Erasmi, Stefan

[["dc.bibliographiccitation.firstpage","40"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","European Journal of Remote Sensing"],["dc.bibliographiccitation.lastpage","59"],["dc.bibliographiccitation.volume","46"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Schucknecht, Anne"],["dc.contributor.author","Niemeyer, Irmgard"],["dc.contributor.author","Matschullat, Jörg"],["dc.date.accessioned","2020-05-11T10:05:47Z"],["dc.date.available","2020-05-11T10:05:47Z"],["dc.date.issued","2013"],["dc.description.abstract","Desertification is a challenge in north-eastern Brazil (NEB) that needs to be understood to develop sustainable land-use strategies. This study analyses regional vegetation dynamics in NEB and the compatibility of two NDVI data sets to support future desertification assessment studies in the semi-arid Caatinga biome. Vegetation variability and trends in NEB are analysed for 1982-2006, based on monthly AVHRR (GIMMS) NDVI data. The GIMMS data are compared with MODIS NDVI for the overlapping period 2001-2006. Existing statistical methods are applied and existing NDVI analyses in NEB expanded in respect to vegetation trend analysis and data set comparison."],["dc.description.sponsorship","Federal State of Saxony"],["dc.identifier.doi","10.5721/EuJRS20134603"],["dc.identifier.isi","000318651700003"],["dc.identifier.scopus","2-s2.0-84875196212"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/31208"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-84875196212&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","2279-7254"],["dc.title","Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","389"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Journal of Photogrammetry, Remote Sensing and Geoinformation Science"],["dc.bibliographiccitation.lastpage","405"],["dc.bibliographiccitation.volume","85"],["dc.contributor.author","Baron, Daniel"],["dc.contributor.author","Erasmi, Stefan"],["dc.date.accessioned","2020-05-11T13:23:44Z"],["dc.date.available","2020-05-11T13:23:44Z"],["dc.date.issued","2017"],["dc.description.abstract","In this study, a workflow for a semi-automated forest/non-forest detection is proposed that is based on multitemporal Sentinel-1 ground range detected (GRD) C-band backscatter and TanDEM-X Coregistered Single look Slant range Complex (CoSSC) X-band imagery and an unsupervised random forest classification approach. Therefore, numerous features that refer to frequency, polarisation, and texture were extracted from SAR data of different seasons. The aim was to develop a processing scheme that is feasible for semi-automated forest mapping and monitoring from SAR data at high spatial resolution and on annual scale. It was tested for seven study sites in Germany and Canada which represent different biomes and forest types. Results were validated against field observations and existing forest maps. The best performance for the German study sites was achieved with multitemporal Sentinel-1 backscatter data from the onset of the growing season with small incidence angle and VH polarisation, together with extracted textural features and TanDEM-X data. Producer’s accuracies for the forest class of the different study sites ranged from 88.4 to 98.0%. User’s accuracies ranged from 85.5 to 87.0%. Using Sentinel-1 data covering the whole growing season at a 12 day repetition rate, ascending and descending orbits and VV and VH polarisations led to comparable results. Limited data availability for the Canadian study sites resulted in on average to less reliable results than at the German sites with a higher range of producer’s (62.4–98.8%) and user’s accuracies (46.2–90.2%)."],["dc.identifier.doi","10.1007/s41064-017-0040-1"],["dc.identifier.scopus","2-s2.0-85053544269"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65047"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-85053544269&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.relation.eissn","2512-2819"],["dc.relation.issn","2512-2789"],["dc.title","High resolution forest maps from interferometric TanDEM-X and multitemporal sentinel-1 SAR data,Großmaßstäbige forstkartierung auf der grundlage von interferometrischen TanDEM-X und multitemporalen sentinel-1-SAR daten"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1173"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Agroforestry