Museomics and morphological analyses of historical and contemporary peninsular Italian wolf (Canis lupus italicus) samples

Abstract

After centuries of decline and protracted bottlenecks, the peninsular Italian wolf population has naturally recovered. However, an exhaustive comprehension of the effects of such a conservation success is still limited by the reduced availability of historical data. Therefore, in this study, we morphologically and genetically analyzed historical and contemporary wolf samples, also exploiting the optimization of an innovative bone DNA extraction method, to describe the morphological variability of the subspecies and its genetic diversity during the last 30 years. We obtained high amplification and genotyping success rates for tissue, blood and also petrous bone DNA samples. Multivariate, clustering and variability analyses confirmed that the Apennine wolf population is genetically and morphologically well-distinguishable from both European wolves and dogs, with no natural immigration from other populations, while its genetic variability has remained low across the last three decades, without significant changes between historical and contemporary specimens. This study highlights the scientific value of well-maintained museum collections, demonstrates that petrous bones represent reliable DNA sources, and emphasizes the need to genetically long-term monitor the dynamics of peculiar wolf populations to ensure appropriate conservation management actions.

Keywords: Canis lupus italicus; Apennine Italian wolves; Conservation management; Genetic variability patterns; Historical biological samples; Multilocus genetic profiles; Museomics; Museum collections; Population genetics.

Fig. 1

Map visualizing the geographical distribution and sampling locations of the Italian reference (WIT), peninsular historical (HW) and contemporary (CW) wolf samples analyzed in this study. Wolf distribution and occupancy probability estimates are derived, according to the policy of the Widely publisher group about Creative Common CC BY license, from Gervasi et al., and using a 10 × 10 km grid adopted at the European level for the Habitats Directive 92/43/EEC reporting (https://www.eea.europa.eu/data-and-maps/data/eea-reference-grids-2).

Fig. 2

(A) Craniometrical parameters measured in wolf adult skulls to describe their morphometry. (A) Dorsal view. TL total length, LF facial length, NL upper neurocranium length, GLN maximum nasal length, CL cranial length, BCA rostrum width, LBBO minimum breadth between the orbits, FB maximum frontal breadth, GNB maximum neurocranium breadth. Ventral view. GPB greatest breadth of the palatine, GDAB greatest diameter of the auditory bulla, ZB zygomatic breadth. Lateral view. HC height of upper canine, LM1 upper carnassial length, SH skull height, LAPI angular process-interdental, TLM total length of the mandible. (B) Body parameters measured in wolf adult carcasses to describe their morphology. HBL head and body length, HL head length, NKL neck length, NKC neck circumference, SL height at the shoulders, CC chest circumference, BL body length, RRF rump to rear foot pad, EL ear length, TL tail length, RPL rear paw length. Morphometric parameters used to compare populations in Principal Component Analyses (Figs. 5 and 6) are indicated by orange stars. Morphometric parameters used to compare among-population minimum, maximum and mean values in box plots represented in Fig. S1 and Fig. S2 are indicated by blue stars.

Fig. 3

(A) Exploratory Principal Component Analysis (PCA) computed in Adegenet and performed using the 39-STR genotypes of 56 Historical Italian wolves HWIT (dark blue dots), 56 Contemporary Italian wolves CWIT (light blue dots), 175 reference Italian wolves (WIT, blue dots), 89 Italian dogs (DIT, red dots) and 196 European wolves from 5 geographical populations: Dinaric = WDIN, Iberian = WIBE, Carpathian = WCARP, Balkan = WBALK, Baltic = WBALT. The first component PC-I explains 43.94% of the total genetic variability and clearly separates the Italian wolf population from the European wolves and domestic dogs, while these latter two are plainly separated along the second component PC-II which explains 21.44% of the total genetic variability. (B) Estimated posterior probability LnP(K) and corresponding standard deviations of the K genetic clusters from 1 to 10. (C) Bar plotting of the individual q_i-values obtained through Bayesian model-based clustering procedures implemented in Structure and performed using the 39-STR genotypes of 56 HWIT, 56 CWIT and, as reference populations, the 39-STR genotypes of 175 Italian wolves (WIT), 89 dogs (DIT) and 196 European wolves from 5 geographical populations (WDIN, WIBE, WCARP, WBALK, WBALT). Each individual is represented by a vertical line partitioned into coloured segments, whose length is proportional to the individual coefficients of membership (qi) to the wolf and dog clusters inferred assuming K = 2 clusters and using the ‘‘Admixture’’ and ‘‘Independent allele frequencies’’ models.

