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Historical colonization and dispersal limitation supplement climate and topography in shaping species richness of African lizards (Reptilia: Agaminae)

View Article: PubMed Central - PubMed

ABSTRACT

To what extent deep-time dispersal limitation shapes present-day biodiversity at broad spatial scales remains elusive. Here, we compiled a continental dataset on the distributions of African lizard species in the reptile subfamily Agaminae (a relatively young, Neogene radiation of agamid lizards which ancestors colonized Africa from the Arabian peninsula) and tested to what extent historical colonization and dispersal limitation (i.e. accessibility from areas of geographic origin) can explain present-day species richness relative to current climate, topography, and climate change since the late Miocene (~10 mya), the Pliocene (~3 mya), and the Last Glacial Maximum (LGM, 0.021 mya). Spatial and non-spatial multi-predictor regression models revealed that time-limited dispersal via arid corridors is a key predictor to explain macro-scale patterns of species richness. In addition, current precipitation seasonality, current temperature of the warmest month, paleo-temperature changes since the LGM and late Miocene, and topographic relief emerged as important drivers. These results suggest that deep-time dispersal constraints — in addition to climate and mountain building — strongly shape current species richness of Africa’s arid-adapted taxa. Such historical dispersal limitation might indicate that natural movement rates of species are too slow to respond to rates of ongoing and projected future climate and land use change.

No MeSH data available.


Related in: MedlinePlus

Distributional knowledge of agamid lizards across Africa.In (a), 1,454 geo-referenced and quality-checked records across all 74 species of agamid lizards are shown. The records are spatially unique at 10 × 10 km resolution. In (b), examples of binary species distribution maps at 10 × 10 km resolution are illustrated as derived from occurrence records and species distribution modelling. Species with <5 records (e.g. Trapelus savignii and Agama robecchii) were not modelled. Species with sample sizes 20 > x ≥ 5 (e.g. Trapelus aspersus and Agama planiceps) were modelled with a bioclimatic envelop (surface range envelope) model. Species with ≥20 records were modelled either with a bioclimatic envelop model (e.g. Agama sankaranica), machine-learning methods such as Maxent (e.g. Agama finchi), or generalized boosting models (e.g. Agama lionotus). In cases where a shortage of locality records did not allow to accurately predict a species distributional range (e.g. Agama planiceps), model predictions were complemented with expert-based range maps (shown with green lines). In (c), agamid species richness is illustrated, derived from summing up all individual species distributions for a grid in cylindrical equal area projection with 110 × 110 km resolution (equivalent to c. 1° × 1° near the equator). Species distributions were modelled using the statistical programming language R and maps were created using ArcGIS (version 10.2, ESRI, Redlands, CA, USA).
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f1: Distributional knowledge of agamid lizards across Africa.In (a), 1,454 geo-referenced and quality-checked records across all 74 species of agamid lizards are shown. The records are spatially unique at 10 × 10 km resolution. In (b), examples of binary species distribution maps at 10 × 10 km resolution are illustrated as derived from occurrence records and species distribution modelling. Species with <5 records (e.g. Trapelus savignii and Agama robecchii) were not modelled. Species with sample sizes 20 > x ≥ 5 (e.g. Trapelus aspersus and Agama planiceps) were modelled with a bioclimatic envelop (surface range envelope) model. Species with ≥20 records were modelled either with a bioclimatic envelop model (e.g. Agama sankaranica), machine-learning methods such as Maxent (e.g. Agama finchi), or generalized boosting models (e.g. Agama lionotus). In cases where a shortage of locality records did not allow to accurately predict a species distributional range (e.g. Agama planiceps), model predictions were complemented with expert-based range maps (shown with green lines). In (c), agamid species richness is illustrated, derived from summing up all individual species distributions for a grid in cylindrical equal area projection with 110 × 110 km resolution (equivalent to c. 1° × 1° near the equator). Species distributions were modelled using the statistical programming language R and maps were created using ArcGIS (version 10.2, ESRI, Redlands, CA, USA).

Mentions: Here, we test to what extent continental colonization and historical dispersal routes can explain present-day species richness of agamid lizards (subfamily Agaminae) in Africa relative to current climate, topography, and paloeclimatic changes. We first compiled a comprehensive database of species occurrence records across the continent, then used species distributions models (SDMs) combined with expert-based knowledge to derive continental species distribution maps of agamid lizards, and finally aggregated all distributional information at c. 110 × 110 km resolution to quantify species richness across Africa (Fig. 1). In a second step, we simulated potential dispersal routes for the entire subfamily as spatial spread patterns from the Arabian Peninsula into the African continent, and then correlated this simulated accessibility with agamid species richness across Africa. Finally, we used the simulated dispersal spread patterns together with other predictor variables (incl. current climate, paleoclimate and topographic heterogeneity; Table 1) to test whether historical dispersal routes are a strong explanatory variable for current species richness after accounting for other factors. We used multi-predictor models, incl. both non-spatial and spatial regressions, to evaluate the relative importance with standardized coefficients and partial residual plots. We show that geographic colonization from the Arabian Peninsula and dispersal limitation is a key predictor of present-day species richness of agamid lizards, suggesting that deep-time dispersal constraints shape biodiversity across Africa.


