Barriers and corridors: Assessment of gene flow and movement among red panda populations in eastern Himalayas.

Landscape features can impede dispersal, gene flow, and population demography, resulting in the formation of several meta-populations within a continuous landscape. Understanding a species' ability to overcome these barriers is critical for predicting genetic connectivity and population persistence, and implementing effective conservation strategies. In the present study, we conducted a fine-scale spatial genetic analysis to understand the contemporary gene flow within red panda populations in the Eastern Himalayas. Employing geometric aspects of reserve design, we delineated the critical core habitats for red pandas, which comprise 14.5 % of the landscape (12,189.75 Km2), with only a mere 443 Km2 falling within the protected areas. We identified corridors among the core habitats, which may be vital for the species' long-term genetic viability. Furthermore, we identified substantial landscape barriers, including Sela Pass in the western region, Siang river in the central region, and the Dibang river, Lohit river, along with Dihang, Dipher, and Kumjawng passes in the eastern region, which hinder gene flow. We suggest managing red panda populations through the creation of Community Conservation Reserves in the identified core habitats, following landscape-level management planning based on the core principles of geometric reserve design. This includes a specific emphasis on identified core habitats of red panda (CH-RP 5 and CH-RP 8) to facilitate corridors and implement meta-population dynamics. We propose the development of a comprehensive, long-term conservation and management plan for red pandas in the transboundary landscape, covering China, Nepal, and Bhutan.

Evaluating hybrid speciation and swamping in wild carnivores with a decision-tree approach.

Hybridization is an important evolutionary force with a principal role in the origin of new species, known as hybrid speciation. However, ongoing hybridization can create hybrid swamping, in which parental genomes are completely lost. This can become a biodiversity threat if it involves species that have adapted to certain environmental conditions and occur nowhere else. Because conservation scientists commonly have a negative attitude toward hybrids, it is important to improve understanding of the influence of interspecific gene flow on the persistence of species. We reviewed the literature on species hybridization to build a list of all known cases in the order Carnivora. To examine the relative impact, we also noted level of introgression, whether fertile offspring were produced, and whether there was mention of negative or positive evolutionary effects (hybrid speciation and swamping). To evaluate the conservation implications of hybrids, we developed a decision-making tree with which to determine which actions should be taken to manage hybrid species. We found 53 hybrids involving 68 unique taxa, which is roughly 23% of all carnivore species. They mainly involved monophyletic (83%) and sympatric species (75%). For 2 species, the outcome of the assessment was to eliminate or restrict the hybrids: Ethiopian wolf (Canis simensis) and Scottish wildcat (Felis silvestris silvestris). Both species hybridize with their domestic conspecifics. For all other cases, we suggest hybrids be protected in the same manner as native species. We found no evidence of genomic extinction in Carnivora. To the contrary, some species appear to be of hybrid origin, such as the Asiatic black bear (Ursus thibetanus) and African golden wolf (Canis lupaster). Other positive outcomes of hybridization are novel genetic diversity, adaptation to extreme environments, and increased reproductive fitness. These outcomes are particularly valuable for counterbalancing genetic drift and enabling adaptive introgression in a human-dominated world.

