More stories

  • in

    Hotspots for rockfishes, structural corals, and large-bodied sponges along the central coast of Pacific Canada

    The Wuikinuxv, Kitasoo/Xai’xais, Heiltsuk and Nuxalk First Nations hold Indigenous rights to their territories, where all data were collected. Scientific staff who are members of these Nations or who work directly for them had direct approvals from Indigenous rights holders and were exempt from other research permit requirements. Collaborating DFO scientists worked in partnership with the First Nations to collect data in their territories..Sampling targeted rocky reefs, the preferred habitat for most Sebastidae38, which we located through local Indigenous knowledge or a bathymetric model49. Data were collected by four fishery-independent methods—shallow diver transects, mid-depth video transects, deep video transects, and hook-and-line sampling—detailed in earlier publications32,33,34,35,50,51 and summarized in Table 1. Data had a spatial resolution of ≤ 130 m2 and each sampling location (N = 2936 for Sebastidae, 2654 for sponges, 2321 for corals) was ascribed to a 1-km2 planning unit within the standardized grid used to design the MPA network (N = 632 for Sebastidae, 525 for sponges, 529 for corals, 516 inclusive of surveys for all taxonomic groups).Table 1 Survey methods used for data collection.Full size tableAlthough sampling encompassed 11 years (2006–2007, 2013–2021: Table 1), 84% of 1-km2 planning units were sampled during only one year (Appendix S2). Analyses, therefore, focus on spatial variability in species distributions and do not address temporal variability within planning units. When all years and methods are combined, 1-km2 planning units had a median of 3 samples (range = 1 to 80, Q1 = 2, Q3 = 6) (i.e., sum of dive transects, video sub-transects, and hook-and-line sessions). Supplementary Data Set 1 reports sampling effort by 1-km2 planning unit, survey type, and year (see Data Availability for link to these data).For each 1-km2 planning unit, u, we calculated hotspot indices for Sebastidae (BSEB,u), structural corals (BCor,u), and large-bodied sponges (BSp,u). These indices did not consider cup corals, whip-like corals or encrusting corals or sponges.As detailed below (Eqs. 1–4), each species of Sebastidae or genera of corals contributed to BSEB,u or BCor,u, according to their abundance weighted by Wt: a conservation prioritization score based on taxon characteristics. For the 26 species of Sebastidae that we observed, Wt equaled the sum of scores for (1) fishery vulnerability, using intrinsic population growth rate, r, as a proxy variable52,53, (2) depletion level, using the ratio of recent biomass to unfished biomass as a proxy variable, (3) ecological role, with trophic level as proxy, and (4) evolutionary distinctiveness14 (Table 2; Appendix S3). Because several rockfishes are very long-lived (i.e., have low values for r) and depleted, maximum potential scores were twice as large for fishery vulnerability and depletion level than for ecological role and evolutionary distinctiveness. Data for depletion level and evolutionary distinctiveness were unavailable for some species, and score calculations (detailed in Table 2) account for missing values (Appendix S3).Table 2 Criteria and equations used to calculate the conservation prioritization score, Wt, for each species of Sebastidae and for each taxa of structural corals.Full size tableFor the 6 genera of structural corals analyzed (Appendix S4), Wt depended on mean height (estimated from video transect images: Table 1), which correlates positively with vulnerability to physical damage from bottom-contact fishing gear (including longer time to recovery)20,54,55 and with strength of ecological role (e.g., amount of biogenic habitat and carbon sequestration increases with height)44,56 (Table 2, Appendix S4). Wt for corals did not include depletion level due to lack of data.The hotspot index for large-bodied sponges, BSp,u did not differentiate between species characteristics (i.e., ({W}_{t}=1)) and we pooled the abundances of all observed species of Hexactinellidae (Aphrocallistes vastus, Farrea occa, Heterochone calyx, Rhabdocalyptus dawsoni, Staurocalyptus dowlingi) and Demospongiae (Mycale cf loveni). This approach is consistent with regional fishery bodies worldwide, which treat large-bodied sponges as a single functional group57.To derive hotspot indices for each taxonomic group (Sebastidae, structural corals, or large-bodied sponges), we first developed a set of candidate generalized linear mixed models (GLMM) to explain relative abundance data for rockfish, corals, and sponges. For each GLMM, we estimated ({lambda }_{t,i,l}), the expected counts (or expected percent cover) for taxa t obtained with survey method i at point location l. (Point locations are individual dive transects, video transect bins, or hook-and-line timed sessions: Table 1.) Specifically,$${lambda }_{t,i,l}=gleft(beta {X}_{t,i,l}right)$$
    (1)
    $${C}_{t,i,l}mathrm {, or ,} {D}_{t,i,l}sim fleft({lambda }_{t,i,l}right)$$
    (2)
    where g was the link function for the GLMM and f the distribution for the likelihood function modelling either the observed counts C (negative binomial) for Sebastidae and structural corals or a combination of counts (negative binomial) and percent cover D (beta distribution) for large-bodied sponges. We used multiple GLMMs to model large-bodied sponges because deep video transects recorded actual counts whereas dive or mid-depth video transects recorded percent cover categories (Table 1).For each taxonomic group, we estimated a set of coefficients (beta) for the vector of X covariates that best estimated counts or percent cover. Our hypothesized covariates included the 1-km2 planning unit (modelled as a random intercept to control for repeated measures within a given planning unit), survey method, depth (including both linear or a 2nd order polynomial), and taxa. Each GLMM controlled for sample effort as an offset—effort was measured either as area covered by dive transects or video bins, or the duration of hook-and-line sessions. We also tested for possible covariate’s effects on the dispersion parameter (for the negative binomial GLMMs) and zero-inflation terms (for both the negative binomial and beta GLMMs). The best set of covariates to predict counts or percent cover were then chosen based on AIC model selection criteria. All models were fitted using ‘glmmTMB’58 in R version 4.0.259, and simulated residuals and diagnostic tests performed for each best-fit model using the package ‘DHARMa’60. For example, our best model for Sebastidae counts predicted 2% fewer zero counts than were observed.We applied depth and survey method selectivity criteria to reduce excessive zeroes in the count data that may be biologically unjustified (Appendix S5). For all taxon, if i detected t, then the method was valid for that taxon. If i did not detect t and t is a Sebastidae, then the method was valid (i.e., count = 0) only if the overall 10th and 90th percentiles of depths sampled by that method encompassed the expected depth range of t (Appendix S5). If i did not detect t and t is a coral or sponge (which are rarer than Sebastidae), then the method is valid only if the depth of the sampling event exceeded or equaled the minimum expected depth of t. Also, hook-and-line gear cannot systematically sample sessile benthic organisms or planktivores and this method was valid only for non-planktivorous Sebastidae (Appendix S5).Using the best-fit models from above, we calculated the expected count (or percent cover) per unit of effort, (mu), for taxa t observed with method i at each planning unit u:$${mu }_{t,i,u}=frac{{sum }_{l=1}^{{n}_{i,u}}left({lambda }_{t,i,l}right)}{{sum }_{l=1}^{{n}_{i,u}}left({mathrm{E}}_{t,i,l}right)}$$
    (3)
    where ({n}_{i,u}) was the total number of point locations sampled by that method within the planning unit and effort was either the cumulative area covered by dive or video surveys or the cumulative duration of hook-and-line sampling sessions within the planning unit. Because survey methods differed in their maximum values and potential biases (e.g., field of view is greater for divers than for video cameras; hook-and-line gear samples one fish at a time while visual methods can observe multiple fish simultaneously),({mu }_{t,i,u}) was rescaled as a min–max normalization,({mu }_{t,i,u}^{^{prime}}) (i.e., difference between the observed value and the minimum value across all u, divided by the range of values across all u).The hotspot index for each of Sebastidae, structural corals, and large-bodied sponges (denoted as taxonomic group g) was then calculated for each planning unit as:$${B}_{g,u }={sum }_{t=1}^{{n}_{s,g}}{sum }_{i=1}^{{n}_{m,g}}{mu }_{t,i,u}^{^{prime}}{W}_{t}$$
    (4)
    where Wt was the taxon-specific weighing factor (Table 2, Appendices S3, S4), ({n}_{s,g}) was the number of species in taxonomic group g, and ({n}_{m,g}) was the number of valid methods to sample group g.For each 1-km2 planning unit where all taxonomic groups were surveyed (N = 518), we then calculated the overall hotspot index:$${B}_{o,u }=H{sum }_{g=1}^{G}{B}_{g,u}.$$
    (5)
    where H is Shannon’s evenness index, with proportional abundance of each taxonomic group represented by BSEB,u, BCor,u, and BSp,u.Hotspot index values were normalized as the proportion of the maximum value and converted to decile ranks. Relationships between decile ranks and index values were nonlinear (Appendix S6).For Sebastidae, large-bodied sponges, and the overall hotspot index, we defined hotspots as planning units containing decile ranks 9 or 10: criterion which we deemed appropriate for the small spatial scales of conservation planning being used for the central portion of the Northern Shelf Bioregion (16-km2 planning units in Fig. 2). We are aware that other studies define hotspots based on a narrower range of values (e.g., top 10%26; top 2.5%28) but their context is generally one in which conservation planning is done at a much greater scale (e.g., ≈50,000-km2 grid cells26;1° latitude × 1° longitude grid cells28). For structural corals, which had near-zero index values in all but the top-ranking planning units (Appendix S6), we defined hotspots as planning units containing decile rank 10.Maximum depths sampled within planning units were deepest in the Mainland Fjord and shallowest in the Aristazabal Banks Upwelling Upper Ocean Subregion (Appendix S7). Accordingly, we used multiple logistic regression implemented with the ‘glm’ function in R to estimate the probabilities hotspot occurrence within 1-km2 planning units in relation to maximum depth sampled (including a 2nd-order polynomial) and Upper Ocean Subregion. Competing models were compared with AIC model selection procedures.Following the directive of Central Coast First Nations, decile rank distributions were mapped as 16-km2 planning units, u16 (N = 283 for Sebastidae, 264 for sponges, 263 for corals, 260 inclusive of surveys for all taxonomic groups), thereby protecting sensitive locations that would be revealed at smaller scales. To do so, we took the average between the maximum index value and the mean of the remainder of index values among the 1-km2 planning units, u, contained within each u16, and converted these values into decile ranks. This approach balances conservation prioritization among u16 that may have good average index values for multiple u, and u16 with a single high-ranking u among multiple low-scoring u. Relationships between decile ranks and hotspot index values also were nonlinear at this scale (Appendix S6). The same hotspot definitions developed for u apply to u16.Eighty one percent of 16-km2 planning units were sampled during only one or two years (Appendix S2). When all years and methods are combined, 16-km2 planning units had a median of 6 samples (range = 1 to 110, Q1 = 3, Q3 = 13). Supplementary Data Set 2 reports sampling effort by 16-km2 planning unit, survey type, and year (see Data Availability for link to these data). More

  • in

    Factors influencing the global distribution of the endangered Egyptian vulture

    1.BirdLife International. Neophron percnopterus, Egyptian vulture. http://www.iucnredlist.org/details/22695180/0 (2017) https://doi.org/10.2305/IUCN.UK.2017-3.RLTS.T22695180A118600142.en2.Gradev, G., Garcia, V., Ivanov, I., Zhelev, P. & Kmetova, E. Data from Egyptian vultures (Neophron percnopterus) tagged with GPS/GSM transmitters in Bulgaria. Acta Zool. Bulg. 64, 141–146 (2012).
    Google Scholar 
    3.Green, R. E. et al. Diclofenac poisoning as a cause of vulture population declines across the Indian subcontinent. J. Appl. Ecol. 41, 793–800 (2004).CAS 
    Article 

    Google Scholar 
    4.Arkumarev, V., Dobrev, V., Abebe, Y. D., Popgeorgiev, G. & Nikolov, S. C. Congregations of wintering Egyptian Vultures Neophron percnopterus in Afar, Ethiopia: Present status and implications for conservation. Ostrich 85, 139–145 (2014).Article 

    Google Scholar 
    5.Grubač, B., Velevski, M. & Avukatov, V. Long-term population decrease and recent breeding performance of the Egyptian vulture Neophron percnopterus in Macedonia. North. West. J. Zool. 10, 25–35 (2014).
    Google Scholar 
    6.Angelov, I., Hashim, I. & Oppel, S. Persistent electrocution mortality of Egyptian vultures neophron percnopterus over 28 years in East Africa. Bird Conserv. Int. 23, 1–6 (2013).Article 

    Google Scholar 
    7.Zuberogoitia, I., Zabala, J., Martínez, J. A., Martínez, J. E. & Azkona, A. Effect of human activities on Egyptian vulture breeding success. Anim. Conserv. 11, 313–320 (2008).Article 

    Google Scholar 
    8.Sen, B., Avares, J. P. & Bilgin, C. C. Nest site selection patterns of a local Egyptian Vulture Neophron percnopterus population in Turkey. Bird Conserv. Int. 27, 568–581 (2017).Article 

    Google Scholar 
    9.Ceballos, O. & Donázar, J. A. Factors influencing the breeding density and nest-site selection of the Egyptian vulture (Neophron percnopterus). J. Ornithol. 130, 353–359 (1989).Article 

    Google Scholar 
    10.Sarà, M. & Vittorio, M. Factors influencing the distribution, abundance and nest-site selection of an endangered Egyptian vulture (Neophron percnopterus) population in Sicily. Anim. Conserv. 6, 317–328 (2003).Article 

    Google Scholar 
    11.KC, K. B. et al. Factors influencing the presence of the endangered Egyptian vulture Neophron percnopterus in Rukum, Nepal. Glob. Ecol. Conserv. 20, e00727 (2019).Article 

    Google Scholar 
    12.Mateo-Tomás, P. & Olea, P. P. Livestock-driven land use change to model species distributions: Egyptian vulture as a case study. Ecol. Indic. 57, 331–340 (2015).Article 

    Google Scholar 
    13.García-RIPOLLÉS, C., López-LÓPEZ, P. & Urios, V. First description of migration and wintering of adult Egyptian vultures neophron percnopterus tracked by GPS satellite telemetry. Bird Study 57, 261–265 (2010).Article 

    Google Scholar 
    14.Oppel, S. et al. Landscape factors affecting territory occupancy and breeding success of Egyptian vultures on the Balkan Peninsula. J. Ornithol. 158, 443–457 (2017).Article 

