Vera Laetitia Mulder
AgreenSkills session, year: 2nd session, 2013
Receiving laboratory: Infosol, Orléans, France
Country of origin : Netherlands
Determining the main controlling factors of subsoil organic carbon for modeling the subsoil carbon storage and its spatial distribution
The role of soils in carbon sequestration and emissions takes a key position in understanding global environmental change. Modeling these changes is necessary for mitigating climate change and requires up-to-date information of soil organic carbon (SOC) over vast areas. Recently, research focused on determining the controlling factors for topsoil SOC and modeling the spatial distribution at various scales. Unfortunately, the subsoil SOC reservoir is, currently, not well modeled.
Within this context, the research foci are (1) determining the controlling factors of SOC in relation to soil depth and, subsequently, spatial modeling of SOC in relation to soil depth for France.
Titia Mulder was born on 26 January 1984 in Delft, the Netherlands. In 2006, she obtained her BSc Soil, Water & Atmosphere, with a minor in Geo-Information Science and Remote Sensing at Wageningen University, the Netherlands. She continued her studies at Wageningen University and obtained her MSc in Soil Science, specializing in Land Dynamics and a minor MSc degree in Geo-Information Science and Remote Sensing (2008). She finalized her studies with an internship at the European Space Research Institute of the European Space Agency (ESA/ESRIN), located in Frascati, Italy. Here, she contributed to the project DesertWatch focusing on satellite retrieved soil moisture as indicator for desertification. Next, she obtained her PhD entitled: Spectroscopy-supported digital soil mapping at Wageningen University, in close collaboration with the Remote Sensing Laboratory, Zurich University (2013).
Having a background in physical geography with a focus on soil science, she is interested in the soil-landscape processes in relation to the spatial variability of various natural resources. In her PhD, she worked on spatial modelling of such processes and mapping natural resources on a regional scale, thereby, fully utilizing the use of remote and proximal sensing data combined with geo-statistical methods. In her current position, as postdoctoral researcher at the INRA Infosol unit, she focuses on mapping the subsoil carbon storage of France. Her work has been part of the e-SOTER (2008-2012), GIS-Sol (ongoing) and GlobalSoilMap (ongoing) projects.
Peer reviewed journals
Mulder, V.L., Lacoste, M., Martin, M., Richer de Forges, A., Arrouays, D., (2015). Understanding large-extent controls of soil organic carbon storage in relation to soil depth and soil- landscape systems. Global Biogeochemical Cycles, 29.
Mulder, V.L., Lacoste, M., Richer-de-Forges, A.C., Martin, M.P., Arrouays, D., (In Press). National versus global modelling the 3D distribution of soil organic carbon in mainland France Geoderma, DOI 10.1016/j.geoderma.201508035.
Mulder, V.L., de Bruin, S., Weyermann, J., Kokaly,R., Schaepman, M.E., (2013). Characterizing regional soil mineral composition using spectroscopy and geostatistics. Remote Sensing of Environment, (139), 415-429.
Mulder, V.L., de Bruin, S., Schaepman, M.E.; Mayr, T. (2011). The use of remote sensing in soil and terrain mapping – A review. Geoderma 162, (1-2), 1-19.
Other scientific publications
Mulder, V.L., Lacoste, M., Saby, N.P.A., Arrouays, D., (2015). Large-extent digital soil mapping approaches for tota soil depth. EGU General Assembly Conference, 12-17 April 2015 – Vienna, Austria.
Mulder, V.L., (2015). Pedometrics and large-extent digital soil mapping applications. Pedometrics 2015, 14-18 September 2015 – Cordoba, Spain.
Wulf, H., Mulder, V.L., Schaepman, M.E., Keller, A., Jörg, P., (2014). Remote Sensing of Soils. Technical report no. 00.0338.PZ / L435-0501, Zurich, Switzerland, 71p.
Mulder, V.L., (2013). Spectroscopy-supported digital soil mapping. PhD thesis, Wageningen University, 188 pp.
IUSS Pedometrics “Best Paper Award” for 2014: Mulder, V.L., Plötze, M., de Bruin, S., Schaepman, M.E., Mavris, C., Kokaly, R., Egli, M., (2014). Quantifying mineral abundances of complex mixtures by coupling spectral deconvolution of SWIR spectra (2.1-2.4 µm) and regression tree analysis. Geoderma, (107-108), 279-290.
IUSS Pedometrics “Best Paper Award” for 2014 nomination: Mulder, V.L., de Bruin, S., Weyermann, J., Kokaly,R., Schaepman, M.E., (2013). Characterizing regional soil mineral composition using spectroscopy and geostatistics. Remote Sensing of Environment, (139), 415-429.
Geoderma “Best Paper Award” for 2014: Mulder, V.L., Plötze, M., de Bruin, S., Schaepman, M.E., Mavris, C., Kokaly, R., Egli, M., (2014). Quantifying mineral abundances of complex mixtures by coupling spectral deconvolution of SWIR spectra (2.1-2.4 µm) and regression tree analysis. Geoderma, (107-108), 279-290.
Website(s): http://www.val-de-loire.inra.fr | https://www.researchgate.net/profile/VL_Mulder/ | http://www.gissol.fr | http://www.globalsoilmap.net | http://www.linkedin.com/pub/v-l-titia-mulder/20/839/430