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Co-occurrence of mylodontid sloths and insights on their potential
distributions during the late Pleistocene
Luciano Varela ⁎,RichardA.Fariña
Sección Paleontología, Facultad de Ciencias, Universidad de la República, Iguá 4225, 11400 Montevideo, Uruguay
abstractarticle info
Article history:
Received 10 March 2015
Available online xxxx
Species distribution models (SDMs) for the last interglacial (LIG), theglobal last glacial maximum (LGM) and the
Holocene climatic optimum (HCO) were generated for three extinct South American Pleistocene mylodontid
giant sloths, Glossotherium robustum,Lestodon armatus and Mylodon darwinii. They are recorded co-occurring
in some localities including Arroyo del Vizcaíno site (AdV) in Uruguay. Co-occurrence records were studied
based on the overlap of their generated areas of potential distributions, and compared with the available
biome reconstructions of South America during theLGM to analyze theirdistribution patterns, ecological require-
ments and possible interactions between them. Our results suggest thatthese sloths could have co-existed main-
ly in the Chaco-Paraná Basin and the plains in the Río de la Plata area. Areas of highsuitability were observed for
submerged parts of the continental shelf that were exposed during the LGM showing an overall increase in po-
tential habitat compared to the LIG and HCO. This suggests that there was a drastic reduction in total available
areas of preferred habitat at the end of the Pleistocene. The co-occurrence of these sloths at the AdV site suggests
the presence of vegetation indicative of mainlyopen, cold to temperate habitats but with mixed patchestypical of
humid climates.
© 2015 University of Washington. Published by Elsevier Inc. All rights reserved.
Keywords:
Ground sloths
Glossotherium
Lestodon
Mylodon
Xenarthra
Species distribution models
Ecological niche modeling
Paleogeography
Last glacial maximum
Quaternary
Introduction
Species distribution models and the South American megafauna
Species distribution models (SDMs)represent an array of techniques
used to model the potential distributions of species from their occur-
rence records and the environmental (mainly climatic) conditions in
those locations (Guisan and Zimmermann, 2000; Guisan and Thuiller,
2005). Among those techniques, maximum entropy approaches like
the one implemented in MAXENT software package (Phillips and
Dudik, 2008), have become widely used because of the ability to use
presence-only data, its robustness to limited amounts of samples and
its higher predictive accuracy when compared to other methods
(see Franklin, 2010). Species distribution models have been used re-
cently to study past and potential future distributions of extant species
(Torres et al., 2013), to better understand speciation processes
(Raxworthy et al., 2008; Blair et al., 2013), the existence of ecologi-
cal processes like competitive exclusion or niche differentiation
(Gutiérrez et al., 2014), and to evaluate the existence of climate refugia
(Waltari et al., 2007). In particular, Mumladze (2014) used species co-
occurrence records and modeled potential co-occurrence areas to
study the importance of interspecific competition in the distribution
patterns of two gastropods. These methods have been increasingly
used in paleobiogeography studies (see Varela et al., 2011; Franklin
et al., 2015).
The South American megafauna, an impressive assortment of giant
mammals that went extinct at the end of the Pleistocene and one of
the main sources for Darwin's ideas, has received considerable attention
in the past decades in regard to their habits and paleoecological prefer-
ences (Fariña et al., 2013). Within the South American Pleistocene
megafauna the giant sloths are of particular interest due to their diver-
sity, very large size and lack of modern analogs, including studies of
their evolution (Gaudin, 2004), ecology (Fariña, 1996; Fariña and
Blanco, 1996; Bargo et al., 2000, 2006a, 2006b; Vizcaíno et al., 2001;
Bargo and Vizcaíno, 2008) and extinction (Lessa and Fariña, 1996;
Barnosky and Lindsey, 2010; Hubbe et al., 2013). Lately, some studies
have focused on the biogeography of the megafauna. Gallo et al.
(2013), for example, used the panbiogeographical method of trackanal-
ysis and concluded that some current distributional patterns already
existed in the Pleistocene and that those patterns were highly influenced
by the main plant communities. Lima-Ribeiro and Diniz-Filho (2012)
and Dantas et al. (2013) studied past potential distributions of Smilodon
populator and Notiomastodon platensis, respectively, using SDMs and
showed the reduction of suitable areas at the beginning of the Holocene.
In particular, Lima-Ribeiro et al. (2012) analyzed the potential distribu-
tions of Eremotherium laurillardi and Megatherium americanum during
the Late Pleistocene and showed a drastic reduction in potentially suit-
able areas for both species at the end of the Pleistocene.
Quaternary Research xxx (2015) xxx–xxx
⁎Corresponding author.
E-mail address: luciano.lvr@gmail.com (L. Varela).
