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

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 ana..., 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.,

在美国西南部区域，高烈度野火正催生规模持续扩大的林木死亡斑块，消除了这类曾以针叶林为主的景观实现自然更新所需的种源储备。人工栽植苗木可加速群落演替进程，恢复野火前森林所提供的各类生态系统服务，但美国西南部半干旱区域内，人工栽植的针叶林苗木存活率普遍偏低。本数据集涵盖2011年新墨西哥州北部拉斯孔查斯野火（Las Conchas Fire）过火范围内开展的苗木种植试验数据：研究通过微气候变量与样地尺度地形指数，明确影响4种针叶树苗木存活的关键调控因子；随后针对最常用的造林树种，将试验结论外推至更大景观尺度，依托易获取的地形数据，生成基于样地与景观尺度因子的概率性苗木存活率空间投影结果。两组分析……数据集包含为期3年的试验人工苗木存活率数据，该试验按坡向（北向、南向）与植被覆盖条件（灌丛下、开阔地）对4个树种的苗木开展分组栽植。同步收录的配套数据还包括微气候变量测定结果，涵盖气温、相对湿度与降水量。试验栽植数据采用分段指数模型（piecewise exponential models）开展分析。在基于地形因子构建人工苗木存活率概率空间模型时，研究使用了数字高程模型（Digital Elevation Model，DEM）、其他遥感数据、黄松（Pinus ponderosa）人工苗木存活率数据，以及提升回归树（Boosted Regression Trees）方法。