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Systematic paleontologySauropterygia Owen, 186038.Eosauropterygia Rieppel, 199439.Pachypleurosauroidea Huene, 195640.Pachypleurosauridae Nopcsa, 192841.Luopingosaurus imparilis gen. et sp. nov.EtymologyThe genus name refers to the Luoping County, at which the fossil site is located. Species epithet imparilis (Latin) means peculiar and unusual.HolotypeA ventrally exposed skeleton with a posterior part of the caudal missing, IVPP V19049.Locality and horizonLuoping, Yunnan, China; Second (Upper) Member of Guanling Formation, Pelsonian (~ 244 Ma), Anisian, Middle Triassic37.DiagnosisA pachypleurosaurid distinguishable from other members of this family by the following combination of features (those unique among pachypleurosaurids identified with an asterisk): snout (preorbital portion) long and anteriorly pointed, 55.0% of skull length (*); orbital length about one quarter of skull length; internal naris retracted, without contribution from premaxilla; nasal ending at level of anterior margin of prefrontal; dentary length 71.7% of mandibular length; hyoid length 9.7% of mandibular length; presence of entepicondylar foramen in humerus; 21 cervical and 27 dorsal vertebrae (*); distinct expansions of distal heads of posterior two sacral ribs; six pairs of caudal ribs; phalangeal formula 2–3-5–5-3 for manus and 2–3-4–6-4 for pes (*); Metatarsal I short and stout with expanded proximal end, 56.4% of Metatarsal V in length (*); and Metatarsal IV being longest phalange in pes.Comparative descriptionThe holotype and only currently known specimen of Luopingosaurus has a preserved length of 46.2 cm from the rostral tip to the 30th caudal vertebra (for measurements, see Table 1). The estimated total length of the body may have reached 64 cm, assuming similar tail proportions of pachypleurosaurids. As such, Luopingosaurus is longer than most of other pachypleurosauroids that are small-sized with a maximum total length rarely exceeding 50 cm4,9,10,11,12,14,15,16,18,23,25, although some pachypleurosaurids are notably larger (e.g., 88 cm in Diandongosaurus cf. acutidentatus22, ~ 120 cm in Neusticosaurus edwardsii8, and ~ 130 cm in Wumengosaurus delicatomandibularis13).Table 1 Measurements (in mm) of the holotype (IVPP V19049) of Luopingosaurus imparilis gen. et sp. nov. R, right.Full size tableThe pre-orbital portion, distinctly longer than the postorbital region, measures 55% of the total skull length (the premaxillary symphysis to the occipital condyle) and 51% of the mandibular length. The paired premaxillae form most of the snout anterior to the naris with a pointed anterior tip, similar to the conditions in Wumengosaurus13,30 and Honghesaurus23. By contrast, other pachypleurosauroids uniformly have a blunt rostrum4,6,7,8,9,10,11,12,14,15,16,18,22,25. The premaxilla bears a long posteromedial process inserting between the anterior parts of the elongate nasals (Fig. 3). The premaxillary teeth are homodont with a tall peduncle and a short, conical crown, but the tooth number is hard to estimate because of occlusion of jaws. The posterior parts of nasals contact each other medially, and posteriorly, they contact the frontals in an interdigitating suture at the level of the anterior margin of the prefrontal. In Honghesaurus23, Wumengosaurus30, Neusticosaurus8 and Serpianosaurus9, the even longer nasal extends posteriorly beyond this level and ends at the anterior portion of the orbit.Figure 3Skull and mandible of Luopingosaurus imparilis gen. et sp. nov., IVPP V19049. Head before (a) and after (b) dusted with ammonium chloride. (c), Line- drawing. (d, e), two computed laminography scanning slices. (f), reconstruction in ventral view. ac, acetabulum; an, angular; ar, articular; ax, axis; c, cervical vertebra; den, dentary; eo, exoccipital; f, frontal; hy, hyoid; in, internal naris; j, jugal; m, maxilla; n, nasal; p, parietal; par, prearticular; pof, postfrontal; prf, prefrontal; pt, pterygoid; q, quadrate; qj, quadratojugal; sa, surangular; sp, splenial; sq, squamosal; stf, supratemporal fossa; v, vomer.Full size imageThe orbit is oval and large, measuring 24.8% of the skull length (Fig. 3). The lateral margin of the frontal contacts the prefrontal anteriorly and the postfrontal posteriorly, and defines most of the medial border of the orbit. The L-shaped jugal, together with the posterolateral process of the maxilla, forms the lateral border of the orbit. No distinct lacrimal is discernable; the bone is probably absent as in other sauropterygians. The postfrontal contacts the dorsal process of the triradiate postorbital ventrally, and both bones define the posterior border of the orbit. Additionally, the posterior process of the postorbital contacts the anterior process of the squamosal, forming the bar between the supratemporal fossa and the ventrally open infratemporal fenestra. The jugal extends beyond the ventral margin of the postorbital and also contacts the anterior process of the squamosal, resembling the conditions in Wumengosaurus30, Honghesaurus23 and Diandongosaurus15. This contact is absent in other pachypleurosauroids4,6,7,8,9,10,11,12.A pair of vomers and pterygoids and a right palatine are discernable in the palate (Fig. 3a–c). The vomer is elongate and slender, extending anteriorly well beyond the nasal. The internal naris, partly covered by the detached splenial, is longitudinally retracted, corresponding to a retracted external naris (Fig. 3d–f). The medial margin of the naris is defined by the nasal, without contribution from the premaxilla. A retracted