用最大熵方法定义生长和产量模型使用的地理界限

IF 2.7 3区 农林科学 Q2 ECOLOGY Frontiers in Forests and Global Change Pub Date : 2023-10-10 DOI:10.3389/ffgc.2023.1215713
W. Spencer Peay, Bronson P. Bullock, Cristian R. Montes
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引用次数: 0

摘要

生长和产量模型是现代林业的基本工具,特别是对美国东南部集约化管理的火炬松人工林。虽然模型开发人员通常很清楚这些模型应该在地理位置的什么地方使用,但是确定模型使用的地理范围可能会令人望而生畏。这样的界限提供了合适的区域,在这些区域中,模型的预测可能表现得与预期一致,或者确定了模型在描述资源增长方面可能做得不好的区域。在这项研究中,我们采用了一种常用的生态位模型方法来确定物种发生的合适地点(最大熵),以确定在美国东南部的下海岸平原和山前/上海岸平原建立的生长和产量模型的区域。该分析的结果确定了与收集数据以适应这些生长和产量模型的地区具有相似气候包络和土壤特性的地区。这些区域与经评估的生长和产量模型规定使用的区域有明显的重叠,并支持从业者在这些区域使用这些模型。此外,只要每个地点都有气候和土壤值,这种方法就可以应用于使用大区域范围建立的不同森林模型。
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A maximum entropy approach to defining geographic bounds on growth and yield model usage
Growth and yield models are essential tools in modern forestry, especially for intensively managed loblolly pine plantations in the southeastern United States. While model developers often have a good idea of where these models should be used with respect to geographic location, determining geographic bounds for model usage can be daunting. Such bounds provide suitable areas where model predictions are likely to behave as expected or identify areas where models may do a poor job of characterizing the growth of a resource. In this research, we adapted a niche model methodology, commonly used to identify suitable spots for species occurrence (maximum entropy), to identify areas for using growth and yield models built from plots established in the Lower Coastal Plain and Piedmont/Upper Coastal Plain in the southeastern United States. The results from this analysis identify areas with similar climatic envelopes and soil properties to the areas where data was collected to fit these growth and yield models. These areas show notable overlap with the areas prescribed for use by the evaluated growth and yield models and support practitioners use of these models throughout these regions. Furthermore, this methodology can be applied to different forest models built using large regional extents as long as climatic and soil values are available for each site.
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来源期刊
CiteScore
4.50
自引率
6.20%
发文量
256
审稿时长
12 weeks
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