Above‐ and below‐ground biodiversity responses to the prolonged flood pulse in central‐western Amazonia, Brazil

Bredin, Yennie Katarina; Hess, Laura L.; Scabin, Andressa Bárbara; Dunthorn, Micah; Haugaasen, Torbjørn; Peres, Carlos A.; Nilsson, R. Henrik; Antonelli, Alexandre; Ritter, Camila Duarte

doi:10.1002/edn3.268

Cited by 2 publications

(1 citation statement)

References 118 publications

(137 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The humid forests in South America have also suffered from severe droughts that lead to tree mortality and threaten the carbon sink (Lapola et al, 2023). Additionally, flooding has become a new disturbance agent that leads to tree mortality and decreased resilience in Amazon forests (Resende et al, 2019;Boulton et al, 2022;Bredin et al, 2022).…”

Section: Driving Factors Of Forest Disturbancesmentioning

confidence: 99%

Recent advances and challenges in monitoring and modeling of disturbances in tropical moist forests

He,

Li,

Zhao

et al. 2024

Front. Remote Sens.

View full text Add to dashboard Cite

Tropical moist forests have been severely affected by natural and anthropogenic disturbances, leading to substantial changes in global carbon cycle and climate. These effects have received great attention in scientific research and debates. Here we review recent progress on drivers and ecological impacts of tropical moist forest disturbances, and their monitoring and modeling methods. Disturbances in tropical moist forests are primarily driven by clearcutting, selective logging, fire, extreme drought, and edge effects. Compound disturbances such as fire and edge effects aggravate degradation in the edge forests. Drought can result in terrestrial carbon loss via physiological impacts. These disturbances lead to direct carbon loss, biophysical warming and microclimate change. Remote sensing observations are promising for monitoring forest disturbances and revealing mechanisms, which will be useful for implementing disturbance processes in dynamic vegetation models. Yet, constrained spatiotemporal coverages and resolutions limit the application of these data in process-based models. It is also challenging to represent physical processes derived from fine-resolution remote sensing data in coarse-resolution models. We highlight the need to continuously integrate new datasets and physical processes in forest disturbance modeling to advance understanding of disturbance patterns and impacts. Interactions and impacts of climate change and anthropogenic activities should also be considered for modeling and assessing feedbacks of tropical moist forest disturbances.

show abstract

Section: Driving Factors Of Forest Disturbancesmentioning

confidence: 99%

Recent advances and challenges in monitoring and modeling of disturbances in tropical moist forests

He,

Li,

Zhao

et al. 2024

Front. Remote Sens.

View full text Add to dashboard Cite

show abstract

Evidence for the efficacy of anti-inflammatory plants used in Brazilian traditional medicine with ethnopharmacological relevance

de Matos,

Bitencourt,

de Oliveira

et al. 2024

Journal of Ethnopharmacology

View full text Add to dashboard Cite

Above‐ and below‐ground biodiversity responses to the prolonged flood pulse in central‐western Amazonia, Brazil

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 2 publications

References 118 publications

Recent advances and challenges in monitoring and modeling of disturbances in tropical moist forests

Recent advances and challenges in monitoring and modeling of disturbances in tropical moist forests

Evidence for the efficacy of anti-inflammatory plants used in Brazilian traditional medicine with ethnopharmacological relevance

Contact Info

Product

Resources

About