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    Effects of fertilizer under different dripline spacings on summer maize in northern China

    1.China. China statistical yearbook. (China Statistics Press, 2020).2.Shiferaw, B., Prasanna, B. M., Hellin, J. & Bänziger, M. Crops that feed the world 6. Past successes and future challenges to the role played by maize in global food security. Food Secur. 3, 307–327 (2011).Article 

    Google Scholar 
    3.Chen, M. P., Sun, F. & Shindo, J. China’s agricultural nitrogen flows in 2011: Environmental assessment and management scenarios. Resour. Conserv. Recycl. 111, 10–27 (2016).Article 

    Google Scholar 
    4.He, Y. X. et al. Tracking ammonia morning peak, sources and transport with 1 Hz measurements at a rural site in North China Plain. Atmos. Environ. 235, 117630 (2020).CAS 
    Article 

    Google Scholar 
    5.Zhang, Y. et al. Agricultural ammonia emissions inventory and spatial distribution in the North China Plain. Environ. Pollut. 158, 490–501 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    6.Ayars, J. E., Fulton, A. & Taylor, B. Subsurface drip irrigation in California—Here to stay?. Agric. Water Manag. 157, 39–47 (2015).Article 

    Google Scholar 
    7.Chauhdary, J. N., Bakhsh, A., Engel, B. A. & Ragab, R. Improving corn production by adopting efficient fertigation practices: Experimental and modeling approach. Agric. Water Manag. 221, 449–461 (2019).Article 

    Google Scholar 
    8.Mali, S. S., Naik, S. K., Jha, B. K., Singh, A. K. & Bhatt, B. P. Planting geometry and growth stage linked fertigation patterns: Impact on yield, nutrient uptake and water productivity of Chilli pepper in hot and sub-humid climate. Sci. Hortic. (Amsterdam) 249, 289–298 (2019).Article 

    Google Scholar 
    9.Silber, A. et al. High fertigation frequency: the effects on uptake of nutrients, water and plant growth. Plant Soil 253, 467–477 (2003).CAS 
    Article 

    Google Scholar 
    10.Wu, D. L. et al. Effect of different drip fertigation methods on maize yield, nutrient and water productivity in two-soils in Northeast China. Agric. Water Manag. 213, 200–211 (2019).Article 

    Google Scholar 
    11.Ning, D. et al. Deficit irrigation combined with reduced N-fertilizer rate can mitigate the high nitrous oxide emissions from Chinese drip-fertigated maize field. Glob. Ecol. Conserv. 20, e00803 (2019).Article 

    Google Scholar 
    12.Sandhu, O. S. et al. Drip irrigation and nitrogen management for improving crop yields, nitrogen use efficiency and water productivity of maize-wheat system on permanent beds in north-west India. Agric. Water Manag. 219, 19–26 (2019).Article 

    Google Scholar 
    13.Li, H. et al. Effects of different nitrogen fertilizers on the yield, water- and nitrogen-use efficiencies of drip-fertigated wheat and maize in the North China Plain. Agric. Water Manag. 243, 106474 (2021).Article 

    Google Scholar 
    14.Lamm, F. R., Stone, L. R., Manges, H. L. & O’Brien, D. M. Optimum lateral spacing for subsurface drip-irrigated corn. Trans. ASAE 40, 1021–1027 (1997).Article 

    Google Scholar 
    15.Bozkurt, Y., Yazar, A., Gençel, B. & Sezen, M. S. Optimum lateral spacing for drip-irrigated corn in the Mediterranean Region of Turkey. Agric. Water Manag. 85, 113–120 (2006).Article 

    Google Scholar 
    16.Chen, R. et al. Lateral spacing in drip-irrigated wheat: The effects on soil moisture, yield, and water use efficiency. Field Crop. Res. 179, 52–62 (2015).Article 

    Google Scholar 
    17.Zhou, L. et al. Drip irrigation lateral spacing and mulching affects the wetting pattern, shoot-root regulation, and yield of maize in a sand-layered soil. Agric. Water Manag. 184, 114–123 (2017).Article 

