Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method.
Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method.
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DOI：
10.1002/ece3.2884
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发表时间：
2017-05
影响因子：
2.6
通讯作者：
Wagner T
中科院分区：
文献类型：
--
作者：
Cheruvelil KS;Yuan S;Webster KE;Tan PN;Lapierre JF;Collins SM;Fergus CE;Scott CE;Henry EN;Soranno PA;Filstrup CT;Wagner T
理解大尺度的生态模式和过程往往涉及到区域尺度的异质性。这样做的一个常见方法是将生态区域纳入抽样计划和经验模型。然而，大多数现有的生态区域是为特定目的开发的，使用的是有限的地理空间特征和不可复制的方法。我们的研究目的是：（1）描述一种方法，该方法利用最近的计算进步和区域和全球数据集的增加的可用性来创建可定制和可再现的生态区域，（2）使该算法可用于研究不同生态系统、感兴趣的变量、研究范围和宏观生态学研究问题的其他人的使用和修改，和（3）证明这种方法的研究问题的力量，这些地区如何捕捉区域尺度的湖泊水质变化？为了实现我们的目标，我们：（1）使用空间约束谱聚类算法，平衡地理空间同质性和区域连续性，使用美国东北部17个州的多个陆地、气候和淡水地理空间数据创建生态区域（~ 1，800，000平方公里）;（2）确定52个地理空间特征中哪些对创建100个区域最有影响力;以及（3）测试这些生态区域捕获约6，000个湖泊的水营养物和透明度的区域变化的能力。我们发现：（1）陆地、气候和淡水地理空间特征的组合影响了区域的创建，这表明经常被忽视的淡水景观提供了传统气候和陆地指标无法捕获的景观变异性的新信息;以及（2）划定的区域捕获了区域划定中未包括的生态系统属性的宏观尺度异质性-约40%湖泊间总磷和水质透明度的变化主要表现在区域尺度上。我们的研究结果表明，这种方法用于创建可定制的和可重复的区域的研究和管理应用程序的有用性。
Understanding broad‐scale ecological patterns and processes often involves accounting for regional‐scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional‐scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft‐ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.