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    Revealing microhabitat requirements of an endangered specialist lizard with LiDAR

    Ceballos, G., García, A. & Ehrlich, P. R. The sixth extinction crisis: Loss of animal populations and species. J. Cosmol. 8, 31 (2010).
    Google Scholar 
    Johnson, C. N. et al. Biodiversity losses and conservation responses in the Anthropocene. Science 356, 270–275 (2017).CAS 
    PubMed 

    Google Scholar 
    Scott, J. M., Goble, D. D., Haines, A. M., Wiens, J. A. & Neel, M. C. Conservation-reliant species and the future of conservation. Conserv. Lett. 3, 91–97 (2010).
    Google Scholar 
    Johnson, M. A., Kirby, R., Wang, S. & Losos, J. What drives variation in habitat use by Anolis lizards: Habitat availability or selectivity?. Can. J. Zool. 84, 877–886 (2006).
    Google Scholar 
    Gaston, K. J., Blackburn, T. M. & Lawton, J. H. Interspecific abundance-range size relationships: an appraisal of mechanisms. J. Anim. Ecol. 66, 579–601 (1997).
    Google Scholar 
    Devictor, V. et al. Defining and measuring ecological specialization. J. Appl. Ecol. 47, 15–25 (2010).
    Google Scholar 
    Razgour, O., Hanmer, J. & Jones, G. Using multi-scale modelling to predict habitat suitability for species of conservation concern: The grey long-eared bat as a case study. Biol. Cons. 144, 2922–2930 (2011).
    Google Scholar 
    Jetz, W., Sekercioglu, C. H. & Watson, J. E. Ecological correlates and conservation implications of overestimating species geographic ranges. Conserv. Biol. 22, 110–119 (2008).PubMed 

    Google Scholar 
    Seddon, P. J. From reintroduction to assisted colonization: Moving along the conservation translocation spectrum. Restor. Ecol. 18, 796–802 (2010).
    Google Scholar 
    Tomlinson, S., Lewandrowski, W., Elliott, C. P., Miller, B. P. & Turner, S. R. High-resolution distribution modeling of a threatened short-range endemic plant informed by edaphic factors. Ecol. Evol. 10, 763–773 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Tomlinson, S., Webber, B. L., Bradshaw, S. D., Dixon, K. W. & Renton, M. Incorporating biophysical ecology into high-resolution restoration targets: insect pollinator habitat suitability models. Restor. Ecol. 26, 338–347 (2018).
    Google Scholar 
    Glen, A. S., Sutherland, D. R. & Cruz, J. An improved method of microhabitat assessment relevant to predation risk. Ecol. Res. 25, 311–314 (2010).
    Google Scholar 
    Limberger, D., Trillmich, F., Biebach, H. & Stevenson, R. D. Temperature regulation and microhabitat choice by free-ranging Galapagos fur seal pups (Arctocephalus galapagoensis). Oecologia 69, 53–59 (1986).PubMed 

    Google Scholar 
    Parmenter, R. R., Parmenter, C. A. & Cheney, C. D. Factors influencing microhabitat partitioning in arid-land darkling beetles (Tenebrionidae): temperature and water conservation. J. Arid Environ. 17, 57–67 (1989).
    Google Scholar 
    Kleckova, I., Konvicka, M. & Klecka, J. Thermoregulation and microhabitat use in mountain butterflies of the genus Erebia: importance of fine-scale habitat heterogeneity. J. Therm. Biol 41, 50–58 (2014).PubMed 

    Google Scholar 
    Napierała, A. & Błoszyk, J. Unstable microhabitats (merocenoses) as specific habitats of Uropodina mites (Acari: Mesostigmata). Exp. Appl. Acarol. 60, 163–180 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Marshall, K. L., Philpot, K. E. & Stevens, M. Microhabitat choice in island lizards enhances camouflage against avian predators. Sci. Rep. 6, 1–10 (2016).
    Google Scholar 
    Lovell, P. G., Ruxton, G. D., Langridge, K. V. & Spencer, K. A. Egg-laying substrate selection for optimal camouflage by quail. Curr. Biol. 23, 260–264 (2013).CAS 
    PubMed 

    Google Scholar 
    Wrege, P. H., Rowland, E. D., Keen, S. & Shiu, Y. Acoustic monitoring for conservation in tropical forests: Examples from forest elephants. Methods Ecol. Evol. 8, 1292–1301 (2017).
    Google Scholar 
    Measey, G. J., Stevenson, B. C., Scott, T., Altwegg, R. & Borchers, D. L. Counting chirps: Acoustic monitoring of cryptic frogs. J. Appl. Ecol. 54, 894–902 (2017).
    Google Scholar 
    Lambert, K. T. & McDonald, P. G. A low-cost, yet simple and highly repeatable system for acoustically surveying cryptic species. Austral Ecol. 39, 779–785 (2014).
    Google Scholar 
    Picciulin, M., Kéver, L., Parmentier, E. & Bolgan, M. Listening to the unseen: Passive Acoustic Monitoring reveals the presence of a cryptic fish species. Aquat. Conserv. Mar. Freshwat. Ecosyst. 29, 202–210 (2019).
    Google Scholar 
    Linkie, M. et al. Cryptic mammals caught on camera: assessing the utility of range wide camera trap data for conserving the endangered Asian tapir. Biol. Cons. 162, 107–115 (2013).
    Google Scholar 
    Balme, G. A., Hunter, L. T. & Slotow, R. Evaluating methods for counting cryptic carnivores. J. Wildl. Manag. 73, 433–441 (2009).
    Google Scholar 
    Carbone, C. et al. The use of photographic rates to estimate densities of tigers and other cryptic mammals in Animal Conservation forum. 75–79 (2001) (Cambridge University Press).Russell, J. C., Hasler, N., Klette, R. & Rosenhahn, B. Automatic track recognition of footprints for identifying cryptic species. Ecology 90, 2007–2013 (2009).PubMed 

    Google Scholar 
    Jarvie, S. & Monks, J. Step on it: can footprints from tracking tunnels be used to identify lizard species?. N. Z. J. Zool. 41, 210–217 (2014).
    Google Scholar 
    Watts, C., Thornburrow, D., Rohan, M. & Stringer, I. Effective monitoring of arboreal giant weta (Deinacrida heteracantha and D. mahoenui; Orthoptera: Anostostomatidae) using footprint tracking tunnels. J. Orthop. Res. 22, 93–100 (2013).
    Google Scholar 
    Williams, E. M. Developing monitoring methods for cryptic species: a case study of the Australasian bittern, Botaurus poiciloptilus: a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Ecology at Massey University, Manawatū, New Zealand, Massey University (2016).Hacking, J., Abom, R. & Schwarzkopf, L. Why do lizards avoid weeds?. Biol. Invasions 16, 935–947 (2014).
    Google Scholar 
    Valentine, L. E. Habitat avoidance of an introduced weed by native lizards. Austral. Ecol. 31, 732–735 (2006).
    Google Scholar 
    Hawkins, J. P., Roberts, C. M. & Clark, V. The threatened status of restricted-range coral reef fish species in Animal Conservation forum. 81–88 (2000) (Cambridge University Press).Mason, L. D., Bateman, P. W. & Wardell-Johnson, G. W. The pitfalls of short-range endemism: High vulnerability to ecological and landscape traps. PeerJ 6, e4715 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Dassot, M., Constant, T. & Fournier, M. The use of terrestrial LiDAR technology in forest science: Application fields, benefits and challenges. Ann. For. Sci. 68, 959–974 (2011).
    Google Scholar 
    Weber, H. LiDAR Sensor Functionality and Variants (2018).Michel, P., Jenkins, J., Mason, N., Dickinson, K. & Jamieson, I. Assessing the ecological application of lasergrammetric techniques to measure fine-scale vegetation structure. Eco. Inform. 3, 309–320 (2008).
    Google Scholar 
    Lim, K., Treitz, P., Wulder, M., St-Onge, B. & Flood, M. LiDAR remote sensing of forest structure. Prog. Phys. Geogr. 27, 88–106 (2003).
    Google Scholar 
    Anderson, L. & Burgin, S. Patterns of bird predation on reptiles in small woodland remnant edges in peri-urban north-western Sydney, Australia. Landsc. Ecol. 23, 1039–1047 (2008).
    Google Scholar 
    Hannam, M. & Moskal, L. M. Terrestrial laser scanning reveals seagrass microhabitat structure on a tideflat. Remote Sensing 7, 3037–3055 (2015).
    Google Scholar 
    Zavalas, R., Ierodiaconou, D., Ryan, D., Rattray, A. & Monk, J. Habitat classification of temperate marine macroalgal communities using bathymetric LiDAR. Remote Sens. 6, 2154–2175 (2014).
    Google Scholar 
    Mandlburger, G., Hauer, C., Wieser, M. & Pfeifer, N. Topo-bathymetric LiDAR for monitoring river morphodynamics and instream habitats—A case study at the Pielach River. Remote Sens. 7, 6160–6195 (2015).
    Google Scholar 
    Laize, C. et al. Use of LIDAR to characterise river morphology (2014).Cooper, C. & Withers, P. Physiological significance of the microclimate in night refuges of the numbat Myrmecobius fasciatus. Austral. Mammal. 27, 169–174 (2005).
    Google Scholar 
    Orell, P. & Morris, K. Chuditch recovery plan. Western Austral. Wildl. Manag. Program 13, 1 (1994).
    Google Scholar 
    Pearson, D. Western Spiny-Tailed Skink (Egernia stokesii) Recovery Plan (Department of Environment and Conservation, 2012).
    Google Scholar 
    McPeek, M. A., Cook, B. & McComb, W. Habitat selection by small mammals. Trans. Kentucky Acad. Sci. 44, 68–73 (1983).
    Google Scholar 
    Armstrong, K. The distribution and roost habitat of the orange leaf-nosed bat, Rhinonicteris aurantius, in the Pilbara region of Western Australia. Wildl. Res. 28, 95–104 (2001).
    Google Scholar 
    Mancina, C. et al. Endemics under threat: an assessment of the conservation status of Cuban bats. Hystrix Ital. J. Mammal. 18, 3–15 (2007).
    Google Scholar 
    Webb, M. H., Holdsworth, M. C. & Webb, J. Nesting requirements of the endangered Swift Parrot (Lathamus discolor). Emu-Austral. Ornithol. 112, 181–188 (2012).
    Google Scholar 
    Watson, S. J., Watson, D. M., Luck, G. W. & Spooner, P. G. Effects of landscape composition and connectivity on the distribution of an endangered parrot in agricultural landscapes. Landsc. Ecol. 29, 1249–1259 (2014).
    Google Scholar 
    Duffield, G. & Bull, M. Stable social aggregations in an Australian lizard, Egernia stokesii. Naturwissenschaften 89, 424–427 (2002).CAS 
    PubMed 

