Refine
Year of publication
Document Type
- Article (14)
- Working Paper (7)
- Conference Proceeding (1)
Language
- English (22)
Has Fulltext
- yes (22)
Is part of the Bibliography
- no (22)
Keywords
- Bewässerung (2)
- Landwirtschaft (2)
- agriculture (2)
- Asien (1)
- Boden (1)
- Digitale Karte (1)
- Drainage (1)
- Erdoberfläche (1)
- Geschichte 1900-2003 (1)
- Karte (1)
Institute
- Geowissenschaften (14)
- Medizin (6)
- Geographie (2)
Background: Alterations in the DNA methylation pattern are a hallmark of leukemias and lymphomas. However, most epigenetic studies in hematologic neoplasms (HNs) have focused either on the analysis of few candidate genes or many genes and few HN entities, and comprehensive studies are required. Methodology/Principal Findings: Here, we report for the first time a microarray-based DNA methylation study of 767 genes in 367 HNs diagnosed with 16 of the most representative B-cell (n = 203), T-cell (n = 30), and myeloid (n = 134) neoplasias, as well as 37 samples from different cell types of the hematopoietic system. Using appropriate controls of B-, T-, or myeloid cellular origin, we identified a total of 220 genes hypermethylated in at least one HN entity. In general, promoter hypermethylation was more frequent in lymphoid malignancies than in myeloid malignancies, being germinal center mature B-cell lymphomas as well as B and T precursor lymphoid neoplasias those entities with highest frequency of gene-associated DNA hypermethylation. We also observed a significant correlation between the number of hypermethylated and hypomethylated genes in several mature B-cell neoplasias, but not in precursor B- and T-cell leukemias. Most of the genes becoming hypermethylated contained promoters with high CpG content, and a significant fraction of them are targets of the polycomb repressor complex. Interestingly, T-cell prolymphocytic leukemias show low levels of DNA hypermethylation and a comparatively large number of hypomethylated genes, many of them showing an increased gene expression. Conclusions/Significance: We have characterized the DNA methylation profile of a wide range of different HNs entities. As well as identifying genes showing aberrant DNA methylation in certain HN subtypes, we also detected six genes—DBC1, DIO3, FZD9, HS3ST2, MOS, and MYOD1—that were significantly hypermethylated in B-cell, T-cell, and myeloid malignancies. These might therefore play an important role in the development of different HNs.
Artificial drainage of agricultural land, for example with ditches or drainage tubes, is used to avoid water logging and to manage high groundwater tables. Among other impacts it influences the nutrient balances by increasing leaching losses and by decreasing denitrification. To simulate terrestrial transport of nitrogen on the global scale, a digital global map of artificially drained agricultural areas was developed. The map depicts the percentage of each 5’ by 5’ grid cell that is equipped for artificial drainage. Information on artificial drainage in countries or sub-national units was mainly derived from international inventories. Distribution to grid cells was based, for most countries, on the "Global Croplands Dataset" of Ramankutty et al. (1998) and the "Digital Global Map of Irrigation Areas" of Siebert et al. (2005). For some European countries the CORINE land cover dataset was used instead of the both datasets mentioned above. Maps with outlines of artificially drained areas were available for 6 countries. The global drainage area on the map is 167 Mio hectares. For only 11 out of the 116 countries with information on artificial drainage areas, sub-national information could be taken into account. Due to this coarse spatial resolution of the data sources, we recommended to use the map of artificially drained areas only for continental to global scale assessments. This documentation describes the dataset, the data sources and the map generation, and it discusses the data uncertainty.
The Land and Water Development Division of the Food and Agriculture Organization of the United Nations and the Johann Wolfgang Goethe University, Frankfurt am Main, Germany, are cooperating in the development of a global irrigation-mapping facility. This report describes an update of the Digital Global Map of Irrigated Areas for the continent of Asia. For this update, an inventory of subnational irrigation statistics for the continent was compiled. The reference year for the statistics is 2000. Adding up the irrigated areas per country as documented in the report gives a total of 188.5 million ha for the entire continent. The total number of subnational units used in the inventory is 4 428. In order to distribute the irrigation statistics per subnational unit, digital spatial data layers and printed maps were used. Irrigation maps were derived from project reports, irrigation subsector studies, and books related to irrigation and drainage. These maps were digitized and compared with satellite images of many regions. In areas without spatial information on irrigated areas, additional information was used to locate areas where irrigation is likely, such as land-cover and land-use maps that indicate agricultural areas or areas with crops that are usually grown under irrigation. Contents 1. Working Report I: Generation of a map of administrative units compatible with statistics used to update the Digital Global Map of Irrigated Areas in Asia 2. Working Report II: The inventory of subnational irrigation statistics for the Asian part of the Digital Global Map of Irrigated Areas 3. Working Report III: Geospatial information used to locate irrigated areas within the subnational units in the Asian part of the Digital Global Map of Irrigated Areas 4. Working Report IV: Update of the Digital Global Map of Irrigated Areas in Asia, Results Maps
Irrigation intensifies land use by increasing crop yield but also impacts water resources. It affects water and energy balances and consequently the microclimate in irrigated regions. Therefore, knowledge of the extent of irrigated land is important for hydrological and crop modelling, global change research, and assessments of resource use and management. Information on the historical evolution of irrigated lands is limited. The new global historical irrigation data set (HID) provides estimates of the temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5 arcmin resolution. We collected sub-national irrigation statistics from various sources and found that the global extent of AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. We developed eight gridded versions of time series of AEI by combining sub-national irrigation statistics with different data sets on the historical extent of cropland and pasture. Different rules were applied to maximize consistency of the gridded products to sub-national irrigation statistics or to historical cropland and pasture data sets. The HID reflects very well the spatial patterns of irrigated land as shown on historical maps for the western United States (around year 1900) and on a global map (around year 1960). Mean aridity on irrigated land increased and mean natural river discharge on irrigated land decreased from 1900 to 1950 whereas aridity decreased and river discharge remained approximately constant from 1950 to 2005. The data set and its documentation are made available in an open-data repository at https://mygeohub.org/publications/8 (doi:10.13019/M20599).
