rWind: download, edit and include wind data in ecological and evolutionary analysis
1) Wind connectivity has been identified as a key factor driving many biological processes. 2) Existing software available for managing wind data are often overly complex for studying many ecological processes and cannot be incorporated into a broad framework. 3) Here we present rWind, an R language...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/129879 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/129879 |
| Access Level: | acceso abierto |
| Palabra clave: | 591.5 581.5 519.87:004 574.9 R Wind connectivity Landscape genetics Ecología (Biología) Software 2401.06 Ecología Animal 2417.13 Ecología Vegetal 1203.26 Simulación 2505.01 Biogeografía |
| Sumario: | 1) Wind connectivity has been identified as a key factor driving many biological processes. 2) Existing software available for managing wind data are often overly complex for studying many ecological processes and cannot be incorporated into a broad framework. 3) Here we present rWind, an R language package to download and manage surface wind data from the Global Forecasting System and to compute wind connectivity between locations. 4) Data obtained with rWind can be used in a general framework for analysis of biological processes to develop hypotheses about the role of wind in driving ecological and evolutionary patterns. |
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