Fig. 4

(A) Exploratory Principal Component Analysis (PCA) computed in Adegenet and performed using the 39-STR genotypes of 55 Historical Italian wolves HWIT (dark blue dots), 56 Contemporary Italian wolves CWIT (light blue dots), 175 reference Italian wolves (WIT, blue dots), 89 Italian dogs (DIT, red dots). The first component PC-I explains 56.40% of the total genetic variability and clearly separates the Italian wolf population from domestic dogs, while the second component PC-II which explains 10.91% of the total genetic variability, describes the genetic variability observed within these latter. (B) Bar plotting of the individual q_i-values obtained through Bayesian model-based clustering procedures implemented in Structure and performed using the 39-STR genotypes of 55 HWIT, 56 CWIT and, as reference populations, the 39-STR genotypes of 175 Italian wolves (WIT) and 89 dogs (DIT). Each individual is represented by a vertical line partitioned into coloured segments, whose length is proportional to the individual coefficients of membership (qi) to the wolf and dog clusters inferred assuming K = 2 clusters and using the ‘‘Admixture’’ and ‘‘Independent allele frequencies’’ models.

Fig. 5

Principal Component Analysis (PCA) computed in PAST using: (A) 17 craniometrical parameters (see Fig. 2A for details) measured to describe the morphometry in adult skulls of 12 Historical Italian male wolves (HW M, green dots), 8 Historical Italian female wolves (HW F, green triangles) and 8 domestic dogs (red dots); (B) 10 craniometrical parameters (signed with yellow asterisk in Fig. 2A) measured to describe the morphometry in adult skulls of 12 Historical Italian male wolves (HW M, green dots), 8 Historical Italian female wolves (HW F, green triangles), 20 Norwegian male wolves (NW M, orange dots), 6 Norwegian female wolves (NW F, orange triangles), 27 Swedish male wolves (SW M, yellow dots), 17 Swedish female wolves (SW F, yellow triangles). The Balkan wolf (W2452) and the 2 dog-introgressed (W0489 and W2453) HW samples are labelled with their individual codes.

Fig. 6

Principal Component Analysis (PCA) computed in PAST using: (A) 11 morphometric parameters (see Fig. 2B for details) measured to describe the morphology in adult carcasses of 8 Historical Italian male wolves (HW M, dark green dots), 6 Historical Italian female wolves (HW F, dark green triangles), 17 Contemporary Italian male wolves (CW M, light green dots), 8 Contemporary Italian female wolves (CW F, light green triangles); (B) 5 morphometric parameters (signed with * in Fig. 2B) measured to describe the morphology in adult carcasses of 8 Historical Italian male wolves (HW M, dark green dots), 6 Historical Italian female wolves (HW F, dark green triangles), 17 Contemporary Italian male wolves (CW M, light green dots), 8 Contemporary Italian female wolves (CW F, light green triangles), 3 Norwegian male wolves (NW M, orange dots), 3 Norwegian female wolves (NW F, orange triangles), 6 Swedish male wolves (SW M, yellow dots), 4 Swedish female wolves (SW F, yellow triangles). The Balkan wolf (W2452) and 2 dog-introgressed (W0489 and W2453) HW samples are labelled with their individual codes.