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Predicting current and future suitable habitat and productivity for Atlantic populations of maritime pine (Pinus pinaster Aiton) in Spain
Annals of Forest Science ( IF 3 ) Pub Date : 2020-04-17 , DOI: 10.1007/s13595-020-00941-5
Marcos Barrio-Anta , Fernando Castedo-Dorado , Asunción Cámara-Obregón , Carlos A. López-Sánchez

By combining inventory data and spatially-continuous environmental information, we were able to develop models for Atlantic populations of maritime pine (Pinus pinasterAiton) in Spain in order to predict suitable habitat and site index at a spatial resolution of 250 × 250 m. Currently available, spatially continuous environmental information was used to make reliable predictions about suitable habitat and forest productivity. To develop raster-based distribution and productivity models for Atlantic populations of maritime pine in Spain to predict current and future suitable habitat and productivity. Occurrence data and site index values were obtained from the Third Spanish National Forest Inventory and research plots, respectively. After testing different algorithms, random forest were selected for modelling the relationships between maritime pine occurrence, site index and spatially continuous environmental variables. The overall accuracy of the suitable habitat model was 73%, and climate (mainly thermal properties) and soil physical properties were the most important variables. The site index model explained 60% of the observed variability, and lithological properties were the most important variables. A slight increase in site index (0.46–0.51%) and a large increase in suitable habitat (50–66%) are expected for 2070 under the most pessimistic climate change scenario. The currently available spatial continuous information enables the development of accurate raster data models for predicting suitable habitat and site productivity without the need for fieldwork. Climate change is expected to increase the potentially suitable habitat of Atlantic maritime pine populations in Spain in the coming decades.

中文翻译:

预测西班牙大西洋海松(Pinus pinaster Aiton)种群当前和未来的适宜栖息地和生产力

通过结合清单数据和空间连续环境信息,我们能够为西班牙的大西洋海松 (Pinus pinasterAiton) 种群开发模型,以便以 250 × 250 m 的空间分辨率预测合适的栖息地和场地指数。目前可用的空间连续环境信息用于对合适的栖息地和森林生产力进行可靠的预测。为西班牙大西洋海松种群开发基于栅格的分布和生产力模型,以预测当前和未来合适的栖息地和生产力。发生数据和场地指数值分别来自西班牙第三次国家森林清单和研究地块。在测试了不同的算法后,选择随机森林来模拟海松发生、场地指数和空间连续环境变量之间的关系。适宜栖息地模型的总体准确率为 73%,气候(主要是热特性)和土壤物理特性是最重要的变量。场地指数模型解释了 60% 的观测变化,岩性是最重要的变量。在最悲观的气候变化情景下,预计 2070 年场地指数略有增加(0.46-0.51%),适宜栖息地大幅增加(50-66%)。当前可用的空间连续信息能够开发准确的栅格数据模型,以预测合适的栖息地和现场生产力,而无需进行实地工作。
更新日期:2020-04-17
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