Fire affects numerous aspects of plant growth and anatomy, particularly in those species adapted to persist in fire‐prone environments. A key aspect of tree survival is rapid accumulation of protective bark within fire return intervals. We compared bark accumulation in five co‐occurring hardwood species within a longleaf pine (Pinus palustris) ecosystem in the mountains of northeastern Alabama, USA. Sampled species included blackjack oak (Quercus marilandica), sand hickory (Carya pallida), common persimmon (Diospyros virginiana), rock chestnut oak (Quercus montana), and red maple (Acer rubrum). Using bark thickness and inside bark diameter measurements taken at 20‐cm intervals along the main stem of saplings (average age 4–5 years) we found that, while average wood diameter did not differ across species, significant differences occurred in the ratio of bark to wood. Bark comprised over half (bark:wood = 0.55) of the basal diameter of blackjack oak, which was 3×, 4×, and 6× greater than the bark:wood ratio of sand hickory and rock chestnut oak, common persimmon, and red maple, respectively. Bark taper revealed that while other species allocated similarly to bark along the length of their stem, blackjack oak allocated much more at its base (in the flaming zone) and relatively less as height increased. Red maple, a commonly cited invader during fire‐free intervals, invested the least in bark thickness and, with rock chestnut oak, had an average height and height:diameter ratio significantly greater than blackjack oak and all other species, respectively. These results confirm the adaptive importance of bark thickness to enhancing species survival in frequent fire regimes.

Drylands comprise 40% of Earth's land mass and are critical to food security, carbon sequestration, and threatened and endangered wildlife. Exotic weed invasions, overgrazing, energy extraction, and other factors have degraded many drylands, and this has placed an increased emphasis on dryland restoration. The increased restoration focus has generated a wealth of experience, innovations and empirical data, yet the goal of restoring diverse, native, dryland plant assemblages composed of grasses, forbs, and shrubs has generally proven beyond reach. Of particular concern are shrubs, which often fail to establish or establish at trivially low densities. We used data from two Great Plains, USA coal mines to explore factors regulating shrub establishment. Our predictor data related to weather and restoration (e.g., seed rates, rock cover) variables, and our response data described shrub abundances on fields of the mines. We found that seeded non‐shrubs, especially grasses, formed an important competitive barrier to shrub establishment: With every one standard deviation increase in non‐shrub seed rate, the probability shrubs were present decreased ~0.1 and shrub cover decreased ~35%. Since new fields were seeded almost every year for >20 years, the data also provided a unique opportunity to explore effects of stochastic drivers (i.e., precipitation, year effects). With every one standard deviation increase in precipitation the first growing season following seeding, the probability shrubs were present decreased ~0.07 and shrub cover decreased ~47%. High precipitation appeared to harm shrubs by increasing grass growth/competition. Also, weak evidence suggested shrub establishment was better in rockier fields where grass abundance/competition was lower. Multiple lines of evidence suggest reducing grass seed rates below levels typically used in Great Plains restoration would benefit shrubs without substantially impacting grass stand development over the long term. We used Bayesian statistics to estimate effects of seed rates and other restoration predictors probabilistically to allow knowledge of the predictors' effects to be refined through time in an adaptive management framework. We believe this framework could improve restoration planning in a variety of systems where restoration outcomes remain highly uncertain and ongoing restoration efforts are continually providing new data of value for reducing the uncertainty.

Maternal effects in production gardens may improve or inhibit the performance of seeds planted in large-scale restoration. In ex situ experiments, we tested seeds of the native grass Poa secunda J. Presl (Poaceae) produced by the same maternal families grown in 3 different production garden environments. We measured progeny performance for 5 variables: germination, emergence, growth, competitive tolerance, and competitive ability. Seed size was correlated with root morphology, with larger seeds producing less root volume. Larger seeds conferred better germination and higher competitive ability only in some progeny growth environments. We found that the production garden affected seed size in some maternal families more than others. Also, other effects of the production garden were uncorrelated with seed size: early plant size, final plant size, and competitive tolerance. Adaptive maternal effects were found for germination in one production environment and for early plant size in another production environment. By understanding the influence of maternal effects under field conditions, we may be able to manipulate production environments to maximize the performance and competitive ability of restoration materials.

Combining Q-methodology with focus groups offers a novel opportunity to explore how researchers and managers can collectively address natural resource management issues. We explored the potential utility of this pairing for prioritizing long-term vegetation recovery research needs after wildfire at a two-day workshop. The approach entailed individual Q-sort activities, followed by focus group discussion about differences and similarities in Q-sort outcomes between managers and researchers. We found that Q-methodology was a versatile discussion tool that offered opportunities for building shared definitions of management issues and identifying new pathways for collaboration between diverse participants. Group discussion around research needs also fostered opportunities for identifying organizational barriers and fostering partnerships to overcome them. Collecting social data on research needs prior to designing or conducting data collection efforts can help ensure that outputs have practical value and utility for land management.Study Implications: Establishing shared research priorities between researchers and managers is one way to ensure that scientific advancements have practical applications. Using outputs from Q-sort activities as a prompt to initiate discussion between researchers and managers is an effective technique for understanding divergent prioritizations, identifying organizational and scientific barriers, and establishing feasible next steps for collective action to produce application-oriented research. Employing mixed-method social data collection early in the land management planning process is increasingly valuable; many recent policies for forest and natural resource management require the incorporation of collaborative components.

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. Remeasured sites (sampled one and 12 years post fire) showed recruitment of new understory species and differing, diverse responses to burning by several common plant species. In 2016, low-severity burned sites had generally the highest woody fuel loading, which may increase risk of repeated surface burning, although the reduction in live tree density would still result in decreased fire risk and behavior. Understory community composition correlated with multiple biotic and abiotic factors, including moss depth, canopy cover, elevation, aspect, and dNBR. Overall, our findings can improve landscape-level predictions of ecosystem condition following fire based on dNBR.