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Compassion Compass Group

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Michael Adams
Michael Adams

Up The Duff Pdf 12 NEW!


Encompassing approximately 13,377 acres that will protect 12 giant sequoia groves, the emergency fuels treatments would remove surface and ladder fuels that present the greatest wildfire risk and include hand cutting of small trees, mechanical removal of trees, application of borate on green stumps, pulling duff away from the base of large giant sequoias and prescribed burning.




Up The Duff Pdf 12



Fire has historically been a primary control on succession and vegetation dynamics in boreal systems, although modern changing climate is potentially increasing fire size and frequency. Large, often remote fires necessitate large-scale estimates of fire effects and consequences, often using Landsat satellite-derived dNBR (differenced Normalized Burn Ratio) to estimate burn severity. However, few studies have examined long-term field measures of ecosystem condition in relation to dNBR severity classes in boreal Alaska, USA. The goals of this study were: 1) assess changes in dominant vegetation at plots resampled one and 12 years post fire; 2) use dNBR classes to characterize vegetation and downed woody fuels 12 years post fire; and 3) characterize the relationship between biophysical, topographic, and remotely sensed characteristics (e.g., moss and duff depth, canopy cover, elevation, aspect, dNBR) and understory species assemblages 12 years post fire.


Understory species richness doubled (from 39 to 73) between 2005 and 2016; some common species increased in cover over time (e.g., Ledum groenlandicum Oeder) while others decreased (e.g., Hylocomium splendens [Hedw.] Schimp.). In 2016, live and dead tree densities, tall shrub cover, and 1- and 100-h woody fuels were significantly different among dNBR classes; moss and duff depth, canopy cover, and spruce seedling density were not. Elevation and aspect significantly influenced tall shrub cover, hardwood sapling density, and downed woody fuel loads. Understory plant communities differed between unburned and all burn classes, as well as between low and high dNBR severity. Ordination analysis showed that overstory (e.g., live tree density), understory (e.g., moss depth, woody fuel loading), and site (elevation, aspect, dNBR) significantly influences understory species assemblages.


The understory vegetation composition, and its association with various biotic and abiotic site characteristics (e.g., moss and duff depth, canopy cover, dNBR), were visualized using non-metric multidimensional scaling (NMDS) implemented with the metaMDS() wrapper from the vegan package (Oksanen et al. 2018), which, by default, implements the recommendations of Minchin (1987) in R. NMDS was chosen because it does not rely on an assumption of linear relationships among variables and allows examination of the trends in understory species in relation to multiple factors while reducing noise inherent in species diversity data (McCune and Grace 2002). The number of zeros in the data was reduced by excluding rare species that occurred at only a single site, resulting in a reduction from 118 to 74 species. A three-axis solution with Bray-Curtis distance measure was chosen, with the default metaMSD() Wisconsin square-root transformation (Minchin 1987) of the data to correct for the large range in cover values. The starting configuration was random and dimensionality was determined based on a scree plot of stress and dimensions (run in PC-ORD), whereby using four dimensions did not measurably improve the stress of the model (McCune and Grace 2002). Site characteristic vectors (e.g., dNBR, fuel loading) were then fit to the final ordination solution using the envfit() function (vegan package).


Density of live and of dead trees varied predictably with dNBR burn severity class, tracking with previous research that showed relatively strong relationships between overstory and remotely sensed indices (Murphy et al. 2008; Hudak et al. 2007). Spruce seedling density, on the other hand, was not significantly different among dNBR severity classes. Previous studies relating spruce regeneration to burn severity have alternately shown that Picea mariana is most successful on sites with some organic layer remaining (Johnstone and Chapin 2006b; Shenoy et al. 2011), that there is no relationship of seedling density to depth of organic layer burning (Gibson et al. 2016), or that regeneration success was highest in areas with exposed mineral soil and minimal organic cover (Mallik et al. 2010). The lack of trend in seedling density could reflect the lack of difference in moss and duff depth among dNBR classes at our sites, which may be traced back to the insensitivity of dNBR to organic layer consumption (French et al. 2008).


Given previous work relating field measures of surface burn severity to dNBR, we did not necessarily expect to see a strong trend in moss and duff depth with dNBR severity class (e.g., Hoy et al. 2008), and in fact there was no significant difference in organic layer depth among dNBR classes at our sites. Likely issues are the insensitivity of Landsat to height variation, and that the 30 m pixel resolution of Landsat is too coarse to capture the highly heterogeneous patterns of organic layer consumption (Alonzo et al. 2017). In addition, issues of topographic and canopy shadowing due to low solar elevation angles that affect dNBR and similar indices, even at lower latitudes, are compounded in high latitude areas such as Alaska (French et al. 2008). Overall, our results support the established understanding that Landsat-based dNBR reflects differences in overstory, but not necessarily understory, burn severity in this ecosystem.


On the other hand, downed woody fuel load did vary significantly among dNBR classes, with higher fuel loads in areas classified as low burn severity. In general, fire is expected to affect downed woody fuels by first consuming them during the active fire event (thus lowering fuel loading) but then by contributing fuels from mortality of trees and woody shrubs that become part of the surface fuel layer as they fall, as was evident upon revisiting the sites 11 years later. Higher fuel loads may raise the risk of more severe reburn effects but only at times when conditions are sufficiently dry to allow for fire to carry in the relatively high-moisture moss and duff ground layer (Johnstone et al. 2010). However, we did not explicitly test the probability of reburn, and the canopy fuel load would still be much lower in these areas than in unburned stands (based on live tree density). Other studies of post-fire downed woody fuel loading in North American boreal forests have generally focused on quantifying accumulation of woody fuels over time (e.g., Johnston et al. 2015) without differentiating between burn severity levels, while others have focused only on finer fuel available for flaming consumption (e.g., Thompson et al. 2017) or on stands at least 30 years post fire (e.g., Hély et al. 2000), making comparison with our results difficult. Our fuel load estimates were similar to those measured in at least some similar stands of a study focused on time since fire (Johnston et al. 2015). However, our estimates of coarse woody debris (1000-h) were higher, likely because our sampling was concentrated in a timeframe when more dead trees had recently fallen to become surface fuel.


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