Sterna forsteri) prey species over an 11-year period by sampling approximately 10,000 prey fish returned to 17 breeding colonies in south San Francisco Bay, California. We compared the species composition among repeatedly-sampled colonies (≥ 4 years), using both relative species abundance and the composition of total dry mass by species. Overall, the relative abundances of prey species at seven repeatedly-sampled tern colonies were more different than would be expected by chance, with the most notable differences in relative abundance observed between geographically distant colonies. In general, Mississippi silverside (Menidia audens) and topsmelt silverside (Atherinops affinis) comprised 42% of individuals and 40% of dry fish mass over the study period. Three-spined stickleback (Gasterosteus aculeatus) comprised the next largest proportion of prey species by individuals (19%) but not by dry mass (6%). Five additional species each contributed ≥ 4% of total individuals collected over the study period: yellowfin goby , longjaw mudsucker , Pacific herring , northern anchovy , and staghorn sculpin . At some colonies, the relative abundance and biomass of specific prey species changed over time. In general, the abundance and dry mass of silversides increased, whereas the abundance and dry mass of three-spined stickleback and longjaw mudsucker decreased. As central place foragers, Forster’s terns are limited in the distance they forage; thus, changes in the prey species returned to Forster’s tern colonies suggest that the relative availability of some fish species in the environment has changed, possibly in response to alteration of the available habitat.Predators sample the available prey community when foraging; thus, changes in the environment may be reflected by changes in predator diet and foraging preferences. We examined Forster’s tern ( Ammodytes marinus) and a switch to a species with lower energy content resulted in decreased breeding success of common guillemots  [Quantifying diet and foraging preferences is important for linking birds with their environment and revealing important prey species and their corresponding habitats. Changes in the environment can be reflected by changes in diet, especially among generalists, because animals often sample the available prey community when foraging –3. Humana aalge) .Bird diet can be challenging to determine, including for adult seabirds provisioning dependent chicks or their mates. Many seabird species nest in locations where direct observation for extended periods is not feasible, expensive, or may cause excessive colony disturbance. Other techniques, such as gastrointestinal tract sampling either involve killing the bird or use of gastric lavage, both of which are invasive. Light stable isotope analysis, using tissues sampled from individual birds, also can be used to estimate diet and foraging behavior , but reqCollecting fish that are returned to seabird colonies, and not consumed, during periodic colony visits is minimally invasive, inexpensive, and can reveal the prey selection of adults provisioning chicks –13. The Sterna forsteri) are a primarily piscivorous species of seabird that breeds on small islands and within marshes in North America [www.southbayrestoration.org) or ecological shifts in the managed pond habitats, could influence tern foraging. A major component of regional restoration involves conversion of former salt evaporation ponds to tidal marsh habitat, which may alter the fish species composition in the habitats adjacent to tern colonies [Forster’s terns  if the species composition of prey items returned to tern colonies varied among colonies and 2) whether the relative abundance, relative mass, and size of the most common prey items changed over time.From 2005 to 2015, we monitored up to 17 Forster’s tern colonies (hereafter colonies) in the southern San Francisco Bay Estuary, mainly located on islands within managed ponds , and entRynchops niger) nest, we are confident that the majority of fish returned to the Forster’s tern colony were brought back by Forster’s terns. We collected all fish and other potential prey items found dropped in the colony during each weekly nest visit and stored samples in reclosable plastic bags. One period of samples from the A16 colony was excluded because it coincided with a major fish kill due to temporarily low dissolved oxygen concentrations in the pond, and because other piscivorous birds were known to be roosting on those islands at that time [During weekly colony visits, we searched for any fish or invertebrates that were on the ground in the colony. Forster’s terns carry prey back to the colony to feed to their chicks or deliver to their mates . Periodihat time . Forsterhat time ,23,25, aMenidia audens) and topsmelt silverside (Atherinops affinis) from the Atherinopsidae family sometimes could not be separated because fish were typically desiccated, which prohibited the use of some identification marks. For example only 5.4% of all Atherinopsidae were identified to species in 2011, whereas > 99% of Atherinopsidae were identified to species in 2005 and 2007. As a result, we combined all Atherinopsidae into one group, silversides, for statistical analyses. We present scientific names of all identified species or the lowest identified taxonomic group in In the laboratory, we identified prey samples to the lowest taxonomic group. Most fish were identified to species although some could only be identified to family. In particular, Mississippi silverside , we substituted a species- and year-specific mean dry mass for those individual fish. Similarly, if we could not obtain an accurate standard length of the dry fish, we substituted the species- and year-specific mean standard length of dried fish. Forster’s terns have been observed to consume fish 10–100 mm in length, with the majority (81%) of freshly-caught fish 50–70 mm in size . For comWe quantified species composition in two ways, one based on species counts (hereafter relative species abundance) and one based on total dry mass of fish species (hereafter dry mass composition), at each tern colony for each year. Then we used a subset of colonies that we repeatedly sampled over time to test whether the relative species abundance and dry mass composition of prey items differed among colonies. Furthermore, we used the same subset of repeatedly sampled colonies to test whether species’ relative abundances changed over the duration of our 11-year study. For these tests, we only used those tern colonies that we sampled repeatedly over the course of the study (during 4–7 different years) and had ≥ 25 fish collected per year.vegan package [A statistic, that describes the effect size of the grouping, and a p value, that quantifies the likelihood that the observed difference is due to chance [A-statistic can be interpreted similarly to the coefficient of determination in a linear model [A = 1. Conversely, A = 0 if within-group heterogeneity equals what is expected by chance [To compare relative species abundance and dry mass composition among colonies, we used a multi-response permutation procedure  in the  package  with the package . This st package . To comp package . Mrpp ano chance ,30. The ar model . If all y chance .p < 0.05), we compared colonies using slope coefficients, standard errors, and 95% confidence intervals produced using the lsmeans package in R [p > 0.05), we dropped the interaction term from the model. For models without a significant interaction effect, we examined pairwise differences in model-generated least squares mean relative abundances if there was a significant colony effect. We used a logit transformation on all proportional data prior to analysis, with the lowest non-zero value (≤ 0.005) as a substitute for all zeros in our dataset [To examine trends in the relative species abundance and dry mass composition of prey items over an 11-year sampling period during the Forster’s tern breeding season, we started globally with a multivariate general linear model (MANOVA) for the proportions of the most abundant prey species, as a function of year, colony, and a year × colony interaction effect. We included the seven species that each comprised > 4% of all samples as dependent variables, with one value per species for every year and colony combination. The year × colony interaction effect provided the ability to test for overall differences in slope coefficients among colonies. After running the global MANOVA, we ran individual univariate linear models for each species with the same fixed effects to determine the source of the significance at the global level. If the interaction term for a specific species was significant . We examined each fish species separately for standard length and log-transformed mass. For each species, we first compared three models with year as a fixed effect and different random effects to determine whether our data were best explained by 1) a random intercept and slope model that allowed both the intercept and slope to vary by colony, 2) a random intercept model that allowed the intercept to vary by colony, or 3) a model with no random terms. We fit each model using restricted maximum likelihood (REML) and used the AIC values to select the best model. The best models to examine temporal trends of fish size for all seven species included a random intercept for colony. The only exception was for standard length of staghorn sculpin, where the best model did not include random effects. Therefore, we present only the results for the best models. We used the  freedom .Gasterosteus aculeatus) were the second most abundant species (18.6%) followed by yellowfin goby , longjaw mudsucker , Pacific herring , northern anchovy , and staghorn sculpin . Other species of goby (Acanthogobius spp), rainwater killifish (Lucania parva), and perch species (family Embiotocidae) each comprised < 2% of total fish collected. Additional fish species and fish that were unable to be identified, comprised 2.5% of total individuals collected. Over the course of the study, other fish species that were identified at tern colonies included black crappie , bluegill , California roach , common carp , largemouth bass , bay pipefish , prickly sculpin , salmonids , starry flounder , and western mosquitofish ; however, the proportional contribution of the remaining groups differed between dry mass composition and their relative abundances Figs  and 3. A9.7%; howThe most prevalent size class (dry standard length) of fish delivered to tern colonies was 50–75 mm (52.1%), followed by 25–50 mm (28.8%), and then 75–100 mm (16.9%). Fish > 100 mm comprised only 1.7% and fish < 25 mm comprised only 0.5% of all fish recovered at tern colonies. Among species, northern anchovy had the greatest mean (± SD) dry standard length (72 ± 12 mm), followed by staghorn sculpin (71 ± 12 mm), yellowfin goby (70 ± 16 mm), longjaw mudsucker (66 ± 16 mm), silversides (64 ± 13 mm), perches (63 ± 13 mm), Pacific herring (55 ± 10 mm), other gobies (52 ± 22 mm), three-spined stickleback (39 ± 7 mm), and rainwater killifish . Among colonies, the relative fish species abundance was the most consistent among years at A2W (δ = 0.32) and A1 (δ = 0.32), followed by AB2 (δ = 0.34). Notably, each of these three tern colonies are located adjacent to each other in the Moffett pond complex. The relative prey fish species abundance at A8, a colony located in Alviso, was the least consistent among years . The dry mass composition was most consistent among years at the A2W (δ = 0.30), A1 (δ = 0.33), and A16 colonies . However, unlike for relative species abundance, the dry mass composition at A7 was marginally indistinguishable from AB1 . In addition, the A8 colony was not different from the A7 or A16 colonies . The A16 colony was the only colony that had a marginally negative slope coefficient . Given the slope coefficient and the substantial restoration actions that occurred at this colony at the start of our study that increased tidal exchange and decreased salinity [t ≥ 2.10, df = 27, p ≤ 0.05). Run separately, there was not enough evidence to show a change in the relative abundance of silversides at A16 over time . For stickleback, the significant interaction  was also being driven by A16, as it had a positive slope coefficient that was significantly different than all of the other colonies . Overall, the relative abundance of stickleback decreased when we excluded A16. In contrast, stickleback showed a marginally non-significant increase at A16 . The relative abundance of longjaw mudsucker decreased at all colonies from 2005 to 2015 and varied among colonies. With the exception of A8, the