Hageer Yasmin, Esperón-Rodríguez Manuel, Baumgartner John B, Beaumont Linda J
Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia.
PeerJ. 2017 Jun 22;5:e3446. doi: 10.7717/peerj.3446. eCollection 2017.
Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent.
This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only.
The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables.
Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants.
灌木在生物地球化学循环中发挥着关键作用，可防止水土流失，为牲畜提供饲料，并且是食物、木材和非木材产品的来源。然而，尽管它们具有生态和社会重要性，但不同环境变量对灌木分布的影响仍不明确。我们评估了气候和土壤特征的影响，以及纳入土壤变量是否能提高物种分布模型（SDM）Maxent的性能。
本研究评估了由于使用不同的预测变量集，29种澳大利亚灌木物种（代表六个灌木地类别的优势成员）的环境适宜性预测的变化。模型分别用（1）仅气候变量、（2）气候和土壤变量以及（3）仅土壤变量进行校准。
SDM的预测能力在不同物种间差异很大，但一般来说，用气候和土壤数据校准的模型比仅用气候变量校准的模型表现更好。仅用土壤变量校准的模型最不准确。由于使用了不同的变量集，我们发现澳大利亚潜在灌木物种丰富度存在区域差异。
我们的研究提供了证据，表明当存在多种合理的替代方案时，预测的物种丰富度模式可能对预测变量集的选择敏感，并证明了在为植物栖息地可用性建模时考虑土壤特性的重要性。
