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1.
An. acad. bras. ciênc ; 89(2): 973-989, Apr.-June 2017. tab, graf
Artigo em Inglês | LILACS | ID: biblio-886715

RESUMO

ABSTRACT In order to contribute to understand the factors that control the provisioning of the ecosystem service of carbon storage by mangroves, data on carbon stock and sequestration in the aboveground biomass (AGB) from 73 articles were averaged and tested for the dependence on latitude, climatic parameters, physiographic types and age. Global means of carbon stock (78.0 ± 64.5 tC.ha-1) and sequestration (2.9 ± 2.2 tC.ha-1.yr-1) showed that mangroves are among the forest ecosystems with greater capacity of carbon storage in AGB per area. On the global scale, carbon stock increases toward the equator (R²=0.22) and is dependent on 13 climatic parameters, which can be integrated in the following predictive equation: Carbon Stock in AGB = -16.342 + (8.341 x Isothermality) + (0.021 x Annual Precipitation) [R²=0.34; p < 0.05]. It was shown that almost 70% of carbon stock variability is explained by age. Carbon stock and sequestration also vary according to physiographic types, indicating the importance of hydroperiod and edaphic parameters to the local variability of carbon stock. By demonstrating the contribution of local and regional-global factors to carbon stock, this study provides information to the forecast of the effects of future climate changes and local anthropogenic forcings on this ecosystem service.


Assuntos
Carbono/análise , Carbono/química , Áreas Alagadas , Sequestro de Carbono , Valores de Referência , Clima Tropical , Análise de Regressão , Análise de Variância , Biomassa
2.
Rev. peru. biol. (Impr.) ; 19(2)ago. 2012.
Artigo em Espanhol | LILACS-Express | LILACS, LIPECS | ID: biblio-1522273

RESUMO

Los bosques de Polylepis son recursos vitales para la conservación de la biodiversidad y funciones hidrológicas, la cual se verá alterada por el cambio climático a nivel mundial desafiando la sostenibilidad de las comunidades locales. Sin embargo, estos ecosistemas andinos de gran altitud son cada vez más vulnerables debido a la presión antropogénica como la fragmentación, deforestación y el incremento en el ganado. La importancia para predecir la distribución de bosques nativos ha aumentado para contrarrestar los efectos negativos del cambio climático a través de la conservación y la reforestación. El objetivo de este estudio fue desarrollar y analizar los modelos de distribución de dos especies, Polylepis sericea y P. besseri, que forman bosques extensos a lo largo de los Andes. Este estudio utilizó el programa Maxent, el clima y capas ambientales de una resolución de 1 Km. El modelo de distribución previsto para P. sericea indica que la especie podría estar situada en una variedad de hábitats a lo largo de la Cordillera de los Andes, mientras que P. besseri se limitaba a las grandes alturas del sur de Perú y Bolivia. Para ambas especies, los metros de elevación y la temperatura son los factores más importantes para la distribución prevista. El perfeccionamiento del modelo de Polylepis y otras especies andinas utilizando datos de satélites cada vez más disponibles al público demuestran el potencial para ayudar a definir las áreas de diversidad y mejorar las estrategias de conservación en los Andes.


Polylepis woodlands are a vital resource for preserving biodiversity and hydrological functions, which will be altered by climate change and challenge the sustainability of local human communities. However, these high-altitude Andean ecosystems are becoming increasingly vulnerable due to anthropogenic pressure including fragmentation, deforestation and the increase in livestock. Predicting the distribution of native woodlands has become increasingly important to counteract the negative effects of climate change through reforestation and conservation. The objective of this study was to develop and analyze the distribution models of two species that form extensive woodlands along the Andes, namely Polylepis sericea and P. weberbaueri. This study utilized the program Maxent, climate and remotely sensed environmental layers at 1 Km resolution. The predicted distribution model for P. sericea indicated that the species could be located in a variety of habitats along the Andean Cordillera, while P. weberbaueri was restricted to the high elevations of southern Peru and Bolivia. For both species, elevation and temperature metrics were the most significant factors for predicted distribution. Further model refinement of Polylepis and other Andean species using increasingly available satellite data demonstrate the potential to help define areas of diversity and improve conservation strategies for the Andes.

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