Category: Articles

06/01/202318/01/2023 michelaleonardi Articles, Research

pastclim v. 1.2 and paper

pastclim, our R package to easily access and use paleoclimatic reconstructions has now been updated to version 1.2. Moreover, is now out in Ecography the paper describing it:

Michela Leonardi, Emily Y. Hallett, Robert Beyer, Mario Krapp, Andrea Manica
pastclim 1.2: an R package to easily access and use paleoclimatic reconstructions
Ecography, First published: 05 January 2023 https://doi.org/10.1111/ecog.06481

Here is a list of what is new compared to the preprint:

pastclim is now on CRAN: https://cran.r-project.org/web/packages/pastclim/index.html;
We have added functions to crop based on an extent or a mask, and to randomly sample points across space and/or time;
We added a cheatsheet summarising the main functions;
A new vignette shows how to work with custom data and how to add them to the package in order for them to be available for all users.

Here is a table summarising the functions used in the package

Download the data
get_data_path()	Retrieve the path in which pastclim automatically stores the data
set_data_path()	Store the data in a custom path
download_dataset()	Download a whole dataset (all variables available)
get_vars_for_dataset() Download variables of choice for a given dataset	Download variables of choice for a given dataset
get_downloaded_datasets()	Summary of the downloaded variables
get_time_steps()	List of time steps available in a given dataset
Get climate for locations or regions
location_slice()	Get the climate for given locations (by coordinates and age)
location_series()	Get time series of the climate for given locations
region_slice()	get the climate for a given region in a given time step
sample_region_slice()	sample a given number of points from the climate of a region
region_series()	get the time series of the climate for a given region
sample_region_series()	sample a given series of points from the time series of a region
Working with biomes and ice sheets
get_biome_classes()	legend of the ‘biome’ categorical variable, when available
get_ice_mask()	get a mask with the extent of the ice sheets for a given time step
get_land_mask()	get a mask with the extent of the land masses for a given time step
Vignettes
vignette(“pastclim_overview”, package = “pastclim”)	overview of pastclim
vignette(“custom_datasets”, package = “pastclim”)	how to add a new dataset to pastclim
vignette(“available_datasets”, package = “pastclim”)	list of datasets available

More info:

website: https://evolecolgroup.github.io/pastclim/index.html
manual: https://rdrr.io/github/EvolEcolGroup/pastclim/
GitHub repository: https://github.com/EvolEcolGroup/pastclim
CRAN: https://cran.r-project.org/web/packages/pastclim/index.html
vignette: https://evolecolgroup.github.io/pastclim/articles/a0_pastclim_overview.html
cheatsheet: evolecolgroup.github.io/pastclim/pastclim_cheatsheet.pdf

If something does not work

You can raise an issue here

29/09/202223/01/2023 michelaleonardi Articles, Research

The impact of the Last Glacial Maximum on European ungulates

It is now out in Communications biology the article that I have written with Andrea Manica (Cambridge), Francesco Boschin e Paolo Boscato (Siena).

Michela Leonardi, Francesco Boschin, Paolo Boscato & Andrea Manica
Following the niche: the differential impact of the last glacial maximum on four European ungulates
Communications Biology volume 5, Article number: 1038 (2022)

What happened to temperate ungulates in Europe during the climatic fluctuations that have affected the last 50,000 years? To answer this question we compiled a database of radiocarbon dates associated with remains of horses, aurochs, deer and wild boars dated between 47,000 and 7,500 years ago (so as to exclude domesticated individuals).

We then developed a new method to reconstruct their (realised) ecological niche, while also testing for changes through time.

Analysing our data we found that all four species changed their niche, mainly during the Last Glacial Maximum (LGM) or shortly after, in a pattern consistent with individual habitat preferences. The distribution of horses and deer (cold-adapted species) spread eastwards until the LGM, while aurochs and wild boar are restricted to Central and Western Europe. The four potential distributions became more similar from the LateGlacial (but it does not imply the same about their preferences).

In more general terms, with this study we demonstrate that even large species, with long generation times, can change their niche in the course of a few thousand years. This must suggest extreme caution when assuming that the ecological niche remains constant both when reconstructing the past and when forecasting the future.

And, if you got this far into this commentary, here is a little surprise for you!