naris is otherwise present in Wumengosaurus13,30, Qianxisaurus16 and Honghesaurus23. Similar to the condition in Honghesaurus23, the retracted naris of Luopingosaurus is relatively short, having a longitudinal diameter distinctly less than half of the longitudinal diameter of the orbit. By contrast, other pachypleurosauroids4,6,7,8,9,10,11,12,25 generally have an oval-shaped naris. The elongate palatine has a slightly convex medial margin suturing with the pterygoid. Because of the coverage of the detached splenial, the lateral portion of the palatine is unexposed, and it is hard to know whether an ectopterygoid is present or not. The pterygoid is the largest and longest element of the palate, measuring 55.2% of the mandibular length. It has an anterior projection that contacts the vomer anteromedially, and does not participate in the margin of the internal naris. At the level of the posterior orbital margin, the pterygoid has a triangular lateral extension, which was termed as the ectopterygoid process of the pterygoid in Neusticosaurus8. The pterygoid extends back to the occipital condyle, and covers the basicranium and parietals in ventral view. Additionally, the bone has a broad posterolateral process that is set off from the palatal surface by a distinct ridge, resembling the conditions in Serpianosaurus9 and Neusticosaurus8. Posteriorly, the basioccipital is exposed in ventral view, showing the area for attachment to the right exoccipital.The left quadrate is exposed in lateral view with its dorsal process extending underneath the base of the descending process of the squamosal. The posterior margin of the quadrate is excavated, as in many other pachypleurosaurids (e.g., Serpianosaurus9 and Honghesaurus23). The quadratojugal is narrow and splint-like, flanking the anterior margin of the quadrate. A pair of hyoids are ossified. They are rod-like, slightly expanded at both ends. The dentary is wedge-shaped, being 71.7% of the mandibular length. Laterally, it bears a longitudinal series of pores and grooves parallel to the oral margin of the bone (Fig. 3a). The elongate angular tapers at both ends, contacting the dentary anterodorsally and the surangular dorsally in ventral view. The surangular, slightly shorter than the angular, contacts the articular posterodorsally, with a pointed anterior tip wedging into the notched posterior margin of the dentary. The retroarticular process of the articular is very short with a rounded posterior margin. Medially, the splenial and prearticular form most of the inner wall of the mandible. The splenial tapers at both ends and enters the mandibular symphysis anteriorly, having a length similar to the dentary. The relatively slender prearticular contacts the splenial anterodorsally, extends posteriorly and abuts the articular dorsally, measuring 41.1% of the mandibular length.The whole series of 21 cervical vertebrae (including the atlas-axis complex) is well exposed ventrally. The atlas centrum is oval, much smaller than the axis centrum (Fig. 3c). From the axis, the cervical vertebrae increase gradually in size toward the trunk vertebrae posteriorly. The bicephalous cervical ribs have typical free anterior and posterior processes as in other pachypleurosauroids8,9. The trunk is relatively long, including 27 dorsal vertebrae. The posterior dorsal ribs show certain pachyostosis (Fig. S1). Each gastralium consists of five elements (a short and more massive median element and two slender rods in line towards each side; Figs. 3, 4a, b, S1), similar to the conditions in most of other pachypleurosauroids9,11,18,25 (except Neusticosaurus8). Three sacral ribs are clearly revealed by X-ray computed microtomography (Fig. 4c–f). They are relatively short and stout, with the posterior twos bearing a distinct expansion on their distal heads. The distal expansion of the sacral rib is also present in Keichousaurus11, Prosantosaurus25, Qianxisaurus16 and Wumengosaurus13, but it is not pronounced in other pachypleurosauroids4,6,7,8,9,10. The caudal ribs are relatively few, six pairs in number. Additionally, several chevron bones are visible in the proximal caudal region, and they are gradually reduced in length posteriorly (Fig. 4d).Figure 4Girdles, limbs and vertebrae of Luopingosaurus imparilis gen. et sp. nov., IVPP V19049. Photo (a) and line-drawing (b) of pectoral girdle, forelimbs and anterior dorsal vertebrae. Photo (c), line-drawing (d) and two computed laminography scanning slices (e, f) of pelvic girdle, hind limbs and posterior vertebrae. as, astragalus; ca, caudal vertebra; cal, calcaneum; car, caudal rib; co, coracoid; d, dorsal vertebra; dltp, deltopectoral crest; enf, entepicondylar foramen; fe, femur; fi, fibula; h, humerus; il, ilium; int, intermedium; is, ischium; mc, metacarpal; mt, metatarsal; pu, pubis; s, sacral vertebra; sc, scapula; sr, sacral rib; ti, tibia; ul, ulna; uln, ulnare.Full size imageThe paired clavicles and the median interclavicle form a transverse bar at the 20th cervical vertebrae (Fig. 4a, b). The blade-like clavicle tapers posterolaterally with its distal projection overlapped by the scapula in ventral view. The left clavicle contacts the right one anterodorsally to the interclavicle. The interclavicle tapers laterally to a point at each end. The anterior margin of the interclavicle is convex and its posterior margin is slightly concave without a midline projection (contra the condition in Anarosaurus42). The scapula consists of a broad ventral portion and a relatively narrow and elongate dorsal wing that varies little through its length. The