    Google Scholar 
    Duffield, G. A. & Bull, M. Characteristics of the litter of the gidgee skink, Egernia stokesii. Wildl. Res. 23, 337–341 (1996).
    Google Scholar 
    Ecoscape. Blue Hills – Mungada East Terrestrial Fauna Assessment. (Sinosteel Midwest Corporation, 2016).Silver Lake Resources. Department of Water and Environmental Regulation Prescribe Premise Licence Application. (Egan Street Resources Limited, 2021).Maptek. I-Site 8800 Scanning System Solutions for Mining (2010).SoilWater Group. 3D LiDAR Scanning (2018).United States Department of Transportation. Ground-Based LiDAR Rock Slope Mapping and Assessment (2008).R Core Team. R: a language and environment for statistical computing, https://www.R-project.org/ (2017).Bartoń, K. Package ‘MuMIn’, https://cran.r-project.org/web/packages/MuMIn/MuMIn.pdf (2020).Converse, S. J., White, G. C. & Block, W. M. Small mammal responses to thinning and wildfire in ponderosa pine-dominated forests of the southwestern United States. J. Wildl. Manag. 70, 1711–1722 (2006).
    Google Scholar 
    Vieira, I. C. G. et al. Classifying successional forests using Landsat spectral properties and ecological characteristics in eastern Amazonia. Remote Sens. Environ. 87, 470–481 (2003).
    Google Scholar 
    Whitford, K. & Williams, M. Hollows in jarrah (Eucalyptus marginata) and marri (Corymbia calophylla) trees: II. Selecting trees to retain for hollow dependent fauna. For. Ecol. Manag. 160, 215–232 (2002).
    Google Scholar 
    Salmona, J., Dixon, K. M. & Banks, S. C. The effects of fire history on hollow-bearing tree abundance in montane and subalpine eucalypt forests in southeastern Australia. For. Ecol. Manag. 428, 93–103 (2018).
    Google Scholar 
    Lindenmayer, D., Cunningham, R., Donnelly, C., Tanton, M. & Nix, H. The abundance and development of cavities in Eucalyptus trees: a case study in the montane forests of Victoria, southeastern Australia. For. Ecol. Manage. 60, 77–104 (1993).
    Google Scholar 
    Craig, M. D. et al. How many mature microhabitats does a slow-recolonising reptile require? Implications for restoration of bauxite minesites in south-western Australia. Aust. J. Zool. 59, 9–17 (2011).
    Google Scholar 
    Schwarzkopf, L., Barnes, M. & Goodman, B. Belly up: Reduced crevice accessibility as a cost of reproduction caused by increased girth in a rock-using lizard. Austral Ecol. 35, 82–86 (2010).
    Google Scholar 
    Cooper, W. E. Jr. & Whiting, M. J. Islands in a sea of sand: Use of Acacia trees by tree skinks in the Kalahari Desert. J. Arid Environ. 44, 373–381 (2000).
    Google Scholar 
    Webb, J. K. & Shine, R. Out on a limb: conservation implications of tree-hollow use by a threatened snake species (Hoplocephalus bungaroides: Serpentes, Elapidae). Biol. Cons. 81, 21–33 (1997).
    Google Scholar 
    Fitzgerald, M., Shine, R. & Lemckert, F. Radiotelemetric study of habitat use by the arboreal snake Hoplocephalus stephensii (Elapidae) in eastern Australia. Copeia 2002, 321–332 (2002).
    Google Scholar 
    Grimm-Seyfarth, A., Mihoub, J. B. & Henle, K. Too hot to die? The effects of vegetation shading on past, present, and future activity budgets of two diurnal skinks from arid Australia. Ecol. Evol. 7, 6803–6813 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Attum, O., Eason, P., Cobbs, G. & El Din, S. M. B. Response of a desert lizard community to habitat degradation: Do ideas about habitat specialists/generalists hold?. Biol. Cons. 133, 52–62 (2006).
    Google Scholar 
    Melville, J. & Schulte Ii, J. A. Correlates of active body temperatures and microhabitat occupation in nine species of central Australian agamid lizards. Austral. Ecol. 26, 660–669. https://doi.org/10.1046/j.1442-9993.2001.01152.x (2001).Article 

    Google Scholar 
    Munguia-Vega, A., Rodriguez-Estrella, R., Shaw, W. W. & Culver, M. Localized extinction of an arboreal desert lizard caused by habitat fragmentation. Biol. Cons. 157, 11–20 (2013).
    Google Scholar 
    Pietrek, A., Walker, R. & Novaro, A. Susceptibility of lizards to predation under two levels of vegetative cover. J. Arid Environ. 73, 574–577 (2009).
    Google Scholar 
    Moreno, S., Delibes, M. & Villafuerte, R. Cover is safe during the day but dangerous at night: The use of vegetation by European wild rabbits. Can. J. Zool. 74, 1656–1660 (1996).
    Google Scholar 
    Tchabovsky, A. V., Krasnov, B., Khokhlova, I. S. & Shenbrot, G. I. The effect of vegetation cover on vigilance and foraging tactics in the fat sand rat Psammomys obesus. J. Ethol. 19, 105–113 (2001).
    Google Scholar 
    Pizzuto, T. A., Finlayson, G. R., Crowther, M. S. & Dickman, C. R. Microhabitat use by the brush-tailed bettong (Bettongia penicillata) and burrowing bettong (B. lesueur) in semiarid New South Wales: Implications for reintroduction programs. Wildl. Res. 34, 271–279 (2007).
    Google Scholar 
    Hawlena, D., Saltz, D., Abramsky, Z. & Bouskila, A. Ecological trap for desert lizards caused by anthropogenic changes in habitat structure that favor predator activity. Conserv. Biol. 24, 803–809 (2010).PubMed 

    Google Scholar 
    Oversby, W., Ferguson, S., Davis, R. A. & Bateman, P. Bad news for bobtails: Understanding predatory behaviour of a resource-subsidised corvid towards an island endemic reptile. Wildl. Res. 45, 595–601 (2018).
    Google Scholar 
    Pianka, E. R. Rarity in A ustralian desert lizards. Austral Ecol. 39, 214–224 (2014).
    Google Scholar 
    Germano, J. M. & Bishop, P. J. Suitability of amphibians and reptiles for translocation. Conserv. Biol. 23, 7–15 (2009).PubMed 

    Google Scholar 
    Tsiouvaras, C., Havlik, N. & Bartolome, J. Effects of goats on understory vegetation and fire hazard reduction in a coastal forest in California. For. Sci. 35, 1125–1131 (1989).
    Google Scholar 
    Tasker, E. M. & Bradstock, R. A. Influence of cattle grazing practices on forest understorey structure in north-eastern New South Wales. Austral. Ecol. 31, 490–502 (2006).
    Google Scholar 
    Payne, A., Van Vreeswyk, A., Leighton, K., Pringle, H. & Hennig, P. An inventory and condition survey of the Sandstone-Yalgoo-Paynes Find area, Western Australia (1998).Shoo, L. P., Freebody, K., Kanowski, J. & Catterall, C. P. Slow recovery of tropical old-field rainforest regrowth and the value and limitations of active restoration. Conserv. Biol. 30, 121–132 (2016).PubMed 

    Google Scholar 
    Lamb, D. in Regreening the Bare Hills 325–358 (Springer, 2011).Bowler, D. E. & Benton, T. G. Causes and consequences of animal dispersal strategies: Relating individual behaviour to spatial dynamics. Biol. Rev. 80, 205–225 (2005).PubMed 

    Google Scholar 
    Stow, A. J., Sunnucks, P., Briscoe, D. & Gardner, M. The impact of habitat fragmentation on dispersal of Cunningham’s skink (Egernia cunninghami): Evidence from allelic and genotypic analyses of microsatellites. Mol. Ecol. 10, 867–878 (2001).CAS 
    PubMed 

    Google Scholar 
    Stow, A. & Sunnucks, P. High mate and site fidelity in Cunningham’s skinks (Egernia cunninghami) in natural and fragmented habitat. Mol. Ecol. 13, 419–430 (2004).CAS 
    PubMed 

    Google Scholar  More

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    The marine biologist whose photography pastime became a profession

    If you are a scientist hoping to photograph and share your own research:
    •    Don’t underestimate the power of modern media and social-media platforms. Content is changing the world and people’s lives, and it can easily change your life. Stay at the forefront of media technology, or at least be aware of developments. It’s a never-ending race, but it’s easy to get into.
    •    If you plan to share your work with others, imagine what will be of interest to them. If you can excitingly describe your work to a 5-year-old, you won’t have any trouble getting anyone interested. Beautiful pictures help, but the story always comes first.

    •    You will stand out much more if you have a niche and unique story. It could be your rare field of science or a special angle that you use to tell the story of your work. Being different is awesome.
    •    Set the bar very high. You can find dozens of examples of truly high-quality content on the Internet. And you can almost always find resources that can help you to learn how to create work of the same calibre. With practice, your skills will inevitably rise — but at any given time, it’s important to know the level you should aim for.
    •    Find people who are cooler than you. Don’t hesitate to ask them for advice or to shadow them. Have them share their experiences, stand behind them and observe their work if they’ll let you. Few things are more useful than real work experience, both your own and that of others.
    •    Take on a project. This could be a an illustrated workbook for colleagues or students, a guide book, a lecture for schoolchildren with compelling visuals, a course for students or a documentary on your topic.
    •    If you work in a team, you can raise the bar even higher. Use each other’s strengths, share experiences, make plans, apply for grants and take on challenging science-communication projects together. This multiplies the fun and the results. More

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    Evaluating the impact of highway construction projects on landscape ecological risks in high altitude plateaus

    Tsering, D. Transport development in Tibet since the democratic reform in 1959. J. Tibetan Stud. 76–85 (2019).Yan, X. et al. Relationships between heavy metal concentrations in roadside topsoil and distance to road edge based on field observations in the Qinghai-Tibet Plateau, China. Int. J. Environ. Res. Public Health. 10(3), 762–765 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Berling-Wolff, S. & Jianguo, W. U. Modeling urban landscape dynamics: A case study in Phoenix, USA. J. Urban Ecosyst. 7(3), 215–240 (2004).
    Google Scholar 
    Jianzhou, G., Yansui, L. & Beicheng, X. Spatial heterogeneity of urban land-cover landscape in Guangzhou from 1990 to 2005. J. Geogr. Sci. 19(2), 213–224 (2009).
    Google Scholar 
    Pan, L., Zhang, H. & Liu, A. Analysis of threshold of road networks effecting landscape fragmentation in Chongqing. J. Ecol. Sci. 34(5), 45–51 (2015).CAS 

