MV008
Vertical tree air temperature measurements within the canopy of the HJ Andrews Experimental Forest, 2011-2019

CREATOR(S): Sarah J. K. Frey, Julia A. Jones

PRINCIPAL INVESTIGATOR(S): Julia A. Jones

ORIGINATOR(S): Sarah J. K. Frey

OTHER RESEARCHER(S): Mark D Schulze, Adam Scott Hadley, Matthew G Betts, Adam M Kennedy

DATA SET CONTACT PERSON: Sarah J. K. Frey

TOOL CONTACT: Matthew J. Gregory

METADATA CREATION DATE:

3 Oct 2017

MOST RECENT METADATA REVIEW DATE:

18 Feb 2020

KEYWORDS:

air temperature, forests

PURPOSE:

This study is intended to understand vertical temperature profiles and their spatial patterns in relation to forest structure and landscape context.

METHODS:

Experimental Design - MV008:

Description: Eleven sites (of the 184 existing sites where temperature and bird data are collected) were chosen for instrumentation of HOBO temperature loggers up through the canopy. Site selection was based on elevation, landscape position, and forest type. Six of the 11 sites are located in old-growth forest and five are located in plantation forest. Loggers were spaced at 5-m intervals starting at 6.5 m, which is 5 m higher than the original 1.5 m logger at these sites. The tallest logger at each site depended on the forest canopy height and the height of the individual tree that the loggers were placed in (ranges from 11.5 m to 46.5 m). Sites are grouped into low elevation (487, 556, 567, 622, 687 m) and high elevation (979, 1082, 1184, 1301, 1301, 1339 m).

Field Methods - MV008:

Description: Each of the 11 trees selected were rigged to set up temperature and light sensors up through the canopy. Loggers were installed using a pulley system and parachute cord so that downloading data and changing batteries is easily accomplished. Half of a 3-inch diameter schedule 40 PVC pipe, cut to 6-in in length for a sun shield was used at each HOBO sensor. All temperature loggers were oriented to face south using a compass (and within what was physically possible based on the parachute cord). Temperature was programmed to be recorded every 20 minutes. The 1.5 meter sensor data is from data collected in MS045 study where temperature resolution is every 20 minutes at the bird sites and every 15 minutes at the vegetation sites. Data is download from the units 1-2 times a year (May - August) and change of batteries once a year based on sampling frequency (generally on the second offload session of each year).

Models/Algorithms - MV008:

Description: A Python workflow, which includes instructions on how the Python code is run, including the yaml and wheel file to be used in the Python code, which can be adjusted by the user to change the flagging of the data, and the definition of flags used in the Python QAQC file.

Processing Procedures - MV008:

Description:

Raw data for entity 1 was run through a locally developed Python program QAQC procedure (hja_hobo_clean) by study originator. There is a version of entity 1 data offline, but available, that have had a light-adjustment applied based on the illumination values in order to account for bias in the temperature measurements created by light hitting the sensor shield. The light adjustment is based on paired light and temperature measurements, from the Discovery Tree (see document hobo_correction_181012.pdf). It is Corrected air T = 0.2267*(lux/1000) + 0.04955 or y = 0.1987x + 0.0726. This light adjustment was applied to the cleaned version of the dataset.

Raw data for entity 2 was flagged and not filled using the GCE Toolbox workflow and based on the flagging algorithms in the hja_hobo_clean workflow. Researchers provide a folder of HOBO data files with a predefined naming convention and structure that can be processed by Andrews Forest System Administrator. The files are run through GCE Data Toolbox, which is a comprehensive software framework for metadata-based analysis, quality control, transformation and management of ecological data sets. https://gce-lter.marsci.uga.edu/public/im/tools/data_toolbox.htm. The GCE workflow was developed based on the original checks from the hja_hobo_clean Python program.

Quality Assurance - MV008:

Description:

Raw data for entity 1 was run through a locally developed Python program QAQC procedure (hja_hobo_clean). These data have only been flagged and include extreme values, gaps, spikes and possible snow indication. Some visual inspection of the data using a visualization tool occurred. The Python program can create cleaned and filled versions of the data based on specified parameters. More information on this is found in the supplementary documents (Python workflow, Python flag definitions).

Raw data for entity 2 was flagged and not filled using the GCE Toolbox workflow and based on the flagging algorithms in the hja_hobo_clean workflow. Like entity 1, these data were checked for burial by snow, detection of extreme values and jumps, as well as the influence of high/extreme light intensity. Rather than having multiple data columns for each flag, as in entity 1, these data use an aggregated flagging system for each data variable (temperature and light).

SUPPLEMENTAL INFORMATION:

See related files.

TAXONOMIC SYSTEM:

None

GEOGRAPHIC EXTENT:

Geographic Extent: H. J. Andrews Experimental Forest, Western Cascades, Oregon

ELEVATION_MINIMUM (meters):

488

ELEVATION_MAXIMUM (meters):

1334

MEASUREMENT FREQUENCY:

15 or 20 minutes

PROGRESS DESCRIPTION:

Active

UPDATE FREQUENCY DESCRIPTION:

annually

CURRENTNESS REFERENCE:

Ground condition