La especiación por hibridación es una fuerza evolutiva importante con un papel principal en el origen de una nueva especie. Sin embargo, la hibridación continua puede generar un estancamiento híbrido en el que se pierden por completo los genomas parentales. Esto puede convertirse en una amenaza para la biodiversidad si involucra a una especie que se ha adaptado a ciertas condiciones ambientales y sólo se encuentra en un lugar. Ya que los científicos de la conservación suelen tener una actitud negativa hacia los híbridos, es importante incrementar el entendimiento de la influencia que tiene el flujo interespecífico sobre la persistencia de las especies. Revisamos la literatura sobre la hibridación de especies para generar una lista de todos los casos conocidos en el orden Carnívora. También observamos el nivel de introgresión, si se produjo descendencia fértil y si hubo mención de los efectos evolutivos positivos o negativos (especiación híbrida y estancamiento) para analizar el impacto relativo. Desarrollamos un árbol de decisión con el cual determinar cuáles acciones deberían tomarse en el manejo de las especies híbridas para evaluar las implicaciones que tienen los híbridos para la conservación. Encontramos 53 híbridos de 68 taxones únicos, lo que representa aproximadamente el 23% de todos los carnívoros. Estos híbridos incluyen principalmente a especies monofiléticas (83%) y simpátricas (75%). Para dos especies, los resultados del análisis fueron la eliminación o restricción de los híbridos: el lobo etíope (Canis simensis) y el lince escocés (Felis silvestris silvestris). Ambas especies hibridan con sus coespecíficos domésticos. Para todos los demás casos sugerimos que se proteja a los híbridos de la misma manera que a las especies nativas. No encontramos evidencias de una extinción genómica en el orden Carnívora. Al contrario, algunas especies parecen tener un origen híbrido, como el oso negro asiático (Ursus thibetanus) y el lobo dorado africano (Canis lupaster). Otros resultados positivos de la hibridación son la diversidad genética novedosa, la adaptación a ambientes extremos y el incremento en la adaptabilidad reproductiva. Estos resultados son de valor particular para contrarrestar la deriva génica y permitir la introgresión adaptativa en un mundo dominado por humanos. Evaluación de la especiación y estancamiento en carnívoros silvestres con una estrategia de árbol de decisión.

Microsatellite Characterization and Panel Selection for Brown Bear (Ursus arctos) Population Assessment.

An assessment of the genetic diversity and structure of a population is essential for designing recovery plans for threatened species. Italy hosts two brown bear populations, Ursus arctos marsicanus (Uam), endemic to the Apennines of central Italy, and Ursus arctos arctos (Uaa), in the Italian Alps. Both populations are endangered and occasionally involved in human-wildlife conflict; thus, detailed management plans have been in place for several decades, including genetic monitoring. Here, we propose a simple cost-effective microsatellite-based protocol for the management of populations with low genetic variation. We sampled 22 Uam and 22 Uaa individuals and analyzed a total of 32 microsatellite loci in order to evaluate their applicability in individual identification. Based on genetic variability estimates, we compared data from four different STR marker sets, to evaluate the optimal settings in long-term monitoring projects. Allelic richness and gene diversity were the highest for the Uaa population, whereas depleted genetic variability was noted for the Uam population, which should be regarded as a conservation priority. Our results identified the most effective STR sets for the estimation of genetic diversity and individual discrimination in Uam (9 loci, PIC 0.45; PID 2.0 × 10-5), and Uaa (12 loci, PIC 0.64; PID 6.9 × 10-11) populations, which can easily be utilized by smaller laboratories to support local governments in regular population monitoring. The method we proposed to select the most variable markers could be adopted for the genetic characterization of other small and isolated populations.

Genetic health and population monitoring of two small black bear (Ursus americanus) populations in Alabama, with a regional perspective of genetic diversity and exchange.

One of the major concerns in conservation today is the loss of genetic diversity which is a frequent consequence of population isolation and small population sizes. Fragmentation of populations and persecution of carnivores has posed a substantial threat to the persistence of free ranging carnivores in North America since the arrival of European settlers. Black bears have seen significant reductions in range size from their historic extent, which is most pronounced in the southeastern United States and even more starkly in Alabama where until recently bears were reduced to a single geographically isolated population in the Mobile River Basin. Recently a second population has naturally re-established itself in northeastern Alabama. We sought to determine size, genetic diversity and genetic connectivity for these two populations in relation to other regional populations. Both populations of black bears in Alabama had small population sizes and had moderate to low genetic diversity, but showed different levels of connectivity to surrounding populations of bears. The Mobile River Basin population had a small population size at only 86 individuals (76-124, 95% C.I.), the lowest genetic diversity of compared populations (richness = 2.33, Ho and He = 0.33), and showed near complete genetic isolation from surrounding populations across multiple tests. The newly recolonizing population in northeastern Alabama had a small but growing population doubling in 3 years (34 individuals 26-43, 95% C.I.), relatively moderate genetic diversity compared to surrounding populations (richness = 3.32, Ho = 0.53, He = 0.65), and showed a high level of genetic connectivity with surrounding populations.