    Google Scholar 
    15.Bhusal, K. Population status and breeding success of Himalayan Griffon, Egyption vulture and Lammergeier in Gherabhir, Arghakhanchi, Nepal. (MSc thesis. Institute of Science and Technology, Tribuvan University, Kritipur, Nepal, 2011). https://doi.org/10.13140/RG.2.2.18494.69447.16.López-lópez, A. P. et al. Food predictability determines space use of endangered vultures: Implications for management of supplementary feeding. Ecol. Appl. 24, 938–949 (2014).PubMed 
    Article 

    Google Scholar 
    17.Cortés-avizanda, A., Ceballos, O. & Donázar, J. Long-term trends in population size and breeding success in the Egyptian Vulture (Neophron percnopterus) in Northern Spain. J. Raptor Res. 43, 43–49 (2009).Article 

    Google Scholar 
    18.Rosenblatt, E. Neophron percnopterus Egyptian vulture. Animal Diversity Web https://animaldiversity.org/accounts/Neophron_percnopterus/ (2007).19.ESRI. ArcGIS Desktop: Release 10.5. Environmental systems research Redlands, California, USA https://www.arcgis.com/features/index.html (2017).20.Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).Article 

    Google Scholar 
    21.USGS/EarthExplorer. Data Sets. United States Geological Survey https://earthexplorer.usgs.gov/ (2017).22.JAXA EORC. Global PALSAR-2/PALSAR/JERS-1 Mosaic and Forest/Non-forest Map. Earth Observation Research Center https://www.eorc.jaxa.jp/ALOS/en/palsar_fnf/data/index.htm (2017).23.CIESIN. Gridded population of the world (GPW), v4. http://sedac.ciesin.columbia.edu/data/collection/gpw-v4 (2000).24.Robinson, T. P. et al. Mapping the global distribution of livestock. PLoS ONE 9, e96084 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    25.FAO/GeoNetwork. Global land cover share database. http://www.fao.org/geonetwork/srv/en/main.home (2014).26.Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography (Cop.) 29, 129–151 (2006).Article 

    Google Scholar 
    27.Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modelling of species geographic distributions. Ecol. Modell. 190, 231–259 (2006).Article 

    Google Scholar 
    28.Lobo, J. M., Jiménez-valverde, A. & Real, R. AUC: a misleading measure of the performance of predictive distribution models. Glob. Ecol. Biogeogr. 17, 145–151 (2008).Article 

    Google Scholar 
    29.Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models : Prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).Article 

    Google Scholar 
    30.Pearce, J. & Ferrier, S. Evaluating the predictive performance of habitat models developed using logistic regression. Ecol. Modell. 133, 225–245 (2000).Article 

    Google Scholar 
    31.Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many?. Methods Ecol. Evol. 3, 327–338 (2012).Article 

    Google Scholar 
    32.Liu, C., White, M. & Newell, G. Selecting thresholds for the prediction of species occurrence with presence-only data. J. Biogeogr. 40, 778–789 (2013).Article 

    Google Scholar 
    33.Cortés-Avizanda, A., Martín-López, B., Ceballos, O. & Pereira, H. M. Stakeholders perceptions of the endangered Egyptian vulture: Insights for conservation. Biol. Conserv. 218, 173–180 (2018).Article 

    Google Scholar 
    34.Hernández, M. & Margalida, A. Poison-related mortality effects in the endangered Egyptian vulture (Neophron percnopterus) population in Spain. Eur. J. Wildl. Res. 55, 415–423 (2009).Article 

    Google Scholar 
    35.Mateo-Tomás, P., Olea, P. P. & Fombellida, I. Status of the Endangered Egyptian vulture Neophron percnopterus in the Cantabrian Mountains, Spain, and assessment of threats. Oryx 44, 434–440 (2010).Article 

    Google Scholar 
    36.Carrete, M. et al. Habitat, human pressure, and social behavior : Partialling out factors affecting large-scale territory extinction in an endangered vulture. Biol. Conserv. https://doi.org/10.1016/j.biocon.2006.11.025 (2007).Article 

    Google Scholar 
    37.Zuberogoitia, I., Zabala, J., Martínez, J. E., González-Oreja, J. A. & López-López, P. Effective conservation measures to mitigate the impact of human disturbances on the endangered Egyptian vulture. Anim. Conserv. 17, 410–418 (2014).Article 

    Google Scholar 
    38.Garcia-Ripolles, C. & Lopez-Lopez, P. Population size and breeding performance of Egyptian vultures (Neophron percnopterus) in eastern Iberian Peninsula. J. Raptor Res. 40, 217–221 (2006).Article 

    Google Scholar 
    39.Velevski, M., Grubac, B. & Tomovic, L. Population viability analysis of the Egyptian vulture Neophron percnopterus in Macedonia and Implications for Its Conservation. Acta Zool. Bulg. 66, 43–58 (2014).
    Google Scholar 
    40.Arkumarev, V. et al. Breeding performance and population trend of the Egyptian vulture Neophron percnopterus in Bulgaria conservation implications. Ornis Fenn. 95, 115–127 (2018).
    Google Scholar 
    41.Dobrev, V. et al. Habitat of the Egyptian vulture (Neophron percnopterus) in Bulgaria and Greece (2003–2014). (2016).42.Milchev, B., Spassov, N. & Popov, V. Diet of the Egyptian vulture (Neophron percnopterus) after livestock reduction in Eastern Bulgaria. N. West. J. Zool. 8, 315–323 (2012).
    Google Scholar 
    43.Milchev, B. & Georgiev, V. Extinction of the globally endangered Egyptian vulture Neophron percnopterus breeding in SE Bulgaria. N. West. J. Zool. 10, 266–272 (2014).
    Google Scholar 
    44.Poirazidis, K., Goutner, V., Skartsi, T. & Stamou, G. Modelling nesting habitat as a conservation tool for the Eurasian black vulture (Aegypius monachus) in Dadia Nature Reserve, northeastern Greece. Biol. Conserv. 118, 235–248 (2004).Article 

    Google Scholar 
    45.Sanchis Serra, A. et al. Towards the identification of a new taphonomic agent: An analysis of bone accumulations obtained from modern Egyptian vulture (Neophron percnopterus) nests. Quat. Int. 330, 136–149 (2014).Article 

    Google Scholar 
    46.Vittorio, M. D., Lopez-Lopez, P., Cortone, G. & Luiselli, L. The diet of the Egyptian vulture (Neophron percnopterus) in Sicily: Temporal variation and conservation implications. Vie Milieu Life Environ. 67, 1–8 (2017).
    Google Scholar 
    47.Di Vittorio, M. et al. Successful fostering of a captive-born Egyptian Vulture (Neophron Percnopterus) in Sicily. J. Raptor Res. 40, 247–248 (2006).Article 

    Google Scholar 
    48.Sarà, M., Grenci, S. & Vittorio, M. D. Status of Egyptian vulture (Neophron percnopterus) in Sicily. J. Raptor Res. 43, 66–69 (2009).Article 

    Google Scholar 
    49.Vittorio, M. D. et al. Dispersal of Egyptian vultures Neophron percnopterus: the first case of long-distance relocation of an individual from France to Sicily. Ringing Migr. 31, 111–114 (2016).Article 

    Google Scholar 
    50.García-Heras, M. S., Cortés-Avizanda, A. & Donázar, J. A. Who are we feeding? Asymmetric individual use of surplus food resources in an insular population of the endangered Egyptian vulture Neophron percnopterus. PLoS ONE 8, e80523 (2013).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    51.Gangoso, L. et al. Susceptibility to infection and immune response in insular and continental populations of Egyptian vulture: Implications for conservation. PLoS ONE 4, e6333 (2009).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    52.Donazar, J. A. et al. Conservation status and limiting factors in the endangered population of Egyptian vulture (Neophron percnopterus) in the Canary Islands Conservation status and limiting factors in the endangered population of Egyptian vulture ( Neophron percnopterus ) in. Biol. Conserv. 107, 89–97 (2002).Article 

    Google Scholar 
    53.Rodríguez, B., Rodríguez, A., Siverio, F. & Siverio, M. Factors affecting the spatial distribution and breeding habitat of an insular cliff-nesting raptor community. Curr. Zool. 64, 173–181 (2018).PubMed 
    Article 

    Google Scholar 
    54.Kret, E. et al. First documented case of the killing of an egyptian vulture (Neophron Percnopterus) for belief-based practices in Western Africa. Life Environ. 68, 45–50 (2018).
    Google Scholar 
    55.Thouless, C. R., Fanshawe, J. H. & Bertram, B. C. R. Egyptian vultures Neophron percnopterus and Ostrich Struthio camelus eggs: the origins of stone-throwing behaviour. Ibis (Lond.) 131, 9–15 (1989).Article 

    Google Scholar 
    56.Cuthbert, R. et al. Rapid population declines of Egyptian vulture (Neophron percnopterus) and red-headed vulture (Sarcogyps calvus) in India. Anim. Conserv. 9, 349–354 (2006).Article 

    Google Scholar 
    57.Samson, A. & Ramakarishnan, B. Observation of a population of Egyptian Vultures Neophron percnopterus in Ramanagaram Hills, Karnataka, southern India. Vulture News 71, 36–49 (2016).Article 

    Google Scholar 
    58.Farashi, A. & Alizadeh-Noughani, M. Niche modelling of the potential distribution of the Egyptian Vulture Neophron percnopterus during summer and winter in Iran, to identify gaps in protected area coverage. Bird Conserv. Int. 29, 423–436 (2019).Article 

    Google Scholar 
    59.Tauler-Ametller, H., Hernández-Matías, A., Pretus, J. L. L. & Real, J. Landfills determine the distribution of an expanding breeding population of the endangered Egyptian vulture Neophron percnopterus. Ibis (Lond). 159, 757–768 (2017).Article 

    Google Scholar 
    60.Mateo-Tomás, P. & Olea, P. P. Diagnosing the causes of territory abandonment by the Endangered Egyptian vulture Neophron percnopterus: The importance of traditional pastoralism and regional conservation. Oryx 44, 424–433 (2010).Article 

    Google Scholar 
    61.Galligan, T. H. et al. Have population declines in Egyptian vulture and Red-headed vulture in India slowed since the 2006 ban on veterinary diclofenac?. Bird Conserv. Int. 24, 272–281 (2014).Article 

    Google Scholar 
    62.Lieury, N., Gallardo, M., Ponchon, C., Besnard, A. & Millon, A. Relative contribution of local demography and immigration in the recovery of a geographically-isolated population of the endangered Egyptian vulture. Biol. Conserv. 191, 349–356 (2015).Article 

    Google Scholar 
    63.Porter, R. F. & Suleiman, A. S. the Egyptian Vulture Neophron percnopterus on Socotra, Yemen: Population, ecology, conservation and ethno-ornithology. Sandgrouse 34, 44–62 (2012).
    Google Scholar  More

  • in

    Coordination during group departures and progressions in the tolerant multi-level society of wild Guinea baboons (Papio papio)

    1.Conradt, L. & Roper, T. J. Group decision-making in animals. Nature 421, 155–158 (2003).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    2.King, A. J. & Cowlishaw, G. Leaders, followers and group decision-making. Commun. Integr. Biol. 2, 147–150 (2009).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    3.Couzin, I. D. & Franks, N. R. Self-organized lane formation and optimized traffic flow in army ants. Proc. R. Soc. B Biol. Sci. 270, 139–146 (2003).CAS 
    Article 

    Google Scholar 
    4.Ballerini, M. et al. Empirical investigation of starling flocks: a benchmark study in collective animal behaviour. Anim. Behav. 76, 201–215 (2008).Article 

    Google Scholar 
    5.Couzin, I. D., Krause, J., James, R., Ruxton, G. D. & Franks, N. R. Collective memory and spatial sorting in animal groups. J. Theor. Biol. 218, 1–11 (2002).ADS 
    MathSciNet 
    PubMed 
    Article 

    Google Scholar 
    6.Dyer, J. R. G., Johansson, A., Helbing, D., Couzin, I. D. & Krause, J. Leadership, consensus decision making and collective behaviour in humans. Philos. Trans. R. Soc. B Biol. Sci. 364, 781–789 (2009).7.Brent, L. J. N. et al. Ecological knowledge, leadership, and the evolution of menopause in killer whales. Curr. Biol. 25, 746–750 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    8.Lee, H. C. & Teichroeb, J. A. Partially shared consensus decision making and distributed leadership in vervet monkeys: older females lead the group to forage. Am. J. Phys. Anthropol. 161, 580–590 (2016).PubMed 
    Article 

    Google Scholar 
    9.Smith, J. E. et al. Collective movements, leadership and consensus costs at reunions in spotted hyaenas. Anim. Behav. 105, 187–200 (2015).Article 

    Google Scholar 
    10.Fischhoff, I. R. et al. Social relationships and reproductive state influence leadership roles in movements of plains zebra Equus burchellii. Anim. Behav. 73, 825–831 (2007).Article 

    Google Scholar 
    11.Conradt, L. & Roper, T. J. Consensus decision making in animals. Trends Ecol. Evol. 20, 449–456 (2005).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Stueckle, S. & Zinner, D. To follow or not to follow: decision making and leadership during the morning departure in chacma baboons. Anim. Behav. 75, 1995–2004 (2008).Article 

    Google Scholar 
    13.Sueur, C. & Petit, O. Shared or unshared consensus decision in macaques?. Behav. Processes 78, 84–92 (2008).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    14.Strandburg, P, Eshkin, A., Farine, D. R., Couzin, I. D. & Crofoot, M. C. Shared decision-making drives collective movement in wild baboons. Science 348, 1358–1361 (2015).15.Fischer, J. & Zinner, D. Communication and cognition in primate group movement. Int. J. Primatol. 32, 1279–1295 (2011).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    16.Pyritz, L. W., King, A. J., Sueur, C. & Fichtel, C. Reaching a consensus: terminology and concepts used in coordination and decision-making research. Int. J. Primatol. 32, 1268–1278 (2011).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    17.Raveling, D. G. Preflight and flight behavior of Canada geese. Auk 86, 671–681 (1969).Article 

    Google Scholar 
    18.Byrne, R. W., Whiten, A. & Henzi, S. P. Social relationships of mountain baboons: leadership and affiliation in a non-female-bonded monkey. Am. J. Primatol. 20, 313–329 (1990).CAS 
    PubMed 
    Article 

    Google Scholar 
    19.Boinski, S. & Garber, P. A. On the move: how and why animals travel in groups: on the move: how and why animals travel in groups. Am. Anthropol. 104, 669–670 (2002).Article 

    Google Scholar 
    20.Ramseyer, A., Thierry, B., Boissy, A. & Dumont, B. Decision-making processes in group departures of cattle. Ethology 115, 948–957 (2009).Article 

