Benjamin Z. Houlton, Ph.D.
Affiliations: | 2005 | Princeton University, Princeton, NJ |
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"Benjamin Houlton"Parents
Sign in to add mentor| Lars O. Hedin | grad student | 2005 | Princeton | |
| (Isotopic evidence for the climate dependence of nitrogen cycles across old tropical rainforests, Mt. Haleakala, Hawaii.) | ||||
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Publications
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| Feng M, Peng S, Wang Y, et al. (2023) Overestimated nitrogen loss from denitrification for natural terrestrial ecosystems in CMIP6 Earth System Models. Nature Communications. 14: 3065 |
| Tao F, Huang Y, Hungate BA, et al. (2023) Microbial carbon use efficiency promotes global soil carbon storage. Nature |
| Yang Q, Liu Z, Houlton BZ, et al. (2022) Isotopic evidence for increased carbon and nitrogen exchanges between peatland plants and their symbiotic microbes with rising atmospheric CO concentrations since 15,000 cal. year BP. Global Change Biology |
| Song W, Liu XY, Houlton BZ, et al. (2022) Isotopic constraints confirm the significant role of microbial nitrogen oxides emissions from the land and ocean environment. National Science Review. 9: nwac106 |
| Wang M, Houlton BZ, Wang S, et al. (2021) Human-caused increases in reactive nitrogen burial in sediment of global lakes. Innovation (New York, N.Y.). 2: 100158 |
| Khalsa SDS, Smart DR, Muhammad S, et al. (2020) Intensive fertilizer use increases orchard N cycling and lowers net global warming potential. The Science of the Total Environment. 722: 137889 |
| Dynarski KA, Houlton BZ. (2020) Isotopic constraints on plant nitrogen acquisition strategies during ecosystem retrogression. Oecologia |
| Xu P, Chen A, Houlton BZ, et al. (2020) Spatial Variation of Reactive Nitrogen Emissions From China's Croplands Codetermined by Regional Urbanization and Its Feedback to Global Climate Change Geophysical Research Letters. 47 |
| Peng J, Wang Y, Houlton BZ, et al. (2020) Global Carbon Sequestration Is Highly Sensitive to Model‐Based Formulations of Nitrogen Fixation Global Biogeochemical Cycles. 34 |
| Sena‐Souza JP, Houlton BZ, Martinelli LA, et al. (2020) Reconstructing continental‐scale variation in soil δ15N: a machine learning approach in South America Ecosphere. 11 |