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Global Agricultural Land Resources – A High Resolution Suitability Evaluation and Its Perspectives until 2100 under Climate Change Conditions (v3.0)
No full textAgricultural land resources – a global suitability evaluation (v3.0)
Local climate, soil and topography determine the conditions under which agricultural crops are suitable for growth or not. The methodology uses a fuzzy logic approach that is described in Zabel et al. (2014). The approach is based on Liebig's law of the minimum. Accordingly, plant suitability is determined not by total available resources, but by the scarcest resource. The limiting factor depends on the local environmental conditions and the crop-specific requirements, that are taken from literature.
Determining Agricultural Suitability
Agricultural suitability is calculated for each of 5 climate models (GFDL, HadGEM2, IPSL, MIROC and NorESM1) from the AR5 ISIMIP fast track protocol. Daily climate model data for temperature, precipitation and solar radiation are statistically downscaled to 30 arc seconds spatial resolution. A monthly bias-correction is applied using WorldClim data. The provided suitability data refers to the model median over the 5 climate simulations. Soil data is taken from the Harmonized World Soil Database (HWSD) v1.21. Considered soil properties are texture, proportion of coarse fragments and gypsum, base saturation, pH content, organic carbon content, salinity, sodicity. Soil depth is taken into account according to Pelletier et al. (2015). Topography data is applied from the Shuttle Radar Topography Mission (SRTM). Irrigation has strong impact on the suitability of crops and is considered in this approach.
Agricultural Suitability
The agricultural suitability data is provided at a spatial resolution of 30 arc seconds (approximately 1 km2 at the equator). The dataset contains four time periods (1980-2009, 2010-2039, 2040-2069, 2070-2099) and two climate change scenarios (RCP2.6 and RCP 8.5). Agricultural suitability is provided for rainfed conditions and for irrigated conditions seperately. Additionally, we provide a dataset in which the current irrigation areas according to Maier et al. (2018) are applied. The suitability is provided for 23 food, feed, fibre, and 1st and 2nd generation bio-energy crops. An 'overall suitability' is provided for all crops that considers the most suitable crop on each pixel. Additionally, we provide a dataset excluding 2nd generation bioenergy crops (18-23) from the overall aggregation of crops.
Food, feed, fiber and first-generation bioenergy crops
Barley
Potato
Sugarbeet
Cassava
Rapeseed
Sugarcane
Groundnut
Rice
Sunflower
Maize
Rye
Summer wheat
Millet
Sorghum
Winter wheat
Oilpalm
Soybean
Second-generation bioenergy crops
Jatropha
Reed canary grass
Miscanthus
Eucalyptus
Switchgrass
Willow
Growing Season Adaptation
The agricultural suitability considers the adaptation of the growing season. For each pixel and crop, the growing season is optimized throughout the year, taking the annual course of precipitation, temperature, and solar radiation as well as their interplay, into account.
Most Suitable Crop
The most suitable crop for each pixel is provided in the data. Please note that a value of 126 means that no crop suitable and 127 means that multiple crops have the same suitability.
Further information
Detailled information are available in the following publications:
Zabel F, Putzenlechner B, Mauser W (2014) Global Agricultural Land Resources – A High Resolution Suitability Evaluation and Its Perspectives until 2100 under Climate Change Conditions. PLOS ONE 9(9): e107522. doi: 10.1371/journal.pone.0107522
Cronin, J., Zabel, F., Dessens, O., Anandarajah, G. (2020): Land suitability for energy crops under scenarios of climate change and land-use. GCB Bioenergy, 12(8). doi: 10.1111/gcbb.12697
Schneider. J.M., Zabel, F., Mauser, W. (2022): Global inventory of suitable, cultivable and available cropland under different scenarios and policies. Scientific Data 9, 527. doi: 10.1038/s41597-022-01632-8
Meier, J., Zabel, F., Mauser, W. (2018): A global approach to estimate irrigated areas – a comparison between different data and statistics. Hydrol. Earth Syst. Sci., 22, 1119–1133, 2018. doi: 10.5194/hess-22-1119-201
Pelletier, J. D., Broxton, P. D., Hazenberg, P., Zeng, X., Troch, P. A., Niu, G.-Y., Williams, Z., Brunke, M. A., and Gochis, D. (2016), A gridded global data set of soil, immobile regolith, and sedimentary deposit thicknesses for regional and global land surface modeling, J. Adv. Model. Earth Syst., 8, 41– 65, doi: 10.1002/2015MS000526.
Improvements in v3.0
Compared to the previous version (v2.0), this version (v3.0) uses updated input data for soil (HWSD v1.21) and high resolution irrigated areas (Maier et al. 2018), and additionally considers soil depth (Pelletier et al. 2016). Moreover, the suitability is calculated for an ensemble of 5 climate models, and is available for more crops, including a number of second generation bioenergy crops.
