Publications in 2022

  1. Adebiyi, J. A., & Olabisi, L. S. (2022). Participatory causal loop mapping of the adoption of organic farming in Nigeria. Environmental Management, 69(2), 410–428. doi:10.1007/s00267-021-01580-w  
  2. Arantes, C. C., Laufer, J., Pinto, M. D., Moran, E. F., Lopez, M. C., Dutka‐Gianelli, J., … Doria, C. R. C. (2022). Functional responses of fisheries to hydropower dams in the Amazonian floodplain of the Madeira River. Journal of Applied Ecology, 59(3), 680–692. doi:10.1111/1365-2664.14082  
  3. Brown, E., Johansen, I. C., Bortoleto, A. P., Pokhrel, Y., Chaudhari, S., Cak, A., … Moran, E. (2022). Feasibility of hybrid in-stream generator–photovoltaic systems for Amazonian off-grid communities. PNAS Nexus, 1(3). doi:10.1093/pnasnexus/pgac077  
  4. Carrera, J. S. (2022). Deconstructing citizenship and the growth of Detroit’s Green Renaissance. Journal of Political Ecology, 29(1). doi:10.2458/jpe.2829  
  5. Chen, C., Dietz, T., Fefferman, N. H., Greig, J., Cetin, K., Robinson, C., … Fu, R. (2022). Extreme events, Energy Security and equality through micro- and macro-levels: Concepts, challenges and methods. Energy Research & Social Science, 85, 102401. doi:10.1016/j.erss.2021.102401  
  6. Chen, J., John, R., Yuan, J., Mack, E. A., Groisman, P., Allington, G., … Qi, J. (2022). Sustainability challenges for the social-environmental systems across the Asian Drylands Belt. Environmental Research Letters, 17(2), 023001. doi:10.1088/1748-9326/ac472f  
  7. Chen, J., Ouyang, Z., John, R., Henebry, G. M., Groisman, P. Ya., Karnieli, A., … Gutman, G. (2020). Social-ecological systems across the Asian Drylands Belt (ADB). Landscape Series, 191–225. doi:10.1007/978-3-030-30742-4_10  
  8. Chen, S., Zhu, S., Wen, X., Shao, H., He, C., Qi, J., … Liu, S. (2022). Mapping potential soil water erosion and flood hazard zones in the Yarlung Tsangpo River Basin, China. Atmosphere, 14(1), 49. doi:10.3390/atmos14010049  
  9. Chen, Z., Yin, L., Zhang, W., Peng, A., Sallach, J. B., Luo, Y., & Li, H. (2022). NaCl salinity enhances tetracycline bioavailability to escherichia coli on agar surfaces. Chemosphere, 302, 134921. doi:10.1016/j.chemosphere.2022.134921  
  10. Cheng, P., Zhang, W., Zhao, X., Yang, B., & Gao, Y. (2022). Nano-goethite-mediated transformation of anthracene derivatives under low moisture conditions. Environmental Science: Nano, 9(1), 289–301. doi:10.1039/d1en00570g  
  11. Clevenger, K. A., Pfeiffer, K. A., & Pearson, A. L. (2022). Using linked accelerometer and GPS data for Characterizing Children’s Schoolyard physical activity: An overview of Hot Spot Analytic decisions with reporting guidelines. Spatial and Spatio-Temporal Epidemiology, 43, 100548. doi:10.1016/j.sste.2022.100548  
  12. Creutzig, F., Nielsen, K. S., Dietz, T., Stern, P., Shwom, R., & Vandenbergh, M. (2022). Social Science Is Key to Effective Climate Change Mitigation: A Reply to Nature Editorial. doi:10.31234/  
  13. De Biasi, A., Carr, J., Almanza, M., & Zwickle, A. (2021). A micro-place evaluation of the relationship between ‘risky places’ and risk perceptions. Journal of Risk Research, 25(4), 520–535. doi:10.1080/13669877.2021.2001672  
  14. Djenontin, I. N., Ligmann-Zielinska, A., & Zulu, L. C. (2022). Landscape-scale effects of farmers’ restoration decision making and investments in Central Malawi: An agent-based modeling approach. Journal of Land Use Science, 17(1), 281–306. doi:10.1080/1747423x.2022.2076948  
