Periodic Reporting for period 4 - MAPAS (Mapping biodiversity cradles and graves)
Période du rapport: 2025-06-01 au 2025-11-30
The MAPAS project addresses a central and long-standing problem in biodiversity science: understanding how large-scale patterns of biodiversity are generated, maintained, and lost through time, and how ecological and evolutionary processes interact across deep time and contemporary timescales to shape the distribution of life on Earth. In particular, the project focuses on explaining the emergence of global patterns such as latitudinal diversity gradients, centers of megadiversity, and the uneven distribution of evolutionary lineages across regions and biomes. Despite decades of research, these patterns remain only partially understood, largely because they require integrating data and theory from multiple disciplines, including ecology, evolution, paleontology, biogeography, and climate science.
This problem is of direct importance for society because biodiversity is being lost at an unprecedented rate, and effective conservation and management strategies require understanding not only where species are today, but why they are there and how these patterns were assembled over millions of years. By identifying the processes that promote diversification, persistence, and extinction, and by quantifying how past climatic and geological changes have shaped present-day biodiversity, MAPAS contributes to a deeper and more predictive understanding of how biodiversity may respond to ongoing and future global change. This knowledge is essential for anticipating large-scale biodiversity reorganization, identifying regions of long-term evolutionary importance, and supporting evidence-based conservation planning in a rapidly changing world.
The overall objective of MAPAS is to develop an integrated, process-based framework to explain the origins and maintenance of global biodiversity patterns by explicitly linking ecological dynamics, evolutionary diversification, Earth history, and climate change. To achieve this, the project combines large-scale biodiversity data, fossil information, paleoclimatic reconstructions, and advanced modeling approaches to reconstruct past dynamics, test competing hypotheses about diversification and dispersal, and identify the mechanisms underlying present-day patterns of biodiversity. More broadly, MAPAS aims to move beyond purely descriptive or correlative approaches and provide a mechanistic, historically informed understanding of the processes that shape the diversity of life on our planet.
This problem is of direct importance for society because biodiversity is being lost at an unprecedented rate, and effective conservation and management strategies require understanding not only where species are today, but why they are there and how these patterns were assembled over millions of years. By identifying the processes that promote diversification, persistence, and extinction, and by quantifying how past climatic and geological changes have shaped present-day biodiversity, MAPAS contributes to a deeper and more predictive understanding of how biodiversity may respond to ongoing and future global change. This knowledge is essential for anticipating large-scale biodiversity reorganization, identifying regions of long-term evolutionary importance, and supporting evidence-based conservation planning in a rapidly changing world.
The overall objective of MAPAS is to develop an integrated, process-based framework to explain the origins and maintenance of global biodiversity patterns by explicitly linking ecological dynamics, evolutionary diversification, Earth history, and climate change. To achieve this, the project combines large-scale biodiversity data, fossil information, paleoclimatic reconstructions, and advanced modeling approaches to reconstruct past dynamics, test competing hypotheses about diversification and dispersal, and identify the mechanisms underlying present-day patterns of biodiversity. More broadly, MAPAS aims to move beyond purely descriptive or correlative approaches and provide a mechanistic, historically informed understanding of the processes that shape the diversity of life on our planet.
The MAPAS project has produced a coherent and high-impact body of work demonstrating that deep-time climatic and physiological constraints can be reconstructed and used to predict large-scale biogeographic responses to climate change. This is exemplified by the papers “100 million years of turtle paleoniche dynamics enable the prediction of latitudinal range shifts in a warming world” (Current Biology) and “Early Jurassic origin of avian endothermy and thermophysiological diversity in dinosaurs” (Current Biology), as well as “Climate drivers and palaeobiogeography of lagerpetids and early pterosaurs” (Nature Ecology & Evolution), which together show how paleoclimate and physiology jointly constrain distributions across hundreds of millions of years. In parallel, the project has demonstrated that long-term historical climate fragmentation, rather than present-day climate alone, explains mammal biogeography and diversity patterns, as shown in “Vrba was right: Historical climate fragmentation, and not current climate, explains mammal biogeography” (Global Change Biology), “Classic hypotheses of area, time, and climatic stability fall short in explaining high tropical species richness” (Journal of Biogeography), and “Future palaeontologists will detect current mammal latitudinal biodiversity gradient” (Global Ecology and Biogeography).
