While Brazil publicly committed to reduce deforestation in Amazonia at the 26th Conference of the Parties (COP26), the Brazilian parliament is moving toward weakening environmental laws. Deforestation rates continue ascending, reaching in 2021 the highest value since 2006 (13,235 km²). To overcome this paradox, strategies to curb deforestation are mandatory. The current strategy, “Plano Amazônia 21/22,” prioritizes law enforcement actions to curb illegal deforestation in only 11 Amazonian municipalities. Here, we show that this prioritization is likely to be insufficient since these municipalities account for just 37% of the current deforestation rate. This strategy may also be undermined by the leakage of deforestation actions to unmonitored municipalities. Using a set of spatially explicit datasets integrated into a deforestation-prediction modeling approach, we propose a science-based alternative method for ranking deforestation hotspots to be prioritized by law enforcement actions. Our prioritization method accounts for more than 60% of the deforestation, detecting larger deforested areas in both private and public lands, while covering 27% less territory than “Plano Amazônia 21/22.” Optimizing the detection of priority areas for curbing deforestation, as proposed here, is the first step to reducing deforestation rates and comply with the Brazilian legal commitment of 3925 km² year⁻¹.

中文翻译：

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基于科学的规划可以支持执法行动，以遏制巴西亚马逊地区的森林砍伐

虽然巴西在第 26 届缔约方大会 (COP26) 上公开承诺减少亚马逊流域的森林砍伐，但巴西议会正朝着削弱环境法的方向发展。森林砍伐率继续上升，2021 年达到 2006 年以来的最高值（13,235 km ²）。为了克服这个悖论，遏制森林砍伐的策略是强制性的。目前的战略，“ Plano Amazonia 21/22”，仅在 11 个亚马逊城市中优先采取执法行动来遏制非法砍伐森林。在这里，我们表明这种优先顺序可能不够，因为这些城市仅占当前森林砍伐率的 37%。这一战略也可能因毁林行动泄漏到不受监控的市政当局而受到破坏。使用一组集成到森林砍伐预测建模方法中的空间显式数据集，我们提出了一种基于科学的替代方法，用于对执法行动优先考虑的森林砍伐热点进行排名。我们的优先级排序方法占森林砍伐的 60% 以上，检测到私人和公共土地上更大的森林砍伐面积，同时覆盖的领土比“ Plano Amazônia 21/22 ”少 27%” 如本文所提议，优化优先区域的检测以遏制森林砍伐是降低森林砍伐率并遵守巴西 3925 km ² year ⁻¹的法律承诺的第一步。