Fig 1.
Paleo-environmental variables used in simulations.
Topographic position index (TPI): a. Mountain tops, b. V-shaped valleys and c. broad flat areas. Hydrological categories (): d. meandering river, e. lake.
,
and Φ respectively stand for precipitation, temperature and physiographic diversity.
Table 1.
Hierarchical classification values, parametrisation for slope and water discharge.
Table 2.
Model forcing framework for testing LDG drivers.
Population dispersal is determined either by geographic distance alone, Δ () or by a combination of geographic distance and physical barriers—such as mountains and rivers—
) (M1d). Speciation begins when populations of a species become isolated either: by geographic distances Δ (
) or by physical barriers (Φ) (M1s). These isolated populations evolve independently through time based on their thermal tolerance (
). Diverging populations become distinct after reaching a threshold of differentiation. Species ecology is drawn from environmental suitability based on species’ niche (i) and carrying capacity (ii).
Table 3.
Model parameter ranges.
Fig 2.
Present day modeled and empirical terrestrial mammal α richness and the Latitudinal Diversity Gradient (LDG).
A. Model average predicted (left) and empirical (right [32]) richness of terrestrial mammals. Both modeled and empirical richness are normalized to their maximum value. B. Comparison of model results (M0, M1s, M1d, M1e) with empirical data [32] (black curve) on terrestrial mammals showing the present-day LDG left). Diversity is the mean richness normalized to its maximum value, per latitudinal degree. C. Mean environmental input variables, also area-scaled and normalized to their maximum values, per latitudinal degree, where : stands for physiographic diversity, T: temperature, P: precipitation, and H for hydrological categories. To ensure comparability with empirical data, mean values were calculated within the latitudinal range of −54° to 71°. Bathymetry is mapped using PALEOMAP reconstructions [6]. Reprinted from [6] under a CC BY license, with permission from C.R. Scotese, original copyright 2018.
Fig 3.
Paleogeography and main biodiversity drivers from modeled scenarios, model M1e.
(a) Richness, (b) Speciation, (c) Extinction, (d) Net diversification rate (Speciation – Extinction) and (e) and Turnover ((Speciation + Extinction)/Richness), over deep time, normalized to their maximum mean value. Paleo-diversity maps are represented using average model M1e as an example, given the high similarity in outcomes across models. Bathymetry is mapped using PALEOMAP reconstructions [6]. Reprinted from [6] under a CC BY license, with permission from C.R. Scotese, original copyright 2018.
Fig 4.
LDG slopes (a. and b.) and widths (c. and d.) derived from a hyperbolic tangent function fitted to the latitudinal α diversity curves and estimated separately for the Northern (a. and c.) and Southern (b. and d.) hemispheres using absolute latitude. Example of the hyperbolic tangent function fit for each modeled scenario for the Southern Hemisphere (e). LDG curves correspond to the normalized mean α richness per latitudinal degree, for models M0 (blue), M1s (green), M1d(orange), and M1e (red).
Fig 5.
Modeled mammalian biodiversification across paleolatitudes and at global scale.
A. Paleolatitude figures are represented using model M1e as an example (outcomes from all other models being similar at first order, see Fig S1, Fig S2, Fig S3). Each variable is measured as area-scaled, representing normalized to their maximum mean biodiversity metric per latitudinal degree. B. Normalized to their maximum mean biodiversity metric at global scale. Color-coded models: M0 (blue), M1s (green), M1d (orange), and M1e (red).
Fig 6.
From top to bottom, each landscape variable is represented as a function of paleolatitude: Mean land surface above sea-level (km2) with isocontour representing the median land surface; Mean elevation above sea-level (m) and simplified Köppen climatic belt, with tropical (A), arid (B), temperate (C), continental (D) and polar (E) regions.