2017
DOI: 10.1007/s10750-017-3285-1
|View full text |Cite
|
Sign up to set email alerts
|

The influence of paleoclimate on the distribution of genetic variability and demography of fishes in a large and highly fragmented neotropical river

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(3 citation statements)
references
References 81 publications
0
3
0
Order By: Relevance
“…Its higher migratory capacity (it can move 1000 km during the reproductive season; Petrere, 1985 ) probably played an important role in causing the lack of spatial genetic differentiation between populations. It is expected that long-distance migratory fishes within a hydrographic basin such as the Upper Paraguay, without physical, abiotic, and/or biotic barriers, will not show a spatial genetic structuring ( Pil et al, 2017 ). However, it seems that S .…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Its higher migratory capacity (it can move 1000 km during the reproductive season; Petrere, 1985 ) probably played an important role in causing the lack of spatial genetic differentiation between populations. It is expected that long-distance migratory fishes within a hydrographic basin such as the Upper Paraguay, without physical, abiotic, and/or biotic barriers, will not show a spatial genetic structuring ( Pil et al, 2017 ). However, it seems that S .…”
Section: Discussionmentioning
confidence: 99%
“…brasiliensis in the Upper Paraguay basin is unknown. Assessing the population genetic pattern of the existing species can identify how its genetic variation was affected by past climate changes and can also provide insights into its demographic response ( Pil et al, 2017 ).…”
Section: Introductionmentioning
confidence: 99%
“…Several approaches have been improved to analyze environmental stochastic events and evolutionary mechanisms, that are based on coalescence reconstruction and tools from computational statistics, including moment matching (Kaut & Wallace, 2003 ), population decline and growth detection (Cornuet & Luikart, 1996 ), and likelihood approaches with varying effective population sizes ( Ne of Wright, 1931 ) (Gilbert & Whitlock, 2015 ) based on contemporary and past Ne (Drummond, Rambaut, Shapiro, & Pybus, 2005 ; Waples, 1989 ; Waples & Yokota, 2007 ). These approaches have helped us to improve our knowledge about how evolutionary processes influence the life history of organisms (i.e., demographic events), in the wild (Hapeman, Latch, Rhodes, Swanson, & Kilpatrick, 2017 ; Perrier, Guyomard, Bagliniere, Nikolic, & Evanno, 2013 ; Pil et al, 2018 ). Likewise that have been recently affected by selection/anthropogenic pressures, such as rapid contemporary climate change (Crozier & Hutchings, 2014 ), habitat degradation and disconnection (Lourenço et al, 2017 ), (re)introduction of species (Hapeman et al, 2017 ), and/or stocking programs (Hansen, Fraser, Meier, & Mensberg, 2009 ).…”
Section: Introductionmentioning
confidence: 99%