Climate Change Data Portal
| OCE-PRF A transferable modeling approach to predict species distributions under changing conditions across multiple life stages | |
| 项目编号 | 2126583 |
| Joshua Cullen | |
| 项目主持机构 | Florida State University |
| 开始日期 | 2021-09-15 |
| 结束日期 | 08/31/2023 |
| 英文摘要 | This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Understanding the distributions of species is fundamental to ecology, especially within the marine environment where biotic and abiotic variables are often dynamic over space and time. Ecological models have been used to make inferences on species-environment relationships in addition to predicting past and future patterns of species distributions. However, these models are typically developed for a single location, time period, spatial scale, or species life stage, resulting in poor predictive accuracy beyond the study domain. This project will provide a new transferable modeling approach that is applicable to a wide range of species, which will be used to test predictions of current and future distributions of green turtles (Chelonia mydas) in the Gulf of Mexico, Brazil, and Qatar. Since there is a lack of information on how marine turtles in general will respond to climate change impacts, these results will provide a crucial evaluation of projected range shifts that could be used by both conservationists and decision makers. This project will foster the integration of research and education through mentoring undergraduate students that identify as underrepresented minorities, teaching marine ecology and conservation at Florida State University, hosting workshops on the analysis of animal movement data, as well as hosting public outreach events. These efforts to disseminate knowledge and results beyond traditional means within the scientific community will be used to engage future scientists and the general public on pressing ecological topics. The overall aim of this project is to develop a transferable modeling approach that can provide accurate and precise estimates of species distributions under changing conditions. This study addresses some of the challenges of model transferability through three hypotheses: 1) a model informed by biological processes and physiological constraints will exhibit greater transferability than those that do not; 2) the analysis of environmental variables at the scale of species perception will result in greater model transferability; 3) a model that accounts for differences among life stages will result in greater model transferability. These hypotheses will be tested using a large dataset of green turtle occurrences at three distant locations (Gulf of Mexico, Brazil, Qatar) with a flexible Bayesian species distribution model. The use of independent datasets (from Brazil and Qatar) to validate the species distribution model (developed on data from the Gulf of Mexico) provides a unique opportunity to critically evaluate the spatial transferability of the model. The findings from this proposed work will provide a roadmap for the further development of transferable ecological models to predict biodiversity, disease outbreaks, and risks of biological invasions across global regions and possibly under future climate change impacts. Elucidating the importance of biological mechanisms, scale, and life stage differences to ecological modeling is transformative because these factors have been largely untested with regard to model transferability. Since predictions remain a major frontier in ecology, products of this work will be of broad interest to a diverse group of scientists, such as marine ecologists, biological oceanographers, fisheries scientists, and conservationists. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. |
| 资助机构 | US-NSF |
| 项目经费 | $273,561.00 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/211384 |
| 推荐引用方式 GB/T 7714 | Joshua Cullen.OCE-PRF A transferable modeling approach to predict species distributions under changing conditions across multiple life stages.2021. |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| [Joshua Cullen]的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| [Joshua Cullen]的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| [Joshua Cullen]的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
