19 research outputs found
Control of dry season evapotranspiration over the Amazonian forest as inferred from observations at a southern Amazon forest site
The extent to which soil water storage can support an average dry season evapotranspiration (ET) is investigated using observations from the Rebio JarĂș site for the period of 2000 to 2002. During the dry season, when total rainfall is less than 100 mm, the soil moisture storage available to root uptake in the top 3-m layer is sufficient to maintain the ET rate, which is equal to or higher than that in the wet season. With a normal or less-than-normal dry season rainfall, more than 75% of the ET is supplied by soil water below 1 m, whereas during a rainier dry season, about 50% of ET is provided by soil water from below 1 m. Soil moisture below 1-m depth is recharged by rainfall during the previous wet season: dry season rainfall rarely infiltrates to this depth. These results suggest that, even near the southern edge of the Amazon forest, seasonal and moderate interannual rainfall deficits can be mitigated by an increase in root uptake from deeper soil. How dry season ET varies geographically within the Amazon and what might control its geographic distribution are examined by comparing in situ observations from 10 sites from different areas of Amazonia reported during the last two decades. Results show that the average dry season ET varies less than 1 mm dayÂż1 or 30% from the driest to nearly the wettest parts of Amazonia and is largely correlated with the change of surface net radiation of 25% and 30%. Thus the geographic variation of the average dry season ET appears to be mainly determined by the surface radiation
Recommended from our members
Leveraging the NEON Airborne Observation Platform for socio-environmental systems research
During the 21st century, humanâenvironment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Humanâenvironment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Networkâs Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data. © 2021 The Authors.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Scaling Uncertainties in Estimating Canopy Foliar Maintenance Respiration for Black Spruce Ecosystems in Alaska
black spruce, boreal forests, canopy, ecosystems, maintenance respiration, modeling, spatial scaling, temporal scaling,