Diana Moanga is a Lecturer and the Manager of the Spatial Analysis Center in the Stanford Doerr School of Sustainability. She teaches the Remote Sensing of Land class and the Fundamentals of Geographic Information Science class. Her research includes studying land use land cover change processes using remote sensing and spatial analysis, focusing on the effects of environmental and anthropogenic stressors on coastal socio-environmental systems. She is particularly passionate about furthering our understating of climate equity for coastal communities and mapping coastal hazards at various scales. She has a Ph.D. in Environmental Science Policy and Management from UC Berkeley in 2020. Her dissertation research used geospatial techniques to study land use and land cover changes across California. Specifically, her research explored management impacts on California’s coastal lands, agricultural transitions in the Central Valley, and wildfire activity under future climate regimes. Diana also earned a Master’s in Science in Marine Affairs and Policy from the University of Miami in 2015. For her master's research she examined the spatial and temporal characteristics of harmful algal blooms and studied coastal zone management and coral conservation.

Academic Appointments

Professional Education

  • BA, University of Miami, Marine Affairs (2013)
  • MS, University of Miami, Marine Affairs and Policy (2015)
  • PhD, University of California Berkeley, Environmental Science Policy and Management (2020)

2023-24 Courses

All Publications

  • A cloudy forecast for species distribution models: Predictive uncertainties abound for California birds after a century of climate and land-use change. Global change biology Clare, J. D., de Valpine, P., Moanga, D. A., Tingley, M. W., Beissinger, S. R. 2023: e17019


    Correlative species distribution models are widely used to quantify past shifts in ranges or communities, and to predict future outcomes under ongoing global change. Practitioners confront a wide range of potentially plausible models for ecological dynamics, but most specific applications only consider a narrow set. Here, we clarify that certain model structures can embed restrictive assumptions about key sources of forecast uncertainty into an analysis. To evaluate forecast uncertainties and our ability to explain community change, we fit and compared 39 candidate multi- or joint species occupancy models to avian incidence data collected at 320 sites across California during the early 20th century and resurveyed a century later. We found massive (>20,000 LOOIC) differences in within-time information criterion across models. Poorer fitting models omitting multivariate random effects predicted less variation in species richness changes and smaller contemporary communities, with considerable variation in predicted spatial patterns in richness changes across models. The top models suggested avian environmental associations changed across time, contemporary avian occupancy was influenced by previous site-specific occupancy states, and that both latent site variables and species associations with these variables also varied over time. Collectively, our results recapitulate that simplified model assumptions not only impact predictive fit but may mask important sources of forecast uncertainty and mischaracterize the current state of system understanding when seeking to describe or project community responses to global change. We recommend that researchers seeking to make long-term forecasts prioritize characterizing forecast uncertainty over seeking to present a single best guess. To do so reliably, we urge practitioners to employ models capable of characterizing the key sources of forecast uncertainty, where predictors, parameters and random effects may vary over time or further interact with previous occurrence states.

    View details for DOI 10.1111/gcb.17019

    View details for PubMedID 37987241

  • Hyperlocal Observations Reveal Persistent Extreme Urban Heat in Southeast Florida Journal of Applied Meteorology and Climatology Clement, A., Troxler, T., Keefe, O., Arcordia, M., Cruz, M., Moanga, D., Hernandez, A., Adefris, Z., Jacobson, S. 2023

    View details for DOI 10.1175/JAMC-D-22-0165.1

  • Farm consolidation and turnover dynamics linked to increased crop diversity and higher agricultural input use. Agricultural Systems Olivia, H., Butsic, V., Moanga, D., Wartenberg, A. 2023
  • The threat of wildfire is unique to cannabis among agricultural sectors in California ECOSPHERE Dillis, C., Van Butsic, Moanga, D., Parker-Shames, P., Wartenberg, A., Grantham, T. E. 2022; 13 (9)

    View details for DOI 10.1002/ecs2.4205

    View details for Web of Science ID 000850311700001

  • Identifying drivers of change and predicting future land-use impacts in established farmlands JOURNAL OF LAND USE SCIENCE Wartenberg, A. C., Moanga, D., Butsic, V. 2022; 17 (1): 161-180
  • Limited Economic-Ecological Trade-Offs in a Shifting Agricultural Landscape: A Case Study From Kern County, California FRONTIERS IN SUSTAINABLE FOOD SYSTEMS Wartenberg, A. C., Moanga, D., Potts, M. D., Butsic, V. 2021; 5
  • A System for Resilience Learning: Developing a community-driven, multi-sector research approach for greater preparedness and resilience to long-term climate stresses and extreme events in the Miami metropolitan region Journal of Extreme Events. Troxler, T., et al 2021
  • The space-time cube as an approach to quantifying future wildfires in California INTERNATIONAL JOURNAL OF WILDLAND FIRE Moanga, D., Biging, G., Radke, J., Butsic, V. 2021; 30 (2): 139-153

    View details for DOI 10.1071/WF19062

    View details for Web of Science ID 000588770100001

  • "Sealed in San Jose:" Paving of front yards diminishes urban forest resource and benefits in low-density residential neighborhoods URBAN FORESTRY & URBAN GREENING Lacan, I., Moanga, D., McBride, J. R., Butsic, V. 2020; 54
  • Avoided land use conversions and carbon loss from conservation purchases in California JOURNAL OF LAND USE SCIENCE Moanga, D., Schroeter, I., Ackerly, D., Butsic, V. 2018; 13 (4): 391-413
  • Using InVEST to assess ecosystem services on conserved properties in Sonoma County, CAYY CALIFORNIA AGRICULTURE Butsic, V., Shapero, M., Moanga, D., Larson, S. 2017; 71 (2): 81-89
  • Eastern Pacific Coral Reef Provinces, Coral Community Structure and Composition: An Overview CORAL REEFS OF THE EASTERN TROPICAL PACIFIC: PERSISTENCE AND LOSS IN A DYNAMIC ENVIRONMENT Glynn, P. W., Alvarado, J. J., Banks, S., Cortes, J., Feingold, J. S., Jimenez, C., Maragos, J. E., Martinez, P., Mate, J. L., Moanga, D. A., Navarrete, S., Reyes-Bonilla, H., Riegl, B., Rivera, F., Vargas-Angel, B., Wieters, E. A., Zapata, F. A., Glynn, P. W., Manzello, D. P., Enochs, I. C. 2017; 8: 107-176