Skip to main content
Dryad logo

Supporting data for: Planted conifer seedling survival in a post-wildfire landscape in New Mexico: From experimental planting to predictive probabilistic surfaces

Citation

Hurteau, Matthew; Marsh, Christopher; Crockett, Joseph (2022), Supporting data for: Planted conifer seedling survival in a post-wildfire landscape in New Mexico: From experimental planting to predictive probabilistic surfaces, Dryad, Dataset, https://doi.org/10.5061/dryad.fn2z34tw6

Abstract

Across the southwestern United States, high-severity wildfire is causing increasingly large patches of tree mortality, removing the seed sources required for the natural regeneration of these formerly conifer-dominated landscapes. Planting tree seedlings can accelerate succession and restore the ecosystem services that pre-wildfire forests provided, but in the semi-arid southwestern US, the survival of planted conifer seedlings is typically low. We present data on a seedling planting experiment within the footprint of the 2011 Las Conchas Fire in northern New Mexico, using microclimate variables and site-level topographic indices to determine which factors influence seedling survival of four conifer tree species. We then extrapolate these findings to the wider landscape for the most commonly planted species, producing a spatial projection of probabilistic seedling survival as a function of both site- and landscape-scale factors, using readily available topographic data. Both sets of analyses highlight the importance of landscape heterogeneity, quantifiable using topographic indices, in shaping microclimatic environments and affecting seedling survival in a predictable manner. Our results demonstrate that using these methods to guide future plantings may increase conifer tree seedling survival in high-severity post-wildfire landscapes.

Methods

Data include planted seedling survival data from a 3-year experiment that included planting four species of tree seedling stratified by aspect (northerly, southerly) and vegetation cover (under shrubs, in the open). Associate measurements of microclimate variables, including temperature, relative humidity, and precipitation are also included. Experimental planting data were analyzed using piecewise exponential models. Spatially modeling the probability of planted seedling survival as a function of topography involved the use of DEM and other remotely sensed data, planted seedling survival data for ponderosa pin, and boosted regression trees.

Funding

U.S. Department of Agriculture, Award: 2017-67004-26486

Joint Fire Science Program, Award: 16-1-05-8