Ecology

1.Walker, M. et al. Formal ratification of the subdivision of the Holocene Series/Epoch (Quaternary System/Period): two new Global Boundary Stratotype Sections and Points (GSSPs) and three new stages/subseries. Episodes [online]. https://doi.org/10.18814/epiiugs/2018/018016 (2018).2.Liu, T., Lu, Y. & Zheng, H. Loess and the Environment. (China Ocean Press, 1985).3.An, Z. et al. Asynchronous Holocene optimum of the East Asian monsoon. Quat. Sci. Rev. 19, 743–762 (2000).ADS 
Article 

Google Scholar 
4.Dai, A. G. & Zhao, T. Uncertainties in historical changes and future projections of drought. Part I: estimates of historical drought changes. Clim. Chang. 144, 519–533 (2017).ADS 
Article 

Google Scholar 
5.Zastrow, M. China’s tree-planting could falter in a warming world. Nature 573, 474–475 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
6.Huang, J., Yu, H., Guan, X., Wang, G. & Guo, R. Accelerated dryland expansion under climate change. Nat. Clim. Change 6, 166–172 (2016).ADS 
Article 

Google Scholar 
7.Jin, G. & Liu, T. Mid-Holocene climate change in North China, and the effect on cultural development. Chin. Sci. Bull. 47, 408–413 (2002).Article 

Google Scholar 
8.Wang, Y. et al. The Holocene Asian monsoon: links to solar changes and North Atlantic climate. Science 308, 854–857 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
9.Cheng, H. et al. The Asian monsoon over the past 640,000 years and ice age terminations. Nature 534, 640–646 (2016).ADS 
CAS 
PubMed 
Article 

Google Scholar 
10.Dong, J. et al. A high-resolution stalagmite record of the Holocene East Asian monsoon from Mt Shennongjia, central China. Holocene 20, 257–264 (2010).ADS 
Article 

Google Scholar 
11.Beck, J. W. et al. A 550,000-year record of East Asian monsoon rainfall from Be-10 in loess. Science 360, 877–881 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
12.Goldsmith, Y. et al. Northward extent of East Asian monsoon covaries with intensity on orbital and millennial timescales. Proc. Natl Acad. Sci. U. S. A. 114, 1817–1821 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
13.Chen, F. et al. East Asian summer monsoon precipitation variability since the last deglaciation. Sci. Rep. 5, 11186 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
14.Li, Q. et al. Reconstructed moisture evolution of the deserts in northern China since the Last Glacial Maximum and its implications for the East Asian Summer Monsoon. Glob. Planet. Change 121, 101–112 (2014).ADS 
Article 

Google Scholar 
15.Xu, Z. et al. Critical transitions in Chinese dunes during the past 12,000 years. Sci. Adv. 6, eaay8020 (2020).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
16.Lu, H. et al. Late Quaternary aeolian activity in the Mu Us and Otindag dune fields (north China) and lagged response to insolation forcing. Geophys. Res. Lett. 32, L21716 (2005).ADS 
Article 

Google Scholar 
17.Peterse, F. et al. Decoupled warming and monsoon precipitation in East Asia over the last deglaciation. Earth Planet. Sci. Lett. 301, 256–264 (2011).ADS 
CAS 
Article 

Google Scholar 
18.Yang, X. et al. Early-Holocene monsoon instability and climatic optimum recorded by Chinese stalagmites. Holocene 29, 1059–1067 (2019).ADS 
Article 

Google Scholar 
19.Wei, Y. et al. Holocene and deglaciation hydroclimate changes in northern China as inferred from stalagmite growth frequency. Glob. Planet. Change 195, 103360 (2020).Article 

Google Scholar 
20.Wang, B. et al. How to measure the strength of the East Asian Summer Monsoon. J. Clim. 21, 4449–4463 (2008).ADS 
Article 

Google Scholar 
21.Liu, J. et al. Holocene East Asian summer monsoon records in northern China and their inconsistency with Chinese stalagmite delta O-18 records. Earth-Sci. Rev. 148, 194–208 (2015).ADS 
CAS 
Article 

Google Scholar 
22.Kutzbach, J. E. & Street-Perrott, F. A. Milankovitch forcing of fluctuations in the level of tropical lakes from 18 to 0 kyr BP. Nature 317, 130–134 (1985).ADS 
Article 

Google Scholar 
23.Liu, Z. et al. Chinese cave records and the East Asia Summer Monsoon. Quat. Sci. Rev. 83, 115–128 (2014).ADS 
Article 

Google Scholar 
24.Wen, X., Liu, Z., Wang, S., Cheng, J. & Zhu, J. Correlation and anti-correlation of the East Asian summer and winter monsoons during the last 21,000 years. Nat. Commun. 7, 11999 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
25.Liu, Z. et al. Transient simulation of last deglaciation with a new mechanism for Bolling-Allerod warming. Science 325, 310–314 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
26.LeGrande, A. N. & Schmidt, G. A. Sources of Holocene variability of oxygen isotopes in paleoclimate archives. Clim. Past 5, 441–455 (2009).Article 

Google Scholar 
27.Zhang, H. et al. East Asian hydroclimate modulated by the position of the westerlies during Termination I. Science 362, 580–583 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
28.Chiang, J. C. H. et al. Role of seasonal transitions and westerly jets in East Asian paleoclimate. Quat. Sci. Rev. 108, 111–129 (2015).ADS 
Article 

Google Scholar 
29.Waelbroeck, C. et al. Sea-level and deep water temperature changes derived from benthic foraminifera isotopic records. Quat. Sci. Rev. 21, 295–305 (2002).ADS 
Article 

Google Scholar 
30.Joos, F. & Spahni, R. Rates of change in natural and anthropogenic radiative forcing over the past 20,000 years. Proc. Natl Acad. Sci. U.S.A. 105, 1425–1430 (2008).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
31.He, C. et al. The hydroclimate footprint accompanying pan-Asian monsoon water isotope evolution during the last deglaciation. Sci. Adv. 7, eabe2611 (2021).PubMed 
Article 

Google Scholar 
32.Wu, D. et al. Decoupled early Holocene summer temperature and monsoon precipitation in southwest China. Quat. Sci. Rev. 193, 54–67 (2018).ADS 
Article 

Google Scholar 
33.Xiao, X., Yao, A., Hillman, A., Shen, J. & Haberle, S. G. Vegetation, climate and human impact since 20 ka in central Yunnan Province based on high-resolution pollen and charcoal records from Dianchi, southwestern China. Quat. Sci. Rev. 236, 106297 (2020).Article 

Google Scholar 
34.Ding, Q. & Wang, B. Circumglobal teleconnection in the Northern Hemisphere summer. J. Clim. 18, 3483–3505 (2005).ADS 
Article 

Google Scholar 
35.Seneviratne, S. I. et al. Investigating soil moisture-climate interactions in a changing climate: a review. Earth-Sci. Rev. 99, 125–161 (2010).ADS 
CAS 
Article 

Google Scholar 
36.Bonan, G. B., Levis, S., Sitch, S., Vertenstein, M. & Oleson, K. W. A dynamic global vegetation model for use with climate models: concepts and description of simulated vegetation dynamics. Glob. Chang. Biol. 9, 1543–1566 (2003).ADS 
Article 

Google Scholar 
37.Yamazaki, T., Yabuki, H., Ishii, Y., Ohta, T. & Ohata, T. Water and energy exchanges at forests and a grassland in Eastern Siberia evaluated using a one-dimensional land surface model. J. Hydrometeor. 5, 504–515 (2004).ADS 
Article 

Google Scholar 
38.Overpeck, J., Anderson, D., Trumbore, S. & Prell, W. The southwest Indian Monsoon over the last 18 000 years. Clim. Dyn. 12, 213–225 (1996).Article 

Google Scholar 
39.Ruddiman, W. F. What is the timing of orbital-scale monsoon changes? Quat. Sci. Rev. 25, 657–658 (2006).ADS 
Article 

Google Scholar 
40.Clemens, S. C. & Prell, W. L. A 350,000 year summer-monsoon multi-proxy stack from the Owen Ridge, Northern Arabian Sea. Mar. Geol. 201, 35–51 (2003).ADS 
Article 

Google Scholar 
41.Xie, P. & Arkin, P. A. Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Am. Meteorol. Soc. 78, 2539–2558 (1997).ADS 
Article 

Google Scholar 
42.Xu, Q. et al. Vegetation succession and East Asian Summer Monsoon Changes since the last deglaciation inferred from high-resolution pollen record in Gonghai Lake, Shanxi Province, China. Holocene 27, 835–846 (2017).ADS 
Article 

Google Scholar 
43.Xiao, J. et al. Holocene vegetation variation in the Daihai Lake region of north-central China: a direct indication of the Asian monsoon climatic history. Quat. Sci. Rev. 23, 1669–1679 (2004).ADS 
Article 

Google Scholar 
44.Blaauw, M. Methods and code for ‘classical’ age-modelling of radiocarbon sequences. Quat. Geochronol. 5, 512–518 (2010).Article 

Google Scholar 
45.Zheng, Z. et al. East Asian pollen database: modern pollen distribution and its quantitative relationship with vegetation and climate. J. Biogeogr. 41, 1819–1832 (2014).Article 

Google Scholar 
46.Song, C. et al. Simulation of China Biome reconstruction based on pollen data from surface sediment samples. Acta Botanica. Sin. 43, 201–209 (2001).
Google Scholar 
47.Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

Google Scholar 
48.Overpeck, J. T., Webb, T. & Prentice, I. C. Quantitative interpretation of fossil pollen spectra: dissimilarity coefficients and the method of modern analogs. Quat. Res. 23, 87–108 (1985).Article 

Google Scholar 
49.Guiot, J. Methodology of the last climatic cycle reconstruction in France from pollen data. Palaeogeogr. Palaeoclimatol. Palaeoecol. 80, 49–69 (1990).Article 

Google Scholar 
50.Peyron, O. et al. Climatic reconstruction in Europe for 18,000 YR B.P. from pollen data. Quat. Res. 49, 183–196 (1998).Article 

Google Scholar 
51.Davis, A. S., Brewer, S., Stevenson, A. C. & Guiot, J. The temperature of Europe during the Holocene reconstructed from pollen data. Quat. Sci. Rev. 22, 1701–1716 (2003).ADS 
Article 

Google Scholar 
52.Marsicek, J., Shuman, B. N., Bartlein, P. J., Shafer, S. L. & Brewer, S. Reconciling divergent trends and millennial variations in Holocene temperatures. Nature 554, 92–96 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
53.Juggins, S. Rioja: analysis of quaternary science data. https://cran.r-project.org/package=rioja (2017).54.Prentice, C. et al. Special paper: a global biome model based on plant physiology and dominance, soil properties and climate. J. Biogeogr. 19, 117–134 (1992).Article 

Google Scholar 
55.Williams, W. & Shuman, B. Obtaining accurate and precise environmental reconstructions from the modern analog technique and North American surface pollen dataset. Quat. Sci. Rev. 27, 669–687 (2008).ADS 
Article 

Google Scholar 
56.Simpson, G. L. “Analogue methods in palaeolimnology” in Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques, (eds Birks, H. J. B., Lotter, A. F., Juggins, S. & Smol, J. P.) 495–522 (Springer, 2012).57.Birks, H. J. B., Line, J. M., Juggins, S., Stevenson, A. C. & ter Braak, C. J. F. Diatoms and pH reconstruction. Philos. Trans. R. Soc. B 327, 263–278 (1990).ADS 

Google Scholar 
58.ter Braak, C. J. F. & Juggins, S. Weighted averaging partial least squares regression (WA-PLS): an improved method for reconstructing environmental variables from species assemblages. Hydrobiologia 269, 485–502 (1993).Article 

Google Scholar 
59.Collins, W. D. et al. The Community Climate System Model version 3 (CCSM3). J. Clim. 19, 2122–2143 (2006).ADS 
Article 

Google Scholar 
60.Berger, A. Long-term variations of daily insolation and quaternary climatic changes. J. Atmos. Sci. 35, 2362–2367 (1978).ADS 
Article 

Google Scholar 
61.Peltier, W. R. Global glacial isostasy and the surface of the ice-age earth: the ICE-5G (VM2) model and GRACE. Annu. Rev. Earth Planet. Sci. 32, 111–149 (2004).ADS 
CAS 
Article 

Google Scholar 
62.He, F. Simulating transient climate evolution of the last deglaciation with CCSM3. PhD thesis, University of Wisconsin-Madison (2011).63.Shakun, J. D. et al. Global warming preceded by increasing carbon dioxide concentrations during the last deglaciation. Nature 484, 49–54 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
64.He, F. et al. Northern hemisphere forcing of southern hemisphere climate during the last deglaciation. Nature 494, 81–85 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
65.Liu, Z. et al. Younger Dryas cooling and the Greenland climate response to CO2. Proc. Natl Acad. Sci. U.S.A. 109, 11101–11104 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
66.Liu, Z. et al. Evolution and forcing mechanisms of El Nino over the past 21,000 years. Nature 515, 550–553 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar 
67.Liu, Z. et al. The Holocene temperature conundrum. Proc. Natl Acad. Sci. U.S.A. 111, E3501–E3505 (2014).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
68.Otto-Bliesner, B. L. et al. Coherent changes of southeastern equatorial and northern African rainfall during the last deglaciation. Science 346, 1223–1227 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar  More