coracoid is hourglass-shaped with a slightly concave posterolateral margin and a conspicuously concave anteromedial margin. The medial margin is straight, along which the coracoids would articulate each other in the midline. The humerus is constricted at the middle portion with a nearly straight preaxial margin and a concave postaxial margin. A slit in the expanded distal portion of this bone indicates the possible presence of an entepicondylar foramen (Fig. 4a, b). The radius, slightly longer than the ulna, is more expanded proximally than distally. The ulna is straight with a slightly constricted shaft. In each forelimb, there is two nearly rounded carpals, ulnare and intermedium; the former is half the width of the latter. Five metacarpals are rod-like, slightly expanded at both ends. Among them, Metacarpal I is the shortest, 48% of the length of Metacarpal II. Metacarpal III is slightly shorter than Metacarpal IV, which is the longest. Metacarpal V is 71% of the length of Metacarpal IV. The phalangeal formula is 2–3–5–5–3 for the manus, indicating presence of hyperphalangy in Luopingosaurus (see Discussion below).In the pelvic girdle, the ilia, pubes and ischia are well exposed (Fig. 4c–f). The ilium is nearly triangular with a relatively long and tapering posterior process. The plate-like pubis is well constricted at its middle portion, with the medial portion nearly equal to the lateral portion. The obturator foramen is slit-like, located at the posterolateral corner of this bone (Fig. 4e). The ischium is also plate-like, having a relatively narrow lateral portion and an expanded medial portion that is notably longer than the medial portion of the pubis. The posterolateral ischial margin is highly concave. The posterior pubic margin and anterior ischial margin are moderately concave, and both together would enclose the thyroid fenestra. The femur is slightly longer than the humerus, with a constricted shaft and equally expanded ends (Fig. 4d). No internal trochanter is developed. The tibia is nearly equal to the fibula in length; the former is straight and thicker than the slightly curved latter. Two ossified tarsals, calcaneum and astragalus, are nearly rounded; the latter is significantly larger than the former. As in Honghesaurus23, the astragalus lacks a proximal concavity. The right metatarsals are well-preserved. Metatarsal I is the shortest and stoutest phalange with an expanded proximal end, and Metatarsal IV is the longest. Metatarsal II is nearly twice the length of Metatarsal I. Metatarsal III is slightly shorter than Metatarsal IV, and Metatarsal V is 76% of the length of Metatarsal IV. The phalangeal count is 2–3–4–6–4, which is complete judging from the appearance of the distal phalanges in the right pes (Fig. 4c). More

Fully terrestrial eDNA sampling approaches offer a potentially powerful addition to biodiversity monitoring efforts23,24. However, protocols for using eDNA-based methods to characterize terrestrial biodiversity, and vertebrate communities in particular, are still nascent27,28,30. In this study, we show for the first time that an eDNA metabarcoding approach can be used to broadly characterize tree-dwelling mammal communities by sampling tree trunks and surrounding soil. Our findings add to recent work (e.g., for reptiles22,24) showing that surface eDNA collection methods, which are relatively untested compared with soil-based eDNA methods, can also be effective at detecting terrestrial vertebrates. Further, we demonstrate that supplementing metabarcoding detection with qPCR-based methods can greatly improve sensitivity, a potentially important consideration for monitoring schemes focused on rare taxa (e.g., Refs.11,12). Together, our results have significant implications for global biodiversity conservation as the broader guild of arboreal vertebrates includes highly threatened5,48,49, as well as invasive alien species50, that are often cryptic, inhabit inaccessible locations, and are therefore challenging to monitor.Our methods captured over 60% of the mammalian diversity expected at the sites, and a similar fraction of the subset of arboreal species, despite sampling only 21 trees. Species accumulation curves suggest that more species would likely have been added with increased sampling effort. These results broadly agree with those of Leempoel et al.23 who found that soil eDNA metabarcoding well characterized mammal communities in California chaparral. However, in both our study and that of Leempoel et al.23, some conspicuous absences were evident. Bats comprised all of the arboreal species that we expected but failed to detect at our sites using metabarcoding (Fig. 1A). Leempoel et al.23 also noted a lack of bat detections (2 of 14 possible taxa detected), which they suggested could be due to low efficiency of either the 12S primer set or of their soil sampling methods for that order. While both reasons could also apply to the lack of bats detected in our study (discussed further below), the performance of the 12S primer set very likely contributed to our lack of American black bear detections as MiMammal-U primers are known to be ineffective at amplifying bear DNA38. These challenges highlight the reality that false negatives and varying detectability among species are common issues to all survey approaches, including eDNA metabarcoding. Our study represents a rare example among metabarcoding studies in that it uses repeated sampling and community occupancy models to quantify false negative rates. This quantitative approach, coupled with continued experimentation