Systems"],["dc.bibliographiccitation.lastpage","1187"],["dc.bibliographiccitation.volume","87"],["dc.contributor.author","Leuschner, Christoph"],["dc.contributor.author","Moser, Gerald"],["dc.contributor.author","Hertel, Dietrich"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Leitner, Daniela"],["dc.contributor.author","Culmsee, Heike"],["dc.contributor.author","Schuldt, Bernhard"],["dc.contributor.author","Schwendenmann, Luitgard"],["dc.date.accessioned","2018-08-10T14:37:12Z"],["dc.date.accessioned","2020-05-11T13:21:03Z"],["dc.date.available","2018-08-10T14:37:12Z"],["dc.date.available","2020-05-11T13:21:03Z"],["dc.date.issued","2013"],["dc.description.abstract","Tropical forests store a large part of the terrestrial carbon and play a key role in the global carbon (C) cycle. In parts of Southeast Asia, conversion of natural forest to cacao agroforestry systems is an important driver of deforestation, resulting in C losses from biomass and soil to the atmosphere. This case study from Sulawesi, Indonesia, compares natural forest with nearby shaded cacao agroforests for all major above and belowground biomass C pools (n = 6 plots) and net primary production (n = 3 plots). Total biomass (above- and belowground to 250 cm soil depth) in the forest (approx. 150 Mg C ha−1) was more than eight times higher than in the agroforest (19 Mg C ha−1). Total net primary production (NPP, above- and belowground) was larger in the forest than in the agroforest (approx. 29 vs. 20 Mg dry matter (DM) ha−1 year−1), while wood increment was twice as high in the forest (approx. 6 vs. 3 Mg DM ha−1 year−1). The SOC pools to 250 cm depth amounted to 134 and 78 Mg C ha−1 in the forest and agroforest stands, respectively. Replacement of tropical moist forest by cacao agroforest reduces the biomass C pool by approximately 130 Mg C ha−1; another 50 Mg C ha−1 may be released from the soil. Further, the replacement of forest by cacao agroforest also results in a 70–80 % decrease of the annual C sequestration potential due to a significantly smaller stem increment."],["dc.identifier.doi","10.1007/s10457-013-9628-7"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65035"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.eissn","1572-9680"],["dc.relation.issn","0167-4366"],["dc.title","Conversion of tropical moist forest into cacao agroforest: consequences for carbon pools and annual C sequestration"],["dc.title.subtitle","consequences for carbon pools and annual C sequestration"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","138"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Basic and Applied Dryland Research"],["dc.bibliographiccitation.lastpage","154"],["dc.bibliographiccitation.volume","1"],["dc.contributor.author","Propastin, Pavel"],["dc.contributor.author","Kappas, Martin"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Muratova, Nadia R."],["dc.date.accessioned","2020-05-12T08:32:47Z"],["dc.date.available","2020-05-12T08:32:47Z"],["dc.date.issued","2007"],["dc.description.abstract","We combined Normalized Difference Vegetation Index (NDVI) datasets derived from the Advanced Very High Resolution Radiometer (AVHRR) and climate records to analyse within-season temporal relationships between vegetation activity and two eco-climatic parameters (precipitation and temperature) in an arid region of Central Kazakhstan. Assessments of these relationships were performed by calculating correlation coefficients between 10-day values of NDVI and the both climatic parameters throughout the growing season (April-October). The correlations were calculated for every pixel as well as for the aggregated datasets representing different land cover types and the entire study area. The results indicate that strong significant positive correlations exist between NDVI and each of the explanatory climatic parameters at all spatial scales. Temperature was considered to be the leading climatic factor controlling intra-annual NDVI dynamics. The correlation coefficients between NDVI-rainfall and NDVI-temperature exhibit a clear structure in terms of spatial distribution. The results indicate that the response of vegetation to climatic factors increases in order from shrubs and desert vegetation to semi-desert, short grassland and to steppe vegetation."],["dc.description.abstract","Die Arbeit untersucht zeitliche Zusammenhänge zwischen Vegetationsdynamik und Dynamik von Klimaelementen (Temperatur und Niederschlag) in einem Trockengebiet des Zentral-Kasachstans. Die Datengrundlagen der Arbeit umfassten den Normalized Difference Vegetation Index (NDVI) von dem Advanced Very High Resolution