YQRES-03695; No. of pages: 9; 4C:
http://dx.doi.org/10.1016/j.yqres.2015.11.009
0033-5894/© 2015 University of Washington. Published by Elsevier Inc. All rights reserved.
Contents lists available at ScienceDirect
Quaternary Research
journal homepage: www.elsevier.com/locate/yqres
Please cite this article as: Varela, L., Fariña, R.A., Co-occurrence of mylodontid sloths and insights on their potential distributionsduring the late
Pleistocene, Quaternary Research (2015), http://dx.doi.org/10.1016/j.yqres.2015.11.009
We apply Paleo-Species Distribution Models (PSDMs)to predict the
co-occurrence of three species of mylodontid ground sloths: Lestodon
armatus,Mylodon darwinii and Glossotherium robustum.L. armatus and
G. robustum are rather similar morphologically, with bulk feeding habits
having been proposed (Bargo and Vizcaíno, 2008) and differing primar-
ily in their body sizes at ~ 4000 kg for L. armatus (Fariña et al., 1998;
Bargo et al., 2000), and between 750 and 1500 kg for the gracile and ro-
bust, possibly sexually dimorphic, forms of G. robustum, respectively
(Bargo et al., 2000; Christiansen and Fariña, 2003). In contrast,
M. darwinii was inferred to have been a selective feeder (Bargo and
Vizcaíno, 2008) and had a body mass between 1000 and 2000 kg
(Christiansen and Fariña, 2003).
The Arroyo Del Vizcaíno site
The Arroyo del Vizcaíno site (Fariña et al., 2014a), near the town of
Sauce, Canelones, Uruguay (34°37′S, 56°02′W, 25 m above mean sea
level [asl]) has yielded over onethousand remains of at least 27 individ-
uals mostly belonging to megafaunal species. About 95% of those re-
mains have been assigned to the giant sloth L. armatus,butM. darwinii
and G. robustum have been found, as well as glyptodonts (Glyptodon
clavipes,Panochthus tuberculatus and Doedicurus clavicaudatus)and
other Pleistocene species including Toxodon platensis, the fossil horses
Equus (Amerhippus)neogeus and Hippidionprincipale, a deer, a probosci-
dean and the saber-toothed felid S. populator.
This site, which has beendated to ~30 ka on the basis of radiocarbon
ages obtained from samples of bone and wood (Fariña and Castilla,
2007; Fariña et al., 2014a), is important as it may provide evidence for
early human presence in South America (Fariña et al., 2014a; Fariña,
2015). The climatic conditions and sea level were similar to those
experienced during the global last glacial maximum (LGM) several
millennium later at ~26.5 to 19.0 ka (Clark et al., 2009).
Material and methods
Species occurrences and paleoclimate data
Data on L. armatus,G. robustum or M. darwinii occurrences were ob-
tained from a review of the literature and the Paleobiology Database
(http://paleobiodb.org). Sixty-one localities containing these Pleisto-
cene taxa occurin South America (Fig. 1). Species occurrence at these lo-
calitiesand their assigned ages are listed in Table 1. Although systematic
revisions might be needed to determine the validity of some species
within these genera, we considered Mylodon and Lestodon as monospe-
cific genera according to Esteban (1996) and Czerwonogora and Fariña
(2013), respectively, and G. robustum as the only valid species for the
Pleistocene according to McAfee (2009). Therefore, all the recorded
occurrences of the genera for the Pleistocene were considered as
belonging to the mentioned species.
A General Circulation Model (GCM) reconstructing the paleoclimate
for the last interglacial (LIG) at ~130 to 115 ka (Dahl-Jensen et al.,
2013), the LGM, and Holocene climatic optimum (HCO) at ~8 to
5.5 ka (Baker et al., 2001), with a spatial resolution of 30′for LIG and
2.5′for the LGM and HCO, were acquiredfrom the WorldClim database
(Hijmans et al., 2005;http://www.worldclim.org/). LIG data were
upscaled by interpolation to the same resolution as the LGM and HCO
for projection purposes (see Franklin et al., 2013). Climate data are cal-
ibrated and statistically downscaled from the PMIP2 LGM data set
(Braconnot et al., 2007;http://pmip2.lsce.ipsl.fr/). The 19 bioclimatic
variables available in the database were used in the analysis, which in-
cludes annual mean temperature, mean diurnal temperature range,
isothermality, temperature seasonality, maximum temperature of
warmest period, minimum temperature of coldest period, temperature
annual range, mean temperature of wettest quarter, mean temperature
of driest quarter, meantemperature of warmest quarter, meantemper-
ature of coldest quarter, annual precipitation, precipitation of wettest
period, precipitation of driest period, precipitation seasonality, precipi-
tation of wettest quarter, precipitation of driest quarter, precipitation of
warmest quarter and precipitation of coldest quarter.