with different molecular techniques and survey methods (e.g., Refs.23,27), will be vital to helping researchers decide how eDNA metabarcoding methods will fit into existing biodiversity monitoring efforts moving forward.Although our results suggest that sampling for tree-roosting bats using eDNA metabarcoding still requires further research and optimization, our approach likely has application to characterizing communities in a much broader range of arboreal species globally. Geographic regions with multiple elusive arboreal mammals of management interest—for example, gliders and tree kangaroos in Australasia, or primates in the global tropics—may be particularly suited for a metabarcoding approach for community-level assessments4,8,9,49. It may be especially useful for rapid biodiversity assessments (RBAs51) in remote forested environments, where the ability to collect multiple samples relatively rapidly without regard to time of day would be a key advantage27. Existing survey methods to monitor arboreal mammals tend to be optimized for particular groups of species, often segregated by body size and behavior, with no suitable single method available to characterize all members of the guild4,8,9,16,49. Diurnal and nocturnal species, for example, often require separate survey methods or timing8. While camera traps capture both diurnal and nocturnal species, they typically miss smaller species16,23. The need for multiple methods to survey for nocturnal and diurnal, or large and small, species separately raises the cost of sampling and can result in datasets that are difficult to compare across sites because of inherent sampling biases8. Excluding bats, we found encouraging results for both diurnal and nocturnal arboreal species of a broad range of body sizes, detecting all seven expected species (Fig. 1A). While more work is needed to assemble robust genetic reference libraries before global arboreal mammal monitoring with eDNA metabarcoding will be broadly feasible, a clear advantage of the technique remains the power to detect a broad swath of species, with widely varying morphologies and behaviors, with a single method23,27,28,51.The promise of eDNA metabarcoding approaches for at least some arboreal guilds is well illustrated by our results for southern flying squirrel, Glaucomys volans. Like other flying squirrels (Tribe: Pteromyini), this species is strictly nocturnal, highly arboreal, and tends to get injured in live traps, making it difficult to directly observe and monitor48,52. Yet G. volans eDNA was readily detectable using metabarcoding in our study, occurring in 19–26% of soil samples and 47–52% of roller samples across both sites. Our similarly encouraging results for detecting other squirrels (Sciuridae) also bode well for management applications. For example, the methods would enable fine-scale mapping of habitat use in places such as the United Kingdom where native red squirrels (Sciurus vulgaris) are outcompeted by eastern gray squirrels, or the Delmarva peninsula (USA) to support the conservation efforts for the Delmarva fox squirrel (Sciurus niger cinereus)53. Further research is needed to determine the extent to which our results for squirrels generalize to other taxa with similar active tree-climbing lifestyles (e.g., gliders4, primates49).Our finding that soil samples revealed fewer species, had lower detection probability, and had lower read counts than roller samples, even for some non-arboreal species like white-tailed deer, likely reflects multiple factors. First, soil and tree bark represent markedly different biological and chemical environments that likely differ in eDNA quantity by species, eDNA persistence rates54,55, and microorganism abundance. The latter may be especially pertinent to our study as we observed a relatively large drop in the number of reads after removal of microorganism reads, especially for soil samples. This suggests that performing additional purification steps prior to sequencing could boost the ability of both methods, and especially soil eDNA, to detect target species by increasing mammalian sequencing depth. Other in-lab factors, such as method of extraction23 or choice of primers, similarly have the potential to influence the recovery and amplification of target species’ DNA and should be the focus of future research.Next, our focal trees were not chosen to occur near any special attractants or areas of multi-species use, such as saltlicks or water sources, which has proven successful in other vertebrate eDNA studies18,25,31,32,56. It is possible that adding a broader range of soil sampling sites, including some targeted towards other guilds (e.g., burrow users32,56), would have yielded a more complete inventory. Nevertheless, both soil and surface methods have advantages over the much more commonly-used metabarcoding approaches that rely on natural water bodies for assessing mammal communities16,17,27,28,29,30,38 as they are not limited to where these features occur. Our study is the first to suggest that surface eDNA metabarcoding methods can be a powerful supplement to established soil-based methods of characterizing mammal communities, especially for arboreal species.As noted, bats were especially lacking from our eDNA metabarcoding results, with only two of six likely species detected. Notably, our metabarcoding species list lacked two of the bat species that our sampling scheme was designed around (eastern red bat and northern long-eared bat) and for which we had confirmed recent presence at the sites (Table 1). The lack of northern long-eared