ABSTRACT
Understanding stress physiology is crucial for species management because high levels of stress can reduce reproduction and the individual's ability to face threats to survive. One of the most popular methods for non-invasive monitoring of animal endocrine status is the glucocorticoid (GC) metabolite measurements, which can provide important information about how animals are affected by their surrounding environment. Here, we carried out the biological validation of corticosterone enzyme immunoassays (EIAs), which together with a cortisol EIA was used to quantified the concentrations of urofaecal GC metabolites (uGCMs) in wild and captive Blue-fronted amazon parrots (Amazona aestiva). Urofaecal GC concentrations were significantly higher (P < 0.05) in free-living parrots (157.9 ± 18.5 ng cortisol/g and 61.14 ± 23.5 ng corticosterone/g dry urofaecal sample) than in those kept in captivity, which showed the comparable levels of GC metabolites independently of the management system applied. The higher uGCM levels obtained in the wild population point to an adaptive response for survival and species propagation in a more challenging environment, in comparison with captive animals. Furthermore, the lower uGCM concentrations in captive parrots may indicate an adaptive capacity of the species A. aestiva to captivity and its potential as a legal pet. The corticosterone EIA applied in this study proved to be an effective technique for the adrenocortical activity monitoring in this species. We discuss our findings considering the management and destiny given to wild-caught birds that are kept in confinement or returned to nature.
ABSTRACT
Abstract The pampas deer (Ozotoceros bezoarticus) is close to being classified as 'globally threatened', with the largest population occurring in the Brazilian Pantanal. Since capture is stressful to these animals, non-invasive sampling methods such as the use of feces can provide reliable sources of DNA. The aim of this study was to use fecal samples to evaluate the genetic variability of the Brazilian Pantanal population of pampas deer. Six heterologous microsatellite markers were used to screen 142 stool specimens. Seventy-four deer were identified, of which 50 adults were used to determine the genetic characteristics of the population. The Pantanal population showed high genetic diversity (mean number of alleles per locus = 11.5, expected heterozygosity = 0.75). This is the first investigation to characterize a South American deer species using fecal DNA and demonstrates the usefulness and efficiency of this approach, as well as the feasibility of obtaining information that could not have been easily obtained by traditional DNA sampling. Our findings suggest that management strategies for this species may be much more effective if applied now when the population still shows high genetic variability.
ABSTRACT
The pampas deer (Ozotoceros bezoarticus) is close to being classified as 'globally threatened', with the largest population occurring in the Brazilian Pantanal. Since capture is stressful to these animals, non-invasive sampling methods such as the use of feces can provide reliable sources of DNA. The aim of this study was to use fecal samples to evaluate the genetic variability of the Brazilian Pantanal population of pampas deer. Six heterologous microsatellite markers were used to screen 142 stool specimens. Seventy-four deer were identified, of which 50 adults were used to determine the genetic characteristics of the population. The Pantanal population showed high genetic diversity (mean number of alleles per locus = 11.5, expected heterozygosity = 0.75). This is the first investigation to characterize a South American deer species using fecal DNA and demonstrates the usefulness and efficiency of this approach, as well as the feasibility of obtaining information that could not have been easily obtained by traditional DNA sampling. Our findings suggest that management strategies for this species may be much more effective if applied now when the population still shows high genetic variability.