Article

Abstract

Predicting the effects of future global changes on species requires a better understanding of the ecological niche dynamics in response to climate; the large climatic fluctuations of the last 50,000 years can be used as a natural experiment to that aim. Here we test whether the realized niche of horse, aurochs, red deer, and wild boar changed between 47,000 and 7500 years ago using paleoecological modelling over an extensive archaeological database. We show that they all changed their niche, with species-specific responses to climate fluctuations. We also suggest that they survived the climatic turnovers thanks to their flexibility and by expanding their niche in response to the extinction of competitors and predators. Irrespective of the mechanism behind such processes, the fact that species with long generation times can change their niche over thousands of years cautions against assuming it to stay constant both when reconstructing the past and predicting the future.

23/06/202131/03/2023 michelaleonardi Articles, Research

Genetics and ecology do not agree in reconstructing how birds reacted to past climate changes

A new paper in which I took part is now available in Molecular Ecology

Eleanor F. Miller, Rhys E. Green, Andrew Balmford, Pierpaolo Maisano Delser, Robert Beyer, Marius Somveille, Michela Leonardi, William Amos, Andrea Manica
Bayesian Skyline Plots disagree with range size changes based on Species Distribution Models for Holarctic birds
Molecular Ecology, Volume 30, Issue 16 August 2021 Pages 3993-4004

We analysed more than 100 species of Holarctic birds finding that genetics and ecology do not agree in reconstructing how more they reacted to past climatic fluctuations.

Why should we care? The reconstructions compared in our paper (one based on genetic data, the other on ecological modelling) are widely used to assess how well species can react to the ongoing climate emergency.

In our study, we show that when we systematically compare them for a lot of species they tend to tell us quite different stories. This does not mean that they are wrong: different methods are based on different assumptions, and each of them is likely to be missing a small but significant part of the whole story.

So, when we use these methods, the key is interdisciplinarity: integrating into the analyses different lines of evidence help tackle these limitations and get more reliable results.

Article

Abstract

During the Quaternary, large climate oscillations impacted the distribution and demography of species globally. Two approaches have played a major role in reconstructing changes through time: Bayesian Skyline Plots (BSPs), which reconstruct population fluctuations based on genetic data, and Species Distribution Models (SDMs), which allow us to back-cast the range occupied by a species based on its climatic preferences. In this paper, we contrast these two approaches by applying them to a large data set of 102 Holarctic bird species, for which both mitochondrial DNA sequences and distribution maps are available, to reconstruct their dynamics since the Last Glacial Maximum (LGM). Most species experienced an increase in effective population size (N_e, as estimated by BSPs) as well as an increase in geographical range (as reconstructed by SDMs) since the LGM; however, we found no correlation between the magnitude of changes in N_e and range size. The only clear signal we could detect was a later and greater increase in N_e for wetland birds compared to species that live in other habitats, a probable consequence of a delayed and more extensive increase in the extent of this habitat type after the LGM. The lack of correlation between SDM and BSP reconstructions could not be reconciled even when range shifts were considered. We suggest that this pattern might be linked to changes in population densities, which can be independent of range changes, and caution that interpreting either SDMs or BSPs independently is problematic and potentially misleading.

10/07/202031/03/2023 michelaleonardi Articles, Research

Climate shaped how Neolithic farmers and European hunter-gatherers interacted after a major slowdown from 6,100 BCE to 4,500 BCE

It just came out in Nature Human Behaviour a new paper to which I collaborated: Climate shaped how Neolithic farmers and European hunter-gatherers interacted after a major slowdown from 6,100 BCE to 4,500 BCE. The article is behind paywall, but there is a read-only version, and the publisher added the full text in Researchgate.

The Neolithic transition in Europe was driven by the rapid spread of Near Eastern farmers who, over a period of 3,500 years, brought food production to the far corners of the continent. However, this wave of expansion was far from homogeneous, with a marked slowdown observed at higher latitudes, which could be related to the different climatic conditions encountered by Neolithic farmers as they moved.

We tested this hypothesis. First, we calculated the expansion routes in the various areas using a large database collating archaeological dates of the first arrival of agriculture throughout Europe. We have identified four of them, shown in the image below.