Paleo-Species Distribution Models
The potential distribution of the three studied sloths was recon-
structed by ecological niche modeling using the software MAXENT v.
3.3.3k (Phillips and Dudik, 2008). MAXENT utilizes a maximum entropy
approach to species distribution modeling with presence-only data
(Phillips et al., 2006). Paleo-Species Distribution Models (PSDMs)
were constructed for the LGM from occurrence records between 13
and 40 ka (Table 1), assuming that the species were also present during
the LGM. The obtained model was then projected to predict the species
potential distribution during the HCO and LIG (according to GCMs).
As high correlation is expected between many variables, an initial
run in MAXENT and a jackknife test were performed to identify vari-
ables with minimal or no contribution to the models. Those variables
were omitted and only a group of 6 significant variables were used in
the final models.We ran each model 100 times with a random subsam-
ple of 30% of the occurrences data set for model testing. Model perfor-
mance was evaluated using the area under curve (AUC) statistic. An
AUC value of 0.5 indicates a random prediction, whereas closer to 1
values indicate better predictive ability. A jackknife procedure was
used to assess the contribution of the variables used in the modeling
process. A qualitative evaluation was made by superimposing the
records not used for model training onto the obtained maps.
Finally, to generate binary distribution maps, two threshold options
where selected in MAXENT, i.e., “Equal training sensitivity plus specifici-
ty”(Higher threshold) and “Maximum training sensitivity plus specifici-
ty”(Lower threshold). These binary maps were used to calculate areas
of potential distribution during the LGM, HCO and LIG as well as areas
Figure 1. Records of Glossotherium robustum,Lestodon armatus and Mylodon darwiniiused
in this study.
2L. Varela, R.A. Fariña / Quaternary Research xxx (2015) xxx–xxx
Please cite this article as: Varela, L., Fariña, R.A., Co-occurrence of mylodontid sloths and insights on their potential distributionsduring the late
Pleistocene, Quaternary Research (2015), http://dx.doi.org/10.1016/j.yqres.2015.11.009
of overlap between the species. Areas of potential co-occurrence were
calculated by superimposing the potential distribution of the three spe-
cies using the software package QGIS (Quantum GIS Development
Team, 2014). In addition, two measures of environmental-niche similari-
ty introduced by Warren et al. (2008) were used to quantitatively address
the potential differentiation in these sloths based on SDMs. One based on
Schoener's (1968) statistic for niche overlap (D)andtheother(I)derived
from Hellinger distance (van der Vaart, 1998). ENMTools v. 1.4.4 (Warren
et al., 2010) package was used to perform these analyses.
Results
Paleo-Species Distribution Models
G. robustum
G. robustum PSDMs for the LGM, LIG and HCO are shown in
Figures 2A–C. An acceptable AUC value of 0.81 was obtained for the
model from the random test subsample indicating a good predicting ca-
pacity. Jackknife analysis showed that the variables having the highest
Table 1
Localities with records of sloths used in this study.
Locality (reference) Species (number of sites) Age
Glossotherium robustum
(35)
Lestodon armatus
(19)
Mylodon darwinii
(20)
Agua de las Palomas (Esteban, 1988)X Late Pleistocene
Arequipa (Pujos and Salas, 2004)X Pleistocene
Arroyo Barrenechea (Ferrero, 2009)X Late Pleistocene (33–11 ka)
Arroyo Chelforó (Zurita et al., 2005)X Late Pleistocene (21–10 ka)
Arroyo del Vizcaíno (Fariña et al., 2014a) X X X Late Pleistocene (30 ka)
Arroyo Seco (Politis and Messineo, 2008)X Late Pleistocene (12 ka)
Arroyo Tapalque (Bargo et al., 1986) X X Late Pleistocene (21–10 ka)
Arroyo Toropí (Miño-Boilini et al., 2012) X X Late Pleistocene
Cavernes de Lagoa Santa (Hoffstetter, 1954)X Pleistocene
