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Review

Selecting Graph Metrics with Ecological Significance for Deepening Landscape Characterization: Review and Applications

by
Felipe de la Barra
1,2,
Audrey Alignier
3,4,
Sonia Reyes-Paecke
1,5,
Andrea Duane
6 and
Marcelo D. Miranda
1,2,*
1
Faculty of Agronomy and Forest Engineering, Pontificia Universidad Católica de Chile, Santiago 7830436, Chile
2
Center of Applied Ecology and Sustainability (CAPES), Pontificia Universidad Católica de Chile, Santiago 7830436, Chile
3
Unité Mixte de Recherche 0980 Biodiversité, Agroécologie et Aménagement du Paysage INRAE-ESA-Institut Agro, CEDEX, 35042 Rennes, France
4
LTSER “Zone Atelier Armorique”, CEDEX, 35042 Rennes, France
5
Center for Sustainable Urban Development, Pontificia Universidad Católica de Chile, Santiago 7830436, Chile
6
Forest Science Centre of Catalonia (CTFC), 25280 Solsona-Lleida, Spain
*
Author to whom correspondence should be addressed.
Land 2022, 11(3), 338; https://doi.org/10.3390/land11030338
Submission received: 28 January 2022 / Revised: 11 February 2022 / Accepted: 15 February 2022 / Published: 25 February 2022

Abstract

The usual approaches to describing and understanding ecological processes in a landscape use patch-mosaic models based on traditional landscape metrics. However, they do not consider that many of these processes cannot be observed without considering the multiple interactions between different land-use patches in the landscape. The objective of this research was to provide a synthetic overview of graph metrics that characterize landscapes based on patch-mosaic models and to analyze the ecological meaning of the metrics to propose a relevant selection explaining biodiversity patterns and ecological processes. First, we conducted a literature review of graph metrics applied in ecology. Second, a case study was used to explore the behavior of a group of selected graph metrics in actual differentiated landscapes located in a long-term socioecological research site in Brittany, France. Thirteen landscape-scale metrics and 10 local-scale metrics with ecological significance were analyzed. Metrics were grouped for landscape-scale and local-scale analysis. Many of the metrics were able to identify differences between the landscapes studied. Lastly, we discuss how graph metrics offer a new perspective for landscape analysis, describe the main characteristics related to their calculation and the type of information provided, and discuss their potential applications in different ecological contexts.
Keywords: landscape graph metrics; landscape heterogeneity; spatial graph; landscape characterization landscape graph metrics; landscape heterogeneity; spatial graph; landscape characterization

Share and Cite

MDPI and ACS Style

de la Barra, F.; Alignier, A.; Reyes-Paecke, S.; Duane, A.; Miranda, M.D. Selecting Graph Metrics with Ecological Significance for Deepening Landscape Characterization: Review and Applications. Land 2022, 11, 338. https://doi.org/10.3390/land11030338

AMA Style

de la Barra F, Alignier A, Reyes-Paecke S, Duane A, Miranda MD. Selecting Graph Metrics with Ecological Significance for Deepening Landscape Characterization: Review and Applications. Land. 2022; 11(3):338. https://doi.org/10.3390/land11030338

Chicago/Turabian Style

de la Barra, Felipe, Audrey Alignier, Sonia Reyes-Paecke, Andrea Duane, and Marcelo D. Miranda. 2022. "Selecting Graph Metrics with Ecological Significance for Deepening Landscape Characterization: Review and Applications" Land 11, no. 3: 338. https://doi.org/10.3390/land11030338

APA Style

de la Barra, F., Alignier, A., Reyes-Paecke, S., Duane, A., & Miranda, M. D. (2022). Selecting Graph Metrics with Ecological Significance for Deepening Landscape Characterization: Review and Applications. Land, 11(3), 338. https://doi.org/10.3390/land11030338

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