Šiuo tyrimo tikslas buvo ištirti laukinių ir naminių kiaulių halotano geną. Tyrimo metodika. Tyrimas atliktas 2012-2013 m. LSMU Biologinių sistemų ir genetinių tyrimų institute K. Janušausko gyvūnų genetikos laboratorijoje. Viso, HAL geno atžvilgiu, ištirta 137 kiaulė (45 šernai, 5 Vietnamietiškos kiaulės, 12 Pekariai, 25 Landrasai, 25 Jorkšyrai ir 25 Pjetrėnai). Kiaulių šeriai buvo naudojami kaip genetinės medžiagos šaltinis. Halotano geno nustatymui buvo atliekama polomerazės grandininės reakcija (PGR). HAL geno įtakai mėsinėms ir penėjimosi savybėms įvertinti buvo atrinkti mišrūnai LxJxP (45) auginti Valstybinėje kiaulių veislininkystės stotyje. Penėjimosi ir mėsinių savybių duomenys gauti iš Valstybinės kiaulių kontrolinio penėjimo stoties Kauno skyriaus. Rezultatai ir išvados. Iš 75 tirtų naminių kiaulių 88 proc. buvo NN ir 12 proc. Nn genotipo. Visos (62) laukinė kiaulės buvo NN genotipo. Aukščiausias n alelio dažnis nustatytas pas Pjetrėnų (p<0,01) veislės kiaules lyginant su Landrasais ir Joršyrais. Tuo tarpų N alelio didžiausias dažnis rastas pas Jorkšyrų veislės kiaules. Kadangi visos tirtos laukinės kiaulės neturėjo streso geno (n) alelio galima daryti prielaidą, jog jos yra atsparesnės stresui. Mūsų tyrimų duomenimis HAL geno homozigotinių ir heterozigotinių kiaulių mėsinių ir penėjimosi savybių rodikliai skiriasi. Šiltos skerdėnos masė, skerdenos puselės ilgis ir bekono puselės ilgis buvo didesni pas NN genotipo namines kiaules. Pas heterozygotinius individus... [toliau žr. visą tekstą] / The aim of present study was to research halothane gene in wild and domestic pigs. Research methodology. Research was performed during 2012 – 2013 year in LSMU Biological Systems and Genetic Research Institute of K. Janusauskas Animals Genetic Laboratory. Samples for DNA testing were collected from wild and domestic pigs. Fattening and meat quality data were obtained from the State of Pigs Control fattening Station of Kaunas Department. A total of 137 pigs (45 wild boars, 5 Vietnamese pigs, 12 Pecari, 25 Landrace, 25 Yorkshire and 25 Pietrian) were tested for halothane genotype. For the effect of HAL gene on meat and fattening properties, 45 crossbreeds (LxJxP) from State Pigs Breeding Station were selected. Plucked hair was used as a source of genomic DNA. All tested animals were characterized as normal homozygotes (NN), heterozygotes (Nn) or recessive homozygotes following amplification of a target region of the HAL gene using the polymerase chain reaction (PCR), followed by a restriction endonuclease assay. The resulting PCR was digested with the restriction enzyme Alw21I, followed by agarose gel electrophoresis. Results and conclusions. In 75 tested domestic pigs, 88 % were NN and 12 % were Nn genotype. In 62 tested wild pigs all animals were NN genotipe. The frequency of n allele was higher (p<0.01) in Petrian pigs (0.25 for n) than in Landrase (0.1 for n) and Yorkshire (0.05 for n). The frequency of N allele was higher in Yorkshire than in the rest of the tested... [to full text]

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Wild pigs (Sus scrofa) are among the world's most destructive mammalian invasive species, and mitigating farther range expansion will require a thorough understanding of movement behavior, diel activity patterns, space use, and resource selection. Currently, limited empirical evidence is available on the ecology of wild pigs in Southwest Florida. Therefore, I examined how wild pigs behaviorally modified their movements and diel activity patterns in response to individual and environmental covariates. I investigated space use dynamics (e.g., home range size and seasonal variation) and evaluated how individual and environmental variation influenced home range size. Next, I determined how fine-scale movement patterns and resource selection of wild pigs are affected by temperature and time of day, and how those resources changed at broad and fine-scales, given their availability. I found that as temperature increased, the probability of foraging increased while the probability of traveling decreased. Foraging behavior occurred predominately between 8:00 and 17:00, and traveling behavior occurred predominately between 18:00 and 7:00, thereby indicating wild pigs were cathemeral. Home range size ranged from 2.6 to 35.8 km2 and averaged 13.0 km2 (n=16). Finally, home range size increased as the proportion of pasture increased and decreased as the proportion of wetlands increased, indicating that resources in agricultural areas were more diffuse than in natural habitats. At the broad (i.e., home range selection) and fine-scale (i.e., within home range) wild pigs selected for wetlands, forests, and pastures. Wild pig movement tended to be tortuous in forested and cropland habitats, but more directed in pasture habitats. Slower movements (i.e., smaller steps) and more directed (i.e., fewer turning) steps were observed during warmer temperatures, particularly avoiding croplands when temperatures were warmer. Wild pigs avoided wetland habitats during dusk and night hours and cropland habitats during dawn hours. Wild pigs selected for forested habitats during night and dawn