    Google Scholar 
    18.Eissa, M. A. Efficiency of P fertigation for drip-irrigated potato grown on calcareous sandy soils. Potato Res. 62, 97–108 (2019).CAS 
    Article 

    Google Scholar 
    19.Irmak, S., Djaman, K. & Rudnick, D. R. Effect of full and limited irrigation amount and frequency on subsurface drip-irrigated maize evapotranspiration, yield, water use efficiency and yield response factors. Irrig. Sci. 34, 271–286 (2016).Article 

    Google Scholar 
    20.Yao, Y. L. et al. Urea deep placement for minimizing NH3 loss in an intensive rice cropping system. Field Crop. Res. 218, 254–266 (2018).Article 

    Google Scholar 
    21.Ziadi, N., Cambouris, A. N., Nyiraneza, J. & Nolin, M. C. Across a landscape, soil texture controls the optimum rate of N fertilizer for maize production. Field Crop. Res. 148, 78–85 (2013).Article 

    Google Scholar 
    22.Fang, H. et al. An optimized model for simulating grain-filling of maize and regulating nitrogen application rates under different film mulching and nitrogen fertilizer regimes on the Loess Plateau. China. Soil Tillage Res. 199, 104546 (2020).Article 

    Google Scholar 
    23.Zheng, J. et al. Interactive effects of mulching practice and nitrogen rate on grain yield, water productivity, fertilizer use efficiency and greenhouse gas emissions of rainfed summer maize in northwest China. Agric. Water Manag. 248, 106778 (2021).Article 

    Google Scholar 
    24.Qi, X. L. et al. Grain yield and apparent N recovery efficiency of dry direct-seeded rice under different N treatments aimed to reduce soil ammonia volatilization. Field Crop. Res. 134, 138–143 (2012).Article 

    Google Scholar 
    25.Han, K., Zhou, C. J. & Wang, L. Q. Reducing ammonia volatilization from maize fields with separation of nitrogen fertilizer and water in an alternating furrow irrigation system. J. Integr. Agric. 13, 1099–1112 (2014).CAS 
    Article 

    Google Scholar 
    26.Amin, A.E.-E.A.Z. Carbon sequestration, kinetics of ammonia volatilization and nutrient availability in alkaline sandy soil as a function on applying calotropis biochar produced at different pyrolysis temperatures. Sci. Total Environ. 726, 138489 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    27.Li, H. T. et al. Film mulching, residue retention and N fertilization affect ammonia volatilization through soil labile N and C pools. Agric. Ecosyst. Environ. 308, 107272 (2021).CAS 
    Article 

    Google Scholar 
    28.Sun, B. et al. Bacillus subtilis biofertilizer mitigating agricultural ammonia emission and shifting soil nitrogen cycling microbiomes. Environ. Int. 144, 105989 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Tabli, N. et al. Plant growth promoting and inducible antifungal activities of irrigation well water-bacteria. Biol. Control 117, 78–86 (2018).Article 

    Google Scholar 
    30.Zhong, X. M. et al. Reducing ammonia volatilization and increasing nitrogen use efficiency in machine-transplanted rice with side-deep fertilization in a double-cropping rice system in Southern China. Agric. Ecosyst. Environ. 306, 107183 (2021).CAS 
    Article 

    Google Scholar 
    31.Li, C., Sun, M. X., Xu, X. B. & Zhang, L. X. Characteristics and influencing factors of mulch film use for pollution control in China: Microcosmic evidence from smallholder farmers. Resour. Conserv. Recycl. 164, 105222 (2021).Article 

    Google Scholar 
    32.Li, M. N., Wang, Y. L., Adeli, A. & Yan, H. J. Effects of application methods and urea rates on ammonia volatilization, yields and fine root biomass of alfalfa. Field Crop. Res. 218, 115–125 (2018).Article 