AD-LIBS: inferring ancestry across hybrid genomes using low-coverage sequence data.

BACKGROUND: Inferring the ancestry of each region of admixed individuals' genomes is useful in studies ranging from disease gene mapping to speciation genetics. Current methods require high-coverage genotype data and phased reference panels, and are therefore inappropriate for many data sets. We present a software application, AD-LIBS, that uses a hidden Markov model to infer ancestry across hybrid genomes without requiring variant calling or phasing. This approach is useful for non-model organisms and in cases of low-coverage data, such as ancient DNA. RESULTS: We demonstrate the utility of AD-LIBS with synthetic data. We then use AD-LIBS to infer ancestry in two published data sets: European human genomes with Neanderthal ancestry and brown bear genomes with polar bear ancestry. AD-LIBS correctly infers 87-91% of ancestry in simulations and produces ancestry maps that agree with published results and global ancestry estimates in humans. In brown bears, we find more polar bear ancestry than has been published previously, using both AD-LIBS and an existing software application for local ancestry inference, HAPMIX. We validate AD-LIBS polar bear ancestry maps by recovering a geographic signal within bears that mirrors what is seen in SNP data. Finally, we demonstrate that AD-LIBS is more effective than HAPMIX at inferring ancestry when preexisting phased reference data are unavailable and genomes are sequenced to low coverage. CONCLUSIONS: AD-LIBS is an effective tool for ancestry inference that can be used even when few individuals are available for comparison or when genomes are sequenced to low coverage. AD-LIBS is therefore likely to be useful in studies of non-model or ancient organisms that lack large amounts of genomic DNA. AD-LIBS can therefore expand the range of studies in which admixture mapping is a viable tool.

Inferring species divergence times using pairwise sequential Markovian coalescent modelling and low-coverage genomic data.

Understanding when species diverged aids in identifying the drivers of speciation, but the end of gene flow between populations can be difficult to ascertain from genetic data. We explore the use of pairwise sequential Markovian coalescent (PSMC) modelling to infer the timing of divergence between species and populations. PSMC plots generated using artificial hybrid genomes show rapid increases in effective population size at the time when the two parent lineages diverge, and this approach has been used previously to infer divergence between human lineages. We show that, even without high coverage or phased input data, PSMC can detect the end of significant gene flow between populations by comparing the PSMC output from artificial hybrids to the output of simulations with known demographic histories. We then apply PSMC to detect divergence times among lineages within two real datasets: great apes and bears within the genus Ursus Our results confirm most previously proposed divergence times for these lineages, and suggest that gene flow between recently diverged lineages may have been common among bears and great apes, including up to one million years of continued gene flow between chimpanzees and bonobos after the formation of the Congo River.This article is part of the themed issue 'Dating species divergences using rocks and clocks'.

ANIMAL PHYSIOLOGY. Exceptionally low daily energy expenditure in the bamboo-eating giant panda.

The carnivoran giant panda has a specialized bamboo diet, to which its alimentary tract is poorly adapted. Measurements of daily energy expenditure across five captive and three wild pandas averaged 5.2 megajoules (MJ)/day, only 37.7% of the predicted value (13.8 MJ/day). For the wild pandas, the mean was 6.2 MJ/day, or 45% of the mammalian expectation. Pandas achieve this exceptionally low expenditure in part by reduced sizes of several vital organs and low physical activity. In addition, circulating levels of thyroid hormones thyroxine (T4) and triiodothyronine (T3) averaged 46.9 and 64%, respectively, of the levels expected for a eutherian mammal of comparable size. A giant panda-unique mutation in the DUOX2 gene, critical for thyroid hormone synthesis, might explain these low thyroid hormone levels. A combination of morphological, behavioral, physiological, and genetic adaptations, leading to low energy expenditure, likely enables giant pandas to survive on a bamboo diet.

