Prioritizing Amazon Forest conservation: Assessing potential biomass under climate change

被引：0

作者：

Campos, Mayara Soares ^{[1
]}

Anjos, Luciano J. S. ^{[2
]}

de Souza, Everaldo B. ^{[3
]}

Bezerra, Francisco Gilney Silva ^{[4
]}

de Lima, Aline Maria Meiguins ^{[5
]}

Galbraith, David Roberto ^{[6
]}

Adami, Marcos ^{[4
,7
]}

机构：

[1] Univ Fed Para, Programa Posgrad Ciencias Ambientais PPGCA, Belem, Para, Brazil

[2] Univ Fed Rural Amazonia UFRA, Campus Parauapebas, Parauapebas, Para, Brazil

[3] Univ Fed Para UFPA, Fac Meteorol, Inst Geociencias, Belem, Para, Brazil

[4] Inst Nacl Pesquisas Espaciais INPE, Coordenacao Geral Ciencias Terra CGCT, Sao Jose Dos Campos, SP, Brazil

[5] Univ Fed Para UFPA, Lab Estudos & Modelagem Hidroambientais, Inst Geociencias, Belem, Para, Brazil

[6] Univ Leeds, Sch Geog, Leeds, England

[7] Ave Astronautas,1-758-Jd Granja, BR-12227010 Sao Jose Dos Campos, SP, Brazil

来源：

GLOBAL ECOLOGY AND CONSERVATION | 2024年 / 54卷

关键词：

CMIP6; Scenarios; Forest Biomass; Amazon Forest biome; Indigenous Land; Protected Areas; SYSTEM MODEL; DEFORESTATION; SENSITIVITY;

D O I：

10.1016/j.gecco.2024.e03106

中图分类号：

X176 [生物多样性保护];

学科分类号：

090705 ;

摘要：

This study aims to identify the capacity of intact forests to maintain Above Ground Biomass (AGB) under new climate conditions. Using a predictive approach under different climate scenarios (SSP1-2.6 and SSP5-8.5), and considering the mean of General Circulation Models (GCMs) for the period (2021-2040), it was revealed that the regions with the greatest capacity for AGB in the optimistic scenario are concentrated in the northwest and southeast regions, covering the basins of the Negro, Xingu and Tapajo<acute accent>s rivers. In the SSP5-8.5 scenario, although potential AGB gains are concentrated in the same regions, the spatial distribution is more restricted and dispersed. Indigenous Landsemerge as areas with the greatest potential AGB gains in both climate scenarios. However, these predictions do not include the impact of extreme climate events, such as storms, severe droughts, and wildfires, which could lead to an underestimation of actual biomass variations.

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页数：11

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