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1.
Curr Biol ; 33(16): 3495-3504.e4, 2023 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-37473761

RESUMO

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%-18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost.


Assuntos
Biodiversidade , Florestas , Humanos , Floresta Úmida , Brasil , Clima Tropical , Conservação dos Recursos Naturais , Ecossistema
2.
Ecology ; 101(3): e02954, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31840235

RESUMO

Tropical forests hold 30% of Earth's terrestrial carbon and at least 60% of its terrestrial biodiversity, but forest loss and degradation are jeopardizing these ecosystems. Although the regrowth of secondary forests has the potential to offset some of the losses of carbon and biodiversity, it remains unclear if secondary regeneration will be affected by climate changes such as higher temperatures and more frequent extreme droughts. We used a data set of 10 repeated forest inventories spanning two decades (1999-2017) to investigate carbon and tree species recovery and how climate and landscape context influence carbon dynamics in an older secondary forest located in one of the oldest post-Columbian agricultural frontiers in the Brazilian Amazon. Carbon accumulation averaged 1.08 Mg·ha-1 ·yr-1 , and species richness was effectively constant over the studied period. Moreover, we provide evidence that secondary forests are vulnerable to drought stress: Carbon balance and growth rates were lower in drier periods. This contrasts with drought responses in primary forests, where changes in carbon dynamics are driven by increased stem mortality. These results highlight an important climate change-vegetation feedback, whereby the increasing dry-season lengths being observed across parts of Amazonia may reduce the effectiveness of secondary forests in sequestering carbon and mitigating climate change. In addition, the current rate of forest regrowth in this region was low compared with previous pan-tropical and Amazonian assessments-our secondary forests reached just 41.1% of the average carbon and 56% of the tree diversity in the nearest primary forests-suggesting that these areas are unlikely to return to their original levels on politically meaningful time scales.


Assuntos
Ecossistema , Florestas , Biodiversidade , Brasil , Mudança Climática , Secas , Árvores , Clima Tropical
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