Collaborative Proposal: MSB-ECA: A multi-scale framework to quantify and forecast population changes and associated uncertainties

在过去的19年里，北美各地的帝王蝶(Danaus Plexippus)由于环境变化而迅速减少，尽管确切的原因正在深入研究中。理解和预测帝王蝶在区域和大陆尺度上的物种变化是具有挑战性的，因为局部和广泛尺度的环境动态都会影响它们的变化。该项目将开发一个模型框架，认识到蝴蝶的数量模式不仅反映了蝴蝶在细尺度上对其环境(例如，当地天气)的反应，而且还反映了对大范围因素(例如，合适栖息地的分布)的反应。具体目标是确定气候和土地利用对一种模式迁徙物种--帝王蝶的相对影响，然后预测未来气候和资源可获得性情景下多个规模的种群变化。该项目将整合来自多个区域和国家蝴蝶监测项目以及气候和土地利用数据库的大陆范围的数据，这些数据跨越整个迁徙周期，跨越所有季节，超过20年。建模方法将明确量化人口-环境关系和未来气候预测的不确定性，以评估保护行动如何扭转人口下降的趋势。这项工作迎接了一个长期阻碍大规模生态学研究的重大挑战：使用不同数据类型结合预测性环境模型在多个尺度上整合生物过程。数据集成建模框架将机制结合到广泛的模型中，为许多真实世界的宏观系统提供了可能的最佳方法，在这些系统中，由于数据限制和/或描述每个相关过程的细节的困难，完全机械化的模型的开发不容易处理。此外，对未来人口规模和分布的预测可以对这些估计进行可量化的置信度。该项目开发的建模框架将有助于确定物种年度周期的不同区域和时期如何影响种群趋势，从而在广泛的空间尺度上进行更准确的估计，并有针对性地收集、建模和保护数据。这些结果将广泛促进这一领域的科学进步，因为建模框架可以转移到其他跨界物种，在这些物种中，跟踪和预测种群丰度和趋势同样困难。该项目还将严格分析导致一个备受瞩目的物种减少的因素，以及在不断变化的气候条件下具体的保护和恢复行动可能如何有效。研究团队将与多机构合作伙伴君主联合企业合作，促进帝王的科学和保护，并通过其现有的在线资源和时事通讯向公众传播成果。

Monarch butterflies (Danaus plexippus) have rapidly declined across North America over the last 19 years from environmental change, although the exact causes are under intensive study. Understanding and forecasting species changes in monarch butterflies at regional and continental scales is challenging because both local- and broad-scale environmental dynamics affect their changes. This project will develop a modeling framework which recognizes that butterfly abundance patterns reflect not only butterfly responses to their environments at fine scales (e.g., local weather), but also to broad-scale factors (e.g., distributions of suitable habitat). The specific goal is to determine the relative effects of climate and land-use on a model migratory species, the monarch butterfly and then forecast population changes at multiple scales under future climate and resource availability scenarios. This project will integrate continental-scale data from multiple regional and national butterfly monitoring programs and climate and land-use databases, spanning their entire migratory cycle, across all seasons, over 20 years. The modeling approach will explicitly quantify uncertainties from both population-environment relationships and future climate projections to evaluate how conservation actions may reverse population declines. This work meets a significant challenge that has long-hindered large-scale ecological research: the integration of biological processes at multi-scales using different data types coupled with predictive environmental models. The data integration modeling framework incorporates mechanism into broad-scale models, representing the best possible approach for many real-world macrosystems in which the development of wholly mechanistic models is not tractable due to data limitations and/or difficulties describing the details of every relevant process. Additionally, predications about the size and distribution of future populations can be made with a quantifiable level of confidence in those estimates. The modeling framework developed in this project will help determine how different regions and periods of a species annual cycle contribute to population trends, leading to more accurate estimations at broad spatial scales, and targeted data collection, modeling, and conservation efforts. The results will contribute broadly to scientific advancement in this field because of the transferability of the modeling framework to other cross-continental species where it is similarly difficult to track and predict population abundance and trends. The project will also offer a rigorous analysis of the factors causing declines of a high profile species and how effective specific conservation and restoration acts could be under changing climate conditions. The research team will collaborate with the Monarch Joint Venture, a multi-institutional partnership, to promote science and conservation of monarchs and disseminate results to the general public through their existing online resources and newsletters.