Altogether nine polished pieces of the lower Cenomanian Kachin amber from northern Myanmar (Figs. 1A–D, 2A–E) were examined in this study (depository: Russian Museum of Biodiversity Hotspots, N. Laverov Federal Center for Integrated Arctic Research of the Ural Branch of the Russian Academy of Sciences, Arkhangelsk, Russia). A brief description of each amber piece is given below.Figure 1Lower Cenomanian Kachin amber samples with specimens and borings of †Palaeolignopholas kachinensis gen. & sp. nov. from northern Myanmar used in this study. (A) RMBH biv1115 (frontal view with the holotype). (B) RMBH biv1101 (lateral view with two paratypes and a shell fragment). (C) RMBH biv1116 (frontal view with the fossilized paratype). (D) RMBH biv1100 (frontal view with borings). The red frames indicate position of the type specimens (holotype and some paratypes). The red arrows indicate bivalve borings. Scale bars = 5 mm. (Photos: Ilya V. Vikhrev).Full size imageFigure 2Lower Cenomanian Kachin amber samples with borings of †Palaeolignopholas kachinensis gen. & sp. nov. from northern Myanmar used in this study. (A) RMBH biv1102 (frontal view). (B) RMBH biv1103 (frontal view). (C) RMBH biv1114 (frontal view). (D) RMBH biv1118 (frontal view). (E) RMBH biv1117 (frontal view). The red arrows indicate bivalve borings. Scale bars = 5 mm. (Photos: Ilya V. Vikhrev).Full size imageRMBH biv1115: Size 8.5 × 5.8 × 8.1 mm (Fig. 1A). Inclusions: articulated shell of †Palaeolignopholas kachinensis gen. & sp. nov., “floating” in the resin (the holotype).RMBH biv1101: Size 15.6 × 6.4 × 11.5 mm (Fig. 1B). Inclusions: two complete articulated shells (paratypes) and a shell fragment of †Palaeolignopholas kachinensis gen. & sp. nov., “floating” in the resin.RMBH biv1116: Size 22.5 × 8.3 × 16.5 mm (Fig. 1C). Inclusions: fossilized shell of †Palaeolignopholas kachinensis gen. & sp. nov. (paratype), borings of this species (filled with fine gray sand), unidentified fly specimens (Insecta: Diptera), and unidentified organic fragments (probably, plant debris).RMBH biv1100: Size 17.5 × 4.9 × 12.0 mm (Fig. 1D). Inclusions: borings of †Palaeolignopholas kachinensis gen. & sp. nov. (filled with fine gray sand), and an unidentified caddisfly specimen (Insecta: Trichoptera).RMBH biv1102: Size 15.6 × 5.1 × 12.7 mm (Fig. 2A). Inclusions: borings of †Palaeolignopholas kachinensis gen. & sp. nov. (filled with fine gray sand), and unidentified organic fragments (probably, plant debris).RMBH biv1103: Size 19.6 × 4.7 × 14.3 mm (Fig. 2B). Inclusions: borings of †Palaeolignopholas kachinensis gen. & sp. nov. (filled with fine gray sand), an unidentified beetle specimen (Insecta: Coleoptera), and unidentified organic fragments (probably, plant debris).RMBH biv1114: Size 33.1 × 7.8 × 21.7 mm (Fig. 2C). Inclusions: multiple borings of †Palaeolignopholas kachinensis gen. & sp. nov. (filled with fine gray sand), and unidentified plant remains.RMBH biv1118: Size 25.1 × 8.4 × 14.3 mm (Fig. 2D). Inclusions: separate borings of †Palaeolignopholas kachinensis gen. & sp. nov. (filled with fine gray sand), a plant fragment with a cluster of borings around, and an unidentified insect specimen.RMBH biv1117: Size 15.5 × 3.9 × 10.7 mm (Fig. 2E). Inclusions: borings of †Palaeolignopholas kachinensis gen. & sp. nov. (filled with fine gray sand), and an unidentified insect specimen.Additionally, six amber samples containing adult and sub-adult specimens of †Palaeolignopholas kachinensis gen. & sp. nov. were examined using photographs in published works as follows: BMNH 20205 (Department of Palaeontology, Natural History Museum, London, UK)15, NIGP 169623 and NIGP 169624 (Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing, China)20, RS.P1450 (Ru D. A. Smith collection, Kuala Lumpur, Malaysia)19, and AMNH (Division of Invertebrates, American Museum of Natural History, New York, NY, United States of America)16.Based on morphological analyses of the fossil piddock shells, it was found to be a genus and species new to science, which is described here.Systematic paleontologyPhylum Mollusca Linnaeus, 1758Class Bivalvia Linnaeus, 1758Family Pholadidae Lamarck, 1809Subfamily Martesiinae Grant & Gale, 1931†Palaeolignopholas gen. novLSID: http://zoobank.org/urn:lsid:zoobank.org:act:1D686DCE-A5E9-41DA-9504-2EC58C93D988Type species: †Palaeolignopholas kachinensis gen. & sp. nov.Etymology. This name is derived from the prefix ‘Palaeo-’ (ancient), and ‘-lignopholas’, the name of a recent genus of estuarine and freshwater piddocks boring into wood, mudstone rocks, brickwork, laterites, etc.11,13. Masculine in gender.Diagnosis. The new monotypic genus is conchologically similar to several other piddock genera such as Lignopholas, Martesia, and Diplothyra Tryon 1862 but can be distinguished from these taxa by the following combination of characters: mesoplax relatively small, triangular, divided longitudinally, posterior slope without concentric sculpture, sculptured valve with concave parallel ridges (Martesia-like “rasping teeth”) curved anteriorly, periostracal lamellae dense, fine, hair-like. The fossil genus †Opertochasma Stephenson, 1952 shares a divided mesoplax but it clearly differs from both †Palaeolignopholas gen. nov. and Lignopholas by having two radial grooves on the shell surface21.Distribution. Kachin State, northern Myanmar; Upper Cretaceous (lower Cenomanian)15,19,22.Comments. Both †Palaeolignopholas gen. nov. and Lignopholas appear to be closely related to each other because they share a longitudinally divided mesoplax and periostracal lamellae, which are considered diagnostic features distinguishing this clade from Martesia + Diplothyra. Based on available conchological characters, we assume that †Palaeolignopholas gen. nov. might be placed on the ancestral stem lineage of the Lignopholas clade, although a possibility of homeomorphy could not entirely be excluded.†Palaeolignopholas kachinensis gen. & sp. nov = Plant Antheridia or Fungal Sporangia indet. sensu Grimaldi et al. (2002): 9, fig. 2a,b (bivalve specimens), fig. 3 (borings), fig. 5 (shell reconstruction of an immature specimen), figs. 6 and 7 (SEMs of borings surface showing rasped ornament at different magnifications)16. = Palaeoclavaria burmitis Poinar & Brown (2003): 765, figs. 1–4 (borings) [this fungal taxon was introduced using a trace fossil (boring) as the holotype]17; Poinar (2016): 2, figs. 10, 15, 16 (borings)18. = Martesiinae indet. sensu Smith & Ross (2018): 4, figs. 1a–c, 2a,b, 3a–d (borings), 4a,b, 5a–e (bivalve specimens)19. = Pholadidae indet. sensu Mao et al. (2018): 99, figs. 8a–f (borings), 8g,h (bivalve specimens)20. = Martesia sp. 2 sensu Mayoral et al. (2020): 10, figs. 4a (borings), 7b, 8a–l (bivalve specimens)15. = Pholadidae indet. sensu Balashov (2020): 623.Figures 1, 2, 3, 4, 5, 6 and 7.Figure 3Holotype and a paratype of †Palaeolignopholas kachinensis gen. & sp. nov. from lower Cenomanian Kachin amber, northern Myanmar. (A) Holotype: ventro-lateral view of articulated shell. (B) Paratype: anterio-lateral view of fossilized shell. VN ventral margin; DR dorsal margin; AN anterior margin; PS posterior margin; d disc; rs rasping surface of the valve; uvs umbonal ventral sulcus; pg pedal gape; pl periostracal lamellae. Scale bars = 500 µm. (Photos: Ilya V. Vikhrev).Full size imageFigure 4Paratypes of †Palaeolignopholas kachinensis gen. & sp. nov. from lower Cenomanian Kachin amber, northern Myanmar. (A) Paratype: dorsal view of articulated shell. Scale bar = 500 µm. (B) Paratype: dorsal view of articulated shell. The detached and deflected umbonal paired fragment of the valves is framed by red square. The blue contour indicates the lifetime position of this fragment. The blue arrows show the shell breakages. Scale bar = 200 µm. (C) Umbonal paired fragment of the holotype valves (inner view). The blue arrows show the shell breakage. Scale bar = 200 µm.  VN ventral margin; DR dorsal margin; AN anterior margin; PS posterior margin; ms longitudinally divided mesoplax (inner view); pr prora; d disc; rs rasping surface of the valve; uvs umbonal ventral sulcus; pg pedal gape; pl periostracal lamellae; sb shell breakage. (Photos: Ilya V. Vikhrev).Full size imageFigure 5Rasping surface of †Palaeolignopholas kachinensis gen. & sp. nov. shell. (A) Holotype shell. The red frame marks position of the enlarged area. (B) Undulated micro-sculpture of the rasping surface. Scale bar = 100 µm. (Photos: Ilya V. Vikhrev).Full size imageFigure 6Schematic reconstruction of †Palaeolignopholas kachinensis gen. & sp. nov. from lower Cenomanian Kachin amber, northern Myanmar based on the type series and other fossil material15,16,19,20. (A) Lateral view of adult specimen. (B) Dorsal view of adult specimen. (C) Ventral view of adult specimen (based on a paratype BMNH 2020515). (D) Anterio-ventral view of immature specimen. (E) Dorsal view of immature specimen. (F) Mesoplax of adult specimen. (G) Mesoplax of immature specimen. d disc; mt metaplax; ms mesoplax; hp hypoplax; ca callum; uvs umbonal ventral sulcus; pg pedal gape; pl periostracal lamellae. Scale bars = 1 mm (A–C). (Line graphics: Yulia E. Chapurina).Full size imageFigure 7Clavate borings of †Palaeolignopholas kachinensis gen. & sp. nov. from lower Cenomanian Kachin amber, northern Myanmar. (A) Cluster of borings. It marks drilling of immature piddocks into soft resin from the unidentified plant (wood?) fragment. (B–D) Clavate borings of adult piddocks. Scale bars = 1 mm. Abbreviation: bg a characteristic bioglyph indicating the shell rotation inside hardening resin. (Photos: Ilya V. Vikhrev).Full size imageLSID: http://zoobank.org/urn:lsid:zoobank.org:act:F6659EBF-B0A4-4B21-A99B-2C56BDB7EC9B.Common name. Kachin Amber Piddock.Holotype. RMBH biv1115, the adult shell with length 3.07 mm and width 1.13 mm “floating” in the resin (Figs. 1A, 3A, 5A,B), local collector leg., Russian Museum of Biodiversity Hotspots, N. Laverov Federal Center for Integrated Arctic Research of the Ural Branch of the Russian Academy of Sciences, Arkhangelsk, Russia.Paratypes. RMBH biv1116, the fossilized adult shell with length 4.05 mm and width 1.83 mm (Figs. 1C, 3B); RMBH biv1101, the immature specimen with articulated shell (width 1.86 mm) sharing a detached and deflected umbonal paired fragment of the valves due to the shell breakage (Figs. 1B, 4B,C); RMBH biv1101, the other immature specimen with shell length 2.68 mm and shell width 2.52 mm in this amber piece (Figs. 1B, 4A); BMNH 20205, adult specimen [illustrated in Mayoral et al. (2020): fig. 7B15], Department of Palaeontology, Natural History Museum, London, UK; NIGP 169623, adult specimen [illustrated in Mao et al. (2018): 100, fig. 8G20], and NIGP 169624, two adult specimens [illustrated in Mao et al. (2018): 100, fig. 8H20], Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing, China; RS.P1450, two sub-adult specimens [illustrated in Smith & Ross (2018): 5, fig. 4A,B19], Ru D. A. Smith collection, Kuala Lumpur, Malaysia.Type locality and strata. The Noije Bum Hill mines, Hukawng Valley, near Tanai (26.3593°N, 96.7200°E), Kachin State, northern Myanmar; Upper Cretaceous (lower Cenomanian; absolute age of youngest zircons in enclosing marine sediment: 98.79 ± 0.62 Ma)19,22.Etymology. The name of this species reflects its type locality, which is situated in the Kachin State of Myanmar.Diagnosis. As for the genus.Description. Shell small (up to 9.3 mm in length15,19,20), conical, with a rounded anterior margin, tapering posteriorly (Figs. 3A,B, 4A–C, 6A–E); its shape is similar to those in the recent Lignopholas, Martesia, and Diplothyra. Valve sculptured, with concave parallel ridges (Martesia-like “rasping teeth”) curved anteriorly (Fig. 5A,B). The ridges share a characteristic wave-like micro-sculpture (Fig. 5B). Sulcus deep (Figs. 3A, 4C, 6A–C). Mesoplax longitudinally divided, relatively small, triangular, tapering or lobed anteriorly (Fig. 3A, 6B,F), in immature specimens sometimes with lateral lobes (Figs. 4C, 6E,G). Metaplax and hypoplax long, narrow, not longitudinally divided but sometimes slightly bifurcated posteriorly (Fig. 6A–C). Periostracum densely covered by fine, hair-like lamellae (Figs. 4B,C and 6D). Umbonal reflection with large flattened ridge. Pedal gape presents in immature (Figs. 4A,B, 6D) and some adult specimens (Fig. 3A) but it is covered by callum in older specimens (Figs. 3B, 6C). Morphological details of the new species were also presented in a series of micro-CT images published Mayoral et al. (see Fig. 8 in that paper15) and in the reconstruction of Grimaldy et al. (see Fig. 5 in that work16).Figure 8Recent freshwater piddock Lignopholas fluminalis (Blanford, 1867) in the middle reaches of the Kaladan River, Rakhine State, Myanmar13. (A) Habitat of the freshwater piddock: river pool with siltstone rocks at the bottom, a possible modern analogue of the Mesozoic riverine ecosystem with †Palaeolignopholas. (B) Siltstone rock fragment with living freshwater piddocks inside their clavate borings. (C) Ethanol-preserved piddock (dorsal view). (D) Living piddock with fully developed callum (ventral view). (E) Living piddock with pedal gape (ventral view). Abbreviations: d disc; mt metaplax; ms mesoplax; ca callum; uvs umbonal ventral sulcus; pg pedal gape; pl periostracal lamellae. Scale bar = 2 mm. (Photos: Olga V. Aksenova).Full size imageBorings and corresponding ichnotaxon. The borings produced by †Palaeolignopholas kachinensis gen. & sp. nov. represent club-shaped (clavate) structures (Figs. 1C,D, 2A–E, 7A–D), sometimes with a characteristic bioglyph revealing the shell rotation in hardening resin (Fig. 7C). These borings were illustrated in detail15,16,17,19,20, and were considered belonging to Teredolites clavatus Leymerie, 184215. Initially, the trace fossils produced by the Kachin amber piddock were described as sporocarps of Palaeoclavaria burmitis Poinar & Brown, 2003, a non-gilled hymenomycete taxon17. The holotype of this taxon represents a club-shaped piddock crypt labelled as follows: “Amber from the Hukawng Valley in Burma; specimen (in piece B with accession number B-P-1) deposited in the Poinar amber collection maintained at Oregon State University (holotype)17”. Hence, Palaeoclavaria Poinar & Brown, 2003 and P. burmitis Poinar & Brown, 2003 must be considered ichnogenus and ichnospecies, respectively. New ichnotaxonomic synonymies are formally proposed here as follows: Teredolites Leymerie, 1842 (= Palaeoclavaria Poinar & Brown, 2003 syn. nov.), and Teredolites clavatus Leymerie, 1842 (= Palaeoclavaria burmitis Poinar & Brown, 2003 syn. nov.). More

