Basal area (BA) is a good predictor of timber stand volume and forest growth. This study developed predictive models using field and airborne LiDAR (Light Detection and Ranging) data for estimation of basal area in Pinus taeda plantation in south Brazil. In the field, BA was collected from conventional forest inventory plots. Multiple linear regression models for predicting BA from LiDAR-derived metrics were developed and evaluated for predictive power and parsimony. The best model to predict BA from a family of six models was selected based on corrected Akaike Information Criterion (AICc) and assessed by the adjusted coefficient of determination (adj. R²) and root mean square error (RMSE). The best model revealed an adj. R²=0.93 and RMSE=7.74%. Leave one out cross-validation of the best regression model was also computed, and revealed an adj. R² and RMSE of 0.92 and 8.31%, respectively. This study showed that LiDAR-derived metrics can be used to predict BA in Pinus taeda plantations in south Brazil with high precision. We conclude that there is good potential to monitor growth in this type of plantations using airborne LiDAR. We hope that the promising results for BA modeling presented herein will stimulate to operate this technology in Brazil.

There are well‐established methods for working in interdisciplinary natural resource management settings, but place‐based cultural differences are often poorly integrated into interdisciplinary projects. Intercultural adequacy is necessary to ensure that water management strategies are acceptable within the local contexts of water users. In this study we followed four cohorts of graduate students from Canada, Chile, Cuba, and the United States that participated in an international graduate‐level water resource management course hosted at the Universidad de Concepción in Chile. The North American students participated in post‐experience surveys and interviews to assess changes in their interdisciplinary and intercultural comfort levels. The interviews and survey identified factors that enhanced or detracted from their progress towards integrating disciplinary and cultural differences into their work. Though course material promoted interdisciplinary collaborations across various disciplinary cultures, participants noted that traditional methods of integrating did not adequately bridge differences in place‐based cultural worldviews. We propose a framework developed during the experience to integrate place‐based cultural differences into all phases of the interdisciplinary research and natural resource management processes.

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