mean relative abundance of longjaw mudsucker at the Alviso colonies was ≥ 4.3 times greater than at the Moffett colonies . Additionally, the mean relative abundance of mudsucker at A8 was ≥ 3.1 times greater than at two of the Moffett colonies, AB2 and A1 . We did not observe any overall increase or decrease in the relative abundance of Pacific herring or northern anchovy over time, although the relative abundance of northern anchovy was ≥ 3.6 times greater at two of the Moffett colonies (A1 and AB1) than the Alviso colonies . The relative abundance of staghorn sculpin had less clear overall temporal trends, with an increase at one Alviso colony  and a decrease at one Moffett colony . There were no clear temporal trends for staghorn sculpin at the other colonies.The relative abundance of certain prey species changed from 2005 to 2015 at some Forster’s tern colonies in San Francisco Bay  was being driven by A16, as it had a positive slope coefficient . When A16 was removed, the relative mass of stickleback decreased from 2005 to 2015. Run separately, stickleback showed a marginally non-significant increase at A16 . Whereas there were no overall differences in the relative mass of silversides and stickleback among colonies, the three Alviso colonies had ≥ 15 times the relative mass of longjaw mudsucker than at the A1 colony in Moffett . For both yellowfin goby and staghorn sculpin, we observed an increase in the relative mass at A16 . Additionally, yellowfin goby increased at AB2  and staghorn sculpin declined at AB1 . We did not observe any overall temporal trends in relative dry mass for northern anchovy or Pacific herring or differences among colonies.Similar to relative abundance, the relative dry mass of some prey species changed from 2005 to 2015 at Forster’s tern colonies in San Francisco Bay  and 6.6% in dry mass . Similarly, northern anchovy decreased annually by 1.0 mm in standard length  and 3.2% in dry mass . Silversides, the most commonly observed species group returned to Forster’s tern colonies, decreased in length annually by 0.2 mm  but did not change in dry mass . In contrast, three-spined stickleback did not change in standard length  but decreased annually by 5.3% in dry mass . Yellowfin goby was the only species that demonstrated an increase in size, by 1.1 mm/yr in standard length  and 4.8% annually in dry mass . Longjaw mudsucker and Pacific herring did not change in standard length  or dry mass .Several fish species returned to Forster’s tern colonies changed in size from 2005 to 2015, with most changes suggestive of an overall decrease in fish body size. The average staghorn sculpin decreased annually by 1.8 mm in standard length  were the predominant prey species returned to Forster’s tern colonies in San Francisco Bay over an 11-year period. Silversides comprised more than twice that of the next most common species, both by relative abundance of individuals (42%) and relative dry mass (40%). Three-spined stickleback were the second most common species returned to Forster’s tern colonies (19% relative abundance) over the entire study. Previous fish sampling studies revealed that topsmelt silverside were present in all sampled ponds and sloughs in south San Francisco Bay, and comprised the majority of fish collected in gillnets from 2004–2006, while three-spined stickleback were the most abundant fish species sampled using minnow traps in ponds sampled in 2006 . These oSterna antillarum browni), where 70% of the diet was comprised of silversides and northern anchovy [Menidia menidia) were suggested to be an important prey item of Forster’s terns on the Atlantic coast, as they comprised 99.6% of samples collected in a seine adjacent to observations of foraging terns [Perca flacescens) and shiner (Notropis spp.) were the most important species in courtship and chick feedings by Forster’s terns, and these two species groups comprised 97% of species collected in seines; Atherinopsidae was not represented by any species in this study [The prey species returned to Forster’s tern colonies had similarities with coastally-foraging California least terns  to colonize, which resulted in a salt-related gradient of species observed from the upstream reaches of the sloughs down to the saltier ponds [www.southbayrestoration.org).We observed temporal differences in the fish returned to Forster’s tern colonies in San Francisco Bay over the 11-year sampling period, suggesting relatively localized changes in relative prey availability and the size of some prey species. Generally, the relative abundance and dry mass of silversides increased over time. Additionally, the average silverside decreased in size by 1.2 mm over our study but did not change in mass. Concurrently, we observed a decrease in the overall relative abundance and dry mass of three-spined stickleback and longjaw mudsucker returned to tern colonies. In contrast to silversides, the average three-spined stickleback decreased in dry mass by 5.3% annually  but dider ponds . Furtherer ponds . ConsequBreeding Forster’s terns are central place foragers that tend to feed within 6.2 km of their breeding colony ; therefon = 69), suggesting that Mississippi silverside had not yet colonized this pond. As the salinity decreased in pond A16, this may have allowed other species, such as three-spined stickleback, to colonize and increase in relative abundance over time.Two of the repeatedly sampled colonies stood apart from the others in terms of the intra-colony species heterogeneity (A8) and temporal trends (A16), which may have been a direct result of altered management practices at those sites or differences in available foraging habitat. Previously, breaching of levees in the south and north regions of San Francisco Bay caused changes in species assemblages as connectivity between habitats was increased and salinity levels changed ,21. In oChanges in prey availability and diet could have important implications for Forster’s terns in the San Francisco Bay Estuary, such as reproductive success and contaminant exposure. In particular, mercury contamination is known to be an important issue for waterbirds breeding within the estuary . The higForster’s terns breeding in the San Francisco Bay area relied heavily on surface-dwelling silversides and our results showed that their dependence on these fishes has increased. As central place foragers, the fish returned to Forster’s tern colonies suggest that there were differences in relative prey availability among colonies and over time. The abundance of three-spined stickleback and longjaw mudsucker returned to Forster’s tern colonies decreased at multiple colonies, suggesting that their relative availability in the environment also has declined, possibly in response to habitat alteration. Future studies could evaluate if changes in diet among colonies and over time has resulted in differential reproductive success and contaminant exposure.


Where do people live, and how has this changed over timescales of centuries? High-resolution spatial information on historical human population distribution is of great significance to understand human-environment interactions and their temporal dynamics. However, the complex relationship between population distribution and various influencing factors coupled with limited data availability make it a challenge to reconstruct human population distribution over timescales of centuries. This study generated 1-km decadal population maps for the conterminous US from 1790 to 2010 using parsimonious models based on natural suitability, socioeconomic desirability, and inhabitability. Five models of increasing complexity were evaluated. The models were validated with census tract and county subdivision population data in 2000 and were applied to generate five sets of 22 historical population maps from 1790–2010. Separating urban and rural areas and excluding non-inhabitable areas were the most important factors for improving the overall accuracy. The generated gridded population datasets and the production and validation methods are described here. Such ecological and societal consequences vary across space. Human population density is considered to be a useful indicator of the type and intensity of the human environment interaction, with higher population density leading to higher levels of impacts4–7. Therefore, it is vital to create reliable spatially explicit, high-resolution estimates of the human population distribution to advance our understanding of coupled human and natural systems, to provide support to policy decision-making, and to achieve ecological and socioeconomic sustainability8.Human actions have caused substantial alterations to the Earth, transforming the landscape, affecting ecosystem patterns and processes, driving biodiversity loss, altering global hydrological and biogeochemical cycles, amplifying resource exploitation and environmental deterioration, and contributing to climate change10. For the conterminous US, census data are available at the county level from 1790 to 2010 14, the Global Rural Urban Mapping Project (GRUMP)15, LandScan16, and WorldPop17.Census data have been routinely collected and applied, however, such data are ascribed to defined administrative units, leading to abrupt changes in population at the administrative boundary, and masking of spatial heterogeneity within administrative units010 ref. . These d18–21. Similar challenges from insufficient data availability occur in estimating historical population distributions. The high resolution mapping efforts described above were all developed based on modern census data since 1990, and are of limited utility for long-term  dynamic analyses23. A notable exception is the History Database of the Global Environment (HYDE)24. While the temporal range from HYDE is vast (from 1000 BC to 2005 AD), the 10-km spatial resolution is relatively low, constrained by input census data.A recent challenge has been to map the human population distribution in low income nations, where detailed updated census data or high resolution geospatial data are lacking25–27. Land use/land cover data, derived from remote sensing images, best reflect population density and have been suggested as an important source for human population mapping28. However, such imagery data only became available beginning with the launch of the first land satellite, Landsat-1, in 1972. Several global land cover datasets29–33 have used census data as an input or a proxy for human activities to simulate the spatial map of anthropogenically managed land . However, it would be circular and infeasible to use such derived land cover data to model population distribution.Major influencing factors that have been considered in human population mapping include land cover, night lights, topography, urban areas, and roads21, we use county-level census data, as this is the highest resolution data consistently available from 1790 to 2010. Despite the scarcity of reliable historical land cover maps, the separation of urban and rural settlement areas could significantly improve the accuracy of population distribution mapping19, since 80.7% of the US population lived in urban areas, which covered only about 3.1% of the total land area, according to the 2010 US census34. Power-law scaling relationships35 between urban area and population were applied to estimate historical urban areas. Additional data including elevation, water bodies, and protected areas were used to allocate population to urban and rural areas within counties. Five models of increasing complexity, from one (M1) to eight variables (M5), were developed to model population distribution. The models were validated with measured data from 2000 based on comparison with census data at the tract and county subdivision levels, and applied to generate five sets of 22 historical decadal population maps from 1790–2010 . The model-generated urban extents were also assessed in two fast-growing regions in which historical data were available37: San Francisco/Sacramento and Baltimore/Washington DC.The goal of this study is to generate spatially explicit human population distribution maps for the conterminous US that could be used to advance studies of anthropogenic effects on the environment, and to provide support for policy decision-making. Recognizing that the spatial resolution of census administrative boundaries is the principal factor affecting map accuracyhttps://www.nhgis.org/)38, were used: total and urban population at county level (1790–2010), county subdivision population (1980–2010), census tract population (1990–2010), and population for urban areas (2000 and 2010). Note that American Indians were