bat detections may directly relate to recent precipitous population declines (~ 99%) caused by white-nose syndrome57. However, the lack of eastern red bat detections was especially surprising as roosting of this species was suspected based on telemetry in 17 of our 21 target trees. Reasons for this omission may relate to the fact that eastern red bats roost singly on small twigs and in leaf clusters, and therefore may not leave much DNA on tree trunks. Another possibility is low efficiency of the 12S primer set for bats, although we were unable to find information about this in the literature. It is notable that Leempoel et al.23 had a similarly poor representation of bats with comparable soil-based methods. However, our metabarcoding results did indicate that we are capable of detecting even uncommon, or at least unexpected, bat species with our methods. Eastern small-footed bat, which is typically viewed as a rock-roosting species and is considered endangered by the International Union for Conservation of Nature (IUCN)58, was detected in both soil and surface eDNA samples from Morristown National Historic Park. This species was not otherwise confirmed as present at the site until a year later, in spring 2022, when it was caught in a mist net (BM, unpublished data). Our results with respect to bat detections, along with those of others23, underscore the need for further research to adapt eDNA metabarcoding methods to this vulnerable group, which could contribute much needed demographic and distribution information. This is especially urgent as 18% of bat species are listed as “data deficient” by the IUCN, while 57% lack basic population trend information5,58.Our comparison of qPCR to metabarcoding detection methods for big brown bat represents a hopeful result for the use of eDNA to monitor rare vertebrates that are of particular conservation interest. It is well-known that qPCR-based eDNA surveys targeted towards individual species return higher detection probabilities and have greater power at low abundance, than metabarcoding approaches59. Our results agree, showing for the first time that adding a qPCR step in the analysis of surface and soil eDNA samples can be effective for detecting bats in forested environments. The addition of a qPCR step opens the door for developing species-specific assays to increase detection power for endangered or elusive bat species, or other cryptic arboreal mammals49. Emerging molecular detection approaches such as droplet digital PCR have the potential to increase this sensitivity even further59. Like other eDNA-based tools and survey tools in general, careful consideration of sampling effort, the natural history of target species, and the configuration of different field and molecular methods will be key to optimizing our approach to characterize mammal communities, or to target a particular species, in different regions.Although eDNA surveys are not inexpensive given the need for both fieldwork and molecular analyses, they can be cheaper than conventional approaches, especially if such approaches require many hours of fieldwork or expensive equipment60. Thus, the relative cost-effectiveness of surface or soil eDNA surveys will depend heavily on the mammal communities of interest, the mix of methods that must be employed to effectively sample them, and the purpose of the sampling efforts. However, even if costs are increased, eDNA surveys can reduce field time to the extent that they can improve detection rates, either by replacing or supplementing conventional sampling methods (e.g., as a supplement to visual observations). With higher detection rates, fewer visits are required to achieve the same results. This operational efficiency would be especially advantageous when field conditions present safety risks, are intrusive to sensitive habitats, or are challenging to access. For example, adding surface eDNA sampling to existing visual surveys of eastern wood rats (Neotoma floridana), a cryptic mammal that inhabits steep, rocky slopes in the eastern US, could likely increase detection power, thereby reducing the need for additional risky and costly sampling visits. More studies involving direct comparisons among methods (e.g., Refs.23,24,30,60), in a variety of ecoregions, are needed to determine the extent to which incorporating our methods into existing vertebrate monitoring workflows would increase efficiency.Finally, we detected other vertebrates, including seven birds and one salamander, in soil and surface eDNA samples, despite our use of a mammal-specific primer set. This is similar to results from Leempoel et al.23 in California using the same primer set, in which six bird species were detected. We found that surface eDNA detected more bird species than soil, perhaps for the same reasons as for mammals (above). Our results provide evidence that surface eDNA surveys, with taxon-specific primers, could be used to survey bird communities, or used to target particularly rare species in forested ecosystems (e.g., Ref.61). Our detection of a salamander, coupled with recent promising research into reptile detection using surface eDNA methods22,24 suggests a broader potential for applications with other vertebrates as well. Finally, both surface and soil eDNA metabarcoding can be expanded beyond forests, providing insight into their effectiveness in other habitats (e.g., caves17 or talus slopes). Our study and others highlight that the potential of coupling surface and soil eDNA methods for detecting and monitoring mammalian biodiversity, and terrestrial organisms generally, has yet to be fully realized. More