    Google Scholar 
    Paukert, C. P., Pitts, K. L., Whittier, J. B. & Oldenc, J. D. Development and assessment of a landscape-scale ecological threat index for the Lower Colorado River Basin. J. Ecol. Indic. 11(2), 304–310 (2011).
    Google Scholar 
    Li, H., Yu, Q., Li, N., Wang, J. & Yang, Y. Study on landscape dynamics and driving mechanisms of the Shudu Lake catchment wetlands in Northwest Yunnan. J. West China Forest. Sci. 42(3), 34–39 (2013).Yunqing, H., Jinxi, W. & Hong, J. The dynamics of land cover change pattern and landscape fragmentation in Jiuzhaigou Nature Reserve, China. J. Proc. SPIE Int. Soc. Opt. Eng. 7498, 74983P (2009).Hu, L. et al. Landscape pattern in Nanwenghe nature reserve and its driving forces. J. Protect. Forest Sci. Technol. 0(7), 18–21 (2015).Li, X. et al. Land use/cover and landscape pattern changes in Manas River Basin based on remote sensing. J. Int. J. Agric. Biol. Eng. 13(5), 141–152 (2020).Andrejs, R. & Merkurjevs, J. Software tool implementing the fuzzy AHP method in ecological risk assessment. J. Inform. Technol. Manag. Sci. 20(1), 34–39 (2017).Peng, J., Dang, W., Liu, Y., Zong, M. & Hu, X. Research progress and prospect of landscape ecological risk assessment. J. Acta Geogr. Sin. 70(04), 664–677 (2015).
    Google Scholar 
    Xu, Y., Fu, B. & Lü, H. Research on landscape pattern and ecological processes based on landscape models. J. Acta Ecol. Sin. 30(1), 212–220 (2010).
    Google Scholar 
    Forman, R. Road ecology: A solution for the giant embracing us. J. Landsc. Ecol. 13(4), 3–5 (1998).
    Google Scholar 
    Minxi, W., Shiliang, L., Baoshan, C. & Min, Y. Impacts of hydroelectric project construction on nature reserve and assessment. J. Acta Ecol. Sin. 28(4), 1663–1671 (2008).
    Google Scholar 
    Yang, K., Deng, X., Xue-Ling, L. I. & Wen, P. Impacts of hydroelectric cascade exploitation on river ecosystem and landscape: A review. J. Acta Ecol. Sin. 22(5), 1359–1367 (2011).
    Google Scholar 
    Chen, L. D., Wang, J. P., Jiang, C. L. & Zhang, H. P. Quantitative study on effect of linear project construction on landscape pattern along pipeline. J. Sci. Geogr. Sin. 30(2), 161–167 (2010).
    Google Scholar 
    Qianqian, H., Luomeng, C. & Shanlin, W. Impact of expressway on land use and landscape pattern: A case study of Putan Guai to Chenghao section of Inner Mongolia Provincial Highway 103. J. Environ. Protect. Sci. 35(05), 58–61 (2009).
    Google Scholar 
    Huang, Y., Li, Y. & Ying, H. Responses of Chongqing-Yi Expressway to land use change and landscape pattern. J. Nat. Resourc. 30(09), 1449–1460 (2015).
    Google Scholar 
    Keken, Z., Sebkova, M. & Skalos, J. Analyzing land cover change—The impact of the motorway construction and their operation on landscape structure. J. Geogr. Inform. Syst. 6(5), 559–571 (2014).Mengna, H. & Ting, M. Assessing the impacts of China’s road network on landscape fragmentation and protected areas. J. Geo-inform. Sci. 21(8), 1183–1195 (2019).
    Google Scholar 
    Mothorpe, C., Hanson, A. & Schnier, K. The impact of interstate highways on land use conversion. J. Ann. Reg. Sci. 51(3), 833–870 (2013).
    Google Scholar 
    Wu, C.-F., Lin, Y.-P., Chiang, L.-C. & Huang, T. Assessing highway’s impacts on landscape patterns and ecosystem services: a case study in Puli Township, Taiwan. J. Landsc. Urban Plan. 128, 60–71 (2014).
    Google Scholar 
    Jia, L., Lei, T. & Yan, S. H. Environmental impact analysis and control measures in tunnel construction. J. Appl. Mech. Mater. 90–93, 3250–3253 (2011).ADS 

    Google Scholar 
    Wang, M. Analysis of high-speed railway construction on ecological environment impact and environmental protection contribution. J. Railway Constr. Technol. https://doi.org/10.3969/j.issn.1009-4539.2015.04.019 (2015).Article 

    Google Scholar 
    He, Y. & Xiong, C. Environmental impact of waste slurry in pile foundation construction of high-speed railway bridges and its countermeasures. J. Adv. Mater. Res. 383–390, 3690–3694 (2011).
    Google Scholar 
    Jing, C. et al. Influence of cross-sea bridge project on water quality and ecological environment of nearby sea and its tracking, monitoring and verification. J. Ocean Dev. Manag. 37(10), 96–100 (2020).
    Google Scholar 
    Jianhua, X., Mingquan, W., Shijian, Z. & Zheng, N. Remote sensing monitoring of ecological and economic impacts of major Railway construction along the Belt and Road. J. Sci. Technol. Eng. 20(11), 9 (2020).
    Google Scholar 
    Fang, L. On ecological environment impact assessment of metal mine construction project. J. Nonferrous Metals (Min. Sect.). 64(03), 58–60 (2012).
    Google Scholar 
    Bian, B., Lin, C. & Wu, H. S. Contamination and risk assessment of metals in road-deposited sediments in a medium-sized city of China. J. Ecotoxicol. Environ. Saf. 112, 87–95 (2015).CAS 

    Google Scholar 
    Limin, Y., Yanhai, Z., Rongzu, Q. & Xisheng, H. The influence of regional road construction on landscape ecology on both sides: A case study of Jiangle County, Fujian Province. J. Sichuan Agric. Univ. 33(2), 159–165 (2015).
    Google Scholar 
    Liang, Z. & Nianlai, C. Analysis on the impact of Jinwu Expressway on ecological environment based on comprehensive index evaluation method. J. Environ. Sustain. Dev. 44(3), 137–139 (2019).
    Google Scholar 
    Ting, W. & Zongmin, W. Study on eco-environmental impact assessment system of highway construction. J. Resourc. Econom. Environ. Protect. 3, 129–132. (2015).
    Google Scholar 
    Igondova, E., Pavlickova, K. & Majzlan, O. The ecological impact assessment of a proposed road development (the Slovak approach). J. Environ. Impact Assessm. Rev. 59, 43–54 (2016).
    Google Scholar 
    Chen, L., Fu, B. & Zhao, W. Source-sink landscape theory and its ecological significance. J. Front. Biol. China 3(2), 131–136 (2008).
    Google Scholar 
    Wu, J. et al. Spatial differentiation of landscape ecological risk in opencast mining area. J. Acta Ecol. Sin. 33(12), 3816–3824 (2013).
    Google Scholar 
    Wang, J., Cui, B., Liu, J., Yao, H. & Juan, H. The effect of land use and its change on ecological risk in the Lancang River watershed of Yunnan Province at the landscape scale. J. Acta Sci. Circumstan. 2, 269–277 (2008).CAS 
    Article 

    Google Scholar 
    Xie, H. Regional eco-risk analysis based on landscape structure and spatial statistics. J. Acta Ecol. Sin. 28(10), 5020–5026 (2008).
    Google Scholar 
    Jinggang, L. I., Chunyang, H. E. & Xiaobing, L. I. Landscape ecological risk assessment of natural/semi-natural landscapes in fast urbanization regions——A case study in Beijing, China. J. Nat. Resourc. 23(1), 33–47 (2008).
    Google Scholar 
    Jie, W., Wanqi, B. & Guoxing, T. Temporal and spatial characteristics of landscape ecological risk in Qinghai-Tibet Plateau. J. Resour. Sci. 42(9), 1739–1749 (2020).
    Google Scholar 
    Xuegong, X., Huiping, L., Zaiyi, F. & Rencang, B. Ecological risk assessment of wetland area in Yellow River Delta. J. Acta Sci. Nat. Univ. Pekinensis. 01, 111–120 (2001).
    Google Scholar 
    Malekmohammadi, B. & Blouchi, L. Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system. J. Ecol. Indic. 41, 133–144 (2014).
    Google Scholar 
    Campos, P., Paz, T., Lenz, L., Qiu, Y. & Paz, I. Multi-criteria decision method for sustainable watercourse management in urban areas. J. Sustain. 12(16), 6493–6514 (2020).
    Google Scholar 
    Peng, L. et al. Research on ecological risk assessment in land use model of Shengjin Lake in Anhui province, China. J. Environ. Geochem. Health. 41(6), 2665–2679 (2019).CAS 

    Google Scholar 
    Zhang, D., Yang, S., Wang, Z., Yang, C. & Chen, Y. Assessment of ecological environment impact in highway construction activities with improved group AHP-FCE approach in China. J. Environ. Monit. Assess. 192(7), 451–469 (2020).
    Google Scholar 
    Luan, B. et al. Evaluating green stormwater infrastructure strategies efficiencies in a rapidly urbanizing catchment using SWMM-based topsis. J. Clean. Prod. 223, 680–691 (2019).
    Google Scholar 
    Ramya, S. & Devadas, V. Integration of GIS, AHP and TOPSIS in evaluating suitable locations for industrial development: A case of Tehri Garhwal district, Uttarakhand, India. J. Clean. Prod. 238, 117872 (2019).Koc, K., Ekmekciolu, M. & Zger, M. An integrated framework for the comprehensive evaluation of low impact development strategies. J. Environ. Manag. 294, 113023 (2021).Xiumei, T., Yu, L., Yanmin, R., Yuchun, P. & Xingyao, H. Study on change of land use and ecosystem service value along expressway. J. China Agric. Univ. 21(2), 132–139 (2016).
    Google Scholar 
    Fei, Z., Shanjiang, Y. & Dongfang, W. Ecological risk assessment due to land use/cover changes (LUCC) in Jinghe County, Xinjiang, China from 1990 to 2014 based on landscape patterns and spatial statistics. J. Environ. Earth. Sci. 77(13), 491 (2018).
    Google Scholar 
    Rangel-Buitrago, N., Neal, W. J. & de Jonge, V. N. Risk assessment as tool for coastal erosion management. J. Ocean Coast. Manag. 186, 105099 (2020).
    Google Scholar 
    Mo, W., Wang, Y., Zhang, Y. & Zhuang, D. Impacts of road network expansion on landscape ecological risk in a megacity, China: A case study of Beijing. J. Sci. Total Environ. 574, 1000–1011 (2017).ADS 
    CAS 

    Google Scholar 
    Getis, A. & Ord, J. K. The analysis of spatial association by use of distance statistics. J. Springer Berlin Heidelberg. 24(3), 189–206 (2010).
    Google Scholar 
    Yingxue, Z., Wenbo, M., Yong, W. & Dafang, Z. Impact of land use change on landscape pattern around expressways in Beijing. J. Geo-Inform. Sci. 19(001), 28–38 (2017).
    Google Scholar 
    Gang, Z., HuiJun, G. & Guang, Z. Changes of wetland landscape pattern in arid inland area of Northwest China: A case study of inner flow area in Junggar, Xinjiang. J. Arid Land Resourc. Environ. 28(8), 77–82 (2014).
    Google Scholar 
    Haihang, W., Qianhui, Z., Jiayao, Z. & Chunguo, Z. Analysis on dynamic change of landscape pattern of land use in Zhushan County. J. Forest Resourc. Manag. 6, 76–83 (2018).
    Google Scholar 
    Shiliang, L., Zhifeng, Y., Baoshan, C. & Shu, G. Impact of road on landscape and ecological risk assessment: A case study of Lancang River Basin. J. Chin. J. Ecol. 8, 897–901 (2005).
    Google Scholar 
    Yuan, Y. et al. Flood-landscape ecological risk assessment under the background of urbanization. J. Water. 11(7), 1418 (2019).Xie, H., Wang, P. & Huang, H. Ecological risk assessment of land use change in the Poyang lake Eco-economic zone, China. J. Int. J. Environ. Res. Public Health. 10(1), 328–346 (2013).
    Google Scholar 
    Fengjiao, X. & Xiao, L. Ecological risk pattern in coastal areas of Jiangsu Province based on land use change. J. Acta Ecol. Sin. 38(20), 7312–7325 (2018).
    Google Scholar 
    Mann, D., Anees, M. M., Rankavat, S. & Joshi, P. K. Spatio-temporal variations in landscape ecological risk related to road network in the Central Himalaya. J. Hum. Ecol. Risk Assess. https://doi.org/10.1080/10807039.2019.1710693 (2020).Article 

