Human land use and agriculture in particular are the principle drivers of many of our biggest environmental challenges. At the same time, current food systems fail to provide food security to all consumers or decent livelihoods to all farmers worldwide. This research will help identify ways to use our land better and to move our food system towards enhanced sustainability by examining key knowledge gaps through interdisciplinary, transdisciplinary and cross-scalar research.
Given the importance of agriculture for human well-being and its huge environmental impact, it is sobering to note that the drivers, land management options and practices of truly sustainable agricultural land use are still largely unknown. This is largely due to the still prevalent disciplinary approach to agricultural research, which prevents the identification of interactions and trade-offs between different socio-economic and environmental dimensions of land use. This research will therefore use cutting-edge quantitative and qualitative methods from a range of different disciplines, ranging from local field surveys and farmer interviews, to regional and global data synthesis and modelling studies, to examine holistically the sustainability of different agricultural land use strategies.
Achieving sustainable land use and sustainable food security represents one of the most important societal challenges of the coming decades. Our research will not only address key knowledge gaps, but also contribute to the identification of levers for the sustainable transformation of our food systems through solutions-oriented and transdisciplinary research. By adopting an applied and human-centered research approach our work will examine research questions and provide answers that are directly relevant for different food system actors and policy-makers.
Transforming agricultural land use through marginal gains in the food system.
2019. Global environmental change, 57, 101932. doi:10.1016/j.gloenvcha.2019.101932
Why the US–China trade war spells disaster for the Amazon.
2019. Nature <London>, 567 (7749), 451–454. doi:10.1038/d41586-019-00896-2
Improving remotely-sensed crop monitoring by NDVI-based crop phenology estimators for corn and soybeans in Iowa and Illinois, USA.
2019. Field crops research, 238, 113–128. doi:10.1016/j.fcr.2019.03.015
Achievement of Paris climate goals unlikely due to time lags in the land system.
2019. Nature climate change. doi:10.1038/s41558-019-0400-5
The impact of conservation farming practices on Mediterranean agro-ecosystem services provisioning - meta-analysis [in press].
2019. Regional environmental change. doi:10.1007/s10113-018-1447-y
Evaluation and Calibration of an Agent Based Land use Model Using Remotely Sensed Land Cover and Primary Productivity Data.
2018. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, E, July 22-27, 2018, 7472–7475, IEEE, Piscataway, NJ. doi:10.1109/IGARSS.2018.8518023
Coupled land use and ecological models reveal emergence and feedbacks in socio-ecological systems.
2018. Ecography. doi:10.1111/ecog.04039
Representation of decision-making in European agricultural agent-based models [in press].
2018. Agricultural systems, 167, 143–160. doi:10.1016/j.agsy.2018.09.007
Bright spots in agricultural landscapes: Identifying areas exceeding expectations for multifunctionality and biodiversity.
2018. Journal of applied ecology, 55 (6), 2731–2743. doi:10.1111/1365-2664.13191
Evidence that organic farming promotes pest control.
2018. Nature Sustainability, 1 (7), 361–368. doi:10.1038/s41893-018-0102-4
Empirical evidence for the diffusion of knowledge in land use change.
2018. Journal of land use science, 1–44. doi:10.1080/1747423X.2018.1515995
Monitoring neonicotinoid exposure for bees in rural and peri-urban areas of the UK during the transition from pre- to post-moratorium.
2018. Environmental science & technology, 52 (16), 9391–9402. doi:10.1021/acs.est.7b06573
Impacts of Land Use Change and Summer Monsoon on Nutrients and Sediment Exports from an Agricultural Catchment.
2018. Water, 10 (5), 544. doi:10.3390/w10050544
Food supply and bioenergy production within the global cropland planetary boundary.
2018. (P. C. Struik, Ed.)PLoS one, 13 (3), Art. Nr.: e0194695. doi:10.1371/journal.pone.0194695
Modelling regional cropping patterns under scenarios of climate and socio-economic change in Hungary.