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Study populationThe study is based on data from mothers and children participating in a longitudinal Southwest Finland cohort, Steps to Healthy development of Children (the STEPS Study) (described in detail in Lagström et al.31). The STEPS study is an ongoing population-based and multidisciplinary study that investigates children’s physical, psychological and social development, starting from pregnancy and continuing until adolescence. All Finnish- and Swedish-speaking mothers delivering a child between 1 January, 2008 and 31 March, 2010 in the Hospital District of Southwest Finland formed the cohort population (in total, 9811 mothers and their 9936 children). Altogether, 1797 mothers with 1805 neonates volunteered as participants for the intensive follow-up group of the STEPS Study. Mothers were recruited by midwives either during the first trimester of pregnancy while visiting maternity health care clinics, or after delivery on the maternity wards of Turku University Hospital or Salo Regional Hospital, or by a letter mailed to the mothers. The participating mothers differ slightly from the whole cohort population in some background characteristics (being older, with first-born child and higher socioeconomic status)31. The ethics committee of the Hospital District of Southwest Finland has approved the STEPS Study (2/2007) and all methods were performed in accordance with relevant guidelines and regulations. Written informed consent was obtained from all the participants and, for children, from one parent for study participation. Subjects have been and are free to withdraw from the study at any time without any specific reason. The STEPS Study have the appropriate government authorization to the use of the National birth register (THL/974/5.05.00/2017).Breastmilk collection and HMO analysisMothers from the STEPS Study were asked to collect breastmilk samples when the infant was approximately 3 months old. In total, 812 of the 1797 mothers (45%) provided a breastmilk sample. There were only slight differences in maternal and child characteristics between the participants providing breastmilk samples and the total STEPS Study cohort40. Altogether, 795 breastmilk samples were included in this study (excluding the duplicate observations and the 2nd born twins, samples with technical unclarity or insufficient sample quantity, one breastmilk sample collected notably later than the other samples, at infant age of 14.5 months (range for the other breastmilk samples: 0.6–6.07 months), one sample with missing information on the date of collection and six mothers missing data on residential green environment) (Supplementary Fig. 2). Mothers received written instructions for the collection of breastmilk samples: samples were collected by manual expression in the morning from one single breast, first milking a few drops to waste before collecting the actual sample (~ 10 ml) into a plastic container (pre-feed sample). The samples were stored in the fridge and the mothers brought the samples to the research center or the samples were collected from their homes on the day of sampling. All samples were frozen and stored at − 70 °C until analysis.High Performance Liquid Chromatography (HPLC) was used to identify HMOs in breastmilk as previously described40,57,58 at the University of California, San Diego (methods described in detail in Berger et al.58). Milk samples were spiked with raffinose (a non-HMO carbohydrate) as an internal standard to allow absolute quantification. HMOs were extracted by high-throughput solid-phase extraction, fluorescently labelled, and measured using HPLC with fluorescent detection (HPLC-FLD)58. Absolute concentrations for the 19 HMOs were calculated based on standard retention times and corrected for internal standard recovery. Quantified HMOs included: 2′-fucosyllactose (2′FL), 3-fucosyllactose (3FL), lacto-N-neotetraose (LNnT), 3′-sialyllactose (3′SL), difucosyllactose (DFlac), 6′-sialyllactose (6′SL), lacto-N-tetraose (LNT), lacto-Nfucopentaose (LNFP) I, LNFP II, LNFP III, sialyl-LNT (LST) b, LSTc, difucosyllacto-LNT (DFLNT), lacto-N-hexaose (LNH), disialyllacto-N-tetraose (DSLNT), fucosyllacto-Nhexaose (FLNH), difucosyllacto-N-hexaose (DFLNH), fucodisialyllacto-lacto-N-hexaose (FDSLNH) and disialyllacto-N-hexaose (DSLNH). HMOs were also summed up to seven groups based on structural features: small HMOs (2′FL, 3FL, 3′SL, 6′SL, and DFLac), type 1 HMOs (LNT, LNFP I, LNFP II, LSTb, DSLNT), type 2 HMOs (LNnT, LNFP III, LSTc), α-1-2-fucosylated HMOs (2’FL, LNFP I), terminal α-2-6-sialylated HMOs (6′SL, LSTc), internal α-2-6-sialylated HMOs (DSLNT, LSTb), terminal α-2-3-sialylated HMOs (3′SL, DSLNT). The total concentration of HMOs was calculated as the sum of the 19 oligosaccharides. HMO-bound fucose and HMO-bound sialic acid were calculated on a molar basis. The proportion of each HMO comprising the total HMO concentration was also calculated. HMO Simpson’s diversity was calculated as Simpson’s Reciprocal Index 1/D, which is the reciprocal sum of the square of the relative abundance of each of the measured 19 HMOs57,59. The higher the diversity value, the more heterogenous is the HMO composition in the sample.Properties of the residential green environmentThe selected residential green environment variables measure the properties of the green environments surrounding the homes of the participants and do not include any measures of the house characteristics, indoor environment or the actual use