Landscape features influence gene flow as measured by cost-distance and genetic analyses: a case study for giant pandas in the Daxiangling and Xiaoxiangling Mountains.

BACKGROUND: Gene flow maintains genetic diversity within a species and is influenced by individual behavior and the geographical features of the species' habitat. Here, we have characterized the geographical distribution of genetic patterns in giant pandas (Ailuropoda melanoleuca) living in four isolated patches of the Xiaoxiangling and Daxiangling Mountains. Three geographic distance definitions were used with the "isolation by distance theory": Euclidean distance (EUD), least-cost path distance (LCD) defined by food resources, and LCD defined by habitat suitability. RESULTS: A total of 136 genotypes were obtained from 192 fecal samples and one blood sample, corresponding to 53 unique genotypes. Geographical maps plotted at high resolution using smaller neighborhood radius definitions produced large cost distances, because smaller radii include a finer level of detail in considering each pixel. Mantel tests showed that most correlation indices, particularly bamboo resources defined for different sizes of raster cell, were slightly larger than the correlations calculated for the Euclidean distance, with the exception of Patch C. We found that natural barriers might have decreased gene flow between the Xiaoxiangling and Daxiangling regions. CONCLUSIONS: Landscape features were found to partially influence gene flow in the giant panda population. This result is closely linked to the biological character and behavior of giant pandas because, as bamboo feeders, individuals spend most of their lives eating bamboo or moving within the bamboo forest. Landscape-based genetic analysis suggests that gene flow will be enhanced if the connectivity between currently fragmented bamboo forests is increased.

Multiple data sources improve DNA-based mark-recapture population estimates of grizzly bears.

A fundamental challenge to estimating population size with mark-recapture methods is heterogeneous capture probabilities and subsequent bias of population estimates. Confronting this problem usually requires substantial sampling effort that can be difficult to achieve for some species, such as carnivores. We developed a methodology that uses two data sources to deal with heterogeneity and applied this to DNA mark-recapture data from grizzly bears (Ursus arctos). We improved population estimates by incorporating additional DNA "captures" of grizzly bears obtained by collecting hair from unbaited bear rub trees concurrently with baited, grid-based, hair snag sampling. We consider a Lincoln-Petersen estimator with hair snag captures as the initial session and rub tree captures as the recapture session and develop an estimator in program MARK that treats hair snag and rub tree samples as successive sessions. Using empirical data from a large-scale project in the greater Glacier National Park, Montana, USA, area and simulation modeling we evaluate these methods and compare the results to hair-snag-only estimates. Empirical results indicate that, compared with hair-snag-only data, the joint hair-snag-rub-tree methods produce similar but more precise estimates if capture and recapture rates are reasonably high for both methods. Simulation results suggest that estimators are potentially affected by correlation of capture probabilities between sample types in the presence of heterogeneity. Overall, closed population Huggins-Pledger estimators showed the highest precision and were most robust to sparse data, heterogeneity, and capture probability correlation among sampling types. Results also indicate that these estimators can be used when a segment of the population has zero capture probability for one of the methods. We propose that this general methodology may be useful for other species in which mark-recapture data are available from multiple sources.

Bayesian clustering using hidden Markov random fields in spatial population genetics.

We introduce a new Bayesian clustering algorithm for studying population structure using individually geo-referenced multilocus data sets. The algorithm is based on the concept of hidden Markov random field, which models the spatial dependencies at the cluster membership level. We argue that (i) a Markov chain Monte Carlo procedure can implement the algorithm efficiently, (ii) it can detect significant geographical discontinuities in allele frequencies and regulate the number of clusters, (iii) it can check whether the clusters obtained without the use of spatial priors are robust to the hypothesis of discontinuous geographical variation in allele frequencies, and (iv) it can reduce the number of loci required to obtain accurate assignments. We illustrate and discuss the implementation issues with the Scandinavian brown bear and the human CEPH diversity panel data set.