    Google Scholar 
    21.Petit, O. & Bon, R. Decision-making processes: the case of collective movements. Behav. Processes 84, 635–647 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.King, A. J., Johnson, D. D. P. & Van Vugt, M. The origins and evolution of leadership. Curr. Biol. 19, R911–R916 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    23.Krause, J., Hoare, D., Krause, S., Hemelrijk, C. K. & Rubenstein, D. I. Leadership in fish shoals. Fish Fish. 1, 82–89 (2000).Article 

    Google Scholar 
    24.Allen, C. R. B., Brent, L. J. N., Motsentwa, T., Weiss, M. N. & Croft, D. P. Importance of old bulls: leaders and followers in collective movements of all-male groups in African savannah elephants (Loxodonta africana). Sci. Rep. 10, 1–9 (2020).Article 
    CAS 

    Google Scholar 
    25.Pettit, B., Ákos, Z., Vicsek, T. & Biro, D. Speed determines leadership and leadership determines learning during pigeon flocking. Curr. Biol. 25, 3132–3137 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Mutinda, H., Poole, J. H. & Moss, C. F. Decision making and leadership in using the ecosystem. in The Amboseli Elephants: A Long-Term Perspective on a Long-Lived Mammal (Chicago Scholarship, 2011).27.Kummer, H. Social Organization of Hamadryas Baboons: A Field Study. Bibliotheca Primatologica (University of Chicago Press, 1968).28.Holekamp, K. E., Boydston, E. E., & Smale, L. Group travel in social carnivores. in On the move: How and why animals travel in groups 587–627 (University of Chicago Press, 2000).29.Pyritz, L. W., Kappeler, P. M. & Fichtel, C. Coordination of group movements in wild red-fronted lemurs (Eulemur rufifrons): processes and influence of ecological and reproductive seasonality. Int. J. Primatol. 32, 1325–1347 (2011).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    30.Jacobs, A., Maumy, M. & Petit, O. The influence of social organisation on leadership in brown lemurs (Eulemur fulvus fulvus) in a controlled environment. Behav. Processes 79, 111–113 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    31.Farine, D. R., Strandburg-Peshkin, A., Couzin, I. D., Berger-Wolf, T. Y. & Crofoot, M. C. Individual variation in local interaction rules can explain emergent patterns of spatial organization in wild baboons. Proc. R. Soc. B Biol. Sci. 284, 25–29 (2017).
    Google Scholar 
    32.Kappeler, P. M. A framework for studying social complexity. Behav. Ecol. Sociobiol. 73, 13 (2019).Article 

    Google Scholar 
    33.Papageorgiou, D. & Farine, D. R. Shared decision-making allows subordinates to lead when dominants monopolize resources. Sci. Adv. 6, 1–8 (2020).Article 

    Google Scholar 
    34.Conradt, L., Krause, J., Couzin, I. D. & Roper, T. J. ‘Leading according to need’ in self-organizing groups. Am. Nat. 173, 304–312 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    35.Rodriguez-Santiago, M. et al. Behavioral traits that define social dominance are the same that reduce social influence in a consensus task. Proc. Natl. Acad. Sci. U. S. A. 117, 18566–18573 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    36.Grueter, C. C. et al. Multilevel organisation of animal sociality. Trends Ecol. Evol. 35, 834–847 (2020).PubMed 
    Article 

    Google Scholar 
    37.Kummer, H. In Quest of the Sacred Baboon: a Scientist’s Journey. (Princeton University Press, 1995).38.Fischer, J. et al. Charting the neglected West: The social system of Guinea baboons. Am. J. Phys. Anthropol. 162, 15–31 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    39.Whitehead, H. et al. Multilevel societies of female sperm whales (Physeter macrocephalus) in the Atlantic and Pacific: Why Are they so different?. Int. J. Primatol. 33, 1142–1164 (2012).Article 

    Google Scholar 
    40.Kummer, H. Two variations in the social organization of baboons. in Primates: studies in adaptation and variability 293–312 (Holt, Rinehart & Winston, 1968).41.Fischer, J. et al. The Natural History of Model Organisms: Insights into the evolution of social systems and species from baboon studies. Elife 8, e50989 (2019).42.Swedell, L. African Papionins: Diversity of social organization and ecological flexibility. in Primates in perspective 241–277 (Oxford University Press, 2011).43.Anandam, M., Bennett, E. & Davenport, T. Species accounts of Cercopithecidae. in Handbook ofthe mammals of the world Vol. 3 primates 628–753 (Lynx Edicions, 2013).44.Barrett, L. & Henzi, S. P. Baboons. Curr. Biol. 18, 404–406 (2008).Article 
    CAS 

    Google Scholar 
    45.Ransom, T. W. Beach troop of the Gombe. (Bucknell University Press, 1981).46.Norton, G. Leadership: decision processes of group movement in yellow baboons. in Primate ecology and conservation. 145–156 (Cambridge University Press, 1986).47.Stoltz, L. & Saayman, G. S. Ecology and behaviour of baboons in the northern transvaal. Nature 26, 99–142 (1970).
    Google Scholar 
    48.Buskirk, W. H., Buskirk, R. E. & Hamilton, W. J. Troop-mobilizing behavior of adult male chacma baboons. Folia Primatol. 22, 9–18 (1974).CAS 
    Article 

    Google Scholar 
    49.Collins, D. A. Spatial pattern in a troop of yellow baboons (Papio cynocephalus) in Tanzania. Anim. Behav. 32, 536–553 (1984).Article 

    Google Scholar 
    50.Rhine, R. J., Hendy, H. M., Stillwell-Barnes, R., Westlund, B. J. & Westlund, H. D. Movement Patterns of YeIIow Baboons (Papio cynocephaius): Central Positioning of Walking Infants. Am. J. Phys. Anthropol. 53, 159–167 (1980).Article 

    Google Scholar 
    51.Rhine, R. J. & Owens, N. W. The order of movement of adult male and black infant baboons (Papio anubis) entering and leaving a potentially dangerous clearing. Folia Primatol. 18, 276–283 (1972).CAS 
    Article 

    Google Scholar 
    52.Rhine, R. J. & Westlund, B. J. Adult Male positioning in baboon progressions: order and chaos revisited. Folia Primatol. 35, 77–116 (1981).CAS 
    Article 

    Google Scholar 
    53.Rhine, R. J., Bioland, P. & Lodwick, L. Progressions of adult male chacma baboons (Papio ursinus) in the moremi wildlife reserve. Int. J. Primatol. 6, 115–122 (1985).Article 

    Google Scholar 
    54.Rowell, T. Long-term changes in a population of ugandan baboons. Folia Primatol. 11, 241–254 (1969).CAS 
    Article 

    Google Scholar 
    55.Sigg, H. & Stolba, A. Home range and daily march in a Hamadryas baboon troop. Folia Primatol. (Basel) 36, 40–75 (1981).CAS 
    Article 

    Google Scholar 
    56.Schweitzer, C., Gaillard, T., Guerbois, C., Fritz, H. & Petit, O. Participant profiling and pattern of crop-foraging in chacma baboons (Papio hamadryas ursinus) in Zimbabwe: Why Does Investigating Age-Sex Classes Matter?. Int. J. Primatol. 38, 207–223 (2017).Article 

    Google Scholar 
    57.Stolba, A. Entscheidungstindung in verbanden von papio hamadryas. (University of Zurich, 1979).58.Strandburg-Peshkin, A., Papageorgiou, D., Crofoot, M. C. & Farine, D. R. Inferring influence and leadership in moving animal groups. Philos. Trans. R. Soc. B Biol. Sci. 373, (2018).59.Harding, R. S. O. Patterns of movement in open country baboons. Am. J. Phys. Anthropol. 47, 349–353 (1977).Article 

    Google Scholar 
    60.DeVore, I. & Washburn, S. L. Baboon Ecology and Human Evolution. in African Ecology and Human Evolution 335–367 (Routledge, 2017).61.Altmann, S. A. Baboon progressions: Order or chaos? A study of one-dimensional group geometry. Anim. Behav. 27, 46–80 (1979).Article 

    Google Scholar 
    62.Goffe, A. S., Zinner, D. & Fischer, J. Sex and friendship in a multilevel society : behavioural patterns and associations between female and male Guinea baboons. Behav. Ecol. Sociobiol. 70, 323–336 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    63.Patzelt, A. et al. Male tolerance and male – male bonds in a multilevel primate society. PNAS 111, 14740–14745 (2014).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    64.Pines, M., Saunders, J. & Swedell, L. Alternative routes to the leader male role in a multi-level society: Follower vs. solitary male strategies and outcomes in hamadryas baboons. Am. J. Primatol. 73, 679–691 (2011).65.Schreier, A. L. & Swedell, L. The fourth level of social structure in a multi-level society: Ecological and social functions of clans in Hamadryas Baboons. Am. J. Primatol. 71, 948–955 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    66.Dal Pesco, F., Trede, F., Zinner, D. & Fischer, J. Kin bias and male pair-bond status shape male-male relationships in a multilevel primate society. Behav. Ecol. Sociobiol. 75, 1–14 (2021).Article 

    Google Scholar 
    67.Strandburg-peshkin, A., Farine, D. R., Couzin, I. D. & Crofoot, M. C. Shared decision-making drives collective movement in wild baboons. Science 348, 1358–1361 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    68.Leca, J. B., Gunst, N., Thierry, B. & Petit, O. Distributed leadership in semifree-ranging white-faced capuchin monkeys. Anim. Behav. 66, 1045–1052 (2003).Article 

    Google Scholar 
    69.Rhine, R. J. The order of movement of yellow baboons. Folia Primatol 23, 72–104 (1975).CAS 
    Article 

    Google Scholar 
    70.Rhine, R. J. & Tilson, R. Reactions to fear as a proximate factor in the sociospatial organization of baboon progressions. Am. J. Primatol. 13, 119–128 (1987).PubMed 
    Article 

    Google Scholar 
    71.Bonnell, T. R., Clarke, P. M., Henzi, S. P. & Barrett, L. Individual-level movement bias leads to the formation of higher-order social structure in a mobile group of baboons. R. Soc. Open Sci. 4, (2017).72.Strandburg-Peshkin, A., Farine, D. R., Crofoot, M. C. & Couzin, I. D. Habitat and social factors shape individual decisions and emergent group structure during baboon collective movement. Elife 6, (2017).73.King, A. J., Douglas, C. M. S., Huchard, E., Isaac, N. J. B. & Cowlishaw, G. Dominance and affiliation mediate despotism in a social primate. Curr. Biol. 18, 1833–1838 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    74.King, A. J., Sueur, C., Huchard, E. & Cowlishaw, G. A rule-of-thumb based on social affiliation explains collective movements in desert baboons. Anim. Behav. 82, 1337–1345 (2011).Article 

    Google Scholar 
    75.Harel, R., Loftus, C. J. & Crofoot, M. C. Locomotor compromises maintain group cohesion in baboon troops on the move. bioRxiv (2020).76.Wang, C. et al. Decision-making process during collective movement initiation in golden snub-nosed monkeys (Rhinopithecus roxellana). Sci. Rep. 10, 1–10 (2020).Article 
    CAS 

    Google Scholar 
    77.Whitehead, H. Consensus movements by groups of sperm whales. Mar. Mammal Sci. 32, 1402–1415 (2016).Article 

    Google Scholar 
    78.Crook, J. H. Gelada baboon herd structure and movement a comparative report. Symp. Zool. Soc. London 18, 237–258 (1966).
    Google Scholar 
    79.Grueter, C. C., Li, D., Ren, B., Wei, F. & Li, M. Deciphering the social organization and structure of wild yunnan snub-nosed monkeys (Rhinopithecus bieti). Folia Primatol. 88, 358–383 (2017).Article 

    Google Scholar 
    80.Zinner, D. et al. Comparative ecology of Guinea baboons (Papio papio). Primate Biol. 8, 19–35 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    81.Altmann, J. Observational study of behavior: sampling methods. Behaviour 49, 227–266 (1974).CAS 
    PubMed 
    Article 

    Google Scholar 
    82.Sueur, C. & Petit, O. Organization of group members at departure is driven by social structure in Macaca. Int. J. Primatol. 29, 1085–1098 (2008).Article 

    Google Scholar 
    83.Seltmann, A., Majolo, B., Schülke, O. & Ostner, J. The Organization of Collective Group Movements in Wild Barbary Macaques (Macaca sylvanus): Social Structure Drives Processes of Group Coordination in Macaques. PLoS One 8, (2013).84.Core Team, R. R: A Language and Environment for Statistical Computing. (2018).85.Baayen, R. H. Analyzing linguistic data: A practical introduction to statistics using R. Anal. Linguist. Data A Pract. Introd. to Stat. Using R 1–353 (2008).86.Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Software 67, 1–48 (2015).Article 

    Google Scholar 
    87.Dobson, A. An introduction to generalized linear models. (CRC Press, 2002).88.Forstmeier, W. & Schielzeth, H. Cryptic multiple hypotheses testing in linear models: Overestimated effect sizes and the winner’s curse. Behav. Ecol. Sociobiol. 65, 47–55 (2011).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    89.Bolker, B. M. et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    90.Barr, D. J., Levy, R., Scheepers, C. & Tily, H. J. Random effects structure for confirmatory hypothesis testing: Keep it maximal. J. Mem. Lang. 68, 255–278 (2013).Article 

    Google Scholar 
    91.Fahrmeir, L., Kneib, T., Lang, S. & Marx, B. Regression Modesl (Springer, 2013).MATH 
    Book 

    Google Scholar 
    92.Hadfield, J. D. MCMCglmm: MCMC Methods for Multi-Response GLMMs in R. J. Stat. Softw. 33, 1–22 (2010).Article 

    Google Scholar  More

  • in

    Turn taking is not restricted by task specialisation but does not facilitate equality in offspring provisioning

    1.Trivers, R. L. Parental investment and sexual selection. in Sexual Selection and the Descent of Man 1871–1971 136–207 (Aldine, 1972). doi:https://doi.org/10.1002/ajpa.13304002262.Stearns, S. Trade-offs in life-history evolution. Funct. Ecol. 3, 259–268 (1989).Article 

    Google Scholar 
    3.McNamara, J. M., Gasson, C. E. & Houston, A. I. Incorporating rules for responding into evolutionary games. Nature 401, 368–371 (1999).ADS 
    CAS 
    PubMed 

    Google Scholar 
    4.Houston, A. I. & Davies, N. B. The evolution of cooperation and life-history in the dunnock. Behav. Ecol. 1, 471–487 (1985).
    Google Scholar 
    5.McNamara, J. M., Houston, A. I., Barta, Z. & Osorno, J. L. Should young ever be better off with one parent than with two?. Behav. Ecol. 14, 301–310 (2003).Article 