    Google Scholar 
    33.Pinheiro, P. L. et al. Straw removal reduces the mulch physical barrier and ammonia volatilization after urea application in sugarcane. Atmos. Environ. 194, 179–187 (2018).ADS 
    CAS 
    Article 

    Google Scholar 
    34.Zhu, H. et al. Interactive effects of soil amendments (biochar and gypsum) and salinity on ammonia volatilization in coastal saline soil. CATENA 190, 104527 (2020).CAS 
    Article 

    Google Scholar 
    35.Oppong Danso, E. et al. Effect of different fertilization and irrigation methods on nitrogen uptake, intercepted radiation and yield of okra (Abelmoschus esculentum L.) grown in the Keta Sand Spit of Southeast Ghana. Agric. Water Manag. 147, 34–42 (2015).Article 

    Google Scholar 
    36.Liu, R. H. et al. Chemical fertilizer pollution control using drip fertigation for conservation of water quality in Danjiangkou Reservoir. Nutr. Cycl. Agroecosystems 98, 295–307 (2014).CAS 
    Article 

    Google Scholar 
    37.Sanz-Cobena, A. et al. Strategies for greenhouse gas emissions mitigation in mediterranean agriculture: A review. Agric. Ecosyst. Environ. 238, 5–24 (2017).CAS 
    Article 

    Google Scholar 
    38.Zhou, J. B., Xi, J. G., Chen, Z. J. & Li, S. X. Leaching and transformation of nitrogen fertilizers in soil after application of n with irrigation: A soil column method. Pedosphere 16, 245–252 (2006).CAS 
    Article 

    Google Scholar 
    39.Rosemary, F., Vitharana, U. W. A., Indraratne, S. P., Weerasooriya, R. & Mishra, U. Exploring the spatial variability of soil properties in an Alfisol soil catena. CATENA 150, 53–61 (2017).CAS 
    Article 

    Google Scholar 
    40.Liu, Y., Lv, J. S., Zhang, B. & Bi, J. Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, Eastern China. Sci. Total Environ. 450–451, 108–119 (2013).ADS 
    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    41.Vasu, D. et al. Assessment of spatial variability of soil properties using geospatial techniques for farm level nutrient management. Soil Tillage Res. 169, 25–34 (2017).Article 

    Google Scholar 
    42.Jin, J. Y., Bai, Y. L. & Yang, L. P. High Efficiency Soil Nutrient Testing Technology and Equipment (China Agriculture Press, 2006) (in Chinese).
    Google Scholar 
    43.Tan, Y. et al. Improving wheat grain yield via promotion of water and nitrogen utilization in arid areas. Sci. Rep. 11, 13821 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    44.Ren, Y. et al. Effect of sowing proportion on above- and below-ground competition in maize–soybean intercrops. Sci. Rep. 11, 15760 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    45.Wang, Z. H., Liu, X. J., Ju, X. T., Zhang, F. S. & Malhi, S. S. Ammonia volatilization loss from surface-broadcast urea: comparison of vented- and closed-chamber methods and loss in winter wheat–summer maize rotation in North China plain. Commun. Soil Sci. Plant Anal. 35, 2917–2939 (2004).CAS 
    Article 

    Google Scholar 
    46.Zhou, L. P. et al. Comparison of several slow-released nitrogen fertilizers in ammonia volatilization and nitrogen utilization in summer maize field. J. Plant Nutr. Fertil. 22, 1449–1457 (2016) (in Chinese).
    Google Scholar 
    47.Huang, T. M. et al. Grain zinc concentration and its relation to soil nutrient availability in different wheat cropping regions of China. Soil Tillage Res. 191, 57–65 (2019).Article 

    Google Scholar 
    48.Wang, Z., Li, J. & Li, Y. Effects of drip system uniformity and nitrogen application rate on yield and nitrogen balance of spring maize in the North China Plain. Field. Crop. Res. 159, 10–20 (2014).Article 

