecosystem productivity simulator (BEPS), the Shiyomi grazing model, and the global fire model (Glob-FIRM) to investigate the impact of the two major types of disturbance in the TES (i.e. domestic grazing and fire) on regional carbon sequestration. Model performance was validated using satellite data and field observations. Model outputs indicate that disturbance has a significant impact on carbon sequestration at a regional scale. The annual total carbon lost due to disturbances was 7.8 TgCyr−1, accounting for 14.2% of the total net ecosystem productivity (NEP). Domestic grazing plays the dominant role in terrestrial carbon consumption, accounting for 95% of the total carbon lost from the two disturbances. Carbon losses from both disturbances significantly increased from 1999 to 2008 (R2=0.82, P < 0.001 for grazing, R2=0.51, P<0.05 for fire). Heavy domestic grazing in relatively barren grasslands substantially reduced carbon sequestration, particularly in the grasslands of Turkmenistan, Uzbekistan, and the far southwest of Inner Mongolia. This spatially-explicit information has potential implications for sustainable management of carbon sequestration in the vast grassland ecosystems."],["dc.description.sponsorship","National Key R&D Program of China"],["dc.description.sponsorship","Fundamental Research Funds for the Central Universities"],["dc.description.sponsorship","National Key R&D Program of China"],["dc.description.sponsorship","APN Global Change Fund Project"],["dc.description.sponsorship","National Youth Science Fund of China"],["dc.identifier.doi","10.1088/1748-9326/aa849b"],["dc.identifier.eissn","1748-9326"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14892"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59089"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.publisher","IOP Publishing"],["dc.relation.issn","1748-9326"],["dc.rights","CC BY 3.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/3.0/"],["dc.subject.ddc","550"],["dc.title","Quantitative assessment of carbon sequestration reduction induced by disturbances in temperate Eurasian steppe"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]Details DOI