not fully included in the census prior to 1900  (900 ref. . Our res900 ref. .http://nhd.usgs.gov/). Protected areas data (version 1.3), designated to preserve biological diversity and other natural, recreation and cultural uses, were released in 2012 and obtained from National Gap Analysis Program . Digital elevation model data (http://www2.jpl.nasa.gov/srtm/), with a resolution of 90 m. Historical data on urban spatial extents for San Francisco/Sacramento and Baltimore/Washington DC region37 were from the USGS Land Cover Institute (LCI).Waterbody data , including lake/pond features, swamps/marshes, reservoirs, playas, estuaries, and ice mass, were completed in 2001 and derived from the National Hydrography Dataset (del data  were relk) in each decade (t) from 1790 to 2010 (excluding 1960). The data were variously applied over the following spatial units: urban area (φ), census tract (c1), county subdivision (c2), county (i), census division (δ), and Region (μ). There were 9 census divisions (δ: D1 – D9) and 7 Regions (μ: R1 – R7) with constant boundaries over time, while the number of other spatial units varied with the expansion of human settlements and the modification of administrative boundaries. For example, the number of counties increased from 292 in 1790 to 3109 in 2010. Also, in 2010, there were 7,754 146 pixels (1 km2), 72,271 census tracts, 35,532 county subdivisions, and 3,535 urban areas in the conterminous US.The above data were used to compute population for each inhabited pixel (PT) and aggregated urban population (PU) for each urban area (φ) determined the remaining rural population (PR) by difference, for each county (i) from 1790 to 2010 :https://www.census.gov/geo/reference/ua/urban-rural-2010.html).Decennial census data on total population (AU) for all of the 3610 urban areas. However, areal extents are incomplete for 1990 and largely unknown in prior decades. The 1990 NHGIS data cover only 396 large urban areas with population larger than 50,000. Thus, the 2000 data were used as a baseline for historical backward projections of urban areal extents. The areal extent of each urban area (φ) in a census division (δ) prior to 2000 was estimated on the basis of a power law scaling relationship with its population PU,φ35:αδ and βδ are the proportionality coefficient and scaling factor for census division δ estimated by fitting log(AU) and log(PU) in 2000 according to AU) and log(PU) have been identified based on modern satellite imagery and census data40–43, and also observed in ancient settlements, for example, the Pre-Hispanic settlements in the Basin of Mexico44. Our hypothesis was that this scaling was stable and could be used to reconstruct historical settlement patterns. Empirical studies45 have revealed spatial variation of β values: 0.375 for England and Wales, 0.914 for Japan, 1.38 for China, and larger than 2/3 for US urbanized areas . Spatial variation of β was incorporated here by developing such relationships for each census division, δ. However, the lack of corresponding AU and PU data for urban areas before 2000 precluded further evaluation of the temporal stationarity of β. Thus, the scaling relationships were considered stable for simplicity, with constant parameter values over time. The extent of rural areas (AR) within each county (i) was determined as the difference between the county total area (AT) and the aggregated extents of all urban areas in the county:The 2000 census includes full coverage of areal extent (Two simplifying assumptions were further made to delineate the extent of each urban area over time: 1) urbanization was monotonic, with historically established urban areas still extant in 2000; 2) urban areas developed outward from their center, so regions farthest from the center would urbanize last. The urban extents for each urban area in each decade were delineated by concentrically shrinking inward towards their center moving backward with time from 2000, with the remainder considered as rural areas.w) of each factor for each pixel (k) is explained below. Note the influence coefficients for inhabitability (wk0) and topographic suitability (wk1) were steady over time, while the influence coefficient for socio-economic desirability (wk2) changed with the urbanization process.Inhabitability, topographic suitability, and socio-economic desirability were the three major factors considered to influence human population distribution. The calculation method for the influence coefficient  with population densityi and μ denote county and Region illustrated in PDi and zi are population density and mean elevation for county i, and bμ and mμ are fitting parameters for Region μ.Elevation has a relatively larger variation and better resolution within counties compared to other natural factors, including temperature and precipitation, and plays an important role in influencing population distributionwk1, for pixel k from the following relationk is elevation for pixel k. Only inhabitable areas were considered when calculating population density. To minimize the number of model parameters, geographically adjacent census divisions and states with similar mμ values from μ: R1 – R7, shown in zi and In (PDi). Two regions correspond to census divisions (R1 and R2), one includes only one state , two comprise multiple contiguous states (R3 and R4), and two are composed of one census division plus multiple neighboring states (R6 and R7). No significant relationship was found for Colorado  were found for all regions except 100 m<z<300 m in R4  and rural (R) areas separately. Urban population density decreases with increasing distance from the urban center. This trend has been described simply with an exponential decay model47, but with growing attention on fractal cities, an inverse power function has been used more recently48–50. Here, we used the inverse power function to describe how the influence coefficient of socioeconomic desirability wk2 for urban pixels (k∈U) changes across space.rkφ is radial distance from the center of urban area φ to the pixel k, and λδ is density gradient for division δ. We applied the following relation suggested by recent studies52 to link parameter λδ from socioeconomic desirability with the urban area-population scaling factor βδ from βδ, λδ values were calculated for divisions and regarded as constant over time.We considered socioeconomic desirability for urban  was determined using a gravity model of market potential53Nφ is the number of urban areas that are within the maximum urban influence distance in decade t, Dt (rkj≤Dt), corresponding to daily per capita travel range which exponentially increased due to transport technology evolution from 30m in 1790 to 100 km in 2000  or rural (R) pixel, and the exponents s and d weight the relative importance of topographic suitability and socioeconomic desirability on population mapping. The latter two parameters were calibrated to obtain the highest mapping accuracy with values evaluated between 0.2 and 3 for each division . M1 simply allocated census county population homogeneously within counties. M2 separated urban and rural areas, and then homogeneously allocated urban and rural population within urban and rural areas, respectively. M3 excluded non-inhabitable areas, including waterbodies, protected areas, highlands, and low population census tracts. M4 extended Model 3 with the addition of topographic suitability. M5 added socio-economic desirability. From M3 to M5, the population distribution maps were obtained by multiplying the population raster by the normalized weighting grid, with each subsequent model contributing an additional influence coefficient to the previous model. The most complete model (M5) included all coefficients as shown in the following equationdivision  and 3. E2, which represented 12.6% of the tracts and 9.7% of the total population for the conterminous US in 2010. We supplemented the tract analysis with reference data at a coarser level, county subdivision, from 1980 to 2010, to achieve a more comprehensive validation and also to assess the accuracy based on reference data at different geographic scales. We again used only county subdivisions with areas larger than 1 km2 .All five models, M1 - M5, were applied to map historical population from 1790 to 2010 (excluding 1960) (Data Citation 1). The best way to assess the accuracy of population distribution maps is to compare them with census data at a finer level than was used for the model input. While the county level input data were already the finest resolution that was available consistently throughout the temporal range of interest, higher resolution census tract data with full coverage of the conterminous US were available from 1990 to 2010, and these were used as a primary reference here. Note that the spatial resolution of our population products precluded validation for census tracts with area less than 1 kmc is reference data geographic unit (census tract or county subdivision), Nc is the number of evaluated units in the conterminous US or census division, Mc is modeled population aggregated for unit c, and Oc is observed population from census data.We generated gridded population data based on county level data and then aggregated population grids by census tracts and county subdivisions to compare them to census data at the corresponding level. We applied mean absolute relative error (MARE) to assess the overall performance of the 2000 population products for the conterminous US and each census division37 developed historical urban extents for two fast-growing regions: San Francisco/Sacramento and Baltimore/Washington DC. Those investigators mapped urban land use change and produced maps from 1900 to 1996 for San Francisco/Sacramento and from 1792 to 1992 for Baltimore/Washington DC. Therefore, the historical urban extents for these regions reconstructed in this study for the closest corresponding years were compared to the USGS LCI results to test the validity of the scaling relationships and the urban area delineation method. We used the relative overlap of urban pixels between our results and those from USGS LCI as an accuracy indicator. Note that the minimum population threshold used to define urban areas in the USGS LCI studies was 500 people, but we constrained our comparison to include only the areas with more than 2500 people, to be consistent with our threshold for urban areas.The five models were assessed in terms of both accuracy and effectiveness. We used MARE to compare model accuracy, with lower MARE values indicating better model performance. Model effectiveness was determined from the importance of the added influence factors based on the magnitude of MARE reduction compared to the previous model. We made full use of the available fine-resolution census population data and assessed the accuracy of the model-generated historical population maps for the conterminous US based on census tract data from 1990 to 2010 and county subdivision data from 1980 to 2010. Furthermore, we assessed the accuracy of our generated historical urban extents for selected regions. There is currently no historical (urban) land use database for the USA from 1790 to present. However, the USGS LCIet al.58 used only four urban areas to validate population products for the entire mainland of China, and Sorichetta et al.18 used six countries for accuracy assessment of population products for 28 countries in Latin America and the Caribbean.Finally, we note that accuracy assessments for population products are commonly conducted using partial datasets due to the availability of higher resolution reference data. For example, Gaughan The reconstructed high-resolution historical human population dataset for the conterminous US from 1790 to 2010 (excluding 1960) are available on figshare, including five sets of population products derived from M1 to M5 . The data can be downloaded in Esri grid format for each decade at a resolution of 1 km, with the values representing the human population per pixel cell.The spatial details generated by M1 to M5 are illustrated in 2 and 4310 persons in 2000. Based on our validation using census tract population for year 2000 (δ: D1 - D9), model accuracy showed similar improving trends from M1 to M5, except M2 for D4 and D9. The model performed worst for D2, however, this division also showed improved performance with increased model complexity.Census tract population data was considered as the primary reference for validation due to its higher resolution, with mean area and population of 120 kmear 2000  for the 2 and 7932 persons) resulted in similar overall results, but with higher accuracy, indicated by