LakeMetabolizer: an R package for estimating lake metabolism from free-water oxygen using diverse statistical models
LakeMetabolizer: an R package for estimating lake metabolism from free-water oxygen using diverse statistical models
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DOI：
10.5268/iw-6.4.883
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发表时间：
2016-01-01
期刊：
影响因子：
3.1
通讯作者：
Read, Jordan S.
中科院分区：
文献类型：
--
作者：
Winslow, Luke A.;Zwart, Jacob A.;Read, Jordan S.
新陈代谢是生态系统中的一个基本过程，跨越从个体生物体到整个生态系统的多个组织尺度。为了改善已发布代谢模型的共享和重用，我们开发了 LakeMetabolizer，这是一个 R 包，用于根据溶解氧、水温和其他环境变量的原位时间序列来估计湖泊代谢。 LakeMetabolizer 实现了 5 种具有不同统计基础的不同代谢模型：簿记、普通最小二乘、最大似然、卡尔曼滤波器和贝叶斯。这 5 种代谢模型中的每一种都可以与 7 种模型中的一种相结合，用于计算空气-水界面上的气体交换系数 (k)。 LakeMetabolizer 还具有各种支持功能，可在估计代谢之前计算转换并实现通常应用于原始数据的计算（例如氧饱和度和光学转换模型）。这些工具已组织到 R 包中，其中包含示例数据、示例用例和功能文档。发布包版本可在综合 R 存档网络 (CRAN) 上获取，完整的开源 GPL 许可代码可免费在线检查和扩展。借助这个统一、开源且免费提供的软件包，我们希望改善可及性并促进新陈代谢在静默生态系统的研究和管理中的应用。
Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air-water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.