首页> 外文期刊>Annals of Forest Science >Using past growth to improve individual-tree diameter growth models for uneven-aged mixtures of Pinus sylvestris L. and Pinus nigra Arn. in Catalonia, north-east Spain
【24h】

Using past growth to improve individual-tree diameter growth models for uneven-aged mixtures of Pinus sylvestris L. and Pinus nigra Arn. in Catalonia, north-east Spain

机译:利用过去的生长来改善樟子松和黑松Arn不均匀老化混合物的个体树径生长模型。在西班牙东北部的加泰罗尼亚

获取原文
获取原文并翻译 | 示例
           

摘要

In this study, growth models of individual tree diameter for uneven-aged mixtures of P. sylvestris and P. nigra in Catalonia were developed using a past growth index as site descriptor. These models were compared to an earlier model, based on the same data, that did not use past growth as a predictor. The growth index was calculated as a ratio of the measured and predicted past growth of sample trees within a given stand, the predictors pertaining to an average site. The models for future growth were based on 7 982 and 5 673 observations, and the models for past growth on 1 997 and 1 686 observations for P. sylvestris and P. nigra, respectively. Due to the applied Snowdon correction, the biases for the diameter growth models were zero. The relative RMSE values were 56.3% for the earlier P. sylvestris model and 52.0% for the new model, and 48.7% for the earlier P. nigra model and 47.1% for the new model. The accuracy of stand-level predictions (10-year change in basal area of living pines in the inventory plots) was better for the new models (Bias % = 2.79 and RMSE % = 34.79) than for the earlier ones ( Bias % = 3.27 and RMSE % = 41.54). The results indicate that the new models adapt to specific stand conditions better than models that omit past growth measurements.
机译:在这项研究中,使用过去的生长指数作为位点描述符,建立了加泰罗尼亚的樟子松和黑黑杨不均匀老化混合物个体树径的生长模型。这些模型与基于相同数据的早期模型进行了比较,该模型没有使用过去的增长作为预测指标。将生长指数计算为给定林分中测得的和预测的样本树过去生长的比例,预测值与平均位点有关。未来增长的模型基于7 982和5 673观测值,而过去增长的模型分别基于樟子松和黑斑病的1 997和1 686观测值。由于应用了斯诺登校正,直径增长模型的偏差为零。相对的RMSE值对于早期的樟子松模型为56.3%,对于新模型而言为52.0%,对于早期的黑黑点菌模型为48.7%,对于新模型为47.1%。对于新模型(Bias%= 2.79和RMSE%= 34.79),新的模型(标准偏差)的准确度要好于标准模型(偏差百分比= 3.27,偏差百分比= 3.27)和RMSE%= 41.54)。结果表明,与省略过去的生长测量值的模型相比,新模型更适合特定的林分条件。

著录项

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号