smaller MARE values for Models 1 to 5 , M2 required the addition of urban population (PU) and extent of urban areas (AU) for a total of 3 variables, M3 added inhabitable area for 4 variables, M4 also included topography and its relative importance (s) for 6 variables, and M5 added socioeconomic desirability and its relative importance (d), culminating in 8 variables.The improved accuracy found above was achieved by the increased complexity from M1 to M5. Models 1 to 5 increased in complexity by adding additional input data. M1 required only one data set  using the scaling relationship between urban area and population. We illustrated the urban extents for Baltimore/Washington DC and San Francisco/Sacramento regions from our reconstructed results for the closest corresponding years and the USGS LCI results in Historical population distribution was reconstructed for the conterminous US from 1790 to 2010 (excluding 1960). Validation is only possible beginning with the available data. For census-tract-based validation (1990-2010), since Models 3 to 5 were calibrated based on 2000 population data, their accuracy for 1990 was unsurprisingly lower than the 2000 output. For example, for M5 MARE values were 2.1 and 1.5 for the conterminous US in 1990 and 2000, respectively . Using tThe dataset generated here provided ready-to-use historical population maps in the conterminous US from 1790 to 2010 at the resolution of 1 km. Our study showed the validity of applying scaling relationships between urban area and urban population to reconstruct historical urban areas, and the effectiveness of modeling spatio-temporal population distributions using existing data. Our backward projection was not just based on current population information but historical population data obtained from NHGIS, which provided accurate information about human settlement and population density at county level and served as a foundation to further disaggregation of population within administrative units. The high resolution of the input census population data, the separation of urban and rural extents, and use of inhabitability, elevation, and socioeconomic desirability influencing factors all contributed to the good accuracy of the final products.Our final output included five sets of historical population products from 1790 to 2010 reconstructed based on models M1 to M5. Generally, model accuracy improved with increasing complexity. According to the census-tract-based validation, we proposed M5 as the most accurate and M3 as the most efficient, while the county-subdivision-based validation suggested M4 as the most accurate and M2 as the most efficient, largely because the larger size of county subdivisions masked the effect of additional factors included in more complex models. Therefore, we suggest that users consider their study units when selecting the model products. Also, we suggest applying the efficient models when transferring our approach to other regions, and adopting the most accurate models when directly applying our model-generated population products. Additionally, considering the varied model performance among the divisions, we caution users to choose the most appropriate products based on their specific study regions.16. Similar to our method, Landscan16 and population modeling for Asia19 and Africa21 also applied multiple ancillary variables and allocated population using associated weights. However, land cover data, which were not available over the long time scales of interest in this study, were the major input for their modeling. Landscan did not provide details on their modeling methods19. The population mapping influence coefficients previously developed19–21 were based on fixed values of population density for specific land covers, while those we developed as continuous functions of elevation, urban proximity, and market potential , precluding their direct inclusion in our models. However, the effect of the transport technology evolution was indirectly reflected in our models through the growth of the daily travel range in the gravity model of market potential. The availability of temporally dynamic data limited the selection of influencing factors. We aimed to apply consistent techniques over time to make the final products appropriate for dynamic analysis.Natural factors other than altitude, including temperature and precipitation, were excluded because of their relatively small variation within most counties. However, altitude was found to be an important factor to account for intra-county natural suitability variability. We further emphasize that our validated population products used the same method for the entire conterminous US, with no significant accuracy differences in the East and West. Another important factor that could be considered more explicitly in extensions to this work is transport networks, given their significant role in influencing human population distribution. Transport networks have evolved over time, shifting from rivers and canals, to roads and railroads, and then to air transportOur historical population products were generated and validated based on census population data. This data-based approach was therefore subject to the limitation of the currently available census data. First, we did not consider American Indians in our population distribution reconstruction since census data did not include American Indians prior to 1900. It is still a challenge to collect and confirm population numbers for American Indians due to the sparse and inconsistent record. Second, urban areas are defined based on a population threshold of 2500, however, areas with less than 2500 people in the past could have held a role similar to modern urban areas. Our reconstruction thus might underestimate the attractiveness of smaller urban areas. Third, lack of high resolution historical data constrained a comprehensive validation dating back to 1790. Our historical population products prior to 1980 can be validated when more detailed census data become available. Despite these limitations, the population data from US Census Bureau are the best currently available source for data-driven analyses.β, and steady inhabitable areas. The first two assumptions were used to reconstruct historical urban areas and the third was applied to determine the influence coefficient of inhabitability. While individual urban development patterns may often deviate from the first assumption , simplifications were necessary to develop efficient models that could be feasibly applied to the large spatial and temporal scale of our study. This assumption could lead to varied impacts on model accuracy for specific cities with different development patterns. However, we found that the dynamic urban extents we generated reflect the general pattern of urban areas based on comparison with measured data available for two fast-growing regions, Baltimore-Washington DC dating back to 1792 and San Francisco/Sacramento dating to 1900  with β=0.86 .Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Gadus morhua) bones. In the current study we use Atlantic cod otoliths from archaeological excavations of a historical fishing sites in north-west Iceland, dated to AD 970 –AD 1910 to examine historical growth trajectories of cod. No large scale growth variations or shifts in growth patterns were observed in the current chronologies, supporting the stability of historical Atlantic cod growth trajectories. The most significant variation in growth patterns was consistent with those that have been observed in recent times, for example, reduced early juvenile growth during periods of colder ocean temperature. The current results represent a high resolution chronological record of north-east Atlantic cod growth, greatly increasing the prior temporal range of such data, thereby providing a valuable baseline for a broad range of studies on Atlantic cod growth.Archaeological excavations of historical fishing sites across the North Atlantic have recovered high quantities of Atlantic cod ( Historical baselines of ecological states can improve the interpretation of current anthropogenically induced change. Such baselines have already shown their value as a guide to modern day management and conservation . RecordsOtoliths, a calcified structure in the inner ear of fish, are occasionally recovered during archaeological excavations . They arFish growth trajectories are plastic and correlate with a number of environmental factors including food availability , temperath century [Archaeological excavations of historical fishing sites across the North Atlantic have unearthed high quantities of Atlantic cod bones , 32 and  century .th century [In the North Atlantic, the medieval and early modern periods were characterized by rapid increase in marine fisheries; as urbanization and globalization in western Europe drove increasing demand for stock fish; and multinational fishing fleets sought favorable fishing grounds for Atlantic cod . At the  century , 40. Adu century  and are  century , 42. How century , 44.th century.In the current study, we analyze growth patterns of Atlantic cod otoliths from archaeological excavations of historical fishing sites in NW Iceland, dated to AD 970 –AD 1910. First, we examine the significance of change in otolith size, linear and quadric growth patterns across the millennium. Our initial hypothesis was based on faster growth in the medieval warm period followed by reductions in growth rate, particularly during the North Atlantic temperature minimum in the 17The archaeological excavations were carried out at the historical fishing sites; Breiðavík  and Kollsvík  in north-western Iceland . In July14C dating (Scottish Universities Environment Research Centre). Mean 14C age, quoted in years AD, was used in analysis. The error around the mean , this involves embedding the otoliths in black resin blocks, removing a thin section from the transverse midplane. Images were taken of each otolith again using Leica IC80 HD  under a stereomicroscope at 10× magnification using a reflected light setting, with resolution 2048 x 1536 pixels. The age determination and annotation of cod otoliths in this study were carried out by highly experienced otolith reader. The otolith sizes at the mid-point of respective annual translucent zones were then marked along a transect from the core to the outer distal edge of the otolith, with the transect being approximately perpendicular to the width of the otolith .We did not attempt back calculations of fish size as archaeological otoliths are known to be subject to shrinkage and estimates of life fish length based on archaeological otoliths may be underestimated . We therFirst, we examined if growth patterns differed between archaeological deposits using the first five years of growth of 220 otoliths, a total of 1100 growth measures . A seconβ0i is the intercept, β1i is the linear slope and β2i the quadratic curvature, εij is the residual error and T is time of the observation (fish age in years). The mean estimated date (AD) for each archaeological deposit , the second group included samples dated to AD 1500—AD 1784 (Early Modern period) and finally samples dated to post AD 1785 (Modern period). This classification represents a common historical designation of periods. We then repeated the GLMM, as described above, but replacing archaeological deposit with period as a fixed effect.Finally, we estimated the typical von Bertalanffy growth function vBGF,  parameteL∞ is the maximum length , K is the relative growth rate, t0 is the theoretical age for time at which length is zero. The vBGF is widely used in fisheries biology [Where Yij is the otolith size observation of individual i at Time j and T is time of the observation (fish age in years).  biology , 50 and  biology  using th biology . The cur biology . HoweverThe results support consistent growth patterns of Atlantic cod through the millennium, that is, repeated fluctuations but no long term shifts in growth patterns. In the first generalized linear mixed model, comparing across all archaeological deposits, the intercept, the linear term and the quadratic term were all significant  showing When the otoliths were grouped by periods, the intercept, the linear term and the quadratic term were all significant but no significant difference in growth patterns were observed between periods .2 = 1.23, p = 0.98). L∞ estimates for the three periods varied between 2.203 and 2.441, estimates of K varied between 0.204 and 0.248 and estimates of t0 varied between -0.018 and 0.124 Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 File(XLSX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.