Irrigation intensifies land use by increasing crop yield but also impacts water resources. It affects water and energy balances and consequently the microclimate in irrigated regions. Therefore, knowledge of the extent of irrigated land is important for hydrological and crop modelling, global change research, and assessments of resource use and management. Information on the historical evolution of irrigated lands is limited. The new global Historical Irrigation Dataset (HID) provides estimates of the temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5 arc-minute resolution. We collected subnational irrigation statistics from various sources and found that the global extent of AEI increased from 63 million ha (Mha) in 1900 to 112 Mha in 1950 and 306 Mha in 2005. We developed eight gridded versions of time series of AEI by combining subnational irrigation statistics with different data sets on the historical extent of cropland and pasture. Different rules were applied to maximize consistency of the gridded products to subnational irrigation statistics or to historical cropland and pasture data sets. The HID reflects very well the spatial patterns of irrigated land in the western United States as shown on historical maps. Mean aridity on irrigated land increased and river discharge decreased from 1900–1950 whereas aridity decreased from 1950–2005. The dataset and its documentation are made available in an open data repository at https://mygeohub.org/publications/8 (doi:10.13019/M2MW2G).
Combined diabetes-obesity syndromes severely impair regeneration of acute skin wounds in mouse models. This study assessed the contribution of subcutaneous adipose tissue to exacerbated wound inflammatory conditions. Genetically obese (ob/ob) mice showed an increased expression of positive transcriptional effectors of adipocyte differentiation such as Krüppel-like factor (KLF)-5 and peroxisome proliferator-activated receptor (PPAR)-γ and an associated expression of leptin and fatty acid-binding protein (FABP)-4, but also CXCL2 in isolated subcutaneous fat. This observation in obese mice is in keeping with differentially elevated levels of KLF-5, PPAR-γ, leptin, FABP-4 and CXCL2 in in vitro-differentiated 3T3-L1 adipocytes. Notably, CXCL2 expression restrictively appeared upon cytokine (IL-1β/TNF-α) stimulation only in mature, but not immature 3T3-L1 adipocytes. Of importance, the critical regulator of adipocyte maturation, PPAR-γ, was merely expressed in the final phase of in-vitro induced adipocyte differentiation from 3T3-L1 pre-adipocytes. Consistently, the PPAR-γ agonist rosiglitazone suppressed cytokine-induced CXCL2 release from mature adipocytes, but not from early 3T3-L1 adipocyte stages. The inhibitory effect of PPAR-γ activation on CXCL2 release appeared to be a general anti-inflammatory effect in mature adipocytes, as cytokine-induced cyclooxygenase (Cox)-2 was simultaneously repressed by rosiglitazone. In accordance with these findings, oral administration of rosiglitazone to wounded obese mice significantly changed subcutaneous adipocyte morphology, reduced wound CXCL2 and Cox-2 expression and improved tissue regeneration. Thus, our data suggest that PPAR-γ might provide a target to suppress inflammatory signals from mature adipocytes, which add to the prolonged wound inflammation observed in diabetes-obesity conditions.
A new version of a digital global map of irrigation areas was developed by combining irrigation statistics for 10 825 sub-national statistical units and geo-spatial information on the location and extent of irrigation schemes. The map shows the percentage of each 5 arc minute by 5 arc minute cell that was equipped for irrigation around the year 2000. It is thus an important data set for global studies related to water and land use. This paper describes the data set and the mapping methodology and gives, for the first time, an estimate of the map quality at the scale of countries, world regions and the globe. Two indicators of map quality were developed for this purpose, and the map was compared to irrigated areas as derived from two remote sensing based global land cover inventories.
A new version of a digital global map of irrigation areas was developed by combining irrigation statistics for 10825 sub-national statistical units and geo-spatial information on the location and extent of irrigation schemes. The map shows the percentage of each 5 arc minute by 5 arc minute cell that was equipped for irrigation around the year 2000. It is thus an important data set for global studies related to water and land use. This paper describes the data set and the mapping methodology and gives, for the first time, an estimate of the map quality at the scale of countries, world regions and the globe. Two indicators of map quality were developed for this purpose, and the map was compared to irrigated areas as derived from two remote sensing based global land cover inventories. We plan to further improve that data set; therefore comments, information and data that might contribute to that effort are highly welcome.