    Google Scholar 
    Oliveira, B. R. D., Costa, E. L. D., Carvalho-Ribeiro, S. M. & Maia-Barbosa, P. M. Land use dynamics and future scenarios of the Rio Doce State Park buffer zone, Minas Gerais, Brazil. J. Environ. Monit. Assessm. 192(1), 39.1–39.12 (2020).
    Google Scholar 
    Li, Y., Sun, Y. & Li, J. Heterogeneous effects of climate change and human activities on annual landscape change in coastal cities of mainland China. J. Ecol. Indic. https://doi.org/10.1016/j.ecolind.2021.107561 (2021).Dadashpoor, H., Azizi, P. & Moghadasi, M. Land use change, urbanization, and change in landscape pattern in a metropolitan area. J. Sci. Total Environ. 655(10), 707–709 (2019).ADS 
    CAS 

    Google Scholar  More

  • in

    Silicon improves ion homeostasis and growth of liquorice under salt stress by reducing plant Na+ uptake

    Zhao, S. et al. Regulation of plant responses to salt stress. Int. J. Mol. Sci. 22, 4609 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Acosta-Motos, J. R. et al. Plant responses to salt stress: Adaptive mechanisms. Agronomy-Basel 7, 18 (2017).
    Google Scholar 
    Munns, R. & Tester, M. Mechanisms of salinity tolerance. Annu. Rev. Plant Biol. 59, 651–681 (2008).CAS 
    PubMed 

    Google Scholar 
    Wu, H. H. Plant salt tolerance and Na+ sensing and transport. Crop J. 6, 215–225 (2018).
    Google Scholar 
    Ali, M. et al. Silicon mediated improvement in the growth and ion homeostasis by decreasing Na+ uptake in maize (Zea mays L.) cultivars exposed to salinity stress. Plant Physiol. Biochem. 158, 208–218 (2021).CAS 
    PubMed 

    Google Scholar 
    Javaid, T., Farooq, M. A., Akhtar, J., Saqib, Z. A. & Anwar-ul-Haq, M. Silicon nutrition improves growth of salt-stressed wheat by modulating flows and partitioning of Na+, Cl- and mineral ions. Plant Physiol. Biochem. 141, 291–299 (2019).CAS 
    PubMed 

    Google Scholar 
    Zelm, E. V., Zhang, Y. X. & Testerink, C. Salt tolerance mechanisms of plants. Annu. Rev. Plant Biol. 71, 403–433 (2020).PubMed 

    Google Scholar 
    Kumar, P. et al. Potassium: A key modulator for cell homeostasis. J. Biotechnol. 324, 198–210 (2020).CAS 
    PubMed 

    Google Scholar 
    Ahmad, P., Ahanger, M. A., Alam, P., Alyemeni, M. N. & Ashraf, M. Silicon (Si) supplementation alleviates NaCl toxicity in mung bean [Vigna radiata (L.) Wilczek] through the modifications of physio-biochemical attributes and key antioxidant enzymes. J. Plant Growth Regul. 38, 1–13 (2018).
    Google Scholar 
    Chiappero, J. et al. Antioxidant status of medicinal and aromatic plants under the influence of growth-promoting rhizobacteria and osmotic stress. Ind. Crops Prod. 167, 113541 (2021).CAS 

    Google Scholar 
    Conceicao, S. S. et al. Silicon modulates the activity of antioxidant enzymes and nitrogen compounds in sunflower plants under salt stress. Arch. Agron. Soil Sci. 65, 1237–1247 (2019).CAS 

    Google Scholar 
    Etesami, H. & Jeong, B. R. Silicon (Si): Review and future prospects on the action mechanisms in alleviating biotic and abiotic stresses in plants. Ecotoxicol. Environ. Saf. 147, 881–896 (2018).CAS 
    PubMed 

    Google Scholar 
    Epstein, E. Silicon. Annu. Rev. Plant Physiol. Plant Mol. Biol. 50, 641–664 (1999).CAS 
    PubMed 

    Google Scholar 
    Epstein, E. The anomaly of silicon in plant biology. Proc. Natl. Acad. Sci. U S A 91, 11–17 (1994).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jadhao, K. R., Bansal, A. & Rout, G. R. Silicon amendment induces synergistic plant defense mechanism against pink stem borer (Sesamia inferens Walker.) in finger millet (Eleusine coracana Gaertn.). Sci. Rep. 10, 15 (2020).
    Google Scholar 
    Li, Z. C. et al. Silicon enhancement of estimated plant biomass carbon accumulation under abiotic and biotic stresses. A meta-analysis. Agron. Sustain. Dev. 38, 19 (2018).CAS 

    Google Scholar 
    Yan, G. C. et al. Silicon improves rice salinity resistance by alleviating ionic toxicity and osmotic constraint in an organ-specific pattern. Front. Plant Sci. 11, 12 (2020).
    Google Scholar 
    Farouk, S., Elhindi, K. M. & Alotaibi, M. A. Silicon supplementation mitigates salinity stress on Ocimum basilicum L. via improving water balance, ion homeostasis, and antioxidant defense system. Ecotoxicol. Environ. Saf. 206, 11 (2020).
    Google Scholar 
    Yin, J. L. et al. Silicon enhances the salt tolerance of cucumber through increasing polyamine accumulation and decreasing oxidative damage. Ecotoxicol. Environ. Saf. 169, 8–17 (2019).CAS 
    PubMed 

    Google Scholar 
    Hurtado, A. C. et al. Different methods of silicon application attenuate salt stress in sorghum and sunflower by modifying the antioxidative defense mechanism. Ecotoxicol. Environ. Saf. 203, 11 (2020).
    Google Scholar 
    Gaur, S. et al. Fascinating impact of silicon and silicon transporters in plants: A review. Ecotoxicol. Environ. Saf. 202, 12 (2020).
    Google Scholar 
    Vandegeer, R. K. et al. Silicon deposition on guard cells increases stomatal sensitivity as mediated by K(+)efflux and consequently reduces stomatal conductance. Physiol. Plant 171, 358–370 (2021).CAS 
    PubMed 

    Google Scholar 
    Lina, et al. Silicon-mediated changes in polyamines participate in silicon-induced salt tolerance in Sorghum bicolor L.. Plant Cell Environ. 39, 245–258 (2016).
    Google Scholar 
    Hassanvand, F., Nejad, A. R. & Fanourakis, D. Morphological and physiological components mediating the silicon-induced enhancement of geranium essential oil yield under saline conditions. Ind. Crops Prod. 134, 19–25 (2019).CAS 

    Google Scholar 
    Altuntas, O., Dasgan, H. Y. & Akhoundnejad, Y. Silicon-induced salinity tolerance improves photosynthesis, leaf water status, membrane stability, and growth in pepper (Capsicum annuum L.). HortScience 53, 1820–1826 (2018).CAS 

    Google Scholar 
    Coskun, D. et al. The controversies of silicon’s role in plant biology. New Phytol. 221, 67–85 (2019).PubMed 

    Google Scholar 
    Jiang, M. Y. et al. An “essential herbal medicine”-licorice: A review of phytochemicals and its effects in combination preparations. J. Ethnopharmacol. 249, 14 (2020).
    Google Scholar 
    Zhang, X. Y. et al. Inhibition effect of glycyrrhiza polysaccharide (GCP) on tumor growth through regulation of the gut microbiota composition. J. Pharmacol. Sci. 137, 324–332 (2018).CAS 
    PubMed 

    Google Scholar 
    Baltina, L. A. et al. Glycyrrhetinic acid derivatives as Zika virus inhibitors: Synthesis and antiviral activity in vitro. Bioorg. Med. Chem. 41, 116204 (2021).CAS 
    PubMed 

    Google Scholar 
    Zhao, Z. Y. et al. Glycyrrhizic ccid nanoparticles as antiviral and anti-inflammatory agents for COVID-19 treatment. ACS Appl. Mater. Interfaces 13, 20995–21006 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lu, J. H., Lv, X., Wu, L. & Li, X. Y. Germination responses of three medicinal licorices to saline environments and their suitable ecological regions. Acta Pratacul. Sin. 22, 198–205 (2013).
    Google Scholar 
    Geng, G. Q. & Xie, X. R. Effect of drought and salt stress on the physiological and biochemical characteristics of Glycyrrhiza uralensis. Pratacult. Sci. 35, 113–120 (2018).
    Google Scholar 
    Cui, J. J., Zhang, X. H., Li, Y. T., Zhou, D. & Zhang, E. H. Effect of silicon addition on seedling morphological and physiological indicators of Glycyrrhiza uralensis under salt stress. Acta Pratacul. Sin. 24, 214–220 (2015).
    Google Scholar 
    Zhang, W. J. et al. Silicon alleviates salt and drought stress of Glycyrrhiza uralensis plants by improving photosynthesis and water status. Biol. Plant. 64, 302–313 (2020).CAS 

    Google Scholar 
    Zhang, W. J. et al. Silicon promotes growth and root yield of Glycyrrhiza uralensis under salt and drought stresses through enhancing osmotic adjustment and regulating antioxidant metabolism. Crop Prot. 107, 1–11 (2018).
    Google Scholar 
    Chen, D. Q. et al. Silicon moderated the K deficiency by improving the plant-water status in sorghum. Sci. Rep. 6, 14 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Cui, J. J., Zhang, E. H., Zhang, X. H. & Wang, Q. Silicon alleviates salinity stress in licorice (Glycyrrhiza uralensis) by regulating carbon and nitrogen metabolism. Sci. Rep. 11, 12 (2021).
    Google Scholar 
    Lichtenthaler, H. K. & Wellburn, A. R. Determinations of total carotenoids and chlorophylls a and b of leaf extracts in different solvents. Analysis 11, 591–592 (1983).CAS 

    Google Scholar 
    Yan, K., Wu, C. W., Zhang, L. H. & Chen, X. B. Contrasting photosynthesis and photoinhibition in tetraploid and its autodiploid honeysuckle (Lonicera japonica Thunb.) under salt stress. Front. Plant Sci. 6, 9 (2015).
    Google Scholar 
    Li, H. S. Principles and Techniques of Plant Physiological and Biochemical Experiments (Higher Education Press, 2000).
    Google Scholar 
    Bradford, M. M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254 (1976).CAS 
    PubMed 

    Google Scholar 
    Lutts, S., Kinet, J. M. & Bouharmont, J. NaCl-induced senescence in leaves of rice (Oryza sativa L) cultivars differing in salinity resistance. Ann. Bot. 78, 389–398 (1996).CAS 