Cerro da Tapera (Pitana et al., 2013)X Late Pleistocene (13–11 ka)
Chuí Creek (Pitana et al., 2013) X X X Late Pleistocene (42–33 ka)
Curimatas (Paula Couto, 1980)X Pleistocene
Ensenada Creek (Brunetto et al., 2015) X X Late Pleistocene (120–60 ka)
Gral Bruguer/Riacho Negro (Hoffstetter, 1978) X X Pleistocene
Japones Cave (Salles et al., 2006)X Late Pleistocene/Holoecene
Joao Cativo —Site 2 (Paula Couto, 1980)X Pleistocene
La Brea —Talara (Pujos and Salas, 2004)X Late Pleistocene (14.4–13.6 ka)
La Huaca —Piura (Pujos and Salas, 2004)X Pleistocene
Las Cátedras (Marshall et al., 1984)X Pleistocene
La Postrera (Czerwonogora et al., 2011)X Late Pleistocene (11 ka)
Lower San José (Deschamps, 2013)X Middle Pleistocene
Luján (Tonni et al., 1985) X X Late Pleistocene (21–10 ka)
Muaco (Aguilera, 2006)X Late Pleistocene (16.3–14.3 ka)
Olivera (Moreno and Mercerat, 1891)X Late Pleistocene
Paso Otero (Martínez et al., 2013) X X X Late Pleistocene (21–10 ka)
Pernambuco —Lage Grande (Rolim, 1974)X Pleistocene
Pilar (Fucks et al., 2005)X Late Pleistocene (N40 ka)
Pintado (Ubilla and Alberdi, 1990) X X Late Pleistocene (43–12 ka)
Quebrada Pistud (Tomiati and Abbazzi, 2002)X Late Pleistocene (18–12 ka)
Sanga da Cruz Creek (Pitana et al., 2013)X Late Pleistocene (15–12 ka)
Santa Elina (Vialou, 2003)X Late Pleistocene (25–10 ka)
Taima - Taima (Rowlett and Mandeville, 1978)X Late Pleistocene (14–12 ka)
Taperoa (Paula Couto, 1980)X Pleistocene
Tarija (Boule and Thevenin, 1920), (Coltorti et al., 2007) X X Late Pleistocene (44–21 ka)
Touro Passo Creek (Pitana et al., 2013)X Late Pleistocene (16.5–11 ka)
Casil Quarry (Alvarenga et al., 2010) X Late Pleistocene (17.5 Ka)
Corrientes (Miño-Boilini et al., 2012) X Late Pleistocene (58–28 ka)
El Caño (Czerwonogora et al., 2011) X Late Pleistocene (12 ka)
Laguna Blanca (Zurita et al., 2010) X Middle/Late Pleistocene
Quequen Salado (Alberdi et al., 1989) X Late Pleistocene (21–10 ka)
San Antonio de Areco (Bargo et al., 2000) X Pleistocene
San Luis (Czerwonogora et al., 2011) X Late Pleistocene
Sr. Oscar Borba Ranch (Paula Couto, 1944) X Pleistocene
Upper Ribeira (Ghilardi et al., 2011) X Late Pleistocene
Arroyo Gutierrez (Perea, 1998) X Late Pleistocene (12 ka)
Cerro Soto (Alberdi et al., 1987) X Late Pleistocene/Holoecene
Cóndor Cave (Borrero and Martin, 2008) X Late Pleistocene (28.6 ka)
Cueva Chica (Martin et al., 2013) X Late Pleistocene (18–12 ka)
Cueva de los Chingues (Prevosti et al., 2003) X Late Pleistocene (13.4–13 ka)
Cueva del Lago Sofia4(Steele and Politis, 2009) X Late Pleistocene (13.4 ka)
Cueva del Medio (Nami and Nakamura, 1995) X Late Pleistocene (13 ka)
Cueva Fell (Alberdi et al., 1987) X Late Pleistocene (12.5 ka)
Cueva Mylodon (Alberdi et al., 1987) X Late Pleistocene (13.5 ka)
Dos Herraduras (Martin et al., 2013) X Late Pleistocene (12.6 ka)
El Membrillo (Seguel et al., 2010) X Late Pleistocene (13.5 ka)
El Palmar (Brandoni et al., 2010) X Late Pleistocene (80–13 ka)
Gruta del Indio (Long et al., 1998) X Late Pleistocene (30–10 ka)
Las Buitreras (Alberdi et al., 1987) X Late Pleistocene (N10 ka)
Pali Aike (Alberdi et al., 1987) X Holocene (8.6 ka)
Piedra Museo (Alberdi et al., 2001) X Late Pleistocene (13 ka)
Rio Anisacate (Tauber and Di Ronco, 2003) X Late Pleistocene (26 ka)
3L. Varela, R.A. Fariña / Quaternary Research xxx (2015) xxx–xxx
Please cite this article as: Varela, L., Fariña, R.A., Co-occurrence of mylodontid sloths and insights on their potential distributions during the late
Pleistocene, Quaternary Research (2015), http://dx.doi.org/10.1016/j.yqres.2015.11.009
gain when used in isolation were “Precipitation of Wettest Month”,
“Minimum Temperature of Coldest Month”,“Mean Temperature of
Wettest Quarter”and “Precipitation of Driest Month”(Table 2). While
“Precipitation of Wettest Month”was the variable that decreases the
gain the most when omitted (Table 2).
