Rolf Gersonde

Examining conifer canopy structural complexity across forest ages and elevations with LiDAR data

LiDAR measurements of canopy structure can be used to classify forest stands into structural stages to study spatial patterns of canopy structure, identify habitat, or plan management actions. A key assumption in this process is that differences in canopy structure based on forest age and elevation are consistent with predictions from models of stand de- velopment. Three LiDAR metrics (95th percentile height, rumple, and canopy density) were computed for 59 secondary and 35 primary forest plots in the Pacific Northwest, USA. Hierarchical clustering identified two precanopy closure classes, two low-complexity postcanopy closure classes, and four high-complexity postcanopy closure classes. Forest de- velopment models suggest that secondary plots should be characterized by low-complexity classes and primary plots char- acterized by high-complexity classes. While the most and least complex classes largely confirmed this relationship, intermediate-complexity classes were unexpectedly composed of both secondary and primary forest types. Complexity classes were not associated with elevation, except that primary Tsuga mertensiana (Bong.) Carriere (mountain hemlock) plots were complex. These results suggest that canopy structure does not develop in a linear fashion and emphasize the im- portance of measuring structural conditions rather than relying on development models to estimate structural complexity across forested landscapes.

POTENTIAL SITE PRODUCTIVITY INFLUENCES THE RATE OF FOREST STRUCTURAL DEVELOPMENT

Development and maintenance of structurally complex forests in landscapes formerly managed for timber production is an increasingly common management objective. It has been postulated that the rate of forest structural development increases with site productivity. We tested this hypothesis for Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) forests using a network of permanent study plots established following complete timber harvest of the original old-growth forests. Forest structural development was assessed by comparing empirical measures of live tree structure to published values for Douglas-fir forests spanning a range of ages and structural conditions. The rate of forest structural development--resilience--exhibited a positive relationship with site index, a measure of potential site productivity. Density of shade-intolerant conifers declined in all study stands from an initial range of 336-4068 trees/ha to a range of 168-642 trees/ha at the most recent measurement. Angiosperm tree species declined from an initial range of 40-371 trees/ha to zero in seven of the nine plots in which they were present. Trends in shade-tolerant tree density were complex: density ranged from 0 to 575 trees/ha at the first measurement and was still highly variable (25-389 trees/ha) at the most recent measurement. Multivariate analysis identified the abundance of hardwood tree species as the strongest compositional trend apparent over the study period. However, structural variables showed a strong positive association with increasing shade-tolerant basal area and little or no association with abundance of hardwood species. Thus, while tree species succession and forest structural development occur contemporaneously, they are not equivalent processes, and their respective rates are not necessarily linearly related. The results of this study support the idea that silvicultural treatments to accelerate forest structural development should be concentrated on lower productivity sites when the management objective is reserve-wide coverage of structurally complex forests. Alternatively, high-productivity sites should be prioritized for restoration treatments when the management objective is to develop structurally complex forests on a portion of the landscape.

Evaluating observational methods to quantify snow duration under diverse forest canopies

Forests cover almost 40% of the seasonally snow-covered regions in North America. However, operational snow networks are located primarily in forest clearings, and optical remote sensing cannot see through tree canopies to detect forest snowpack. Due to the complex influence of the forest on snowpack duration, ground observations in forests are essential. We therefore consider the effectiveness of different strategies to observe snow-covered area under forests. At our study location in the Pacific Northwest, we simultaneously deployed fiber-optic cable, stand-alone ground temperature sensors, and time-lapse digital cameras in three diverse forest treatments: control second-growth forest, thinned forest, and forest gaps (one tree height in diameter). We derived fractional snow-covered area and snow duration metrics from the colocated instruments to assess optimal spatial resolution and sampling configuration, and snow duration differences between forest treatments. The fiber-optic cable and the cameras indicated that mean snow duration was 8 days longer in the gap plots than in the control plots (p < 0.001). We conducted Monte Carlo experiments for observing mean snow duration in a 40 m forest plot, and found the 95% confidence interval was ±5 days for 10 m spacing between instruments and ±3 days for 6 m spacing. We further tested the representativeness of sampling one plot per treatment group by observing snow duration across replicated forest plots at the same elevation, and at a set of forest plots 250 m higher. Relative relationships between snow duration in the forest treatments are consistent between replicated plots, elevation, and two winters of data.

Observations of distributed snow depth and snow duration within diverse forest structures in a maritime mountain watershed

See associated paper: Dickerson-Lange, S.E., Lutz, J.A., Gersonde, R., Martin, K.A., Forsyth, J.E., and J.D. Lundquist (2015, in preparation for Water Resources Research), Field observations of distributed snow depth and snow duration within diverse forest structures in a maritime mountain watershed