  15. Duan, R., Zwickle, A., & Takahashi, B. (2021). Refining the application of construal level theory: Egocentric and nonegocentric psychological distances in climate change visual communication. Environmental Communication, 16(1), 92–107. doi:10.1080/17524032.2021.1964999  
  16. Elkouk, A., Pokhrel, Y., Luo, L., Payton, E., Livneh, B., & Cheng, Y. (2022). Mechanistic Drivers of Runoff Sensitivity to Temperature in the Community Land Model: A Study on the Upper Colorado River Basin . AGU Fall Meeting Abstracts, 2022 
  17. Fan, P., Chen, J., Fung, C., Naing, Z., Ouyang, Z., Nyunt, K. M., … Peter, B. G. (2022). Urbanization, economic development, and environmental changes in transitional economies in the Global South: A case of Yangon. Ecological Processes, 11(1). doi:10.1186/s13717-022-00409-6  
  18. Fan, P., Cho, M. S., Lin, Z., Ouyang, Z., Qi, J., Chen, J., & Moran, E. F. (2022). Recently constructed hydropower dams were associated with reduced economic production, population, and Greenness in nearby areas. Proceedings of the National Academy of Sciences, 119(8). doi:10.1073/pnas.2108038119  
  19. Ferguson, D. P., Leszczynski, E. C., Horton, T. H., Pfeiffer, K. A., Gardiner, J., & Pearson, A. L. (2022). C-reactive protein and telomerase reverse transcriptase (TERT) associate with chronic disease markers in a sample from low-income neighborhoods in Detroit, Michigan. Sports Medicine and Health Science, 4(4), 275–279. doi:10.1016/j.smhs.2022.07.002  
  20. Frank, K. A., Lin, Q., Maroulis, S., Mueller, A. S., Xu, R., Rosenberg, J. M., … Zhang, L. (2022). Response to “Three comments on the RIR method.” Journal of Clinical Epidemiology, 146, 124–127. doi:10.1016/j.jclinepi.2022.01.020  
  21. Gage, R., Chambers, T., Smith, M., McKerchar, C., Puloka, V., Pearson, A. L., … Signal, L. (2022). Children’s perspectives on the wicked problem of child poverty in Aotearoa New Zealand: a wearable camera study . The New Zealand Medical Journal, 135(1559).  
  22. Galib, A. H., McDonald, A., Wilson, T., Luo, L., & Tan, P.-N. (2022). Deepextrema: A deep learning approach for forecasting block Maxima in time series data. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. doi:10.24963/ijcai.2022/413  
  23. Gao, F., Shen, Y., Brett Sallach, J., Li, H., Zhang, W., Li, Y., & Liu, C. (2022). Predicting crop root concentration factors of organic contaminants with machine learning models. Journal of Hazardous Materials, 424, 127437. doi:10.1016/j.jhazmat.2021.127437  
  24. Gao, F., Zhang, W., Baccarelli, A. A., & Shen, Y. (2022). Predicting chemical ecotoxicity by Learning Latent Space Chemical Representations. Environment International, 163, 107224. doi:10.1016/j.envint.2022.107224  
  25. Gunathilaka, G. U., He, J., Li, H., Zhang, W., & Ryser, E. T. (2022). Behavior of silver nanoparticles in chlorinated Lettuce Wash Water. Journal of Food Protection, 85(7), 1061–1068. doi:10.4315/jfp-22-018  
  26. Hamm, J. A., & colleagues. (2022). (Re)organizing legitimacy theory. CrimRxiv. doi:10.21428/cb6ab371.eab5fe6a  
  27. Hamm, J. A., Cavanagh, C., & Lee, S. (2022). Pushing past the plateau. Legal and Criminological Psychology, 27(2), 166–169. doi:10.1111/lcrp.12215  