These demarcated hypomineralised lesions of enamel manifest as white-cream or yellow-brown opacities, with possible post-eruptive localised loss of enamel. Aetiological hypotheses have involved contemporary life factors  in contrast to factors not limited to a specific time period (i.e. hypoxia at birth or genetic predisposition). Evidence of MIH in ancient populations would reinforce aetiological factors present for many centuries. By means of microtomographic and X-ray fluorescence analyses the present study provides evidence that (i) two archaeological specimens: “S407” (Sains-en-Gohelle, France, 12 Teeth have been a focus of interest for physical anthropologists over many generations. Teeth provide much information about humans including cultural environment, locational migration, pathology, morphological variation, age estimation and sex differentiation2. Pathologies, such as enamel hypoplasia and dental caries, are informative for understanding the health and nutritional status of individuals and populations4. A modified Developmental Defects of Enamel (DDE) index classifies enamel anomalies, with enamel demarcated opacities separated into two subgroups: white-cream and yellow-brown5. In 2001, Molar Incisor Hypomineralisation (MIH)6 was defined as a qualitative demarcated enamel hypomineralisation defect of tooth enamel affecting at least one first permanent molar (FPM), often affecting permanent incisors6. More recently, the term Hypomineralised Second Primary Molar (HSPM) was used to describe similar defects affecting second primary molars7. The presence of HSPM increases the risk of MIH, but the absence of HSPM does not exclude the presence of MIH10. The European Academy of Paediatric Dentistry agreed on MIH diagnosis criteria characterised by at least one of these factors affecting one or more FPMs: demarcated enamel opacity, post-eruptive enamel breakdown, atypical restoration, or atypical extraction due to MIH11. Post-eruptive enamel breakdown is defined as a defect that indicates a decrease in the depth of enamel after eruption of the tooth. Loss of initially formed surface enamel after tooth eruption is often associated with a pre-existing demarcated opacity11. Today, the worldwide prevalence of MIH is between 2.9 and 44% (average 15%) of children based on current population studies12. Given the difficulties involved in treating MIH , it is essential that the aetiology is determined in order to allow risk assessment and early diagnosis, and if possible, prevention of risk factors14. Without early diagnosis, post-eruptive structural damage may occur quickly and eventually lead to FPM extraction. Currently, in the absence of identified cause(s), no risk prevention actions can be implemented. MIH constitutes a public health problem, with consequences that are not only health-related but also economic. MIH may impact on the well-being of young patients in a crucial period of infant development16. The proposal for a single term “MIH” and the establishment of specific diagnosis criteria by consensus promoted and encouraged the multiplication and quality of research works, but some issues remain unresolved11. Amongst the aetiological hypotheses mentioned in the literature, some recently introduced factors such as pollutants (dioxin derivatives17 or Bisphenol18) or drugs19 (antibiotics22 or asthma drugs23) have been proposed. Other hypotheses of putative factors that have occurred over time, such as childhood illness (in particular fever), prematurity, hypoxia at birth or a genetic predisposition, are also mentioned regularly29. Most studies are retrospective in nature and there is currently insufficient published evidence to identify specific aetiological factors relevant to MIH30, but authors agree a multifactorial aetiology is likely27. The relationship between the occurrence of HSPM and MIH suggests common risk factors9. The identification of MIH and HSPM amongst ancient populations would highlight that aetiological factors apart from the proposed contemporary factors have relevance. Except for a few anthropological studies33, demarcated enamel hypomineralisation has only been observed in individuals from the 20th and 21st centuries. Anthropological researchers have diagnosed MIH in historical populations based on clinical diagnosis33. To date, no author has identified an HSPM case in a past population.Teeth contribute to human bodily functions such as mastication, phonation, appearance and maxillofacial development. Enamel is the most highly mineralised bodily tissue, and thus in an archaeological context is the best-preserved34, as chemical elements (e.g. Iron or Manganese) contained in the burial ground can stain teeth36 (post mortem) and the resultant staining can be similar in appearance to discoloration caused by MIH38 (ante mortem). Before concluding that MIH was present in past populations, it is necessary to discriminate between discolouration caused by pathological (ante mortem) or taphonomic (post mortem) processes37.In an archaeological context, McKay and colleagues demonstrated, by means of microcomputed tomography, that brown enamel opacities caused by taphonomic contamination can be confused with hypomineralisation37, teeth showing defects indicative of MIH and HSPM, including respectively, 298 and 14 individuals aged from 6 to 18 years were analysed. Three individuals affected by yellow-brown opacities on first permanent molars, incisors or second primary molars were selected for analysis: B335 , S323  and S407 . After distribution of shared high resolution images securely via the internet, clinical diagnoses of the three individuals were given by nineteen MIH specialists. This study aimed, by means of enamel microanalyses, to confirm or refute these clinical diagnoses of MIH and HSPM and discuss their implications.Here, two historic osteological series  selected owing to a significant number of children aged 6 to 18 years were assessed. Using a diagnostic guideB335, S323 and S407 materials highlighted opacities and post-eruptive enamel breakdown appearing similar to MIH and HSPM 39. This individual was a teenager, aged 14 years 5 months (95% CI between 10 years and 5 months to 18 years 5 months). All permanent teeth were present at death and a brown demarcated opacity was observed on tooth 16  of enamel with brown discoloration was present on tooth 46. The other mandibular teeth were sound.The anthropological study of the SPM Figs –3. The mS323 and S407 are from the Sains-en-Gohelle series dated to the medieval period 40. The material from S323 included the first permanent incisor germs, the first permanent molars and the primary molars. Age was estimated at 3 years and 9 months to 6 years40  and slight occlusal wear was observed on the primary molars.The individuals Photographic images of the three specimens Figs –3 were eMineral densities of discoloured and normal enamel areas at the same coronal height for each tooth were measured from µCT data in 3D Fig.  and 2D .Figure 4Mineral concentration line profiles from Dento-Enamel Junction (DEJ) to surface through apparently normal enamel (line AB) and through a discoloured region (line CD) in the discoloured teeth group (n = 8 with the exception of S323(11)) and the control group (n = 3) are illustrated in Fig. Elemental chemical analyses (see Methods) provided information on taphonomic contamination by one or several chemical elements . The discolorations on teeth 65 and 75 from S323 were characterised by an increase in Mn  in some samples (B335 and S323), putatively explained by increased porosity of hypomineralised enamel44.Mineral density analyses suggest that the three studied specimens showed evidence of demarcated enamel hypomineralisation on first permanent molars. Moreover, for one specimen (S323), demarcated enamel hypomineralisation on second primary molars is present. A mean mineral density decrease of 7% was calculated at the midway between the DEJ and the surface. Studies highlighted decreased mineral density in hypomineralised areas from 5 to 28% in contemporary hypomineralised teethth–11th centuries. This is the first study investigating the structure of discoloured enamel structure to confirm MIH and HSPM diagnoses. No reports of HSPM in past populations have been published; however, authors have reported “probable” MIH in historical populations. A collection of a London cemetery (Broadgate), including individuals suffering from rickets, dated from the 17th–18th centuries was previously studied48. Scrutiny of the results highlighted a number of points to be clarified. In 2007, these authors reported prevalence for hypoplasia of 93.2% amongst 41 sub-adults, confirmed in some cases by scanning electron microscope. The hypoplastic enamel included 63.6% of molars with severe or moderate lesions31. One year later, in another publication, the authors reattributed all the molar teeth with hypoplastic enamel to MIH, and claimed MIH prevalence of 93.2% with 63.6% of molars “showing moderate or severe lesions” amongst the samples48. The MIH prevalence of the studied population (93.2%) appears to be very high in comparison to current data (2.9–44%)12. Enamel microanalysis for mineral density and elemental profile as well as µCT analysis to allow the determination of enamel thickness would allow the enamel hypoplasia to be distinguished from “probable” MIH. Another case of ‘probable’ MIH was reported in teeth from a skull dating from the mid-15th century32. As a result of unusual localization of brown discolorations  and molar wear, further investigations are required to confirm whether this is MIH or taphonomic stain. A substantial study involving the clinical examination of three archaeological series (dated from 12th to 20th centuries) reported prevalence of 3.1% for MIH and 30.3% for linear enamel hypoplasia33. As mentioned by the authors, ‘mix-ups’ between wear , nutrition, pre and post mortem discolouration, MIH and other enamel defects in archaeological series are more than probable33; the reason why confirmation of diagnosis by microanalyses is important. The present results regarding the uncertainty of visual diagnosis by MIH experts showed that no clinical diagnosis of MIH in past populations is reliable. In fact, authors should confirm their results by means of non-destructive microanalyses37.All of these signs clearly point to the most ancient case of MIH with HSPM in an osteological collection dated to the 7th–11th centuries) reported to be affected by MIH and HSPM confirmed by microanalyses raises questions about the importance of modern aetiological hypotheses such as medications or environmental pollutants. Several authors have raised the possibility of a link between taking antibiotics during the first years of life and the occurrence of MIH51. However, the subsequent discovery of the first antibiotic (penicillin) in 1928 and its commercialisation in France in 194552 negates a possible link with MIH and HSPM amongst our sample. This is consistent with Ghanim’s study showing no link between MIH