Calum Brown researches the processes that cause change in land management and ecosystems. He uses statistical and computational methods to try and understand these processes, and to explore how they might develop in the future. His background is in physics and ecology, and his PhD was on the ecology of tropical rainforests. He still works on forest ecology, but now mainly focuses on human land use and its interactions with climate change. This work involves modelling the ways in which land management decisions are made, attempting to build on knowledge of underlying social and environmental processes.
Telephone: +49 8821 183 190
Publications Calum Brown
Knowledge sharing, problem solving and professional development in a Scottish Ecosystem Services Community of Practice [in press].
2019. Regional environmental change. doi:10.1007/s10113-019-01537-0
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
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
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
Modelling dynamic effects of multi-scale institutions on land use change.
2018. Regional environmental change. doi:10.1007/s10113-018-1424-5
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
Reviewing the evidence base for the effects of woodland expansion on biodiversity and ecosystem services in the United Kingdom.
2018. Forest ecology and management, 430, 366–379. doi:10.1016/j.foreco.2018.08.003
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
Contrasting effects of space and environment on functional and phylogenetic dissimilarity in a tropical forest.
2018. Journal of plant ecology, 12 (2), 314–326. doi:10.1093/jpe/rty026
Green Gold to Wild Woodlands; understanding stakeholder visions for woodland expansion in Scotland [in press].
2018. Landscape ecology. doi:10.1007/s10980-018-0674-4
Improving the representation of adaptation in climate change impact models.
2018. Regional environmental change. doi:10.1007/s10113-018-1328-4
Bridging uncertainty concepts across narratives and simulations in environmental scenarios [in press].
2018. Regional environmental change, 1–12. doi:10.1007/s10113-018-1338-2
Intra-specific relatedness, spatial clustering and reduced demographic performance in tropical rainforest trees.
2018. Ecology letters. doi:10.1111/ele.13086
A taxonomic, functional, and phylogenetic perspective on the community assembly of passerine birds along an elevational gradient in southwest China.
2018. Ecology and evolution, 8 (5), 2712–2720. doi:10.1002/ece3.3910
Lack of phylogenetic signals within environmental niches of tropical tree species across life stages.
2017. Scientific reports, 7, 42007. doi:10.1038/srep42007
Snow damage to the canopy facilitates alien weed invasion in a subtropical montane primary forest in southwestern China.
2017. Forest ecology and management, 391, 275–281. doi:10.1016/j.foreco.2017.02.031
Can we be certain about future land use change in Europe? A multi-scenario, integrated-assessment analysis.
2017. Agricultural systems, 151, 126–135. doi:10.1016/j.agsy.2016.12.001
The effect of forest owner decision-making, climatic change and societal demands on land-use change and ecosystem service provision in Sweden.
2017. Ecosystem Services, 23, 174–208. doi:10.1016/j.ecoser.2016.12.003
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
The relative importance of subjective and structural factors for individual adaptation to climate change by forest owners in Sweden.
2017. Regional environmental change, 1–10. doi:10.1007/s10113-017-1218-1
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
The importance of socio-ecological system dynamics in understanding adaptation to global change in the forestry sector.
2017. Journal of environmental management, 196, 36–47. doi:10.1016/j.jenvman.2017.02.066
Losses, inefficiencies and waste in the global food system.
2017. Agricultural systems, 153, 190–200. doi:10.1016/j.agsy.2017.01.014
A model of environmental institutions and their adaptive actions in the Swedish forestry sector.
2016. Environmental science & policy
Uncertainty: Lessons Learned for Climate Services.
2016. Bulletin of the American Meteorological Society, 97 (12), ES265–ES269. doi:10.1175/BAMS-D-16-0173.1
Success of spatial statistics in determining underlying process in simulated plant communities.
2016. Journal of ecology, 104 (1), 160–172. doi:10.1111/1365-2745.12493
Land managers’ behaviours modulate pathways to visions of future land systems.
2016. Regional environmental change, 1–15. doi:10.1007/s10113-016-0999-y
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
Assessing uncertainties in land cover projections.
2016. Global change biology, 23 (2), 767–781. doi:10.1111/gcb.13447
Analysing uncertainties in climate change impact assessment across sectors and scenarios.
2015. Climatic change, 128 (3-4), 293–306. doi:10.1007/s10584-014-1133-0
Characterising forest owners through their objectives, attributes and management strategies.
2015. European journal of forest research, 134 (6), 1027–1041. doi:10.1007/s10342-015-0907-x
From meta-studies to modeling: Using synthesis knowledge to build broadly applicable process-based land change models.
2015. Environmental modelling & software, 72, 10–20. doi:10.1016/j.envsoft.2015.06.009
Experiments in Globalisation, Food Security and Land Use Decision Making.
2014. PLoS one, 9 (12), Art.Nr. e114213. doi:10.1371/journal.pone.0114213
Combining agent functional types, capitals and services to model land use dynamics.
2014. Environmental modelling & software, 59, 187–201. doi:10.1016/j.envsoft.2014.05.019
Global models of human decision-making for land-based mitigation and adaptation assessment.
2014. Nature climate change, 4, 550–557. doi:10.1038/NCLIMATE2250
Multispecies coexistence of trees in tropical forests: spatial signals of topographic niche differentiation increase with environmental heterogeneity.
2013. Proceedings of the Royal Society of London / B, 280 (1764), 20130502. doi:10.1098/rspb.2013.0502
Linking ecological processes with spatial and non-spatial patterns in plant communities.
2011. Journal of ecology, 99 (6), 1402–1414. doi:10.1111/j.1365-2745.2011.01877.x