Contents lists available at ScienceDirect Ecological Informatics journal homepage: www.elsevier.com/locate/ecolinf Modelling of the carbon sequestration and its prediction under climate change Vilém Pechanec a,⁎ , Jan Purkyt b,c , Antonín Benc a , Chukwudi Nwaogu a , Lenka Štěrbová b , Pavel Cudlín b a Palacký University Olomouc, Department of Geoinformatics, 17. listopadu 50, 771 46 Olomouc, Czech Republic b Global Change Research Institute CAS, Lipová 9, 370 05 České Budějovice, Czech Republic c University of South Bohemia in České Budějovice, Faculty of Agriculture, Studentská 1668, 370 05 České Budějovice, Czech Republic ARTICLE INFO Keywords: Carbon sequestration Climate change InVEST Land use modelling GIS ABSTRACT The aim of the presented study is to quantify the total carbon stock of habitats in addition the estimation of aboveground and belowground biomass, necromass, and soil organic carbon. Prediction of carbon storage under climate change is based on future land-use changes, identification of new land-use distribution, and evaluation of changes in human impacts on biomass production and carbon storage. Widely used InVEST model was applied to determine the existing carbon stocks and the amount of carbon captured over time. Changes in the carbon storage were calculated from aboveground biomass, belowground biomass, necromass, and soil organic carbon pools. The original model was modified to vector space to better identify land heterogeneity. The values of the four carbon pools for individual land-use categories were derived from literature and experimental investigation. Land Change Modeller was then used to model future land use by applying business-as-usual scenario on data derived from 1990, 2000, 2006, and 2012 Corine Land Cover data. In this contribution, land cover predictions are calculated using three CORDEX climate models and two emission scenarios (RCP 4.5 and RCP 8.5). Results describe current carbon stock by basic carbon pools and prediction of the total amount of carbon stored in four reservoirs in three time period. Results show that the difference in predictions between specific scenarios in each period is increasing and in all predictions, roughly the same proportional carbon ratio is maintained between the individual stocks. 1. Introduction Ecosystems regulate Earth's climate by adding and removing greenhouse gases such as CO 2 from the atmosphere. Forests, grasslands, peat swamps, and other terrestrial ecosystems collectively store much more carbon than does the atmosphere (Lal, 2004). By storing this carbon in wood, other biomass, and soil, ecosystems keep CO 2 out of the air, where it would contribute to climate change (Watson et al., 2000). Beyond just storing carbon, many ecosystems also contribute to its accumulation in plants and soil over time, thereby “sequestering” additional carbon each year. Disturbing these systems with fire, disease, or vegetation change through land use/land cover (LULC) conversion, significant amounts of CO 2 is released into the atmosphere (Kareiva et al., 2011). Therefore, information on current soil carbon stocks and possible changes are needed in the context of the United Nations Fra- mework Convention on Climate Change. Managing landscapes for carbon storage and sequestration require information about volume and location of already stored carbon, quantity of carbon sequestered or lost over time, and relationship between land use change and its effect on carbon storage and sequestration over time (Oulehle et al., 2011). A terrestrial-based carbon sequestration process is perhaps the most widely recognized of all ecosystem services (Canadell and Raupach, 2008; IPCC, 2006; Pagiola, 2008; Stern, 2007). Determination of carbon stocks in the aboveground biomass can be accomplished by a variety of methods, including both contact field measurements and contactless measurement using remote sensing. Contact measurement methods always provide more accurate results but they are costly and time consuming (Brown, 2002; Coomes et al., 2002; Gibbs et al., 2007; Machar et al., 2016). Therefore, for large areas, the contact methods are almost unusable. That is why in present time numerous studies are devoted to incorporate remote sensing technology for quick and contactless determination of carbon stocks (Goodenough et al., 2005; Mandal and van Laake, 2005; Vicharnakorn et al., 2014). http://dx.doi.org/10.1016/j.ecoinf.2017.08.006 Received 16 February 2017; Received in revised form 17 August 2017; Accepted 29 August 2017 ⁎ Corresponding author. E-mail address: vilem.pechanec@upol.cz (V. Pechanec). Ecological Informatics xxx (xxxx) xxx–xxx 1574-9541/ © 2017 Elsevier B.V. All rights reserved. Please cite this article as: Pechanec, V., Ecological Informatics (2017), http://dx.doi.org/10.1016/j.ecoinf.2017.08.006