Radiometer (AVHRR) sowie Messwerten der Klimastationen für Niederschlag und Temperatur. Die Schätzung der Stärke des Zusammenhanges erfolgte durch Berechnung des Koeffizienten der Korrelation und Kreuzkorrelation zwischen den Zeitreihen der Dekadenwerte der NDVI und der beiden Klimaelemente während der Pflanzenwachstumsperiode. Die statistischen Zusammenhänge wurden auf verschiedenen Skalen räumlicher Generalisierung betrachtet: von dem gesamten Gebiet bis zu einzelnem Pixel. Die Ergebnisse beweisen, dass auf allen Betrachtungsskalen strenge Interrelationen zwischen der Dynamik des NDVI auf einer Seite und den beiden Klimaelementen auf der anderen Seite bestehen. Temperatur erwies sich als der Hauptfaktor für die Kontrolle der Vegetationsdynamik durch das Klima. Die räumliche Verbreitung der Werte des Korrelationskoeffizienten zeigte ein deutliches Muster. Dieses Muster spiegelt die Unterschiede zwischen einzelnen Vegetationstypen in bezug auf ihre Reaktionskraft und Reaktionsgeschwindigkeit zu der Einwirkung der Klimaelemente wider."],["dc.identifier.doi","10.1127/badr/1/2007/138"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65138"],["dc.language.iso","en"],["dc.relation.issn","1864-3191"],["dc.title","Remote sensing based study on intra-annual dynamics of vegetation and climate in drylands of Kazakhastan"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Bioagro"],["dc.bibliographiccitation.volume","22"],["dc.contributor.author","Andrade, O."],["dc.contributor.author","Briceño, J."],["dc.contributor.author","Unda, J."],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Kappas, Martin"],["dc.date.accessioned","2020-05-11T09:22:25Z"],["dc.date.accessioned","2020-05-11T13:22:49Z"],["dc.date.available","2020-05-11T09:22:25Z"],["dc.date.available","2020-05-11T13:22:49Z"],["dc.date.issued","2010"],["dc.identifier.scopus","2-s2.0-79953289769"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/64993"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-79953289769&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.title","Generating and mapping of environmental parameters to make land evaluations in Torres Municipality, Lara State, Venezuela,Generación y mapeo de parámetros ambientales con fines de evaluación de tierras en el Municipio Torres, Estado Lara, Venezuela"],["dc.title.alternative","Generación y mapeo de parámetros ambientales con fines de evaluación de tierras en el Municipio Torres, Estado Lara, Venezuela"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1688"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Environmental Science & Technology"],["dc.bibliographiccitation.lastpage","1694"],["dc.bibliographiccitation.volume","47"],["dc.contributor.author","Fritz, Steffen"],["dc.contributor.author","See, Linda"],["dc.contributor.author","van der Velde, Marijn"],["dc.contributor.author","Nalepa, Rachel A."],["dc.contributor.author","Perger, Christoph"],["dc.contributor.author","Schill, Christian"],["dc.contributor.author","McCallum, Ian"],["dc.contributor.author","Schepaschenko, Dmitry"],["dc.contributor.author","Kraxner, Florian"],["dc.contributor.author","Cai, Ximing"],["dc.contributor.author","Zhang, Xiao"],["dc.contributor.author","Ortner, Simone"],["dc.contributor.author","Hazarika, Rubul"],["dc.contributor.author","Cipriani, Anna"],["dc.contributor.author","Di Bella, Carlos"],["dc.contributor.author","Rabia, Ahmed H."],["dc.contributor.author","Garcia, Alfredo"],["dc.contributor.author","Vakolyuk, Mar'yana"],["dc.contributor.author","Singha, Kuleswar"],["dc.contributor.author","Beget, Maria E."],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Albrecht, Franziska"],["dc.contributor.author","Shaw, Brian"],["dc.contributor.author","Obersteiner, Michael"],["dc.date.accessioned","2018-11-07T09:28:15Z"],["dc.date.accessioned","2020-05-11T13:23:23Z"],["dc.date.available","2018-11-07T09:28:15Z"],["dc.date.available","2020-05-11T13:23:23Z"],["dc.date.issued","2013"],["dc.description.abstract","Recent estimates of additional land available for bioenergy production range from 320 to 1411 million ha. These estimates were generated from four scenarios regarding the types of land suitable for bioenergy production using coarse-resolution inputs of soil productivity, slope, climate, and land cover. In this paper, these maps of land availability were assessed using high-resolution satellite imagery. Samples from these maps were selected and crowdsourcing of Google Earth images was used to determine the