S. N. Burrows

Application of Geostatistics to Characterize Leaf Area Index (LAI) from Flux Tower to Landscape Scales Using a Cyclic Sampling Design

AbstractAccurate characterization of leaf area index (LAI) is required to quantify the exchange of energy, water, and carbon between terrestrial ecosystems and the atmosphere. The objective of this study was to use a cyclic sampling design to compare the spatial patterns of LAI of the dominant terrestrial ecosystems that comprised the area around the 447-m WLEF television tower, equipped with an eddy flux system, near Park Falls, Wisconsin, USA. A second objective was to compare the efficiency of cyclic, random, and uniform sampling designs in terms of the precision of spatial information derived per unit sampling effort. The vegetation surrounding the tower was comprised (more than 80%) of four major forest cover types: forested wetlands, upland aspen forests, upland northern hardwood forests, and upland pine forests, and a fifth, nonforested cover type, grass (open meadow). LAI differed significantly among the five cover types and averaged 3.45, 3.57, 3.82, 3.99, and 1.14 for northern hardwoods, aspen, forested wetlands, upland conifers, and grass, respectively. The cyclic sampling design maximized information about the variance of vegetation characteristics of the heterogeneous landscape and decreased by 60% the number of plots needed to obtain the same confidence interval width using a random sampling design. The range of spatial autocorrelation for LAI was 147 m, but it was decreased to 117 m when vegetation cover was included as a covariate. The cyclic sampling design has several important advantages over other sampling designs. The cyclic sampling design increased the sampling efficiency by optimizing the placement of plots so they were distributed more efficiently for geostatistical analyses such as semi-variograms, correlograms, and spatial regression and can incorporate covariates (for example, vegetation cover, soil properties, and so on) that may explain the sources of spatial patterns. The cyclic sampling design was used to derive a spatial map of LAI and the average LAI for the 3 × 2 km area centered on the flux tower was 3.51 ± 0.89 (with a minimum of 0 and a maximum of 6.35). Airborne and satellite reflectance data have also been used to characterize LAI, but in this region, and many other forests of the world, remotely sensed vegetation indexes saturate in forests with an LAI greater than 3–5. The cyclic sampling design also provides a general ecological sampling approach that can be used at multiple scales.

Physiological Tradeoffs in the Parameterization of a Model of Canopy Transpiration

We examined physiological parameter tradeoffs in modeling stomatal control of transpiration from a number of forest species. Measurements of sapflux, micrometeorology, and leaf area index were made in stands representing 85% of the forest ecosystems around the WLEF eddy flux tower in northern Wisconsin. A Jarvis-based canopy conductance model was used to simulate canopy transpiration (EC) for five tree species from these stands. They consisted of conifers and deciduous species in both upland and wetland locations. Parameter estimation was used to assess the tradeoffs between physiological parameters used in the calculation of stomatal conductance. These tradeoffs were then evaluated against current theory on stomatal regulation of leaf water potential. The results showthat the best simulations of EC were obtained with values of maximum stomatal conductance (gSmax) and stomatal sensitivity to vapor pressure deficit (d) that closely followed this hydraulic theory. The model predictions reveal a large variation in the strategies used to regulate water potential among species. Aspen showed the greatest tendency towards efficiency, indicating that it has high EC under lowvapor pressure deficit ( D) conditions, but is susceptible to rapid EC decline at moderate to high D. Other species showed more conservative water use. The results indicate that inter-specific differences in dynamic response to D can produce large spatial variation in EC under typical environmental conditions. 2002 Elsevier Science Ltd. All rights reserved.

Spatial Controls of Pre–Euro-American Wind and Fire Disturbance in Northern Wisconsin (USA) Forest Landscapes

We elucidate spatial controls of wind and fire disturbance across northern Wisconsin (USA), where climatic and topographic gradients are not strong, using data from the original US Public Land Survey (PLS) notes. These records contain information on the location and extent of heavy windthrows and stand-replacing fires prior to Euro-American settlement. The spatial patterns of windthrow and fire were spatially clustered at all scales in this historical environment, with stronger associations at local than regional scales. Logistic regression shows environmental variables to have a strong influence on this pattern. In the case of heavy windthrow, environmental drivers of disturbance pattern are fairly consistent across the region. The effects of climate and vegetation are predominant at all scales, but effects are often indirect, with strong interactions between them. Interactions between these two drivers and soil characteristics are also sometimes present. In contrast, models of stand-replacing fire show simple and direct control within and across fire-prone landscapes of historical northern Wisconsin, with climate and physiography as the main factors explaining the distribution of fire disturbance. This simple and direct control is lost at the regional scale, where climate, physiographic, soil, and vegetation variables, along with interactions between them, are significant factors. Contrary to other regions, the topographic effects are generally not important in predicting either wind or fire disturbance. Our work suggests that, in landscapes that lack strong environmental patterning, climate maintains its role as a primary driver of these natural disturbances, but topography is replaced by interactions and feedbacks with other forms of environmental heterogeneity.

Automated Parameterization of Land Surface Process Models Using Fuzzy Logic

All land surface process models require parameters that are proxies for spatial processes that are impractical or impossible to measure. Recent developments in model parameter estimation theory suggest that information obtained from calibrating such models is inherently uncertain in nature. As a consequence, identification of optimum parameter values is often highly non-specific. A calibration framework using fuzzy logic is presented to deal with such uncertain information. An application of this technique to calibrate the sub-canopy controls on transpiration in a land surface process model demonstrates that objective estimates of parameter values and expected ranges of predictions can be obtained with suitable choices for objective functions. An iterative refinement in parameter estimates was possible with conditional sampling techniques. The automated approach was able to correctly identify parameter tradeoffs such that two strongly different sets of parameters could