Modelling dendritic ecological networks in space: anintegrated network perspective
Ecology Letters
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Abstract
Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within
the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Modelling dendritic ecological networks in space: anintegrated network perspective |
| Series title | Ecology Letters |
| DOI | 10.1111/ele.12084 |
| Volume | 16 |
| Issue | 5 |
| Year Published | 2013 |
| Language | English |
| Publisher | Wiley |
| Contributing office(s) | Forest and Rangeland Ecosystem Science Center |
| Description | 13 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Ecology Letters |
| First page | 707 |
| Last page | 719 |
| Google Analytic Metrics | Metrics page |