1.Hurka, H. et al. The Eurasian steppe belt: Status quo, origin and evolutionary history. Turczaninowia 22, 5–71 (2019).
Google Scholar 
2.Walter, H. Die Vegetation Osteuropas (Gustav Fischer Verlag, 1974).
Google Scholar 
3.Walter, H. Die Vegetation der Erde in öko-physiologischer Betrachtung , Band II : Die gemäßigten und arktischen Zonen, in ökologischer Betrachtung (Gustav Fischer Verlag, 1968).
Google Scholar 
4.Cohen, K. M. & Gibbard, P. L. Global chronostratigraphical correlation table for the last 2.7 million years, version 2019 QI-500. Quat. Int. 500, 20–31 (2019).Article 

Google Scholar 
5.Frenzel, B. Grundzüge der Pleistozänen Vegetationsgeschichte Nord-Euroasiens. Geogr. J. 136, 291 (1968).
Google Scholar 
6.Tarasov, P. E. et al. Last glacial maximum biomes reconstructed from pollen and plant macrofossil data from northern Eurasia. J. Biogeogr. 27, 609–620 (2000).Article 

Google Scholar 
7.Caves Rugenstein, J., Sjostrom, D., Mix, H., Winnick, M. & Chamberlain, C. Aridification of Central Asia and uplift of the Altai and Hangay Mountains, Mongolia: Stable isotope evidence. Am. J. Sci. 314, 1171–1201 (2014).ADS 
Article 
CAS 

Google Scholar 
8.Yanina, T., Sorokin, V., Bezrodnykh, Y. & Romanyuk, B. Late Pleistocene climatic events reflected in the Caspian Sea geological history (based on drilling data). Quat. Int. 465, 130–141 (2018).Article 

Google Scholar 
9.Dolukhanov, P. M., Chepalyga, A. L., Shkatova, V. K. & Lavrentiev, N. V. Late Quaternary Caspian: Sea-levels, environments and human settlement. Open Geogr. J. 2, 1–15 (2009).Article 

Google Scholar 
10.Tudryn, A. et al. Late Quaternary Caspian Sea environment: Late Khazarian and Early Khvalynian transgressions from the lower reaches of the Volga River. Quat. Int. 292, 193–204 (2013).Article 

Google Scholar 
11.Dengler, J., Janišová, M., Török, P. & Wellstein, C. Biodiversity of Palaearctic grasslands: A synthesis. Agric. Ecosyst. Environ. 182, 1–14 (2014).Article 

Google Scholar 
12.Hejcman, M., Hejcmanová, P., Pavlů, V. & Beneš, J. Origin and history of grasslands in Central Europe—a review. Grass Forage Sci. 68, 345–363 (2013).Article 

Google Scholar 
13.Franzke, A. et al. Molecular signals for Late Tertiary/Early Quaternary range splits of an Eurasian steppe plant: Clausia aprica (Brassicaceae). Mol. Ecol. 13, 2789–2795 (2004).CAS 
PubMed 
Article 

Google Scholar 
14.Hurka, H., Friesen, N., German, D. A., Franzke, A. & Neuffer, B. ‘Missing link’ species Capsella orientalis and Capsella thracicaelucidate evolution of model plant genus Capsella (Brassicaceae). Mol. Ecol. 21, 1223–1238 (2012).PubMed 
Article 

Google Scholar 
15.Seregin, A. P., Anačkov, G. & Friesen, N. Molecular and morphological revision of the Allium saxatile group (Amaryllidaceae): Geographical isolation as the driving force of underestimated speciation. Bot. J. Linn. Soc. 178, 67–101 (2015).Article 

Google Scholar 
16.Friesen, N. et al. Dated phylogenies and historical biogeography of Dontostemon and Clausia (Brassicaceae) mirror the palaeogeographical history of the Eurasian steppe. J. Biogeogr. 43, 738–749 (2015).Article 

Google Scholar 
17.Friesen, N. et al. Allium species of section Rhizomatosa, early members of the Central Asian steppe vegetation. Flora 263, 151536 (2020).Article 

Google Scholar 
18.Friesen, N. et al. Evolutionary history of the Eurasian steppe plant Schivereckia podolica (Brassicaceae) and its close relatives. Flora 268, 151602 (2020).Article 

Google Scholar 
19.Volkova, P. A., Herden, T. & Friesen, N. Genetic variation in Goniolimon speciosum (Plumbaginaceae) reveals a complex history of steppe vegetation. Bot. J. Linn. Soc. 184, 113–121 (2017).
Google Scholar 
20.Žerdoner Čalasan, A., Seregin, A. P., Hurka, H., Hofford, N. P. & Neuffer, B. The Eurasian steppe belt in time and space: Phylogeny and historical biogeography of the false flax (Camelina Crantz, Camelineae, Brassicaceae). Flora 260, 151477 (2019).Article 

Google Scholar 
21.Kirschner, P. et al. Long-term isolation of European steppe outposts boosts the biome’s conservation value. Nat. Commun. 11, 1968 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
22.Heklau, H. & von Wehrden, H. Wood anatomy reflects the distribution of Krascheninnikovia ceratoides (Chenopodiaceae). Flora Morphol. Distrib. Funct. Ecol. Plants 206, 300–309 (2011).Article 

Google Scholar 
23.Heklau, H. & Röser, M. Delineation, taxonomy and phylogenetic relationships of the genus Krascheninnikovia (Amaranthaceae subtribe Axyridinae). Taxon 57, 563–576 (2008).
Google Scholar 
24.Takhtajan, A. Floristic Regions of the World (University of California Press, 1986).
Google Scholar 
25.Manafzadeh, S., Staedler, Y. M. & Conti, E. Visions of the past and dreams of the future in the Orient: The Irano-Turanian region from classical botany to evolutionary studies. Biol. Rev. Camb. Philos. Soc. 92, 1365–1388 (2017).PubMed 
Article 

Google Scholar 
26.Walter, H. & Breckle, S.-W. Ecological systems of the geobiosphere. 2 Tropical and subtropical zonobiomes (Springer, 1986). https://doi.org/10.1007/978-3-662-06812-0.
Google Scholar 
27.Hartmann, H. Zur Flora und Vegetation der Halbwüsten, Steppen und Rasengesellschaften im südöstlichen Ladakh (Indien). in Jahrbuch des Vereins zum Schutz der Bergwelt 129–188 (1997).28.Kraudzun, T., Vanselow, K. A. & Samimi, C. Realities and myths of the Teresken syndrome—An evaluation of the exploitation of dwarf shrub resources in the Eastern Pamirs of Tajikistan. J. Environ. Manag. 132, 49–59 (2014).Article 

Google Scholar 
29.Vanselow, K. & Samimi, C. Predictive mapping of dwarf shrub vegetation in an arid high mountain ecosystem using remote sensing and random forests. Remote Sens. 6, 6709–6726 (2014).ADS 
Article 

Google Scholar 
30.Smoliak, S. & Bezeau, L. M. Chemical composition and in vitro digestibility of range forage plants of the Stipa-Bouteloua prairie. Can. J. Plant Sci. 47, 161–167 (1967).CAS 
Article 

Google Scholar 
31.Waldron, B. L., Eun, J.-S., ZoBell, D. R. & Olson, K. C. Forage kochia (Kochia prostrata) for fall and winter grazing. Small Rumin. Res. 91, 47–55 (2010).Article 

Google Scholar 
32.Steshenko, A. P. Formation of the semi-shrub structure in the high mountains of Pamir. Trans Akad Nauk Tadzhik SSR 50, 2 (1956).
Google Scholar 
33.Zalenski, O. V. & Steshenko, A. P. On the special features of the main species of the vegetation of the Pamir mountains. Proc. Bot. Soc. 7, 9–12 (1957).
Google Scholar 
34.Barnes, M. The Effect of Plant Source Location on Restoration Success: A Reciprocal Transplant Experiment with Winterfat (Krascheninnikovia lanata) (University of New Mexico, 2009).
Google Scholar 
35.Seidl, A. et al. Phylogeny and biogeography of the Pleistocene Holarctic steppe and semi-desert goosefoot plant Krascheninnikovia ceratoides. Flora 262, 151504 (2020).Article 

Google Scholar 
36.Yang, J. Y., Fu, X. Q., Yan, G. X. & Zhang, S. Z. Analysis of three species of the genus Ceratoides. Grassl. China 1, 67–71 (1996).
Google Scholar 
37.Rubtsov, M., Sagimbaev, R., Shakhanov, E., Tiran, T. & Balyan, G. Natural polyploids of prostrate summer cypress and winterfat as initial material for breeding. Sov. Agric. Sci. 4, 20–24 (1989).
Google Scholar 
38.Yan, G., Zhang, S., Yan, J., Fu, X. & Wang, L. Chromosome numbers and geographical distribution of 68 species of forage plants. Grassl. China 4, 53–60 (1989).
Google Scholar 
39.Kurban, N. Karyotype analysis of three species of Ceratoides (Chenopodiaceae). J. Syst. Evol. 22, 466–468 (1984).
Google Scholar 
40.Zakharjeva, O. I. & Soskov, Y. D. Chromosome numbers in desert herbage plants. Bulleten VNII Rastenievod. Im. N.I. Vavilova 108, 57–60 (1981).
Google Scholar 
41.Domínguez, F. et al. Krascheninnikovia ceratoides (L.) Gueldenst (Chenopodiaceae) en Aragón (España): Algunos resultados para su conservación. Bol. R. Soc. Esp. Hist. Nat. (Sec. Biol.) 96, 15–26 (2001).
Google Scholar 
42.Zakirova, R. Chromosome numbers of some Alliaceae, Salicaceae, Polygonaceae, and Chenopodiaceae of the South Balkhash territory. Citologija 41, 1064 (1999).
Google Scholar 
43.Dobes, C. H., Hahn, B. & Morawetz, W. Chromosomenzahlen zur Gefässpflanzenflora Österreichs. Linzer Biol. Beitr 29, 5–43 (1997).
Google Scholar 
44.Sainz Ollero, H., Múgica, F. & Arias Torcal, J. Estrategias para la conservación de la flora amenazada de Aragón (Consejo de Protección de la Naturaleza de Aragón, 1996).
Google Scholar 
45.Lomonosova, M. N. & Krasnikov, A. A. Chromosome numbers in some members of the Chenopodiaceae. Bot. Zurn. (Moscow Leningrad) 78, 158–159 (1993).
Google Scholar 
46.Castroviejo, S. & Soriano, C. Krascheninnikovia ceratoides Gueldenst (Publicaciones del CSIC, 1990).
Google Scholar 
47.Takhtajan, A. Numeri chromosomatum magnoliophytorum florae URSS. Aceraceae–Menyanthaceae. (Academis Scientiarum Rossica, Institutum Botanicum nomine VL Komarovii;” Nauka”, 1990).48.Ghaffari, S. M., Balaei, Z., Chatrenoor, T. & Akhani, H. Cytology of SW Asian Chenopodiaceae: New data from Iran and a review of previous records and correlations with life forms and C4 photosynthesis. Plant Syst. Evol. 301, 501–521 (2014).Article 

Google Scholar 
49.eFloras. Published on the Internet http://www.efloras.org. (2008).50.Kadereit, G., Mavrodiev, E. V., Zacharias, E. H. & Sukhorukov, A. P. Molecular phylogeny of Atripliceae (Chenopodioideae, Chenopodiaceae): Implications for systematics, biogeography, flower and fruit evolution, and the origin of C4 photosynthesis. Am. J. Bot. 97, 1664–1687 (2010).PubMed 
Article 

Google Scholar 
51.Di Vincenzo, V. et al. Evolutionary diversification of the African achyranthoid clade (Amaranthaceae) in the context of sterile flower evolution and epizoochory. Ann. Bot. 122, 69–85 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
52.Janis, C. M. Tertiary mammal evolution in the context of changing climates, vegetation, and tectonic events. Annu. Rev. Ecol. Syst. 24, 467–500 (1993).Article 

Google Scholar 
53.Doležel, J. & Greilhuber, J. Nuclear genome size: Are we getting closer?. Cytom. Part A 77, 635–642 (2010).Article 
CAS 

Google Scholar 
54.Yokoya, K., Roberts, A. V., Mottley, J., Lewis, R. & Brandham, P. E. Nuclear DNA amounts in roses. Ann. Bot. 85, 557–561 (2000).CAS 
Article 

Google Scholar 
55.Poland, J. A., Brown, P. J., Sorrells, M. E. & Jannink, J.-L. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS ONE 7, e32253 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
56.Catchen, J., Hohenlohe, P. A., Bassham, S., Amores, A. & Cresko, W. A. Stacks: An analysis tool set for population genomics. Mol. Ecol. 22, 3124–3140 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
57.Weiß, C. L., Pais, M., Cano, L. M., Kamoun, S. & Burbano, H. A. nQuire: A statistical framework for ploidy estimation using next generation sequencing. BMC Bioinform. 19, 122 (2018).Article 
CAS 

Google Scholar 
58.Corrêa, A., dos Santos, R., Goldman, G. H. & Riaño-Pachón, D. M. ploidyNGS: Visually exploring ploidy with next generation sequencing data. Bioinformatics 33, 2575–2576 (2017).Article 
CAS 

Google Scholar 
59.Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
60.Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
61.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing (2013).62.Frichot, E. & François, O. LEA: An R package for landscape and ecological association studies. Methods Ecol. Evol. 6, 925–929 (2015).Article 

Google Scholar 
63.Jombart, T. adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).CAS 
PubMed 
Article 

Google Scholar 
64.Gruber, B., Unmack, P. J., Berry, O. F. & Georges, A. dartr: An R package to facilitate analysis of SNP data generated from reduced representation genome sequencing. Mol. Ecol. Resour. 18, 691–699 (2018).PubMed 
Article 

Google Scholar 
65.Bradley, M. raxml_ascbias. GitHub https://github.com/btmartin721/raxml_ascbias (2018).66.Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
67.Minh, B. Q. et al. IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
68.Lewis, P. O. A likelihood approach to estimating phylogeny from discrete morphological character data. Syst. Biol. 50, 913–925 (2001).CAS 
PubMed 
Article 

Google Scholar 
69.Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: Assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).CAS 
PubMed 
Article 

