StoX:种子传播效果的随机多阶段招募模型

IF 1.3 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Julio Martín-Herrero , María Calviño-Cancela
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引用次数: 0

摘要

种子传播的有效性是指通过种子传播者的服务有效产生的新植物的数量。这取决于一个涉及多个阶段和参与者的复杂过程,对自然保护有着深远的影响。StoX 是一个与分布无关的多阶段随机模型,可区分不同散播者对种子雨和新植株的贡献。该模型可根据实地测量的扩散数量和质量要素进行参数化。它保留了引种过程固有的随机性,并可通过统计比较其预测结果和实地引种模式来验证。StoX 已成功应用于多项研究,包括种群和群落层面的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
StoX: Stochastic multistage recruitment model for seed dispersal effectiveness

Seed dispersal effectiveness measures the number of new plants effectively produced by the services of seed disperser agents. This depends on a complex process involving multiple stages and actors, and has profound implications for conservation. StoX is a distribution agnostic multistage stochastic model that differentiates among dispersers in their contribution to seed rain and recruitment. It can be parameterized with quantity and quality components of dispersal measured in the field. It preserves the inherent stochastic nature of the recruitment process and can be validated by statistical comparison between its predictions and recruitment patterns in the field. StoX has already been used in several successful studies, at both population and community levels.

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来源期刊
Software Impacts
Software Impacts Software
CiteScore
2.70
自引率
9.50%
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审稿时长
16 days
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