of green spaces by the participants. The residential green environment variables were selected due to their previously observed associations with residential microbiota and health33,34,35. The variables of the residential green environments were derived from multispectral satellite images series, with a 30 m × 30 m of spatial resolution (Landsat TM 5, National Aeronautics and Space Administration—NASA) and land cover data (CORINE). We used Landsat TM images obtained over the summertime (June–August, greenest months in Finland), to minimize the seasonal variation of living vegetation and cloud cover as well as to better identify vegetation areas and maximise the contrast in our estimated exposure. In each selected Landsat TM 5 images, the cloud was masked out, and the Normalized Difference Vegetation Index (NDVI)36 was calculated. The final NDVI map was the mean of NDVI images collected over three consecutive years (2008–2010), to make an NDVI map with non-missing values due to cloud cover for the study area. NDVI map measures the vegetation cover, vitality and density. The NDVI can get values ranging from − 1 to 1 where values below zero represent water surfaces, values close to zero indicate areas with low intensity of living vegetation and values close to one indicate high abundance of living vegetation. For the analyses, areas covered by water were removed and the value ranged from 0 to 1, to prevent negative values for underestimating the greenness values of the residential area like in some prior studies60. We assumed that summertime NDVI identified the green space and vegetation density well, but greenness intensity might vary seasonally.Second, we used calculated indicators related to the diversity and naturalness of the land cover from CORINE Land Cover data sets of the year 201261. The 12 land cover types include: (1) Residential area, (2) Industrial/commercial area, (3) Transport network, (4) Sport/leisure, (5) Agriculture, (6) Broad-leave forest, (7) Coniferous forest, (8) Mixed forest, (9) Shrub/grassland, (10) Bare surface, (11) Wetland, and (12) Water bodies. From this information, we calculated two vegetation cover indexes. The Vegetation Cover Diversity Index (Simpson’s Diversity Index of Vegetation Cover, VCDI)37, only includes vegetation classes from CORINE land cover types (categories 5–9 and 11). VCDI approaches 1 as the number of different vegetation classes increases and the proportional distribution of area among the land use classes becomes more equitable. Furthermore, because we were particularly interested in the natural vegetation cover in the residential area, we calculated the area-weighted Naturalness Index (NI)38. This is an integrated indicator used to measure the human impact and degree of all human interventions on ecological components. The index is based on CORINE Land Cover data but reclassified to 15 classes. Residential areas have been divided to two classes: Continuous residential area (High density buildings) and Discontinuous residential area (Low density, mostly individual houses area). Agricultural area has also been divided to two classes: Agricultural area (Cropland) and Pasture as well as class 9 (Shrub/grassland) has been separated to Woodland and Natural grassland. Assignment of CORINE Land Cover classes to degrees of naturalness has been made based on Walz and Stein 201438. The area-weighted NI range from 1 to 7, where low values represent low human impact (≤ 3 = Natural), medium values moderate human impact (4–5 = Semi-natural) and high values strong human impact (6–7 = Non-Natural). To ease the interpretation of results and to correspond to the same direction than the other residential green environment variables, we have reverse-scaled the NI values, so that higher values illustrate more natural residential areas.Background factorsAs genetics is strongly linked to HMO composition, maternal secretor status was determined by high abundance (secretor) or near absence (non-secretor) of the HMO 2’FL in the breastmilk samples. Mothers with active secretor (Se) genes and FUT2 enzyme produce high amounts of α-1-2-fucosylated HMOs such as 2′-fucosyllactose (2′FL), whereas in the breastmilk of non-secretor mothers these HMOs are almost absent. Beyond genetics, other maternal and infant characteristics may influence HMO composition. So far, several associations have been reported, including lactation stage, maternal pre-pregnancy BMI, maternal age, parity, maternal diet, mode of delivery, infant gestational age and infant sex22,40. Information on the potential confounding factors, child sex, birth weight, maternal age at birth, number of previous births, marital status, maternal occupational status, smoking during pregnancy (before and during pregnancy), maternal pre-pregnancy BMI, mode of delivery, duration of pregnancy and maternal diseases [including both maternal disorders predominantly related to pregnancy such as pre-eclampsia and gestational diabetes and chronic diseases (diseases of the nervous, circulatory, respiratory, digestive, musculoskeletal and genitourinary systems, cancer and mental and behavioral disorders, according to ICD-10 codes, i.e. WHO International Classification of Diseases Tenth Revision)], were obtained from Medical Birth Registers. Self-administered questionnaires upon recruitment provided information on family net income and maternal education level. Those who had no professional training or a maximum of an intermediate level of vocational training (secondary education) were classified as “basic”. Those who had studied at a University