Moon J B, DeWitt T H, Errend M N, Bruins R J F, Kentula M E, Chamberlain S J, Fennessy M S, Naithani K J
Oak Ridge Institute for Science and Education Postdoctoral Fellow, in residence at U.S. Environmental Protection Agency, National Health & Environmental Effects Laboratory, Western Ecology Division, Pacific Coast Ecology Branch, Newport, OR, U.S.A., 97365.
Department of Biological Sciences, University of Arkansas, Fayetteville, AR, U.S.A., 72701.
Ecosphere. 2017 Oct;8(10). doi: 10.1002/ecs2.1974. Epub 2017 Oct 20.
The use of models by ecologists and environmental managers, to inform environmental management and decision-making, has grown exponentially in the past 50 years. Due to logistical, economical, and theoretical benefits, model users frequently transfer preexisting models to new sites where data are scarce. Modelers have made significant progress in understanding how to improve model generalizability during model development. However, models are always imperfect representations of systems and are constrained by the contextual frameworks used during their development. Thus, model users need better ways to evaluate the possibility of unintentional misapplication when transferring models to new sites. We propose a method of describing a model's application niche for use during the model selection process. Using this method, model users synthesize information from databases, past studies, and/or past model transfers to create model performance curves and heat maps. We demonstrated this method using an empirical model developed to predict the ecological condition of plant communities in riverine wetlands of the Appalachian Highland physiographic region, U.S.A. We assessed this model's transferability and generalizability across (1) riverine wetlands in the contiguous U.S.A., (2) wetland types in the Appalachian Highland physiographic region, and (3) wetland types in the contiguous U.S.A. With this methodology and a discussion of its critical steps, we set the stage for further inquiries into the development of consistent and transparent practices for model selection when transferring a model.
在过去50年里，生态学家和环境管理者为指导环境管理与决策而使用模型的情况呈指数级增长。由于后勤、经济和理论方面的益处，模型使用者经常将现有的模型转移到数据稀缺的新地点。建模者在理解如何在模型开发过程中提高模型通用性方面取得了重大进展。然而，模型始终是系统的不完美表示，并且受到其开发过程中所使用的背景框架的限制。因此，模型使用者需要更好的方法来评估将模型转移到新地点时无意误用的可能性。我们提出了一种在模型选择过程中描述模型应用生态位的方法。使用这种方法，模型使用者整合来自数据库、以往研究和/或以往模型转移的信息，以创建模型性能曲线和热图。我们使用一个为预测美国阿巴拉契亚高地自然地理区域河流湿地植物群落生态状况而开发的实证模型演示了这种方法。我们评估了该模型在以下方面的可转移性和通用性：（1）美国本土的河流湿地，（2）阿巴拉契亚高地自然地理区域的湿地类型，以及（3）美国本土的湿地类型。通过这种方法及其关键步骤的讨论，我们为进一步探究在转移模型时进行一致且透明的模型选择实践的发展奠定了基础。