  28. He, J., Zhang, L., He, S. Y., Ryser, E. T., Li, H., & Zhang, W. (2022). Stomata facilitate foliar sorption of silver nanoparticles by Arabidopsis thaliana. Environmental Pollution, 292, 118448. doi:10.1016/j.envpol.2021.118448  
  29. He, S., Shao, H., Xian, W., Yin, Z., You, M., Zhong, J., & Qi, J. (2022). Monitoring cropland abandonment in hilly areas with sentinel-1 and sentinel-2 timeseries. Remote Sensing, 14(15), 3806. doi:10.3390/rs14153806  
  30. Ishaq, S. L., Wissel, E. F., Wolf, P. G., Grieneisen, L., Eggleston, E. M., Mhuireach, G., … Hosler, S. (2022). Designing the microbes and Social Equity Symposium: A novel interdisciplinary virtual research conference based on achieving group-directed outputs. Challenges, 13(2), 30. doi:10.3390/challe13020030  
  31. Jia, D., Zhang, R., Shao, J., Zhang, W., Cai, L., & Sun, W. (2022). Exposure to trace levels of metals and fluoroquinolones increases inflammation and tumorigenesis risk of zebrafish embryos. Environmental Science and Ecotechnology, 10, 100162. doi:10.1016/j.ese.2022.100162  
  32. Jin, D., Yan, R., Li, L., Qi, J., Chen, J., Xu, H., … Xin, X. (2022). Stocking rate changed the magnitude of carbon sequestration and flow within the plant-soil system of a meadow steppe ecosystem. Plant and Soil, 473(1–2), 33–47. doi:10.1007/s11104-021-05213-3  
  34. Lan, X., Luo, L., & Xu, Z. (2022). Long-term Temperature Change in a Lake under Climate Change . AGU Fall Meeting Abstracts, 2022 
  35. Lee, S. U., Hamm, J., & Lee, Y. H. (2022). Instrumental and normative pathways to police legitimacy: Why do people cooperate with the police? Policing: An International Journal, 45(5), 812–827. doi:10.1108/pijpsm-03-2022-0037  
  36. Li, Y., Sallach, J. B., Zhang, W., Boyd, S. A., & Li, H. (2022). Characterization of plant accumulation of pharmaceuticals from soils with their concentration in soil pore water. Environmental Science & Technology, 56(13), 9346–9355. doi:10.1021/acs.est.2c00303  
  37. Li, Z., Yang, Q., Yang, X., Ouyang, Z., Cai, X., & Qi, J. (2022). Assessing farmers’ attitudes towards rural land circulation policy changes in the Pearl River Delta, China. Sustainability, 14(7), 4297. doi:10.3390/su14074297  
  38. Lin, Q., Frank, K. A., Xu, R., Mueller, A. S., & Dietz, T. (2022). Robustness of Inference to Replacement Using the Konfound R Package  
  39. Ling, W., Ma, B., & Zhang, W. (2022). Rhizosphere microbiology: Toward a clean and healthy soil environment. Frontiers in Microbiology, 13. doi:10.3389/978-2-88976-939-1  
  40. Liu, W., Gage, R., Park, H., Pearson, A. L., Chambers, T., Smith, M., … Signal, L. (2022). The distribution of harmful product marketing in public outdoor spaces and the effectiveness of marketing bans. Health & Place, 76, 102861. doi:10.1016/j.healthplace.2022.102861  
  41. Margerum, R. D., Zwickle, A., Bruce, J., & Thomas, C. (2022). The effects of Enhanced Information Utilization in collaborative Hazard Mitigation Planning. Journal of the American Planning Association, 88(4), 464–478. doi:10.1080/01944363.2021.1997352  
  42. Matthews, A. D., Costa, G. H., Erickson, K., Pfeiffer, K. A., Pearson, A. L., & Dougherty, B. V. (2022). Community Members’ Perspectives on a Community-Engaged Process for Supporting Vibrant Greenspaces in Detroit. . Journal of Community Engagement and Higher Education, 14(4), 26–41.  
