## 3 Results and Discussion
### Ecosystem Performance Anomalies  
The 2000-2008 average EPA values were averaged and grouped into seven classes based on the relative confidence of their anomaly from expected values: severe under and over performance (95% confidence limits), under and over performance (90% confidence limits), low-normal and high-normal (80% confidence limits), and normal (\(<\)80% confidence limits) (Table 1). Because the EEP and site potential models are developed from unburned areas, a disturbance often generates a statistically significant negative EPA, as the EEP model does not 'expect' the disturbance because it is driven by only weather and site conditions and trained on unburned pixels. Since early successional stands were excluded from model development, the EEP model reflects an undisturbed/mature stand performance, allowing successional dynamics (normalized to yearly weather variations) to be represented as anomalies from mature forests. Annual maps of the model residuals (EPA) indicated that 72.7% of the evaluated boreal forest performed normally (within the 90% confidence limits) when averaged over the study period (Figure 2), while individual years tended to have a lower percentage (\(\sim\)60%) in the range of normal EPA values (Table 1). Years that had a low percentage of normal performance tended to be associated with years of high fire occurrence (e.g., 2004) and those immediately following a fire (e.g., 2005). The distribution of EPA values was strongly skewed toward underperformance (Table 1), with an overall average value of \(-\)28.7 due to disturbance [43] (Figures 2 and 3). For example, the 2000-2008 average EPA was underperforming in 23.4% of the study area, far more than the 3.9% occupied by overperforming classes (Table 1, Figure 2). The majority of EPA perturbations were caused by fires and insect outbreaks (insect damage perimeters were from the Alaska Department of Natural Resources) [5]. Correspondingly, the relationship between current plus previous year percent area burned and proportion of EPA in severe underperformance follows a positive linear relationship (R\({}^{2}=0.70\), \(p<0.05\)). The years 2007 and 2008 appeared to be outliers, with a higher than average proportion of overperforming EPA values. This overperformance may be due to the dominance of productive herbaceous vegetation and liberation of nutrients in areas impacted by 2004 and 2005 fires. The 2000-2008 average EPA in coniferous forest was \(-1.5\) (\(\pm 3.5\) SE). Our model development occurred in areas of coniferous and mixed forest that were not recently disturbed, hence the average coniferous EPA near zero indicated that our model performed as expected. EPA values could therefore also be thought of as the performance departure from the conditions expected of an undisturbed coniferous stand. Deciduous stands for example, had an average EPA of 33.8 (\(\pm 2.7\) SE), suggesting greater ecosystem performance than coniferous forest, a commonly reported finding [5,16,29,34]. This is partly driven by higher deciduous productivity [29], but also by higher near-infrared reflectance and higher NDVI from broadleaf vegetation than need leaf vegetation. This near-infrared reflectance difference is driven by the broadleaf mesophyll internal structure [56]. This pattern is supported by Figure 3, which demonstrates that areas of deciduous forest tended to be overperforming or highly overperforming. Areas within river meanders, oxbows, and areas of moist soils also tend to be overperforming because these sites are protected from fire, allowing them to mature longer than the study area average. To validate our EPA results, we compared GSN, our proxy of actual ecosystem performance, to Landsat-derived aboveground biomass measurements for the Yukon Flats area [44]. This comparison yielded a moderately strong linear relationship (R\({}^{2}\) = 0.47, \(p<0.01\)), indicating that GSN is a reasonable proxy of ecosystem performance. Figure 2: Years 2000 to 2008 average Ecosystem Performance Anomaly (EPA) for the Yukon River Basin boreal forest.