A data set of monthly growing areas of 26 irrigated crops (MGAG-I) and related crop calendars (CC-I) was compiled for 402 spatial entities. The selection of the crops consisted of all major food crops including regionally important ones (wheat, rice, maize, barley, rye, millet, sorghum, soybeans, sunflower, potatoes, cassava, sugar cane, sugar beets, oil palm, rapeseed/canola, groundnuts/peanuts, pulses, citrus, date palm, grapes/vine, cocoa, coffee), major water-consuming crops (cotton), and unspecified other crops (other perennial crops, other annual crops, managed grassland). The data set refers to the time period 1998-2002 and has a spatial resolution of 5 arc minutes by 5 arc minutes which is 8 km by 8 km at the equator. This is the first time that a data set of cell-specific irrigated growing areas of irrigated crops with this spatial resolution was created. The data set is consistent to the irrigated area and water use statistics of the AQUASTAT programme of the Food and Agriculture Organization of the United Nations (FAO) (http://www.fao.org/ag/agl/aglw/aquastat/main/index.stm) and the Global Map of Irrigation Areas (GMIA) (http://www.fao.org/ag/agl/aglw/aquastat/irrigationmap/index.stm). At the cell-level it was tried to maximise consistency to the cropland extent and cropland harvested area from the Department of Geography and Earth System Science Program of the McGill University at Montreal, Quebec, Canada and the Center for Sustainability and the Global Environment (SAGE) of the University of Wisconsin at Madison, USA (http://www.geog.mcgill.ca/~nramankutty/ Datasets/Datasets.html and http://geomatics.geog.mcgill.ca/~navin/pub/Data/175crops2000/). The consistency between the grid product and the input data was quantified. MGAG-I and CC-I are fully consistent to each other on entity level. For input data other than CC-I, the consistency of MGAG-I on cell level was calculated. The consistency of MGAG-I with respect to the area equipped for irrigation (AEI) of GMIA and to the cropland extent of SAGE was characterised by the sum of the cell-specific maximum difference between the MGAG-I monthly total irrigated area and the reference area when the latter was exceeded in the grid cell. The consistency of the harvested area contained in MGAG-I with respect to SAGE harvested area was characterised by the crop-specific sum of the cell-specific difference between MGAG-I harvested area and the SAGE harvested area when the latter was exceeded in the grid cell. In all three cases, the sums are the excess areas that should not have been distributed under the assumption that the input data were correct. Globally, this cell-level excess of MGAG-I as compared to AEI is 331,304 ha or only about 0.12 % of the global AEI of 278.9 Mha found in the original grid. The respective cell-level excess of MGAG-I as compared to the SAGE cropland extent is 32.2 Mha, corresponding to about 2.2 % of the total cropland area. The respective cell-level excess of MGAG-I as compared to the SAGE harvested area is 27 % of the irrigated harvested area, or 11.5 % of the AEI. In a further step that will be published later also rainfed areas were compiled in order to form the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000). The data set can be used for global and continental-scale studies on food security and water use. In the future, it will be improved, e.g. with a better spatial resolution of crop calendars and an improved crop distribution algorithm. The MIRCA2000 data set, its full documentation together with future updates will be freely available through the following long-term internet site: http://www.geo.uni-frankfurt.de/ipg/ag/dl/forschung/MIRCA/index.html. The research presented here was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) within the framework of the research project entitled "Consistent assessment of global green, blue and virtual water fluxes in the context of food production: regional stresses and worldwide teleconnections". The authors thank Navin Ramankutty and Chad Monfreda for making available the current SAGE datasets on cropland extent (Ramankutty et al., 2008) and harvested area (Monfreda et al., 2008) prior to their publication.
This study presents a global scale analysis of cropping intensity, crop duration and fallow land extent computed by using the global dataset on monthly irrigated and rainfed crop areas MIRCA2000. MIRCA2000 was mainly derived from census data and crop calendars from literature. Global cropland extent was 16 million km2 around the year 2000 of which 4.4 million km2 (28%) was fallow, resulting in an average cropping intensity of 0.82 for total cropland extent and of 1.13 when excluding fallow land. The lowest cropping intensities related to total cropland extent were found for Southern Africa (0.45), Central America (0.49) and Middle Africa (0.54), while highest cropping intensities were computed for Eastern Asia (1.04) and Southern Asia (1.0). In remote or arid regions where shifting cultivation is practiced, fallow periods last 3–10 years or even longer. In contrast, crops are harvested two or more times per year in highly populated, often irrigated tropical or subtropical lowlands where multi-cropping systems are common. This indicates that intensification of agricultural land use is a strategy that may be able to significantly improve global food security. There exist large uncertainties regarding extent of cropland, harvested crop area and therefore cropping intensity at larger scales. Satellite imagery and remote sensing techniques provide opportunities for decreasing these uncertainties and to improve the MIRCA2000 inventory.