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Article analysis:

The article "Monitoring selective logging in western Amazonia with repeat lidar flights" presents a study on the use of airborne laser scanning data (lidar) for estimating changes associated with low-impact selective logging in natural tropical forests in the Western Brazilian Amazon. The study investigates changes in the area impacted by selective logging, tall canopy area, lidar canopy structure metrics, and above ground biomass (AGB) using a model-based statistical framework.

The article provides detailed information on the methodology used to estimate changes due to selective logging. However, it is important to note that the study only focuses on low-impact selective logging, which accounts for approximately 10-15 m3 ha−1 or 5-7% of total standing volume harvested. This means that the results may not be applicable to other types of logging activities that have a higher impact on forest ecosystems.

Furthermore, while the article acknowledges the importance of reducing emissions from deforestation and forest degradation (REDD), it does not provide any information on how this study can contribute to achieving this goal. The article also fails to mention any potential risks associated with low-impact selective logging or how these risks can be mitigated.

Another potential bias in this article is its focus on lidar methods for monitoring selective logging. While lidar is a useful tool for estimating changes in forest structure and biomass, it is not without limitations. For example, lidar cannot detect changes in soil carbon or other below-ground carbon stocks that may be affected by logging activities.

Overall, while this article provides valuable insights into the use of lidar for monitoring low-impact selective logging in tropical forests, it is important to consider its limitations and potential biases when interpreting its findings.