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Predicting resilience and stability of early second-growth forests
Remote Sensing in Ecology and Conservation ( IF 3.9 ) Pub Date : 2022-02-15 , DOI: 10.1002/rse2.256 Lucas Andrigo Maure 1, 2 , Milena Fiuza Diniz 3 , Marco Túlio Pacheco Coelho 3 , Marina P. Souza de Oliveira 4 , Milton Cezar Ribeiro 5 , Fernando Rodrigues Silva 2 , Érica Hasui 4
Remote Sensing in Ecology and Conservation ( IF 3.9 ) Pub Date : 2022-02-15 , DOI: 10.1002/rse2.256 Lucas Andrigo Maure 1, 2 , Milena Fiuza Diniz 3 , Marco Túlio Pacheco Coelho 3 , Marina P. Souza de Oliveira 4 , Milton Cezar Ribeiro 5 , Fernando Rodrigues Silva 2 , Érica Hasui 4
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Identifying deforested areas with high potential for natural forest recovery can be used as an aid for ecological restoration projects at large-scale. However, accurate predictions that infer the resilience (i.e. recovery rate after deforestation) and stability (i.e. the ability of the ecosystem to maintain its functions) of early second-growth forests are scarce at a regional scale. Here, we investigated the effect of climate, soil and topography on the resilience and stability of 165 early second-growth forests throughout the Brazilian Atlantic Forest. We also built prediction maps of potential resilience and stability to identify where reforestation could be optimized in the early stages of forest succession. We assessed the resilience and stability through an interannual plant primary productivity time series using a normalized difference vegetation index. Our analysis reveals that resilience was mainly associated with isothermality (i.e. diurnal temperature oscillation relative to the annual temperature oscillation) and precipitation of the warmest quarter. In turn, stability was mainly associated with the probability of bedrock occurrence, annual precipitation and precipitation seasonality. The prediction maps show a spatial pattern in which potential resilience and stability increase from north to south of the Atlantic Forest. Forest restoration can be optimized in regions with high potential resilience and stability, such as an isolated area on the north coast in the Bahia state and the southern region. However, restoration may require active practices and management in regions with low potential for both ecosystem properties, such as the north inland in the Bahia and Minas Gerais states. This ecosystemic approach can help achieve Atlantic Forest restoration commitments.
中文翻译：
预测早期次生林的恢复力和稳定性
识别具有高天然林恢复潜力的森林砍伐区域可作为大规模生态恢复项目的辅助手段。然而，准确的预测推断早期二次生长森林的恢复力（即森林砍伐后的恢复率）和稳定性（即生态系统维持其功能的能力）在区域范围内很少见。在这里，我们调查了气候、土壤和地形对整个巴西大西洋森林的 165 个早期二次生长森林的恢复力和稳定性的影响。我们还构建了潜在恢复力和稳定性的预测图，以确定在森林演替的早期阶段可以优化重新造林的地方。我们使用归一化差异植被指数通过年际植物初级生产力时间序列评估了恢复力和稳定性。我们的分析表明，弹性主要与等温性（即相对于年温度波动的昼夜温度波动）和最热季度的降水有关。反过来，稳定性主要与基岩发生概率、年降水量和降水季节性有关。预测图显示了大西洋森林从北到南潜在弹性和稳定性增加的空间模式。可以在具有高潜在恢复力和稳定性的地区优化森林恢复，例如巴伊亚州北部海岸和南部地区的孤立地区。然而，恢复可能需要在生态系统特性潜力较低的地区进行积极的实践和管理，例如巴伊亚州和米纳斯吉拉斯州的北内陆。这种生态系统方法可以帮助实现大西洋森林恢复承诺。
更新日期：2022-02-15
中文翻译：
预测早期次生林的恢复力和稳定性
识别具有高天然林恢复潜力的森林砍伐区域可作为大规模生态恢复项目的辅助手段。然而，准确的预测推断早期二次生长森林的恢复力（即森林砍伐后的恢复率）和稳定性（即生态系统维持其功能的能力）在区域范围内很少见。在这里，我们调查了气候、土壤和地形对整个巴西大西洋森林的 165 个早期二次生长森林的恢复力和稳定性的影响。我们还构建了潜在恢复力和稳定性的预测图，以确定在森林演替的早期阶段可以优化重新造林的地方。我们使用归一化差异植被指数通过年际植物初级生产力时间序列评估了恢复力和稳定性。我们的分析表明，弹性主要与等温性（即相对于年温度波动的昼夜温度波动）和最热季度的降水有关。反过来，稳定性主要与基岩发生概率、年降水量和降水季节性有关。预测图显示了大西洋森林从北到南潜在弹性和稳定性增加的空间模式。可以在具有高潜在恢复力和稳定性的地区优化森林恢复，例如巴伊亚州北部海岸和南部地区的孤立地区。然而，恢复可能需要在生态系统特性潜力较低的地区进行积极的实践和管理，例如巴伊亚州和米纳斯吉拉斯州的北内陆。这种生态系统方法可以帮助实现大西洋森林恢复承诺。
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