基于gis的生境模型预测外来入侵植物含羞草的潜在发生区域。

Q4 Agricultural and Biological Sciences
T. Le, P. T. K. Thoa, N. Tuan
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引用次数: 1

摘要

摘要/ Abstract摘要:在越南岘港市和旺区发现了超入侵植物Mimosa pigra L.的入侵。这种入侵物种对本港的农业及自然环境构成威胁,尤其是位于该区的巴纳-乃蔡自然保护区。在这项研究中,建立了一个栖息地模型来预测该植物即将出现的潜在区域。利用7个环境层(15 m空间分辨率)分析了该物种的检测位置,并计算了马氏距离(D2)的多元统计量。含含橙发生情况被分为建模子集(用于模型构建)和验证数据子集(用于从重复运行中选择最佳模型)。使用1,000个随机点的零模型对模型性能进行了测试,结果表明D2值与含羞草发生之间存在显著关系。D2模型明显优于随机模型。null模型结合整个含羞草位置数据集来识别阈值D2值。使用该阈值,检测到99.5%的现有含羞草地点,并确定20.3%的研究区域为含羞草发生的高风险区域。这些确定的高风险区将对当地外来入侵物种的管理做出重要贡献。鉴于非法捕捞对这些物种的潜在威胁,这些信息可以作为未来栖息地和种群评估的重要基准。本研究的空间模拟技术可以很容易地应用于其他物种和地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GIS-based habitat model to predict potential areas for the upcoming occurrences of an alien invasive plant, Mimosa pigra L.
Abstract Incursions of Mimosa pigra L., a super-invasive plant, were detected in Hoa Vang district, Da Nang city, Vietnam. This invasive species posed threats to the local agricultural and natural areas, especially to Ba Na - Nui Chua Nature Reserve located in the district. In this study, a habitat model was developed to predict potential areas for the upcoming occurrences of the plant. Detected locations of the species were analyzed in association with seven environmental layers (15 m spatial resolution), which characterized the habitat conditions facilitating the plant incursion, to calculate a multivariate statistic, Mahalanobis distance (D2). Mimosa occurrences were divided into subsets of modelling (for model construction) and validating data (for selecting the best model from replicate runs). The model performance was tested using a null model of 1,000 random points and indicated a significant relationship between D2 values and mimosa occurrence. The D2 model performed markedly better than the random model. The null model in combination with the entire dataset of mimosa locations was also used to identify the threshold D2 value. Using that threshold value, 99.5% of existing mimosa locations were detected and 20.3% of the study area was determined as high-risk areas for mimosa occurrence. These identified high risk areas would make an important contribution to the local alien invasive species management. Given the potential threats to these species from illegal harvesting, that information may serve as an important benchmark for future habitat and population assessments. The spatial modelling techniques in this study can easily be applied to other species and areas.
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来源期刊
Forestry Studies
Forestry Studies Agricultural and Biological Sciences-Forestry
CiteScore
0.70
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