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Landscape Ecology

, Volume 29, Issue 4, pp 677–687 | Cite as

Microclimate influences on vegetation water availability and net primary production in coastal ecosystems of Central California

  • Christopher Potter
Research Article

Abstract

Field sampling and satellite remote sensing were used to test the hypothesis that site microclimate variability leading to divergent soil water use by vegetation types is closely associated with variability in annual net primary productivity (NPP) at the landscape scale. A simulation model based on satellite observations of seasonal phenology was used to estimate NPP of grassland, shrubland, and conifer forest vegetation types on the Central California coast near Big Sur. Daily microclimate at the soil surface was monitored over 4 years (2008–2011) for each vegetation type to infer soil moisture controls on plant production. Grassland soils were found to have lower soil organic matter content and were subjected to extreme radiation and wind events, and thereby dry-down faster with daily spring–summer warming than do shrubland or redwood forest soils. This reduced moisture microclimate affected the water stress on grassland plants to reduce NPP fluxes from April to October each year on the Central Coast far sooner than for shrubland or redwood stands. Results from this study suggested that the satellite-observed canopy greenness variations represented can be used to quantify plant production in coastal ecosystems at the landscape scale of defined microclimate variation.

Keywords

Plant production Soil moisture Remote sensing MODIS Big Sur Central California Coast 

Notes

Acknowledgments

This work was supported by grants from NASA Ames Research. The author acknowledges assistance from the US Forest Service, Los Padres National Forest (Ecosystem Manager Jeff Kwasny) for access to the Brazil Ranch property. The author thanks Shuang Li for assistance with the CASA Express model runs, and acknowledges assistance in field sample collections from Cyrus Hiatt, Lisa Mammel, Cole Potter, Enza Potter, and Stephen Rosenfield. CASA model data sets are available online at http://geo.arc.nasa.gov/sge/casa/, as part of the NASA Carbon Query and Evaluation Support Tools (CQUEST) project.

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Copyright information

© Springer Science+Business Media Dordrecht (outside the USA) 2014

Authors and Affiliations

  1. 1.NASA Ames Research CenterMoffett FieldUSA

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