of Applied Sciences or higher (tertiary education) were classified as “advanced”. The advanced level included any academic degree (bachelor’s, master’s, licentiate or doctoral degree). Maternal diet quality was assessed in late pregnancy using the Index of Diet Quality (IDQ62) which measures adherence to health promoting diet and nutrition recommendations. The IDQ score was used in its original form by setting the statistically defined cut-off value at 10, with scores below 10 points indicating unhealthy diets and non-adherence and scores of 10–15 points indicating a health-promoting diet and adherence dietary guidelines. Lactation time postpartum (child age) and season were received from the recorded breastmilk collection dates. Lactation status (exclusive/partial/unknown breastfeeding) at the time of breastmilk collection were gathered from follow-up diaries. From partially breastfeeding mothers (n = 277) 253 had started formula feeding and 28 solids at the time of milk collection. Last, a summary z score representing socio-economic disadvantage in the residential area was obtained from Statistics Finland grid database for the year 2009 and is based on the proportion of adults with low level of education, the unemployment rate, and proportion of people living in rented housing at each participant’s residential area55.Statistical analysesTo harmonize the residential green environment variables we calculated the mean values for NDVI, VCDI and NI in 750 × 750 m squares (and 250 × 250 m) around participant homes in a Geographical Information System (QGIS, www.qgis.org). The same grid sizes were used to calculate residential socioeconomic disadvantage in the residential area55 at the time of child birth. The geographical coordinates (latitude/longitude) of the cohort participants’ home address (795 mothers) were obtained from the Population Register Centre at the time of their child birth.The background characteristics of the mothers and children are given as means and standard deviations (SD) for continuous variables and percentages for categorical variables. Due to non-normal distribution, natural logarithmic transformation was performed for all HMO variables (19 individual components, sum of HMOs, HMO-bound sialic acid, HMO-bound fucose and HMO groups (all in nmol/mL)) except for HMO diversity. Associations between each background factor and HMO diversity and 19 individual HMO components were analysed with univariate generalized linear models to identify factors independently associated with HMO composition. All factors demonstrating a significant association (p  More

Sample collection and postmortem evaluationBald eagle carcasses, and/or oropharyngeal and cloacal swabs were collected in the field and submitted to the Southeastern Cooperative Wildlife Disease Study Research and Diagnostic Service. In some cases, live bald eagles were found moribund and transported to wildlife rehabilitation clinics and either died in transit or soon after arrival. Carcasses underwent postmortem evaluation, including gross and histopathology. Tissue samples [heart, brain, kidney, spleen, lung, adrenal gland, pancreas, liver, small and large intestine, and cloacal bursa (if present)] were fixed in 10% neutral buffered formalin and routinely processed for histopathology23 at the Athens Veterinary Diagnostic Laboratory. Histopathology was assessed by a board-certified veterinary pathologist.Additional bald eagle and waterfowl species mortality dataData on wild bird deaths attributed to highly pathogenic influenza A viruses were retrieved from the U.S. Department of Agriculture, Animal and Plant Health Inspection Service website, at: https://www.aphis.usda.gov/aphis/ourfocus/animalhealth/animal-disease-information/avian/avian-influenza/hpai-2022/2022-hpai-wild-birds. These data are publicly available and include state, county, date detected, and species of individual birds that tested positive for HP IAV.ImmunohistochemistryImmunohistochemistry (IHC) for avian influenza virus was performed in select cases on brain, pancreas, spleen, liver, and/or adrenal gland at the Athens Veterinary Diagnostic Laboratory. IHC was performed on an automated stainer (Nemesis 3600, Biocare Medical). Polyclonal antiserum against influenza A virus was used as the primary antibody (ab155877, Abcam), diluted 1:3000, and incubated for 60 min at 37 °C with agent-positive control. Antigen retrieval was with Target Retrieval Solution (S2367, Dako) pH (10x) at 110 °C for 15 min. Enzyme blockage was via 3% H2O2 for 20 min (H324-500, Fisher Scientific); protein blockage was with Universal Blocking Reagent (10x) Power Block diluted at 1:10 for 5 min (HK085-5 K, BioGenex); link was by biotinylated rabbit anti-goat (BA-5000, Vector) at a 1:100 dilution for 10 min with 4 + streptavidin alkaline phosphatase label for 10 min (AP605H, BioCare Medical). Staining was with warp red chromogen kit for 5 min (WR8065, BioCare Medical). Known influenza A-virus positive control tissues were tested alongside each case.Polymerase chain reactionOropharyngeal and cloacal swabs from bald eagle carcasses were pooled for each individual eagle and tested by real-time reverse transcription polymerase chain reaction (rRT-PCR). Briefly, swabs samples were extracted with the KingFisher magnetic particle processer using the MagMAX-96 AI/ND Viral RNA isolation Kit (Ambion/Applied Biosystems, Foster City, CA) following a modified MagMAX-S protocol24. Resultant nucleic acids were screened against primers specific for H5 IAV in rRT-PCR; samples that yielded a cycle threshold value  More