    Google Scholar 
    6.Lessells, C. M. & McNamara, J. M. Sexual conflict over parental investment in repeated bouts: negotiation reduces overall care. Proc. R. Soc. B Biol. Sci. 279, 1506–1514 (2012).CAS 
    Article 

    Google Scholar 
    7.Harrison, F., Barta, Z. & Székely, T. How is sexual conflict over parental care resolved? A meta-analysis.. J. Evol. Biol. 22, 1800–1812 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    8.Johnstone, R. A. & Hinde, C. A. Negotiation over offspring care – how should parents respond to each other’s efforts?. Behav. Ecol. 17, 818–827 (2006).Article 

    Google Scholar 
    9.Johnstone, R. A. et al. Reciprocity and conditional cooperation between great tit parents. Behav. Ecol. 25, 216–222 (2014).Article 

    Google Scholar 
    10.Gächter, S. Conditional cooperation: behavioral regularities from the lab and the field and their policy implications. In Psychology and economics: a promising new cross-disciplinary field (eds Frey, B. S. & Stutzer, A.) 19–50 (MIT Press, 2007).
    Google Scholar 
    11.Hinde, C. A. Negotiation over offspring care? – A positive response to partner-provisioning rate in great tits. Behav. Ecol. 17, 6–12 (2006).Article 

    Google Scholar 
    12.Meade, J., Nam, K.-B., Lee, J.-W. & Hatchwell, B. J. An experimental test of the information model for negotiation of biparental care. PLoS ONE 6, e19684 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    13.Savage, J. L., Browning, L. E., Manica, A., Russell, A. F. & Johnstone, R. A. Turn-taking in cooperative offspring provisioning: by-product of individual provisioning behaviour or active response rule?. Behav. Ecol. Sociobiol. 71, 162 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    14.Santema, P., Schlicht, E. & Kempenaers, B. Testing the conditional cooperation model: What can we learn from parents taking turns when feeding offspring?. Front. Ecol. Evol. 7, 1–6 (2019).Article 

    Google Scholar 
    15.Baldan, D., Curk, T., Hinde, C. A. & Lessells, C. M. Alternation of nest visits varies with experimentally manipulated workload in brood-provisioning great tits. Anim. Behav. 156, 139–146 (2019).Article 

    Google Scholar 
    16.Baldan, D., Hinde, C. A. & Lessells, C. M. Turn-Taking Between Provisioning Parents: Partitioning Alternation. Front. Ecol. Evol. 7, 1 (2019).Article 

    Google Scholar 
    17.Iserbyt, A., Fresneau, N., Kortenhoff, T., Eens, M. & Müller, W. Decreasing parental task specialization promotes conditional cooperation. Sci. Rep. 7, 6565 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    18.Lessells, C. M. Sexual selection. in The evolution of parental care (eds. Royle, N. J., Smiseth, P. T. & Kolliker, M.) 150–170 (Oxford university press, 2012).19.Barta, Z., Székely, T., Liker, A. & Harrison, F. Social role specialization promotes cooperation between parents. Am. Nat. 183, 747–761 (2014).PubMed 
    Article 

    Google Scholar 
    20.Andreasson, F., Nord, A. & Nilsson, J. -Å. Brood size constrains the development of endothermy in blue tits. J. Exp. Biol. 219, 2212–2219 (2016).PubMed 
    Article 

    Google Scholar 
    21.Perrins, C. M. British tits. (Collins, 1979).22.Banbura, J. et al. Sex differences in parental care in a Corsican Blue Tit Parus caeruleus population. Ardea 89, 517–526 (2001).
    Google Scholar 
    23.García-Navas, V., Ferrer, E. S. & Sanz, J. J. Plumage yellowness predicts foraging ability in the blue tit Cyanistes caeruleus. Biol. J. Linn. Soc. 106, 418–429 (2012).Article 

    Google Scholar 
    24.Mainwaring, M. C. et al. Latitudinal variation in blue tit and great tit nest characteristics indicates environmental adjustment. J. Biogeogr. 39, 1669–1677 (2012).Article 

    Google Scholar 
    25.Pagani-Núñez, E. & Senar, J. C. One hour of sampling is enough: Great tit Parus major parents feed their nestlings consistently across time. Acta Ornithol. 48, 194–200 (2013).Article 

    Google Scholar 
    26.Griffioen, M., Müller, W. & Iserbyt, A. A fixed agreement—consequences of brood size manipulation on alternation in blue tits. PeerJ 7, e6826 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    27.Ihle, M., Pick, J. L., Winney, I. S., Nakagawa, S. & Burke, T. Measuring up to reality: Null models and analysis simulations to study parental coordination over provisioning offspring. Front. Ecol. Evol. 7, 142 (2019).Article 

    Google Scholar 
    28.Schlicht, E., Santema, P., Schlicht, R. & Kempenaers, B. Evidence for cooperation in biparental care systems? A comment on Johnstone et al.. Behav. Ecol. 27, 1 (2016).Article 

    Google Scholar 
    29.Griffioen, M., Iserbyt, A. & Müller, W. Handicapping males does not affect their rate of parental provisioning, but impinges on their partners’ turn taking behavior. Front. Ecol. Evol. 7, 1–7 (2019).Article 

    Google Scholar 
    30.Andreasson, F., Nord, A. & Nilsson, J.-Å. Experimentally increased nest temperature affects body temperature, growth and apparent survival in blue tit nestlings. J. Avian Biol. Biol. e01620, (2018).31.Iserbyt, A., Griffioen, M., Eens, M. & Müller, W. Enduring rules of care within pairs – how blue tit parents resume provisioning behaviour after experimental disturbance. Sci. Rep. 9, 2776 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    32.Lucass, C., Fresneau, N., Eens, M. & Müller, W. Sex roles in nest keeping – how information asymmetry contributes to parent-offspring co-adaptation. Ecol. Evol. 6, 1825–1833 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    33.Yoon, J., Sofaer, H. R., Sillett, T. S., Morrison, S. A. & Ghalambor, C. K. The relationship between female brooding and male nestling provisioning: Does climate underlie geographic variation in sex roles ?. J. Avian Biol. 47, 1–9 (2016).Article 

    Google Scholar 
    34.Amininasab, S. M., Kingma, S. A., Birker, M., Hildenbrandt, H. & Komdeur, J. The effect of ambient temperature, habitat quality and individual age on incubation behaviour and incubation feeding in a socially monogamous songbird. Behav. Ecol. Sociobiol. https://doi.org/10.1007/s00265-016-2167-2 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    35.Bryan, S. M. & Bryant, D. M. Heating nest-boxes reveals an energetic constraint on incubation behaviour in great tits, Parus major. Proc. R. Soc. B 266, 157 (1999).PubMed Central 
    Article 

    Google Scholar 
    36.Sanz, J. J. & Moreno, J. Mass loss in brooding female pied flycatchers ficedula hypoleuca: No evidence for reproductive stress. J. Avian Biol. 26, 313 (1995).Article 

    Google Scholar 
    37.Chastel, O. & Kersten, M. Brood size and body condition in the House Sparrow Passer domesticus: The influence of brooding behaviour. Ibis (Lond. 1859). 144, 284–292 (2002).38.Stearns, S. The evolution of life histories. (Oxford University Press (OUP), 1992). https://doi.org/10.5962/bhl.title.166231.39.Ardia, D. R., Perez, J. H. & Clotfelter, E. D. Experimental cooling during incubation leads to reduced innate immunity and body condition in nestling tree swallows. Proc. R. Soc. B – Biol. Sci. 277, 1881–1888 (2010).40.Perez, J. H., Ardia, D. R., Chad, E. K. & Clotfelter, E. D. Experimental heating reveals nest temperature affects nestling condition in tree swallows ( Tachycineta bicolor ). Biol. Lett. 4, 468–471 (2008).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    41.Nour, N., Currie, D., Matthysen, E., Van Damme, R. & Dhondt, A. A. Effects of habitat fragmentation on provisioning rates, diet and breeding success in two species of tit (great tit and blue tit). Oecologia 114, 522–530 (1998).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    42.Grieco, F. Time constraint on food choice in provisioning blue tits, Parus caeruleus: The relationship between feeding rate and prey size. Anim. Behav. 64, 517–526 (2002).Article 

    Google Scholar 
    43.Jenkins, J. B., Mueller, A. J., Thompson, C. F., Sakaluk, S. K. & Bowers, E. K. Female birds monitor the activity of their mates while brooding nest-bound young. Anim. Cogn. https://doi.org/10.1007/s10071-020-01453-5 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    44.Johnstone, R. A. & Savage, J. L. Conditional cooperation and turn-taking in parental care. Front. Ecol. Evol. 7, 1 (2019).Article 

    Google Scholar 
    45.Santema, P., Schlicht, E., Schlicht, L. & Kempenaers, B. Blue tits do not return faster to the nest in response to either short- or long-term begging playbacks. Anim. Behav. 123, 117–127 (2017).Article 

    Google Scholar 
    46.Székely, T. Sexual Conflict Between Parents: Offspring Desertion and Asymmetrical Parental Care. Cold Spring Harb. Perspect. Biol. 6, 1–20 (2014).Article 

    Google Scholar 
    47.Griffith, S. C. Cooperation and Coordination in Socially Monogamous Birds: Moving Away From a Focus on Sexual Conflict. Front. Ecol. Evol. 7, 1–15 (2019).Article 

    Google Scholar 
    48.Patrick, S. C., Corbeau, A., Réale, D. & Weimerskirch, H. Coordination in parental effort decreases with age in a long-lived seabird. Oikos 129, 1763–1772 (2020).Article 

    Google Scholar 
    49.Lejeune, L. et al. Environmental effects on parental care visitation patterns in blue tits Cyanistes caeruleus. Front. Ecol. Evol. 7, 1–15 (2019).Article 

    Google Scholar 
    50.Baldan, D. & Ouyang, J. Q. Urban resources limit pair coordination over offspring provisioning. Sci. Rep. 1, 1–11. https://doi.org/10.1038/s41598-020-72951-2 (2020).CAS 
    Article 

    Google Scholar 
    51.Bebbington, K. & Hatchwell, B. J. Coordinated parental provisioning is related to feeding rate and reproductive success in a songbird. Behav. Ecol. 27, 652–659 (2016).Article 

    Google Scholar 
    52.Koenig, W. D. & Walters, E. L. Provisioning patterns in the cooperatively breeding acorn woodpecker: does feeding behaviour serve as a signal?. Anim. Behav. 119, 125–134 (2016).Article 

    Google Scholar 
    53.Leniowski, K. & Węgrzyn, E. Synchronisation of parental behaviours reduces the risk of nest predation in a socially monogamous passerine bird. Sci. Rep. 8, 7385 (2018).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    54.Tyson, C. et al. Coordinated provisioning in a dual foraging pelagic seabird. Anim. Behav. 132, 73–79 (2017).Article 

    Google Scholar 
    55.Wojczulanis-Jakubas, K., Araya-Salas, M. & Jakubas, D. Seabird parents provision their chick in a coordinated manner. PLoS ONE 13, 1–13 (2018).Article 
    CAS 

    Google Scholar  More

  • in

    Genetic diversity in North American Cercis Canadensis reveals an ancient population bottleneck that originated after the last glacial maximum

    1.Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913. https://doi.org/10.1038/35016000 (2000).ADS 
    Article 
    PubMed 
    CAS 

    Google Scholar 
    2.Hewitt, G. Genetic consequences of climatic oscillations in the Quaternary. Philos. Trans. R. Soc. Lond. 359, 183–195. https://doi.org/10.1098/rstb.2003.1388 (2004).Article 
    CAS 

    Google Scholar 
    3.Ehlers, J. & Gibbard, P. Quaternary Glaciations-Extent and Chronology: Part I: Europe Vol. 2 (Elsevier, New York, 2004).
    Google Scholar 
    4.Call, A. et al. Genetic structure and post-glacial expansion of Cornus florida L. (Cornaceae): Integrative evidence from phylogeography, population demographic history, and species distribution modeling. J. Syst. Evol. 54, 136–151. https://doi.org/10.1111/jse.12171 (2016).Article 

    Google Scholar 
    5.Jackson, S. et al. Vegetation and environment in eastern North America during the Last Glacial Maximum. Quatern. Sci. Rev. 19, 489–508. https://doi.org/10.1016/S0277-3791(99)00093-1 (2000).ADS 
    Article 

    Google Scholar 
    6.Nadeau, S. et al. Contrasting patterns of genetic diversity across the ranges of Pinus monticola and P. strobus: A comparison between eastern and western North American postglacial colonization histories. Am. J. Bot. 102, 1342–1355. https://doi.org/10.3732/ajb.1500160 (2015).Article 
    PubMed 
    CAS 

    Google Scholar 
    7.Beaulieu, J. & Simon, J. Genetic structure and variability in Pinus strobus in Quebec. Can. J. For. Res. 24, 1726–1733. https://doi.org/10.1139/x94-223 (1994).Article 

    Google Scholar 
    8.Provan, J. & Bennett, K. Phylogeographic insights into cryptic glacial refugia. Trends Ecol. Evol. 23, 564–571. https://doi.org/10.1016/j.tree.2008.06.010 (2008).Article 
    PubMed 

    Google Scholar 
    9.Soltis, D., Morris, A., McLachlan, J., Manos, P. & Soltis, P. Comparative phylogeography of unglaciated eastern North America. Mol. Ecol. 15, 4261–4293. https://doi.org/10.1111/j.1365-294X.2006.03061.x (2006).Article 
    PubMed 

    Google Scholar 
    10.Mee, J. & Moore, J. The ecological and evolutionary implications of microrefugia. J. Biogeogr. 41, 837–841. https://doi.org/10.1111/jbi.12254 (2014).Article 

    Google Scholar 
    11.Hoban, S. et al. Range-wide distribution of genetic diversity in the North American tree Juglans cinerea: A product of range shifts, not ecological marginality or recent population decline. Mol. Ecol. 19, 4876–4891. https://doi.org/10.1111/j.1365-294X.2010.04834.x (2010).Article 
    PubMed 

    Google Scholar 
    12.Hampe, A. & Petit, R. Conserving biodiversity under climate change: The rear edge matters. Ecol. Lett. 8, 461–467. https://doi.org/10.1111/j.1461-0248.2005.00739.x (2005).Article 
    PubMed 

    Google Scholar 
    13.Excoffier, L., Foll, M. & Petit, R. Genetic consequences of range expansions. Annu. Rev. Ecol. Evol. Syst. 40, 481–501. https://doi.org/10.1146/annurev.ecolsys.39.110707.173414 (2009).Article 

