4.8 Article

Extrapolating demography with climate, proximity and phylogeny: approach with caution

期刊

ECOLOGY LETTERS
卷 19, 期 12, 页码 1429-1438

出版社

WILEY
DOI: 10.1111/ele.12691

关键词

COMPADRE Plant Matrix Database; comparative demography; damping ratio; elasticity; matrix population model; phylogenetic analysis; population growth rate (lambda); spatially lagged models

类别

资金

  1. ARC Center of Excellence in Environmental Decisions
  2. Trinity College Dublin
  3. Australian Research Council [DE140100505]
  4. NERC IRF [R/142195-11-1]
  5. Science Foundation Ireland (SFI) [15/ERCD/2803]
  6. Marie-Curie Career Integration Grant
  7. Science Foundation Ireland (SFI) [15/ERCD/2803] Funding Source: Science Foundation Ireland (SFI)
  8. Natural Environment Research Council [NE/M018458/1] Funding Source: researchfish
  9. NERC [NE/M018458/1] Funding Source: UKRI
  10. Australian Research Council [DE140100505] Funding Source: Australian Research Council

向作者/读者索取更多资源

Plant population responses are key to understanding the effects of threats such as climate change and invasions. However, we lack demographic data for most species, and the data we have are often geographically aggregated. We determined to what extent existing data can be extrapolated to predict population performance across larger sets of species and spatial areas. We used 550 matrix models, across 210 species, sourced from the COMPADRE Plant Matrix Database, to model how climate, geographic proximity and phylogeny predicted population performance. Models including only geographic proximity and phylogeny explained 5-40% of the variation in four key metrics of population performance. However, there was poor extrapolation between species and extrapolation was limited to geographic scales smaller than those at which landscape scale threats typically occur. Thus, demographic information should only be extrapolated with caution. Capturing demography at scales relevant to landscape level threats will require more geographically extensive sampling.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据