  43. Mayer, A., García, M. A., Castro-Diaz, L., Lopez, M. C., & Moran, E. F. (2022). Pretend participation: Procedural injustices in the Madeira Hydroelectric Complex. Global Environmental Change, 75, 102524. doi:10.1016/j.gloenvcha.2022.102524  
  44. Mayer, A., Lopez, M. C., & Moran, E. F. (2022). Uncompensated losses and damaged livelihoods: Restorative and distributional injustices in Brazilian hydropower. Energy Policy, 167, 113048. doi:10.1016/j.enpol.2022.113048  
  45. Mayer, A., Lopez, M. C., Cavallini Johansen, I., & Moran, E. (2021). Hydropower, social capital, Community Impacts, and self‐rated health in the Amazon*. Rural Sociology, 87(2), 393–426. doi:10.1111/ruso.12419  
  46. Mayer, A., Lopez, M. C., Leturcq, G., & Moran, E. (2022). Changes in social capital associated with the construction of the Belo Monte Dam: Comparing a resettled and a host community. Human Organization, 81(1), 22–34. doi:10.17730/1938-3525-81.1.22  
  47. McDonald, A., Tan, P.-N., & Luo, L. (2022). Comet flows: Towards generative modeling of multivariate extremes and tail dependence. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. doi:10.24963/ijcai.2022/462  
  48. Moran, E. F. (2022). Human Adaptability: An Introduction to Ecological Anthropology  
  49. Moran, E. F., Lopez, M. C., Mourao, R., Brown, E., McCright, A. M., & Walgren, J. (2022). Advancing convergence research: Renewable energy solutions for off-grid communities . Proceedings of the National Academy of Sciences, 119(49).  
  50. Mungai, L. M., Messina, J. P., Zulu, L. C., Qi, J., & Snapp, S. (2022). Modeling spatiotemporal patterns of land use/land cover change in central Malawi using a neural network model. Remote Sensing, 14(14), 3477. doi:10.3390/rs14143477  
  51. Olabisi, L. S., Sidibé, A., Assan, E., Adebiyi, J., Totin, E., & Thompson-Hall, M. (2022). Building consensus and increasing self-efficacy: Participatory scenarios as a tool for developing food security solutions in West Africa. Regional Environmental Change, 22(1). doi:10.1007/s10113-022-01893-4  
  52. Ouma, Y. O., Moalafhi, D. B., Anderson, G., Nkwae, B., Odirile, P., Parida, B. P., & Qi, J. (2022). Dam water level prediction using vector autoregression, random forest regression and MLP-ann models based on land-use and climate factors. Sustainability, 14(22), 14934. doi:10.3390/su142214934  
  53. Ouma, Y. O., Moalahi, D., Anderson, G., Nkwae, B., Odirile, P., Parida, B., … Qi, J. (2022). Predicting the variability of dam water levels with land-use and climatic factors using random forest and vector autoregression models. Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV. doi:10.1117/12.2635933  
  54. Ouma, Y., Nkwae, B., Moalafhi, D., Odirile, P., Parida, B., Anderson, G., & Qi, J. (2022). Comparison of machine learning classifiers for multitemporal and multisensor mapping of Urban LULC features. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B3-2022, 681–689. doi:10.5194/isprs-archives-xliii-b3-2022-681-2022  
