Applying network theory to animal movements to identify properties of landscape space use

被引:37
作者
Bastille-Rousseau, Guillaume [1 ,2 ]
Douglas-Hamilton, Iain [2 ]
Blake, Stephen [3 ,4 ]
Northrup, Joseph M. [5 ]
Wittemyer, George [1 ,2 ]
机构
[1] Colorado State Univ, Dept Fish Wildlife & Conservat Biol, Ft Collins, CO 80523 USA
[2] Save Elephants, Nairobi, Kenya
[3] Max Planck Inst Ornithol, Radolfzell am Bodensee, Germany
[4] Charles Darwin Fdn, Puerto Ayora, Galapagos, Ecuador
[5] Ontario Minist Nat Resources & Forestry, Wildlife Res & Monitoring Sect, Peterborough, ON K9L 1Z8, Canada
基金
美国国家科学基金会; 加拿大自然科学与工程研究理事会;
关键词
animal movement; connectivity; GPS radio telemetry; movement corridor; network (graph) theory; space use; HABITAT-SELECTION; WOODLAND CARIBOU; SPATIAL NETWORK; CONNECTIVITY; MODELS; DYNAMICS; INFERENCE; REVEALS; TOOLS;
D O I
10.1002/eap.1697
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a framework for conservationists to analyze movement data. Functions created for the analyses are available within the R package moveNT.
引用
收藏
页码:854 / 864
页数:11
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