墨西哥哈里斯科(Jalisco)林分结构小面积估测(英文)

Small-area estimation of forest stand structure in Jalisco, Mexico

对小的生态经济区开展自然资源统计是很困难的,政府决策人员只能依靠州水平的数据库来评价一定区域或局部的自然资源(森林、牧场、草地、农田等)状况。小面积评估技术可以用于评定这些资源。然而,哪一种小面积估测法可以给出最可靠、最准确的结果还不得而知。本研究检测了小面积评估分析常用的两种方法(即综合估计法和回归估计法)的可靠性、准确性。运用这两种方法分析墨西哥哈里斯科(Jalisco)州全州的自然资源数据,从而检测每种方法对所选择的森林林分结构特征预测结果的好坏。研究表明,回归方法在多个地理尺度上,对森林林分结构特征预测的可靠性和准确性均最好。因此,推荐州或地方资源管理者,在没有其他适当的辅助信息资料的情况下,可运用回归分析法来评估小区域内自然资源状况。

Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources （i.e., forests, rangelands, grasslands, agriculture, etc.） at the regional or local level. These resources can be evaluated using small-area estimation techniques. However, it is unknown which small area technique produces the most valid and precise results. The reliability and accuracy of two methods, synthetic and regression estimators, used in smallarea analyses, were examined in this study. The two small-area analysis methods were applied to data from Jalisco＇s state-wide natural resource inventory to examine how well each technique predicted selected characteristics of forest stand structure. The regression method produced the most valid and precise estimates of forest stand characteristics at multiple geographical scales. Therefore, state and local resource managers should utilize the regression method unless appropriate auxiliary information is not available.