    Google Scholar 
    Havir, E. A. & Mchale, N. A. Biochemical and developmental characterization of multiple forms of catalase in tobacco leaves. Plant Physiol. 84, 450–455 (1987).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rizwan, M. et al. Mechanisms of silicon-mediated alleviation of drought and salt stress in plants: A review. Environ. Sci. Pollut. Res. 22, 15416–15431 (2015).CAS 

    Google Scholar 
    Al-Huqail, A. A., Alqarawi, A. A., Hashem, A., Malik, J. A. & Abd Allah, E. F. Silicon supplementation modulates antioxidant system and osmolyte accumulation to balance salt stress in Acacia gerrardii Benth. Saudi J. Biol. Sci. 26, 1856–1864 (2019).CAS 
    PubMed 

    Google Scholar 
    Hurtado, A. C. et al. Silicon application induces changes C:N: P stoichiometry and enhances stoichiometric homeostasis of sorghum and sunflower plants under salt stress. Saudi J. Biol. Sci. 27, 3711–3719 (2020).
    Google Scholar 
    Zhang, X. H., Zhang, W. J., Lang, D. Y., Cui, J. J. & Li, Y. T. Silicon improves salt tolerance of Glycyrrhiza uralensis Fisch by ameliorating osmotic and oxidative stresses and improving phytohormonal balance. Environ. Sci. Pollut. Res. 25, 25916–25932 (2018).CAS 

    Google Scholar 
    Liang, W. J., Ma, X. L., Wan, P. & Liu, L. Y. Plant salt-tolerance mechanism: A review. Biochem. Biophys. Res. Commun. 495, 286–291 (2018).CAS 
    PubMed 

    Google Scholar 
    Tester, M. & Davenport, R. Na+ tolerance and Na+ transport in higher plants. Ann. Bot. 91, 503–527 (2003).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Khan, W. U. D. et al. Silicon nutrition mitigates salinity stress in maize by modulating ion accumulation, photosynthesis, and antioxidants. Photosynthetica 56, 1047–1057 (2018).CAS 

    Google Scholar 
    Zahoor, R. et al. Potassium fertilizer improves drought stress alleviation potential in cotton by enhancing photosynthesis and carbohydrate metabolism. Environ. Exp. Bot. 137, 73–83 (2017).CAS 

    Google Scholar 
    Hurtado, A. C. et al. Silicon alleviates sodium toxicity in sorghum and sunflower plants by enhancing ionic homeostasis in roots and shoots and increasing dry matter accumulation. SILICON 13, 475–486 (2021).CAS 

    Google Scholar 
    Yan, G. C. et al. Silicon alleviates salt stress-induced potassium deficiency by promoting potassium uptake and translocation in rice (Oryza sativa L.). J. Plant Physiol. 258, 7 (2021).
    Google Scholar 
    Dhiman, P. et al. Fascinating role of silicon to combat salinity stress in plants: An updated overview. Plant Physiol. Biochem. 162, 110–123 (2021).CAS 
    PubMed 

    Google Scholar 
    Bosnic, P., Bosnic, D., Jasnic, J. & Nikolic, M. Silicon mediates sodium transport and partitioning in maize under moderate salt stress. Environ. Exp. Bot. 155, 681–687 (2018).CAS 

    Google Scholar 
    Alamri, S. et al. Silicon-induced postponement of leaf senescence is accompanied by modulation of antioxidative defense and ion homeostasis in mustard (Brassica juncea) seedlings exposed to salinity and drought stress. Plant Physiol. Biochem. 157, 47–59 (2020).CAS 
    PubMed 

    Google Scholar 
    Ahmad, P. et al. Nitric oxide mitigates salt stress by regulating levels of osmolytes and antioxidant enzymes in chickpea. Front. Plant Sci. 7, 1–11 (2016).
    Google Scholar 
    Zhu, Y. X. et al. Silicon confers cucumber resistance to salinity stress through regulation of proline and cytokinins. Plant Physiol. Biochem. 156, 209–220 (2020).CAS 
    PubMed 

    Google Scholar  More

  • in

    First titanosaur dinosaur nesting site from the Late Cretaceous of Brazil

    Carballido, J. L. et al. A new giant titanosaur sheds light on body mass evolution among sauropod dinosaurs. Proc. R. Soc. B Biol. Sci. 284, 20171219 (2017).
    Google Scholar 
    Hechenleitner, E. M. et al. Two Late Cretaceous sauropods reveal titanosaurian dispersal across South America. Commun. Biol. 3, 622 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Otero, A., Carballido, J. L., Salgado, L., Canudo, I. & Garrido, A. C. Report of a giant titanosaur sauropod from the Upper Cretaceous of Neuquén Province, Argentina. Cretaceous Res. 122, 104754 (2021).
    Google Scholar 
    Sander, P. M. et al. Biology of the sauropod dinosaurs: The evolution of gigantism. Biol. Rev. 86, 117–155 (2011).PubMed 

    Google Scholar 
    Gorscak, E. & O’Connor, P. M. A new African titanosaurian sauropod dinosaur from the middle Cretaceous Galula Formation (Mtuka Member), Rukwa Rift Basin, southwestern Tanzania. PLoS One 14, e0211412 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Poropat, S. F. et al. Second specimen of the Late Cretaceous Australian sauropod dinosaur Diamantinasaurus matildae provides new anatomical information on the skull and neck of early titanosaurs. Zool. J. Linn. Soc. 192, 610–674 (2021).
    Google Scholar 
    González Riga, B. J. et al. An overview of the appendicular skeletal anatomy of South American titanosaurian sauropods, with definition of a newly recognized clade. An. Acad. Bras. Ciênc. 91, e20180374 (2019).
    Google Scholar 
    Gorscak, E. & O’connor, P. M. Time-calibrated models support congruency between Cretaceous continental rifting and titanosaurian evolutionary history. Biol. Lett. 12, 20151047 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Pérez Moreno, A., Carballido, J. L., Otero, A., Salgado, L. & Calvo, J. O. The axial skeleton of Rinconsaurus caudamirus (Sauropoda: Titanosauria) from the Late Cretaceous of Patagonia, Argentina. Ameghiniana 59, 1–46 (2022).
    Google Scholar 
    Chiappe, L. M., Jackson, F., Coria, R. A. & Dingus, L. Nesting titanosaurs from Auca Mahuevo and adjacent sites. In The Sauropods: Evolution and Paleobiology (eds Curry Rogers, K. A. & Wilson, J. A.) 285–302 (University of California Press, 2005).
    Google Scholar 
    Hechenleitner, E. M., Grellet-Tinner, G. & Fiorelli, L. E. What do giant titanosaur dinosaurs and modern Australasian megapodes have in common?. PeerJ 3, e1341 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Cojan, I., Renard, M. & Emmanuel, L. Palaeoenvironmental reconstruction of dinosaur nesting sites based on a geochemical approach to eggshells and associated palaeosols (Maastrichtian, Provence Basin, France). Palaeogeogr. Palaeoclimatol. Palaeoecol. 191, 111–138 (2003).
    Google Scholar 
    Grellet-Tinner, G., Codrea, V., Folie, A., Higa, A. & Smith, T. First evidence of reproductive adaptation to “island effect” of a dwarf Cretaceous Romanian titanosaur, with embryonic integument in ovo. PLoS One 7(3), e32051 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Khosla, A. & Lucas, S. Late Cretaceous dinosaur eggs and eggshells of peninsular India. Top. Geobiol. 51, 1–295 (2020).
    Google Scholar 
    Vila, B., Galobart, A., Oms, O., Poza, B. & Bravo, A. M. Assessing the nesting strategies of Late Cretaceous titanosaurs: 3-D clutch geometry from a new megaloolithid egg site. Lethaia 43, 197–208 (2009).
    Google Scholar 
    Chiappe, L. M. et al. Sauropod dinosaur embryos from the Late Cretaceous of Patagonia. Nature 396, 258–261 (1998).ADS 
    CAS 

    Google Scholar 
    Salgado, L. et al. Upper Cretaceous dinosaur nesting sites of Río Negro (Salitral Ojo de Agua and Salinas de Trapalco-Salitral de Santa Rosa), Northern Patagonia, Argentina. Cretaceous Res. 28, 392–404 (2007).
    Google Scholar 
    Salgado, L., Magalhães Ribeiro, C. M., García, R. A. & Fernández, M. A. Late Cretaceous megaloolithid eggs from Salitral de Santa Rosa (Río Negro, Patagonia, Argentina): Inferences on the titanosaurian reproductive biology. Ameghiniana 46, 605–620 (2009).
    Google Scholar 
    Grellet-Tinner, G. & Fiorelli, L. E. A new Argentinean nesting site showing neosauropod dinosaur reproduction in a Cretaceous hydrothermal environment. Nat. Commun. 1, 32 (2010).ADS 
    PubMed 

    Google Scholar 
    Hechenleitner, E. M. et al. A new Upper Cretaceous titanosaur nesting site from La Rioja (NW Argentina), with implications for titanosaur nesting strategies. Palaeontology 59, 433–446 (2016).
    Google Scholar 
    Kundrát, M. et al. Specialized craniofacial anatomy of a titanosaurian embryo from Argentina. Curr. Biol. 30, 4263–4269 (2020).PubMed 

    Google Scholar 
    Chiappe, L. M., Salgado, L. & Coria, R. A. Embryonic skulls of titanosaur sauropod dinosaurs. Science 293, 2444–2446 (2001).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Grellet-Tinner, G., Chiappe, L. M., Norell, M. & Bottjer, D. Dinosaur eggs and nesting behaviors: A paleobiological investigation. Palaeogeogr. Palaeoclimatol. Palaeoecol. 232, 294–321 (2006).
    Google Scholar 
    Coria, R. A. & Chiappe, L. M. Embryonic skin from Late Cretaceous sauropods (Dinosauria) of Auca Mahuevo, Patagonia, Argentina. J. Paleontol. 81, 1528–1532 (2007).
    Google Scholar 
    Leuzinger, L. et al. Life and reproduction of titanosaurians: Isotopic hallmark of mid-palaeolatitude eggshells and its significance for body temperature, diet, and nesting. Chem. Geol. 583, 120452 (2021).ADS 
    CAS 