    Google Scholar 
    49.Brar, H. S., Vashist, K. K. & Bedi, S. Phenology and yield of spring maize (Zea mays L.) under different drip irrigation regimes and planting methods. J. Agric. Sci. Technol. 18, 831–843 (2016).
    Google Scholar 
    50.Poch-Massegú, R., Jiménez-Martínez, J., Wallis, K. J., Ramírez de Cartagena, F. & Candela, L. Irrigation return flow and nitrate leaching under different crops and irrigation methods in Western Mediterranean weather conditions. Agric. Water Manag. 134, 1–13 (2014).Article 

    Google Scholar 
    51.Yuan, Z. Q. et al. Film mulch with irrigation and rainfed cultivations improves maize production and water use efficiency in Ethiopia. Ann. Appl. Biol. 175, 215–227 (2019).Article 

    Google Scholar 
    52.Wang, J. L. Research on the use of water and fertilizer for drip irrigation multiple cropping silage maize (Shihezi University, 2016) (in Chinese).
    Google Scholar 
    53.Lamm, F. R. & Trooien, T. P. Subsurface drip irrigation for corn production: a review of 10 years of research in Kansas. Irrig. Sci. 22, 195–200 (2003).Article 

    Google Scholar 
    54.Yan, X. L., Jia, L. M. & Dai, T. F. Effects of water and nitrogen coupling under drip irrigation on tree growth and soil nitrogen content of Populus × euramericana cv. ‘Guariento’. Chin. J. Appl. Ecol. 29, 2195 (2018) (in Chinese).
    Google Scholar 
    55.Sun, W. T., Sun, Z. X., Wang, C. X., Gong, L. & Zhang, Y. L. Coupling effect of water and fertilizer on corn yield under drip fertigation. Sci. Agric. Sin. 39, 563–568 (2006) (in Chinese).
    Google Scholar 
    56.Banerjee, B., Pathak, H. & Aggarwal, P. Effects of dicyandiamide, farmyard manure and irrigation on crop yields and ammonia volatilization from an alluvial soil under a rice (Oryza sativa L.)-wheat (Triticum aestivum L.) cropping system. Biol. Fertil. Soils 36, 207–214 (2002).CAS 
    Article 

    Google Scholar 
    57.Yang, Q. L., Liu, P., Dong, S. T., Zhang, J. W. & Zhao, B. Effects of fertilizer type and rate on summer maize grain yield and ammonia volatilization loss in northern China. J. Soils Sediments 19, 2200–2211 (2019).CAS 
    Article 

    Google Scholar 
    58.Zhou, G. W. et al. Effects of saline water irrigation and N application rate on NH3 volatilization and N use efficiency in a drip-irrigated cotton field. Water Air Soil Pollut. 227, 103 (2016).ADS 
    Article 
    CAS 

    Google Scholar 
    59.Zheng, J., Kilasara, M. M., Mmari, W. N. & Funakawa, S. Ammonia volatilization following urea application at maize fields in the East African highlands with different soil properties. Biol. Fertil. Soils 54, 411–422 (2018).CAS 
    Article 

    Google Scholar 
    60.Li, Z. et al. Nitrogen use efficiency and ammonia oxidation of corn field with drip irrigation in Hetao irrigation district. J. Irrig. Drain. 37, 37–42,49 (2018) (in Chinese).61.Zheng, L. et al. Impact of fertilization on ammonia volatilization and N2O emissions in an open vegetable field. Chin. J. Appl. Ecol. 29, 4063–4070 (2018) (in Chinese).
    Google Scholar 
    62.Li, Y. Q., Liu, G., Hong, M., Wu, Y. & Chang, F. Effect of optimized nitrogen application on nitrous oxide emission and ammonia volatilization in Hetao irrigation area. Acta Sci. Circumst. 39, 578–584 (2019) (in Chinese).CAS 

    Google Scholar 
    63.Das, P. et al. Emissions of ammonia and nitric oxide from an agricultural site following application of different synthetic fertilizers and manures. Geosci. J. 12, 177–190 (2008).ADS 
    CAS 
    Article 