Google Scholar 
70.Minh, B. Q., Nguyen, M. A. T. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol. 30, 1188–1195 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
71.Huson, D. H. & Bryant, D. Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol. 23, 254–267 (2005).PubMed 
Article 
CAS 

Google Scholar 
72.Rambaut, A. FigTree v1.3.1. (2010).73.Kalinowski, S. T. hp-rare 1.0: A computer program for performing rarefaction on measures of allelic richness. Mol. Ecol. Notes 5, 187–189 (2005).CAS 
Article 

Google Scholar 
74.Brummitt, R. World geographical scheme for recording plant distributions. (2001).75.Britton, T., Anderson, C. L., Jacquet, D., Lundqvist, S. & Bremer, K. Estimating divergence times in large phylogenetic trees. Syst. Biol. 56, 741–752 (2007).PubMed 
Article 

Google Scholar 
76.Matzke, N. J. BioGeoBEARS: BioGeography with Bayesian (and likelihood) evolutionary analysis with R scripts. Version 1.1. 1, published on GitHub on 6 November 2018. (2018).77.Matzke, N. J. Model selection in historical biogeography reveals that founder-event speciation is a crucial process in island clades. Syst. Biol. 63, 951–970 (2014).PubMed 
Article 

Google Scholar 
78.Matzke, N. J. Probabilistic historical biogeography: New models for founder-event speciation, imperfect detection, and fossils allow improved accuracy and model-testing. Front. Biogeogr. 5, 2 (2013).Article 

Google Scholar 
79.Ronquist, F. Dispersal-vicariance analysis: A new approach to the quantification of historical biogeography. Syst. Biol. 46, 195–203 (1997).Article 

Google Scholar 
80.Strömberg, C. A. E. Evolution of grasses and grassland ecosystems. Annu. Rev. Earth Planet. Sci. 39, 517–544 (2011).ADS 
Article 
CAS 

Google Scholar 
81.Linder, H. P., Lehmann, C. E. R., Archibald, S., Osborne, C. P. & Richardson, D. M. Global grass (Poaceae) success underpinned by traits facilitating colonization, persistence and habitat transformation. Biol. Rev. 93, 1125–1144 (2017).PubMed 
Article 

Google Scholar 
82.Devyatkin, E. V. Meridional distribution of Pleistocene ecosystems in Asia: Basic problems. Stratigr. Geol. Correl. 1, 77–83 (1993).
Google Scholar 
83.Arkhipov, S. A. & Volkova, V. S. Geological history of Pleistocene landscapes and climate in West Siberia. (1994).84.Akhmetyev, M. A. et al. Chapter 8: Kazakhstan and Central Asia (plains and foothills). In Cenozoic Climatic and Environmental Changes in Russia (Geological Society of America, 2005). https://doi.org/10.1130/0-8137-2382-5.139.
Google Scholar 
85.Arkhipov, S. A. et al. Chapter 4: West Siberia. In Cenozoic Climatic and Environmental Changes in Russia (Geological Society of America, 2005). https://doi.org/10.1130/0-8137-2382-5.67.
Google Scholar 
86.Li, Q. Q. et al. Phylogeny and biogeography of Allium (Amaryllidaceae: Allieae) based on nuclear ribosomal internal transcribed spacer and chloroplast rps16 sequences, focusing on the inclusion of species endemic to China. Ann. Bot. 106, 709–733 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
87.Hais, M., Komprdová, K., Ermakov, N. & Chytrý, M. Modelling the last glacial maximum environments for a refugium of Pleistocene biota in the Russian Altai mountains Siberia. Palaeogeogr. Palaeoclimatol. Palaeoecol. 438, 135–145 (2015).Article 

Google Scholar 
88.Fedeneva, I. N. & Dergacheva, M. I. Paleosols as the basis of environmental reconstruction in Altai mountainous areas. Quat. Int. 106–107, 89–101 (2003).Article 

Google Scholar 
89.Braun-Blanquet, J. & Bolòs i Capdevila, O. de. Les groupements végétaux du bassin moyen de l’Ebre et leur dynamisme. An. la Estac. Exp. Aula Dei 5, 1–266 (1957).
Google Scholar 
90.Tutin, T., Webb, D., Heywood, V., Walters, S. & Moore, D. Flora Europaea (Cambridge University Press, 1993).
Google Scholar 
91.Heklau, H. Proposal to conserve the name Krascheninnikovia against Ceratoides (Chenopodiaceae. Taxon 55, 1044–1045 (2006).Article 

Google Scholar 
92.Davis, P. H. Flora of Turkey and the east Aegean islands (Edinburgh University Press, 1988).
Google Scholar 
93.Welsh, S., Atwood, N., Higgins, L. & Goodrich, S. A Utah Flora. Gt. Basin Nat. 9, 123 (1987).
Google Scholar 
94.Täckholm, V. Students’ Flora of Egypt (Cairo University Publishing, 1974).
Google Scholar 
95.Komarov, V. Flora of the U.R.S.S (Academiae Sciencitarum U.R.S.S, 1964).
Google Scholar 
96.Rechinger, K. Flora Iranica (Akademische Druck- und Verlagsanstalt, 1963).
Google Scholar 
97.Crawford, K. M. & Whitney, K. D. Population genetic diversity influences colonization success. Mol. Ecol. 19, 1253–1263 (2010).CAS 
PubMed 
Article 

Google Scholar 
98.Hilbig, W. Vegetation of Mongolia (SPB Academic Pubishing, 1995).
Google Scholar 
99.Briggs, J. C. Chapter 7 Neogene. In Global Biogeography Vol. 14 (ed. Briggs, J. C.) 147–189 (Elsevier, Amsterdam, 1995).
Google Scholar 
100.Yurtsev, B. A. The Pleistocene ‘Tundra-steppe’ and the productivity paradox: The landscape approach. Quat. Sci. Rev. 20, 165–174 (2001).ADS 
Article 

Google Scholar 
101.Stewart, J. R., Lister, A. M., Barnes, I. & Dalén, L. Refugia revisited: Individualistic responses of species in space and time. Proc. Biol. Sci. 277, 661–671 (2010).PubMed 

Google Scholar 
102.Varga, Z. Extra-Mediterranean refugia, post-glacial vegetation history and area dynamics in eastern Central Europe. Relict Species https://doi.org/10.1007/978-3-540-92160-8_3 (2009).Article 

Google Scholar 
103.Willis, K. J. & Vanandel, T. Trees or no trees? The environments of central and eastern Europe during the Last Glaciation. Quat. Sci. Rev. 23, 2369–2387 (2004).ADS 
Article 

Google Scholar 
104.Tremetsberger, K. et al. Pleistocene refugia and polytopic replacement of diploids by tetraploids in the Patagonian and Subantarctic plant Hypochaeris incana (Asteraceae, Cichorieae). Mol. Ecol. 18, 3668–3682 (2009).CAS 
PubMed 
Article 

Google Scholar  More

1.Tsukamoto, K., Nakai, I. & Tesch, W.-V. Do all freshwater eels migrate?. Nature 396, 635–636 (1998).ADS 
CAS 
Article 

Google Scholar 
2.Fromentin, J.-M. & Powers, J. E. Atlantic bluefin tuna: population dynamics, ecology, fisheries and management. Fish. Fish. 6, 281–306 (2005).Article 

Google Scholar 
3.Kerr, L. A. & Secor, D. H. Bioenergetic trajectories underlying partial migration in Patuxent River (Chesapeake Bay) white perch (Morone americana). Can. J. Fish. Aquat. Sci. 66, 602–612 (2009).Article 

Google Scholar 
4.Cadrin, S. X. et al. Population structure of beaked redfish, Sebastes mentella: evidence of divergence associated with different habitats. ICES J. Mar. Sci. 67, 1617–1630 (2010).Article 

Google Scholar 
5.Doak, D. F. et al. The statistical inevitability of stability-diversity relationships in community ecology. Am. Nat. 151, 264–276 (1998).CAS 
PubMed 
Article 

Google Scholar 
6.Tilman, D., Lehman, C. L. & Bristow, C. E. Diversity-stability relationships: statistical inevitability or ecological consequence?. Am. Nat. 151, 277–282 (1998).CAS 
PubMed 
Article 

Google Scholar 
7.Secor, D. H., Kerr, L. A. & Cadrin, S. X. Connectivity effects on productivity, stability, and persistence in a herring metapopulation model. ICES J. Mar. Sci. 66, 1726–1732 (2009).Article 

Google Scholar 
8.Cadrin, S. X. & Secor, D. H. Accounting for spatial population structure in stock assessment: past, present, and future. In The Future of Fisheries Science in North America (eds Beamish, R. J. & Rothschild, B. J.) 405–426 (Springer, 2009).
Google Scholar 
9.Secor, D. H. The unit stock concept: bounded fish and fisheries. In Stock Identification Methods: Applications in Fishery Science 2nd edn (eds Cadrin, S. X. et al.) 7–28 (Elsevier, 2014).
Google Scholar 
10.Ricker, W. E. Maximum sustained yields from fluctuating environments and mixed stocks. J. Fish. Res. Board Can. 15, 991–1006 (1958).Article 

Google Scholar 
11.Kerr, L. A. et al. Lessons learned from practical approaches to reconcile mismatches between biological population structure and stock units of marine fish. ICES J. Mar. Sci. 74, 1708–1722 (2017).Article 

Google Scholar 
12.Kerr, L. A., Cadrin, S. X. & Kovach, A. I. Consequences of a mismatch between biological and management units on our perception of Atlantic cod off New England. ICES J. Mar. Sci. 71, 1366–1381 (2014).Article 

Google Scholar 
13.Goethel, D. R. & Berger, A. M. Accounting for spatial complexities in the calculation of biological reference points: effects of misdiagnosing population structure for stock status indicators. Can. J. Fish. Aquat. Sci. 74, 1878–1894 (2017).Article 

Google Scholar 
14.Van Beveren, E., Duplisea, D. E., Brosset, P. & Castonguay, M. Assessment modelling approaches for stocks with spawning components, seasonal and spatial dynamics, and limited resources for data collection. PLoS ONE 14, e0222472 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
15.Cadrin, S. X. Defining spatial structure for fishery stock assessment. Fish. Res. 221, 105397 (2020).Article 

Google Scholar 
16.Sette, O. E. Biology of the Atlantic mackerel (Scomber scombrus) of North America. Part II:migration and habits. Fish. Bull. 51, 251–358 (1950).
Google Scholar 
17.Moores, J. A., Winters, G. H. & Parsons, L. S. Migrations and biological characteristics of Atlantic mackerel (Scomber scombrus) occurring in Newfoundland waters. J. Fish. Res. Board Can. 32, 1347–1357 (1975).Article 

Google Scholar 
18.Redding, S. G., Cooper, L. W., Castonguay, M., Wiernicki, C. & Secor, D. H. Northwest Atlantic mackerel population structure evaluated using otolith δ18O composition. ICES J. Mar. Sci. 77, 2582–2589 (2020).Article 

Google Scholar 
19.Overholtz, W. J., Link, J. S. & Suslowicz, L. E. Consumption of important pelagic fish and squid by predatory fish in the northeastern USA shelf ecosystem with some fishery comparisons. ICES J. Mar. Sci. 57, 1147–1159 (2000).Article 

Google Scholar 
20.Tyrrell, M. C., Link, J. S., Moustahfid, H. & Overholtz, W. J. Evaluating the effect of predation mortality on forage species population dynamics in the Northeast US continental shelf ecosystem using multispecies virtual population analysis. ICES J. Mar. Sci. 65, 1689–1700 (2008).Article 

Google Scholar 
21.Jansen, T. & Gislason, H. Population structure of Atlantic mackerel (Scomber scombrus). PLoS ONE 8, e64744 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
22.Nøttestad, L. et al. Quantifying changes in abundance, biomass, and spatial distribution of Northeast Atlantic mackerel (Scomber scombrus) in the Nordic seas from 2007 to 2014. ICES J. Mar. Sci. 73, 359–373 (2016).Article 

Google Scholar 
23.Olafsdottir, A. H. et al. Geographical expansion of Northeast Atlantic mackerel (Scomber scombrus) in the Nordic Seas from 2007 to 2016 was primarily driven by stock size and constrained by low temperatures. Deep-Sea. Res. Part II 159, 152–168 (2019).Article 

Google Scholar 
24.FAO. The state of world fisheries and aquaculture 2020. Sustainability in action. 244 http://www.fao.org/documents/card/en/c/ca9229en (2020). Accessed on 23 July 2020.25.NEFSC. 64th Northeast Regional Stock Assessment Workshop (64th SAW) Assessment Report. 536 (2018).26.DFO. Assessment of the Atlantic mackerel stock for the Northwest Atlantic (Subareas 3 and 4) in 2018. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2019/035: 14 (2019).27.Secor, D. H. Specifying divergent migrations in the concept of stock: the contingent hypothesis. Fish. Res. 43, 13–34 (1999).Article 

Google Scholar 
28.Sette, O. E. Biology of the Atlantic mackerel (Scomber scombrus) of North America. Part I: early life history, including the growth, drift, and mortality of the egg and larval populations. Fish. Bull. 50, 149–237 (1943).
Google Scholar 
29.Berrien, P. L. Eggs and larvae of Scomber scombrus and Scomber japonicus in continental shelf waters between Massachusetts and Florida. Fish. Bull. 76, 95–115 (1978).
Google Scholar 
30.Overholtz, W. J., Hare, J. A. & Keith, C. M. Impacts of interannual environmental forcing and climate change on the distribution of Atlantic mackerel on the U.S. Northeast continental shelf. Mar. Coast. Fish. 3, 219–232 (2011).Article 

Google Scholar 
31.McManus, M. C., Hare, J. A., Richardson, D. E. & Collie, J. S. Tracking shifts in Atlantic mackerel (Scomber scombrus) larval habitat suitability on the Northeast U.S. Continental Shelf. Fish. Oceanogr. 27, 49–62 (2018).Article 

Google Scholar 
32.Richardson, D. E., Carter, L., Curti, K. L., Marancik, K. E. & Castonguay, M. Changes in the spawning distribution and biomass of Atlantic mackerel (Scomber scombrus) in the western Atlantic Ocean over 4 decades. Fish. Bull. 118, 120–134 (2020).Article 

Google Scholar 
33.Moura, A. et al. Population structure and dynamics of the Atlantic mackerel (Scomber scombrus) in the North Atlantic inferred from otolith chemical and shape signatures. Fish. Res. 230, 105621 (2020).Article 

