Microclimatic variation associated with dispersed and aggregated retention harvests in western Washington (DEMO).

CREATOR(S): Troy Heithecker
ORIGINATOR(S): Troy Heithecker
OTHER RESEARCHER(S): Charles B. Halpern
ABSTRACTOR: Troy Heithecker
14 Feb 2007
23 Jan 2015
silviculture, microclimate, resource management, timber harvest
We addressed the following questions:
  1. How does microclimate vary along a broad gradient of dispersed-retention harvests (0-100% of original basal area)?
  2. How does within-treatment (plot-level) variation in microclimate vary along this gradient?
  3. Are there easily collected/derived structural variables (including overstory attributes and understory conditions) that are strong predictors of microclimate?
  4. How does microclimate vary as a function of distance from the edge of 1-ha circular forest aggregates (retention patches)?
  5. Are gradients in microclimate across forest aggregates influenced by aspect?
Experimental Design - MS034:

We selected a subset of treatments at three of the Washington experimental blocks (Butte, Little White Salmon, and Paradise Hills; These were chosen to represent a broad gradient in dispersed retention and to capture variation associated with aggregated retention harvests. The full experimental design is described at

Harvest treatments were completed in 1997 and 1998 (see Data from this study thus represent conditions 6-7 yr after harvest. We selected 4 treatments to represent a gradient of dispersed retention: 0% (harvested portions of the 15% aggregated treatment), 15% dispersed (15%D), 40% dispersed retention (40%D), and 100% retention (control). For the study of gradients in microclimate across forest aggregates, we used the harvested portions of the 15% A treatment. Full details of the DEMO experimental design can be found in Aubry et al. (1999) and Halpern et al. (2005).

Field Methods - MS034:
Description: Sampling designs:

For the comparison of microclimate in dispersed-retention treatments, we randomly established 20 (in one case 21) sampling points in each of the 4 treatment units per block; these were selected from a larger pool of 22-32 permanent tree plots (Halpern et al. 1999) arrayed on a systematic grid of 8 x 8 or 7 x 9 points spaced 40 m apart (Aubry et al. 1999). To represent the 0% retention treatment, plots were selected from within the harvested portions of 15%A.

For the study of gradients across forest aggregates, we established 4 transects in each of the 15%A harvest units (2 per 1-ha forest aggregate). Each transect had 16 sample points representing varying distances from the aggregate edge: -56.4 (aggregate center), -40, -30, -20, -15, -10, -5, 0 (edge), 5, 10, 15, 20, 30, 40, 63, and 103 m.

Microclimatic measurements:

At each sample point a microclimatic station was established in a random direction 1.5 m from the center of the tree plot. At each point we measured slope, aspect (transformed to "southwestness" (cos[aspect-225 ]) and four microclimatic variables: light, air temperature, soil temperature, and soil moisture (described in detail below).

Light.--An index of light availability was obtained from hemispherical photography of the forest canopy. A Nikon Coolpix 990 digital camera with a Nikon FC-E8 fisheye converter was leveled on a monopod 2 m from the ground, with the top of the camera oriented north. Photographs were taken under overcast sky conditions between June and November 2004. Images were analyzed with the software Gap Light Analyzer 2.0 (GLA; Frazer et al. 1999), employing the standard overcast sky model (UOC). Total transmitted light, or photosynthetic photon flux density (PPFD; mol m-2 day-1), was calculated for the growing season (June through September).

Air and soil temperature.--Air and soil temperature were measured using temperature data loggers (Model DS1921G, iButton Thermochron, Maxim/Dallas Semiconductor Corp., Dallas, Texas). Two loggers were placed at each point: the first on a wooden stake 1 m above the ground surface (air), the second at 15 cm beneath the soil surface (soil).

For measurements of air temperature, loggers were placed on the inside of one-half of a small (10 cm long) plastic container shielded with aluminum foil to prevent direct radiation, and perforated to allow airflow and minimize heat accumulation. Plastic containers were attached to a wooden "arm" extending perpendicular from the top of each stake.

Temperature was recorded hourly at each point over a 2-3 wk period between mid July and late September 2004 to sample the most stressful portion of the growing season. Measurements were taken synchronously within each block, but sampling was staggered in time among blocks (Little White Salmon = 19 July to 5 August, Butte = 10 to 31 August, and Paradise Hills = 1 to 23 September 2004).

Soil moisture.--Volumetric soil moisture was measured using time domain reflectometry (TDR). Stainless steel probes, 30 cm long, were inserted at an angle of 30 from the soil surface to sample the upper 15 cm of soil; probes remained in place for the entire sampling period. Multiple measurements were taken over the growing season.

At each measurement, all points within a block were sampled over a 1-2 day period of dry weather (no precipitation in the previous 48 hr) and all blocks were visited within the same 1-wk period. Probes were attached to a TDR monitor with alligator clips soldered to coaxial wire; data were recorded on a palmtop computer. Volumetric soil moisture was calculated using calibration curves of Gray and Spies (1995).

Vegetation measurements:

Within each tree plot, all stems 5 cm dbh were measured for diameter. Heights for all trees were estimated from species- and treatment-specific height:diameter equations (D. Maguire, unpublished data). Four predictors of overstory structure were then generated for each plot: total tree density, total basal area, stand density index ([density * basal area]1/2), and total tree height (summed heights of all trees). In addition, overstory canopy cover was obtained from the hemispherical photograph taken at the center of each plot.

To quantify the potential shading effects of understory vegetation and logging slash, two additional estimates were made at each microclimatic station. Using a 1-m2 frame centered on each wooden post, visual estimates of cover were made for all vegetation less than 1.5 m tall and for logging slash (fine branches and other woody debris resulting from harvest operations).

For other details see Heithecker (2005).


Aubry, K. B., M. P. Amaranthus, C. B. Halpern, J. D. White, B. L. Woodard, C. E. Peterson, C. A. Lagoudakis, and A. J. Horton. 1999. Evaluating the effects of varying levels and patterns of green-tree retention: experimental design of the DEMO study. Northwest Science 73(Special Issue):12-26.

Drever, R. C., and K. P. Lertzman. 2003. Effects of a wide gradient of retained tree structure on understory light in coastal Douglas-fir forests. Canadian Journal of Forest Research 33:137-146.

Frazer, G. W., C. D. Canham, and K. P. Lertzman. 1999. Gap Light Analyzer (GLA) Version 2.0: Imaging software to extract canopy structure and gap light transmission indices from true-colour fisheye photographs, user manual and program documentation. Simon Fraser University and the Institute of Ecosystem Studies, Burnaby, British Columbia.

Gray, A. N., and T. A. Spies. 1995. Water content measurement in forest soils and decayed wood using time domain reflectometry. Canadian Journal of Forest Research 25:376-385.

Halpern, C. B., D. McKenzie, S. A. Evans, and D. A. Maguire. 2005. Initial responses of forest understories to varying levels and patterns of green-tree retention. Ecological Applications 15:175-195.

Heithecker, T. D. 2005. Variation in microclimate associated with dispersed-retention harvests in coniferous forests of the Pacific Northwest. M.S. thesis, University of Washington, Seattle, WA. 44 pp.

Western Washington
Ground condition