    Google Scholar 
    Faccio, G. Dinosaurian eggs from the upper Cretaceous of Uruguay. In Dinosaur Eggs and Babies (eds Carpenter, K. et al.) 47–53 (Cambridge University Press, 1994).
    Google Scholar 
    Vianey-Liaud, M., Hirsch, K., Sahni, A. & Sigé, B. Late Cretaceous Peruvian eggshells and their relationships with Laurasian and Eastern Gondwanian material. Geobios 30, 75–90 (1997).
    Google Scholar 
    Magalhães Ribeiro, C. M. Microstructural analysis of dinosaur eggshells from Bauru Basin (Late Cretaceous), Minas Gerais, Brasil. In First International Symposium on Dinosaur Eggs and Babies (eds Bravo, A. M. & Reyes, T.) 117–122 (Isona I Conca Dellà Catalonia, 2000).
    Google Scholar 
    Magalhães Ribeiro, C. M. Ovo e fragmentos de cascas de ovos de dinossauros, provenientes de região de Peirópolis, Uberaba, Minas Gerais. Arq. Mus. Nac. 60, 223–228 (2002).
    Google Scholar 
    Grellet-Tinner, G. & Zaher, H. Taxonomic identification of the Megaloolithidae egg and eggshells from Cretaceous Bauru Basin (Minas Gerais, Brazil): Comparison with the Auca Mahuevo (Argentina) titanosaurid eggs. Papéis Avulsos Zool. 47, 105–112 (2007).
    Google Scholar 
    Martinelli, A. G. & Teixeira, V. P. A. The Late Cretaceous vertebrate record from the Bauru Group in the Triângulo Mineiro, southeastern Brazil. Bol. Geol. Minero 126, 129–158 (2015).
    Google Scholar 
    Soares, M. V. T. et al. Sedimentology of a distributive fluvial system: The Serra da Galga Formation, a new lithostratigraphic unit (Upper Cretaceous, Bauru Basin, Brazil). Geol. J. 56, 951–975 (2021).
    Google Scholar 
    Soares, M. V. T. et al. Landscape and depositional controls on palaeosols of a distributive fluvial system (Upper Cretaceous, Brazil). Sedim. Geol. 409, 105774 (2020).
    Google Scholar 
    Martinelli, A. G. et al. Palaeoecological implications of an Upper Cretaceous tetrapod burrow (Bauru Basin; Peirópolis, Minas Gerais, Brazil). Palaeogeogr. Palaeoclimatol. Palaeoecol. 528, 147–159 (2019).
    Google Scholar 
    Grellet-Tinner, G., Chiappe, L. M. & Coria, R. A. Eggs of titanosaurid sauropods from the Upper Cretaceous of Auca Mahuevo (Argentina). Can. J. Earth Sci. 41, 949–960 (2004).ADS 

    Google Scholar 
    Wilson, J. A., Mohabey, D. M., Peters, S. E. & Head, J. J. Predation upon hatchling dinosaurs by a new snake from the Late Cretaceous of India. PLoS Biol. 8, e1000322 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Garcia, G. & Vianey-Liaud, M. Nouvelles données sur les coquilles d’œufs de dinosaures Megaloolithidae du Sud de la France: Systématique et variabilité intraspécifique. C. R. Acad. Sci. A. 332, 185–191 (2001).
    Google Scholar 
    Vianey-Liaud, M., Khosla, A. & Garcia, G. Relationships between European and Indian dinosaur eggs and eggshells of the oofamily Megaloolithidae. J. Vertebr. Paleontol. 23, 575–585 (2003).
    Google Scholar 
    Campos, D. A., Kellner, A. W. A., Bertini, R. J. & Santucci, R. M. On a titanosaurid (Dinosauria, Sauropoda) vertebral column from the Bauru Group, Late Cretaceous of Brazil. Arq. Mus. Nac. 63, 565–593 (2005).
    Google Scholar 
    Kellner, A. W. A., Campos, D. A. & Trotta, M. N. F. Description of a titanosaurid caudal series from the Bauru Group, Late Cretaceous of Brazil. Arq. Mus. Nac. 63, 529–564 (2005).
    Google Scholar 
    Machado, E. B., Avilla, L. S., Nava, W. R., Campos, D. A. & Kellner, A. W. A. A new titanosaur sauropod from the Late Cretaceous of Brazil. Zootaxa 3701, 301–321 (2013).PubMed 

    Google Scholar 
    Silva Junior, J. C. G. et al. Reassessment of Aeolosaurus maximus, a titanosaur dinosaur from the Late Cretaceous of Southeastern Brazil. Hist. Biol. 34, 402–411 (2022).
    Google Scholar 
    Bandeira, K. L. N. et al. A new giant Titanosauria (Dinosauria: Sauropoda) from the Late Cretaceous Bauru Group, Brazil. PLoS One 11, e0163373 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Pearce, J. M. Philopatry: A return to origins. Auk 124, 1085–1087 (2007).
    Google Scholar 
    Kokko, H. & López-Sepulcre, A. From individual dispersal to species ranges: Perspectives for a changing world. Science 313, 789–791 (2006).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Basilici, G., Hechenleitner, E. M., Fiorelli, L. E., Dal Bó, P. F. & Mountney, N. P. Preservation of titanosaur egg clutches in Upper Cretaceous cumulative palaeosols (Los Llanos Formation, La Rioja, Argentina). Palaeogeogr. Palaeoclimatol. Palaeoecol. 482, 83–102 (2017).
    Google Scholar 
    Mueller-Töwe, I. J., Sander, P. M., Schüller, H. & Thies, D. Hatching and infilling of dinosaur eggs as revealed by computed tomography. Palaeontogr. Abt. A 267, 119–168 (2002).
    Google Scholar 
    Paganelli, C. V. The physics of gas exchange across the avian eggshell. Am. Zool. 20, 329–338 (1980).
    Google Scholar 
    Grellet-Tinner, G., Fiorelli, L. E. & Salvador, R. B. Water vapor conductance of the Lower Cretaceous dinosaurian eggs from Sanagasta, La Rioja, Argentina: Paleobiological and paleoecological implications for South American faveoloolithid and megaloolithid eggs. Palaios 27, 35–47 (2012).ADS 

    Google Scholar 
    Grellet-Tinner, G. Phylogenetic interpretation of eggs and eggshells: Implications for phylogeny of Palaeognathae. Alcheringa 30, 141–182 (2006).
    Google Scholar 
    Mikhailov, K. E., Bray, E. S. & Hirsch, K. F. Parataxonomy of fossil egg remains (Veterovata): Principles and applications. J. Vertebr. Paleontol. 16, 763–769 (1996).
    Google Scholar 
    Nys, Y., Gautron, J., Garcia-Ruiz, J. M. & Hincke, M. T. Avian eggshell mineralization: Biochemical and functional characterization of matrix proteins. C. R. Palevol 3, 549–562 (2004).
    Google Scholar 
    Fernández, M. S., Passalacqua, K., Arias, J. I. & Arias, J. L. Partial biomimetic reconstitution of avian eggshell formation. J. Struct. Biol. 148, 1–10 (2004).PubMed 

    Google Scholar 
    Arias, J. L. & Fernández, M. S. Biomimetic processes through the study of mineralized shells. Mater. Charact. 50, 189–195 (2003).CAS 

    Google Scholar 
    Arias, J. L., Mann, K., Nys, Y., Garcia Ruiz, J. M. & Fernández, M. S. Eggshell growth and matrix macromolecules. In Handbook of Biomineralization (ed. Baeuerlein, E.) 309–328 (Wiley, 2007).
    Google Scholar 
    Chien, Y.-C., Hincke, M. T., Vali, H. & Mckee, M. D. Ultrastructural matrix–mineral relationships in avian eggshell, and effects of osteopontin on calcite growth in vitro. J. Struct. Biol. 163, 84–99 (2008).CAS 
    PubMed 

    Google Scholar 
    Hincke, M. T. et al. The eggshell: Structure, composition and mineralization. Front. Biosci. 17, 1266–1280 (2012).CAS 

    Google Scholar 
    Stapane, L. et al. Avian eggshell formation reveals a new paradigm for vertebrate mineralization via vesicular amorphous calcium carbonate. J. Biol. Chem. 295, 15853–15869 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Norell, M. A. et al. A theropod dinosaur embryo and the affinities of the Flaming Cliffs dinosaur eggs. Science 266, 779–782 (1994).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Araújo, R. et al. Filling the gaps of dinosaur eggshell phylogeny: Late Jurassic Theropod clutch with embryos from Portugal. Sci. Rep. 3, 1924 (2013).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Xing, L. et al. An exquisitely preserved in-ovo theropod dinosaur embryo sheds light on avian-like prehatching postures. iScience 103516, 24 (2021).
    Google Scholar 
    Sato, T., Cheng, Y.-N., Wu, X.-C., Zelenitsky, D. K. & Hsiao, Y.-F. A pair of shelled eggs inside a female dinosaur. Science 308, 375 (2005).CAS 
    PubMed 

    Google Scholar 
    Norell, M. A., Clark, J. M. & Chiappe, L. M. A nesting dinosaur. Nature 378, 774–776 (1995).ADS 
    CAS 

    Google Scholar 
    Dong, Z. M. & Currie, P. J. On the discovery of an oviraptorid skeleton on a nest of eggs at Bayan Mandahu, Inner Mongolia, People’s Republic of China. Can. J. Earth Sci. 33, 631–636 (1996).ADS 

    Google Scholar  More

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    Water ecological security assessment and spatial autocorrelation analysis of prefectural regions involved in the Yellow River Basin

