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，它试图预测随着时间的推移生态系统的变化。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界的科学理解非常重要。生态系统的行为受到规模--研究区域的大小和时间--的影响，因为不同生态过程的重要性往往随着区域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。这项研究将利用对大沼泽地涉禽的长期监测来促进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行，本研究将利用这些空间和时间尺度来促进我们对尺度如何影响生态预测的理解。该项目将提供信息，说明哪些尺度可以提供最准确的预报，天气预报的准确度随尺度变化对此有何影响，以及在一个尺度上开发的预报模型是否可以用于在其他尺度上进行准确预测。这将产生改进的预测，以指导大沼泽地的恢复，并对如何将区域大小和预测的时间纳入总体生态预测有广泛的理解。该项目还将广泛提供湿地涉禽的数据和预报，并促进它们用于科学和教育。利用对湿地涉禽和水文的密集监测，该研究将解决生态预测中尺度的影响和整合的三个方面：1)通过比较适用于整个湿地、生态水文区和单个殖民地的模型，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)利用跨空间尺度驱动因素和相互作用，通过拟合两种类型的跨尺度模型，将它们与单尺度模型进行比较，并评估跨尺度驱动因素与驱动因素预测的关系，来了解跨尺度生态和改善生态预报；以及3)评估年度尺度模型向季节预报的可转换性，通过评估年度尺度模型对季节预报的表现并将其与季节性模型进行比较，来了解年度尺度模型是否可以用于改进季节预报。为了便于将结果数据和预报用于研究、教育和管理，该项目将：1)使现有的沼泽地涉禽动态数据可查找、可访问、可互操作和可重复使用(FIRE)；2)开发使用这些数据和相关生态水文驱动因素的软件，并利用它制作和评估近期迭代预报；3)制作一套教育资源，供个人使用，并纳入学院和大学课程，包括互动预报网站、YouTube视频和课程材料；以及4)为研究生和本科生提供沼泽地生态预测方面的培训和研究经验。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.