The predicted potential distribution during the LGM (Fig. 2B)
displayed a wide distribution for the species in South America. Areas
of high probability were obtained for the Chaco-Paraná Basin and the
Pampas, some zones in the Pacific coast of Chile, Peru and Ecuador,
the Caribbean coasts of Colombia and Venezuela, and the northeastern
intertropical region of Brazil. In all cases, high probability areas occur
on exposed areas of the continental shelf (now submerged) due to
lower sea level during LGM.
The model projection for the LIG (Fig. 2A) also showed high proba-
bility areas for the Chaco-Paraná Basin and the Pampas, an increase of
suitable areas in the Brazil's intertropical region and a decrease in the
Pacific and Caribbean coasts sites during the LGM. Also, theHCO projec-
tion (Fig. 2C) showed similar results to LIG, but with increased suitabil-
ity in tropical regions, particularly in the Amazon basin.
L. armatus
L. armatus PSDMs for the LGM, LIG and HCO are shown in
Figures 2D–F. Model predicting capacity was acceptable with an
AUC of 0.87. Variables that had the highest gain when used alone in-
cluded “Maximum Temperature of Warmest Month”,“Mean Tempera-
ture of Wettest Quarter”,“Precipitation of Wettest Month”and “Mean
Temperature of Driest Quarter”(Table 2). While “Precipitation of
Wettest Month”decreased the gain the most when omitted (Table 2).
The LGM predicted potential areas (Fig. 2E) showed a limited distri-
bution restricted principally to the Chaco-Paraná Basin and the Pampas.
Again, high probability zones are seen on exposed areas of the
continental shelf.
Similar results in the Chaco-Paraná Basin and the Pampas were ob-
tained for the LIG projection (Fig. 2D), although a decrease in extremely
high probability areas was also apparent. Moreover, there was a high
probability area in Patagonia. The projection for HCO (Fig. 2F) showed
comparable results to the LGM and LIG models, and a slight increase
in potential suitable areas in the Brazil intertropical region, the
Caribbean coast sites and the Amazon basin.
Figure 2. Potential distribution of Glossotheriumrobustum for (A) LIG,(B) LGM and (C) HCO, Lestodon armatusfor (D) LIG, (E) LGM and(F) HCO and Mylodon darwinii for (G) LIG, (H) LG M
and (I) HCO. Light green points represent records used for training while dark blue points represent records not related to the LGM or lack of precise stratigraphic control. (For interpre-
tation of the references to color in this figure legend, the reader is referred to the web version of this article.)
4L. Varela, R.A. Fariña / Quaternary Research xxx (2015) xxx–xxx
Please cite this article as: Varela, L., Fariña, R.A., Co-occurrence of mylodontid sloths and insights on their potential distributions during the late
Pleistocene, Quaternary Research (2015), http://dx.doi.org/10.1016/j.yqres.2015.11.009
M. darwinii
M. darwinii PSDMs for the LGM, LIG and HCO are shown in
Figures 2G–I. An AUC of 0.86 for the model was obtained indicating a
good predicting capacity. Environmental variables “Precipitation of Wet-
test Month”,“Mean Temperature of Coldest Quarter”,“Isothermality”
and “Mean Temperature of Driest Quarter”showed the highest gain
when used in isolation, while “Precipitation of Wettest Month”was the
variable that decreases the gain the most when excluded (Table 2).
The predicted suitable areas for LGM (Fig. 2H) indicated a high prob-
ability of occurrence of this species in Patagonia and Tierra del Fuego,
which has its limit in the northern part of the Pampas. An extension of
its distribution to the north is apparent for northern Chile and along
the Pacific coast of Peru and Ecuador, along with a region in the Andes
that forms a passage connecting the areas of its distribution. Results
show the Rio de la Plata region representing the northeastern edge of
the potential distribution during the LGM. Again, in all Patagonia and
Tierra del Fuego Atlantic coasts, high probability areas are apparent on
exposed areas of the continental shelf during the LGM.
The model projection for the LIG (Fig. 2G) displayed more concen-
trated areas in the southern part of the continent, although there was
not noticeable change along the Pacific coasts. The HCO projection
(Fig. 2I) showed a slight increase in suitability for the Pacific coasts
and the Brazilian Intertropical regions.
Areas of potential co-occurrence and niche overlap
Areas (in km
2
) of potential occurrence for each species andareas of
potential co-occurrence for the LGM, HCO and LIG for both higher and
lower thresholds are shown in Table 3. For the LGM (Fig. 3A), the
areas concentrated mainly in the south Chaco-Paraná Basin, the Pampas
and exposed areas of the continental shelf. Pairwise comparisons of
environment-niche similarity are shown in Table 4. Both statistics
showed good similarity between the three sloths (evenhigher between
Glossotherium and Lestodon), while less overlap for Lestodon and
Mylodon was evident.