    Water ecological security evaluation results of Yellow River BasinIndex weight analysisThis study selects the index weights in 2009, 2014, and 2019 for comparative analysis. As shown in Table 3, in terms of space, in the pressure layer, indicator A6 (Water area) has the most prominent weight, and indicator A3 (Natural population growth rate) has the most negligible weight; in the state layer, indicator B6 (Proportion of wetland area to total area) has the most prominent weight, and B1 (COD emissions per 10,000 yuan GDP) has the most negligible weight; in the response layer, indicator C3 (Green area rate of built-up area) has the most prominent weight, and indicator C2 (Centralized treatment rate of urban domestic sewage) has the most negligible weight. In summary, water area, wetland area, and built-up green space are the key indicators affecting the water ecology of the Yellow River Basin, including natural factors and economic and social factors.Table 3 Water ecological security index weight.Full size tableIn terms of time, indicators A6 and B6 have equal weights in three years and have always been in an important position. The weight of indicator C1 (the rate of stable compliance of wastewater discharge by industrial enterprises) has fallen for three consecutive years, from 0.38 to 0.09. It shows that after years of environmental management in various cities, the rate of compliance with wastewater discharge standards of industrial enterprises has been continuously increasing. It plays a positive role in the construction of water ecological security. The weight of indicator C3 has increased significantly in three years, from 0.31 in 2009 to 0.90 in 2019, indicating that with the continuous development of urbanization, the built-up area has become larger and larger, which has a massive impact on water ecological security. Therefore, the green area in the built-up area is vital, which is the key to ensuring the urban ecological environment. It is also a critical factor in maintaining the water ecological security.Trend analysis of water ecological securityThis study is based on Eq. (4) to calculate the WESI of the nine provinces in the past ten years, as shown in Fig. 3. From the perspective of the changes in WESI from 2009 to 2019, the overall trend is slowly increasing. Compared with 2009, WESI increased by 5.96% in 2019, but the average annual growth rate was only 0.59%. The sharp rise stage was in 2009–2012, with an average annual growth rate of 1.84%. Since 2009, there has been no inferior V water in the main stream of the Yellow River, and the water quality has been improving year by year. During this period, the nine provinces implemented the Yellow River Basin Flood Control Plan under the guidance of The State Council. The plan calls for strengthening infrastructure construction in the Yellow River Basin and conducting work such as river improvement and soil and water conservation. Therefore, we will promote the restoration of water ecology in the river basin and improve the safety of water ecology. From 2012 to 2019, WESI showed a trend of ups and downs. This is because the provinces have gradually shifted their development focus to the economy after achieving significant results in restoring water ecology in the river basin. The rapid economic development has brought more significant pressure to environmental governance and hindered water ecological safety improvement.Figure 3Trend map of water ecological security index (WESI) of nine provinces.Full size imageCriterion layer quantitative resultsTo further study and appraise the water ecological security of the study area, this paper quantifies the criteria layers (i.e., pressure, state, response) on account of the SMI-P method. It selects 2009, 2014, and 2019 for comparative analysis. As shown in Fig. 4, the criterion layer has undergone specific changes over time. First of all, the distribution of pressure in 62 cities has not changed much in three years. The areas with more tremendous pressure on water ecological security are mainly concentrated in eastern cities, including Shuozhou, Taiyuan, Jinzhou, Luliang, Linfen, Jincheng, and Changzhi, Anyang, Hebi, Jiaozuo, Puyang, Liaocheng, and other cities. Areas with less pressure are mainly concentrated in western and eastern cities, including Guoluo Tibetan Autonomous Prefecture, Hainan Tibetan Autonomous Prefecture, Haibei Tibetan Autonomous Prefecture, Ordos, Bayannaoer, Yulin, and other cities. In 2009, the precipitation in spring and winter in Lanzhou is less, the degree of drought is serious, and the flood disaster is more severe in flood season, which brings tremendous pressure to the water ecological security. After 2015, Lanzhou continued to implement the Action Plan for Prevention and Control of Water Pollution and then the river chief system was implemented. In 2019, The Work Plan of Lanzhou Municipal Water Pollution Prevention and Control Action in 2019 was issued and implemented. All these measures and actions have laid a foundation for water ecological security. On the contrary, with the rapid development of urbanization and economy and society, the pressure of water ecological security in Jinan has increased.Figure 4Quantitative spatial distribution map of the 62 cities in the Yellow River Basin. Note This was created by ArcMap-GIS, version 10.5. https://www.esri.com/.Full size imageThe larger the value of the status layer, the better the aquatic ecological status. On the contrary, the worse the aquatic ecological security. The overall spatial distribution of the status layer has not changed significantly in the past three years, and the changes are mainly concentrated in some cities. For example, the water ecological security status of Wuhan and Ulan Chab has gradually deteriorated in three years. The reason is that the urban population is becoming denser and sewage discharge is increasing, but related management and measures have not been fully implemented. In Dongying, the water ecological security status improved in 2014 and 2019. According to the Environmental Status Bulletin, in 2014, Dongying deepened its drainage basin pollution control system, continuously strengthened the restraint mechanism to improve river water quality, and carried out a pilot wetland ecological restoration.In the three years of 2009, 2014, and 2019, the response layer has changed more significantly than the pressure and status layers. It can be seen that the degree of response scarcity has gradually shifted from western cities to eastern cities. The reason can be understood as that due to their superior natural conditions, western cities have relatively weak awareness of water ecological protection and governance, and their ability to respond to emergencies is insufficient. However, with the increasingly prominent ecological and environmental problems, the awareness of maintaining water ecological safety is increasing, and the protection and governance measures are constantly improving. For example, Guoluo Tibetan Autonomous Prefecture, Hainan Tibetan Autonomous Prefecture, and Haibei Tibetan Autonomous Prefecture. Eastern cities are densely populated, urbanization development is faster than western cities, and environmental problems occur more frequently. Therefore, the awareness of ecological and environmental protection is more substantial, the governance system is relatively complete, and responsiveness is relatively good. However, as time progresses, some cities have somewhat slackened their ecological environment governance, and therefore their responsiveness has also weakened. For example, Shuozhou, Jinzhou, Lvliang, Linfen, and other places.Final quantitative resultsIn order to show the water ecological security status of 62 cities more intuitively, this paper shows the water ecological status level in Table 2 through the GIS spatial distribution map (Fig. 5).Figure 5Distribution map of water ecological security status in 62 cities of the Yellow River Basin. Note This was created by ArcMap-GIS, version 10.5. https://www.esri.com/.Full size imageLooking at the overall situation in the past three years, the water ecological security status is relatively stable, with little overall change. The reasons mainly include natural geographical location and economic and social development. In terms of physical geography, the safer areas are concentrated in the upper reaches of the Yellow River Basin, all of which have the characteristics of large land and sparsely populated areas and relatively superior natural conditions. They provide good conditions and foundations for the construction of water ecological security. The moderate warning cities are primarily located in the Loess Plateau and the North China Plain, where water resources are scarce, and the dense population, posing a threat to water ecological security. In terms of economic and social development, relatively safe areas are located in remote areas with inconvenient transportation. The region is dominated by agriculture and animal husbandry, with relatively backward economic development and a low level of urbanization. In addition, the threat to water ecological security is relatively tiny. Residents in the moderate warning area have a significant living demand, and the over-exploitation and utilization of natural resources have led to the destruction of the ecological environment. Therefore, it poses a more significant threat to water ecological security.Combining Fig. 5 and Table A.2 of appendix, it can be seen that in 2009, there were 8 safer cities, 22 with early warning level, and 32 with moderate warning. Relatively safe cities are concentrated in the southwest and north of the Yellow River Basin; cities with moderate warning level are distributed in the central and eastern areas. In 2014, the number of safer cities increased to 10, and the number of cities with moderate warning level decreased to 30. The means that water ecological security has received more and more attention, and cities have consciously strengthened the protection and governance of water ecology to maintain water ecological security. In 2019, there are 11 relatively safe cities, 21 cities with warning level, and 30 cities with moderate warning level. The overall situation has not changed much, and some cities have changed significantly. For example, Erdos had increased from an early warning status in 2009 to a safer status in 2014, and its safety index has risen from 0.57 to 0.65. Wuzhong has been upgraded from the warning level in 2009 (0.39) to the relatively safe in 2014 (0.44), and the safety index (0.47) in 2019 has also increased. Binzhou had improved from its early warning status (0.60) in 2009 to a relatively safe level (0.64) in 2014, and its safety index (0.66) has also increased in 2019, but the increase is not significant. On the contrary, Jinan has deteriorated from the early warning level in 2009 and 2014 to the moderate warning level in 2019, indicating that the water ecological security of Jinan has been seriously threatened in the process of rapid development.Spatial autocorrelation analysis of 62 cities in the Yellow River BasinGlobal spatial autocorrelation analysisThis paper selects 2009, 2014 and 2019, and analyzes the global spatial autocorrelation based on GeoDa. Combining Table 4 and Fig. 6, the Moran index for these three years was 0.298, 0.359, and 0.334 respectively, which were all in the [0,1] interval, indicating the water ecological security of 62 cities in the past three years showed significant spatial autocorrelation. Moreover, there is a positive spatial correlation, and the spatial autocorrelation is strong. The four quadrants of the scatter chart are high-high (i.e., first quadrant) aggregation area, low–high (i.e., second quadrant) aggregation area, low-low (i.e., third quadrant) aggregation area, and high-low (i.e., fourth quadrant) aggregation area. After testing, z-value  > 1.96, p-value  More

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    Tracing the invasion of a leaf-mining moth in the Palearctic through DNA barcoding of historical herbaria

    Detection of archival Phyllonorycter mines in historical herbariaOnly 1.5% (225 out of 15,009) of herbarium specimens of Tilia spp. examined from the Palearctic contained Ph. issikii leaf mines. These 225 herbarium specimens occurred in 185 geographical locations across the Palearctic, with the westernmost point in Germany (Hessen; the herbarium specimen dated by 2004) to the most eastern locations in Japan (on the island of Hokkaido; 1885–1974) (Fig. 1).Figure 1The localities where herbarium specimens of Tilia spp. carrying Phyllonorycter mines were collected in the Palearctic in the last 253 years. The dotted line divides Ph. issikii range to native (below the line) and invaded (above the line). The map was generated using ArcGIS 9.3 (Release 9.3. New York St., Redlands, CA. Environmental Systems Research Institute, http://www.esri.com/software/arcgis/eval-help/arcgis-93).Full size imageMost specimens with leaf mines (90%; 203/225) originated from Eastern Palearctic, in particular from the Russian Far East (RFE) (67.5%, 137/203) (Fig. 2a). In some cases, leaves were severely attacked, carrying up to 12 mines per leaf (as documented in the Russian Far East in 1930s–1960s). On the other hand, we found only 22 herbarium specimens with mines (10%; 22/225) from the putative invaded region in Western Palearctic, with the majority of herbarium specimens with mines (7% 15/225) from European Russia (Fig. 2b).Figure 2The presence of Phyllonorycter issikii mines in the herbarium specimens collected in the putative native (a) and invaded (b) ranges over the past 253 years (1764–2016). The number of herbarium specimens with and without mines and the percentage of the specimens with mines in each region or country from all herbarium specimens examined in a region or country (in brackets) are given next to each graph. The total number of herbarium specimens, including those with and without mines, is given for Eastern (a) and Western Palearctic (b) separately and altogether (a + b).Full size imageThe average number of leaf mines per herbarium specimen found in native (5.68 ± 0.77) and invaded regions (6.09 ± 1.70) was not significantly different (Mann–Whitney U-test: U = 20,145; Z = 0.43; p = 0.43). However, the infestation rate by Ph. issikii, i.e. percentage of leaves with mines per herbarium specimen was statistically higher in the West than in the East: 35% ± 8.19 versus 23% ± 1.94 (Mann–Whitney U-test: U = 1339; Z = 2.30; p = 0.02).Leaf mines from the East were significantly older than those from the West (Mann–Whitney U-test: U = 81; Z =  − 4.4; p  400 bp) were obtained for 71 archival specimens that were between 7 and 162 years old (Fig. 4, the points in dashed frame) (Table S4). Nine of these 71 specimens were over one century old (106–162-year-old): eight originated from the Palearctic and one from the Nearctic (Fig. 4, the points in gray cloud).In the Palearctic, the oldest successfully DNA barcoded Ph. issikii specimen (obtained sequence length 408 bp) was a 162-year-old larva dissected from the leaf mine on Tilia amurensis from the RFE (village Busse, Amur Oblast, the year 1859), sequence ID LMINH119-19 (Fig. 5, Table S5). In the Nearctic, the oldest sequenced specimen (obtained sequence length 658 bp) was 127-year-old larva of Ph. tiliacella on T. americana from USA, Pennsylvania (Fig. 5, Table S5).Figure 5A maximum likelihood tree of 81 COI sequences of Phyllonorycter spp. Overall, 71 archival sequenced specimens were dissected from herbaria collected in the Palearctic and the Nearctic in 1859–2014 and ten specimens (highlighted in blue) originated from the modern range20. The tree was generated with the K2P nucleotide substitution model and bootstrap method (2500 iterations), p  More

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    Effects of COVID-19 lockdowns on shorebird assemblages in an urban South African sandy beach ecosystem