2018. The science of the total environment, 622-623, 1611–1620. doi:10.1016/j.scitotenv.2017.10.038
The future potential for wine production in Scotland under high-end climate change.
2017. Regional environmental change, 1–10. doi:10.1007/s10113-017-1240-3
Behavioral models of climate change adaptation and mitigation in land-based sectors.
2017. Wiley interdisciplinary reviews / Climate change, 8 (2), Art.Nr. e448. doi:10.1002/wcc.448
Relating farmer’s perceptions of climate change risk to adaptation behaviour in Hungary.
2017. Journal of environmental management, 185, 21–30. doi:10.1016/j.jenvman.2016.10.051
To what extent are land resource managers preparing for high-end climate change in Scotland?.
2017. Climatic change, 141 (2), 181–195. doi:10.1007/s10584-016-1881-0
Could consumption of insects, cultured meat or imitation meat reduce global agricultural land use?.
2017. Global food security, 15, 22–32. doi:10.1016/j.gfs.2017.04.001
Losses, inefficiencies and waste in the global food system.
2017. Agricultural systems, 153, 190–200. doi:10.1016/j.agsy.2017.01.014
Scale-dependent effects of landscape composition and configuration on natural enemy diversity, crop herbivory, and yields.
2016. Ecological applications, 26 (2), 448–462. doi:10.1890/15-0856
Mapping Fractional Land Use and Land Cover in a Monsoon Region: The Effects of Data Processing Options.
2016. IEEE journal of selected topics in applied earth observations and remote sensing, 9 (9), 3941–3956. doi:10.1109/JSTARS.2016.2544802
Climate change impact modelling needs to include cross-sectoral interactions.
2016. Nature climate change, 6 (9), 885–890. doi:10.1038/nclimate3039
Crop selection under price and yield fluctuation : Analysis of agro-economic time series from South Korea.
2016. Agricultural systems, 148, 1–11. doi:10.1016/j.agsy.2016.06.003
Land managers’ behaviours modulate pathways to visions of future land systems.
2016. Regional environmental change, 1–15. doi:10.1007/s10113-016-0999-y
Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework.
2016. Earth System Dynamics, 7 (4), 893–915. doi:10.5194/esd-7-893-2016
Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.
2016. Global change biology, 22 (12), 3967–3983. doi:10.1111/gcb.13337
Human appropriation of land for food : The role of diet.
2016. Global environmental change, 41, 88–98. doi:10.1016/j.gloenvcha.2016.09.005
Applying Occam’s razor to global agricultural land use change.
2016. Environmental modelling & software, 75, 212–229. doi:10.1016/j.envsoft.2015.10.015
Pest control of aphids depends on landscape complexity and natural enemy interactions.
2015. PeerJ, 3, e1095. doi:10.7717/peerj.1095
Evaluating potential policies for the UK perennial energy crop market to achieve carbon abatement and deliver a source of low carbon electricity.
2015. Biomass and bioenergy. doi:10.1016/j.biombioe.2015.04.025
Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea.
2014. Hydrology and earth system sciences, 18 (2), 539–557. doi:10.5194/hess-18-539-2014
Deriving a per-field land use and land cover map in an agricultural mosaic catchment.
2014. Earth system science data, 6 (2), 339–352. doi:10.5194/essd-6-339-2014
Identifying the Factors That Influence Farmer Participation in Environmental Management Practices in Switzerland.
2014. Human ecology, 42 (6), 951–963. doi:10.1007/s10745-014-9701-5
Carbon dioxide exchange and biomass productivity of the herbaceous layer of a managed tropical humid savanna ecosystem in western Kenya.
2013. Journal of plant ecology, 6 (4), 286–297. doi:10.1093/jpe/rts038
Natural enemy interactions constrain pest control in complex agricultural landscapes.
2013. Proceedings of the National Academy of Sciences of the United States of America, 110 (14), 5534–5539. doi:10.1073/pnas.1215725110