    Google Scholar 
    14.McLachlan, J., Clark, J. & Manos, P. Molecular indicators of tree migration capacity under rapid climate change. Ecology 86, 2088–2098. https://doi.org/10.1890/04-1036 (2005).Article 

    Google Scholar 
    15.Bemmels, J. & Dick, C. Genomic evidence of a widespread southern distribution during the Last Glacial Maximum for two eastern North American hickory species. J. Biogeogr. 45, 1739–1750. https://doi.org/10.1111/jbi.13358 (2018).Article 

    Google Scholar 
    16.Jaramillo-Correa, J., Beaulieu, J., Khasa, D. & Bousquet, J. Inferring the past from the present phylogeographic structure of North American forest trees: Seeing the forest for the genes. Can. J. For. Res. 39, 286–307. https://doi.org/10.1139/X08-181 (2009).Article 

    Google Scholar 
    17.Eckert, C., Samis, K. & Lougheed, S. Genetic variation across species’ geographical ranges: The central–marginal hypothesis and beyond. Mol. Ecol. 17, 1170–1188. https://doi.org/10.1111/j.1365-294X.2007.03659.x (2008).Article 
    PubMed 
    CAS 

    Google Scholar 
    18.Foll, M. & Gaggiotti, O. Identifying the environmental factors that determine the genetic structure of populations. Genetics 174, 875–891. https://doi.org/10.1534/genetics.106.059451 (2006).Article 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar 
    19.Loveless, M. & Hamrick, J. Ecological determinants of genetic structure in plant populations. Ann. Rev. Ecol. Syst. 15, 65–95. https://doi.org/10.1146/annurev.es.15.110184.000433 (1984).Article 

    Google Scholar 
    20.Roberts, D., Werner, D., Wadl, P. & Trigiano, R. Inheritance and allelism of morphological traits in eastern redbud (Cercis canadensis L.). Hortic. Res. 2, 1–11 (2015).Article 

    Google Scholar 
    21.Couvillon, G. Cercis canadensis L. seed size influences germination rate, seedling dry matter, and seedling leaf area. HortScience 37, 206–207 (2002).Article 

    Google Scholar 
    22.Li, S. et al. Methods for breaking the dormancy of eastern redbud (Cercis canadensis) seeds. Seed Sci. Technol. 41, 27–35 (2013).Article 

    Google Scholar 
    23.Cheong, E. & Pooler, M. Micropropagation of Chinese redbud (Cercis yunnanensis) through axillary bud breaking and induction of adventitious shoots from leaf pieces. In Vitro Cell. Dev. Biol. Plant 39, 455–458 (2003).Article 

    Google Scholar 
    24.Pooler, M., Jacobs, K. & Kramer, M. Differential resistance to Botryosphaeria ribis among Cercis taxa. Plant Dis. 86, 880–882. https://doi.org/10.1094/PDIS.2002.86.8.880 (2002).Article 
    PubMed 
    CAS 

    Google Scholar 
    25.Trigiano, R., Beaty, R. & Graham, E. Somatic embryogenesis from immature embryos of redbud (Cercis canadensis). Plant Cell Rep. 7, 148–150. https://doi.org/10.1007/BF00270127 (1988).Article 
    PubMed 
    CAS 

    Google Scholar 
    26.Wadl, P., Trigiano, R., Werner, D., Pooler, M. & Rinehart, T. Simple sequence repeat markers from Cercis canadensis show wide cross-species transfer and use in genetic studies. J. Am. Soc. Hortic. Sci. 137, 189–201. https://doi.org/10.21273/JASHS.137.3.189 (2012).Article 

    Google Scholar 
    27.Ony, M. et al. Habitat fragmentation influences genetic diversity and differentiation: Fine-scale population structure of Cercis canadensis (eastern redbud). Ecol. Evol. 10, 3655–3670. https://doi.org/10.1002/ece3.6141 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    28.Amos, W. et al. Automated binning of microsatellite alleles: Problems and solutions. Mol. Ecol. Resour. 7, 10–14. https://doi.org/10.1111/j.1471-8286.2006.01560.x (2007).Article 
    CAS 

    Google Scholar 
    29.R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2019).30.Kamvar, Z., Tabima, J. & Grünwald, N. Poppr: An R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2, e281. https://doi.org/10.7717/peerj.281 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    31.Kamvar, Z., Brooks, J. & Grünwald, N. Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Front. Genet. 6, 208. https://doi.org/10.3389/fgene.2015.00208 (2015).Article 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar 
    32.Tsui, C. et al. Population structure and migration pattern of a conifer pathogen, Grosmannia clavigera, as influenced by its symbiont, the mountain pine beetle. Mol. Ecol. 21, 71–86. https://doi.org/10.1111/j.1365-294X.2011.05366.x (2012).Article 
    PubMed 

    Google Scholar 
    33.Nei, M. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89, 583–590 (1978).Article 
    CAS 

    Google Scholar 
    34.Shannon, C. E. A mathematical theory of communication. Bell System Tech. J. 27, 379–423 (1948).MathSciNet 
    Article 

    Google Scholar 
    35.Goudet, J. Hierfstat, a package for R to compute and test hierarchical F-statistics. Mol. Ecol. Notes 5, 184–186. https://doi.org/10.1111/j.1471-8286.2004.00828.x (2005).Article 

    Google Scholar 
    36.Hurlbert, S. The nonconcept of species diversity: A critique and alternative parameters. Ecology 52, 577–586. https://doi.org/10.2307/1934145 (1971).Article 

    Google Scholar 
    37.El Mousadik, A. & Petit, R. High level of genetic differentiation for allelic richness among populations of the Argan tree [Argania spinosa (L.) Skeels] endemic to Morocco. Theor. Appl. Genet. 92, 832–839. https://doi.org/10.1007/BF00221895 (1996).Article 
    PubMed 

    Google Scholar 
    38.Bird, C., Karl, S., Smouse, P. & Toonen, R. In Phylogeography and Population Genetics in Crustacea Vol. 19 (eds Held Christoph, Koenemann Stefan, & Schubart Christoph) pp. 31–55 (Boca Raton, FL: CRC Press, 2011).39.Meirmans, P. & Hedrick, P. Assessing population structure: FST and related measures. Mol. Ecol. Resour. 11, 5–18. https://doi.org/10.1111/j.1755-0998.2010.02927.x (2011).Article 
    PubMed 

    Google Scholar 
    40.Pritchard, J., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).Article 
    CAS 

    Google Scholar 
    41.Earl, D. & Bridgett, V. STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361. https://doi.org/10.1007/s12686-011-9548-7 (2012).Article 

    Google Scholar 
    42.Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x (2005).Article 
    CAS 

    Google Scholar 
    43.Francis, R. Pophelper: An R package and web app to analyse and visualize population structure. Mol. Ecol. Resour. 17, 27–32. https://doi.org/10.1111/1755-0998.12509 (2017).Article 
    PubMed 
    CAS 

    Google Scholar 
    44.Becker, R. & Wilks, A. MAPS: An R Package to Drae Geographical Maps (Version package 3.3.0, 2018).45.Lemon, J. Plotrix: An R Package for Various Plotting Functions (Version R package 3.8–1, 2006).46.Bruvo, R., Michiels, N., D’souza, T. & Schulenburg, H. A simple method for the calculation of microsatellite genotype distances irrespective of ploidy level. Mol. Ecol. 13, 2101–2106. https://doi.org/10.1111/j.1365-294X.2004.02209.x (2004).Article 
    PubMed 
    CAS 

    Google Scholar 
    47.Grünwald, N., Everhart, S., Knaus, B. & Kamvar, Z. Best practices for population genetic analyses. Phytopathology 107, 1000–1010. https://doi.org/10.1094/PHYTO-12-16-0425-RVW (2017).Article 
    PubMed 

    Google Scholar 
    48.Jombart, T. & Ahmed, I. adegenet 1.3–1: New tools for the analysis of genome-wide SNP data. Bioinformatics 27, 3070–3072. https://doi.org/10.1093/bioinformatics/btr521 (2011).Article 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar 
    49.Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11, 9. https://doi.org/10.1186/1471-2156-11-94 (2010).Article 

    Google Scholar 
    50.Cullingham, C., Cooke, J. & Coltman, D. Effects of introgression on the genetic population structure of two ecologically and economically important conifer species: Lodgepole pine (Pinus contorta var. latifolia) and jack pine (Pinus banksiana). Genome 56, 577–585. https://doi.org/10.1139/gen-2013-0071 (2013).Article 
    PubMed 
    CAS 

    Google Scholar 
    51.Diniz-Filho, J. et al. Mantel test in population genetics. Genet. Mol. Biol. 36, 475–485. https://doi.org/10.1590/S1415-47572013000400002 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    52.Mantel, N. The detection of disease clustering and a generalized regression approach. Can. Res. 27, 209–220 (1967).CAS 

    Google Scholar 
    53.Vegan: Community ecology package v. R package version 2.5–3 (R package version 2.5–3). (2018).54.Excoffier, L., Smouse, P. & Quattro, J. Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA restriction data. Genetics 131, 479–491 (1992).Article 
    CAS 

    Google Scholar 
    55.Cornuet, J., Ravigné, V. & Estoup, A. Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0). BMC Bioinform. 11, 401–411. https://doi.org/10.1186/1471-2105-11-401 (2010).Article 
    CAS 

    Google Scholar 
    56.Cornuet, J. et al. DIYABC v2.0: A software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data. Bioinformatics 30, 1187–1189. https://doi.org/10.1093/bioinformatics/btt763 (2014).Article 
    PubMed 
    CAS 

    Google Scholar 
    57.Dickson, J. In Silvics of North America Vol. 2 (eds Burns, R. & Honkala, B.) 266–269 (United States Department of Agriculture-Forest Service, 1990).58.Thomson, A., Dick, C. & Dayanandan, S. A similar phylogeographical structure among sympatric North American birches (Betula) is better explained by introgression than by shared biogeographical history. J. Biogeogr. 42, 339–350. https://doi.org/10.1111/jbi.12394 (2015).Article 

    Google Scholar 
    59.Petit, R. et al. Glacial refugia: Hotspots but not melting pots of genetic diversity. Science 300, 1563–1565 (2003).ADS 
    Article 
    CAS 

    Google Scholar 
    60.David, R. & Hamann, A. Glacial refugia and modern genetic diversity of 22 western North American tree species. Proc. R. Soc. B Biol. Sci. 282, 20142903. https://doi.org/10.1098/rspb.2014.2903 (2015).Article 

    Google Scholar 
    61.Lumibao, C., Hoban, S. & McLachlan, J. Ice ages leave genetic diversity ‘hotspots’ in Europe but not in Eastern North America. Ecol. Lett. 20, 1459–1468. https://doi.org/10.1111/ele.12853 (2017).Article 
    PubMed 

    Google Scholar 
    62.Bialozyt, R., Ziegenhagen, B. & Petit, R. Contrasting effects of long distance seed dispersal on genetic diversity during range expansion. J. Evol. Biol. 19, 12–20. https://doi.org/10.1111/j.1420-9101.2005.00995.x (2006).Article 
    PubMed 
    CAS 

    Google Scholar 
    63.Petit, R. Early insights into the genetic consequences of range expansions. Heredity 106, 203–204. https://doi.org/10.1038/hdy.2010.60 (2011).Article 
    PubMed 
    CAS 

    Google Scholar 
    64.Dubreuil, M. et al. Genetic effects of chronic habitat fragmentation revisited: Strong genetic structure in a temperate tree, Taxus baccata (Taxaceae), with great dispersal capability. Am. J. Bot. 97, 303–310. https://doi.org/10.3732/ajb.0900148 (2010).Article 
    PubMed 

    Google Scholar 
    65.Hamrick, J., Godt, M. & Sherman-Broyles, S. In Population Genetics of Forest Trees Vol. 42 (eds Adams, W., Strauss, S., Copes, D. & Griffin, A) 95–124 (Springer, Dordrecht, 1992).66.Hamrick, J. & Godt, M. Effects of life history traits on genetic diversity in plant species. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 351, 1291–1298 (1996).ADS 
    Article 

    Google Scholar 
    67.Spaulding, H. & Rieske, L. The aftermath of an invasion: Structure and composition of central appalachian hemlock forests following establishment of the hemlock woolly adelgid, Aelges tsugae. Biol. Invasions 12, 3135–3143. https://doi.org/10.1007/s10530-010-9704-0 (2010).Article 

    Google Scholar 
    68.Hadziabdic, D. et al. Analysis of genetic diversity in flowering dogwood natural stands using microsatellites: The effects of dogwood anthracnose. Genetica 138, 1047–1057. https://doi.org/10.1007/s10709-010-9490-8 (2010).Article 
    PubMed 
    CAS 

    Google Scholar 
    69.Marquardt, P., Echt, C., Epperson, B. & Pubanz, D. Genetic structure, diversity, and inbreeding of eastern white pine under different management conditions. Can. J. For. Res. 37, 2652–2662 (2007).Article 
    CAS 

    Google Scholar 
    70.Potter, K. et al. Widespread inbreeding and unexpected geographic patterns of genetic variation in eastern hemlock (Tsuga canadensis), an imperiled North American conifer. Conserv. Genet. 13, 475–498. https://doi.org/10.1007/s10592-011-0301-2 (2012).Article 

    Google Scholar 
    71.Thammina, C., Kidwell-Slak, D., Lura, S. & Pooler, M. SSR markers reveal the genetic diversity of asian Cercis taxa at the US National Arboretum. HortScience 52, 498–502. https://doi.org/10.21273/hortsci11441-16 (2017).Article 

    Google Scholar 
    72.Chang, C., Bongarten, B. & Hamrick, J. Genetic structure of natural populations of black locust (Robinia pseudoacacia L.) at Coweeta, North Carolina. J. Plant Res. 111, 17–24. https://doi.org/10.1007/BF02507146.pdf (1998).Article 

    Google Scholar 
    73.Marquardt, P. & Epperson, B. Spatial and population genetic structure of microsatellites in white pine. Mol. Ecol. 13, 3305–3315. https://doi.org/10.1111/j.1365-294X.2004.02341.x (2004).Article 
    PubMed 
    CAS 

    Google Scholar 
    74.Victory, E., Glaubitz, J., Rhodes-Jr, O. & Woeste, K. Genetic homogeneity in Juglans nigra (Juglandaceae) at nuclear microsatellites. Am. J. Bot. 93, 118–126. https://doi.org/10.3732/ajb.93.1.118 (2006).Article 
    CAS 

    Google Scholar 
    75.Hadziabdic, D. et al. Genetic diversity of flowering dogwood in the Great Smoky Mountains National Park. Tree Genet. Genomes 8, 855–871. https://doi.org/10.1007/s11295-012-0471-1 (2012).Article 

