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The North African catfish (Clarias gariepinus) is a significant species in aquaculture, which is crucial for ensuring food and nutrition security. Their high adaptability to diverse environments has led to an increase in the number of farms that are available for their production. However, long-term closed breeding adversely affects their reproductive performance, leading to a decrease in production efficiency. This is possibly caused by inbreeding depression. To investigate the root cause of this issue, the genetic diversity of captive North African catfish populations was assessed in this study. Microsatellite genotyping and mitochondrial DNA D-loop sequencing were applied to 136 catfish specimens, collected from three populations captured for breeding in Thailand. Interestingly, extremely low inbreeding coefficients were obtained within each population, and distinct genetic diversity was observed among the three populations, indicating that their genetic origins are markedly different. This suggests that outbreeding depression by genetic admixture among currently captured populations of different origins may account for the low productivity of the North African catfish in Thailand. Genetic improvement of the North African catfish populations is required by introducing new populations whose origins are clearly known. This strategy should be systematically integrated into breeding programs to establish an ideal founder stock for selective breeding. [ABSTRACT FROM AUTHOR]

The association between patch metrics and roosting site (n = 31) suitability of Lyle’s flying fox (Pteropus lylei) in 26 Central Eastern and Western provinces of Thailand was quantified. Land use classes with 90-m resolution were identified based on various vegetation and land cover types to calculate patch metrics using FRAGSTATS. Then, Maximum Entropy Modeling (MaxEnt) was performed using patch metrics covariates to produce a predictive potential distribution map. The results indicated that patch contiguity (contiguity index, 63.7%), patch area (29.3%), and patch shape complexity (shape index, 5.7%) are the most influential patch metrics, all of which have negative effects on roosting site suitability. In total, 13,222 small patches were considered highly suitable patches, with a mean area of 0.921 ± 0.698 (SD) ha, which accounted for 122,090 ha (2.04%) of the study area. Roosting sites predicted from the model were consistently associated with occurrences of roosting sites observed in temples; such habitats likely provide shelter from external threats for colonies roosting in a human-dominated landscape.

Bats are reservoirs for various pathogens, including SARS-like coronaviruses (CoVs). Understanding the distribution of bat species is crucial to identifying areas where viral spillover from bats to other animals or humans might occur. In this study, we performed species distribution modeling to predict suitable habitats within Thailand under current and predicted future climate conditions for Rhinolophus acuminatus, a bat species that has been found to host SARS-CoV-2-related viruses. Our assessment of current conditions revealed that temperature seasonality had the greatest impact on habitat suitability and that suitable habitats were primarily restricted to the southern and eastern regions of Thailand. Over time, the projections indicate a diminishing availability of suitable habitats, suggesting a potential trend toward migration into neighboring areas. We next combined modeled bat distribution with urbanization data to estimate regions in Thailand where bat–human interactions might occur. The resulting map highlighted regions of heightened interaction risk, encompassing approximately 46,053.94 km2 across 58 provinces and representing approximately 9.24% of Thailand's total area. These risk concentrations are prominently situated in the southern, central, and eastern Thai regions, with extensions into neighboring border areas. Our findings will significantly aid future risk surveillance efforts and enhance the effectiveness of monitoring and managing emerging diseases within the country and in contiguous regions. [ABSTRACT FROM AUTHOR]

A Bayesian approach was used to develop binary quantile regression models featuring the lasso penalty. The models afford the advantages of all quantile regression models, such as robustness and detailed insights into covariate effects; they also handle issues associated with overfitting well. Thus, this model was used to investigate habitat suitability for the management of tiger prey species. Field data were collected from 150 sampling sites (2,416 sub-plots) in Thap Lan National Park of the Dong Phayayen-Khao Yai Forest Complex (DPKY) from August 2019 to March 2021. We focused on sambar deer (Rusa unicolor) and gaur (Bos gaurus) because they are the principal prey species of tigers. Vegetation was sampled for biomass and nutrient content to identify suitable habitat. The "bayesQR" package of R was used to identify habitats appropriate for these species. The correlation between forage crop biomass and the normalized difference vegetation index (NDVI) was significantly associated with tiger prey species presence. The habitat can be improved by increasing grass and forb biomasses as the prey species prefer open habitats, such as grassland and open areas of dry evergreen forest. Habitat management has ensured that the grass biomass of open forest is significantly higher than that of dense forest. In addition, the hemicellulose content of open forest was significantly greater than that of dense forest. We found that spatial modeling combined with Bayesian, lasso binary quantile regression could aid wildlife habitat management in a Thai National Park. [ABSTRACT FROM AUTHOR]