Google Scholar 
34.Rooker, J. et al. Evidence of trans-Atlantic movement and natal homing of bluefin tuna from stable isotopes in otoliths. Mar. Ecol. Prog. Ser. 368, 231–239 (2008).ADS 
Article 

Google Scholar 
35.Clarke, L. M., Munch, S. B., Thorrold, S. R. & Conover, D. O. High connectivity among locally adapted populations of a marine fish (Menidia menidia). Ecology 91, 3526–3537 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
36.Wells, R. J. D. et al. Natural tracers reveal population structure of albacore (Thunnus alalunga) in the eastern North Pacific. ICES J. Mar. Sci. 72, 2118–2127 (2015).Article 

Google Scholar 
37.Moreira, C. et al. Population structure of the blue jack mackerel (Trachurus picturatus) in the NE Atlantic inferred from otolith microchemistry. Fish. Res. 197, 113–122 (2018).Article 

Google Scholar 
38.Trueman, C. N., MacKenzie, K. M. & Palmer, M. R. Identifying migrations in marine fishes through stable-isotope analysis. J. Fish. Biol. 81, 826–847 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
39.McMahon, K. W., Hamady, L. L. & Thorrold, S. R. A review of ecogeochemistry approaches to estimating movements of marine animals. Limnol. Oceanogr. 58, 697–714 (2013).ADS 
CAS 
Article 

Google Scholar 
40.Kalish, J. M. 13C and 18O isotopic disequilibria in fish otoliths: metabolic and kinetic effects. Mar. Ecol. Prog. Ser. 75, 191–203 (1991).ADS 
Article 

Google Scholar 
41.Solomon, C. T. et al. Experimental determination of the sources of otolith carbon and associated isotopic fractionation. Can. J. Fish. Aquat. Sci. 63, 79–89 (2006).CAS 
Article 

Google Scholar 
42.Tohse, H. & Mugiya, Y. Sources of otolith carbonate: experimental determination of carbon incorporation rates from water and metabolic CO2, and their diel variations. Aquat. Biol. 1, 259–268 (2008).Article 

Google Scholar 
43.Chung, M.-T., Trueman, C. N., Godiksen, J. A., Holmstrup, M. E. & Grønkjær, P. Field metabolic rates of teleost fishes are recorded in otolith carbonate. Commun. Biol. 2, 24 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
44.Rooker, J. R. & Secor, D. H. Microchemistry: migration and ecology of Atlantic bluefin tuna. In The Future of Bluefin Tunas: Ecology, Fisheries Management, and Conservation (ed. Block, B. A.) (Johns Hopkins University Press, 2019).
Google Scholar 
45.Uriarte, A. et al. Spatial pattern of migration and recruitment of North East Atlantic mackerel. ICES CM 2001/O:17 (2001).46.Mendiola, D., Alvarez, P., Cotano, U. & Martínez de Murguía, A. Early development and growth of the laboratory reared north-east Atlantic mackerel (Scomber scombrus) L. J. Fish. Biol. 70, 911–933 (2007).Article 

Google Scholar 
47.Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

Google Scholar 
48.Harrison, X. A. et al. A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ 6, e4794 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
49.Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models (2020).50.Kerr, L. A. et al. Mixed stock origin of Atlantic bluefin tuna in the U.S. rod and reel fishery (Gulf of Maine) and implications for fisheries management. Fish. Res. 224, 105461 (2020).Article 

Google Scholar 
51.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
Google Scholar 
52.Smith, A. D. et al. Atlantic mackerel (Scomber scombrus L.) in NAFO Subareas 3 and 4 in 2018. DFO Can. Sci. Advis. Sec. Res. Doc. 2020/013. iv + 37 p. (2020).53.Lambrey de Souza, J., Sévigny, J.-M., Chanut, J.-P., Barry, W. F. & Grégoire, F. High genetic variability in the mtDNA control region of a Northwestern Atlantic teleost, Scomber scombrus L. Can. Tech. Rep. Fish. Aquat. Sci. 2625, vi+25 (2006).
Google Scholar 
54.Radlinski, M. K., Sundermeyer, M. A., Bisagni, J. J. & Cadrin, S. X. Spatial and temporal distribution of Atlantic mackerel (Scomber scombrus) along the northeast coast of the United States, 1985–1999. ICES J. Mar. Sci. 70, 1151–1161 (2013).Article 

Google Scholar 
55.Castonguay, M., Plourde, S., Robert, D., Runge, J. A. & Fortier, L. Copepod production drives recruitment in a marine fish. Can. J. Fish. Aquat. Sci. 65, 1528–1531 (2008).Article 

Google Scholar 
56.McManus, M. C. Atlantic Mackerel (Scomber scombrus) Population and Habitat Trends in the Northwest Atlantic (University of Rhode Island, 2017).
Google Scholar 
57.Schloesser, R. W., Rooker, J. R., Louchuoarn, P., Neilson, J. D. & Secord, D. H. Interdecadal variation in seawater δ13C and δ18O recorded in fish otoliths. Limnol. Oceanogr. 54, 1665–1668 (2009).ADS 
CAS 
Article 

Google Scholar 
58.Schloesser, R. W., Neilson, J. D., Secor, D. H. & Rooker, J. R. Natal origin of Atlantic bluefin tuna (Thunnus thynnus) from Canadian waters based on otolith δ13C and δ18O. Can. J. Fish. Aquat. Sci. 67, 563–569 (2010).CAS 
Article 

Google Scholar 
59.Thorrold, S. R., Campana, S. E., Jones, C. M. & Swart, P. K. Factors determining δ13C and δ18O fractionation in aragonitic otoliths of marine fish. Geochim. Cosmochim. Acta. 61, 2909–2919 (1997).ADS 
CAS 
Article 

Google Scholar 
60.Campana, S. E. Chemistry and composition of fish otoliths: pathways, mechanisms and applications. Mar. Ecol. Prog. Ser. 188, 263–297 (1999).ADS 
CAS 
Article 

Google Scholar 
61.Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G. & Saba, V. Observed fingerprint of a weakening Atlantic Ocean overturning circulation. Nature 556, 191–196 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
62.Saba, V. S. et al. Enhanced warming of the Northwest Atlantic Ocean under climate change. J. Geophys. Res. Oceans 121, 118–132 (2016).ADS 
Article 

Google Scholar 
63.Pershing, A. J. et al. Slow adaptation in the face of rapid warming leads to collapse of the Gulf of Maine cod fishery. Science 350, 809–812 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
64.Brickman, D., Hebert, D. & Wang, Z. Mechanism for the recent ocean warming events on the Scotian Shelf of eastern Canada. Cont. Shelf. Res. 156, 11–22 (2018).ADS 
Article 

Google Scholar 
65.Thorrold, S. R., Latkoczy, C., Swart, P. K. & Jones, C. M. Natal homing in a marine fish metapopulation. Science 291, 297–299 (2001).ADS 
CAS 
PubMed 
Article 

Google Scholar 
66.Gillanders, B. M. Using elemental chemistry of fish otoliths to determine connectivity between estuarine and coastal habitats. Estuar. Coast. Shelf. Sci. 64, 47–57 (2005).ADS 
Article 

Google Scholar 
67.Høie, H., Andersson, C., Folkvord, A. & Karlsen, Ø. Precision and accuracy of stable isotope signals in otoliths of pen-reared cod (Gadus morhua) when sampled with a high-resolution micromill. Mar. Biol. 144, 1039–1049 (2004).Article 

Google Scholar 
68.Martino, J. C., Doubleday, Z. A., Chung, M.-T. & Gillanders, B. M. Experimental support towards a metabolic proxy in fish using otolith carbon isotopes. J. Exp. Biol. 223, jeb217091 (2020).PubMed 
Article 

Google Scholar 
69.Manel, S., Gaggiotti, O. E. & Waples, R. S. Assignment methods: matching biological questions with appropriate techniques. Trends Ecol. Evol. 20, 136–142 (2005).PubMed 
Article 

Google Scholar 
70.Siskey, M. R., Wilberg, M. J., Allman, R. J., Barnett, B. K. & Secor, D. H. Forty years of fishing: changes in age structure and stock mixing in northwestern Atlantic bluefin tuna (Thunnus thynnus) associated with size-selective and long-term exploitation. ICES J. Mar. Sci. 73, 2518–2528 (2016).Article 

Google Scholar 
71.Kerr, L. A., Cadrin, S. X. & Secor, D. H. The role of spatial dynamics in the stability, resilience, and productivity of an estuarine fish population. Ecol. Appl. 20, 497–507 (2010).CAS 
PubMed 
Article 

Google Scholar 
72.Goethel, D. R., Quinn, T. J. & Cadrin, S. X. Incorporating spatial structure in stock assessment: movement modeling in marine fish population dynamics. Rev. Fish. Sci. 19, 119–136 (2011).Article 

Google Scholar 
73.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).
Google Scholar  More

1.Firth, L. B. et al. Ocean sprawl: Challenges and opportunities for biodiversity management in a changing world. Oceanogr. Mar. Biol. Annu. Rev. 54, 193–269 (2016).
Google Scholar 
2.Forman, R. T. T. et al. Road Ecology: Science and Solutions (Island Press, 2003).
Google Scholar 
3.Bishop, M. J. et al. Effects of ocean sprawl on ecological connectivity: Impacts and solutions. J. Exp. Mar. Biol. Ecol. 492, 7–30. https://doi.org/10.1016/j.jembe.2017.01.021 (2017).Article 

Google Scholar 
4.Sobocinski, K. L., Cordell, J. R. & Simenstad, C. A. Effects of shoreline modifications on supratidal macroinvertebrate fauna on Puget Sound, Washington beaches. Estuar. Coast 33, 699–711. https://doi.org/10.1007/s12237-009-9262-9 (2010).CAS 
Article 

Google Scholar 
5.Carlton, J. T. & Hodder, J. Maritime mammals: Terrestrial mammals as consumers in marine intertidal communities. Mar. Ecol. Prog. Ser. 256, 271–286. https://doi.org/10.3354/meps256271 (2003).ADS 
Article 

Google Scholar 
6.Levin, L. A. et al. The function of marine critical transition zones and the importance of sediment biodiversity. Ecosystems 4, 430–451. https://doi.org/10.1007/s10021-001-0021-4 (2001).CAS 
Article 

Google Scholar 
7.Lee, Y. Study on Changes in the Coastal Environment Due to Human Interference: A Case Study of Sand Beach Coast in Gangneung. Master’s Thesis. Korea National University of Education, Cheongju (2011).8.Son, S. et al. Analysis of Influential factors of roadkill occurrence—A case study of Seorak national park. J. Korean Inst. Landsc. Arch. 44, 1–12. https://doi.org/10.9715/KILA.2016.44.3.001 (2016).ADS 
Article 

Google Scholar 
9.Carr, L. W. & Fahrig, L. Effect of road traffic on two amphibian species of differing vagility. Conserv. Biol. 15, 1071–1078. https://doi.org/10.1046/j.1523-1739.2001.0150041071.x (2001).Article 

Google Scholar 
10.Coffin, A. W. From roadkill to road ecology: A review of the ecological effects of roads. J. Transp. Geogr. 15, 396–406. https://doi.org/10.1016/j.jtrangeo.2006.11.006 (2007).Article 

Google Scholar 
11.Zielin, S. B., Littlejohn, J., de Rivera, C. E., Smith, W. P. & Jacobson, S. L. Ecological investigations to select mitigation options to reduce vehicle-caused mortality of a threatened butterfly. J. Insect Conserv. 20, 845–854. https://doi.org/10.1007/s10841-016-9916-4 (2016).Article 

Google Scholar 
12.Bonnet, X., Naulleau, G. & Shine, R. The dangers of leaving home: Dispersal and mortality in snakes. Biol. Conserv. 89, 39–50. https://doi.org/10.1016/S0006-3207(98)00140-2 (1999).Article 

Google Scholar 
13.Fahrig, L., Pedlar, J. H., Pope, S. E., Taylor, P. D. & Wegner, J. F. Effect of road traffic on amphibian density. Biol. Conserv. 73, 177–182. https://doi.org/10.1016/0006-3207(94)00102-V (1995).Article 

Google Scholar 
14.Hobday, A. J. & Minstrell, M. L. Distribution and abundance of roadkill on Tasmanian highways: Human management options. Wildl. Res. 35, 712–726. https://doi.org/10.1080/15627020.2015.1021161 (2008).Article 

Google Scholar 
15.Finder, R. A., Roseberry, J. L. & Woolf, A. Site and landscape conditions at white-tailed deer/vehicle collision locations in Illinois. Landsc. Urban Plan. 44, 77–85. https://doi.org/10.1016/S0169-2046(99)00006-7 (1999).Article 

Google Scholar 
16.Glista, D. J., DeVault, T. L. & DeWoody, J. A. Vertebrate road mortality predominantly impacts amphibians. Herpetol. Conserv. Biol. 3, 77–87 (2008).
Google Scholar 
17.Grilo, C., Bissonette, J. A. & Cramer, P. C. Mitigation measures to reduce impacts on biodiversity. In Highways: Construction (ed. Jones, S. R.) 73–114 (Management and Maintenance. Nova Science Publishers, 2010).
Google Scholar 
18.Baine, M. et al. The development of management options for the black land crab (Gecarcinus ruricola) catchery in the San Andres Archipelago, Colombia. Ocean Coast Manage. 50, 564–589. https://doi.org/10.1016/j.ocecoaman.2007.02.007 (2007).Article 

Google Scholar 
19.Kantola, T., Tracy, J. L., Baum, K. A., Quinn, M. A. & Coulson, R. N. Spatial risk assessment of eastern monarch butterfly road mortality during autumn migration within the southern corridor. Biol. Conserv. 231, 150–160. https://doi.org/10.1016/j.biocon.2019.01.008 (2019).Article 

Google Scholar 
20.Koivula, M. J. & Vermeulen, H. J. W. Highways and forest fragmentation—Effects on carabid beetles (Coleoptera, Carabidae). Landsc. Ecol. 20, 911–926. https://doi.org/10.1007/s10980-005-7301-x (2005).Article 

Google Scholar 
21.Costa, L. L., Mothé, N. A. & Zalmon, I. R. Light pollution and ghost crab road-kill on coastal habitats. Reg. Stud. Mar. Sci. 39, 101457. https://doi.org/10.1016/j.rsma.2020.101457 (2020).Article 

Google Scholar 
22.Hübner, L., Pennings, S. C. & Zimmer, M. Sex- and habitat-specific movement of an omnivorous semi-terrestrial crab controls habitat connectivity and subsidies: A multi-parameter approach. Oecologia 178, 999–1015. https://doi.org/10.1007/s00442-015-3271-0 (2015).ADS 
Article 
PubMed 

