Individual tree mortality: Risks of climate change in the eastern Brazilian Amazon region

IF 5.8 2区环境科学与生态学 Q1 ECOLOGY

Ecological Informatics Pub Date : 2024-11-04 DOI:10.1016/j.ecoinf.2024.102880

Erica Karolina Barros de Oliveira , Alba Valéria Rezende , Leonidas Soares Murta Júnior , Lucas Mazzei , Renato Vinícius Oliveira Castro , Marcus Vinicio Neves D'Oliveira , Rafael Coll Delgado

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Abstract

The mortality of trees in humid tropical forests plays a fundamental role in understanding forest development, particularly after disturbances such as those caused by logging and extreme weather events. The aim of this study was to evaluate estimates of individual tree mortality following Reduced Impact Logging (RIL) in the Eastern Brazilian Amazon at biennial intervals from 2005 to 2012. RIL is based on operations planning, personnel training, and investments in forest management, and harvesting through RIL must: (a) minimize environmental damage, (b) diminish operation cost by increasing work efficiency, and (c) reduce operational waste. A mortality model was constructed based on the estimation of three distance-independent competition-indices (DII) and five models for predicting the probability of individual tree mortality. The Kolmogorov-Smirnov statistical test was used to determine the most representative model, from which a Neural Network Autoregressive (NNAR) model was constructed to forecast mortality after RIL. Mortality data was correlated with the El Niño–Southern Oscillation (ENSO) and climate (Rainfall, Maximum, Minimum, and Average air temperature). The tested models showed similar and accurate estimates with R² exceeding 0.90, although underestimation and overestimation trends were observed. The NNAR satisfactorily represented species mortality over the simulated years. The period from 2012 to 2014 was characterized by a Neutral and Weak El Niño event, and exhibited the highest mortality value for a 25 cm DBH (diameter at breast height), the smallest DBH class measured in this study. In the correlation matrix analysis, maximum air temperature showed the highest positive correlation with trees mortality. Despite the challenges in estimating individual tree mortality in tropical forests after selective logging, accurate estimates were achieved using traditional regression techniques and NNAR. These results can support technical and silvicultural decisions regarding forest management in the Eastern Amazon region of Brazil.

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树木个体死亡：巴西亚马逊东部地区的气候变化风险

潮湿热带森林中树木的死亡率对了解森林的发展起着至关重要的作用，尤其是在伐木和极端天气事件等干扰之后。本研究旨在评估 2005 年至 2012 年巴西亚马逊东部地区每两年一次的减少影响采伐（RIL）后单株树木死亡率的估计值。减少影响采伐以作业规划、人员培训和森林管理投资为基础，通过减少影响采伐必须做到以下几点(a) 尽量减少对环境的破坏，(b) 通过提高工作效率降低运营成本，以及 (c) 减少运营浪费。在估算三个与距离无关的竞争指数（DII）和五个预测单棵树木死亡概率的模型的基础上，构建了一个死亡率模型。通过 Kolmogorov-Smirnov 统计检验确定了最具代表性的模型，并据此构建了神经网络自回归（NNAR）模型，用于预测 RIL 后的死亡率。死亡率数据与厄尔尼诺-南方涛动（ENSO）和气候（降雨量、最高气温、最低气温和平均气温）相关。尽管出现了低估和高估的趋势，但所测试的模型显示出相似且准确的估计值，R2 超过 0.90。在模拟年份中，NNAR 对物种死亡率的表现令人满意。2012 年至 2014 年期间的特点是中性和弱厄尔尼诺事件，25 厘米 DBH（胸径）的死亡率值最高，这是本研究测量的最小 DBH 等级。在相关矩阵分析中，最高气温与树木死亡率的正相关性最高。尽管在选择性采伐后的热带森林中估算单棵树木的死亡率存在挑战，但使用传统的回归技术和 NNAR 仍能获得准确的估算结果。这些结果可为巴西亚马逊东部地区森林管理的技术和造林决策提供支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ecological Informatics 环境科学-生态学

CiteScore

8.30

自引率

11.80%

发文量

346

审稿时长

46 days

期刊介绍： The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.