A second major line of results concerns the limits and biases of the fossil and historical record, and their consequences for macroevolutionary inference. The paper “Silent past: Biogeographic gaps in the Cenozoic fossil archive” (Palaeogeography, Palaeoclimatology, Palaeoecology) quantifies, for the first time, how entire regions and biomes are systematically missing from the fossil record, while “The structure of the end-Cretaceous dinosaur fossil record in North America” (Current Biology) and “Mind the uncertainty: Global plate model choice impacts deep-time palaeobiological studies” (Methods in Ecology and Evolution) show that both sampling biases and paleogeographic uncertainty fundamentally affect deep-time biodiversity reconstructions. Complementarily, the project delivered key community resources such as palaeoverse (Methods in Ecology and Evolution), Wallace 2 (Ecography), which now provide essential infrastructure for reproducible macroecological and paleobiological research.
A third major achievement of MAPAS is the explicit integration of ecology, evolution, and Earth system processes. This includes demonstrating that physiological and ecological innovations have immediate demographic and macroevolutionary consequences, as shown in “C₄ photosynthesis provided an immediate demographic advantage to populations of the grass Alloteropsis semialata” (New Phytologist) and “The division of food space among mammalian species on biomes” (Ecography). Finally, diversification dynamics across major clades and systems were addressed in works such as “Do marine mammals diversify more slowly than non-marine mammals?” (Journal of Biogeography) and multiple studies linking climate change, biodiversity, and early human dispersals (e.g. Ecography, Palaeogeography, Palaeoclimatology, Palaeoecology, Journal of Paleolithic Archaeology). Together, these results show that MAPAS has delivered a genuinely integrative, process-based understanding of how global biodiversity patterns emerge, are recorded, and are reshaped through deep time and into the present.
A second major line of results concerns the limits and biases of the fossil and historical record, and their consequences for macroevolutionary inference. The paper “Silent past: Biogeographic gaps in the Cenozoic fossil archive” (Palaeogeography, Palaeoclimatology, Palaeoecology) quantifies, for the first time, how entire regions and biomes are systematically missing from the fossil record, while “The structure of the end-Cretaceous dinosaur fossil record in North America” (Current Biology) and “Mind the uncertainty: Global plate model choice impacts deep-time palaeobiological studies” (Methods in Ecology and Evolution) show that both sampling biases and paleogeographic uncertainty fundamentally affect deep-time biodiversity reconstructions. Complementarily, the project delivered key community resources such as palaeoverse (Methods in Ecology and Evolution), Wallace 2 (Ecography), which now provide essential infrastructure for reproducible macroecological and paleobiological research.
A third major achievement of MAPAS is the explicit integration of ecology, evolution, and Earth system processes. This includes demonstrating that physiological and ecological innovations have immediate demographic and macroevolutionary consequences, as shown in “C₄ photosynthesis provided an immediate demographic advantage to populations of the grass Alloteropsis semialata” (New Phytologist) and “The division of food space among mammalian species on biomes” (Ecography). Finally, diversification dynamics across major clades and systems were addressed in works such as “Do marine mammals diversify more slowly than non-marine mammals?” (Journal of Biogeography) and multiple studies linking climate change, biodiversity, and early human dispersals (e.g. Ecography, Palaeogeography, Palaeoclimatology, Palaeoecology, Journal of Paleolithic Archaeology). Together, these results show that MAPAS has delivered a genuinely integrative, process-based understanding of how global biodiversity patterns emerge, are recorded, and are reshaped through deep time and into the present.
The MAPAS project has gone beyond the state of the art by moving from mainly descriptive or correlative analyses of biodiversity patterns to a genuinely process-based, historically informed framework that integrates paleoclimate, paleogeography, physiology, and ecology. It has shown that deep-time climatic and biological constraints can be quantitatively reconstructed and used to explain and predict large-scale biogeographic patterns, while also demonstrating how biases and uncertainties in the fossil record and paleogeographic reconstructions fundamentally affect macroevolutionary inference.