Historical colonization and dispersal limitation supplement climate and topography in shaping species richness of African lizards (Reptilia: Agaminae)
Distributional knowledge of agamid lizards across Africa.In (a), 1,454 geo-referenced and quality-checked records across all 74 species of agamid lizards are shown. The records are spatially unique at 10 × 10 km resolution. In (b), examples of binary species distribution maps at 10 × 10 km resolution are illustrated as derived from occurrence records and species distribution modelling. Species with <5 records (e.g. Trapelus savignii and Agama robecchii) were not modelled. Species with sample sizes 20 > x ≥ 5 (e.g. Trapelus aspersus and Agama planiceps) were modelled with a bioclimatic envelop (surface range envelope) model. Species with ≥20 records were modelled either with a bioclimatic envelop model (e.g. Agama sankaranica), machine-learning methods such as Maxent (e.g. Agama finchi), or generalized boosting models (e.g. Agama lionotus). In cases where a shortage of locality records did not allow to accurately predict a species distributional range (e.g. Agama planiceps), model predictions were complemented with expert-based range maps (shown with green lines). In (c), agamid species richness is illustrated, derived from summing up all individual species distributions for a grid in cylindrical equal area projection with 110 × 110 km resolution (equivalent to c. 1° × 1° near the equator). Species distributions were modelled using the statistical programming language R and maps were created using ArcGIS (version 10.2, ESRI, Redlands, CA, USA).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5037428&req=5

f1: Distributional knowledge of agamid lizards across Africa.In (a), 1,454 geo-referenced and quality-checked records across all 74 species of agamid lizards are shown. The records are spatially unique at 10 × 10 km resolution. In (b), examples of binary species distribution maps at 10 × 10 km resolution are illustrated as derived from occurrence records and species distribution modelling. Species with <5 records (e.g. Trapelus savignii and Agama robecchii) were not modelled. Species with sample sizes 20 > x ≥ 5 (e.g. Trapelus aspersus and Agama planiceps) were modelled with a bioclimatic envelop (surface range envelope) model. Species with ≥20 records were modelled either with a bioclimatic envelop model (e.g. Agama sankaranica), machine-learning methods such as Maxent (e.g. Agama finchi), or generalized boosting models (e.g. Agama lionotus). In cases where a shortage of locality records did not allow to accurately predict a species distributional range (e.g. Agama planiceps), model predictions were complemented with expert-based range maps (shown with green lines). In (c), agamid species richness is illustrated, derived from summing up all individual species distributions for a grid in cylindrical equal area projection with 110 × 110 km resolution (equivalent to c. 1° × 1° near the equator). Species distributions were modelled using the statistical programming language R and maps were created using ArcGIS (version 10.2, ESRI, Redlands, CA, USA).
Mentions: Here, we test to what extent continental colonization and historical dispersal routes can explain present-day species richness of agamid lizards (subfamily Agaminae) in Africa relative to current climate, topography, and paloeclimatic changes. We first compiled a comprehensive database of species occurrence records across the continent, then used species distributions models (SDMs) combined with expert-based knowledge to derive continental species distribution maps of agamid lizards, and finally aggregated all distributional information at c. 110 × 110 km resolution to quantify species richness across Africa (Fig. 1). In a second step, we simulated potential dispersal routes for the entire subfamily as spatial spread patterns from the Arabian Peninsula into the African continent, and then correlated this simulated accessibility with agamid species richness across Africa. Finally, we used the simulated dispersal spread patterns together with other predictor variables (incl. current climate, paleoclimate and topographic heterogeneity; Table 1) to test whether historical dispersal routes are a strong explanatory variable for current species richness after accounting for other factors. We used multi-predictor models, incl. both non-spatial and spatial regressions, to evaluate the relative importance with standardized coefficients and partial residual plots. We show that geographic colonization from the Arabian Peninsula and dispersal limitation is a key predictor of present-day species richness of agamid lizards, suggesting that deep-time dispersal constraints shape biodiversity across Africa.

View Article: PubMed Central - PubMed

ABSTRACT

To what extent deep-time dispersal limitation shapes present-day biodiversity at broad spatial scales remains elusive. Here, we compiled a continental dataset on the distributions of African lizard species in the reptile subfamily Agaminae (a relatively young, Neogene radiation of agamid lizards which ancestors colonized Africa from the Arabian peninsula) and tested to what extent historical colonization and dispersal limitation (i.e. accessibility from areas of geographic origin) can explain present-day species richness relative to current climate, topography, and climate change since the late Miocene (~10 mya), the Pliocene (~3 mya), and the Last Glacial Maximum (LGM, 0.021 mya). Spatial and non-spatial multi-predictor regression models revealed that time-limited dispersal via arid corridors is a key predictor to explain macro-scale patterns of species richness. In addition, current precipitation seasonality, current temperature of the warmest month, paleo-temperature changes since the LGM and late Miocene, and topographic relief emerged as important drivers. These results suggest that deep-time dispersal constraints &mdash; in addition to climate and mountain building &mdash; strongly shape current species richness of Africa&rsquo;s arid-adapted taxa. Such historical dispersal limitation might indicate that natural movement rates of species are too slow to respond to rates of ongoing and projected future climate and land use change.

No MeSH data available.


Related in: MedlinePlus