Non‐invasive genotyping of the endangered Apennine brown bear: a case study not to let one's hair down

Lorenzini, Rita; Posillico, Mario; Lovari, Sandro; Petrella, Annino

doi:10.1017/s1367943004001301

Cited by 49 publications

(51 citation statements)

References 54 publications

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“…Knowledge of the species' taxonomic status and population genetic structure is fundamental to developing effective strategies to this end (Lorenzini et al, 2004). Inter-and intraspecific phylogenetic knowledge also would help clarify the species' biology, and would resolve appropriate conservation and management units for this species (An, 2006).…”

Section: Introductionmentioning

confidence: 99%

Genetic diversity and population structure of the long-tailed goral, <i>Naemorhedus caudatus</i>, in South Korea

Choi

Chun

et al. 2015

Genes Genet. Syst.

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The long-tailed goral, Naemorhedus caudatus, is an internationally endangered species. This species is distributed throughout Northeastern Asia including Northeastern China, the Russian Far East and the Korean peninsula. The population size of long-tailed gorals is currently decreasing in South Korea, and thus effective conservation of the animal is urgently needed. Although the evolution and phylogeny of this animal have been studied, population genetic studies are needed to design effective conservation and management strategies. To evaluate the present status of genetic diversity and genetic structure of long-tailed gorals in South Korea, we investigated genetic variability among 68 goral individuals from different regions, including 11 captive zoo animals, at 12 microsatellite loci. The level of genetic diversity was moderate in wild goral populations, but lower in the captive group. The goral population from the lower northeast region of South Korea was distinct from the upper northeast population, probably due to the natural climatic and geographic conditions. The genetic characteristics of the captive group were more similar to those of the upper northeast population than the lower northeast, confirming that the zoo animals originated in the Seorak Mountain range. Direct translocations between the upper and lower northeast populations are not currently recommended considering the natural population structure and the moderate levels of genetic diversity in the two populations. This study highlights the importance of genetic information in designing effective conservation strategies and translocations of endangered animals, including the Korean goral.

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Section: Introductionmentioning

confidence: 99%

Genetic diversity and population structure of the long-tailed goral, <i>Naemorhedus caudatus</i>, in South Korea

Choi

Chun

et al. 2015

Genes Genet. Syst.

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“…After checking the concentration, the DNA was stored in a freezer at -20 °C. Five nuclear microsatellite loci were used (Røed and Midthjell 1998;Postma et al 2001;Lorenzini et al 2004): NVHRT30, NVHRT71, NVHRT48, NVHRT16 and NVHRT24 (further abbreviated as N30, N71, N48, N16 and N24). We used two multiplex reactions for PCR amplification -N30 and N71 as multiplex No 1, and N48, N16 and N24 as multiplex No 2.…”

Section: Dna Marker Analysismentioning

confidence: 99%

Differentiation of European roe deer populations and ecotypes in Lithuania based on DNA markers, cranium and antler morphometry

Sabalinkiene¹,

Danusevičius²,

Manton³

et al. 2017

Silva Fenn.

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Highlights• Lithuanian roe deer populations are genetically structured into southern and northern groups, most likely affected by a divergent gene flow and Lithuania's largest rivers slowing down migration.• Microsatellite and skull morphology based genetic differentiation between field and forest ecotypes are weak.• Geographical location has a significant effect on antler morphometry traits and skull size of male roe deer, the latter increasing northwards. AbstractThe objective of our study was to assess the genetic and morphological differentiation of European roe deer (Capreolus capreolus L.) in Lithuania based on DNA markers, skull and anther morphology. DNA was extracted from 79 culled individuals at 13 locations and genotyped at five nuclear microsatellite loci. Based on culling location, individuals were assigned to either a field (N = 43) or a forest ecotype (N = 36). Skull and antler morphometry was studied on 603 and 292 individuals, respectively. Results showed no significant genetic and skull morphology differentiation between the ecotypes. The forest ecotype tends to exhibit lower genetic diversity compared to the field ecotype, particularly for male individuals. The genetic differentiation of roe deer in Lithuania was significant based on the R ST values, but not on the F ST values. A STRUCTURE analyses revealed southern and northern genetic clusters, most likely affected by divergent gene flow. The country's major rivers Nemunas and Neris are likely to increase differentiation between the clusters. ANOVA on skull morphology by gender and age indicated a significant effect of geographical location. Skull size (especially length) is greater in the northern part of the country. We also found significant effects of age, ecotype and geographical location on most of the roe deer male antler morphometric traits.