    Google Scholar 
    64.Cai, G. X. et al. Nitrogen losses from fertilizers applied to maize, wheat and rice in the North China Plain. Nutr. Cycl. Agroecosyst. 63, 187–195 (2002).CAS 
    Article 

    Google Scholar 
    65.Wang, X. L. et al. Corn compensatory growth upon post-drought rewatering based on the effects of rhizosphere soil nitrification on cytokinin. Agric. Water Manag. 241, 106436 (2020).Article 

    Google Scholar 
    66.Li, G. et al. Effect of drip fertigation on summer maize in north China. Sci. Agric. Sin. 52, 1930–1941 (2019) (in Chinese).
    Google Scholar  More

  • in

    Specialization directs habitat selection responses to a top predator in semiaquatic but not aquatic taxa

    1.Binckley, C. A. & Resetarits, W. J. Habitat selection determines abundance, richness and species composition of beetles in aquatic communities. Biol. Lett. 1, 370–374 (2005).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    2.Foltz, S. J. & Dodson, S. I. Aquatic Hemiptera community structure in stormwater retention ponds: A watershed land cover approach. Hydrobiologia 621, 49–62 (2009).Article 

    Google Scholar 
    3.Goldberg, F. J., Quinzio, S. & Vaira, M. Oviposition-site selection by the toad Melanophryniscus rubriventris in an unpredictable environment in Argentina. Can. J. Zool. 84, 699–705 (2006).Article 

    Google Scholar 
    4.Blaustein, L. Oviposition site selection in response to risk of predation: Evidence from aquatic habitats and consequences for population dynamics and community. In Evolutionary Theory and Processes: Modern Perspectives (ed. Wasser, S. P.) 441–456 (Kluwer, 1999).5.Resetarits, W. J. & Binckley, C. A. Spatial contagion of predation risk affects colonization dynamics in experimental aquatic landscapes. Ecology 90, 869–876 (2009).PubMed 
    Article 

    Google Scholar 
    6.Kraus, J. M. & Vonesh, J. R. Feedbacks between community assembly and habitat selection shape variation in local colonization. J. Anim. Ecol. 79, 795–802 (2010).PubMed 

    Google Scholar 
    7.Resetarits, W. J. Oviposition site choice and life history evolution. Am. Zool. 36, 205–215 (1996).Article 

    Google Scholar 
    8.Morris, D. W. Toward an ecological synthesis: A case for habitat selection. Oecologia 136, 1–13 (2003).ADS 
    PubMed 
    Article 

    Google Scholar 
    9.Resetarits, W. J. & Wilbur, H. M. Choice of oviposition site by Hyla chrysoscelis: Role of predators and competitors. Ecology 70, 220–228 (1989).Article 

    Google Scholar 
    10.Resetarits, W. J., Binckley, C. A. & Chalcraft, D. R. Habitat selection, species interactions, and processes of community assembly in complex landscapes: A metacommunity perspective. In Metacommunities: Spatial Dynamics and Ecological Communities (eds. Holyoak, M., Leybold, A. & Holt, R. D.) 374–398 (University of Chicago Press, Chicago, 2005).11.Lima, S. L. & Dill, L. M. Behavioral decisions made under the risk of predation: A review and prospectus. Can. J. Zool. 68, 619–640 (1990).Article 

    Google Scholar 
    12.Langellotto, G. A. & Denno, R. F. Responses of invertebrate natural enemies to complex-structured habitats: A meta-analytical synthesis. Oecologia 139, 1–10 (2004).ADS 
    PubMed 
    Article 

    Google Scholar 
    13.Åbjörnsson, K., Brönmark, C. & Hansson, L.-A. The relative importance of lethal and non-lethal effects of fish on insect colonisation of ponds: Influence of fish on insect colonisation. Freshw. Biol. 47, 1489–1495 (2002).Article 

    Google Scholar 
    14.Pintar, M. R. & Resetarits, W. J. Jr. Out with the old, in with the new: Oviposition preference matches larval success in cope’s gray treefrog, Hyla chrysoscelis. J. Herpetol. 51, 186–189 (2017).Article 