    Google Scholar 
    76.Nybom, H. Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Mol. Ecol. 13, 1143–1155. https://doi.org/10.1111/j.1365-294X.2004.02141.x (2004).Article 
    PubMed 
    CAS 

    Google Scholar 
    77.Donselman, H. Variation in native populations of eastern redbud (Cercis canadensis L.) as influenced by geographic location [USA]. In Proceedings, of the Florida State Horticulture Society Vol. 89. 370–373 (1976).78.Dirr, M. Manual of Woody Landscape Plants: Their Identification, Ornamental Characteristics, Culture, Propagation and Uses (Stipes Publishing Co, Champaign, 1990).
    Google Scholar 
    79.Fritsch, P., Schiller, A. & Larson, K. Taxonomic implications of morphological variation in Cercis canadensis (Fabaceae) from Mexico and adjacent parts of Texas. Syst. Bot. 34, 510–520. https://doi.org/10.1600/036364409789271254 (2009).Article 

    Google Scholar 
    80.Nevo, E. et al. Drought and light anatomical adaptive leaf strategies in three woody species caused by microclimatic selection at evolution canyon, Israel. Israel J. Plant Sci. 48, 33–46 (2000).
    Google Scholar 
    81.Fritsch, P. et al. Leaf adaptations and species boundaries in North American Cercis: Implications for the evolution of dry floras. Am. J. Bot. 105, 1577–1594. https://doi.org/10.1002/ajb2.1155 (2018).Article 
    PubMed 

    Google Scholar 
    82.Raulston, J. Redbud. Am. Nurseryman 171, 39–51 (1990).
    Google Scholar 
    83.Robertson, K. Cercis: The redbuds. Arnoldia 36, 37–49 (1976).
    Google Scholar 
    84.Davis, C., Fritsch, P., Li, J. & Donoghue, M. Phylogeny and biogeography of Cercis (Fabaceae): Evidence from nuclear ribosomal ITS and chloroplast ndhF sequence data. Syst. Bot. 27, 289–302. https://doi.org/10.1043/0363-6445-27.2.289 (2002).Article 

    Google Scholar 
    85.Hopkins, M. In Rhodora Vol. 44 (eds M Fernald, C Eatherby, L Griscom, & S Marris) 193–211 (New England Botanical Club, Inc., 1942).86.Griffin, J., Ranney, T. & Pharr, D. Heat and drought influence photosynthesis, water relations, and soluble carbohydrates of two ecotypes of redbud (Cercis canadensis). J. Am. Soc. Hortic. Sci. 129, 497–502. https://doi.org/10.21273/JASHS.129.4.0497 (2004).Article 
    CAS 

    Google Scholar 
    87.Fritsch, P. & Cruz, B. Phylogeny of Cercis based on DNA sequences of nuclear ITS and four plastid regions: Implications for transatlantic historical biogeography. Mol. Phylogenet. Evol. 62, 816–825. https://doi.org/10.1016/j.ympev.2011.11.016 (2012).Article 
    PubMed 

    Google Scholar 
    88.Chung, M., Chung, M., Oh, G. & Epperson, B. Spatial genetic structure in a Neolitsea sericea population (Lauraceae). Heredity 85, 490–497. https://doi.org/10.1046/j.1365-2540.2000.00781.x (2000).Article 
    PubMed 

    Google Scholar 
    89.Dean, D. et al. Analysis of genetic diversity and population structure for the native tree Viburnum rufidulum occurring in Kentucky and Tennessee. J. Am. Soc. Hortic. Sci. 140, 523–531. https://doi.org/10.21273/JASHS.140.6.523 (2015).Article 
    CAS 

    Google Scholar 
    90.Hagler, J., Mueller, S., Teuber, L., Machtley, S. & Van-Deynze, A. Foraging range of honey bees, Apis mellifera, in alfalfa seed production fields. J. Insect Sci. 11, 144. https://doi.org/10.1673/031.011.14401 (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    91.Pasquet, R. et al. Long-distance pollesn flow assessment through evaluation of pollinator foraging range suggests transgene escape distances. Proc. Natl. Acad. Sci. 105, 13456–13461 (2008).ADS 
    Article 

    Google Scholar 
    92.Hayden, W. Redbud seedpods hold surprises. Bull. Virginia Native Plant Soc. 32, 1–6 (2013).
    Google Scholar 
    93.Schnabel, A., Laushman, R. & Hamrick, J. Comparative genetic structure of two co-occurring tree species, Maclura pomifera (Moraceae) and Gleditsia triacanthos (Leguminosae). Heredity 67, 357–364. https://doi.org/10.1038/hdy.1991.99 (1991).Article 

    Google Scholar 
    94.Nakanishi, A., Tomaru, N., Yoshimaru, H., Manabe, T. & Yamamoto, S. Effects of seed- and pollen-mediated gene dispersal on genetic structure among Quercus salicina saplings. Heredity 102, 182–189. https://doi.org/10.1038/hdy.2008.101 (2008).Article 
    PubMed 
    CAS 

    Google Scholar 
    95.Vekemans, X. & Hardy, O. New insights from fine-scale spatial genetic structure analyses in plant populations. Mol. Ecol. 13, 921–935. https://doi.org/10.1046/j.1365-294X.2004.02076.x (2004).Article 
    PubMed 
    CAS 

    Google Scholar 
    96.Gonzales, E., Hamrick, J., Smouse, P., Trapnell, D. & Peakall, R. The impact of landscape disturbance on spatial genetic structure in the Guanacaste tree, Enterolobium cyclocarpum (Fabaceae). J. Hered. 101, 133–143. https://doi.org/10.1093/jhered/esp101 (2009).Article 
    PubMed 
    CAS 

    Google Scholar 
    97.Post, D. Change in nutrient content of foods stored by eastern woodrats (Neotoma floridana). J. Mammal. 73, 835–839 (1992).Article 

    Google Scholar 
    98.Surrency, D. & Owsley, C. (ed. Natural Resources Conservation Service United States Department of Agriculture) 146 (United States Department of Agriculture, Natural Resources Conservation Service, 2001).99.Wakeland, B. & Swihart, R. Ratings of white-tailed deer preferences for woody browse in Indiana. Proceedings of the Indiana Academy of Science 118, 96–101 (2009).
    Google Scholar 
    100.Wright, V., Fleming, E. & Post, D. Survival of Rhyzopertha dominica (Coleoptera, Bostrichidae) on fruits and seeds collected from woodrat nests in Kansas. J. Kansas Entomol. Soc. 63, 344–347 (1990).
    Google Scholar 
    101.Sullivan, J. (ed. Forest Service U.S. Department of Agriculture, Rocky Mountain Research Station) (U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. Fire Sciences Laboratory, 1994).102.Weir, B. & Ott, J. Genetic data analysis II. Trends Genet. 13, 379 (1997).Article 

    Google Scholar 
    103.Magni, C., Ducousso, A., Caron, H., Petit, R. & Kremer, A. Chloroplast DNA variation of Quercus rubra L. in North America and comparison with other Fagaceae. Mol. Ecol. 14, 513–524. https://doi.org/10.1111/j.1365-294X.2005.02400.x (2005).Article 
    PubMed 
    CAS 

    Google Scholar 
    104.Peterson, B. & Graves, W. Chloroplast phylogeography of Dirca palustris L. indicates populations near the glacial boundary at the Last Glacial Maximum in eastern North America. Journal of Biogeography 43, 314–327, doi:https://doi.org/10.1111/jbi.12621 (2016).105.Shaw, J. & Small, R. Chloroplast DNA phylogeny and phylogeography of the North American plums (Prunus subgenus Prunus section Prunocerasus, Rosaceae). Am. J. Bot. 92, 2011–2030. https://doi.org/10.3732/ajb.92.12.2011 (2005).Article 
    PubMed 
    CAS 

    Google Scholar 
    106.Rowe, K., Heske, E., Brown, P. & Paige, K. Surviving the ice: Northern refugia and postglacial colonization. Proc. Natl. Acad. Sci. 101, 10355–10359 (2004).ADS 
    Article 
    CAS 

    Google Scholar 
    107.Graignic, N., Tremblay, F. & Bergeron, Y. Influence of northern limit range on genetic diversity and structure in a widespread North American tree, sugar maple (Acer saccharum Marshall). Ecol. Evol. 8, 2766–2780. https://doi.org/10.1002/ece3.3906 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    108.Bemmels, J., Knowles, L. & Dick, C. Genomic evidence of survival near ice sheet margins for some, but not all, North American trees. Proc. Natl. Acad. Sci. 116, 8431–8436. https://doi.org/10.7302/Z2JS9NNG (2019).Article 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar 
    109.Jia, H. & Steven, R. Fossil leaves and fruits of Cercis L. (Leguminosae) from the Eocene of western North America. International Journal of Plant Sciences 175, 601–612, doi:https://doi.org/10.1086/675693 (2014).110.Kraemer, M. & Favi, F. Emergence phenology of Osmia lignaria subsp lignaria (Hymenoptera: Megachilidae), its parasitoid Chrysura kyrae (Hymenoptera: Chrysididae), and bloom of Cercis canadensis. Environ. Entomol. 39, 351–358. https://doi.org/10.1603/en09242 (2010).Article 
    PubMed 
    CAS 

    Google Scholar 
    111.USDA. Census of horticultural specialties. Volume 3 AC-12-SS-3, Washington, DC (2014). More

  • in

    ‘I have to use a torch and watch my step’: netting seabirds at night

    Download PDF

    Netting seabirds is great fun. And it’s crucial for science and conservation.In this photo, taken in July, I’m heading out to capture birds on Inishtrahull, Ireland’s northernmost island. Lying about 10 kilometres northeast of the mainland, the island is home to thousands of seabirds during the summer nesting season, including storm petrels (Hydrobates pelagicus), Manx shearwaters (Puffinus puffinus) and fulmars (Fulmarus glacialis). The fulmars are experiencing a population crash, which I’m investigating.Migratory birds are protected here, but we need to know where they go when they leave their nests. I attach an identification band and a light-level geolocator — a sensor that helps to estimate location from day length — to every bird I catch. A few birds get GPS monitors, but we dole those out carefully, because each costs about £1,000 (US$1,368).The birds tend to nest on cliffs, and on a bad day I’ll catch just three. Some days I get as many as 12. Shearwaters are a challenge, because they nest only at night: I have to use a torch and watch my step.The birds don’t enjoy getting caught, but the stress is only temporary. The data they provide help us to understand their migration patterns. Fulmars spend almost their entire lives at sea. I’m interested in finding out how often they share waters with long-line fishers, which would be a potentially fatal scenario for the birds. That’s not the only threat: a study has found that more than half of beached North Sea fulmars have large amounts of plastic in their stomachs (see go.nature.com/3cosy8j).The lighthouse behind me is now home to the Inishtrahull Bird Observatory, a base for birdwatchers. I’m the founding chairman, but the observatory, part of a network of monitoring spots stretching 1,200 kilometres from Scotland to southern Ireland, will outlive me. It will be a centre for science and education for years to come.

    Nature 599, 340 (2021)
    doi: https://doi.org/10.1038/d41586-021-03055-8

    Related Articles

    Tracking Chernobyl’s effects on wildlife

    Preserving pieces of history in eggshells and birds’ nests

    Subjects

    Careers

    Ecology

    Ocean sciences

    Latest on:

    Careers

    Tips for managing an industry move without your academic supervisor’s support
    Career Feature 02 NOV 21

    When you recommend someone for an opportunity, follow through
    Career Column 29 OCT 21

    Cassyni aims to make online seminars more findable and citable
    Career News 28 OCT 21

    Ecology

    Whales’ gigantic appetites, climate fears — the week in infographics
    News 05 NOV 21

    COP26 climate pledges: What scientists think so far
    News 05 NOV 21

    Baleen whale prey consumption based on high-resolution foraging measurements
    Article 03 NOV 21

    Ocean sciences

    A whale of an appetite revealed by analysis of prey consumption
    News & Views 03 NOV 21

    Pliocene decoupling of equatorial Pacific temperature and pH gradients
    Article 20 OCT 21

    Mercury stable isotopes constrain atmospheric sources to the ocean
    Article 29 SEP 21

    Jobs

    Staff Scientist – RNA Biology

    Baylor College of Medicine (BCM)
    Houston, TX, United States

    Postdoctoral Associate-RNA Biology

    Baylor College of Medicine (BCM)
    Houston, TX, United States

    Postdoctoral Associate-RNA Biology

    Baylor College of Medicine (BCM)
    Houston, TX, United States

    Postdoctoral Associate-RNA Biology

    Baylor College of Medicine (BCM)
    Houston, TX, United States More

  • in

    Genomic characterization between strains selected for death-feigning duration for avoiding attack of a beetle