type of land cover and the degree of human impact. Based on this sample, a set of rules was formulated to downward adjust the original estimates for each of the four scenarios that were previously used to generate the maps of land availability for bioenergy production. The adjusted land availability estimates range from 56 to 1035 million ha depending upon the scenario and the ruleset used when the sample is corrected for bias. Large forest areas not intended for biofuel production purposes were present in all scenarios. However, these numbers should not be considered as definitive estimates but should be used to highlight the uncertainty in attempting to quantify land availability for biofuel production when using coarse-resolution inputs with implications for further policy development."],["dc.identifier.doi","10.1021/es303141h"],["dc.identifier.isi","000314675500065"],["dc.identifier.pmid","23308357"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65045"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.eissn","1520-5851"],["dc.relation.issn","0013-936X"],["dc.title","Downgrading Recent Estimates of Land Available for Biofuel Production"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","4429"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Sensors"],["dc.bibliographiccitation.lastpage","4440"],["dc.bibliographiccitation.volume","8"],["dc.contributor.author","Boloorani, Ali Darvishi"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Kappas, Martin"],["dc.date.accessioned","2018-11-07T11:13:49Z"],["dc.date.accessioned","2020-05-08T08:28:35Z"],["dc.date.accessioned","2020-05-11T13:17:32Z"],["dc.date.available","2018-11-07T11:13:49Z"],["dc.date.available","2020-05-08T08:28:35Z"],["dc.date.available","2020-05-11T13:17:32Z"],["dc.date.issued","2008"],["dc.description.abstract","In this work a new gap-fill technique entitled projection transformation has been developed and used for filling missed parts of remotely sensed imagery. In general techniques for filling missed area of an image are broken down into three main categories: multi-source techniques that take the advantages of other data sources (e.g. using cloud free images to reconstruct the cloudy areas of other images); the second ones fabricate the gap areas using non-gapped parts of an image itself, this group of techniques are referred to as single-source gap-fill procedures; and third group contains methods that make up a combination of both mentioned techniques, therefore they are called hybrid gap-fill procedures. Here a new developed multi-source methodology called projection transformation for filling a simulated gapped area in the Landsat7/ETM+ imagery is introduced. The auxiliary imagery to filling the gaps is an earlier obtained L7/ETM+ imagery. Ability of the technique was evaluated from three points of view: statistical accuracy measuring, visual comparison, and post classification accuracy assessment. These evaluation indicators are compared to the results obtained from a commonly used technique by the USGS as Local Linear Histogram Matching (LLHM) [1]. Results show the superiority of our technique over LLHM in almost all aspects of accuracy."],["dc.identifier.doi","10.3390/s8074429"],["dc.identifier.isi","000258180500025"],["dc.identifier.pmid","27879945"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8776"],["dc.identifier.scopus","2-s2.0-48749126097"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65020"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-48749126097&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","1424-8220"],["dc.rights","CC BY 3.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/3.0/"],["dc.title","Multi-Source Remotely Sensed Data Combination: Projection Transformation Gap-Fill Procedure"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","109"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Erdkunde"],["dc.bibliographiccitation.lastpage","122"],["dc.bibliographiccitation.volume","67"],["dc.contributor.author","Köhler, Stefan"],["dc.contributor.author","Jungkunst, Hermann F."],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Gerold, Gerhard"],["dc.date.accessioned","2018-11-07T09:26:10Z"],["dc.date.accessioned","2020-05-11T13:17:09Z"],["dc.date.available","2018-11-07T09:26:10Z"],["dc.date.available","2020-05-11T13:17:09Z"],["dc.date.issued","2013"],["dc.description.abstract","Deposition rates in remote areas due to anthropogenic emissions are increasing in Asian countries and elsewhere. The