Cross-scale forecasting of Everglades wading bird dynamics

生态预测是一个重要的新兴科学研究领域，它试图预测生态系统随时间的变化。准确预测未来的变化对于管理自然资源、保护保护区和提高对自然世界的科学认识非常重要。生态系统的行为受到尺度的影响——面积的大小和被研究的时间——因为不同生态过程的重要性往往随着面积或时间的增加而变化。然而，这如何影响生态预测目前尚不清楚。这项研究将利用对沼泽地涉禽的长期监测来加深我们对规模如何影响生态预测的理解。在大沼泽地，大自然在各种不同的空间和时间尺度上运作，这项研究将利用这些尺度来推进我们对尺度如何影响生态预测的理解。该项目将提供资料，说明哪些尺度可作出最准确的预报，这种预报如何受到随尺度变化的天气预报准确性的影响，以及在一个尺度上发展的预报模式是否可用于在其他尺度上作出准确的预报。这将产生更好的预测，以指导沼泽地的恢复，并广泛了解如何将面积的大小和预测的时间量纳入一般的生态预测中。该项目还将广泛提供大沼泽地涉水鸟类的数据和预测，并促进它们在科学和教育方面的应用。利用对沼泽地涉禽和水文的密集监测，研究将从三个方面探讨尺度在生态预测中的影响和整合：1)通过比较适合整个沼泽地、生态水文区和单个群落的模型，量化可预测性、驱动因素和不确定性在空间尺度上的变化；2)通过拟合两类跨尺度模型，并与单尺度模型进行比较，评估跨尺度驱动因素对驱动因素预测的重要性，利用跨空间尺度驱动因素及其相互作用来理解跨尺度生态学，改进生态预测；3)评估年尺度模式对季节预报的可转移性，通过评估年尺度模式在季节预报中的表现并将其与季节模式进行比较，了解年尺度模式是否可以用于改进季节预报。为了便于将结果数据和预测用于研究、教育和管理，该项目将：1)使沼泽地涉禽动态的现有数据可查找、可获取、可互操作和可重复使用（FAIR）；2)开发用于处理这些数据和相关生态水文驱动因素的软件，并使用它来制作和评估近期迭代预测；3)制作一套教育资源，既可供个人使用，也可纳入学院和大学课程，包括互动预测网站、YouTube视频和课程材料；4)为研究生和本科生提供沼泽地生态预报的培训和研究经验。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Ecological forecasting is a crucial emerging area of scientific research that attempts to predict changes in ecosystems over time. Accurately predicting future change is important for managing natural resources, conserving protected areas, and improving scientific understanding of the natural world. The behavior of ecosystems is affected by scale -- the size of the area and amount of time being studied -- because the importance of different ecological processes often changes as area or time increases. However, how this impacts ecological forecasts is currently unknown. This research will use long-term monitoring of wading birds in the Everglades to advance our understanding of how scale impacts ecological forecasting. In the Everglades, nature operates at a variety of distinct scales of space and time that this research will use to advance our understanding of how scale impacts ecological forecasting. The project will provide information on which scales allow for the most accurate forecasts, how this is influenced by changes in the accuracy of weather forecasts with scale, and whether forecast models developed at one scale can be used to make accurate predictions at other scales. This will produce improved forecasts to guide Everglades restoration and a broad understanding of how to incorporate the size of the area, and amount of time being predicted, into ecological forecasts in general. The project will also make data and forecasts for Everglades wading birds broadly available and facilitate their use for science and education.Leveraging the intensive monitoring of wading birds and hydrology in the Everglades, the research will address three aspects of the impact and integration of scale in ecological forecasting: 1) Quantify how forecastability, drivers, and uncertainty vary across spatial scales by comparing models fit to the entire Everglades, ecohydrological regions, and individual colonies; 2) Leverage cross-spatial scale drivers and interactions to understand cross-scale ecology and improve ecological forecasts by fitting two types of cross-scale model, comparing them to single scale models, and evaluating how the importance of cross-scale drivers is related to driver forecasts; and 3) Evaluate transferability of annual scale models to seasonal forecasting to understand if annual scale models can be used to improve seasonal forecasting by assessing how well annual models perform for seasonal forecasts and comparing them to seasonal models. To facilitate the use of the resulting data and forecasts for research, education, and management, the project will: 1) Make existing data on Everglades wading bird dynamics findable, accessible, interoperable, and reusable (FAIR); 2) Develop software for working with this data and associated ecohydrological drivers and using it to make and evaluate near-term iterative forecasts; 3) Produce a suite of educational resources designed for both individual use and incorporation into college and university courses including interactive forecasting websites, YouTube videos, and lesson material; and 4) Provide training and research experiences in ecological forecasting in the Everglades for both graduate students and undergraduates.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.