2016
DOI: 10.1098/rstb.2015.0225
|View full text |Cite
|
Sign up to set email alerts
|

Fossil biogeography: a new model to infer dispersal, extinction and sampling from palaeontological data

Abstract: Methods in historical biogeography have revolutionized our ability to infer the evolution of ancestral geographical ranges from phylogenies of extant taxa, the rates of dispersals, and biotic connectivity among areas. However, extant taxa are likely to provide limited and potentially biased information about past biogeographic processes, due to extinction, asymmetrical dispersals and variable connectivity among areas. Fossil data hold considerable information about past distribution of lineages, but suffer fro… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
63
0

Year Published

2016
2016
2024
2024

Publication Types

Select...
6
2

Relationship

1
7

Authors

Journals

citations
Cited by 53 publications
(63 citation statements)
references
References 69 publications
(155 reference statements)
0
63
0
Order By: Relevance
“…[32,33]). The past decade or so has also witnessed the merging of two fields to develop the new discipline of phylogenetic community ecology [34][35][36] along with the emergence of conservation palaeobiology [37], the rise of palaeobiogeography ( [38] and see [39]) and the recognition of the importance of biodiversity time series [9] and palaeo(macro)ecology. This issue builds upon these efforts, highlighting the importance of integrating the dynamic nature of environmental, biological and geological processes through time and thus necessitating the synthesis of many of these individual fields.…”
Section: Introductionmentioning
confidence: 99%
“…[32,33]). The past decade or so has also witnessed the merging of two fields to develop the new discipline of phylogenetic community ecology [34][35][36] along with the emergence of conservation palaeobiology [37], the rise of palaeobiogeography ( [38] and see [39]) and the recognition of the importance of biodiversity time series [9] and palaeo(macro)ecology. This issue builds upon these efforts, highlighting the importance of integrating the dynamic nature of environmental, biological and geological processes through time and thus necessitating the synthesis of many of these individual fields.…”
Section: Introductionmentioning
confidence: 99%
“…A major problem with most methods that use extant data only is the fact that ancestral geographical ranges inferred from phylogenies might be blind to local past extinction and temporal changes in the asymmetry of dispersal rates. Silvestro et al [97] applied their method to a genus-level empirical dataset of Cenozoic terrestrial plants. Their empirical results suggest a predominant dispersal from Eurasia to North America in the Eocene climatic cooling period, but a higher dispersal from North America to Eurasia during the more stable climatic period between 32 and 14 Ma.…”
Section: The Regulators and Their Signaturesmentioning
confidence: 99%
“…The preservational biases of the fossil record are exacerbated when variations through space and time require analytical attention. In this volume, Silvestro et al [97] develop flexible new dispersal-extinction approaches that use fossil data to infer macroevolutionary and biogeographic processes while taking into account the incompleteness (temporal and spatial) of the fossil record [98,99]. The impact of migration is not symmetric [97,100], implying a role for biotic interactions among already existing species and the new invaders in determining macroevolutionary fates.…”
Section: The Regulators and Their Signaturesmentioning
confidence: 99%
See 1 more Smart Citation
“…These numbers include not only living species but also fossil taxa, allowing for biogeographic analyses based on both sources of data (e.g., Antonelli et al 2015; Silvestro et al 2016). Species occurrence data are steadily increasing thanks to new agreements on data sharing, on-going digitalization programs, and tools that enable automated geo-referencing of older museum specimens (Guralnick et al 2006; Garcia-Milagros and Funk 2010).…”
mentioning
confidence: 99%