5 research outputs found

    Efluxo de Co2 do Solo em uma 脕rea de Bosque Localizada no Campus ii da UFPA, Santar茅m, PA

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    Este trabalho tem como objetivo determinar as trocas de CO2na interface solo-atmosfera. As medidas de CO2 foram realizadas porum analisador de g谩s por infravermelho (IRGA) LI-COR 6262, c芒marasest谩tica de concentra莽茫o, conectado a um notebook. A m茅dia do fluxode CO2 para o solo seco e 煤mido foram 4,3 卤 1,0 渭mol CO2 m-2 s-1 e 5,2卤 1,8 渭mol CO2 m-2 s-1, respectivamente. Essa diferen莽a dos fluxos podeter sido devido 脿 precipita莽茫o na 谩rea de estudo

    Comparing the Air Turbulence above Smooth and Rough Surfaces in the Amazon Region

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    The goal of this work is to compare the main air turbulence characteristics of two common areas in the Amazonian landscape: a dense forest (rough surface) and a water surface (smooth surface). Using wind components data collected at high frequency by sonic anemometers located just above these surfaces, turbulence intensity and power spectra, temporal and length scales of the eddies, as well as the main terms of the TKE budget (TKE = turbulent kinetic energy) were evaluated for each surface type. The results showed that in general, the air turbulence intensity above the forest was higher than above the lake during the daytime, due to the high efficiency of the forest in absorbing the momentum of the turbulent flow. During the nighttime, the situation was reversed, with greater air turbulence intensity above the lake, except in some periods in which intermittent turbulence bursts occured above the forest

    Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts

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    The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence.We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajos (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition.The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7yr, depending upon soil texture and leaf phenology.From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss >20% in 50yr according to ED2 predictions. Nearly 25% (1.8 million km(2)) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2 sigma. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100

    Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts.

    No full text
    The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapaj贸s (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2蟽. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100
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