    Google Scholar 
    15.Wellborn, G. A., Skelly, D. K. & Werner, E. E. Mechanisms creating community structure across a freshwater habitat gradient. Annu. Rev. Ecol. Evol. Syst. 27, 337–363 (1996).Article 

    Google Scholar 
    16.Caudill, C. C. & Peckarsky, B. L. Lack of appropriate behavioral or developmental responses by mayfly larvae to trout predators. Ecology 84, 2133–2144 (2003).Article 

    Google Scholar 
    17.Binckley, C. A. & Resetarits, W. J. Functional equivalence of non-lethal effects: Generalized fish avoidance determines distribution of gray treefrog, Hyla chrysoscelis, larvae. Oikos 102, 623–629 (2003).Article 

    Google Scholar 
    18.Pollard, C. J. et al. Removal of an exotic fish influences amphibian breeding site selection: Exotic fish removal. J. Wildl. Manag. 81, 720–727 (2017).Article 

    Google Scholar 
    19.Petranka, J. W. & Fakhoury, K. Evidence of a chemically-mediated avoidance response of ovipositing insects to bluegills and green frog tadpoles. Copeia 1991, 234–239 (1991).Article 

    Google Scholar 
    20.McPeek, M. A. Differential dispersal tendencies among Enallagma damselflies (Odonata) inhabiting different habitats. Oikos 56, 187–195 (1989).Article 

    Google Scholar 
    21.Šigutová, H., Šigut, M. & Dolný, A. Intensive fish ponds as ecological traps for dragonflies: An imminent threat to the endangered species Sympetrum depressiusculum (Odonata: Libellulidae). J. Insect Conserv. 19, 961–974 (2015).Article 

    Google Scholar 
    22.Potts, K. M. Survival and development of larval odonates (Anisoptera) and female oviposition site choice in response to predatory fish. https://egrove.olemiss.edu/etd/1854 (2020).23.Blaustein, L., Kiflawi, M., Eitam, A., Mangel, M. & Cohen, J. E. Oviposition habitat selection in response to risk of predation in temporary pools: Mode of detection and consistency across experimental venue. Oecologia 138, 300–305 (2004).ADS 
    PubMed 
    Article 

    Google Scholar 
    24.Wildermuth, H. Habitat selection and oviposition site recognition by the dragonfly Aeshna juncea (L.): An experimental approach in natural habitats (Anisoptera: Aeshnidae). Odonatologica 22, 27–44 (1993).25.Wildermuth, H. Habitatselektion bei Libellen. Adv. Odonatol. 6, 223–257 (1994).
    Google Scholar 
    26.Laurila, A. Breeding habitat selection and larval performance of two anurans in freshwater rock-pools. Ecography 21, 484–494 (1998).Article 

    Google Scholar 
    27.Schwind, R. Spectral regions in which aquatic insects see reflected polarized light. J. Comp. Physiol. A 177, 439–448 (1995).Article 

    Google Scholar 
    28.Horváth, G. & Kriska, G. Polarization vision in aquatic insects and ecological traps for polarotactic insects in Aquatic Insects: Challenges to Populations (eds. Lancaster, J. & Briers, R. A.) 204–229 (CAB International Publishing, 2008).29.Schulte, L. M. et al. The smell of success: Choice of larval rearing sites by means of chemical cues in a Peruvian poison frog. Anim. Behav. 81, 1147–1154 (2011).Article 

    Google Scholar 
    30.Corbet, P. S. Dragonflies: Behavior and ecology of Odonata. (Harley Books, 1999).31.Nicolet, P. et al. The wetland plant and macroinvertebrate assemblages of temporary ponds in England and Wales. Biol. Conserv. 120, 261–278 (2004).Article 

    Google Scholar 
    32.Henrikson, B.-I. Sphagnum mosses as a microhabitat for invertebrates in acidified lakes and the colour adaptation and substrate preference in Leucorrhinia dubia (Odonata, Anisoptera). Ecography 16, 143–153 (1993).Article 

