Juan David Carrillo Sanchez
SNSF Postdoc
Research Associate SNSF
Department of Biology
Biography
My main scientific goal is to understand the drivers and mechanisms that generate and erode biodiversity across space and time. I am interested in elucidating the relationships between i) biotic interactions and ii) abiotic factors (e.g., environmental changes) and changes of diversification, migration, and morphological variation. To achieve this goal, I used an interdisciplinary approach combining data from fossil and living organisms to study changes in diversity, in the distribution of species, and in their morphological evolution through time. I am also engaged in communicating science to society and increasing awareness of evolution and biodiversity.
Research and publications
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Books
4 publications
Plioceno , in Hace Tiempo 2nd Edition
Juan D. Carrillo, Federico Moreno (2023) | Book chapter -
Journal Articles
26 publications
Southernmost record of Megadolodus (Litopterna, Proterotheriidae, Megadolodinae) from the late Middle Miocene of Fitzcarrald, Peruvian Amazonia, and mesowear analysis of diet in megadolodine litopterns
Journal of Vertebrate Paleontology (2024) | Journal articleChallenges in estimating species' age from phylogenetic trees
Global Ecology and Biogeography (2024) | Journal articleThe Clade Replacement Theory: a framework to study age-dependent extinction
Journal of Evolutionary Biology (2024) | Journal articleEvolution of Amazonian biodiversity: A review
Acta Amazonica (2024) | Journal article -
Other publications
12 publications
3D models related to the publication: New remains of Neotropical bunodont litopterns and the systematics of Megadolodinae (Mammalia: Litopterna)
Juan David Carrillo, Catalina Suarez, Aldo Benites-Palomino, Andrés Vanegas, Andrés Link, Aldo F. Rincón, Javier Luque, Siobhán B Cooke, Melissa Tallman, Guillaume Billet, (2023) | Data set -
Pre-prints
2 publications
Challenges in estimating species age from phylogenetic trees
Rachel C.M. Warnock, Carlos Calderon del Cid, Sr., Torsten Hauffe, Juan D. Carrillo, Daniele Silvestro, Rachel C. M. Warnock, Carlos Calderón del Cid, (2023) | PreprintDecoupled diversity and disparity after faunistic turnover in caviomorph rodents
Juan D. Carrillo, María Fernanda Torres Jímenez, Francisco J Urrea-Barreto, Alexandre Antonelli, Christine Bacon, Søren Faurby, Daniele Silvestro, (2023) | Preprint -
Research projects
Elucidating the effect of past climatic changes on species abundances in the tropics
Status: CompletedStart 01.08.2022 End 31.07.2024 Funding SNSF Open project sheet Fossils provide unique data to understand the biotic and abiotic drivers of changes in community composition and diversification in geologic time. Palaeobiologists have developed models and methods to estimate the rates of speciation and extinction accounting for biases in fossil sampling and preservation. However, to date, there are not models to estimate species abundances (the estimated number of individuals per species) from the fossil record. The incorporation of data from species abundances in macroevolutionary models would provide a better understanding of the dynamics and causes of speciation and extinction, and could reveal previously undetected effects of past environmental changes in biological communities. The study of changes in species abundances through time could also clarify the relationship between species abundances and longevity (the lifespan of a species). Species longevity is traditionally studied in macroevolution by looking at the times of origination and extinction. It has been proposed that under constant ecological conditions, the probability of extinction does not increase or decrease during the life-span of a species. However, little is known about the relationship between species longevity and abundances. To establish such relationship could provide links between microevolutionary and macroevolutionary research programs. In this project, I will address a major problem in macroevolution by developing new models to estimate changes in species abundances through time. I will apply these novel methods in the exceptionally complete dataset of fossil mammals to: (1) understand the effect of the Miocene global warming and subsequent cooling in the community structure of mammals from a tropical ecosystem, and (2) evaluate the relationship between species abundances and longevity. The Miocene (23 – 5.3 million years [Ma]) represents a period when the biota and palaeogeography were similar to modern, but extreme climatic changes occurred. The Miocene warming was a global climatic event that occurred between ca. 17-14 Ma and was followed by a short period of cooling. Despite the increasing understanding of past climates, there is a gap of knowledge on how tropical ecosystems (which record the highest levels of biodiversity today) were affected by past global warmings. The fossil fauna of La Venta in Colombia, South America, is the most fossil-rich fauna of the tropics representing a high diversity of land animals that inhabited an ancient tropical forest between ca. 19 -11 Ma. La Venta offers a unique opportunity to understand how the Miocene climatic changes affected biotic communities in in the tropics. This project will result in substantial scientific progress in the fields of palaeobiology and macroevolution. It will provide a major methodological advance by developing new models and methods to estimate species abundances from fossils. In addition, it will clarify how the community composition and species abundances of tropical mammals were affected during the Miocene climatic changes. Finally, it will establish the relationship between species abundances, and longevity, potentially providing links between micro and macroevolutionary research. Unravelling the effects of the Miocene global warming event in the tropics
Status: CompletedStart 01.08.2021 End 31.07.2022 Funding SNSF Open project sheet The Miocene climatic optimum (MCO) is a global warming event that occurred between 17-14 million years ago and was followed by a relative short period of cooling known as the Miocene climatic transition (MCT). The MCO is comparable in magnitude to the present and predicted future warming. In the ongoing climate change, it is apparent that temperature is increasing more rapidly at high latitudes than in the tropics. However, it is unclear whether tropical regions were also more resilient to rapid climate change in the past. While paleotemperature estimates are available from high latitudes, the effect of the MCO and the subsequent MCT in the tropics remains unknown, due to gaps in Miocene data and low fossil preservation rates in tropical regions in general. Furthermore, available paleoclimatic models do not provide a robust replacement to empirical data to understand the past climate change in the tropics. In this project, I will evaluate the magnitude of climate and environmental change at tropical latitudes during MCO and subsequent cooling period. Morphological traits of fossil mammals can be used to infer the paleoclimate and the traditional approach used linear regressions. I will build upon the most recent developments in machine learning to reconstruct the paleoclimate and paleoenvironment in the tropics using the mammal fossil record. I will use a dataset of 12 functional traits of extant herbivore mammals to train a neural network model for paleoenvironmental analyses. Then, I will use a unique set of trait data of mammals from the La Venta site, the most fossil-rich locality in the Neotropics, to quantify changes precipitation, temperature and primary productivity across a 3-million-year long time frame that includes the transition from the MCO to the MCT. Current evidence suggests that the temperature in the tropics increased less than at higher latitudes during global warming events. I hypothesize that the temperature decrease in La Venta after the MCO was smaller than the ~7°C decrease inferred for temperate regions. This research has the potential to provide accurate estimates of the temperature and other climatic variables in the tropics during the peak of the MCO and the MCT. Furthermore, it will provide a new methodological approach for paleoenvironmental reconstructions using neural networks, which I expect to outperform the regression methods previously used for this task.