The four Neolithic expansion routes identified via radiocarbon dates associated with the first appearance of agriculture in the various areas

Along three of these routes, we observed a slowdown (thicker lines in the image) where the value of Growing Degrees Days (reflects the quality of the growing season) exceeds a certain threshold (light green in the map). This suggests that crops that originated in the Near East may have struggled to grow in harsher climatic conditions, not allowing Neolithic populations to produce enough to support population increase and/or expansion.

Furthermore, the study of ancient DNA shows us that in conjunction with the same threshold in growing degree days, the level of admixture between farmers and hunter-gatherers increases, suggesting that unreliable harvests in these regions may have favoured the contact between the two groups.

Lia Betti, Robert M. Beyer, Eppie R. Jones, Anders Eriksson, Francesca Tassi, Veronika Siska, Michela Leonardi, Pierpaolo Maisano Delser, Lily K. Bentley, Philip R. Nigst, Jay T. Stock, Ron Pinhasi & Andrea Manica

Climate shaped how Neolithic farmers and European hunter-gatherers interacted after a major slowdown from 6,100 BCE to 4,500 BCE

The Neolithic transition in Europe was driven by the rapid dispersal of Near Eastern farmers who, over a period of 3,500 years, brought food production to the furthest corners of the continent. However, this wave of expansion was far from homogeneous, and climatic factors may have driven a marked slowdown observed at higher latitudes. Here, we test this hypothesis by assembling a large database of archaeological dates of first arrival of farming to quantify the expansion dynamics. We identify four axes of expansion and observe a slowdown along three axes when crossing the same climatic threshold. This threshold reflects the quality of the growing season, suggesting that Near Eastern crops might have struggled under more challenging climatic conditions. This same threshold also predicts the mixing of farmers and hunter-gatherers as estimated from ancient DNA, suggesting that unreliable yields in these regions might have favoured the contact between the two groups.

Nat Hum Behav (2020). https://doi.org/10.1038/s41562-020-0897-7

31/05/201919/02/2023 michelaleonardi Articles, Research

Tracking five millennia of horse management with extensive ancient genome time series

A herd of Kazakh horses in the Pavlodar region of Kazakhstan in August 2016. Credit: Ludovic Orlando — A herd of Kazakh horses in the Pavlodar region of Kazakhstan in August 2016.
Credit: Ludovic Orlando

A new paper to which I collaborated just came out, “Tracking five millennia of horse management with extensive ancient genome time series“, which is the result of a huge collaboration between more than a hundred scientists from many different research centres around the world. The lead authors are Antoine Fages, Kristian Hanghøj and Naveed Khan, and the senior author Ludovic Orlando (University of Toulouse and University of Copenhagen).

Antoine Fages, Kristian Hanghøj, Naveed Khan, Charleen Gaunitz, Andaine Seguin-Orlando, Michela Leonardi, [116 more authors] and Ludovic Orlando

Tracking five millennia of horse management with extensive ancient genome time series

Highlights

Two now-extinct horse lineages lived in Iberia and Siberia some 5,000 years ago
Iberian and Siberian horses contributed limited ancestry to modern domesticates
Oriental horses have had a strong genetic influence within the last millennium
Modern breeding practices were accompanied by a significant drop in genetic diversity

Horse domestication revolutionized warfare and accelerated travel, trade, and the geographic expansion of languages. Here, we present the largest DNA time series for a non-human organism to date, including genome-scale data from 149 ancient animals and 129 ancient genomes (≥1-fold coverage), 87 of which are new. This extensive dataset allows us to assess the modern legacy of past equestrian civilizations. We find that two extinct horse lineages existed during early domestication, one at the far western (Iberia) and the other at the far eastern range (Siberia) of Eurasia. None of these contributed significantly to modern diversity. We show that the influence of Persian-related horse lineages increased following the Islamic conquests in Europe and Asia. Multiple alleles associated with elite-racing, including at the MSTN “speed gene,” only rose in popularity within the last millennium. Finally, the development of modern breeding impacted genetic diversity more dramatically than the previous millennia of human management.

Cell, Volume 177, Issue 6, 30 May 2019, Pages 1419-1435.e31
DOI: https://doi.org/10.1016/j.cell.2019.03.049