  55. Pearson, A. L., Shewark, E. A., & Burt, S. A. (2022). Associations between neighborhood built, social, or toxicant conditions and child externalizing behaviors in the Detroit metro area: A cross-sectional study of the neighborhood ‘exposome.’ BMC Public Health, 22(1). doi:10.1186/s12889-022-13442-z  
  56. Pokhrel, Y., Elkouk, A., Livneh, B., Luo, L., Payton, E. A., & Clifford, K. R. (2022). A systems modeling approach to examine water and environmental sustainability pathways in the southwestern US . Chapman Conference on Solving Water Availability Challenges through an Interdisciplinary Framework 
  57. Pokhrel, Y., Shin, S., Yamazaki, D., Lin, Z., & Qi, J. (2019). Changes in Flood Dynamics in the Lower Mekong River Basin Due to Upstream Flow Regulation. doi:10.1002/essoar.10500604.1  
  58. Qi, J., Pueppke, S., Cho, M. S., Xie, Y., Navanugraha, C., & Makathy, T. (2022). The role of land in the water-energy-food nexus. Exploring Policy Coherence in Indias Electricity-Water Nexus, 291–306. doi:10.4337/9781839100550.00023  
  59. Qin, R., Zhang, F., Yu, C., Zhang, Q., Qi, J., & Li, F. (2022). Contributions made by rain-fed potato with mulching to food security in China. European Journal of Agronomy, 133, 126435. doi:10.1016/j.eja.2021.126435  
  60. Radonic, L., Jacob, C., Kalman, R., & Lewis, E. Y. (2022). Questionable Quality: Using Photovoice to Document Women’s Experiences of Water Insecurity in Flint, USA . Case Studies in the Environment, 6(1).  
  61. Ren, T., Xu, H., Cai, X., Yu, S., & Qi, J. (2022). Smallholder crop type mapping and rotation monitoring in mountainous areas with sentinel-1/2 imagery. Remote Sensing, 14(3), 566. doi:10.3390/rs14030566  
  62. Reuben, A., Moffitt, T. E., Abraham, W. C., Ambler, A., Elliott, M. L., Hariri, A. R., … Caspi, A. (2022). Improving risk indexes for alzheimer’s disease and related Dementias for use in midlife. Brain Communications, 4(5). doi:10.1093/braincomms/fcac223  
  63. Sanciangco, J. C., Breetzke, G. D., Lin, Z., Wang, Y., Clevenger, K. A., & Pearson, A. L. (2021). The relationship between city “greenness” and homicide in the US: Evidence over a 30-year period. Environment and Behavior, 54(2), 538–571. doi:10.1177/00139165211045095  
  64. Seyd, B., Jennings, W., & Hamm, J. (2022). People who trust scientists are more likely to get a COVID vaccine. So what traits make scientists trustworthy? . LSE COVID-19 Blog 
  65. Shen, Y., Zhao, E., Zhang, W., Baccarelli, A. A., & Gao, F. (2022). Predicting pesticide dissipation half-life intervals in plants with machine learning models. Journal of Hazardous Materials, 436, 129177. doi:10.1016/j.jhazmat.2022.129177  
  66. Stern, P. C., Dietz, T., & Vandenbergh, M. P. (2022). The science of mitigation: Closing the gap between potential and actual reduction of environmental threats. Energy Research & Social Science, 91, 102735. doi:10.1016/j.erss.2022.102735  
  67. Stoler, J., Pearson, A. L., Rosinger, A. Y., & Lee, A. E. (2022). The role of water in environmental migration . Wiley Interdisciplinary Reviews: Water, 9(3).  