    The present study compared DNA sequences in a whole genome between the long strain and standard genome samples as references or the short strain and standard ones in T. castaneum. The results of resequencing analysis showed variations of DNA sequence from the reference sequence in both long and short strains, and the variations were detected more frequently in the long strain in a whole genome. Small nucleotide variants (SNV), multi-nucleotide variants (MNV), deletion, insertion, and replacement were detected in a whole genome in long and short strains. The same DNA sequence variants sharing between long and short strains were removed for the analyses. The numbers of small variants in total were larger in long strains than short strains (Fig. 1, Tables S1 and S2). The most frequent type of small variants was SNV, and the proportions of SNV were 82.7% (93,233/112,783) in long strains and 82.8% (13,817/16,697) in short strains, respectively (Fig. 1A). The SNVs compared with the reference nucleotide occurred frequently between adenine and guanine or cytosine and thymine in both long and short strains (Fig. 1B), and the frequencies were up to three times as large as other base combinations, indicating more frequent transition and fewer transversion variants. Deletion and insertion ranged from one to nine bases in both long and short strains, with one base was frequently deleted or inserted (Fig. 1C). Homozygosity presented more frequently than heterozygosity in all linkage groups, but the rate of homozygosity to heterozygosity depended on the linkage groups (Fig. 1D). Homozygosity of variants was more frequent in linkage groups 3 (LG3), 5 (LG5) and 7 (LG7) than other linkage groups in both strains. The ratios of homozygosity to heterozygosity were the largest in LGX and LG2 in long and short strains, respectively.Figure 1Analytical results of small variants of DNA sequence in a whole genome level in long and short strains. Proportion of small variants as SNV, MNV, deletion, insertion, and replacement in long and short strains (A). The numbers of small variants are indicated as the diameter of a pie graph. Frequencies of the SNVs in both long and short strains were compared with the reference nucleotide (B). Insertion and deletion ranged from one to nine bases in both long and short strains (C). Frequency of homozygosity or heterozygosity and its ratio in all linkage groups in long and short strains (D).Full size imageThe variants distributed in cording and non-cording regions. Figure 2A shows the results of narrowing down the variants in genic region from the variants in a whole genome in the long and short strains, and then aggregating the variants information in the exon, intron, URT and other regions. In all genic region, numbers of variants were larger in long strain than short strain. Then, genes containing these variants were counted in each strain (Fig. 2B). In exon region, genes with nonsynonymous variants were more numerous in the long strain (3243) than the short strain (844), and 464 common genes containing different DNA sequence variants between the strains were detected (Fig. 2B). In the genes with synonymous variants or the genes with variants in intron or UTR, the numbers of genes in long strain were constantly larger than those in short strain (Fig. 2B). The functions of long-unique, short-unique and common genes with variants were sorted into four categories by enrichment analyses as gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) ongoloty (KO) terms (Fig. 2C, Table S3). In the biological process, cellular component, and molecular function, and KEGG pathway, characteristics of nonsynonymous variants in long-unique, short-unique and common genes did not basically overlap among them, indicating specific selection of gene characteristics for each strain. Characteristics of synonymous variants were also sorted, but the synonymous variants may not influence the amino acid sequence of the gene and structure of the protein translated, rather these characteristics may be necessary to maintain the strain and preserved under artificial selection. Variants in intron and UTR may have potential effects on the gene expression, but should be investigated in detail in future study. Analyses of cis-regulatory elements might be important to understand regulation of gene expression, but the information on this region in T. castaneum is not available, therefore, the variants in cis-regulatory elements could not be analyzed.Figure 2Analytical results of the position of small variants in a whole genome in long and short strains (A) Numbers of variants in genic region including exon region, intron, UTR and other non-cording regions were indicated. As shown in parentheses, some ncRNAs and tRNAs were contained in exon, intron, and UTR regions. In short strain, there were five regions where two different genes overlap in 5′-UTR and 3′-UTR, respectively. Numbers of genes with variants in exon, intron and UTR regions in long and short strains (B). Numbers of long-unique, short-unique and common genes were shown by Venn diagrams. Common genes contain variants with different DNA sequences between long and short strains. Enrichment analyses of the function of genes with variants sorted into four categories (biological process, cellular component, molecular function, and KEGG pathway) (C). The heatmap is generated using the R package “gplots” (version 3.1.1, https://cran.r-project.org/web/packages/gplots/index.html). The list of each ontology shows the ID and term. The KO id is shown by a three- or four-letter organism code, the first-letter of the genus name and the first two- or three-letters of the species name of the scientific name of the organism, with pathway number. For example, Neuroactive ligand-receptor interaction of Tribolium castaneum is shown as “tca04080”.Full size imageTo explore the position of genes with variants associated with duration of death feigning in linkage groups, bulk segregant analysis was carried out (Fig. 3). The red approximate lines of the plot data crossed over the green threshold lines (P  More

  • in

    An injured pachypleurosaur (Diapsida: Sauropterygia) from the Middle Triassic Luoping Biota indicating predation pressure in the Mesozoic