Discussion and conclusions
Model results for the three studied species indicated acceptable AUC
values and good prediction capacity when superimposed with sites not
used for training. Different distribution patterns were predicted for the
sloths, although some areas of co-occurrence were observed for the
LGM, LIG and HCO. This is not unexpected if sloths had similar general
ecological preferences, particularly given that very large animals have
wide geographical ranges (Gaston and Blackburn, 1996; Olifiers et al.,
2004; Fernández and Vrba, 2005). This is also in accordance with the ex-
istence of co-occurrence records of these sloths during the LGM that
overlap well with our model (although there are no registered co-
occurrences for the LIG). Overall, G. robustum was present in 35 locali-
ties, L. armatus in 19 and M. darwinii in 20, with Glossotherium and
Lestodon co-occurring without Mylodon in 7 sites and Mylodon never
co-occurring with either of the other two species except when the
two are found together. Of note is that, in our models and in the fossil
record, the probability of finding Glossotherium and Lestodon together
is higher than either of these species being found with Mylodon.
The most important contributing environmental variables were par-
tially shared by the three models (Table 2). Of those, the precipitation of
the wettest month was present in the three cases and was the most im-
portant variable in Glossotherium and Mylodon and the third in Lestodon.
The other important variables were related mainly to temperature. In
the three models the probability of presence was favored by low
levels of precipitation during the wettest month, while Glossotherium
showed favorable probability of presence with higher precipitation dur-
ing the driest month. Also, relatively colder temperatures favored the
probability of presence of Mylodon, while relatively warmer tempera-
tures favored the presence of Glossotherium and Lestodon. These envi-
ronmental variables could be related to the preferred habitats often
proposed for these sloths. Late Pleistocene mylodontid sloths have
been inferred to have been open habitat dwellers and, as noted above,
assigned different dietary habits. Also, Mylodon has been traditionally
linked to colder habitats (Moore, 1978; Scillato-Yané et al., 1995) but
also thought to have been capable of great ecological tolerance based
on its wide latitudinal distribution and the paleoenvironmental condi-
tions purposed for the localities that have fossils of M. darwinii
(Brandoni et al., 2010). In comparison, Lestodon and Glossotherium are
associated with more temperate open habitats (Czerwonogora et al.,
2011), in particularthe latter genus, whichis present in the more north-
ern tropical zones in South America (Pitana et al., 2013). The association
of the studied species with open habitats is clear when comparing our
results with the Pleistocene biome reconstructions of Ray and Adams
Table 2
Most contributing bioclimatic variables for the species distribution models.
Jackknife analysis
Species Variables % contribution Train gain only Train gain without Test gain only Test gain without
Glossotherium robustum Precipitation of Wettest Month 64.5 0.4814 0.3484 0.5804 −0.1300
Min Temperature of Coldest Month 14.7 0.2251 0.7673 0.2474 0.5868
Mean Temperature of Wettest Q 11.1 0.0101 0.7670 −0.0092 0.4495
Precipitation of Driest Month 4.1 0.0432 0.7302 −0.2670 0.7688
Lestodon armatus Max Temperature of Warmest Month 45.6 0.8006 1.6300 0.9452 1.7442
Mean Temperature of Wettest Q 19.9 0.7495 1.4311 0.8054 1.4338
Precipitation of Wettest Month 19.3 0.0016 1.4052 0.0016 1.3536
Mean Temperature of Driest Q 9.4 0.2783 1.5813 0.2994 1.5070
Mylodon darwinii Precipitation of Wettest Month 36.4 0.8719 0.7978 0.9671 0.7874
Mean Temperature of Coldest Q 25.9 0.6707 0.9879 0.8471 0.9579
Isothermality 17.8 0.6636 0.9785 0.7801 0.9045
Mean Temperature of Driest Q 15.1 0.5514 0.9779 0.7144 0.9328
Table 3
Higher and lower threshold areas (in km
2
) of potential distribution of the three sloths as well as areas of potential co-occurrence for the LGM, LIG and HCO.
LIG LGM HCO
Species Higher Lower Higher Lower Higher Lower
Glossotherium robustum 3,251,111 2,998,489 3,081,649 2,149,913 2,395,868 1,995,191
Lestodon armatus 1,886,962 1,199,896 3,543,316 1,818,125 2,151,944 992,240
Mylodon darwinii 2,490,364 1,344,375 4,615,538 3,401,979 2,929,069 1,651,875
Overlap 588,941 116,336 894,444 419,131 536,892 150,729
5L. Varela, R.A. Fariña / Quaternary Research xxx (2015) xxx–xxx
Please cite this article as: Varela, L., Fariña, R.A., Co-occurrence of mylodontid sloths and insights on their potential distributions during the late
Pleistocene, Quaternary Research (2015), http://dx.doi.org/10.1016/j.yqres.2015.11.009
(2001),De Vivo and Carmignotto (2004),Mayle (2006) and Anhuf et al.