and antibiotics20. Noting that in these retrospective studies, it is not possible to identify the real causative factors such as childhood illness (putatively high fever) or the associated medication or both. The hypothesis of environmental dioxins has also been raised in the literature54. In fact, authors proposed that dioxins delivered via maternal breastfeeding could be a causative factor of MIH53. However, these compounds have only been present in the environment since 187455. The majority of international studies have not established links between MIH and dioxins57. More recently, another modern aetiological factor hypothesis has arisen, the bisphenols18; used as base compounds in the manufacturing of polycarbonates and epoxy resins. Bisphenol A (BPA) was used worldwide in plastic containers (such as baby bottles and food containers) and since prohibition in France (2015), BPAs were replaced by bisphenol analogues (BPS and BPF)58. The commercialisation of BPA took place in 195059, which is not compatible with a possible link with the cases of MIH and HSPM living in the medieval period. None of these modern aetiological hypotheses can explain the enamel defects on the three investigated individuals. If the possible aetiological factors which may have occurred during the 7th–18th centuries are studied, childhood illness and peripartum events seem to be most plausible. Diseases such as otitis media50, pneumonia50, infections of the urinary tract60, or chicken pox21 have been positively associated with MIH. A systematic review investigating 25 studies on MIH aetiological factors determined a probable link with childhood disease27. It has also been suggested that the causative factor of MIH could have been a lack of oxygen occurring during deliveries63. Hypoxia can be associated with medical problems at birth, such as prematurity, caesarean sections29, respiratory difficulties and prolonged duration of labour61. Other studies have also implicated prematurity in MIH occurrence64. More recently a genetic predisposition in conjunction with one or several others factors has also been proposed26. Prospective studies should provide more complete temporal results but they are long and complex to carry out. It would take at least six years and the eruption of the FPM in order to collect the initial results, and the initial sample must be large enough to meet the challenges of frequent medical monitoring over a long period (from the third trimester of pregnancy until the age of six to seven years). The first publication using this methodology provides limited information confirming aetiological hypotheses54. Pending the results of prospective studies, the increase of MIH prevalence study numbers on ancient populations, including well documented archaeological series, will improve understanding of the MIH pathophysiology.The discovery of the oldest specimen . The present study highlights the potential contribution of bio-archaeological studies on a current public health problem.Thus, the discovery of the oldest specimens with MIH and the first archaeological specimen with HSPM in an immature individual from archaeological series dated from 765. Some precautionary principles were applied; individuals with taphonomic discoloration of the mandible or maxilla and individuals showing discoloration on all teeth were excluded. Three individuals presenting the most complete dental remains and showing enamel defects indicative of MIH and/or HSPM were selected for analyses: B335, S323 and S407. The first individual (B335) was retrieved from the cemetery of the convent “Les soeurs Grises”, located in Beauvais . The convent was occupied by the religious community between 1480 and the late 18th century66. The age at death of B335 was estimated using the Liversidge and Marsden method67. The other specimens (S323 and S407) are from the Sains-en-Gohelle cemetery 40. The age at death of these two specimens was estimated by means of the Moorrees method68.Individuals with estimated ages from 6 to 18 years old were studied from two archaeological series . Only young individuals were chosen owing to the potential for early breakdown of enamel caused by dental caries or wear in archaeological materials in older individuals. The diagnosis of MIH requires erupted FPM in individuals 6 years and older®  SLR camera D90, a Metz®  macro ring flash and a Tamron®  lens SP AF 90 mm f/2.8. Each maxilla, mandible and teeth were photographed on a black matt paper: occlusal view for bones and five views  for each tooth.The individuals’ teeth were examined by means of a hand magnifying lens with artificial lighting. Standardised photographs of the three specimens showing brown discolorations similar to MIH and HSPM were taken with a Nikon®, CA, USA). The reliability of MIH and HSPM diagnosis by means of photographs were previously validated69. Participants selected were authors who had published on MIH in either first or last position in an international journal with an impact factor or in the journal of the EAPD (European Academy of Paediatric Dentistry). A search was performed on 15 February 2016 on Medline/Pubmed with the words “enamel AND hypomineralisation” and 76 authors were identified. From this group, 19 participants answered. The Fleiss’ kappa test was performed between the three possible responses  for each specimen. In a recent published diagnostic guide it was advised that enamel microanalyses should be undertaken to avoid taphonomic bias and MIH misdiagnosis37. Therefore, the authors recommended using X-ray fluorescence analyses aiming to highlight a post mortem contamination by Fe or Mn in addition to microtomographic analyses to confirm enamel hypomineralisation37.A questionnaire asking for each specimen  “is it typical of MIH lesions?” and “How did you make your decision?” including photographs of the three specimens was created. It was sent on 23 February 2016 to 76 MIH specialists by means of ‘Google forms’ . In order to take measurements at the same coronal height, images were reconstructed according to the plane of section through two points located at the buccal cervical surface and one point on the lingual cervical surface.The samples including nine discoloured teeth (B335(46), B335(16), S323(26), S323(11), S323(55), S323(65), S323(75), S323(85) and S407(26)) and three control teeth (B335(36), S323(16) and S323(21)), were imaged using high resolution microtomography at the laboratory PLACAMAT (UMS 3626) in Bordeaux, France . The scanning parameters were 120 kV, 147 µA for the X-ray tube, exposure time 500 ms with four integrations per projection, 2550 projections/360° and 0.1 mm copper filter placed on the source to reduce beam hardening artefacts. The voxel size was 7 × 7 × 7 μm3) were located by means of the square brush segmentation tool from the enamel surface to the DEJ ;at the DEJ (cube n°5).From a selected tooth area, five cubes  provided in Table formula: normal enamel mineral density - discoloured enamel mineral density. To achieve a 3D representation of the MIH defect . From a slice through affected enamel, the average of grey levels represented by the line from the DEJ to the surface was calculated , this line was segmented in 99 equidistant points starting at the DEJ and finishing at the surface (SI). Then, the mean values of these 99 measurements for hypomineralised and normal areas were compared , B335(16), S323(26), S323(11), S323(55), S323(65), S323(75), S323(85) and S407(26)) were analysed by means of X-Ray fluorescence  with the following parameters: collimator (0.5 × 0.5 mm), time measurement of 300 s and Rhodium anticathode. Two experimental conditions were used: condition 1 (without filter and tube voltage: 15 kV) to determine relative concentrations of P and Ca, and condition 2 (filter for lead and tube voltage: 50 kV) to determine relative concentrations of Sn, Mn, Cu, Zn, Fe, Pb and Sr. A spot in normal enamel was located at the same coronal height of its homologous spot in stained enamel. This process was repeated a second time. Thus, two measures by area in two distinct zones were performed in stained and normal enamel on the tooth surface. Only chemical elements (in oxide form) that may stain enamel were selected: Mn, Cu, Pb and Fe® software Package Version 7.1  to compare data from normal and discoloured enamel. A Fleiss’s kappa test was performed with R software to test the inter-examiner agreement (n = 19).Non-parametric statistical tests (Wilcoxon test for paired samples) were carried out using StatisticaSupplementary Information


Taken together, our findings provide new evidence on the loss of fertility induced by overweight in males.Semen quality has certainly declined over the past few decades, possibly owing to modern lifestyle factors. In this sense, the role of overweight and obesity in the development of subfertility in males has generated a considerable amount of interest in recent years. However, there is no consensus on whether overweight or obesity impaired sperm quality. Thus, based on the ongoing debate about risk factors for subfertility associated with overweight and obesity in men, this study was designed to investigate the effect of overweight on sperm quality parameters and fertility success in randomized controlled trial in a rabbit model. Fourteen male rabbits were randomly assigned to a control group in which nutritional requirements were satisfied or a group fed to satiety from 12 to 32 weeks of age. At 24 weeks of age, semen samples were analysed weekly by conventional semen analysis for 8 weeks. In addition, during the trial female rabbits were artificially inseminated by each male to assess the fertility success and the number of offspring. Young males fed to satiety were associated with a significant increase in body weight (13.6% overweight) and perirenal fat thickness (5%). Male overweight presented a significant decrease in sperm concentration. There were no differences in the remaining sperm parameters. However, male overweight showed a clear and significant decrease in fertility success (control group, 64±8.9%  Semen quality has certainly declined over the past few decades, possibly due to modern lifestyle factors . In factMany relevant research works published in succession, including meta-analyses, have described a negative association between BMI and different semen quality parameters .All chemicals, unless otherwise stated, were reagent-grade and purchased from Sigma-Aldrich Química S.A. . All the experimental procedures used in this study were performed in accordance with Directive 2010/63/EU EEC for animal experiments and reviewed and approved by the Ethical Committee for Experimentation with Animals of the Polytechnic University of Valencia, Spain (research code: 2015/VSC/PEA/00061).A total of fourteen males from a synthetic line of rabbits called line R were used in the experiment . Line R Animals were housed at the Polytechnic University of Valencia experimental farm in flat deck indoor cages (75×50×30 cm). The photoperiod is set to provide 16 h of