Diana Moanga

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

  Abstract

  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

  View details for DOI 10.1016/j.agsy.2023.103708

• 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

  View details for DOI 10.1080/1747423X.2021.2018061

  View details for Web of Science ID 000733661800001

• 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

  View details for DOI 10.3389/fsufs.2021.650727

  View details for Web of Science ID 000641262300001

• 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

  View details for DOI 10.1016/j.ufug.2020.126755

  View details for Web of Science ID 000569421200017

• 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

  View details for DOI 10.1080/1747423X.2018.1533043

  View details for Web of Science ID 000455153200002

• 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

  View details for DOI 10.3733/ca.2017a0008

  View details for Web of Science ID 000400939800009

• 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

  View details for DOI 10.1007/978-94-017-7499-4_5

  View details for Web of Science ID 000400151600007