English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/155627
COMPARTIR / IMPACTO:
Estadísticas
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Título

Seven shortfalls that beset large-scale knowledge of biodiversity

AutorHortal, Joaquín ; Bello, Francesco de; Diniz-Filho, J.A.F.; Lewinsohn, T.M.; Lobo, Jorge M. ; Ladle, R.J.
Palabras claveUncertainty
Macroecology
Knowledge shortfalls
Functional ecology
Bias
Scientific ignorance
Biodiversity data
Fecha de publicación2015
EditorAnnual Reviews
CitaciónAnnual Review of Ecology Evolution and Systematics 46: 523-549 (2015)
ResumenEcologists and evolutionary biologists are increasingly using big-data approaches to tackle questions at large spatial, taxonomic, and temporal scales. However, despite recent efforts to gather two centuries of biodiversity inventories into comprehensive databases, many crucial research questions remain unanswered. Here, we update the concept of knowledge shortfalls and review the tradeoffs between generality and uncertainty. We present seven key shortfalls of current biodiversity data. Four previously proposed shortfalls pinpoint knowledge gaps for species taxonomy (Linnean), distribution (Wallacean), abundance (Prestonian), and evolutionary patterns (Darwinian). We also redefine the Hutchinsonian shortfall to apply to the abiotic tolerances of species and propose new shortfalls relating to limited knowledge of species traits (Raunkiæran) and biotic interactions (Eltonian). We conclude with a general framework for the combined impacts and consequences of shortfalls of large-scale biodiversity knowledge for evolutionary and ecological research and consider ways of overcoming the seven shortfalls and dealing with the uncertainty they generate.
URIhttp://hdl.handle.net/10261/155627
DOI10.1146/annurev-ecolsys-112414-054400
Identificadoresdoi: 10.1146/annurev-ecolsys-112414-054400
issn: 1545-2069
Aparece en las colecciones: (MNCN) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
accesoRestringido.pdf15,38 kBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo
 


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.