Spatial modeling is an analytical procedure that simulates real-world conditions using remote sensing and geographic information systems. The field data in this study were collected from 318 survey plots in the area surrounding highway 304 in the Dong Phayayen-Khao Yai Forest Complex (DPKY-FC) during the 2019 rainy season. Forage-crop biomass was collected from all plots. We focused on sambar deer (Rusa unicolor) and gaur (Bos gaurus), which are the main prey for tigers in this area. We created spatial models using generalized linear models with stepwise regression. The results indicated that the normalized difference vegetation index (NDVI) varied directly with grass biomass but inversely with shrub biomass (p<0.05). Elevation varied directly with forb biomass but inversely with shrub biomass (p<0.05). The probability of occurrence of sambar deer varied directly with distance from disturbance variables, distance from the stream, and grass biomass (p<0.001), but inversely with NDVI (p<0.05). The occurrence of gaur varied directly with NDVI (p=0.08), but varied inversely with slope, distance from the road, and distance from the stream (p<0.05). Our results demonstrate that spatial modeling can be an effective tool for wildlife habitat management in the area surrounding highway 304. [ABSTRACT FROM AUTHOR]

Background: Bats are natural reservoirs for several highly pathogenic and novel viruses including coronaviruses (CoVs) (mainly Alphacoronavirus and Betacoronavirus). Lyle’s flying fox (Pteropus lylei)‘s roosts and foraging sites are usually in the proximity to humans and animals. Knowledge about age-specific pattern of CoV infection in P. lylei, prevalence, and viral shedding at roosts and foraging sites may have an impact on infection-age-structure model to control CoV outbreak. Methods: P. lylei bats were captured monthly during January–December 2012 for detection of CoV at three areas in Chonburi province; two human dwellings, S1 and S2, where few fruit trees were located with an open pig farm, 0.6 km and 5.5 km away from the bat roost, S3. Nested RT-PCR of RNA-dependent RNA polymerase (RdRp) gene from rectal swabs was used for CoV detection. The strain of CoV was confirmed by sequencing and phylogenetic analysis. Results: CoV infection was found in both juveniles and adult bats between May and October (January, in adults only and April, in juveniles only). Of total rectal swab positives (68/367, 18.5%), ratio was higher in bats captured at S1 (11/44, 25.0%) and S2 (35/99, 35.4%) foraging sites than at roost (S3) (22/224, 9.8%). Juveniles (forearm length ≤ 136 mm) were found with more CoV infection than adults at all three sites; S1 (9/24, 37.5% vs 2/20, 10%), S2 (22/49, 44.9% vs 13/50, 26.0%), and S3 (10/30, 33.3% vs 12/194, 6.2%). The average BCI of CoV infected bats was significantly lower than uninfected bats. No gender difference related to infection was found at the sites. Phylogenetic analysis of conserved RdRp gene revealed that the detected CoVs belonged to group D betacoronavirus (n = 64) and alphacoronavirus (n = 4). Conclusions: The fact that CoV infection and shedding was found in more juvenile than adult bats may suggest transmission from mother during peripartum period. Whether viral reactivation during parturition period or stress is responsible in maintaining transmission in the bat colony needs to be explored. [ABSTRACT FROM AUTHOR]

Objective: The remarkable adaptability to the environment, high growth rate, meat with good taste and aroma, and ornamental appearance of the Pradu Hang Dam (PDH) and Samae Dam (SD) chickens make them valuable for improvement of poultry production to enhance food security. However, despite their close phenotypic similarity, distinct classification of PDH and SD chickens remains controversial. Thus, this study aimed to clarify genetic origins and variation between PDH and SD chickens, genetic diversity and structures of PDH and SD chickens., Methods: This study analyzed 5 populations of PDH and 2 populations of SD chickens using 28 microsatellite markers and compared with those of other indigenous and local chicken breeds using Thailand's "The Siam Chicken Bioresource Project" database., Results: Considerably high genetic variability was observed within PDH (370 total alleles; 4.086 ± 0.312 alleles/locus) and SD chickens (179 total alleles; 3.607 ± 0.349 alleles/locus). A partial overlap of gene pools was observed between SD chickens from the Department of Livestock, Uthai Thani (SD1) and PDH chickens, suggesting a potentially close relationship between the two chicken breeds. A gene pool that is partially overlapped with that of the red junglefowl was observed in the SD chicken population from the Sanhawat Farm Uthai Thani population (SD2). Distinct subclusters were observed within SD chickens, indicating the possibility that genetic differentiation occurred early in the process of establishment of SD chickens., Conclusion: These findings could offer valuable insights into genetic verification of Thai local chicken breeds and their sustainable conservation and utilization.