The Latitudinal Diversity Gradient: Novel Understanding through Mechanistic Eco-evolutionary Models
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 relative importance of different processes for generating the LDG.
What the paper shows and why it matters
(AI-generated)
The latitudinal diversity gradient, the rise in species richness from the poles to the equator, has at least 26 proposed explanations. They fall into three groups: differences in ecological limits (how many species a region can support), in diversification rates (how fast species form) and in the time available for species to accumulate. Each names an explicit driver that varies with latitude, and data appear compatible with many of them, yet no consensus has emerged. The paper traces this largely to the verbal form of the hypotheses: each rests on one driver, predicts few patterns and leaves assumptions about other processes unstated. Because the explanations may not be mutually exclusive, such predictions alone may not separate them, and how strongly each underlying process contributes remains unresolved.
The paper proposes to replace competing verbal explanations of the latitudinal diversity gradient with computer simulations of four processes that any explanation must involve: selection, ecological drift (chance variation in births and deaths), dispersal and speciation. Such models produce many patterns at once, such as species ranges, family trees and trait distributions. Fitting these patterns to data could estimate how much each process contributes, rather than only asking which hypothesis wins. Re-reading four classic hypotheses through the four processes exposes hidden assumptions: the more-individuals hypothesis assumes that richness has reached equilibrium, and tropical niche conservatism implicitly assumes no zero-sum limit on the number of individuals, hence no diversity-limiting competition. An existing simulation model (Hurlbert and Stegen 2014), run with settings that mimic three hypotheses, shows how this works. Some patterns arose under all of them, including the gradient itself and the imbalance of family trees (how unevenly lineages branch), while others, such as the relation between speciation rate and latitude, may tell the hypotheses apart.
The paper concludes that the unit of analysis should be the processes and their assumptions, not the names of hypotheses. Hypotheses then become alternative model structures within one framework. Each is compared with data by matching simulated to observed patterns or by fitting with simulation-based methods such as Approximate Bayesian Computation, and a model that fails to reproduce a pattern shows where it needs improving. The paper presents this as a roadmap rather than a fitted analysis; model complexity, implementation choices and computing cost remain open challenges.
References
- Hurlbert & Stegen (2014). On the processes generating latitudinal richness gradients: identifying diagnostic patterns and predictions. Frontiers in Genetics 5. doi:10.3389/fgene.2014.00420