Niche Diversification and Coexistence of Insect Herbivores along the Food Quality Axis: Do Grasshoppers Ride the Rails?

基于功能营养生态学的新进展，这项研究解决了中心问题：食物质量和可用性对于确定共存的昆虫食草动物物种的数量、组成和相对丰富度有多重要？主要营养质量(蛋白质和碳水化合物水平)对昆虫食草动物的表现至关重要，在自然产生的食用植物中差异很大，物种对不同食物可获得性的反应也不同。利用受控喂养研究，将设计出有利于某些物种的营养条件的准确预测，以预测物种的共存和相对丰度。研究的重点是蝗虫，这是一种数量丰富、种类繁多、具有重要功能和经济意义的昆虫食草动物，在大多数草原上都有发现。对于蛋白质和碳水化合物比例不同的食物，将确定支持最佳表现的营养摄入量目标(“平衡饮食”)、次优饮食的表现以及常见蝗虫物种调节营养摄入量以实现平衡饮食的能力。由于天然食用植物的叶子质量对蝗虫来说通常不是最优的，因此由此产生的分析框架将预测蝗虫如何以次优食物应对不断变化的环境--这是典型的情况。基于营养的理论预测蝗虫群落物种丰富度和共存模式的能力将在自然变化的条件下进行测试。

Based on new advances in functional nutritional ecology, this study addresses the central question: How important is food quality and availability for determining the number, composition and relative abundances of coexisting insect herbivore species? Primary nutritional quality (protein and carbohydrate levels) important to insect herbivore performance varies greatly in naturally occurring food plants, and species responses to variable food availability differ. Using controlled feeding studies, exact predictions about nutritional conditions that favor some species over others will be devised to predict coexistence and relative abundances of species. Research focuses on grasshoppers, which are abundant, diverse, functionally significant, and economically important insect herbivores found in most grassland. Nutritional intake targets supporting optimal performance ("balanced diets"), performance on suboptimal diets, and capacities of common grasshopper species to regulate nutritional intake to achieve balanced diets will be determined for food that varies in the ratio of protein:carbohydrate. Because leaf quality of naturally occurring food plants is not typically optimal to grasshoppers, the resulting analytical framework will predict how grasshoppers can respond to changing environments with suboptimal food - the typical situation. The ability of nutrition-based theory to predict patterns of species abundance and coexistence in grasshopper communities will be tested under naturally varying conditions.