hours, possibly in response to human activity. In addition, I found that wild pigs were less likely to step into a location with a daily temperature of 35.7°C than 16.1 C°. Wild pigs were less likely to choose warmer locations and more likely to select intermediate temperatures, thus avoiding locations with extremely low or high daily temperatures. Also, I found that wild pigs were more likely to select home ranges nearer to wetlands, forests, and pastures, while avoiding areas near cropland habitats. However, within their home ranges they were more likely to select habitats farther from croplands, forests, and wetlands. My findings reinforce the importance of wetlands, forests and pastures to wild pig selection of home ranges, where they likely utilize these landcover types for thermoregulation (e.g. forests and wetlands) and for foraging resources (e.g. pastures). Within their home ranges wild pigs may avoid forests and wetlands due to perceived predation risk being higher in those habitats, thus causing wild pigs to forgo higher quality resources to reduce risk. These results contribute information useful to wildlife managers to better predict which landcover types provide refuge (e.g., wetlands and forests) or potential movement corridors (e.g., pasture and cropland habitats) for wild pigs. In Southwest Florida, wild pigs have broad inter-individual variation in home range size, are strongly regulated by temperature, and are largely dependent on wetlands and forests to meet their energetic demands. / Doctor of Philosophy / Wild pigs are one of the world's most destructive invasive species. Although, hunters often oppose efforts to reduce wild pig populations, agricultural and natural resource managers support reduction efforts because they cause major economic and ecological damage. In addition, wild pigs carry a plethora of diseases and pose direct health risks to livestock, wildlife, and humans. Therefore, a better understanding of how environmental and landscape factors influence wild pig movements and space use is of broad interest to multiple stakeholder groups. I found that wild pigs mostly foraged during daytime and traveled at night, indicative of irregular activity patterns. Home range size averaged 13.0 km2 across 16 individuals and tended to increase as the proportion of pasture habitat increased and decreased as herbaceous wetlands increased. This indicated that resources were more abundant in natural habitats. Wild pigs preferred wetlands, forests, and pastures, and avoided croplands. However, they were more likely to forage in forests and croplands, and travel in pastures. Wild pigs avoided wetlands during dusk and night hours and croplands at dawn, while selecting forests during night and dawn hours. Wild pigs tended to move slower with less turning during warmer temperatures, particularly avoiding croplands when temperatures were hot. In general, wild pigs avoided locations with extremely low or high daily temperatures. I found wild pigs were more likely to select home ranges nearer to wetlands, forests, and pastures, while avoiding areas near cropland habitats. Wild pigs likely utilized these landcover types for thermoregulation (e.g. forests and wetlands) and for foraging resources (e.g. pastures), while avoiding open areas (e.g. croplands) due to a lack of shade. However, within their home ranges they were more likely to select habitats farther from croplands, forests, and wetlands, possibly because they perceived these areas to have higher predation risk. I highlight differences in space use among individuals and identify habitat types that are most likely to meet energetic demands. By understanding how environmental factors (e.g., habitat type and temperature) influence home range movement behaviors of wild pigs, land managers can focus on scale-dependent population control efforts. My results will aid land managers in better predicting which landcover types are providing refuge (e.g., wetlands and forests) or serving as potential movement corridors (e.g., pasture and cropland habitats).

Studies of animal spatial distributions typically use prior knowledge of animal habitat requirements and behavioral ecology to deduce the most likely explanations of observed habitat use. Animal-borne accelerometers can be used to distinguish behaviors which allows us to incorporate in situ behavior into our understanding of spatial distributions. Past research has focused on using supervised machine-learning, which requires a priori specification of behavior to identify signals whereas unsupervised approaches allow the model to identify as many signal types as permitted by the data. The following framework couples direct observation to behavioral clusters identified from unsupervised machine learning on a large accelerometry dataset. A behavioral profile was constructed to describe the proportion of behaviors observed per cluster and the framework was applied to an acceleration dataset collected from wild pigs (Sus scrofa). Although, most clusters represented combinations of behaviors, a leave-p-out validation procedure indicated this classification system accurately predicted new data.