Suppr超能文献

一种用于物候-气候模型的新物候指标:以……的植物标本馆标本为例的研究

A new phenological metric for use in pheno-climatic models: A case study using herbarium specimens of .

作者信息

Love Natalie L Rossington, Park Isaac W, Mazer Susan J

机构信息

Department of Ecology, Evolution, and Marine Biology University of California, Santa Barbara Santa Barbara California 93106 USA.

出版信息

Appl Plant Sci. 2019 Jul 12;7(7):e11276. doi: 10.1002/aps3.11276. eCollection 2019 Jul.

Abstract

PREMISE

Herbarium specimens have been used to detect climate-induced shifts in flowering time by using the day of year of collection (DOY) as a proxy for first or peak flowering date. Variation among herbarium sheets in their phenological status, however, undermines the assumption that DOY accurately represents any particular phenophase. Ignoring this variation can reduce the explanatory power of pheno-climatic models (PCMs) designed to predict the effects of climate on flowering date.

METHODS

Here we present a protocol for the phenological scoring of imaged herbarium specimens using an ImageJ plugin, and we introduce a quantitative metric of a specimen's phenological status, the phenological index (PI), which we use in PCMs to control for phenological variation among specimens of (Brassicaceeae) when testing for the effects of climate on DOY. We demonstrate that including PI as an independent variable improves model fit.

RESULTS

Including PI in PCMs increased the model relative to PCMs that excluded PI; regression coefficients for climatic parameters, however, remained constant.

DISCUSSION

Our protocol provides a simple, quantitative phenological metric for any observed plant. Including PI in PCMs increases and enables predictions of the DOY of any phenophase under any specified climatic conditions.

摘要

前提

植物标本馆的标本已被用于通过使用采集年份的日期(DOY)作为首次开花或开花高峰期的代理来检测气候引起的开花时间变化。然而,植物标本馆标本在物候状态上的差异破坏了DOY准确代表任何特定物候阶段的假设。忽略这种差异会降低旨在预测气候对开花日期影响的物候 - 气候模型(PCM)的解释力。

方法

在此,我们提出了一种使用ImageJ插件对成像的植物标本馆标本进行物候评分的方案,并引入了标本物候状态的定量指标——物候指数(PI),我们在PCM中使用它来控制十字花科标本在测试气候对DOY的影响时物候上的差异。我们证明将PI作为自变量可改善模型拟合。

结果

在PCM中纳入PI相对于排除PI的PCM增加了模型 ;然而,气候参数的回归系数保持不变。

讨论

我们的方案为任何观察到的植物提供了一个简单的定量物候指标。在PCM中纳入PI可增加 ,并能够预测在任何指定气候条件下任何物候阶段的DOY。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2783/6636619/a4660e50d649/APS3-7-e11276-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验