  68. Tao, Y., Tao, Q., Sun, X., Qiu, J., Pueppke, S. G., Ou, W., … Qi, J. (2022). Mapping Ecosystem Service Supply and demand dynamics under rapid urban expansion: A case study in the Yangtze River Delta of China. Ecosystem Services, 56, 101448. doi:10.1016/j.ecoser.2022.101448  
  69. Taufique, K. M., Nielsen, K. S., Dietz, T., Shwom, R., Stern, P. C., & Vandenbergh, M. P. (2022). Revisiting the promise of Carbon Labelling. Nature Climate Change, 12(2), 132–140. doi:10.1038/s41558-021-01271-8  
  70. Van Fossen, J. A., Ropp, J. W., Darcy, K., & Hamm, J. A. (2022). Comfort with and willingness to participate in COVID-19 contact tracing: The role of risk perceptions, trust, and political ideology. Social Science & Medicine, 306, 115174. doi:10.1016/j.socscimed.2022.115174  
  71. Wang, W., Rhodes, G., Zhang, W., Yu, X., Teppen, B. J., & Li, H. (2022). Implication of cation-bridging interaction contribution to sorption of perfluoroalkyl carboxylic acids by soils. Chemosphere, 290, 133224. doi:10.1016/j.chemosphere.2021.133224  
  72. Webster, D., Aytur, S., Axelrod, M., Wilson, R., Hamm, J., Sayed, L., … Young, O. (2022). Learning from the past: Pandemics and the governance treadmill. Sustainability, 14(6), 3683. doi:10.3390/su14063683  
  73. Whitehead, J., Pearson, A. L., Lawrenson, R., & Atatoa Carr, P. (2020). Selecting health need indicators for spatial equity analysis in the New Zealand Primary Care Context. The Journal of Rural Health, 38(1), 194–206. doi:10.1111/jrh.12519  
  74. Wilson, T., McDonald, A., Galib, A. H., Tan, P.-N., & Luo, L. (2022). Beyond point prediction: Capturing Zero-inflated & heavy-tailed spatiotemporal data with deep extreme mixture models. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. doi:10.1145/3534678.3539464  
  75. Wilson, T., Tan, P.-N., & Luo, L. (2022). DeepGPD: A deep learning approach for modeling Geospatio-temporal extreme events. Proceedings of the AAAI Conference on Artificial Intelligence, 36(4), 4245–4253. doi:10.1609/aaai.v36i4.20344  
  76. Wutich, A., Beresford, M., Montoya, T., Radonic, L., & Workman, C. (2022). Water security and scarcity. Oxford Research Encyclopedia of Anthropology. doi:10.1093/acrefore/9780190854584.013.475  
  77. Xia, S., Shao, H., Wang, H., Xian, W., Shao, Q., Yin, Z., & Qi, J. (2022). Spatio-temporal dynamics and driving forces of multi-scale CO2 emissions by integrating DMSP-OLS and NPP-VIIRS DATA: A case study in Beijing-tianjin-hebei, China. Remote Sensing, 14(19), 4799. doi:10.3390/rs14194799  
  78. Xie, Y., Qi, J., Zhang, R., Jiao, X., Shirkey, G., & Ren, S. (2022). Toward a carbon-neutral state: A carbon–energy–water nexus perspective of China’s coal power industry. Energies, 15(12), 4466. doi:10.3390/en15124466  
  79. Yang, H., Dietz, T., Li, Y., Dou, Y., Wang, Y., Huang, Q., … Liu, J. (2022). Unraveling human drivers behind complex interrelationships among Sustainable Development Goals: A demonstration in a flagship protected area. Ecology and Society, 27(3). doi:10.5751/es-13275-270315  
  80. Yang, H., Ligmann-Zielinska, A., Dou, Y., Chung, M. G., Zhang, J., & Liu, J. (2022). Complex effects of telecouplings on Forest Dynamics: An agent-based modeling approach. Earth Interactions, 26(1), 15–27. doi:10.1175/ei-d-20-0029.1  
  81. Zhang, F., Zeng, B., Cao, Y., Li, F., Tang, Z., & Qi, J. (2022). Human activities have markedly altered the pattern and trend of net primary production in the Ili River basin of Northwest China under current climate change. Land Degradation & Development, 33(14), 2585–2595. doi:10.1002/ldr.4334  
  82. Zhang, S., Shao, H., Li, X., Xian, W., Shao, Q., Yin, Z., … Qi, J. (2022). Spatiotemporal dynamics of ecological security pattern of urban agglomerations in Yangtze River Delta based on Lucc Simulation. Remote Sensing, 14(2), 296. doi:10.3390/rs14020296