burning of biomass in slash-and-burn activities, in addition to burning fossil fuel result in higher rates of atmospheric deposition at forest and agricultural sites. An investigation of bulk depositions in Central Sulawesi was conducted at 13 field sites along a land use cover gradient that included natural and unused sites, slash-and-burn sites, and consolidated agricultural systems around and in the Lore Lindu National Park, an area of more than 2310 km(2). Bulk depositions rates were measured with passive ion exchange collectors. Our results show that Central Sulawesi generally experiences low deposition rates. Depositions that originate mainly from anthropogenic sources, such as nitrate, are very low, i.e. between 0.1 and 0.8 kg ha(-1) a(-1), but increase to 2.4 nitrate kg ha(-1) a(-1) near slash-and-burn areas. Similar patterns were found for elements such as potassium and calcium. Indeterminate depositions were found for geogenic elements such as iron, manganese and aluminium and in some cases phosphorus. A principal component analysis allowed differentiation between the contributions of different sources and different element to the total deposition impact in most cases. Specific deposition rates were recorded for different land use systems. The main factor that generated different deposition patterns was biomass burning resulting from slash-and-burn activities. The latter determined the composition of atmospheric depositions of nearby sites, but the more distant sites inside the national park do not appear to be influenced by these anthropogenic activities yet."],["dc.description.sponsorship","German Research Foundation (DFG) [SFB 552]"],["dc.identifier.doi","10.3112/erdkunde.2013.02.01"],["dc.identifier.isi","000324807900001"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65017"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","0014-0015"],["dc.title","The effects of land use change on atmospheric nutrientdeposition in Central Sulawesi"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1319"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Biogeosciences"],["dc.bibliographiccitation.lastpage","1333"],["dc.bibliographiccitation.volume","15"],["dc.contributor.author","Klinge, Michael"],["dc.contributor.author","Dulamsuren, Choimaa"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Karger, Dirk Nikolaus"],["dc.contributor.author","Hauck, Markus"],["dc.date.accessioned","2019-07-09T11:45:23Z"],["dc.date.accessioned","2020-05-11T13:15:36Z"],["dc.date.available","2019-07-09T11:45:23Z"],["dc.date.available","2020-05-11T13:15:36Z"],["dc.date.issued","2018"],["dc.description.abstract","In northern Mongolia, at the southern boundary of the Siberian boreal forest belt, the distribution of steppe and forest is generally linked to climate and topography, making this region highly sensitive to climate change and human impact. Detailed investigations on the limiting parameters of forest and steppe in different biomes provide necessary information for paleoenvironmental reconstruction and prognosis of potential landscape change. In this study, remote sensing data and gridded climate data were analyzed in order to identify main distribution patterns of forest and steppe in Mongolia and to detect environmental factors driving forest development. Forest distribution and vegetation vitality derived from the normalized differentiated vegetation index (NDVI) were investigated for the three types of boreal forest present in Mongolia (taiga, subtaiga and forest–steppe), which cover a total area of 73 818 km2. In addition to the forest type areas, the analysis focused on subunits of forest and nonforested areas at the upper and lower treeline, which represent ecological borders between vegetation types. Climate and NDVI data were analyzed for a reference period of 15 years from 1999 to 2013. The presented approach for treeline delineation by identifying representative sites mostly bridges local forest disturbances like fire or tree cutting. Moreover, this procedure provides a valuable tool to distinguish the potential forested area. The upper treeline generally rises from 1800 m above sea level (a.s.l.) in the northeast to 2700 m a.s.l. in the south. The lower treeline locally emerges at 1000 m a.s.l. in the northern taiga and rises southward to 2500 m a.s.l. The latitudinal gradient of both treelines turns into a longitudinal one on the eastern flank of mountain ranges due to higher aridity caused by rain-shadow effects. Less