Seed Dispersal Workshop Proposal; Annapolis, MD - Spring, 2016

扩散是种群扩散、从地方到全球范围的生物多样性模式、基因流动和新环境中的潜在适应以及物种对全球变化的反应中的一个关键过程。全球变化过程，如气候变化和破碎化，改变了物种的当地生境条件，也改变了生态和扩散的演变。 这些变化影响了物种的迁移能力或适应这些过程的能力。本次研讨会将汇集一组不同的生态学家和数学生物学家，他们研究跨尺度，方法和系统的扩散，并将汇集现有的经验信息，理论概念和数学方法的知识。研讨会的主要成果将是评估如何将数据与理论预测和新的分析，计算和统计进展相结合，以研究扩散。其成果将有助于提高应对全球变化的能力。 科学家之间的合作也将得到促进。一个研讨会将确定我们对植物种群中种子传播作用的理解目前存在的差距，并确定如何解决这些突出的差距，以便对全球变化下的植物种群进行预测性理解。种子传播生态学主要是基于对少数物种的短期、局部规模的经验研究，或者是基于经常做出简化假设的理论传播模型。 这些因素限制了进行定量预测的能力. 通过将数据与模型相结合，研讨会将导致计算机实验，以a）获得植物种群动态中扩散作用的机械理解; B）使用经验数据测试理论预测;和c）进行敏感性分析，以确定结论对可用数据类型，缺失数据和不同类型模型的鲁棒性。 将查明知识差距和进展障碍，并加强科学网络。

Dispersal is a key process in the spread of populations, in biodiversity patterns from local to global scales, in gene flow and potential adaptation in novel environments, and in species responses to global change. Global change processes, such as climate change and fragmentation, alter local habitat conditions of species, and also the ecology and evolution of dispersal. These changes affect the ability of species to move or adapt in response to these processes. This workshop will assemble a diverse group of ecologists and mathematical biologists who study dispersal across scales, methodologies, and systems and who will bring together knowledge of existing empirical information, theoretical concepts, and mathematical approaches. The primary outcome of the workshop will be an evaluation of how data can be integrated with theoretical predictions and novel analytical, computational, and statistical advances for studying dispersal. The outcome will contribute to the ability to respond to global change. Collaborations among scientists will also be fostered.A workshop will identify current gaps in our understanding of the role of seed dispersal in plant populations and determine how to address these outstanding gaps in order to move towards a predictive understanding of plant populations under global change. Seed dispersal ecology is largely based on short-term, local-scale empirical studies for a small number of species or on theoretical dispersal models that often make simplified assumptions. These factors limit generality the ability to make quantitative predictions. By integrating data with models, the workshop will lead to computer experiments to a) gain a mechanistic understanding of the role of dispersal in plant population dynamics; b) test theoretical predictions using empirical data; and c) conduct sensitivity analyses to determine the robustness of conclusions to the type of available data, to missing data, and to different types of models. Gaps in knowledge and obstacles to progress will be identified, and scientific networking will be enhanced.