Google Scholar 
23.Burggren, W. W. & McMahon, B. R. Biology of the Terrestrial Crabs (Cambridge University Press, 1988).
Google Scholar 
24.Micheli, F., Gherardi, F. & Vannini, M. Feeding and burrowing ecology of two East African mangrove crabs. Mar. Biol. 111, 247–254. https://doi.org/10.1007/BF01319706 (1991).Article 

Google Scholar 
25.Green, P. T., O’Dowd, D. J. & Lake, P. S. Recruitment dynamics in a rainforest seedling community: Context independent impact of a keystone consumer. Oecologia 156, 373–385. https://doi.org/10.1007/s00442-008-0992-3 (2008).ADS 
Article 
PubMed 

Google Scholar 
26.Suzuki, S. The life history of Sesarma haematocheirin the Miura peninsula. Res. Crust 11, 51–65. https://doi.org/10.18353/rcustacea.11.0_51 (1981).Article 

Google Scholar 
27.Adamczewska, A. M. & Morris, S. Ecology and behavior of Gecarcoideanatalis, the Christmas Island red crab, during the annual breeding migration. Biol. Bull. 200, 305–320. https://doi.org/10.2307/1543512 (2001).Article 

Google Scholar 
28.Le Galliard, J.-F., Fitze, P. S., Ferriere, R. & Clobert, J. Sex ratio bias, male aggression, and population collapse in lizards. Proc. Natl. Acad. Sci. 102, 18231–18236. https://doi.org/10.1073/pnas.0505172102 (2005).ADS 
CAS 
Article 
PubMed 

Google Scholar 
29.Caswell, H. Matrix Population Models: Construction, Analysis, and Interpretation (Sinauer Associates, 2001).
Google Scholar 
30.Aresco, M. J. The effect of sex-specific terrestrial movements and roads on the sex ratio of freshwater turtles. Biol. Conserv. 123, 37–44. https://doi.org/10.1016/j.biocon.2004.10.006 (2005).Article 

Google Scholar 
31.Mumme, R. L., Schoech, S. J., Woolfenden, G. E. & Fitzpatrick, J. W. Life and death in the fast lane: Demographic consequences of road mortality in the Florida scrub-jay. Conserv. Biol. 14, 501–512. https://doi.org/10.1046/j.1523-1739.2000.98370.x (2000).Article 

Google Scholar 
32.Kioko, J., Kiffner, C., Jenkins, N. & Collinson, W. J. Wildlife roadkill patterns on a major highway in northern Tanzania. Afr. Zool. 50, 17–22. https://doi.org/10.1080/15627020.2015.1021161 (2015).Article 

Google Scholar 
33.Seo, C., Thorne, J. H., Choi, T., Kwon, H. & Park, C. H. Disentangling roadkill: The influence of landscape and season on cumulative vertebrate mortality in South Korea. Landsc. Ecol. Eng. 11, 87–99. https://doi.org/10.1007/s11355-013-0239-2 (2015).Article 

Google Scholar 
34.Beebee, T. J. C. Effects of road mortality and mitigation measures on amphibian populations. Conserv. Biol. 27, 657–668. https://doi.org/10.1111/cobi.12063 (2013).Article 
PubMed 

Google Scholar 
35.Zhang, W. et al. Daytime driving decreases amphibian roadkill. PeerJ 6, e5385. https://doi.org/10.7717/peerj.5385 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
36.Saigusa, M. & Hidaka, T. Semilunar rhythm in the zoea-release activity of the terrestrial crabs Sesarma. Oecologia 37, 163–176. https://doi.org/10.1007/BF00344988 (1978).ADS 
Article 
PubMed 

Google Scholar 
37.Hartnoll, R. G. et al. Reproduction in the land crab Johngarthialagostoma on Ascension Island. J. Crust. Biol. 30, 83–92. https://doi.org/10.1651/09-3143.1 (2010).Article 

Google Scholar 
38.Schmidt, A. J., Bemvenutia, C. E. & Dieleet, K. Effects of geophysical cycles on the rhythm of mass mate searching of a harvested mangrove crab. Anim. Behav. 84, 333–340. https://doi.org/10.1016/j.anbehav.2012.04.023 (2012).Article 

Google Scholar 
39.Saigusa, M. Ecological distribution of three species of the genus Sesarma in winter season. Zool. Mag. 87, 142–150 (1978).
Google Scholar 
40.Saigusa, M. Adaptive significance of a semilunar rhythm in the terrestrial crab Sesarma. Biol. Bull. 160, 311–321. https://doi.org/10.2307/1540891 (1981).Article 

Google Scholar 
41.Saigusa, M., Terajima, M. & Yamamoto, M. Structure, formation, mechanical properties, and disposal of the embryo attachment system of an estuarine crab, Sesarma haematocheir. Biol. Bull. 203, 289–306. https://doi.org/10.2307/1543572 (2002).CAS 
Article 
PubMed 

Google Scholar 
42.Saigusa, M. Hatching of an estuarine crab, sesarma haematochier: Factors affecting the timing of hatching in detached embryos, and enhancement of hatching synchrony by the female. J. Oceanogr. 56, 93–102. https://doi.org/10.1023/A:1011118726283 (2000).Article 

Google Scholar 
43.Saigusa, M. Larval release rhythm coinciding with solar day and tidal cycles in the terrestrial crab Sesarma-harmony with the semilunar timing and its adaptive significance. Biol. Bull. 162, 371–386. https://doi.org/10.2307/1540990 (1982).Article 

Google Scholar 
44.Forward, R. B. Larval release rhythms of decapod crustaceans: An overview. Bull. Mar. Sci. 41, 165–176 (1987).
Google Scholar 
45.Hicks, J. W. The breeding behaviour and migrations of the terrestrial crab Gecarcoideanatalis (Decapoda: Brachyura). Aust. J. Zool. 33, 127–142. https://doi.org/10.1071/ZO9850127 (1985).Article 

Google Scholar 
46.Morgan, S. G. & Christy, J. H. Adaptive significance of the timing of larval release by crabs. Am. Nat. 145, 457–479. https://doi.org/10.1086/285749 (1995).Article 

Google Scholar 
47.Paula, J. Rhythms of larval release of decapod crustaceans in the Mira Estuary, Portugal. Mar. Biol. 100, 309–312. https://doi.org/10.1007/BF00391144 (1989).Article 

Google Scholar 
48.Bergin, M. E. Hatching rhythms in Ucapugilator (Decapoda: Brachyura). Mar. Biol. 63, 151–158. https://doi.org/10.1007/BF00406823 (1981).Article 

Google Scholar 
49.Christy, J. H. Adaptive significance of semilunar cycles of larval release in fiddler crabs (Genus Uca): Test of a hypothesis. Biol. Bull. 163, 251–263. https://doi.org/10.2307/1541264 (1982).Article 

Google Scholar 
50.Quintero-Angel, A., Osorio-Dominguez, D., Vargas-Salinas, F. & Saavedra-Rodriguez, C. A. Roadkill rate of snakes in a disturbed landscape of central Andes of Columbia. Herpetol. Notes 5, 99–105 (2012).
Google Scholar 
51.Orłowski, G. Roadside hedgerows and trees as factors increasing road mortality of birds: Implications for management of roadside vegetation in rural landscapes. Landsc. Urban Plan. 86, 153–161. https://doi.org/10.1016/j.landurbplan.2008.02.003 (2008).Article 

Google Scholar 
52.Saeki, M. & Macdonald, D. W. The effects of traffic on the raccoon dog (Nyctereutes procyonoides viverrinus) and other mammals in Japan. Biol. Conserv. 118, 559–571. https://doi.org/10.1016/j.biocon.2003.10.004 (2004).Article 

Google Scholar 
53.Costa, L. L., Secco, H., Arueira, V. F. & Zalmon, I. R. Mortality of the Atlantic ghost crab Ocypode quadrata (Fabricius, 1787) due to vehicle traffic on sandy beaches: A road ecology approach. J. Environ. Manage. 260, 110168. https://doi.org/10.1016/j.jenvman.2020.110168 (2020).Article 
PubMed 

Google Scholar 
54.Tsai, J. R., Hsieh, Y. T., Lin & H. C. The effect of dike types on terrestrial crab passage through the access road: The predicament of terrestrial crab conservation in Gaomei Wetland. In Proceedings of the 39th Oceans Engineering Conference in Taiwan Hungkuang University, November (2017)55.Bellis, M. A., Jackson, S. D., Griffin, C. R., Warren, P. S. & Thompson, A. O. Utilizing a multi-technique, multi-taxa approach to monitoring wildlife passageways in southern Vermont. Oecol. Aust. 17, 111–128. https://doi.org/10.4257/oeco.2013.1701.10 (2007).Article 

Google Scholar 
56.Song, J. et al. Roadkill of amphibians in the Korea national park. Korean J. Environ. Ecol. 23, 187–193 (2009).
Google Scholar 
57.Ryu, M. & Kim, J. G. Influence of roadkill during breeding migration on the sex ratio of land crab (Sesarma haematoche). J. Environ. Ecol. 44, 23. https://doi.org/10.1186/s41610-020-00167-6 (2020).Article 

Google Scholar 
58.Mizuta, T. Moonlight-related mortality: Lunar conditions and roadkill occurrence in the Amami woodcock Scolopax mira. Wilson J. Ornithol. 126, 544–552. https://doi.org/10.1676/13-159.1 (2014).Article 

Google Scholar 
59.Gibbs, J. P. & Steen, D. A. Trends in sex ratios of turtles in the United States: Implications of road mortality. Conserv. Biol. 19, 552–556. https://doi.org/10.1111/j.1523-1739.2005.000155.x (2005).Article 

Google Scholar 
60.Rytwinski, T. & Fahrig, L. Do species life history traits explain population responses to roads? A meta-analysis. Biol. Conserv. 147, 87–98. https://doi.org/10.1016/j.biocon.2011.11.023 (2012).Article 

Google Scholar 
61.Korea Astronomy and Space Science Institute. Korean Astronomical Almanac (Korea Astronomy and Space Science Institute, 2017).
Google Scholar  More

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1.Holzner, W. Concepts, categories and characteristics of weeds. Biol. Ecol. Weeds https://doi.org/10.1007/978-94-017-0916-3_1 (1982).Article 

Google Scholar 
2.Randall, J. M. Weed control for the preservation of biological diversity. Weed Technol. 10, 370–383 (1996).Article 

Google Scholar 
3.Atkinson, I. A. E. Problem Weeds on New Zealand Islands. (Dept. of Conservation, 1997).4.Goslee, S. C., Peters, D. P. C. & Beck, K. G. Modeling invasive weeds in grasslands: the role of allelopathy in Acroptilon repens invasion. Ecological Modelling (2001). https://www.sciencedirect.com/science/article/pii/S0304380001002319. Accessed 2 Oct 2020.5.Dawson, W., Burslem, D. F. R. P. & Hulme, P. E. Factors explaining alien plant invasion success in a tropical ecosystem differ at each stage of invasion. J. Ecol. 97, 657–665 (2009).Article 

Google Scholar 
6.Baker, H. G. The evolution of weeds, annual review of ecology, evolution, and systematics. DeepDyve (1974). https://www.deepdyve.com/lp/annual-reviews/the-evolution-of-weeds-YxSFG7LI8J. Accessed 2 Oct 2020.7.Perrins, J., Williamson, M. & Fitter, A. A survey of differing views of weed classification: Implications for regulation of introductions. Biol. Conserv. 60, 47–56 (1992).Article 

Google Scholar 
8.Mack, R. N. Predicting the identity and fate of plant invaders: Emergent and emerging approaches. Biol. Conserv. 78, 107–121 (1996).Article 

Google Scholar 
9.Sutherland, S. What Makes a Weed a Weed: Life History Traits of Native (2004). https://www.jstor.org/stable/pdf/40005745.pdf. Accessed 2 Oct 2020.10.Leather, G. R. Weed control using allelopathic crop plants. J. Chem. Ecol. 9, 983–989 (1983).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
11.Mersie, W. & Singh, M. Allelopathic effect of parthenium (Parthenium hysterophorus L.) extract and residue on some agronomic crops and weeds. J. Chem. Ecol. 13, 1739–1747 (1987).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
12.Derya, E., yildiz, O. & Nelson, E. T. (PDF) Ecology, Competitive Advantages, and Integrated (2006). https://www.researchgate.net/publication/287491753_Ecology_Competitive_Advantages_and_Integrated_Control_of_Rhododendron_An_Old_Ornamental_yet_Emerging_Invasive_Weed_Around_the_Globe. Accessed 2 Oct 2020.13.Clements, D. R. & Ditommaso, A. Climate change and weed adaptation: Can evolution of invasive plants lead to greater range expansion than forecasted?. Weed Res. 51, 227–240 (2011).Article 

Google Scholar 
14.Sebasky, M. E., Keller, S. R. & Taylor, D. R. Investigating past range dynamics for a weed of cultivation, Silene vulgaris. Ecol. Evol. 6, 4800–4811 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
15.Hodgins, K. Unearthing the impact of human disturbance on a notorious weed. Mol. Ecol. 23, 2141–2143 (2014).PubMed 
Article 
PubMed Central 

Google Scholar 
16.Hobbs, R. J. & Huenneke, L. F. Disturbance, diversity, and invasion: Implications for conservation. Ecosyst. Manag. https://doi.org/10.1007/978-1-4612-4018-1_16 (1992).Article 

Google Scholar 
17.Lozon, J. D. & Macisaac, H. J. Biological invasions: Are they dependent on disturbance?. Environ. Rev. 5, 131–144 (1997).Article 

Google Scholar 
18.Ditomaso, J. M. Invasive weeds in rangelands: Species, impacts, and management. Weed Sci. 48, 255–265 (2000).CAS 
Article 

Google Scholar 
19.Larson, D. L., Anderson, P. J. & Newton, W. Alien plant invasion in mixed-grass prairie: Effects of vegetation type and anthropogenic disturbance. Ecol. Appl. 11, 128–141 (2001).Article 

Google Scholar 
20.Chiuffo, M. C., Cock, M. C., Prina, A. O. & Hierro, J. L. Response of native and non-native ruderals to natural and human disturbance. Biol. Invasions 20, 2915–2925 (2018).Article 

