13. Metodologías para el análisis de la conectividad

The topics covered in this video are as follows: Simple spatial indices. Spatially explicit population models. Graphs. Graphs and landscape connectivity. Components, direct connections, and indirect connections. Data requirements versus level of detail in the results. Graphs: operational and adaptable. Graphs: spatially explicit results without population projection. Summary of the advantages and characteristics of graphs. The rest of the course, beyond the content of this video (13), was taught in person and is not currently available as videos. The in-person portion of the course comprises slightly more than two-thirds of its total length and focuses on the core methods and tools for connectivity analysis, their details, and their application in various exercises and practical case studies drawn from real-world scenarios. These are primarily addressed in the computer lab using specialized connectivity analysis software and geographic information systems. You can subscribe to the channel if you wish to receive notifications of new videos that may be added in the future, covering other sections of the course not currently available in video format. If you are interested in some of the content of the rest of the course, it is recommended that you read the following two publications, both first authored by Santiago Saura, the first in Spanish and the second in English: 1) The book chapter "Methods and Tools for Landscape Connectivity Analysis and its Integration into Conservation Plans," published on pages 1-46 of the book "Advances in the Spatial Analysis of Ecological Data: Methodological and Applied Aspects," published in 2013 by the Spanish Association of Terrestrial Ecology. This is available at http://www.conefor.org/files/usuarios... 2) The book chapter "Connectivity as the amount of reachable habitat: conservation priorities and the roles of habitat patches in landscape networks," published on pages 229-254 of the book "Learning Landscape Ecology: A Practical Guide to Concepts and Techniques, 2nd edition" (Springer-Verlag) in 2017. This book chapter includes a series of exercises related to landscape connectivity analysis for interested parties to complete, primarily using the Conefor tool (http://www.conefor.org/) and the indices implemented within it. The chapter includes instructions for using the Conefor tool in these practical exercises. The book chapter, along with the necessary files to address and solve the exercises and their solutions, is available at http://www.conefor.org/files/usuarios... Regarding the specific content of this video (13), the following articles in English are recommended as a complement and expansion of said content: Calabrese and Fagan (2004), entitled "A comparison-shopper’s guide to connectivity metrics" and available at http://www.clfs.umd.edu/biology/fagan... This article presents a review and comparison of different methodologies and indices for connectivity analysis and concludes that graphs are the methodology that offers the best balance between effort (amount of data required) and benefit (type and detail of the results provided) for characterizing connectivity at large scales. Visconti and Elkin (2009), entitled "Using connectivity metrics in conservation planning – when does habitat quality matter?" and available at https://onlinelibrary.wiley.com/doi/f... This article shows how some graph-based indices, and specifically the Connectivity Probability (CP) index, which will be covered in detail in the face-to-face portion of the course, provide tile importance prioritizations similar to those of much more complex and dynamic population models. Minor and Urban (2007), entitled "Graph theory as a proxy for spatially explicit population models in conservation planning" and available at http://citeseerx.ist.psu.edu/viewdoc/... This article shows how graphs are capable of providing management and conservation prioritizations similar to those of much more complex, spatially explicit population models, and therefore concludes that, in general, graphs are a feasible and possibly preferable alternative for applications related to species conservation in heterogeneous landscapes.