(2006) (Fig. 3).Also, the northern range limit of Mylodon coincides with
the southern limit of more tropical habitats on both biome reconstruc-
tions, while Lestodon's limited potential range seems to coincide with
areas of temperate grasslands or steppes. The limits of Mylodon to the
north and Lestodon to the south seem to define the areas of potential
co-occurrence of the three sloths and indicate the transition from tem-
perate to cold temperature climates.
The patterns of potential distribution obtained and the records of oc-
currence suggest the existence of niche partitioning in these species,
something already examined in morphological studies of sloths (Bargo
et al., 2006b; Bargo and Vizcaíno, 2008) and glyptodonts (Vizcaíno,
2000; Vizcaíno et al., 2011). This assumption is also suggested by our
environmental-niche similarity results, which support the stronger sim-
ilarity between Glossotherium and Lestodon feeding ecology in relation
to Mylodon. PSDMs, however, do not take into account biotic interac-
tions and, even if our model suggests niche partitioning over competi-
tive exclusion in these sloths based on the overlap of their potential
distribution and the existence of records of the three species in those
areas, interactions with other species should not be ruled out. Our
models, for example, predict highly suitable areas in the western
part of the Pampas for Lestodon but currently there are no known
occurrences of the species in this region. This may be because conditions
that did not permit fossilization or that the area has not been sufficiently
examined in detail. In contrast, late Pleistocene megatheriids,
Megatherium and Eremotherium, according to their occurrence records
have been related to temperate and more tropical climates, respectively
(Bargo and De Iuliis, 1999; De Iuliis et al., 2000), and lack co-occurrence
records, although some overlap in their potential distribution exists
(Nascimento, 2008; Lima-Ribeiro et al., 2012). The difference in the dis-
tribution of these sloths, as noted above, might be a consequence of
niche partitioning in mylodontid sloths, while competitive exclusion
could be interpreted in the case for megatheriids based on the lack of
sites in which the two species co-occur in the modeled regions of
their potential overlap.
In addition, our results are consistent with the isotope studies of in
Mylodon,Glossotherium and Lestodon bones from Patagonia, Buenos
Aires Province and Uruguay, respectively, which indicate a preference
for C3 vegetation in open environments similar to those in northern
Figure 3. (A) Higher andlower threshold areas of potential distribution for each sloth as well asareas of potential co-occurrence and sites with registered co-occurrence of the three
sloths. LGM biomes reconstruction (B) modified from Ray and Adams (2001) and (C) based on de Vivo and Carmignotto (2004),Mayle (2006),andAnhuf et al. (2006) and modified
from de Melo França et al. (2015).
Table 4
Environmental-niche similarity statistics for the studied sloths based on the generated
SDMs.
Comparison DI
Glossotherium–Lestodon 0.69 0.91
Glossotherium–Mylodon 0.66 0.91
Lestodon–Mylodon 0.61 0.88
6L. Varela, R.A. Fariña / Quaternary Research xxx (2015) xxx–xxx
Please cite this article as: Varela, L., Fariña, R.A., Co-occurrence of mylodontid sloths and insights on their potential distributions during the late
Pleistocene, Quaternary Research (2015), http://dx.doi.org/10.1016/j.yqres.2015.11.009
Patagonia today (Politis and Messineo, 2008; Czerwonogora et al., 2011;
Prevosti and Martin, 2013).
McDonald et al. (2013) studied the sloths co-occurrence records for
the Fairmead Landfill locality (Irvingtonian) in North America to ad-
dress the presence of different habitats in theregion based on the differ-
ent ecological requirements of the recorded sloths. This hypothesis was
in accordance with supplementary pollen and faunal diversity studies
at the site. Sites containing the three sloths in our study have been re-
corded but are rare (Fig. 3A). In addition to the AdV site, Mylodon,
Glossotherium and Lestodon co-occur at toscas del Río de la Plata present
from the Ensenadan Age, Early Pleistocene (Soibelzon et al., 2008)and
Paso Otero present from the late Pleistocene to Holocene (Martínez
et al., 2013) in Buenos Aires Province of Argentina, and in Chuí Creek
in Brazil (Pereira et al., 2012; Pitana et al., 2013). The faunal assemblage
of all of these sites is typical of arid to semi-arid open habitat that must
have been colder than today's climates. Onthe other hand, toscas del Río
de la Plata, Chuí Creek and AdV also include records of taxa associated
with more temperate and mixed habitats, such as Tapirus in toscas
del Río de la Plata, a cervid at AdV and the typical intertropical
E. laurillardi in Chuí Creek. The existence of those faunal assemblages
in these three sites, particularly the two assigned to the LGM, that lie
in the northern limit of the predicted co-occurrence area, and the
model for the LGM support the existence of a complex pattern of vege-
tation dominated by grasslands but including woodlands typical of
more humid climates in the Río de la Plata region during the LGM.