Google Scholar 
21.Kariyat, R. R., Scanlon, S. R., Mescher, M. C., De Moraes, C. M. & Stephenson, A. G. Inbreeding depression in Solanum carolinense (Solanaceae) under field conditions and implications for mating system evolution. PLoS ONE (2011). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3236180/. Accessed 2 Oct 2020.22.Li, B., Shibuya, T., Yogo, Y. & Hara, T. Effects of ramet clipping and nutrient availability on growth and biomass allocation of yellow nutsedge. Ecol. Res. 19, 603–612 (2004).Article 

Google Scholar 
23.Jia, X., Pan, X. Y., Li, B., Chen, J. K. & Yang, X. Z. Allometric growth, disturbance regime, and dilemmas of controlling invasive plants: A model analysis. Biol. Invasions 11, 743–752 (2008).Article 

Google Scholar 
24.Ramula, S. Annual mowing has the potential to reduce the invasion of herbaceous Lupinus polyphyllus. Biol. Invasions 22, 3163–3173 (2020).Article 

Google Scholar 
25.Liu, X. & Huang, B. Mowing effects on root production, growth, and mortality of creeping bentgrass. Crop Sci. 42, 1241–1250 (2002).Article 

Google Scholar 
26.Biazzo, J. & Milbrath, L. R. Response of pale swallowwort (Vincetoxicum rossicum) to multiple years of mowing. Invasive Plant Sci. Manag. 12, 169–175 (2019).Article 

Google Scholar 
27.Yong, X.-H. et al. Maternal Mowing Effect on Seed Traits of an Invasive Weed, Erigeron annus in farmland. Sains Malay. 44, 347–354 (2015).Article 

Google Scholar 
28.Mithöfer, A., Wanner, G. & Boland, W. Effects of feeding spodoptera littoralis on lima bean leaves. II. Continuous mechanical wounding resembling insect feeding is sufficient to elicit herbivory-related volatile emission. Plant Physiol. 137, 1160–1168 (2005).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
29.Engelberth, J. & Engelberth, M. The Costs of Green Leaf Volatile-Induced Defense Priming: Temporal Diversity in Growth Responses to Mechanical Wounding and Insect Herbivory. Plants 8, 23 (2019).CAS 
PubMed Central 
Article 

Google Scholar 
30.Erfmeier, A. & Bruelheide, H. Invasive and nativeRhododendron ponticumpopulations: Is there evidence for genotypic differences in germination and growth?. Ecography 28, 417–428 (2005).Article 

Google Scholar 
31.Milbau, A., Nijs, I., Van Peer, L., Reheul, D. & De Cauwer, B. Disentangling invasiveness and invasibility during invasion in synthesized grassland communities. New Phytol. 159, 657–667 (2003).Article 

Google Scholar 
32.Etten, M. L. V., Conner, J. K., Chang, S.-M. & Baucom, R. S. Not all weeds are created equal: A database approach uncovers differences in the sexual system of native and introduced weeds. Ecol. Evol. 7, 2636–2642 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
33.Baker, H. G. Self-compatibility and establishment after “long-distance” dispersal. Evolution 9, 347 (1955).
Google Scholar 
34.Tabassum, S. & Leishman, M. R. It doesn’t take two to tango: Increased capacity for self-fertilization towards range edges of two coastal invasive plant species in eastern Australia. Biol. Invasions 21, 2489–2501 (2019).Article 

Google Scholar 
35.Pannell, J. R. & Barrett, S. C. H. Baker’s law revisited: reproductive assurance in a metapopulation. Evolution 52, 657–668 (1998).PubMed 
Article 
PubMed Central 

Google Scholar 
36.Pannell, J. R. Evolution of the mating system in colonizing plants. Mol. Ecol. 24, 2018–2037 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
37.Mena-Ali, J. I., Keser, L. H. & Stephenson, A. G. Inbreeding depression in Solanum carolinense (Solanaceae), a species with a plastic self-incompatibility response. BMC Evol. Biol. 8, 10 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
38.Chauhan, B. S., Migo, T., Westerman, P. R. & Johnson, D. E. Post-dispersal predation of weed seeds in rice fields. Weed Res. 50, 553–560 (2010).Article 

Google Scholar 
39.Muniappan, R. & Viraktamath, C. A. Invasive alien weeds in the Western Ghats. Curr. Sci. 64, 555–558 (1993).
Google Scholar 
40.Ziller S. R. A Estepe Gramineo-Lenhosa no Segundo Plan-alto do Paraná: Diagnóstico Ambiental com Enfoque à Contami-nacão Biológica (PhD Thesis). Universidade Federal doParaná (2000).41.Javaid, A. & Riaz, T. Parthenium hysterophorus L., an alien invasive weed threatening natural vegetations in Punjab, Pakistan. Pak. J. Bot. 44, 123–126 (2012).
Google Scholar 
42.Alves, M. T. & Hilker, F. M. Hunting cooperation and Allee effects in predators. J. Theor. Biol. 419, 13–22 (2017).MathSciNet 
MATH 
Article 

Google Scholar 
43.Kariyat, R. R., Mauck, K. E., Moraes, C. M. D., Stephenson, A. G. & Mescher, M. C. Inbreeding alters volatile signalling phenotypes and influences tri-trophic interactions in horsenettle (Solanum carolinense L..). Ecol. Lett. 15, 301–309 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
44.Nihranz, C. T. et al. Herbivory and inbreeding affect growth, reproduction, and resistance in the rhizomatous offshoots of Solanum carolinense (Solanaceae). Evol. Ecol. 33, 499–520 (2019).Article 

Google Scholar 
45.Nihranz, C. T. et al. Transgenerational impacts of herbivory and inbreeding on reproductive output in Solanum carolinense. Am. J. Bot. 107, 286–297 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
46.Wilkens, R. T., Shea, G. O., Halbreich, S. & Stamp, N. E. Resource availability and the trichome defenses of tomato plants. Oecologia 106, 181–191 (1996).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
47.Zaynab, M. et al. Role of secondary metabolites in plant defense against pathogens. Microb. Pathog. 124, 198–202 (2018).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Neilson, E. H., Goodger, J. Q., Woodrow, I. E. & Møller, B. L. Plant chemical defense: at what cost?. Trends Plant Sci. 18, 250–258 (2013).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
49.Boyd, J. W., Murray, D. S. & Tyrl, R. J. Silverleaf nightshade, Solarium elaeagnifolium, origin, distribution, and relation to man. Econ. Bot. 38, 210–217 (1984).Article 

Google Scholar 
50.EPPO Global Database. Solanum elaeagnifolium (SOLEL)[Documents]| EPPO Global Database. https://gd.eppo.int/taxon/SOLEL/documents. Accessed 5th Nov 2020.51.Travlos, I. S. Responses of invasive silverleaf nightshade (Solanum elaeagnifolium) populations to varying soil water availability. Phytoparasitica 41, 41–48 (2012).Article 

Google Scholar 
52.Mekki, M. Biology, distribution and impacts of silverleaf nightshade (Solanum elaeagnifolium Cav.). EPPO Bull. 37, 114–118 (2007).Article 

Google Scholar 
53.Cuthbertson, E.G. Morphology of the underground parts of silverleaf nightshade. 5th Australian Weeds Conference (1976).54.Heap, J., Honan, I. & Smith, E. Silverleaf nigthshade: A Technical Handbook for Animal and Plant Control Boards in South Australia (Adelaide, 1997).
Google Scholar 
55.Petanidou, T. et al. Self-compatibility and plant invasiveness: Comparing species in native and invasive ranges. Perspect. Plant Ecol. Evol. Syst. 14, 3–12 (2012).Article 

Google Scholar 
56.Kariyat, R. R. & Chavana, J. Field data on plant growth and insect damage on the noxious weed Solanum eleaegnifolium in an unexplored native range. Data Brief 19, 2348–2351 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
57.Centibas, M. & Koyuncu, F. The ripening and fruit quality of ‘Monroe’ peaches in response to pre-harvest application gibberellic acid. Akdeniz Üniv. Ziraat Fakült. Dergisi 26, 73–80 (2013).
Google Scholar 
58.Pornaro, C., Macolino, S., Menegon, A. & Richardson, M. WinRHIZO technology for measuring morphological traits of Bermudagrass Stolons. Agron. J. 109, 3007–3010 (2017).CAS 
Article 

Google Scholar 
59.Kariyat, R. R. et al. Inbreeding, herbivory, and the transcriptome of Solanum carolinense. Entomol. Exp. Appl. 144, 134–144 (2012).Article 

Google Scholar 
60.Kariyat, R. R. et al. Feeding on glandular and non-glandular leaf trichomes negatively affect growth and development in tobacco hornworm (Manduca sexta) caterpillars. Arthropod Plant Interact. 13, 321–333 (2019).Article 

Google Scholar 
61.Tayal, M., Chavana, J. & Kariyat, R. R. Efficiency of using electric toothbrush as an alternative to a tuning fork for artificial buzz pollination is independent of instrument buzzing frequency. BMC Ecol. 20, 1 (2020).Article 

Google Scholar 
62.Singh, S. & Kariyat, R. R. Exposure to polyphenol-rich purple corn pericarp extract restricts fall armyworm (Spodoptera frugiperda) growth. Plant Signal. Behav. 15, 1784545 (2020).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
63.Kariyat, R. R. et al. Constitutive and herbivore-induced structural defenses are compromised by inbreeding in Solanum carolinense (Solanaceae). Am. J. Bot. 100, 1014–1021 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
64.Paez-Garcia, A. et al. Root traits and phenotyping strategies for plant improvement. Plants 4, 334–355 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
65.Pinke, G., Pál, R. & Botta-Dukát, Z. Effects of environmental factors on weed species composition of cereal and stubble fields in western Hungary. Open Life Sci. 5, 283–292 (2010).Article 

Google Scholar 
66.Tremayne, M. A. & Richards, A. J. Seed weight and seed number affect subsequent fitness in outcrossing and selfing Primula species. New Phytol. 148, 127–142 (2000).Article 

Google Scholar 
67.Ramesh, K., Matloob, A., Aslam, F., Florentine, S. K. & Chauhan, B. S. Weeds in a changing climate: Vulnerabilities, consequences, and implications for future weed management. Front. Plant Sci. 8, 1 (2017).CAS 
Article 

Google Scholar 
68.Rha, E. S. & Jamil, M. Gibberellic acid (GA3) enhance seed water uptake, germination and early seedling growth in sugar beet under salt stress. Pak. J. Biol. Sci. 10, 654–658 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
69.Stoller, E. W. & Wax, L. M. Periodicity of germination and emergence of some annual weeds. Weed Sci. 21, 574–580 (1973).Article 

Google Scholar 
70.Meyer, S. E. & Pendleton, B. K. Factors affecting seed germination and seedling establishment of a long-lived desert shrub (Coleogyne ramosissima: Rosaceae). Plant Ecol. 178, 171–187 (2005).Article 

Google Scholar 
71.Milbau, A., Scheerlinck, L., Reheul, D., De Cauwer, B. & Nijs, I. Ecophysiological and morphological parameters related to survival in grass species exposed to an extreme climatic event. Physiol. Plant. 125, 500–512 (2005).CAS 
Article 

Google Scholar 
72.Gioria, M. & Pyšek, P. Early bird catches the worm: Germination as a critical step in plant invasion. Biol. Invasions 19, 1055–1080 (2016).Article 

Google Scholar 
73.Mahmood, A. H. et al. Influence of various environmental factors on seed germination and seedling emergence of a noxious environmental weed: Green galenia (Galenia pubescens). Weed Sci. 64, 486–494 (2016).Article 

Google Scholar 
74.Mcnaughton, S. J. Grazing lawns: On domesticated and wild grazers. Am. Nat. 128, 937–939 (1986).Article 

Google Scholar 
75.McNaughton, S. J. Adaptation of herbivores to seasonal changes in nutrient supply. Nutr. Herb. 1, 391–408 (1987).
Google Scholar 
76.Laliberté, E., Lambers, H., Burgess, T. I. & Wright, S. J. Phosphorus limitation, soil-borne pathogens and the coexistence of plant species in hyperdiverse forests and shrublands. New Phytol. 206, 507–521 (2014).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
77.Kramer-Walter, K. R. et al. Root traits are multidimensional: Specific root length is independent from root tissue density and the plant economic spectrum. J. Ecol. 104, 1299–1310 (2016).Article 

Google Scholar 
78.Losapio, G. et al. An invasive plant species enhances biodiversity in overgrazed pastures but inhibits its recovery in protected areas. J. Ecol. https://doi.org/10.1101/2020.08.16.227066 (2020).Article 

Google Scholar 
79.Onen, H., Farooq, S., Gunal, H., Ozaslan, C. & Erdem, H. Higher tolerance to abiotic stresses and soil types may accelerate common ragweed (Ambrosia artemisiifolia) invasion. Weed Sci. 65, 115–127 (2016).Article 

Google Scholar 
80.Wittstock, U. & Gershenzon, J. Constitutive plant toxins and their role in defense against herbivores and pathogens. Curr. Opin. Plant Biol. 5, 300–307 (2002).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
81.Mooney, E. H., Tiedeken, E. J., Muth, N. Z. & Niesenbaum, R. A. Differential induced response to generalist and specialist herbivores by Lindera benzoin (Lauraceae) in sun and shade. Oikos 118, 1181–1189 (2009).Article 

Google Scholar 
82.Baldwin, I. T. Plant volatiles. Curr. Biol. 20, 392–397 (2011).Article 
CAS 

Google Scholar 
83.Coley, P. D., Bryant, J. P. & Chapin, F. S. Resource availability and plant antiherbivore defense. Science 230, 895–899 (1985).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
84.Fine, P. V. A. Herbivores promote habitat specialization by trees in amazonian forests. Science 305, 663–665 (2004).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
85.Zandt, P. A. V. Plant defense, growth, and habitat: A comparative assessment of constitutive and induced resistance. Ecology 88, 1984–1993 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
86.Salminen, S. O. & Grewal, P. S. Does decreased mowing frequency enhance alkaloid production in endophytic tall fescue and perennial ryegrass?. J. Chem. Ecol. 28, 939–950 (2002).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
87.Freeman. An Overview of Plant Defenses against Pathogens and Herbivores. The Plant Health Instructor (2008). https://doi.org/10.1094/phi-i-2008-0226-01.88.Davis, H. N. et al. Review of Major Crop and Animal Arthropod Pests of South Texas. Subtropical Agriculture and Environments (2020).89.Traw, M. B., Kim, J., Enright, S., Cipollini, D. F. & Bergelson, J. Negative cross-talk between salicylate- and jasmonate-mediated pathways in the Wassilewskija ecotype of Arabidopsis thaliana. Mol. Ecol. 12, 1125–1135 (2003).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
90.Bostock, R. M. Signal crosstalk and induced resistance: Straddling the line between cost and benefit. Annu. Rev. Phytopathol. 43, 545–580 (2005).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
91.Lefoe, G. et al. Assessing the fundamental host-range of Leptinotarsa texana Schaeffer as an essential precursor to biological control risk analysis. Biol. Control 143, 104165 (2020).CAS 
Article 

