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The rediscovery of remnant Florida panthers (Puma concolor coryi) in southern Florida swamplands prompted a program to protect and stabilize the population. In 1995, conservation managers translocated eight female pumas (P. c. stanleyana) from Texas to increase depleted genetic diversity, improve population numbers, and reverse indications of inbreeding depression. We have assessed the demographic, population-genetic, and biomedical consequences of this restoration experiment and show that panther numbers increased threefold, genetic heterozygosity doubled, survival and fitness measures improved, and inbreeding correlates declined significantly. Although these results are encouraging, continued habitat loss, persistent inbreeding, infectious agents, and possible habitat saturation pose new dilemmas. This intensive management program illustrates the challenges of maintaining populations of large predators worldwide.

Pumas are the most widely distributed felid in the Western Hemisphere. Increasingly, however, human persecution and habitat loss are isolating puma populations. To explore the genomic consequences of this isolation, we assemble a draft puma genome and a geographically broad panel of resequenced individuals. We estimate that the lineage leading to present-day North American pumas diverged from South American lineages 300–100 thousand years ago. We find signatures of close inbreeding in geographically isolated North American populations, but also that tracts of homozygosity are rarely shared among these populations, suggesting that assisted gene flow would restore local genetic diversity. The genome of a Florida panther descended from translocated Central American individuals has long tracts of homozygosity despite recent outbreeding. This suggests that while translocations may introduce diversity, sustaining diversity in small and isolated populations will require either repeated translocations or restoration of landscape connectivity. Our approach provides a framework for genome-wide analyses that can be applied to the management of similarly small and isolated populations. Pumas are experiencing increased isolation as human persecution and habitat loss fragment the populations of this once widespread species. Here, the authors estimate the genomic consequences of this isolation by analyzing the genomes of ten pumas from across North and South America.

Modern felid species descend from relatively recent (<11 million years ago) divergence and speciation events that produced successful predatory carnivores worldwide but that have confounded taxonomic classifications. A highly resolved molecular phylogeny with divergence dates for all living cat species, derived from autosomal, X-linked, Y-linked, and mitochondrial gene segments (22,789 base pairs) and 16 fossil calibrations define eight principal lineages produced through at least 10 intercontinental migrations facilitated by sea-level fluctuations. A ghost lineage analysis indicates that available felid fossils underestimate (i.e., unrepresented basal branch length) first occurrence by an average of 76%, revealing a low representation of felid lineages in paleontological remains. The phylogenetic performance of distinct gene classes showed that Y-chromosome segments are appreciably more informative than mitochondrial DNA, X-linked, or autosomal genes in resolving the rapid Felidae species radiation.

The elusive nature and endangered status of most carnivore species imply that efficient approaches for their non-invasive sampling are required to allow for genetic and ecological studies. Faecal samples are a major potential source of information, and reliable approaches are needed to foster their application in this field, particularly in areas where few studies have been conducted. A major obstacle to the reliable use of faecal samples is their uncertain species-level identification in the field, an issue that can be addressed with DNA-based assays. In this study we describe a sequence-based approach that efficiently distinguishes jaguar versus puma scats, and that presents several desirable properties: (1) considerably high amplification and sequencing rates; (2) multiple diagnostic sites reliably differentiating the two focal species; (3) high information content that allows for future application in other carnivores; (4) no evidence of amplification of prey DNA; and (5) no evidence of amplification of a nuclear mitochondrial DNA insertion known to occur in the jaguar. We demonstrate the reliability and usefulness of this approach by evaluating 55 field-collected samples from four locations in the highly fragmented Atlantic Forest biome of Brazil and Argentina, and document the presence of one or both of these endangered felids in each of these areas.

Acquiring reliable data on large felid populations is crucial for effective conservation and management. However, large felids, typically solitary, elusive and nocturnal, are difficult to survey. Tagging and following individuals with VHF or GPS technology is the standard approach, but costs are high and these methodologies can compromise animal welfare. Such limitations can restrict the use of these techniques at population or landscape levels. In this paper we describe a robust technique to identify and sex individual pumas from footprints. We used a standardized image collection protocol to collect a reference database of 535 footprints from 35 captive pumas over 10 facilities; 19 females (300 footprints) and 16 males (235 footprints), ranging in age from 1-20 yrs. Images were processed in JMP data visualization software, generating one hundred and twenty three measurements from each footprint. Data were analyzed using a customized model based on a pairwise trail comparison using robust cross-validated discriminant analysis with a Ward's clustering method. Classification accuracy was consistently > 90% for individuals, and for the correct classification of footprints within trails, and > 99% for sex classification. The technique has the potential to greatly augment the methods available for studying puma and other elusive felids, and is amenable to both citizen-science and opportunistic/local community data collection efforts, particularly as the data collection protocol is inexpensive and intuitive.

