Evapotranspiration (ET) comprises a major portion of the water budget in forests, yet few studies have measured or estimated ET in semi‐arid, high‐elevation ponderosa pine forests of the south‐western USA or have investigated the capacity of models to predict ET in disturbed forests. We measured actual ET with the eddy covariance (eddy) method over 4 years in three ponderosa pine forests near Flagstaff, Arizona, that differ in disturbance history (undisturbed control, wildfire burned, and restoration thinning) and compared these measurements (415–510 mm year−1 on average) with actual ET estimated from five meteorological models [Penman–Monteith (P‐M), P‐M with dynamic control of stomatal resistance (P‐M‐d), Priestley–Taylor (P‐T), McNaughton–Black (M‐B), and Shuttleworth–Wallace (S‐W)] and from the Moderate Resolution Imaging Spectroradiometer (MODIS) ET product. The meteorological models with constant stomatal resistance (P‐M, M‐B, and S‐W) provided the most accurate estimates of annual eddy ET (average percent differences ranged between 11 and −14%), but their accuracy varied across sites. The P‐M‐d consistently underpredicted ET at all sites. The more simplistic P‐T model performed well at the control site (18% overprediction) but strongly overpredicted annual eddy ET at the restoration sites (92%) and underpredicted at the fire site (−26%). The MODIS ET underpredicted annual eddy ET at all sites by at least 51% primarily because of underestimation of leaf area index. Overall, we conclude that with accurate parameterization, micrometeorological models can predict ET within 30% in forests of the south‐western USA and that remote sensing‐based ET estimates need to be improved through use of higher resolution products. Copyright © 2014 John Wiley & Sons, Ltd.

Koa (Acacia koa) forests are found across broad environmental gradients in the Hawai‘ian Islands. Previous studies have identified koa forest health problems and dieback at the plot level, but landscape level patterns remain unstudied. The availability of high-resolution satellite images from the new GeoEye1 satellite offers the opportunity to conduct landscape-level assessments of forest health. The goal of this study was to develop integrated remote sensing and geographic information systems (GIS) methodologies to characterize the health of koa forests and model the spatial distribution and variability of koa forest dieback patterns across an elevation range of 600–1,000 m asl in the island of Kaua‘i, which correspond to gradients of temperature and rainfall ranging from 17–20 °C mean annual temperature and 750–1,500 mm mean annual precipitation. GeoEye1 satellite imagery of koa stands was analyzed using supervised classification techniques based on the analysis of 0.5-m pixel multispectral bands. There was clear differentiation of native koa forest from areas dominated by introduced tree species and differentiation of healthy koa stands from those exhibiting dieback symptoms. The area ratio of healthy koa to koa dieback corresponded linearly to changes in temperature across the environmental gradient, with koa dieback at higher relative abundance in warmer areas. A landscape-scale map of healthy koa forest and dieback distribution demonstrated both the general trend with elevation and the small-scale heterogeneity that exists within particular elevations. The application of these classification techniques with fine spatial resolution imagery can improve the accuracy of koa forest inventory and mapping across the islands of Hawai‘i. Such findings should also improve ecological restoration, conservation and silviculture of this important native tree species.

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An 8-year-old dense monotypic stand of naturally regenerated koa (Acacia koa A. Gray) on the Island of Hawai'i was selected to determine the effects of precommercial release thinning, phosphorous (P) fertilization and herbaceous weed control on growth of potential crop trees over approximately 30 months. Thinning consisted of cutting down all stems within a 4.5-m radius of the crop tree. Phosphorus was added at a rate of 300 kg ha -1 over two years. Herbaceous weeds were sprayed once with imazapyr, a broad-spectrum herbicide. Thinning alone or in combination with P fertilization significantly increased stem diameter increment and allometric estimates of the growth of leaf area and aboveground biomass. There was no significant increase in stem diameter, leaf area or biomass in the absence of thinning. Within the thinned treatment, P fertilization resulted in significant increases in tree height over time. Herbaceous weed control had no effect on tree growth. The atmospherically resistant vegetation index (ARVI), which was derived from spectral analyses of high-resolution satellite imagery (GeoEye1), was significantly