DISSERTATION RESEARCH: FORECASTING GLOBAL WARMING EFFECTS ON DEVELOPMENTAL PERFORMANCE OF PRAIRIE STREAM FISHES ALONG THE RIVER CONTINUUM

论文研究：预测全球变暖对河流连续体沿岸草原河流鱼类发育性能的影响

• 批准号: 1311183
• 负责人: Keith Gido
• 金额: $ 1.27万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-05-01 至 2014-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1311183&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; FORECASTING; GLOBAL; WARMING

Predicting where species occur on a landscape is a fundamental aspect of ecology and an essential step in the conservation of biological diversity. Environmental niche modeling is a common tool for predicting species distributions, but limited understanding of causal relationships between the occurrence or abundance of a species and environmental variables limits the generality of these models. Improved understanding of how individual performance varies along environmental gradients is necessary to develop mechanistically-based environmental niche models. This research is motivated by the observation that the distribution of many stream fishes varies along a stream size gradient, but little is known about the mechanistic relationship between stream size and species distribution. The project will develop niche models to predict distribution of fish species in streams draining the Flint Hills of the central United States, which exhibit a strong temperature gradient from headwaters to large rivers. Given the universal importance of temperature as an environmental factor constraining metabolic, survival, and growth rates of individuals and vital rates of populations, it is predicted that temperature-dependent performance varies among species and determines among-species differences in distributional patterns. This study will test that hypothesis by quantifying inter- and intraspecific variation in egg developmental rate as a function of temperature to see if it explains differences in stream size - abundance relationships among four fish species.This study will provide mechanistically-based environmental niche models for four temperate freshwater fish species, which will inform conservation planners about current distributions and distributional changes in response to anthropogenic climate change. The project will also advance a broadly-applicable framework for developing environmental niche models for other temperate freshwater fish species, particularly threatened and endangered species. These models will be disseminated to state natural resource agencies and will be incorporated into planning tools used to inform conservation efforts in the Great Plains. This project will provide an undergraduate student with practical research experience in field and laboratory settings and support the dissertation research of a doctoral student.

预测物种在景观上发生的地方是生态学的基本方面，也是保护生物多样性的重要一步。 环境利基建模是预测物种分布的常见工具，但对物种的发生或丰度之间的因果关系和环境变量之间的因果关系有限，这限制了这些模型的一般性。 对个人绩效如何沿环境梯度变化的改善，对于开发基于机械的环境利基模型是必要的。这项研究的激励是，观察到许多流鱼的分布沿着溪流梯度变化，但对溪流大小和物种分布之间的机械关系知之甚少。该项目将开发利基模型，以预测排出美国中部火石丘陵的溪流中的分布，该溪流表现出从源水流到大河流的强温度梯度。鉴于温度作为限制了个体的代谢，生存率和人口的生长速率的环境因素的普遍重要性，因此可以预测，依赖温度的性能在物种之间有所不同，并决定分布模式的种类差异。这项研究将通过量化鸡蛋发育率的间种间和种内变化来检验假设，以查看它是否解释了流的差异 - 四种鱼类之间的差异 - 这项研究将为机械学的环境利基模型提供用于机械的环境利基模型四种温带淡水鱼类将为保护计划者提供有关当前分布和分配变化的响应，以应对人为气候变化。该项目还将推进一个广泛的框架，用于为其他温带淡水鱼物种（尤其是受威胁和濒危物种）开发环境利基模型。这些模型将被传播到国家自然资源机构，并将纳入用于为大平原上的保护工作提供信息的计划工具中。 该项目将为一名本科生提供现场和实验室环境的实践研究经验，并支持博士生的论文研究。