productive trees in terms of NDVI were identified at both the upper and lower treeline in relation to the respective total boreal forest type area. The mean growing season temperature (MGST) of 7.9–8.9 °C and a minimum MGST of 6 °C are limiting parameters at the upper treeline but are negligible for the lower treeline. The minimum of the mean annual precipitation (MAP) of 230–290 mm yr−1 is a limiting parameter at the lower treeline but also at the upper treeline in the forest–steppe ecotone. In general, NDVI and MAP are lower in grassland, and MGST is higher compared to the corresponding boreal forest. One exception occurs at the upper treeline of the subtaiga and taiga, where the alpine vegetation consists of mountain meadow mixed with shrubs. The relation between NDVI and climate data corroborates that more precipitation and higher temperatures generally lead to higher greenness in all ecological subunits. MGST is positively correlated with MAP of the total area of forest–steppe, but this correlation turns negative in the taiga. The limiting factor in the forest–steppe is the relative humidity and in the taiga it is the snow cover distribution. The subtaiga represents an ecological transition zone of approximately 300 mm yr−1 precipitation, which occurs independently from the MGST. Since the treelines are mainly determined by climatic parameters, the rapid climate change in inner Asia will lead to a spatial relocation of tree communities, treelines and boreal forest types. However, a direct deduction of future tree vitality, forest composition and biomass trends from the recent relationships between NDVI and climate parameters is challenging. Besides human impact, it must consider bio- and geoecological issues like, for example, tree rejuvenation, temporal lag of climate adaptation and disappearing permafrost."],["dc.identifier.doi","10.5194/bg-15-1319-2018"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15188"],["dc.identifier.scopus","2-s2.0-85043494931"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65009"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59218"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-85043494931&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.relation.issn","1726-4189"],["dc.subject.ddc","550"],["dc.title","Climate effects on vegetation vitality at the treeline of boreal forests of Mongolia"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","327"],["dc.bibliographiccitation.lastpage","349"],["dc.contributor.author","Waltert, Matthias"],["dc.contributor.author","Langkau, Maike"],["dc.contributor.author","Maertens, Miet"],["dc.contributor.author","Härtel, Michael"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Mühlenberg, Michael"],["dc.contributor.editor","Gerold, Gerhard"],["dc.contributor.editor","Fremerey, M."],["dc.contributor.editor","Guhardja, Edi"],["dc.date.accessioned","2020-05-12T08:32:54Z"],["dc.date.available","2020-05-12T08:32:54Z"],["dc.date.issued","2004"],["dc.description.abstract","Tropical deforestation and forest fragmentation are probably the most serious threats to biodiversity (see Turner 1996) and it has been theoretically stated that even the largest protected areas in the tropics might be too small to sustain populations of all species of the original system (Terborgh 1999). But species loss in forest fragments is a complex process and appears often only after considerable time lags, especially in vertebrates (Brooks et al. 1999b). Therefore, empirical evidence for such extinctions can only be obtained from areas with a long deforestation history and long-known faunal composition (e.g. van Balen 1999). Such empirical data are scarce but are essential in order to convince land use managers of the long-term effects of forest loss on biodiversity. Species area models, however, are a valuable tool in the prediction of tropical vertebrate species loss (van Balen 1999; Brooks et al. 1997, 1999a, c, 2002; Cowlishaw 1999)."],["dc.identifier.doi","10.1007/978-3-662-08237-9_19"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65139"],["dc.language.iso","en"],["dc.publisher","Springer"],["dc.relation.eisbn","978-3-662-08237-9"],["dc.relation.isbn","978-3-642-05617-8"],["dc.relation.ispartof","Land Use, Nature Conservation and the Stability of Rainforest Margins in Southeast Asia. Environmental Science."],["dc.title","Predicting Losses of Bird Species from Deforestation in Central Sulawesi"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]