Yes, they can! Three-banded armadillos Tolypeutes sp. (Cingulata: Dasypodidae) dig their own burrows

Attias, Nina; Miranda, Flávia Regina; Sena, Liana Mara Mendes de; Tomás, Walfrido Moraes; Mourão, Guilherme

doi:10.1590/s1984-4689zool-20160035

Cited by 16 publications

(15 citation statements)

References 1 publication

(3 reference statements)

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“…Also, when the user chooses only one of the classifiers, complementary statistics analyses are generated helping it to verify it is possible significantly discriminate all species based on the three measurements (width, height, and angle). It represents a traditional statistics commonly used to discriminate between the armadillo species (e.g., Carter & Encarnação, 1983;Trovati, 2015;Attias et al, 2016). However, the significant difference will be more frequent as higher the n_sim value.…”

Section: Discussionmentioning

confidence: 99%

“…In addition to their conspicuous carapace, they have relatively low metabolic rates (McNab, 1985), which may contribute to their relatively poor thermoregulatory abilities. Diets emphasize invertebrate prey , and all species dig burrows (Eisenberg & Redford, 1999;Attias et al, 2016). By so doing, armadillos can create new habitats or modify ecosystem features.…”

Section: Introductionmentioning

confidence: 99%

“…Although armadillos are rarely observed in nature, they dig burrows directly related to the construction of shelter (housing, raising offspring), protection (to hide from predators and to buffer against environmental temperatures), and feed (foraging burrows) Eisenberg & Redford, 1999;. Burrows created by armadillos have peculiar shapes and sizes (Carter & Encarnação, 1983;Trovati, 2015;Attias, Miranda, Sena, Tomas, & Mourão, 2016;, which are influenced by anatomical and morphological differences among the species (e.g. Attias et al, 2016;.…”

Section: Introductionmentioning

confidence: 99%

“…Burrows created by armadillos have peculiar shapes and sizes (Carter & Encarnação, 1983;Trovati, 2015;Attias, Miranda, Sena, Tomas, & Mourão, 2016;, which are influenced by anatomical and morphological differences among the species (e.g. Attias et al, 2016;. Several studies have been used armadillo burrows to estimate population parameters including habitat use, density, activity and behaviour (Zimmerman, 1990;Platt, Rainwater, & Brewer, 2004;Arteaga & Venticinque, 2008;Abba, Udrizar-Sauthier, & Vizcaino, 2005;Abba, Zufiaurre, Codesido, & Bilenca, 2015;.…”

Section: Introductionmentioning

confidence: 99%

“…By contrast, the fact of solely Dasypus novemcinctus be found in the USA has resulted in well-known burrow measurements (Zimmerman, 1990;Platt et al, 2004;Sawyer et al, 2012). Other armadillo species were also monitored for describing their burrows measurements (Medri, 2008;Attias et al, 2016;. Nevertheless, how to use those reported measurements to correctly identify armadillo species remains poorly explored (e.g.…”

Section: Introductionmentioning

confidence: 99%

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The armadillos: from ecosystem services and online opinions to land use in agricultural landscapes

Rodrigues¹

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This thesis revolves around the idea that armadillos represent an important group of mammals that perform essential ecological functions; however, over the years have received little attention from both scientists and the general public, which raises a concern about the conservation status of this group. Over the five chapters of this thesis, using armadillos as a study model, I demonstrate their importance for the terrestrial ecosystem, access the perceptions of the general public, develop a computacional tool to enable an increase in research and seek to understand how human-modified landscapes can influence this group. For that, I use a multidisciplinary approach. In Chapter 1, I identify the ecological contributions provided by armadillos directly related to humans, including social, economic, cultural, environmental, and biological aspects. In Chapter 2, I recognize through comments on social media that the general public has aroused great interest for this group, but they are unaware of most species and their corresponding ecological functions. In Chapter 3, I develop a tool that aims to enable the use of burrows as a low-cost non-invasive method to identify four species of armadillos. In Chapter 4, I elucidate that native forests inside and outside protected areas are essential for maintaining a species of armadillo, the nine-banded armadillo, in agricultural landscapes, with implications regarding the importance of the Brazilian Forest Code. Finally, Chapter 5 advances in the understanding of the underexplored consequences of human-modified landscapes on biodiversity, by showing how two poorly known armadillo species (Cabassous sp.) respond to a scenario predominantly dominated by sugarcane. Altogether, this results contribute to broadening our understanding of the importance of armadillos, as well as offer ways to improve the conservation status of this important group.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The armadillos: from ecosystem services and online opinions to land use in agricultural landscapes

Rodrigues¹

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Noninvasive Low‐cost Method to Identify Armadillos' Burrows: A Machine Learning Approach

Rodrigues

Nogueira

Chiarello

2021

Wildlife Society Bulletin

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Having accurate information about population parameters of armadillos (Mammalia, Cingulata) is essential for the conservation and management of the taxon, most species of which remain poorly studied. We investigated whether we could accurately identify 4 armadillo species (Euphractus sexcinctus, Dasypus novemcinctus, Cabassous tatouay, and Cabassous unicinctus) based on burrow morphometry. We first selected published studies that reported measurements of width, height, and angle of the burrows used by the 4 species of armadillos. Then, using such data we simulated burrow measurements for each of the 4 species of armadillos and we created predictive models through supervised machine learning that were capable of correctly identifying the species of armadillos based on their burrows' morphometry. By using classification algorithms such as Random Forest, K-Nearest Neighbor, Support Vector Machine, Naive Bayes, and Decision Tree C5.0, we achieved the overall accuracy for the classification task by about 71%, including an overall Kappa index by about 61%. Euphractus sexcinctus was the most difficult species to discriminate and classify (approximately 68% of accuracy), whereas C. unicinctus was the easiest to discriminate (approximately 93% of accuracy). We found that it was possible to identify similar-sized armadillos based on the measurements of their burrows described in the literature. Finally, we developed an R function (armadilloID) that automatically identified the 4 species of armadillos using burrow morphology. As the data we used represented all studies that reported the morphometry of burrows for the 4 species of armadillos, we can generalize that our function can predict armadillo species beyond our data.

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Xenarthran Synsacrum Morphology and Evolution

Galliari¹,

Carlini

2018

J Mammal Evol

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Yes, they can! Three-banded armadillos Tolypeutes sp. (Cingulata: Dasypodidae) dig their own burrows

Cited by 16 publications

References 1 publication

The armadillos: from ecosystem services and online opinions to land use in agricultural landscapes

The armadillos: from ecosystem services and online opinions to land use in agricultural landscapes

Noninvasive Low‐cost Method to Identify Armadillos' Burrows: A Machine Learning Approach

Xenarthran Synsacrum Morphology and Evolution

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