Evidence of compounded disturbance effects on vegetation recovery following high-severity wildfire and spruce beetle outbreak.

Spruce beetle (Dendroctonus rufipennis) outbreaks are rapidly spreading throughout subalpine forests of the Rocky Mountains, raising concerns that altered fuel structures may increase the ecological severity of wildfires. Although many recent studies have found no conclusive link between beetle outbreaks and increased fire size or canopy mortality, few studies have addressed whether these combined disturbances produce compounded effects on short-term vegetation recovery. We tested for an effect of spruce beetle outbreak severity on vegetation recovery in the West Fork Complex fire in southwestern Colorado, USA, where much of the burn area had been affected by severe spruce beetle outbreaks in the decade prior to the fire. Vegetation recovery was assessed using the Landsat-derived Normalized Difference Vegetation Index (NDVI) two years after the fire, which occurred in 2013. Beetle outbreak severity, defined as the basal area of beetle-killed trees within Landsat pixels, was estimated using vegetation index differences (dVIs) derived from pre-outbreak and post-outbreak Landsat images. Of the seven dVIs tested, the change in Normalized Difference Moisture Index (dNDMI) was most strongly correlated with field measurements of beetle-killed basal area (R2 = 0.66). dNDMI was included as an explanatory variable in sequential autoregressive (SAR) models of NDVI2015. Models also included pre-disturbance NDVI, topography, and weather conditions at the time of burning as covariates. SAR results showed a significant correlation between NDVI2015 and dNDMI, with more severe spruce beetle outbreaks corresponding to reduced post-fire vegetation cover. The correlation was stronger for models which were limited to locations in the red stage of outbreak (outbreak ≤ 5 years old at the time of fire) than for models of gray-stage locations (outbreak > 5 years old at the time of fire). These results indicate that vegetation recovery processes may be negatively impacted by severe spruce beetle outbreaks occurring within a decade of stand-replacing wildfire

A Comment on “Management for Mountain Pine Beetle Outbreak Suppression: Does Relevant Science Support Current Policy?”

There are two general approaches for reducing the negative impacts of mountain pine beetle, Dendroctonus ponderosae Hopkins, on forests. Direct control involves short-term tactics designed to address current infestations by manipulating mountain pine beetle populations, and includes the use of fire, insecticides, semiochemicals, sanitation harvests, or a combination of these treatments. Indirect control is preventive, and designed to reduce the probability and severity of future infestations within treated areas by manipulating stand, forest and/or landscape conditions by reducing the number of susceptible host trees through thinning, prescribed burning, and/or alterations of age classes and species composition. We emphasize that “outbreak suppression” is not the intent or objective of management strategies implemented for mountain pine beetle in the western United States, and that the use of clear, descriptive language is important when assessing the merits of various treatment strategies

The Effectiveness of Vegetation Management Practices for Prevention and Control of Bark Beetle Infestations in Coniferous Forests of the Western and Southern United States

Insects are major components of forest ecosystems, representing most of the biological diversity and affecting virtually all processes and uses. In the USA, bark beetles (Coleoptera: Curculionidae, Scolytinae) heavily influence the structure and function of these ecosystems by regulating certain aspects of primary production, nutrient cycling, ecological succession and the size, distribution and abundance of forest trees. The purpose of this report is to review tree and stand factors associated with bark beetle infestations and analyze the effectiveness of vegetation management practices for mitigating the negative impacts of bark beetles on forest ecosystems. We describe the current state of our knowledge and identify gaps for making informed decisions on proposed silvicultural treatments. This review draws from examination of 498 scientific publications (many of which are cited herein) on this and related topics

Comparison between spruce beetle outbreak extent detected by ADS from 2002 to the indicated year (left; ADS polygons shown in orange) and dNDMI (right).

<p>Top dNDMI = NDMI₂₀₀₆ –NDMI₂₀₀₂; bottom dNDMI = NDMI₂₀₁₂ –NDMI₂₀₀₂. Color scales for dNDMI are based on standard deviations within images.</p

Variable importance plots for the best-fitting multivariate models for red and gray-stage outbreak locations.

<p>Variable importance is determined by the ΔAIC between the full model and model with the indicated variable removed.</p

Overview map of the West Fork Complex burn area.

<p>Locations of the nearest weather station (Blue Park RAWS) and field sampling locations around Wolf Creek Pass are indicated. Area in red indicates burn area classified as ‘high severity’ by the US Forest Service Burned Area Emergency Response (BAER). Red square in inset shows the location of the study area within Colorado. Base imagery is from the USGS National Map server.</p

R² values from OLS regression tests comparing 2002–2015 dVIs to the beetle-killed basal area of spruce in field plots measured in 2015.

<p>R² values from OLS regression tests comparing 2002–2015 dVIs to the beetle-killed basal area of spruce in field plots measured in 2015.</p

Top-performing multivariate SAR models predicting 2015 NDVI for point locations in red-stage and gray-stage of spruce beetle outbreak prior to fire.

<p>Top-performing multivariate SAR models predicting 2015 NDVI for point locations in red-stage and gray-stage of spruce beetle outbreak prior to fire.</p

Relationship of measured basal area of killed <i>P</i>. <i>engelmannii</i> in field plots to dNDMI values at plot locations.

<p>Plot areas are 20 x 20 m.</p

Date and sensor type for Landsat scenes used in analysis.

<p>Date and sensor type for Landsat scenes used in analysis.</p