light and 8 h of dark, and the room temperature is regulated to keep temperatures between 10°C and 28°C. Young males were fed to satiety until 12 weeks of age with a commercial pelleted diet (minimum of 15 g of crude protein per kg of dry matter (DM), 15 g of crude fibre per kg of DM, and 10.2 MJ of digestible energy per kg of DM). Until 9 weeks of age, young males were caged collectively, and subsequently housed individually. At 12 weeks of age, males were then randomly assigned to the control feed group in which nutritional requirements were satisfied, or the fed to satiety group. The control feeding regime consisted of a daily intake of 130 g to cover energy requirements for maintenance (340 kJ day-1 kg-1 LW0.75 ). The avRoutine diagnostic semen analyses were carried out in this experiment. Semen samples were obtained by artificial vagina and collected into a sterile tube. Previously, males began the training period with an artificial vagina at 20 weeks of age . Traini6 cells/ml with Tris-citrate-glucose extender. Finally, each female was inseminated with 0.5 mL (10x106 cells per doe), which was performed within 2–4 h of semen collection. At insemination time, each female was injected intramuscularly with 1 μg of buserelin acetate  to induce ovulation. Only receptive does (red colour of vulvar lips) were inseminated, using a standard curved plastic pipette . The number of females that gave birth by number of inseminations (fertility rate) and number of offspring per litter were recorded.During the trial period, a total of 375 inseminations were carried out (189 in fed to satiety group and 186 in control group). The semen sample for each male was adjusted to a final sperm concentration of 20x10Body weight and perirenal fat thickness (PFT) were measured across three testing sessions during the trial: at the beginning (24 weeks of age), in the middle (28 weeks of age) and at the last session (32 weeks of age). PFT was measured by ultrasound as described by Pascual et al. . BrieflyThe model used to examine the relation between daily food intake and semen parameters was a mixed model , according to a repeated measures design that takes into account the variation between animals and covariation within them. Covariance structures were objectively compared using the most severe criteria (Schwarz Bayesian criterion ). The moTo compare fertility between groups, a general linear model was performed including the daily food intake regimen with two levels (control or fed to satiety) as a fixed factor. The error was designated as having a binomial distribution using the probit link function. Binomial data for fertility were assigned a value of one if AI was positive. Failure to inseminate resulted in a score of zero. Prolificacy was compared with a generalized linear model including the daily food intake regime with two levels (fed to satiety and control) as a fixed effect. Finally, body weight and perirenal fat thickness were compared using a T-test.Differences of p<0.05 were considered significant. Data are shown as means ± standard error means (S.E.M.). All analyses, except mixed model  were performed with SPSS 21.0 software package .versus 130.0 g/day). In addition, young males fed to satiety were associated with a significant increase in body weight at the end of experimental period  when compared with normal weight (308.7±25.38 x106/mL). There were no differences in the remaining sperm parameters among groups , the most interesting finding in this work was that overfeeding was related to subsequent overweight, resulting in a fertility rate decreased by half. A similar effect has been described in infertile couples undergoing assisted reproductive technology, with lower odds of live birth after in vitro fertilization treatment compared with intracytoplasmic sperm injection (ICSI) among overweight and obese men, supporting the hypothesis that ICSI may overcome a possible obesity-related impairment of the sperm-oocyte interaction . Our datIn conclusion, the present study reports that sperm quality parameters analysed by conventional semen analysis, except sperm concentration, are not associated with male overweight in our rabbit model. However, our data provide evidence that overweight is related to a clear reduction in fertility capacity. Thus, future studies contrasting the “genomic” and “proteomic” profiles of sperm cells are warranted to identify the specific changes that could impair sperm fertility capacity in overweight/obese males.S1 Fig(TIFF)Click here for additional data file.


Rhinolophus macrotis complex contains a large form and a small form, suggesting the existence of a cryptic bat species. Our field surveys found these two sibling species have a continuous and widespread distribution with partial sympatry. However, their evolutionary history has received little attention. Here, we used extensive sampling, morphological and acoustic data, as well as different genetic markers to investigate their evolutionary history. Genetic analyses revealed discordance between the mitochondrial and nuclear data. Mitochondrial data identified three reciprocally monophyletic lineages: one representing all small forms from Southwest China, and the other two containing all large forms from Central and Southeast China, respectively. The large form showed paraphyly with respect to the small form. However, clustering analyses of microsatellite and Chd1 gene sequences support two divergent clusters separating the large form and the small form. Moreover, morphological and acoustic analyses were consistent with nuclear data. This unusual pattern in the R. macrotis complex might be accounted for by palaeoclimatic oscillations, shared ancestral polymorphism and/or interspecific hybridization.Palaeoclimatic oscillations and different landscapes frequently result in complex population-level structure or the evolution of cryptic species. Elucidating the potential mechanisms is vital to understanding speciation events. However, such complex evolutionary patterns have rarely been reported in bats. In China, the  Species are not only the basic taxonomic unit, but also one of the most important units of interaction between ecology and evolution. Species delimitations and their distributions have traditionally been through morphological traitsmt) DNA analyses have been reported67889In some taxa with complex evolutionary histories, unexpectedly widespread species-level paraphyly and polyphyly in mitochondrial (Rhinolophus is one of the most diverse and complex bat genera. We recently explored the taxonomy of big-eared horseshoe bats (Rhinolophus macrotis) based on sampling in one province. Since the large and small form are sympatric, and have significant differences in both morphology (size) and echolocation frequencies (~16 kHz) as well as a relatively high mitochondrial cytochrome b (Cytb) divergence (3.16–3.25%), this is a species complex with cryptic speciesR. macrotis complex.Bats represent over 20% of mammal species13141516b and control region) and ncDNA (eight microsatellite loci and Chd1 gene) to reconstruct the phylogeny of the big-eared horseshoe bat species complex from China. We combined this with morphological data  and acoustic data (i.e. echolocation frequency). Our study aimed to (i) determine genetic lineages in this species complex; (ii) determine whether the mtDNA variation is congruent or conflicts with the nuclear and phenotypic data ; (iii) if conflicting, evaluate potential mechanisms leading to patterns within this species complex; (iv) and, evaluate the effect of palaeoclimatic changes on this species complex.In this study, in order to examine their evolutionary history and speciation, we used ten unlinked genetic markers, including mtDNA  and control region (464 bp). A total of 29 haplotypes of Cytb were defined based on 103 polymorphic sites (71 of which were parsimony informative). No insertions or deletions were found. Fifty haplotypes of the control region were defined based on 115 polymorphic sites (90 of which were parsimony informative). The alignment of the combined Cytb and control region  resulted in 53 haplotypes. For the autosomal Chd1 gene (742 bp), a total of 20 haplotypes were defined from 71 individuals based on 24 polymorphic sites (6 of which were parsimony informative).For 79 individuals in the R. macrotis from Southwest China, including those small forms identified previouslyR. macrotis from Central and Southeast China, respectively. The large forms identified in Sun et al.Maximum likelihood and Bayesian phylogenetic reconstruction based on the combined mtDNA data  and on tThe ranges of the three clades were partially sympatric . Both SXbb to calculate the intra-lineage and inter-lineage genetic differences. In this species complex, the maximum level of uncorrected intra-clade divergence was ≤2% , with similar divergence times mt Clades 1 and 2 . In contrast, mt Clade 3 originated much later. Tajima’s D values and Fu’s Fs tests indicated that none of the three mt lineages deviated significantly from neutrality . However, when excluding the GD1 population, the test of IBD suggested that the two lineages had not evolved separately but were connected because smooth clinal variation rather than a geographic break was observed in the nuclear genetic variation  and latitude . When excluding GD1, clinal variation was much more significant .We focused on the geographic pattern of acoustic variation within mt and nuclear genetic structures. Three mt lineages were identified: Clade 1  and Clade 2 (large form), which are closely related and separated by short genetic distances, and the more distantly related Clade 3 (large form). In contrast, only two genetic entities were identified on the basis of nuclear data: small form (mt Clade 1) and large form (combined mt Clades 2 and 3). The morphological and acoustic data were consistent with the nuclear genetic data, as they also did not separate the mt Clade 2 and mt Clade 3 lineages. These results suggest the occurrence of complex processes during the evolution of the big-eared horseshoe bats in the study area, such as palaeoclimatic changes, allopatric speciation, incomplete lineage sorting and/or genetic introgression.This study highlights the complex evolutionary history of big-eared horseshoe bats in China, and adds to the limited literature documenting complex evolutionary histories in bats. We document here the incongruence between R. macrotis complex populations dated to 1.51 Ma. During this period, China was experiencing glacial-interglacial cycles, including the Poyang glacial stage (1.8 Ma) and the Dagu glacial stage (1.1 Ma)Pleistocene climatic fluctuations and accompanying ecological changes in China have presented severe challenges to the survival of bat species, greatly affecting their population differentiation and contemporary distribution321mt Clade 1  and mt Clade 2 (large form) dated to 1.16 Ma, suggesting that the two mt lineages differentiated from each other between 1.16–0.64 Ma. This time was consistent with two major