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Biweekly soil-moisture in the 18 CARBONO Project plots, La Selva Biological Station, March 1998-October 2018

Cite this dataset

Clark, Deborah; Oberbauer, Steven (2021). Biweekly soil-moisture in the 18 CARBONO Project plots, La Selva Biological Station, March 1998-October 2018 [Dataset]. Dryad. https://doi.org/10.5061/dryad.73n5tb2x5

Abstract

This publication presents the complete 20-year record of volumetric soil moisture in the 18 plots of the CARBONO Project in the old-growth tropical rainforest at La Selva Biological Station, Costa Rica. The measurements were made biweekly through the period March 1998 – October 2018. Volumetric soil moisture was assessed over the top 30 cm of soil. The publication consists of the full data record and documentation of the cross-sensor regressions.

Methods

Volumetric soil moisture was monitored biweekly in each of the 18 CARBONO project 0.5-ha plots, which were stratified across the major landscape variation of the old-growth rainforest at the La Selva Biological Station. The biweekly readings were made from one or more permanently-installed sensors buried vertically at the center of each CARBONO plot to assess the soil moisture in the top 30 cm of soil. For most of the record (1998 -  2013) all readings were by Frequency Domain Reflectometry, using a CS615 FDR sensor buried vertically at the center of each CARBONO plot. The readings were converted to volumetric soil moisture using a prior published calibration of that sensor for the La Selva soils. With discontinuation of that sensor model, beginning in 2014 new Time Domain Reflectometry CS616 sensors were deployed across the plots to run in parallel with the FDR sensors and to replace original FDR sensors that failed. Highly significant regressions between the two sensor types enabled an internally-consistent two-decade record of topsoil soil moisture across this old-growth tropical rainforest landscape.

Usage notes

Missing values are indicated as blanks or #N/A. Comments related to the qa/qc of the data are in the notes variable in the data file.

Funding

National Science Foundation, Award: 1357177

National Science Foundation, Award: 1147367

National Science Foundation, Award: 0421178