LTER Cross-site: Collaborative Research - Assessing the Geographic and Temporal Consistency of Life History and Demographic Patterns: A Long-term, Multi-site Comparison

LTER 跨站点：协作研究 - 评估生活史和人口统计模式的地理和时间一致性：长期、多站点比较

• 批准号: 0087096
• 负责人: William Morris
• 金额: --
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-10-01 至 2007-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0087096&HistoricalAwards=false
• 关键词: LTER; Cross; site; Collaborative; Research

0087096MorrisEcologists increasingly understand the importance of spatial variability in natural systems, a recognition that led to the creation of the LTER network. However, we still know surprisingly little about spatial variation in the demography of individual species, creating an important gap in knowledge for both applied and basic ecology. The paucity of full demographic studies that span multiple populations across substantial geographic scales creates two general problems. First, population biologists are forced to extrapolate from the population dynamics and life history patterns found in single, well-studied populations to those occurring in distant parts of a species range. Such extrapolation is commonplace in conservation biology, comparative life history analysis, and climate change predictions, and is currently done with little understanding of how much spatial variation actually exists in the demography of individual species. Second is the question of what sets the range limits of species. While the physiological effects of climate are often well-known, the lack of broad-scale demographic studies makes it less clear how population dynamics vary near range limits, and thus the extent to which poor demographic performance versus other proposed factors, such as metapopulation dynamics, determine the distributional limits of species. As a result, we have little ground for building mechanistic predictions about how species ranges will shift as climate changes. To address these problems, a demographic study of two widespread tundra plant species, moss campion and alpine bisort, will be conducted as part of this LTER cross-site research project. These species will be studied in 16 populations across two habitats and four geographic sites. These sites span most of the latitudinal range of the species in North America. The study is designed to parameterize stochastic matrix models for each population of each species. While multi-site demographic studies are unusual, ones that measure and properly analyze temporal stochasticity in vital rates are even rarer. In addition to statistical analysis of the means and variance in individual vital rates, the PIs will base much of the analysis on outputs of these stochastic models, including stochastic growth rates, stochastic elasticity values and extinction risk predictions. Furthermore, the work will utilize LTER climate data to tie spatial and temporal variability in vital rates to specific environmental factors. The results will be used to test for the strength and pattern of life history variation across geographic sites and habitats, and to determine how best to make predictions about demographic variability with limited data. Finally, specific tests will be conducted for demographic factors leading to both northern and southern range boundaries. Overall, this study will be the first multi-site, multi-year demographic analysis to carefully include temporal stochasticity and to explicitly test how and in what ways life history patterns vary across species' ranges.

0087096Morris生态学家越来越了解自然系统中空间变异的重要性，这种认识导致了 LTER 网络的创建。然而，令人惊讶的是，我们对单个物种人口统计的空间变化知之甚少，这在应用生态学和基础生态学方面造成了重要的知识空白。缺乏涵盖大量地理范围内多个人群的全面人口统计研究，造成了两个普遍问题。首先，种群生物学家被迫从经过充分研究的单一种群中发现的种群动态和生活史模式推断出发生在物种范围较远地区的种群动态和生活史模式。这种推断在保护生物学、比较生活史分析和气候变化预测中很常见，但目前对单个物种的人口统计中实际存在多少空间变异知之甚少。其次是物种范围限制的问题。虽然气候的生理影响通常是众所周知的，但缺乏大规模的人口统计研究使得人们不太清楚人口动态在范围限制附近如何变化，因此不太清楚人口统计表现与其他拟议因素（例如集合种群动态）相比在多大程度上决定了物种的分布限制。因此，我们几乎没有基础来建立关于物种分布范围将如何随着气候变化而变化的机械预测。 为了解决这些问题，作为 LTER 跨站点研究项目的一部分，将对两种广泛分布的苔原植物物种（苔藓植物和高山双子植物）进行人口统计研究。这些物种将在两个栖息地和四个地理位置的 16 个种群中进行研究。这些地点跨越了北美该物种的大部分纬度范围。该研究旨在对每个物种的每个种群的随机矩阵模型进行参数化。虽然多地点人口统计研究并不常见，但测量和正确分析生命率时间随机性的研究则更为罕见。除了对个体生命率的平均值和方差进行统计分析外，PI 还将根据这些随机模型的输出进行大部分分析，包括随机增长率、随机弹性值和灭绝风险预测。此外，这项工作将利用 LTER 气候数据将生命率的空间和时间变化与特定环境因素联系起来。结果将用于测试跨地理位置和栖息地的生活史变化的强度和模式，并确定如何利用有限的数据最好地预测人口变化。最后，将对导致北部和南部范围边界的人口因素进行具体测试。总体而言，这项研究将是第一个多地点、多年人口分析，仔细考虑时间随机性，并明确测试不同物种范围内生活史模式如何以及以何种方式变化。