Given the geographic location of these sites, these patterns could be ex-
plained by seasonal floods of the Paleoparaná river, as discussed in
Sánchez-Saldías and Fariña (2014), that must have provided water to
an otherwise rather dry environment. Indeed, the primary productivity
required to sustain such an array of giant mammals must have been dif-
ficult to achieve if the climatic conditions of the region neighboring
today's Río de la Plata were as arid as previously proposed by re-
searchers such as Fariña (1996). Seasonal floods of the large
Palaeoparaná could have contributed to enrich soil in the area that is
today entirely submerged under the Río de la Plata and the contiguous
oceanic area (Fariña et al., 2014b).
The models also show high probability of occurrence for the three
sloths in regions now submerged but exposed during the LGM. This is
consistent with findings that involve underwater excavations and also
with fossils collected along ocean shorelines. Cartajena et al. (2013)
has undertaken submarine excavation along the Pacific coast of Chile
yielding the remains of a diverse fauna including mylodontid sloths
(López et al., 2015). Fossil remains are also common along the Atlantic
coasts of Uruguay and Brazil (Czerwonogora et al., 2002; Aires and
Lopes, 2012) and have been collected from the continental shelf by fish-
ing boats (Cione e t al., 2005; Lope s and Buchmann, 2 011). In these cases,
the fossils represent a diverse range of groups, including the three
genera of sloths that we studied.
Our results support the hypothesis that these megamammals occu-
pied areas exposed during the LGM and show that the reduction in
available land, as sea-level raised, along with the warming and humid-
ification of the continent should have heavily impacted their potential
areas of distribution at the end of the Pleistocene. In particular, bulk
feeders such as Glossotherium and Lestodon hadmoresuitableenviron-
ments in those regions than the selective feeders (more abundant in
Argentina) (Fariña et al., 2014b). Comparing these results with the pro-
jections for HCO, the reduction in suitable areas clearly emerges from
the reduction in available land, as no major changes are evident in re-
gard to climatically suitable areas. Nonetheless, this reduction in land
area could account for as much as 22%, 45% and 51% of potentially suit-
able areas for Glossotherium,Lestodon and Mylodon, respectively, proba-
bly representing a role in the increase of the extinction risk (Cardillo
et al., 2005). However, it is noteworthy that model predictions for the
LIG show similar, if not more suitable, patterns to those predicted in
the HCO for all the three species (Fig. 2;Table 3). This suggests
that climatic change was not the only cause for increased risk of the
extinction, leaving other causes, mainly human impact, as possible fac-
tors in the demise of these and other large mammals at the end of the
Pleistocene (Sandom et al., 2014).
Overall, our results show the existence of overlap between the suit-
able areas predicted for Glossotherium,Lestodon and Mylodon mainly
limited to the Río de la Plata and Pampas regions. This agrees with the
co-occurrence records. The suitable areas for the co-existence of all
three sloths were strongly associated with open habitats when com-
pared to the LGM biome reconstructions based on different proxies.
The three sloths showed high probability of presence in submarine
areas that were subaerial during the LGM. While no major fluctuations
were observed in patterns of highly suitable areas between the studied
periods, a significant reduction in those areas between the LGM and
HCO was observed due to the sea-level rise at the end of the Pleistocene.
The study of the potential distribution patterns of the extinct
Pleistocene megafauna provides an important approach to understand-
ing their paleogeography and evolution, as well as their extinction atthe
limit of the Pleistocene–Holocene. Moreover, those patterns could shed
particular light on the paleoenvironments and paleoclimates of South
America during the last 120 ka. Likewise, the study of potential areas
of co-occurrence of extinct species with equal or different ecological
requirements represents a valuable tool to infer paleoenvironmental
conditions, the interactions between species, and their evolutionary
history. Better stratigraphic control and more dating should greatly
improve results obtained from PSDMs.
Acknowledgments
We thank Álvar Carranza for the ideas in early stages of this work
and Santiago Lisidini for helping with the use of QGis. Ximena Martínez
Blanco, Sebastián Tambusso and Mariana Di Giacomo made important
suggestions to previous versions of this manuscript. Also, H. Greg
McDonald, Diego Brandoni, Curtis W. Marean and an anonymous
reviewer made constructive reviews that helped to improve the
manuscript.
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Pleistocene, Quaternary Research (2015), http://dx.doi.org/10.1016/j.yqres.2015.11.009