    Graded lockdowns imposed by the South African government to manage the COVID-19 pandemic27,28,29 has afforded us a unique opportunity to quantify shorebird responses to increasing human density in Muizenberg Beach over 8 months in 2020, including a 2-month period of virtual human exclusion. In spite of our study being limited to one beach over 2 years, we were able to take advantage of data collected prior to- (2019) and during the 2020 COVID lockdowns, to better understand a pervasive feature of sandy beach ecosystems (human recreation) that is predicted to intensify in future10.Findings for the 2019–2020 component of our study generally conformed to hypotheses posed. Firstly, shorebird abundance was inversely associated with human abundance and was positively related to lockdown level in 2020. Secondly, shorebird abundance was generally greatest during lockdown levels 5 and 4, when humans were effectively absent from the beach. To contextualise, shorebird abundance was roughly six times greater at the start of lockdown level 5 (2020) than the equivalent period in 2019. Thirdly, lowest shorebird abundance occurred during lockdown level 1 when human abundance was greatest in 2020. Collectively, these findings indicate a strong inverse association between shorebird- and human abundance on Muizenberg Beach and align with results of other studies36,37,38,39. Cumulatively, our findings, allied with prior research highlight the potential for human recreational activity, particularly at high intensities, to impact shorebird utilisation of sandy beach ecosystems, which may in turn affect ecological functions they provide that contribute to ecosystem multifunctionality.The inverse relationship that we recorded between human- and shorebird abundance likely manifests through the diverse ways in which recreational activity impacts fundamental processes and ecosystem components, which in turn link ecologically to shorebirds10,36,37,38,39,40. Muizenberg Beach is popular for surfing, bait-harvesting and general recreational activities, and it is these activities that likely drive the human-shorebird relationship that we report, particularly in 2020. When carried out under high human densities, such activities can lead to a reduction in space available, rendering the ecosystem less suitable as a substrate for birds36. Noise pollution and the presence of dogs may further depress habitat suitability41. Repeated trampling of sediment can negatively impact macrofaunal populations, which together with altered sedimentary biogeochemistry (e.g. increased anoxia), can reduce trophic resource availability to shorebirds, with benthic bait-collecting compounding these effects42,43. At the start of our data collection in 2020, we were unable to identify shorebird species due to lockdown levels 5 and 4 prohibiting human presence on the beach27,28,29. It is probable though that shorebird assemblages during lockdown levels 5 and 4 were not the same as those we identified between lockdown level 3 to 1 (mainly gulls; Table 3). This is based on research showing that increasing environmental disturbances can induce switches in biotic assemblages to those that can tolerate human activities44. Thus, the shorebird assemblages we identified during lockdown levels 3 to 1 is potentially the end-result of the mechanisms highlighted above (space reduction, noise, reduced resource availability) acting on shorebird assemblages in the absence of humans (lockdown levels 5 and 4) following humans being permitted onto the beach.At an inter-annual level, our data revealed idiosyncratic patterns that raise interesting questions about human-shorebird relationships. In 2019, in the absence of any lockdowns, shorebird abundance rose over the winter period (May–August). Winter peaks in abundance have previously been recorded in the literature45,46,47, including for kelp gulls (Larus dominicanus), which were the dominant shorebird in Muizenberg Beach. Specifically, winter abundance peaks for this species have been recorded in sandy beaches in the Eastern Cape, the Swartkops Estuary and Algoa Bay in South Africa (southeast coast)45,46,47. However, the absence of a winter abundance peak in 2020 raises the possibility that the 2019 winter-peak was not seasonal but an opportunistic response to decreased human abundance (see Fig. 4A). In South Africa, coastal ecosystems generally experience greatest human numbers in summer, due to warmer conditions and long end-of-year-vacation periods, based on our observations and experiences.The second inter-annual trend worth noting in our findings is that shorebird abundance was greater in 2019 than 2020, despite lockdowns being implemented in 2020. This counterintuitive finding is likely due to lockdowns that excluded people from the beach in 2020 (levels 5 to 3) being too short in duration to facilitate increases in bird numbers in 2020 beyond the 2019 level. This is supported by our data showing that humans were excluded from the beach for a total of 2 months (April and May 2020; levels 5-4) out of the 8-month period during which photographs were analysed. It would have been expected at the onset of the study that humans would be excluded from the beach during lockdown level 329, which would have resulted in an additional two and a half months of human exclusion and potentially a higher mean shorebird abundance for 2020. However, it is clear from our data that humans were present on the beach during level 3. On closer inspection, it is evident that human numbers increased even prior to the end of lockdown level 4. In fact, human abundance was greater under lockdown level 3 in 2020 than in the same period in 2019. Such high numbers of humans on the beach despite prohibitions are likely due to a lack of compliance, confusion around regulations and/or ‘covid fatigue’, which describes the propensity of humans to grow tired of COVID-19 regulations48. An additional consideration is that human numbers on the beach increased dramatically during lockdown levels 2 and 1, being almost twice the level recorded in 2019 in the same period. The lower 2020 bird count that we recorded is thus likely a product of the short duration of human exclusions in 2020 (lockdown levels 4 and 5) and the magnitude and rate of increase in human numbers thereafter (levels 3-1). Separately, our findings additionally suggest that surrogates (lockdown levels in our case) are unreliable estimators of human presence or abundance and align with findings elsewhere24.The last noteworthy inter-annual trend in our data was the difference in strength of human-shorebird relationships. While the inverse relationship between human and shorebird numbers was evident in both years, it was only during 2020, when humans were excluded from Muizenberg Beach, that the extent of this relationship was revealed. Specifically, in 2020, human exclusion at the start of lockdown level 5 was accompanied by a six-fold increase in shorebird abundance relative to 2019 at the same period. Additional support for the difference in strength of the human-shorebird relationship is the (1) significant interaction recorded between human numbers and year in explaining shorebird abundance and (2) the almost twofold stronger negative relationship (based on regression slopes) between shorebird and human abundance in 2020 vs 2019. These findings suggest that were it not for the COVID lockdowns in 2020, the extent of increasing human numbers on shorebirds may have been masked. However, it must be borne in mind that inter-annual variation may have played some role in the difference in trends recorded for 2019 versus 2020, though we cannot quantify this, given that we only have data for 2 years. Nevertheless, we suggest that when making conservation/management recommendations, decision-makers need to be cognisant of the potential for human effects on sandy beach ecosystems to be underestimated in studies based on variation in human density, in which human exclusion at appropriate spatial and temporal scales is absent24. Concerns have been expressed in the past about the failure of studies to consistently detect large-scale changes in sandy beach ecosystems, including those induced by recreational activities19. We suggest that such deficiencies may relate in part to the scarcity of true human exclusions in disturbance studies at meaningful scales in space and time.Findings from the in situ component of our study suggested that shorebird assemblages were negligibly affected by the transition from lockdown level 3 to 1, but that spatial differences among zones were more prominent. The lack of cases in which lockdown levels interacted statistically with zones (Tables 2, 4) further reinforces our conclusion regarding lockdown effects. Shorebird assemblage structure did vary between lockdown levels 3 and 2, due mainly to increasing contributions of Chroicocephalus hartlaubii (Hartlaub’s Gull) from level 3 to 2 and the opposite for L. dominicanus. Contrary to our hypothesis, differences in assemblage (Shannon–Wiener diversity was the exception) and species metrics were not detected among lockdown levels. This was likely due to the gradient in human abundance being weak among lockdown levels 3 to 1, relative to levels 5 and 4, with there being no virtual exclusion of humans under level 3 lockdown, as would have been expected given government regulations29. It is also possible that under lockdown levels 3, 2 and 1, the shorebird assemblage was simplified and comprised species tolerant of human activities44. The increase in Shannon–Wiener diversity value from lockdown level 3 to 2 was counter expectation, but likely reflects increased evenness during lockdown level 2, brought on by the declining dominance of L. dominicanus and a greater contribution of C. hartlaubii.Taken in its entirety, our findings provide valuable perspectives on human-shorebird interactions in sandy beaches. Based on our 2020 data spanning lockdowns of decreasing severity, our findings suggest that shorebirds are likely to benefit from human-free periods. This benefit is in reality likely to extend across multiple-trophic levels and is unlikely to be shorebird-specific, based on prior research reporting positive organism metrics at lower trophic levels in low human and/or human-free conditions in beach ecosystems20. Broadly, our findings attest to the value of using current and future lockdowns associated with managing the global COVID-19 pandemic to provide data on responses of birds and other organism groups to human-free spaces and times25,26,49. These human-free conditions can additionally provide invaluable data on sensitivities of ecosystem components and processes to increasing human density25,26,49. Data collected during lockdowns can provide better approximations of baseline conditions in sandy beach ecosystems, thereby providing a more meaningful basis for (1) evaluating future ecosystem change in response to human and global change stressors and (2) developing ecosystem restoration programs. This would be central to preventing long-term ecosystem degradation through the shifting base-line syndrome, where successive generations of decision makers/scientists judge the magnitude of change experienced by ecosystem components against increasingly deteriorating conditions over generational time-scales50. We also advocate for data emanating from COVID lockdown studies to be used in public education initiatives, so that beach users are made aware of the ways in which recreational activities can influence beach ecosystems. Such initiatives can improve involvement of public stakeholders in management of sandy beach ecosystems, which has been shown to provide cost-effective and sound decision-making, while increasing support for conservation initiatives51,52,53.Lastly, our findings have shed light on the sensitivity of shorebirds to increasing human numbers, mainly for recreational purposes. By moving beyond binary contrasts of human presence/absence, our work has also shown the magnitude of increasing human numbers on shorebirds, by virtue of the 34.18% increase in human abundance in our study corresponding with a 79.63% decline in bird numbers during the transition from lockdown level 4 to 3 in 2020. This finding is highly relevant considering that our work was based on an urban ecosystem—such systems are thought to have avian communities that are more disturbance tolerant relative to rural or suburban ecosystems54. Broadly, our work emphasises the need for environmental managers and city planners to be cognisant of the sensitivity of shorebirds to human recreational activities, even in urban settings, and to develop appropriate management plans in conjunction with scientists and stakeholders51,52,53. It should be noted that bird responses that we recorded in 2020 are unlikely to be driven solely by changing human numbers in Muizenberg Beach. Processes influencing bird assemblages in beaches surrounding our focal study area, including changes in human numbers and behaviour, may also have been influential determinants of trends recorded. We lack the data to comment meaningfully on this, but is an area worth exploring in future studies.Concluding perspectivesThe global COVID-19 anthropause has been described as the greatest large-scale experiment in modern history. This period has afforded scientists a unique opportunity to refine understanding of the consequences of human activities on Earth’s natural environments25,26,49. This is particularly relevant for human-dominated ecosystems such as sandy beaches, which are arguably the most utilised of Earth’s ecosystems for recreational purposes. In the absence of the COVID-19 anthropause, it is doubtful whether human exclusions could be carried out at scales that would allow meaningful detection of responses to human recreational disturbance. Our findings broadly attest to the points raised thus far, illustrating not only the potential for conventional approaches to underestimate human effects in sandy beaches, but also the sensitivity of shorebirds to human recreation and the magnitude of human influence. We hope that our findings stimulate further research on human recreational effects on sandy beach ecosystems, particularly with a view towards quantifying disturbance sensitivities and response thresholds of fundamental processes that drive multifunctionality in these heavily utilised, yet highly significant coastal ecosystems. We suggest that this is an imperative, given the exponential human population growth expected in the future, particularly along the coast, and the increasing demand predicted on sandy beach ecosystems from recreation, tourism and commercial sectors10,18. At its broadest level, our work dovetails with prior calls for scientists to capitalise on current and future COVID lockdowns to refine our understanding of human-nature interactions25, so that ecosystems and socio-ecological services provided can be sustainably utilised in the future. More