Douglas J. Shinneman

The efficacy of salvage logging in reducing subsequent fire severity in conifer-dominated forests of Minnesota, USA

Although primarily used to mitigate economic losses following disturbance, salvage logging has also been justified on the basis of reducing fire risk and fire severity; however, its ability to achieve these secondary objectives remains unclear. The patchiness resulting from a sequence of recent disturbances-blowdown, salvage logging, and wildfire-provided an excellent opportunity to assess the impacts of blowdown and salvage logging on wildfire severity. We used two fire-severity assessments (tree-crown and forest-floor characteristics) to compare post-wildfire conditions among three treatment combinations (Blowdown-Salvage-Fire, Blowdown-Fire, and Fire only). Our results suggest that salvage logging reduced the intensity (heat released) of the subsequent fire. However, its effect on severity (impact to the system) differed between the tree crowns and forest floor: tree-crown indices suggest that salvage logging decreased fire severity (albeit with modest statistical support), while forest-floor indices suggest that salvage logging increased fire severity. We attribute the latter finding to the greater exposure of mineral soil caused by logging operations; once exposed, soils are more likely to register the damaging effects of fire, even if fire intensity is not extreme. These results highlight the important distinction between fire intensity and severity when formulating post-disturbance management prescriptions.

Challenges of Establishing Big Sagebrush (Artemisia tridentata) in Rangeland Restoration: Effects of Herbicide, Mowing, Whole-Community Seeding, and Sagebrush Seed Sources☆,☆☆

Abstract The loss of big sagebrush (Artemisia tridentata Nutt.) on sites disturbed by fire has motivated restoration seeding and planting efforts. However, the resulting sagebrush establishment is often lower than desired, especially in dry areas. Sagebrush establishment may be increased by addressing factors such as seed source and condition or management of the plant community. We assessed initial establishment of seeded sagebrush and four populations of small outplants (from different geographies, climates, and cytotypes) and small sagebrush outplants in an early seral community where mowing, herbicide, and seeding of other native plants had been experimentally applied. No emergence of seeded sagebrush was detected. Mowing the site before planting seedlings led to greater initial survival probabilities for sagebrush outplants, except where seeding also occurred, and these effects were related to corresponding changes in bare soil exposure. Initial survival probabilities were > 30% greater for the local population of big sagebrush relative to populations imported to the site from typical seed transfer distances of ∼320–800 km. Overcoming the high first-year mortality of outplanted or seeded sagebrush is one of the most challenging aspects of postfire restoration and rehabilitation, and further evaluation of the impacts of herb treatments and sagebrush seed sources across different site types and years is needed.

Exploring Climate Niches of Ponderosa Pine ( Pinus ponderosa Douglas ex Lawson) Haplotypes in the Western United States: Implications for Evolutionary History and Conservation

Ponderosa pine (Pinus ponderosa Douglas ex Lawson) occupies montane environments throughout western North America, where it is both an ecologically and economically important tree species. A recent study using mitochondrial DNA analysis demonstrated substantial genetic variation among ponderosa pine populations in the western U.S., identifying 10 haplotypes with unique evolutionary lineages that generally correspond spatially with distributions of the Pacific (P. p. var. ponderosa) and Rocky Mountain (P. p. var. scopulorum) varieties. To elucidate the role of climate in shaping the phylogeographic history of ponderosa pine, we used nonparametric multiplicative regression to develop predictive climate niche models for two varieties and 10 haplotypes and to hindcast potential distribution of the varieties during the last glacial maximum (LGM), ~22,000 yr BP. Our climate niche models performed well for the varieties, but haplotype models were constrained in some cases by small datasets and unmeasured microclimate influences. The models suggest strong relationships between genetic lineages and climate. Particularly evident was the role of seasonal precipitation balance in most models, with winter- and summer-dominated precipitation regimes strongly associated with P. p. vars. ponderosa and scopulorum, respectively. Indeed, where present-day climate niches overlap between the varieties, introgression of two haplotypes also occurs along a steep clinal divide in western Montana. Reconstructed climate niches for the LGM suggest potentially suitable climate existed for the Pacific variety in the California Floristic province, the Great Basin, and Arizona highlands, while suitable climate for the Rocky Mountain variety may have existed across the southwestern interior highlands. These findings underscore potentially unique phylogeographic origins of modern ponderosa pine evolutionary lineages, including potential adaptations to Pleistocene climates associated with discrete temporary glacial refugia. Our predictive climate niche models may inform strategies for further genetic research (e.g., sampling design) and conservation that promotes haplotype compatibility with projected changes in future climate.

Lidar Aboveground Vegetation Biomass Estimates in Shrublands: Prediction, Uncertainties and Application to Coarser Scales

Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure and statistical measures of this structure (e.g., standard deviation of height was a strong predictor of biomass). Using our model results, we developed spatially-explicit Lidar estimates of total and shrub biomass across our study site in the Great Basin, U.S.A., for monitoring and planning in this imperiled ecosystem.

Approaches to Modeling Landscape-Scale Drought-Induced Forest Mortality

Drought stress is an important cause of tree mortality in forests, and drought-induced disturbance events are projected to become more common due to climate change. Landscape Disturbance and Succession Models (LDSM) are becoming widely used to project climate change effects on forests, including potential interactions with natural and anthropogenic disturbances, and to explore the efficacy of alternative management actions to mitigate consequences of global changes on forests and ecosystem services. Recent studies in which drought mortality effects were incorporated into LDSMs project significant potential changes in forest composition and carbon storage, largely due to differential effects of drought on tree species and interactions with other disturbance agents. In this chapter, we review how drought affects forest ecosystems and the different ways drought effects have been modeled (both spatially and aspatially) in the past. Building on those efforts, we describe several approaches to modeling drought effects in LDSMs, discuss advantages and shortcomings of each, and include two case studies for illustration. The first approach features the use of empirically derived relationships between measures of drought and the loss of tree biomass to drought-induced mortality. The second uses deterministic rules of species mortality for given drought events to project changes in species composition and forest distribution. A third approach is more mechanistic, simulating growth reductions and death caused by water stress. Because modeling of drought effects in LDSMs is still in its infancy, and because drought is expected to play an increasingly important role in forest health, further development of modeling drought–forest dynamics is urgently needed.

Identifying key climate and environmental factors affecting rates of post-fire big sagebrush (Artemisia tridentata) recovery in the northern Columbia Basin, USA

Sagebrush steppe of North America is considered highly imperilled, in part owing to increased fire frequency. Sagebrush ecosystems support numerous species, and it is important to understand those factors that affect rates of post-fire sagebrush recovery. We explored recovery of Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) and basin big sagebrush (A. tridentata ssp. tridentata) communities following fire in the northern Columbia Basin (Washington, USA). We sampled plots across 16 fires that burned in big sagebrush communities from 5 to 28 years ago, and also sampled nearby unburned locations. Mixed-effects models demonstrated that density of large–mature big sagebrush plants and percentage cover of big sagebrush were higher with time since fire and in plots with more precipitation during the winter immediately following fire, but were lower when precipitation the next winter was higher than average, especially on soils with higher available water supply, and with greater post-fire mortality of mature big sagebrush plants. Bunchgrass cover 5 to 28 years after fire was predicted to be lower with higher cover of both shrubs and non-native herbaceous species, and only slightly higher with time. Post-fire recovery of big sagebrush in the northern Columbia Basin is a slow process that may require several decades on average, but faster recovery rates may occur under specific site and climate conditions.

Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change

Abstract. Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently available, geographically widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype‐climate relationship using a niche‐overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.