Among the species described within the Onchocercidae family, Dirofilaria immitis is regarded as the most common worldwide, causing severe and often fatal conditions in dogs, cats, and occasionally humans. Dirofilaria spp. are vectored by mosquitoes, simulids, and culicoids, with their epidemiology dependent on the geographical distribution of competent vectors. Eight species of Dirofilaria have been reported so far in Brazil, of which six parasitize non-human primates, deer, procyonids, and marsupials. Here, we investigated the occurrence of Onchocercidae in wild felids (i.e., Panthera onca , Puma concolor , Herpailurus yagouaroundi , Leopardus geoffroyi , Leopardus guttulus , Leopardus pardalis , Leopardus wiedii , Leopardus munoai ) from different locations in Brazil. Overall, 82 samples ( n  = 63 blood; n  = 19 tissues) were molecularly screened for cytochrome c oxidase subunit-1 ( cox 1) gene. Four (i.e., 4.8%) wild felid samples were positive, and at BLAST analysis, the obtained sequences showed varying percentage of nucleotide identity with the genera Brugia (i.e., 87–88%), Setaria (i.e., 89%), and D. immitis (i.e., 94.4%). Phylogenetic analyses clustered sequences obtained into three distinct clades, one with D. immitis and the remaining two with other Onchocercidae spp. Data herein obtained highlight the need for a more comprehensive understanding of the diversity and biology of Onchocercidae in South America in order to assess the potential impact that these species may have for domestic and wild animals, as well as humans.

Sonoran felids are threatened by drought and habitat fragmentation. Vector range expansion and anthropogenic factors such as habitat encroachment and climate change are altering viral evolutionary dynamics and exposure. However, little is known about the diversity of viruses present in these populations. Small felid populations with lower genetic diversity are likely to be most threatened with extinction by emerging diseases, as with other selective pressures, due to having less adaptive potential. We used a metagenomic approach to identify novel circoviruses, which may have a negative impact on the population viability, from confirmed bobcat (Lynx rufus) and puma (Puma concolor) scats collected in Sonora, Mexico. Given some circoviruses are known to cause disease in their hosts, such as porcine and avian circoviruses, we took a non-invasive approach using scat to identify circoviruses in free-roaming bobcats and puma. Three circovirus genomes were determined, and, based on the current species demarcation, they represent two novel species. Phylogenetic analyses reveal that one circovirus species is more closely related to rodent associated circoviruses and the other to bat associated circoviruses, sharing highest genome-wide pairwise identity of approximately 70% and 63%, respectively. At this time, it is unknown whether these scat-derived circoviruses infect felids, their prey, or another organism that might have had contact with the scat in the environment. Further studies should be conducted to elucidate the host of these viruses and assess health impacts in felids.

Ensuring sustainable and resilient agricultural systems in the face of intensifying crop disease threats requires intelligent, data-driven tools for early detection and intervention. This study proposes a novel hybrid framework for potato disease classification that integrates copula-based dependency modeling with a Restricted Boltzmann Machine (RBM), further enhanced through hyperparameter tuning using the biologically inspired Puma Optimization (PO) algorithm. The system is trained and evaluated on a real-world dataset derived from structured field experiments, comprising 52 instances and 42 agronomic, microbial, and ecological variables. By fusing copulabased transformations with PO-driven optimization, the framework effectively models complex nonlinear dependencies among heterogeneous features, enabling high-fidelity probabilistic inference in high-dimensional ecological spaces. The RBM baseline outperformed conventional classifiers such as KNN, Random Forest, XGBoost, and MLP, achieving 94.77% accuracy. With PO-based optimization, performance improved significantly to 98.54% accuracy, with parallel gains in sensitivity, specificity, and F1-score. Statistical analysis using ANOVA and Wilcoxon signed-rank testing confirmed the significance of these improvements (p <0.002). In contrast, convergence analysis demonstrated PO-RBM’s computational efficiency relative to PSO, GWO, and GA alternatives. These findings underscore the utility of the proposed framework as a scalable and ecologically grounded decision-support system for integrated pest management (IPM), offering a practical path toward low-impact, adaptive plant health monitoring solutions.