Modelling tree habitat suitability (HS) is a common practice to assess tree species distribution across a broad range of spatial scales. However, it is seldom used to test the extent that modelled HS-scores (probability of species occurrence) can represent on-the-ground measures of species-structural characteristics. In this study, we compare four parametric and non-parametric models generated with the R-package, sdm, to assess the potential for these models to estimate tree species distribution of balsam fir [Abies balsamea (L.) Mill.] in naturally-growing forests across an extensive landscape. Central to this development are inventory plot data of species presence-absence and four abiotic factors linked to plant growth and distribution. The study’s abiotic factors include: (1) photosynthetically active radiation; (2) growing degree-days; (3) relative extractable soil water content; and (4) near-surface wind speed, all expressed spatially at 30-m resolution. To gauge whether modelled HS can explain structural characteristics in balsam fir-dominated stands, field-based estimates of site index (SI) and cumulative aboveground biomass (ABG) were compared against independently-derived HS-scores. The results showed that: (i) random forest was the most successful at representing species distribution of balsam fir among the four methods considered; (ii) overall growing conditions for balsam fir was observed to be most favourable on north-facing slopes, particularly in the northwest part of the target landscape, where near-surface air temperatures are cooler, soils are moderately wetter, and wind speeds are lower; (iii) tree-based calculations of SI were partially characterised by patterns in modelled HS-scores, due to scale differences (i.e., from individual tree to 30-m grid cells) and an inadequate number of sample trees; and (iv) patterns of cumulative AGB were more accurately represented by species HS. Modelled HS-scores, as potential indicators of tree species habitat preference, AGB, and species distribution, can offer key ecological information essential to inform forest management and conservation planning at the landscape level.

对树木栖息地适应性（HS）进行建模是一种评估大范围空间尺度上树种分布的常用方法。但是，很少使用它来测试建模的HS分数（物种发生的概率）可以代表物种结构特征的实地度量的程度。在这项研究中，我们比较了用R包sdm生成的四个参数模型和非参数模型，以评估这些模型评估香脂冷杉[ Abies balsamea]的树种分布的潜力。（L.）Mill。]在广阔景观中自然生长的森林中。这一发展的中心是物种不存在和与植物生长和分布相关的四个非生物因素的库存图数据。该研究的非生物因素包括：（1）光合有效辐射；（2）生长日数；（3）相对可提取土壤含水量；（4）近地表风速，均以30 m分辨率在空间上表示。为了评估建模的HS是否可以解释香脂冷杉为主的林分的结构特征，基于现场的站点指数（SI）和累积地上生物量（ABG）的估计）与独立来源的HS得分进行了比较。结果表明：（i）在所考虑的四种方法中，随机森林最能代表苦瓜冷杉的物种分布；（ii）香脂冷杉的总体生长条件在朝北的山坡上最为有利，特别是在目标景观的西北部，那里的近地表气温较低，土壤适度湿润，风速较低; （iii）由于尺度差异（例如，从单个树到30米网格单元）以及样本树数量不足，基于树的SI计算的部分特征在于建模的HS分数中的模式；（iv）累积AGB的模式用物种HS更准确地表示。建模的HS分数作为树木物种栖息地偏好，AGB和物种分布的潜在指标，可以提供关键的生态信息，这些信息对于在景观层面为森林管理和保护规划提供依据。