Interplay between trait variation, food web dynamics and maintenance of biodiversity

性状变异、食物网动态和生物多样性维护之间的相互作用

• 批准号: 257405112
• 负责人: Professorin Dr. Ursula Gaedke
• 金额: --
• 依托单位: Arbeitsgruppe Ökologie/Ökosystemmodellierung
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/257405112?language=en
• 关键词: Interplay; between; trait; variation; food

Trait variation within individuals, populations and communities allows them to adjust to altering environmental conditions, giving rise to biomass-trait feedbacks including eco-evolutionary dynamics. Using mathematical models, we will contribute to a unifying theory that explicitly considers how such feedbacks affect the structure and dynamics of predator-prey systems and more complex food webs. We postulate that (1) the standing trait variation (functional diversity) influences biomass and trait dynamics and (2) this, in turn, influences the maintenance of trait variation in concert with the trade-off(s) among traits. We will use four complementary model approaches: multispecies or multiclonal sorting models, full trait distribution models, aggregate models approximating full models by explicitly describing the dynamics of the mean and variance of the underlying trait distribution, and hybrid models considering intra- and interspecific trait variation simultaneously by combining a multispecies model with an aggregate approach. This enables us to investigate the intertwined ecological and evolutionary processes, and to test the robustness of our results against model assumptions. Our main objectives are:1. To synthesize current theory of biomass-trait feedbacks in bi-trophic food web models. We focus on (1) how different food web structures evolve by evolutionary diversification of prey and predators, and (2) how differences in structure, functional traits, trade-offs and sources of trait variation affect community dynamics, e.g. to explain unusual predator-prey dynamics. This includes considering a multi-dimensional trait space.2. To extend our models to tri-trophic systems including food chains and intra-guild predation, to bridge between more abstract but also more tractable predator-prey models, and more realistic complex food web models, and to contribute to mechanistic interpretations of experimental tri-trophic systems. 3. To develop adaptive food web modules reflecting properties and dynamics arising from the natural complexity of plankton food webs, we will combine our recent insights from our more abstract models with comprehensive data from Lake Constance. This will also help to improve the realism of biogeochemical models tailored to specific ecosystems.4. To confront the developed theory with data and improve the realism of the mathematical models, we will closely cooperate with four experimental partners within this priority program by applying our models to their data. This will help optimizing the experimental designs, interpreting the experimental results, and facilitating the comparison among findings derived from different experimental set-ups.5. To execute general tasks such as promoting synergies within DynaTrait, e.g. by leading synthesis papers, and teaching summer schools. The anticipated results will stimulate a reconsideration of concepts in fundamental ecology that form the basis for nature conservation.

个体、种群和群落内的性状变异使它们能够适应不断变化的环境条件，从而产生生物量性状反馈，包括生态进化动力学。使用数学模型，我们将有助于一个统一的理论，明确考虑如何这样的反馈影响捕食者-猎物系统和更复杂的食物网的结构和动态。我们假设：（1）现存性状变异（功能多样性）影响生物量和性状动态，（2）这反过来又影响性状变异的维持，并与性状之间的权衡一致。我们将使用四个互补的模型方法：多物种或多克隆排序模型，全性状分布模型，聚合模型近似完整的模型，通过明确描述的动态的平均值和方差的基础性状分布，和混合模型，同时考虑内和种间性状变异相结合的多物种模型与聚合的方法。这使我们能够研究相互交织的生态和进化过程，并测试我们的结果对模型假设的鲁棒性。我们的主要目标是：1. 综合当前双营养食物网模型中生物量-性状反馈的理论。我们专注于（1）不同的食物网结构如何演变的猎物和捕食者的进化多样化，以及（2）结构，功能性状，权衡和性状变异的来源的差异如何影响社区动态，例如，解释不寻常的捕食者-猎物动态。这包括考虑多维特质空间。2. 将我们的模型扩展到三营养系统，包括食物链和行会内捕食，更抽象，但也更听话的捕食者-猎物模型之间的桥梁，更现实的复杂的食物网模型，并有助于实验三营养系统的机械解释。3. 为了开发自适应的食物网模块，反映浮游生物食物网的自然复杂性所产生的属性和动态，我们将结合我们最近的见解，从我们更抽象的模型与博登湖的综合数据联合收割机。这也将有助于提高针对特定生态系统的地球化学模型的现实性。 为了将开发的理论与数据相结合并提高数学模型的真实性，我们将与该优先计划中的四个实验合作伙伴密切合作，将我们的模型应用于他们的数据。这将有助于优化实验设计，解释实验结果，并便于不同实验装置所得结果的比较。 执行一般任务，如促进DynaTrait内部的协同作用，例如通过领导综合论文和教授暑期学校。预期的结果将促使人们重新考虑构成自然保护基础的基本生态学概念。