Contact
Please contact: Dr. Florian Zabel, [email protected], Department of Geography, LMU München (www.geografie.uni-muenchen.de
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Natural potential for future cropland expansion
No full textNatural potentials for future cropland expansion
The potential for the expansion of cropland is restricted by the availability of land resources and given local natural conditions. As a result, area that is highly suitable for agriculture according to the prevailing local biophysical conditions but is not under cultivation today has a high natural potential for expansion. Policy regulations can further restrict the availability of land for expansion by designating protected areas, although they may be suitable for agriculture. Conversely, by applying e.g. irrigation practices, land can be brought under cultivation, although it may naturally not be suitable. Here, we investigate the potentials for agricultural expansion for near future climate scenario conditions to identify the suitability of non-cropland areas for expansion according to their local natural conditions.
We determine the available energy, water and nutrient supply for agricultural suitability from climate, soil and topography data, by using a fuzzy logic approach according to Zabel et al. (2014). It considers the 16 globally most important staple and energy crops. These are: barley, cassava, groundnut, maize, millet, oil palm, potato, rapeseed, rice, rye, sorghum, soy, sugarcane, sunflower, summer wheat, winter wheat. The parameterization of the membership functions that describe each of the crops’ specific natural requirements is taken from Sys et al. (1993). The considered natural conditions are: climate (temperature, precipitation, solar radiation), soil properties (texture, proportion of coarse fragments and gypsum, base saturation, pH content, organic carbon content, salinity, sodicity), and topography (elevation, slope). As a result of the fuzzy logic approach, values in a range between 0 and 1 describe the suitability of a crop for each of the prevailing natural conditions at a certain location. The smallest suitability value over all parameters finally determines the suitability of a crop. The daily climate data is provided by simulation results from the global climate model ECHAM5 (Jungclaus et al. 2006) for near future (2011-2040) SRES A1B climate scenario conditions. Soil data is taken from the Harmonized World Soil Database (HWSD) (FAO et al. 2012), and topography data is applied from the Shuttle Radar Topography Mission (SRTM) (Farr et al. 2007). In order to gather a general crop suitability, which does not refer to one specific crop, the most suitable crop with the highest suitability value is chosen at each pixel.
In addition the natural biophysical conditions, we consider today’s irrigated areas according to (Siebert et al. 2013). We assume that irrigated areas globally remain constant until 2040, since adequate data on the development of irrigated areas do not exist, although it is likely that freshwater availability for irrigation could be limited in some regions, while in other regions surplus water supply could be used to expand irrigation practices (Elliott et al. 2014). However, it is difficult to project where irrigation practices will evolve, since it is driven by economic investment costs that are required to establish irrigation infrastructure.
In principle, all agriculturally suitable land that is not used as cropland today has the natural potential to be converted into cropland. We assume that only urban and built-up areas are not available for conversion, although more than 80% of global urban areas are agriculturally suitable (Avellan et al. 2012). However, it seems unlikely that urban areas will be cleared at the large scale due to high investment costs, growing cities and growing demand for settlements. Concepts of urban and vertical farming usually are discussed under the aspects of cultivating fresh vegetables and salads for urban population. They are not designed to extensively grow staple crops such as wheat or maize for feeding the world in the near future. Urban farming would require one third of the total global urban area to meet only the global vegetable consumption of urban dwellers (Martellozzo et al. 2015). Thus, urban agriculture cannot substantially contribute to global agricultural production of staple crops.
Protected areas or dense forested areas are not excluded from the calculation, in order not to lose any information in the further combination with the biodiversity patterns (see chapter 2.3). We use data on current cropland distribution by Ramankutty et al. (2008) and urban and built-up area according to the ESA-CCI land use/cover dataset (ESA 2014). From this data, we calculate the ‘natural expansion potential index’ (Iexp) that expresses the natural potential for an area to be converted into cropland as follows:
Iexp = S * Aav
The index is determined by the quality of agricultural suitability (S) (values between 0 and 1) multiplied with the amount of available area (Aav) for conversion (in percentage of pixel area). The available area includes all suitable area that is not cultivated today, and not classified as urban or artificial area. The index ranges between 0 and 100 and indicates where the conditions for cropland expansion are more or less favorable, when taking only natural conditions into account, disregarding socio-economic factors, policies and regulations that drive or inhibit cropland expansion. The index is a helpful indicator for identifying areas where cropland expansion could take place in the near future.
Further information
Detailled information are available in the following publication:
Delzeit, R., F. Zabel, C. Meyer and T. Václavík (2017). Addressing future trade-offs between biodiversity and cropland expansion to improve food security. Regional Environmental Change 17(5): 1429-1441. DOI: 10.1007/s10113-016-0927-1
Contact
Please contact: Dr. Florian Zabel, [email protected], Department für Geographie, LMU München (www.geografie.uni-muenchen.de)This research was carried out within the framework of the GLUES (Global Assessment of Land Use Dynamics, Greenhouse Gas Emissions and Ecosystem Services) Project, which has been supported by the German Ministry of Education and Research (BMBF) program on sustainable land management (grant number: 01LL0901E)
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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