Distance models as a tool for modelling detection probability and density of native bumblebees

Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombus spp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/ non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp. and other pollinators

Transcriptomic analysis supports similar functional roles for the two thymuses of the tammar wallaby

Background: The thymus plays a critical role in the development and maturation of T-cells. Humans have a single thoracic thymus and presence of a second thymus is considered an anomaly. However, many vertebrates have multiple thymuses. The tammar wallaby has two thymuses: a thoracic thymus (typically found in all mammals) and a dominant cervical thymus. Researchers have known about the presence of the two wallaby thymuses since the 1800s, but no genome-wide research has been carried out into possible functional differences between the two thymic tissues. Here, we used pyrosequencing to compare the transcriptomes of a cervical and thoracic thymus from a single 178 day old tammar wallaby.Results: We show that both the tammar thoracic and the cervical thymuses displayed gene expression profiles consistent with roles in T-cell development. Both thymuses expressed genes that mediate distinct phases of T-cells differentiation, including the initial commitment of blood stem cells to the T-lineage, the generation of T-cell receptor diversity and development of thymic epithelial cells. Crucial immune genes, such as chemokines were also present. Comparable patterns of expression of non-coding RNAs were seen. 67 genes differentially expressed between the two thymuses were detected, and the possible significance of these results are discussed.Conclusion: This is the first study comparing the transcriptomes of two thymuses from a single individual. Our finding supports that both thymuses are functionally equivalent and drive T-cell development. These results are an important first step in the understanding of the genetic processes that govern marsupial immunity, and also allow us to begin to trace the evolution of the mammalian immune system

Distance models as a tool for modelling detection probability and density of native bumblebees

Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombus spp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/ non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp. and other pollinators

Magellanic Woodpeckers in three national parks of central-southern Chile: habitat effects and population variation over the last two decades

A major challenge for protected areas is providing wildlife with enough suitable habitat to cope with stochastic environment and increased pressure from the surrounding landscapes. In this study, we addressed changes in local populations of Magellanic Woodpeckers (Campephilus magellanicus) occupying three national parks of central-southern Chile. We compared the breeding and postbreeding abundance of woodpeckers during the 1990s with the present (2016) abundance (n = 4 years), and assessed the extent to which abundance was explained by forest type and quality of foraging habitat (as quantified through the plant senescence reflectance index; PSRI). Results show a distinctive temporal variation in woodpecker abundance at each park, with local populations of Magellanic Woodpeckers declining by 42.2% in Conguillío National Park, but increasing by 34.3% in Nahuelbuta National Park. Woodpeckers responded to forest conditions within each park such that their abundance increased with high quality of foraging habitat, i.e., large PSRI values, and the presence of old-growth Monkey puzzle (Araucaria araucana) - Nothofagus pumilio mixed forest. Anecdotal evidence suggests that populations of woodpeckers in Conguillío National Park might have responded negatively to large-scale disturbances from recent forest fires affecting part of the forest area within park. Because stochastic events seemed to strongly mediate population changes, our findings suggest that regional conservation of Magellanic Woodpeckers requires expanding the current conservation area network in central-southern Chile

Single-Cell Transcriptomes Distinguish Stem Cell State Changes and Lineage Specification Programs in Early Mammary Gland Development

Summary: The mammary gland consists of cells with gene expression patterns reflecting their cellular origins, function, and spatiotemporal context. However, knowledge of developmental kinetics and mechanisms of lineage specification is lacking. We address this significant knowledge gap by generating a single-cell transcriptome atlas encompassing embryonic, postnatal, and adult mouse mammary development. From these data, we map the chronology of transcriptionally and epigenetically distinct cell states and distinguish fetal mammary stem cells (fMaSCs) from their precursors and progeny. fMaSCs show balanced co-expression of factors associated with discrete adult lineages and a metabolic gene signature that subsides during maturation but reemerges in some human breast cancers and metastases. These data provide a useful resource for illuminating mammary cell heterogeneity, the kinetics of differentiation, and developmental correlates of tumorigenesis. : Single-cell RNA sequencing of developing mouse mammary epithelia reveals the timing of lineage specification. Giraddi et al. find that fetal mammary stem cells co-express factors that define distinct lineages in their progeny and bear functionally relevant metabolic program signatures that change with differentiation and are resurrected in human breast cancers and metastases. Keywords: mammary gland development, stem cells, epithelial lineage specification, single-cell RNA sequencing, cell states, cell fates, heterogeneit