cold glacial stages, Xixiabangma glaciations (1.17–0.8 Ma)The TMRCAs of the combined mt Clades 2 and 3). The small forms clearly formed a distinct genetic pool on the basis of nuclear genetic analyses . The observed pattern of geographic variation could be due, at least in part, to cultural drift. In general, cultural transmission and copying errors are major drivers of stochastic divergence in learned vocal signals28mt Clade 1  was nested within the mt Clades 2 + 3 group (large forms), rendering large forms paraphyletic with respect to small forms. Two evolutionary processes may account for this mitochondrial paraphyly: (i) incomplete lineage sorting and the persistence of highly divergent mt lineages, and (ii) mitochondrial introgression.An increasing number of studies have reported mitochondrial species-level paraphyly (e.g. refs mt lineages within a species may reflect maintenance of two lineages in a panmictic population with a large effective population sizemt genome (such as we observed) can also occur after two mt lineages come into contact. Since most bat species have female philopatry and male-biased dispersalmt lineages may spread more slowly than the nuclear genome, as occurs in the big brown bat (Eptesicus fuscus)mt Clades 2 and 3 was likely a consequence of isolation in different Pleistocene refugia, followed by range expansion and the establishment of a secondary contact zone. Thus, retention of unique mt lineages that arose in isolation, followed by homogenization of the nuclear genome, is possible in the R. macrotis complex.The persistence of highly divergent mt genome plus an introgressed mt genome. This scenario implies that another unsampled species with a different nuclear genome and one of the mt lineages identified in our data set exists elsewhere in China. One of individual from JX1 population in mt Clade 3 had 0.79–1.76% mitochondrial Cytb divergence with an unidentified Rhinolophus species, Rhinolophus sp1.mt genome may have occurred. We reconstructed trees using all of our data with the published Cytb sequence of R. sp1.  GlaciationFor the HuN and JX1 populations, the individuals were assigned to the correct forms based on microsatellite NJ tree, FCA and Bayesian clustering, suggesting a recent secondary contact between two forms or the maintenance of reproductive isolating barriers in two populations. However, for the GD1 population, only one individual was correctly assigned to the large form group, but five individuals were genetically assigned to the small form group , though R. macrotis complex appears to be complex. This complexity has led to strong incongruence between mt genetic structure, and that from nuclear loci, morphology and acoustic patterns in this species complex. The divergence between the small and large form likely occurred in allopatry due to isolation of populations during Pleistocene glaciation events, and current areas of sympatry appear to be due to more recent secondary contact . Current hybridization may be occurring in one sympatric population, though there appears to be reproductive isolation between the small and large forms in other sympatric populations. The occurrence of two highly divergent mt lineages in large forms conflicts with the nuclear plus phenotypic data , which might be due to the persistence of highly divergent mt lineages, geographically structured during Pleistocene glaciations, and/or genetic introgression from a species yet to be identified. While such complex patterns have been observed frequently in birds, they have rarely been reported in bats, which are also quite vagile. Our observations add to several other studies on bats, and suggest that the limited studies in bats (relative to birds) may be due to the paucity of studies on bats rather than a fundamental difference in their evolutionary histories. Overall, our results suggest that additional studies in bats may help highlight other cases of complex evolutionary histories.In summary, the evolutionary history of the et al.In China, 79 individuals of big-eared horseshoe bat complex were sampled during 2006–2012 from 14 localities , includiSampling sizes were different for morphological characters, echolocation calls, mtDNA, microsatellite DNA and the Chd1 gene. For morphological characters (forearm length), 133 independent samples were measured. For echolocation calls, 109 independent samples were recorded. From those individuals with morphological and echolocation data, 79 samples were sequenced for mtDNA, 78 and 71 were examined using microsatellite DNA and Chd1 analyses, respectively. For each sampling locality, we determined the latitude and longitude using GPS (eTrex Vista) and then calculated the geographic distance matrixes among localities.We used a UNIQ-10 column animal genomic DNA isolation kit  to extract total genomic DNA from collected bat wing membranes which had been preserved in 99% ethanol.b gene  and 464 bp of the control region. The complete Cytb fragment for 67 individuals was amplified using primers L14724 and H1591541et al.et al.b and control region haplotypes of R. macrotis complex were deposited in GenBank with accession numbers KX261888-KX261916 and KX261917- KX261966, respectively. All sequences were aligned using GENEIOUS PRO (v. 5.6.6)We sequenced two mtDNA fragments: the complete Cytet al.et al.Eight microsatellite loci, Reffer 15, 22, 24, 27, H3, PD3, A4 and PH69A, were amplified using fluorescently labeled primers for 78 individuals. Primer sequences and PCR conditions followed those of Rossiter The autosomal Chd1 gene was amplified using two sets of primers b and control region for each population and mt lineage. The uncorrected Cytb genetic distances within and among mt lineages were calculated in MEGA 5.05e) and observed herterozygosity (Ho) were calculated using Genepop, and mean allele number and allelic richness for per locus and per taxon was assessed in Fstat 2.9.3e and Ho for each taxon was calculated using Arlequin v3.5Haplotype diversity (h) and nucleotide diversity (π) were calculated for mitochondrial Cytmt lineage, we only analyzed the control region due to its greater variability at this level. We used Tajima’s DFs tests as implemented in Arlequin to test for neutrality. The goodness-of-fit of distributions was tested and its significant difference from a model of sudden expansion was assessed using the sum of squared deviations (SSD) and the raggedness index (r) with 1,000 parametric bootstrap replicates. Generally, low and non-significant SSD and r values indicate population expansion. For the expanding mt lineages, we estimated the time of expansion (t) from τ = 2ut, where τ is calculated as the time to expansion in mutational units and u is the mutation rate per generation for the entire sequence. The u is equal to μgk, where μ is the mutation rate per nucleotide, g is the generation time and k is the sequence length. We used a mutation rate of 20% ⁄ Myr for the current control region based on previous studies on bats1756To examine the demographic history of each ST (given by FST/(1 − FST)). An isolation by distance (IBD) model was estimated from the large forms based on microsatellites.We calculated nuclear genetic distances between localities using Slatkin’s linearized FRhinolophus mashalli and R. pusillus were selected as outgroups . The nuclear Chd1 gene was not included in this analysis as part of the goal was to explore the different signals between the mitochondrion and the nuclear genome. Phylogenetic reconstruction using maximum likelihood (ML) in PhyML-aBayes58b and control region separately as well as combined.For the mitochondrial analyses, two closely related species, b, (2) TIM3 + I + G  for control region, TrN + I + G  for the combined mtDNA data. For ML analysis, the starting tree was obtained with BIONJ6 generations. Trees and parameters were sampled every 10 generations. When the run terminated, the deviation of split frequencies reached a value <0.01. The ln-likelihoods of trees reached an asymptote. The first 25% of the sampled trees were discarded as a burn-in.We used jModelTestet al.A distance between individuals and reconstructed using a NJ algorithm using Populations v1.2.30 a priori designation for populations was used and the number of tested clusters (K) was based on the mtDNA results. For K = 1 to 5, 10 runs were performed with 500,000 iterations after 100,000 iterations were discarded as “burn-in”. The most likely number of populations was determined using the ΔK method described by Evanno et al.R. macrotis species complex. Fourth, we used GENELANDK = 2 which is most likely according to STRUCTURE and FCA outputs. Five independent runs were performed for K = 2, using 107 iterations with a burn-in of 30,000 iterations and 250 thinning. As the correlated model seems to be more prone to algorithm instabilities and more sensitive to departure from model assumptions, such as the presence of isolation by distance, we used the uncorrelated model of allele frequencies for microsatellite lociFor the microsatellite analyses, we used a phylogenetic tree based on Nei b sequences because the molecular evolutionary rate of this gene is well-known for inter-clade and interspecific comparisons. The time to the most recent common ancestor (TMRCA) among lineages was estimated in BEAST v1.7.4−8 subs/site/year [calculated based on Nabholz et al.To estimate the time of divergence among clades, we only used Cytet al.Echolocation calls were recorded with a D980 Pettersson bat detector . This detector was positioned approximately 30 cm in front of hand-held bats. The recordings were transferred to a computer with a time expansion of ×10 using BatSound Pro 3.10 . The resting frequency that the bats emitted under these conditions is the stable constant frequency portion of the echolocation pulses emitted by the motionless bat. We selected a portion of a recording in which resting frequency calls were continuously uttered. Using criteria proposed by Sun Geographic variation for phenotypic characters was explored via box plots, with longitude and latitude on the abscissa. The relationship of resting frequency to either longitude or latitude was estimated by linear regression analysis, with averaging of frequency by site.mt Clade 2 and mt Clade 3 in the large form, we used a general linear model with type III sums of squares to test for an effect of sex, site and mt lineage on forearm length and echolocation frequency. All variables were treated as fixed effects in the model.To estimate the phenotypic differentiation between Accession Codes: All sequence data has been uploaded to GenBank . Microsatellite genotypes, sequence alignments by markers, phylogenetic trees and morphological and acoustic data files are uploaded on the Dryad Digital Repository (doi:10.5061/dryad.b1c88).How to cite this article: Sun, K. et al. The complex evolutionary history of big-eared horseshoe bats (Rhinolophus macrotis complex): insights from genetic, morphological and acoustic data. Sci. Rep.6, 35417; doi: 10.1038/srep35417 (2016).