| 项目编号: | NE/P004180/1
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| 项目名称: | NSFDEB-NERC: Informing population models with evolutionary theory to infer species' conservation status |
| 作者: | Jason Matthiopoulos
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| 承担单位: | University of Glasgow
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| 批准年: | 2015
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| 开始日期: | 2016-01-11
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| 结束日期: | 2019-31-10
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| 资助金额: | GBP243444
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| 资助来源: | UK-NERC
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| 项目类别: | Research Grant
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| 国家: | UK
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| 语种: | 英语
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| 特色学科分类: | Ecol, biodivers. & systematics 
; (80%)
; Mathematical sciences 
; (20%)
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| 英文摘要: | Natural mortality and environmental resources are intimately related to physiology, body size,
fecundity, and lifespan, all of which play an instrumental role in population dynamics. Yet
mortality and resource limitation are notoriously difficult to measure in wild populations,
hindering our ability to prioritize marine species that are at greatest risk of overexploitation.
Crucially, we lack mechanistic theory linking physiology, life histories and population dynamics.
Our central hypothesis is that evolutionary theory can take the place of missing information
on demographic rates or population trends, and can be used to combine data from similar species
to predict population dynamics. We propose to develop a scientific research program to test
this idea and add to our knowledge of the processes regulating the dynamics of marine populations.
We will use a combination of evolutionary theory and hierarchical Bayesian state-space models
of data to infer and predict the life history and population dynamics of three marine fish
clades with diverse life histories: sharks and rays, tunas, and groupers.
Specifically, we will 1) use state-dependent life history theory to develop evolutionary priors
for demographic rates, including mortality and resource limitation and 2) use state-space
models to impute the population trajectories of related species, given our evolutionary priors.
This will 3) generate and refine new theory for the evolution of sharks and rays, groupers,
and tunas that can ultimately be tested comparatively. Finally, we will 4) engage in species'
assessments, training, and outreach to boost the broader impacts of our work. Our research
will produce theory predicting the demographic rates that are correlated with suites of life
history traits, and then generate more precise posterior estimates of these demographic rates
by fitting a structured population model. This integrative approach will allow us to refine
and validate our results with species that have been assessed, and then to assess the vulnerability
of data-limited and potentially endangered species of sharks and rays, groupers, and tunas.
Along the way, our work will generate new insights about the relationship between life-history
traits of marine species, environmental drivers such as resources and mortality, and resilience
to anthropogenic or environmental perturbations.
Intellectual Merit :
We take a new approach to linking evolutionary theory with ecological data. While previous
work has used evolutionarily derived priors in fishery stock assessments (He et al. 2006;
Mangel et al. 2010), this research will provide a mechanistic framework assessing how stage-specific
mortality and resource limitation determine life history evolution and population dynamics.
The novelty of this approach is that we are not hardwiring our assumptions about life history
trait co-variation into the model. We will test our predictions for how resources and natural
mortality select on life histories by confronting our population dynamics model with real-world
data from wild fishes. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/100584
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| Appears in Collections: | 科学计划与规划
气候变化与战略
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作者单位: | University of Glasgow
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| Recommended Citation: | |
Jason Matthiopoulos. NSFDEB-NERC: Informing population models with evolutionary theory to infer species' conservation status. 2015-01-01.
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