The Latitudinal Diversity Gradient : Novel Understanding through Mechanistic Eco-evolutionary Models
(2019) In Trends in Ecology and Evolution 34(3). p.211-223- Abstract
The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the... (More)
The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the relative importance of different processes for generating the LDG.
(Less)
- author
- organization
- publishing date
- 2019-03-01
- type
- Contribution to journal
- publication status
- published
- keywords
- biogeography, diversity patterns, ecology, evolution, macroecology, mechanistic modeling
- in
- Trends in Ecology and Evolution
- volume
- 34
- issue
- 3
- pages
- 13 pages
- publisher
- Elsevier
- external identifiers
-
- pmid:30591209
- scopus:85058961693
- ISSN
- 0169-5347
- DOI
- 10.1016/j.tree.2018.11.009
- project
- Theoretical Macroevolutionary Ecology
- language
- English
- LU publication?
- no
- id
- 30b54a48-6c23-4505-9302-012d65b8a61c
- date added to LUP
- 2019-04-10 10:24:25
- date last changed
- 2024-04-16 03:14:04
@article{30b54a48-6c23-4505-9302-012d65b8a61c, abstract = {{<p>The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the relative importance of different processes for generating the LDG.</p>}}, author = {{Pontarp, Mikael and Bunnefeld, Lynsey and Cabral, Juliano Sarmento and Etienne, Rampal S. and Fritz, Susanne A. and Gillespie, Rosemary and Graham, Catherine H. and Hagen, Oskar and Hartig, Florian and Huang, Shan and Jansson, Roland and Maliet, Odile and Münkemüller, Tamara and Pellissier, Loïc and Rangel, Thiago F. and Storch, David and Wiegand, Thorsten and Hurlbert, Allen H.}}, issn = {{0169-5347}}, keywords = {{biogeography; diversity patterns; ecology; evolution; macroecology; mechanistic modeling}}, language = {{eng}}, month = {{03}}, number = {{3}}, pages = {{211--223}}, publisher = {{Elsevier}}, series = {{Trends in Ecology and Evolution}}, title = {{The Latitudinal Diversity Gradient : Novel Understanding through Mechanistic Eco-evolutionary Models}}, url = {{http://dx.doi.org/10.1016/j.tree.2018.11.009}}, doi = {{10.1016/j.tree.2018.11.009}}, volume = {{34}}, year = {{2019}}, }