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1.
Nature ; 625(7996): 728-734, 2024 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-38200314

RESUMO

Trees structure the Earth's most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1-6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth's 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world's most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.


Assuntos
Florestas , Árvores , Clima Tropical , Biodiversidade , Árvores/anatomia & histologia , Árvores/classificação , Árvores/crescimento & desenvolvimento , África , Sudeste Asiático
2.
Ecol Evol ; 11(24): 18691-18707, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-35003702

RESUMO

Most Central African rainforests are characterized by a remarkable abundance of light-demanding canopy species: long-lived pioneers (LLP) and non-pioneer light demanders (NPLD). A popular explanation is that these forests are still recovering from intense slash-and-burn farming activities, which abruptly ended in the 19th century. This "human disturbance" hypothesis has never been tested against spatial distribution patterns of these light demanders. Here, we focus on the 28 most abundant LLP and NPLD from 250 one-ha plots distributed along eight parallel transects (~50 km) in the Yangambi forest. Four species of short-lived pioneers (SLP) and a single abundant shade-tolerant species (Gilbertiodendron dewevrei) were used as reference because they are known to be strongly aggregated in recently disturbed patches (SLP) or along watercourses (G. dewevrei). Results show that SLP species are strongly aggregated with clear spatial autocorrelation of their diameter. This confirms that they colonized the patch following a one-time disturbance event. In contrast, LLP and NPLD species have random or weakly aggregated distribution, mostly without spatial autocorrelation of their diameter. This does not unambiguously confirm the "human disturbance" hypothesis. Alternatively, their abundance might be explained by their deciduousness, which gave them a competitive advantage during long-term drying of the late Holocene. Additionally, a canonical correspondence analysis showed that the observed LLP and NPLD distributions are not explained by environmental variables, strongly contrasting with the results for the reference species G. dewevrei, which is clearly aggregated along watercourses. We conclude that the abundance of LLP and NPLD species in Yangambi cannot be unambiguously attributed to past human disturbances or environmental variables. An alternative explanation is that present-day forest composition is a result of adaptation to late-Holocene drying. However, results are inconclusive and additional data are needed to confirm this alternative hypothesis.

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