    Geological backgroundThe Luoping Biota from quarries near Daaozi Village, Luoping County, Yunnan Province, China, includes diverse arthropods, conodonts, foraminifers, molluscs, echinoderms, brachiopods, fishes, marine reptiles, plants, and trace fossils8,10,11,12,13. The fossil beds occur in Member II of the Guanling Formation which in the Daaozi section comprises approximately 16 m of dark-coloured micritic limestone, thin to moderately thickly bedded, indicating a semi-enclosed intraplatform setting10,11. The co-occurring conodont assemblages, primarily consisting of Cratognathodus sp. and Nicoraella kockeli, indicate that the Luoping Biota belongs to the Pelsonian Substage of the middle Anisian, and the U–Pb age, which is 246.6 ± 1.4 Ma, of the volcanic tuff at the bottom of Member I confirms this age10,14.Systematic palaeontologySuperorder Sauropterygia Owen, 186015.Order Eosauropterygia Rieppel, 199416.Family Incertae Sedis.Genus Diandongosaurus Shang, Wu & Li, 2011.Type speciesDiandongosaurus acutidentatus Shang, Wu & Li, 2011.Revised diagnosisSmall-to-medium-sized eosauropterygian with the following unique combination of characters: premaxilla with long, fang-shaped teeth; maxilla with single enlarged fang alongside smaller teeth; parietal foramen about level with anterior margin of supratemporal fenestra; supratemporal smaller than orbit; interorbital bridge broad; frontal excluded from orbit; posterolateral processes of frontal extending over anterior margin of supratemporal fenestra; postorbital excluded from infratemporal fenestra by contact between jugal and squamosal; ectopterygoid present; vertebral column consisting of about 38 presacral, 3 sacral, and more than 30 caudal vertebrae; anterior caudal ribs elongate without tapering distal end; clavicle with distinct anterior processes laterally; entepicondylar foramen absent; acetabular process of pubis strongly offset from the main body.Diandongosaurus cf. acutidentatus.MaterialWIGM SPC V 1105, a nearly complete skeleton exposed ventrally (Fig. 1).Figure 1Full skeleton of WIGM SPC V 1105, viewed from above. Note the missing left foot. Scale bar = 10 cm.Full size imageLocality and horizonDaaozi Village, Luoping County, Yunnan Province, China; Member II of the Guanling Formation, Anisian, Middle Triassic.DescriptionWIGM SPC V 1105 is a large pachypleurosaur with a length of 88.6 cm from the tip of the snout to the end of the caudal vertebral column (Fig. 1). The specimen is exposed in ventral view, with the cranium exposed both ventrally and dorsally. In the holotype, the cranium comprises 7.8% of the total length, neck 22.9%, trunk 32.4%, and tail 36.9% (Table 1).Table 1 Selected measurements (in mm) of WIGM SPC V 1105.Full size tableSkullThe skull of WIGM SPC V 1105 is exposed in both dorsal and ventral views and is dorsoventrally compressed (Fig. 2). The external naris and the supratemporal fenestra are oval-shaped, while the orbit is nearly circular.Figure 2Photograph and interpretative drawing of the skull of WIGM SPC V 1105. (a, b) In dorsal view; (c, d) In ventral view. ang. Angular, at.c atlantal centrum, at.nar atlantal neural arch, ax.c axial centrum, ax.nar axial neural arch, bo basioccipital, d dentary, ec ectopterygoid, eo-op exoccipital-opisthotic, f frontal, hd hyoid, j jugal, m maxilla, n nasal, p parietal, pat proatlas, pl palatine, pm premaxilla, pob postorbital, pof postfrontal, prf prefrontal, pt pterygoid, q quadrate, qrp quadrate ramus of pterygoid, rap retroarticular process, sang surangular, so supraoccipital, sp splenial, sq squamosal, vo vomer. Scale divisions in (a) = 1 mm. Scale bar in (b–d) = 2 cm. The figure is generated using CorelDRAW X7 (https://www.coreldraw.com/en/pages/coreldraw-x7/).Full size imageIn dorsal view (Fig. 2a,b), the premaxillary portion of the rostrum protrudes, defined by snout constriction at the anterior maxilla, different from the reported specimens of D. acutidentatus17,18. The premaxilla forms the anterior and the medial margins of the external naris. The nasal process extends and narrows posteriorly alongside the nasal posteromedially, reaching the anterior margin of the orbit, and contacting the anterior frontal with a cuspidal border line. The premaxilla contacts the maxilla lateral to the external naris.The maxilla is elongate, with a laterally broad anterior portion and tapering posterior process. Its anteromedial margin forms the posterolateral border of the external naris and is overlapped by the posterior premaxilla laterally. The anterior snout constriction is mostly defined by strong medial curvature of the anterolateral maxilla margin. Medially the maxilla contacts the nasal immediately posterior to the external naris, and the prefrontal posterior to that; the nasal contact is likely the longer. Posteriorly, the maxilla borders the anterolateral margin of the orbit. The posterior process of the maxilla contacts the jugal lateral to the orbit. The nasals are broken. They are separated medially by the premaxilla and make a small contribution to the posterior external naris. The external naris is subcircular.The prefrontal is an arch-shaped bone, fused with the lacrimal. Its dorsal portion expands posteriorly, with its ventral portion forming the anterodorsal margin of the orbit. Posteriorly, the prefrontal overlaps the postfrontal obliquely at the midpoint of the dorsal border of the orbit. The postfrontal is a small trapezoid-shaped bone that forms the posterodorsal margin of the orbit, and is more extensive than in Dianopachysaurus dingi19. Posteriorly, it meets the postorbital anterior to the supratemporal fenestra and has a small medial contact with the parietal, separating the postfrontal from the supratemporal fenestra. Both the prefrontal and postfrontal contact the frontal dorsally, preventing it from entering the orbit.The frontals are fused medially into a butterfly shape in dorsal view, expanding obliquely in four directions. Anteriorly the contacts with the nasals are uncertain but were likely to have been broad. The median contact with the premaxilla is narrow and irregular. The frontal meets the prefrontal and the postfrontal laterally along the arc of the dorsal orbital margin, preventing it from entering the orbit, as in Diandongsosaurus acutidentatus17, but unlike both Keichousaurus hui and Dianopachysaurus dingi19,20. The frontal does not enter the supratemporal fenestra either, being narrowly excluded by the parietal and the postorbital as in D. acutidentatus17. In Dianopachysaurus dingi19, contact between the postfrontal and parietal excludes the frontal from the supratemporal fenestra. Posteriorly, the frontal expands slightly, laterally towards the supratemporal fenestrae, and diverges into a narrow fork around the anterior processes of the parietals, separating them from the postfrontal.The parietals are partly fused, showing a suture only anterior to the pineal foramen. The anterior processes insert between the posterior frontal margins with an arch-shaped border. Laterally, the parietal extends a short process to meet the postorbital in a narrow contact at the anterior margin of the supratemporal fenestra, posterior to the postfrontal. This differs from K. hui and Dianopachysaurus dingi19,20, in which the parietal contacts the postfrontal anterolaterally. The bone forms the medial margin of the supratemporal fenestra. The narrow posterolateral processes are inserted by the dorsal processes of the squamosal. The pineal foramen is sub-circular and aligns with the anterior margin of the supratemporal fenestra, more anterior than in K. hui20 and not elongate as in Dianopachysaurus dingi19.The postorbital is roughly triradiate, developing three processes: anteroventral, anteromedial, and posterior. The anteroventral process outlines the posterior border of the orbital, overlapped by the jugal laterally. The narrow anteromedial process extends dorsally, forming the anterior margin of the supratemporal fenestra, and meeting the postfrontal and the parietal anterior to the supratemporal fenestra, unlike in the reported specimens of D. acutidentatus, K. hui, and Dianopachysaurus dingi17,19,20, and more like nothosaurs21,22. It is broadly overlapped by the postfrontal. The posterior process is triangular and extends nearly to the posterolateral margin of the supratemporal fenestra, forming the border of most of its lateral portion. Posteriorly, the tip of the process inserts into the squamosal.The jugal is boomerang-shaped, forming most of the lateral border of the orbit. It contacts the maxilla at the anteroventral margin of the orbital, dorsally overlapping it. Posteriorly, the jugal forms the anterior border of the infratemporal fenestra. Its posterior process is anteroposteriorly broad and extends dorsally, overlapping the postorbital at the posteroventral margin of the orbital. As in D. acutidentatus17, the posterior process of the jugal has a small contact dorsally with the anterior process of the squamosal.The squamosal is a large bone expanded in four directions. The anterior process forms most of the upper temporal bar, extending anterior to the level of the anterior margin of the supratemporal fenestra and partially overlapped medially by the postorbital, except where the squamosal holds the posteriormost point of the postorbital. Anteriormost on the squamosal, there is a small lateral contact with the posterior process of the jugal. The medial process of the squamosal forms almost the whole posterior margin of the supratemporal fenestra, inserting into the posterolateral process of the parietal medially. The posterolateral descending process is robust and expands ventrally, forming a sheet at the posterior margin of the cranium and contacting the lateral portion of the quadrate on its posteromedial face. However, the posterior process, the shortest of these four processes, is not as obvious as in the reported specimens of Dianopachysaurus. acutidentatus or K. hui17,20. The supratemporal fenestra is rounded and smaller than the orbit, with a straighter lateral margin. It is less elongate than in Dianopachysaurus dingi and K. hui19,20.The quadratojugal is not exposed. The supraoccipital is a rhomboid bone inserted ventral to the parietal but is substantially broken; it forms the dorsal margin of the foramen magnum. The exoccipital-opisthotic forms the lateral margin of the foramen magnum, while the basioccipital forms the ventral; these elements are also broken.In ventral view (Fig. 2c,d), the internal choana is roughly circular. The vomer is a long bone with a bifurcating posterior portion along the midline of the palate and forms the medial margin of the internal choana. Anteriorly, the bone meets the palatal portion of the premaxilla and contacts the maxilla anterolaterally. Posteriorly, the posteromedial processes of the two vomers are separated by the anterior process of the pterygoid and the posterior contact with the palatine is small, as in D. acutidentatus18,22 but unlike in K. hui20.The palatine is a strap-like bone. It forms the posterolateral margin of the internal choanae. Anterolaterally, it contacts the maxilla, and meets the vomer on its medial side. Posteromedially, there is a highly irregular, oblique suture line between the palatine and the pterygoid.The pterygoid is one of the largest bones of the skull, forming most of the palate posteriorly. The two pterygoids are fused along the midline leaving a straight groove anteriorly that becomes more irregular posteriorly. Unlike D. acutidentatus, it has neither central opening, nor posterior vacuity18. The tapering anterior process of the pterygoid inserts between the two vomers, whereas it is overlapped in K. hui20, and anterolaterally the pterygoid has a large oblique contact with the palatine. Laterally, the transverse process of the pterygoid expands ventral and posterior to the posterior margin of the ectopterygoid. The pterygoid forms almost the entirety of the subtemporal fenestra margin anteriorly, medially, and posteriorly. The elongate quadrate ramus of the pterygoid extends posterolaterally to the posterior margin of the quadrate, making a long contact with the pterygoid ramus of the quadrate.The ectopterygoid is roughly a small square bone, suturing to the transverse process of the pterygoid. It is not as prominent as in nothosaurs (e.g. Nothosaurus21, Lariosaurus22), but is relatively larger than in the reported specimens of D. acutidentatus18,23, whereas the presence of an ectopterygoid is uncertain in K. hui and Dianopachysaurus dingi19,20. The ectopterygoid contacts the palatine anteriorly, excluding the palatine from the subtemporal fenestra. Posteriorly it makes a small contribution to the subtemporal fenestra margin lateral to the transverse process of the pterygoid. The quadrate is exposed partly, contacting the quadrate ramus of the pterygoid with its pterygoid ramus. Two rod-like hyoids are ossified and well preserved, lying beneath the pterygoid. They are elongate and slightly expanded at each end.MandibleThe mandible is exposed mainly in ventral view and partly in dorsal (Fig. 2). The dentary is a long bone, occupying over one-half of the ramus as a counterpart to the premaxilla, with a laterally broader symphyseal portion than in D. acutidentatus or K. hui18,20,23. The surangular is partly exposed in dorsal view along the dorsal margin of the mandible, extending ventral to the squamosal. The angular is a long strap-shaped bone that meets the dentary anteriorly and the retroarticular process posteriorly. The articular is sutured dorsal to the angular, with a distinct retroarticular process that extends posteriorly with a tapering end.DentitionIn ventral view (Fig. 2c,d), nine premaxillary teeth and seven lower teeth are visible, which are procumbent, fang-like and with apicobasal striations. The 2nd and 3rd right and the 1st, 3rd and 5th left premaxillary teeth are fully grown, elongate and less curved compared to the other teeth. However, the reported specimens of D. acutidentatus and the nothosauroids Lariosaurus and Nothosaurus carry five teeth on each premaxilla17. The space between the 2nd and 3rd right premaxillary teeth suggests that there might be one or two missing teeth. There is one fang-like tooth on each maxilla, surrounded by small tapering teeth, and there are five to six corresponding teeth in the lower jaw. The caniniform teeth also have apicobasal striations like the premaxillary teeth. The row of dentary teeth is restricted to a level anterior to the posterior margin of the orbit.Vertebrae and ribsThere are 38 presacral vertebrae, 3 sacral and 33 caudal (Fig. 1); these counts are roughly the same in coeval Eosauropterygia19,24,25. The atlas and axis are dorsally exposed (Fig. 2a,b). The atlas leans anteriorly, and its neural spine does not meet its counterpart. The proatlas is a pentagonal bone, disarticulated from the atlas. The axis has been rotated laterally, but still articulates with the atlas.There are 19 cervical vertebrae, compared to 20/21 in Dianopachysaurus dingi19. The centra cylinders are rhomboidal in ventral view, increase in length posteriorly and the vertebrae articulate with one another compactly. The parapophyseal articulation on the cervical rib (CR), visible in ventral view, is robust and offset about 90° from the long axis of the rib, defined between the main body and a prominent anterior process. These posterior and anterior extensions are approximately equal in length until about CR14, where the posterior extension starts to lengthen strongly. The anterior process becomes strongly reduced from CR16 onwards.There are approximately 19 thoracolumbar vertebrae, most of which are covered by the gastralia (18 in Dianmeisaurus gracilis25); the count estimated from two gastralial rows corresponding to one vertebra. The intercentral articulation is less compact than in the cervical vertebrae. The transverse processes face posteriorly. The dorsal ribs are single-headed arch-shaped bones with slightly expanded proximal flat ends, but otherwise retain constant diameter along their whole length, ending distally in a flattened stub. Dorsal ribs DR1–6 are exposed ventrally, while the rest are mostly overlain by the gastralia. There are 24 rows of gastralia, suggesting 12 more dorsal vertebrae covered, each gastralium consisting of one medial element and four lateral elements (Fig. 4a).Three sacral vertebrae can be recognized in dorsal view (Fig. 4b), the same as in Dianmeisaurus gracilis, Dianmeisaurus dingi and K. hui19,24,26. The sacral ribs are elongate and cylindrical with thickened distal ends, and closely articulate with the centrum and possibly overlap the rib posterior to each proximally. Distally the sacral rib is expanded posteriorly into a small triangular process that overlaps the next sacral rib posteriorly. Sacral ribs SR2 and SR3 likely articulate with the ilium, while the others are overlain by pubis and ischium (Fig. 3c,d).Figure 3Photographs and interpretative drawings of the pectoral girdle, forelimb, pelvic girdle and hindlimb of WIGM SPC V 1105 in ventral view. (a, b) Pectoral girdle and forelimb. (c, d) Pelvic girdle and hindlimb. as astragalus, cal calcaneum, cl clavicle, co coracoid, cr1 caudal rib 1, cr19 cervical rib 19, cv1 caudal vertebra 1, cv19 cervical vertebra 19, dc2 distal carpal 2, dc3 distal carpal 3, dc4 distal carpal 4, dr2 dorsal rib 2, dv2 dorsal vertebra 2, dr19 dorsal rib 19, dv19 dorsal vertebra 19, f femur, fi fibular, hu humerus, icl interclavicle, il Ilium, in intermedium, is ischium, mc1 metacarpal 1, mc5 metacarpal 5, mt1 metatarsal 1, mt5 metatarsal 5, pu pubis, ra radius, sc scapula, sr1 sacral rib 1, ti tibia, ul ulna, uln ulnare. Scale bar in (a, b, d) = 2 cm. Scale divisions in (a) = 1 mm. The figure is generated using CorelDRAW X7 (https://www.coreldraw.com/en/pages/coreldraw-x7/).Full size imageThere are 33 rhomboidal caudal vertebrae that decrease in size gradually towards the posterior end of the tail. Caudal vertebrae CV13–21 have strap-shaped neural spines. Caudal ribs are present in CV1–11. They are flat, arch-shaped bones directed slightly posteriorly. The size of the ribs remains roughly the same from CR1–5, but this decreases suddenly from CR6–11 (Fig. 4c). The distal ends of CR3–8 are flat, while more posterior ribs have pointed ends.Figure 4Selected postcranial parts of WIGM SPC V 1105. (a) gastralia near the sacral region in ventral view, the arrow indicating each gastralium consists of one medial element and four lateral elements; (b) sacral region in dorsal view; (c) part of the caudal region in ventral view. cr5 caudal rib 5, cv5 caudal vertebra 5, cv15 caudal vertebra 15, dr19 dorsal rib 19, dv16 dorsal vertebra 16, dv17 dorsal vertebra 17, dv19 dorsal vertebra 19, il ilium, pu pubis, sr1 sacral rib 1, sr2 sacral rib 2, sr3 sacral rib 3, sv1 sacral vertebra 1, sv2 sacral vertebra 2, sv3 sacral vertebra 3. Scale bar = 5 cm. The figure is generated using CorelDRAW X7 (https://www.coreldraw.com/en/pages/coreldraw-x7/).Full size imagePectoral girdle and forelimbThe pectoral girdle is exposed in ventral view (Fig. 3a,b). The interclavicle is an arrowhead-shaped bone with a strongly concave posterior border and two posterolaterally directed lateral processes, unlike the more diamond shape of D. gracilis24. Its tip points anteriorly but does not reach the anterior margin of the pectoral girdle between the clavicles. The clavicle is an L-shaped, strap-like bone with a characteristic prominence anterolaterally, as in D. acutidentatus and larger than in D. gracilis17,24. The clavicle develops a tiny posterolateral process, overlying the dorsal surface of the scapula. The tapering medial process expands to meet its counterpart, forming the anterior margin of the pectoral girdle. The scapula is exposed in ventral view, so the dorsal blade is covered. In this view it is sub-rectangular, with a rounded anterior margin and two posterior facets for the clavicle and humerus, angled obliquely and separated by a small ridge. The coracoid is a strap-shaped bone with proximal and distal ends widened, and the largest element in the pectoral girdle. Its anteromedial margin is more strongly concave than the posteromedial margin. Proximally, the coracoid is flattened and meets the contralateral element in a straight median facet. Distally the coracoid is more robust and expanded anteriorly into a broad rounded process on the anterior margin. The distal margin is straight and articulates with the scapula anteriorly and has a smaller articulation with the humerus posteriorly on a smaller, triangular posterodistal process. There is a small foramen exposed near the anterodistal margin along the scapular facet, larger than in Dianmeisaurus gracilis24.Both forelimbs are nearly complete, ventrally exposed, about 13.7% of the body length (Fig. 3a,b). The humerus is strongly curved (40°) and shorter than the femur (Table 1). The proximal articular surface is rounded, with a larger facet for the scapula than the coracoid, while the articular surface of the distal end is convex, contacting the radius and the ulna with two straight, oblique facets. These facets are more strongly offset than in D. acutidentatus17. There is no evidence for an entepicondylar foramen20,24. The ulna and the radius are nearly equal in length and relatively gracile compared to the humerus (Table 1). The two ends of the ulna are equally widened, while the ends of the radius expand less obviously and are directed slightly medially.There are more than four elements in the carpus, all round and flat in ventral view. The intermedium is slightly larger than the ulnare (Table 1), unlike in D. acutidentatus17, and articulates mediodistally to the ulna, medially to the ulnare. Distal carpal 2 is the largest of the distal carpals and articulates distally between the intermedium and ulnare. Distal carpals 3 and 4 are present but extremely reduced. The metacarpals are elongate and strongly hourglass shaped. Metacarpal 1 is the shortest of the five while metacarpals 2–4 are almost equal in length, and metacarpal 5 is slightly shorter. All the digits are directed towards the ulnar side of the limb. The interosseous space between metacarpals 4 and 5 is the widest. The phalangeal elements are well preserved, but digit 5 of the right manus demonstrates unusual preservation, which will be discussed further in the Discussion. The ungual phalanges of digits 4 and 5 on the left are small and round, while the ungual phalanx of digit 5 on the right is missing. Given that, the forelimb is likely to have had a phalangeal formula of 2–3–4–4–3.Pelvic girdle and hindlimbThe pelvic girdle is exposed ventrally (Fig. 3c,d). The pubis is a large plate-like bone. Both the anterior and posterior margins of the bone are concave near the distal end (about one-third of the whole length), forming a ‘waisted’ shape that is narrower than in Dianmeisaurus gracilis24. The ischium is large and irregularly shaped. Medially it is expanded into a large, squared, plate-like portion that meets the contralateral element along a straight median symphysis. Anterodistally, the ischium is waisted, separating the large, robust anterodistal process with a broad, rounded end that contacts the distal pubis and ilium to form the acetabulum. The anterodistal process is narrower and more strongly offset from the main body than in Dianmeisaurus gracilis24. Posterodistally there is a further broad extension. The thyroid fenestra is large and rectangular and is bounded by the posterior pubis and anterior ischium on both sides. The ilium is covered by the pubis and the ischium in ventral view.The left hindlimb is well preserved and exposed in ventral view (Fig. 3c,d), and the amputated right femur is discussed below. The femur is long and rounded with a slightly waisted epiphysis; it is larger and slenderer than the humerus (Table 1). The proximal end is wider than the distal but is damaged in this specimen. The tibia and the fibula are similarly elongate bones, with the tibia somewhat more robust but more similar in size than in the holotype of D. acutidentatus17. Both have slightly expanded proximal and distal ends, but the proximal end of the fibula is hidden beneath the distal femur. The stronger waist on the fibula gives it a more strongly curved appearance and creates a large interosseous fenestra.The astragalus and calcaneum are the only elements of the tarsus. The astragalus is larger than the calcaneum and located between the distal tibia and fibula with a pointed proximal margin (Table 1). The facets of the astragalus contacting the tibia and the fibula are straight. The calcaneum is subcircular. Length increases from metatarsals 1–4, then decreases in metatarsal 5; metatarsal 1 is the shortest. All the metatarsals have an elongate hourglass shape. The pes is not so well preserved, as digits 1 and 2 are crushed together. The phalanges are less elongate than the metatarsals and shaped like waisted cylinders, except for the ungual phalanx of digit 5; consequently, there may be some missing ungual phalanges from the other digits. The pedal phalangeal formula cannot be determined due to the preservation.Phylogenetic analysisWe added WIGM SPC V 1105 to the cladistic matrix of Lin et al.27 and replicated their analytical methods in PAUP* version 4a169. Our cladistic analysis produced four most parsimonious trees (tree length = 485 steps, CI 0.388, RI 0.622). Strict consensus of these trees (Fig. 5) matches the result of former studies, in that Diandongosaurus share a close relationship with Dianmeisaurus24.Figure 5Strict consensus tree of four most parsimonious tree (TL = 485 steps, CI = 0.388, RI = 0.622), demonstrating the phylogenetic position of WIGM SPC V 1105. Bootstrap support values ≥ 50% (1000 replicates) are labelled. The figure is generated using Adobe Illustrator 2021 (https://www.adobe.com/products/illustrator.html).Full size imageDiandongosaurus shows some similarities with Keichousaurus and Dianopachysaurus18,19, but many morphological differences exist. Keichousaurus and Dianopachysaurus have small tapering teeth19,20, while Diandongosaurus has serried long fang-shaped teeth. The supratemporal fenestra of Diandongosaurus is oval-shaped and larger than in the other two taxa considering the size of the orbit. The caudal ribs of Dianopachysaurus develop a tapering distal end, different from Diandongosaurus, whose caudal ribs have a flat distal end17,20.Diandongosaurus also differs from other Triassic eosauropterygians. The strongly procumbent anterior teeth discriminate it from the pistosauroids, which have upright anterior teeth. The size of the supratemporal fenestra is noticeably larger than in Qianxisaurus28, while the characteristic tapering snout of Wumengosaurus29 differs from the blunt snout of Diandongosaurus. Its clavicle develops an anterior process, which does not exist in European pachypleurosaurs. Diandongosaurus has a smaller supratemporal fenestra than in Lariosaurus and Nothosaurus, in some species of which it is nearly twice the size of the orbit.WIGM SPC V 1105 broadly resembles D. acutidentatus but differs in several features, including being considerably larger and the constricted snout of WIGM SPC V 1105 is a novelty in pachypleurosaur. These morphological distinctions between WIGM SPC V 1105 and D. acutidentatus could be regarded as evidence for establishing a new species. Alternatively, WIGM SPC V 1105 lacks the pterygoid opening in the two referred specimens (specimen NMNS-000933-F03498 and BGPDB-R0001) of D. acutidentatus18,23, and other differences, like the larger size and the rounded ends of humerus and femur, could have been caused by ontogenetic variation or even preservational issues. Based on previous documented specimens, interspecific variation of phalangeal formula exists in D. acutidentatus, as the pedal formular counts 2–3–4–5–4 in the holotype, but 2–3–4–6–4 in the referred specimen BGPDB-R000123. In this case, WIGM SPC V 1105 could be an adult of D. acutidentatus. Given these considerations, we assigned WIGM SPC V 1105 as a conformis (cf.) of D. acutidentatus. More