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“…In 2004, we produced a preliminary, hair-snag based estimate of 43 bears (95% CI = 35-67) for this population, but low capture probability and limited power to model heterogeneity affected precision and reliability of the population estimate (Gervasi et al 2008). In addition, the low genetic variability of this population (Lorenzini et al 2004;Randi et al 1994) potentially reduces our power in distinguishing individual genotypes as observed in similar studies on brown bears (Paetkau 2004;Waits et al 2001), thus requiring an increased number of microsatellite loci.…”

Section: Introductionmentioning

confidence: 98%

“…The Apennine brown bear lives in a small and isolated population (Ciucci and Boitani 2008;Gervasi et al 2008), and is highly depleted of genetic variability (Lorenzini et al 2004;Randi et al 1994). In 2004, we produced a preliminary, hair-snag based estimate of 43 bears (95% CI = 35-67) for this population, but low capture probability and limited power to model heterogeneity affected precision and reliability of the population estimate (Gervasi et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Addressing challenges in non invasive capture-recapture based estimates of small populations: a pilot study on the Apennine brown bear

et al. 2010

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It is often difficult to determine optimal sampling design for non-invasive genetic sampling, especially when dealing with rare or elusive species depleted of genetic diversity. To address this problem, we ran a hair-snag pilot study on the remnant Apennine brown bear population. We used occupancy models to estimate the performance of an improved field protocol, a meta-analysis approach to indirectly model capture probability, and simulations to evaluate the effect of genotyping errors on the accuracy of capture-recapture population estimates. In spring 2007 we collected 70 bear hair samples in 15 5 x 5 km cells, using 5 10-day trapping sessions. Bear detectability was higher in 2007 than in a previous attempt on the same population in 2004, reflecting improved field protocols and sampling design. However, individual capture probability was 0.136 (95% CI = 0.120-0.152), still below the minimum requirements of capture-mark-recapture closed population models. We genotyped hair samples (n = 63) at 9 microsatellite loci, obtaining 94% Polymerase Chain Reaction success, and 13 bear genotypes. Estimated P(IDsib) was 0.00594, and per-genotype error rate was 0.13, corresponding to a 99% probability of correct individual identification. Simulation studies showed that the effect of non-corrected or filtered genetic errors on the accuracy of population estimates was negligible only when individual capture probability was > 0.2. Our results underline how the interaction among field protocols, sampling strategies and genotyping errors may affect the accuracy of DNA-based estimates of small and genetically depleted populations, and warned us about the feasibility of a survey using only traditional hair-snag sampling. In this and similar cases, indications from pilot studies can provide cost-effective means to evaluate the efficiency of designed sampling and modelling procedures

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Non‐invasive genotyping of the endangered Apennine brown bear: a case study not to let one's hair down

Cited by 49 publications

References 54 publications

Genetic diversity and population structure of the long-tailed goral, <i>Naemorhedus caudatus</i>, in South Korea

Genetic diversity and population structure of the long-tailed goral, <i>Naemorhedus caudatus</i>, in South Korea

Differentiation of European roe deer populations and ecotypes in Lithuania based on DNA markers, cranium and antler morphometry

Addressing challenges in non invasive capture-recapture based estimates of small populations: a pilot study on the Apennine brown bear

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