Google Scholar 
92.Chung, S. H. & Felton, G. W. Specificity of induced resistance in tomato against specialist lepidopteran and coleopteran species. J. Chem. Ecol. 37, 378–386 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
93.Korpita, T., Gómez, S. & Orians, C. M. Cues from a specialist herbivore increase tolerance to defoliation in tomato. Funct. Ecol. 28, 395–401 (2013).Article 

Google Scholar 
94.Yang, Q. et al. Plant–soil biota interactions of an invasive species in its native and introduced ranges: Implications for invasion success. Soil Biol. Biochem. 65, 78–85 (2013).CAS 
Article 

Google Scholar 
95.Blair, A. C. & Wolfe, L. M. The evolution of an invasive plant: An experimental study with Silene latifolia. Ecology 85, 3035–3042 (2004).Article 

Google Scholar 
96.Kariyat, R. R., Smith, J. D., Stephenson, A. G., Moraes, C. M. D. & Mescher, M. C. Non-glandular trichomes of Solanum carolinense deter feeding by Manduca sexta caterpillars and cause damage to the gut peritrophic matrix. Proc. R. Soc. B 284, 20162323 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
97.Kariyat, R. R. et al. Leaf trichomes affect caterpillar feeding in an instar-specific manner. Commun. Integr. Biol. 11, 1–6 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
98.Karabourniotis, G., Liakopoulos, G., Nikolopoulos, D. & Bresta, P. Protective and defensive roles of non-glandular trichomes against multiple stresses: Structure–function coordination. J. For. Res. 31, 1–12 (2019).Article 
CAS 

Google Scholar 
99.Kang, J.-H., Shi, F., Jones, A. D., Marks, M. D. & Howe, G. A. Distortion of trichome morphology by the hairless mutation of tomato affects leaf surface chemistry. J. Exp. Bot. 61, 1053–1064 (2009).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
100.Tian, D., Tooker, J., Peiffer, M., Chung, S. H. & Felton, G. W. Role of trichomes in defense against herbivores: Comparison of herbivore response to woolly and hairless trichome mutants in tomato (Solanum lycopersicum). Planta 236, 1053–1066 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
101.An, F. et al. Ethylene-induced stabilization of ETHYLENE INSENSITIVE3 and EIN3-LIKE1 is mediated by proteasomal degradation of EIN3 binding F-Box 1 and 2 That requires EIN2 in arabidopsis. Plant Cell 22, 2384–2401 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
102.Lämke, J. & Bäurle, I. Epigenetic and chromatin-based mechanisms in environmental stress adaptation and stress memory in plants. Genome Biol. 18, 1 (2017).Article 
CAS 

Google Scholar 
103.Weinhold, A. Transgenerational stress-adaption: an opportunity for ecological epigenetics. Plant Cell Rep. 37, 3–9 (2017).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
104.Miryeganeh, M. & Saze, H. Epigenetic inheritance and plant evolution. Popul. Ecol. 62, 17–27 (2019).Article 

Google Scholar  More

In this study, we gave a comprehensive description of the mating behavior of the greenhouse whitefly, T. vaporariorum. In particular, we defined the strict association between vibrational signals and behavioral steps of the pair formation process, from the male call to the final mating. We also described some social interactions between two or more individuals of both sexes, confined to a small portion of leaf, thus simulating a natural occurring aggregation. In this regard, we found that males tend to modify the quality of their vibrational signals, by changing some spectral features, according to either the social context or the behavioral step. For example, they tend to increase the fundamental frequency of their signals (i.e., chirps and PT) when in the presence of potential rivals. A possible explanation of this behavior could be associated with the male competition for food and/or mating. In fact, species that live in high population densities are subjected to strong male-male competitions and a male needs to show his quality to females but also to be clearly recognizable from the others24. The higher quality can be witnessed by the emission of specific aggressive calls which are characterized by lower frequencies, like in some anurans25 or in Chiropteran where the relative frequency of the social calls increases when more individuals compete for a food source. An example of individual recognition behavior is the change of frequency of the calling song to avoid signal overlapping thus allowing an individual to perceive the presence of more potential partners. Frequency overlapping, in general, can be noxious to animal communication, and male responsiveness can be reduced when background noise from conspecific signals obscure the species-specific temporal pattern of a female song26. In the southern green stink bug, Nezara viridula (Heteroptera, Pentatomidae), females were found to change their calling song frequency to let the males recognize them when exposed to a disturbance stimulus27. Even if small variations of the frequency pattern may potentially affect the partner responsiveness to a call28, overlapping frequencies can seriously compromise the signal reception29. In this way, the change to a different value of frequency in presence of other calling males seems to be a more desirable solution.Another signal variation that we observed in GW males, in the presence of another male (i.e., male duos trials), regarded the chirp duration. By increasing the duration of a mating signal, some species also increase the chances to elicit the female response at the earliest stage of the mating behavior30. In various acoustic insects, females prefer longer calls and males can vary their length by adding or subtracting call elements31. However, a limit of our study was that we could not associate the signal emissions to specific individuals, therefore we did not determine not only if one or both the males were actually singing but also whether this change of chirp duration involved one or both the individuals. A definitive explanation about male-male calling interactions and how males regulate their calling activities should be provided with additional experiments with the use of playbacks to stimulate single specimens.In general, we need to consider that the alteration of the signal features is a common strategy in animals with a complex mating behavior in which different stages can alternate in a non-linear sequence29,32,33. Such an intricate behavior is on the one hand, at the basis of a species-specific mate recognition system, on the other hand, is a result of the sexual selection that worked to shape signals with certain characteristics that are able to elicit the female acceptance to mate34. Despite the considerable knowledge about vibrational signal production in the family Aleyrodidae19, we still have little information about the importance of the courtship and of the female choice in driving the reproductive isolation and speciation in this family. Aleyrodid species are known to be morphologically similar and to form a species complex (i.e. Bemisia tabaci) with several biotypes35, where the characterization of the mating behavior can be an important tool to discriminate among them. For instance, variations in the courtship behavior between different B. tabaci biotypes demonstrated the presence of pre-copulation barriers36,37. Moreover, the analysis of male vibrational signals during the courtship, combined with genetic and morphological analysis, allowed to discriminate between the camellia spiny whitefly Aleurocanthus camelliae and the citrus spiny whitefly Aleurocanthus spiniferus18. In such a context, knowing the characteristics of the mating ritual may lead to distinguish, not only among different species, but also among different populations. For example, before this study, the GW mating behavior was described only from Japanese populations where the pair formation process started with the male approaching a female before emitting any vibrational signal (i.e. courtship stage)17. Instead, in our study with European populations of GW, we observed that the male, before starting the approach, emits calling signals which can elicit the female response from a certain distance. Such a difference between geographically distant GW populations seems to suggest a different strategies of mating behavior, likely associated to distinct populations or biotypes. On this regard, it would be interesting to test them with crossed mating trials (Japanese vs Europeans) to assess the effects of the observed differences on the mating success rate.In our study, we also measured a difference of male signal parameters between different behavioral phases of the pair formation process and in particular between the courtship stage and the call and alternated duet stages. We found a significant increase of signal duration, fundamental frequency and pulse repetition rate. The duration of the courtship stage was very variable in our trials, from zero (it was skipped when females replied immediately to the male signals) up to 78 min. This means, in first instance, that the role of the courtship is to elicit the female response and thus promoting her acceptance to mate. Indeed any single behavioral step is functional to elicit the female’s acceptance and in fact, whenever females showed high responsiveness since the early stage of the mating process, males could skip whole stages and even go directly from the call to the final precopula stage, the alternated duet. It also indicates that males are available to spend a remarkable amount of energy to perform the courtship38. The use of elaborated and energetic signals during the courtship is rather common in animals34. For example, the leafhopper S. titanus and the glassy-winged sharpshooter Homalodisca vitripennis have a mating strategy that reminds the GW’s, starting with a call which is followed by the location of the partner and by the courtship. While during call and location males make use of extremely simplified signals, during the courtship they emit the most elaborated (and energetically demanding) signals, through which they try to convince the female to accept the mating21,39. A study of Las (1980) demonstrated that the GW courtship persistence (i.e., duration) is an important trigger to address the female choice. A fast and prolonged male “cycling rate” (alternation of wing flicking and antennation) during the courtship is preferred by females who become even more selective after the first mating. On the other hand, in our tests, males showed a remarkable perseverance in courting the females. The ethogram showed that after a failed mating attempt, a male always restarted from the courtship. This means that the courtship phase is the key part of the mating process but also that the female choice drives the selection in favor of “stubborn” males that persist in courting the potential partner, performing a prolonged courtship, even if the first mating attempt fails. Stubbornness affects male’s survival for its energetic cost and risk of eavesdropping. Such character fits the handicap theory model, in which condition dependent and costly traits are honest indicators of male quality40,41. On the other hand, the option of an easy surrender, and the search for another available female, after investing so many energies in courting the first one, seems to be not convenient for the male in that it would mean to spend more energy in searching for/courting a new partner also risking the possibility of dealing with competitors42.In the GW, the male courtship can be considered successful when the mating moves to the overlapped duet stage in which the female emits the Female Responding Signal (FRS). The FRS is produced in synchronous with the courtship chirp and PT and, for this reason, it requires high degree of coordination between male and female. The presence of female acceptance signals synchronized with the male’s is known for the whitefly species Aleurothrixus floccosus (Maskell)43, in which the female signal can partially overlap the male’s one, but it was unknown in the GW, until now.Another signal that we found for the first time in the GW is the male rivalry signal (MRS). Males exhibit aggressiveness towards other males. A random encounter on the leaf is enough to trigger the expression of rivalry behavior in presence of a female. Such interaction has never been observed in duos, but only in groups with responsive females, thus suggesting that the presence of receptive/active females is required to trigger the MRS production and thus provoking a context of aggressiveness and competition between males. Another male rivalry behavior that we observed in the presence of a receptive female is the silent approach (satellite behavior) to intercept a female while duetting with another male44. This behavior is known in other aleyrodids like in B. tabaci. In this species, rival males interrupt the ongoing courtship of the duetting male by approaching the female from the opposite side. In response to the competitor, the first male spreads the wings and beats the rival on the head45. In GW, the rivalry behavior is associated with the continuous production of the MRS, which is the male signal at highest frequency. Such finding strengthens the hypothesis that the frequency shift has a role in competitor’s deterrence. The rivalry behavior of GW seems to be extraordinarily strong, as much to push females to abandon the interaction with both males. In our experiments, none of the females, even those that had already established a duet with a male, eventually mated. On the contrary, they left the arena before the end of the trial. Our findings are consistent with previous observations of GW behavior, in which the contended female always walked away when two males were competing15. Therefore, we can speculate that the adaptive advantage of the male rivalry behavior in GW is not immediate and the disruption of another male’s attempt could provide more chances in the future to the intruder, by leaving a receptive female unmated. Beside the effects of the male’s rivalry, we also observed females that refused to mate and rejected approaching males with the emission of specific vibrational signals. There are several reasons to refuse mating: immature females are not yet available to mate, and recently mated females must undergo to a refractory period before they accomplish other copulations15. On the other hand, a mature female can choose whether to accept or not a courting male depending on the level of his fitness which is, very likely, testified by the courtship performance. Females can evaluate the male’s quality based on the courtship persistence, so that they need to let males perform the whole ritual before choosing whether to mate or not46. In fact, we observed both females that rejected approaching males and females that rejected them at the end of the courtship performance. The latter, in particular, was associated to wing flicking and/or male’s aedeagus parrying with the legs. Similar behaviors were also observed in B. tabaci, in which the female can either walk or fly away from approaching males, flap the wings or push the male’s abdomen away with the middle pair of legs45. What seems to be a peculiar treat of GW is the use of a specific rejective signal (FRjS). The emission of FRjS seems to reinforce the motivation of the female to reject the male. However, it is not clear to us why the FRjS signal has been observed only in the group (males and females together) trials and never in pairs (one male and one female). Our hypothesis is that in case of groups, males can approach the “wrong” female, who was close the receptive one. This implies that males are not capable of precisely locating the responding female and that the emission of FRjS by an unreceptive female would help the males to not waste too much time (and energy) with them.To conclude, this study unveiled many aspects of the mating behavior of the GW that were previously overlooked and thus it contributes to fill several gaps of knowledge that will be important to start a program in the field of applied biotremology10. The question, from which originally arose this research study, was whether the use of vibrational signals could be suitable to manipulate the mating behavior of the GW. We can say that the vibrational communication is fundamental to accomplish mating and, in our trials, with pairs and groups, we never observed mating without the exchange of vibrational signals between male and female. This means that the interruption or the disruption of this communication could be potentially useful to reduce the rate of mating success. Manipulation of intraspecific communication by means of vibrational signals has been already developed for other insect species both in the lab and in the field10. For example, the male rivalry signal has been exploited for the development of a vibrational mating disruption strategy against the grapevine leafhopper Scaphoideus titanus29, while the female playback has been used to attract and trap males in the brown marmorated stink bug Halyomorpha halys47. The use of playbacks that cover the fundamental frequencies of the male and female signals could be used to mask their communication2. Another possible approach could be to use signals that mimic the natural signals of the species48. In the case of the GW, the FRS could be employed to disrupt males and induce them in courting unreceptive females. This would lead to a substantial reduction of the mating success rate but also to a considerable increase of wasted energy caused by the male persistence in courting unreceptive females. Another possible outcome could be a change of the gender balance in the population. GW females reproduce by arrhenotokous parthenogenesis in which unfertilized eggs develop into males49. Delays in mating could lead to a sex bias that could eventually mine the population structure. Another option is the use of the MRS to generate an aggressive and stressful environment. The transmission of MRS into the plant tissues in loop could eventually negatively affect the development of GW populations. All these approaches are potentially effective and could be in the future considered as tools for IPM and/or organic protection programs. Further applied research will provide a final answer to our question and will test the effectiveness of behavioural manipulation strategies for the control of the GW. Finally, considering that the GW uses a short range sexual pheromone emitted by females50 olfactory and vibratory cues could be potentially integrated to develop new pest control technologies10. 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