    Google Scholar 
    33.Kokko, H. & Sutherland, W. J. Ecological traps in changing environments: Ecological and evolutionary consequences of a behaviourally mediated Allee effect. Evol. Ecol. Res. 3, 537–551 (2001).
    Google Scholar 
    34.Gilroy, J. J. & Sutherland, W. J. Beyond ecological traps: Perceptual errors and undervalued resources. Trends Ecol. Evol. 22, 351–356 (2007).PubMed 
    Article 

    Google Scholar 
    35.Abrams, P. A., Cressman, R. & Křivan, V. The role of behavioral dynamics in determining the patch distributions of interacting species. Am. Nat. 169, 505–518 (2007).PubMed 
    Article 

    Google Scholar 
    36.Denton, J. & Beebee, T. J. C. Palatability of anuran eggs and embryos. Amphib. Reptil. 12, 111–112 (1991).Article 

    Google Scholar 
    37.Larson, D. J. The predaceous water beetles (Coleoptera: Dytiscidae) of Alberta: Systematics, natural history and distribution. Quaest. Entomol. 11, 245–498 (1985).
    Google Scholar 
    38.Mikolajewski, D. J. & Rolff, J. Benefits of morphological defence demonstrated by direct manipulation in larval dragonflies. Evol. Ecol. Res. 6, 619–626 (2004).
    Google Scholar 
    39.Relyea, R. A. Morphological and behavioral plasticity of larval anurans in response to different predators. Ecology 82, 523–540 (2001).Article 

    Google Scholar 
    40.Benard, M. F. Predator-induced phenotypic plasticity in organisms with complex life histories. Annu. Rev. Ecol. Evol. Syst. 35, 651–673 (2004).Article 

    Google Scholar 
    41.McCauley, S. J., Davis, C. J. & Werner, E. E. Predator induction of spine length in larval Leucorrhinia intacta (Odonata). Evol. Ecol. Res. 10, 435–447 (2008).
    Google Scholar 
    42.Nöllert, A. & Nöllert, C. Die Amphibien Europas. (Franckh-Kosmos Verlags-GmbH and Company, 1992).43.Maštera, J., Zavadil, V. & Dvořák, J. Vajíčka a larvy obojživelníků České republiky. (Academia, 2015).44.Speybroeck, J., Beukema, W., Bok, B. & Van der Voort, J. Field Guide to the Amphibians and Reptiles of Britain and Europe. (Bloomsbury Natural History, 2016).45.Sternberg, K. & Buchwald, R. Die Libellen Baden-Württembergs. Band 2: Großlibellen (Anisoptera). (Verlag Eugen Ulmer Gmbh & Co., 2000).46.Mikolajewski, D. J. & Johansson, F. Morphological and behavioral defenses in dragonfly larvae: Trait compensation and cospecialization. Behav. Ecol. 15, 614–620 (2004).Article 

    Google Scholar 
    47.Kjærstad, G., Dolmen, D., Olsvik, H. A. & Tilseth, E. The backswimmer Notonecta glauca L. (Hemiptera, Notonectidae) in Central Norway. Nor. J. Entomol. 56, 44–49 (2009).
    Google Scholar 
    48.Svensson, B. G., Tallmark, B. & Petersson, E. Habitat heterogeneity, coexistence and habitat utilization in five backswimmer species (Notonecta spp.; Hemiptera, Notonectidae). Aquat. Insects 22, 81–98 (2000).Article 

    Google Scholar 
    49.Macan, T. T. A twenty-one-year study of the water-bugs in a Moorland Fishpond. J. Anim. Ecol. 45, 913–922 (1976).Article 

    Google Scholar 
    50.Lock, K., Adriaens, T., Meutter, F. V. D. & Goethals, P. Effect of water quality on waterbugs (Hemiptera: Gerromorpha & Nepomorpha) in Flanders (Belgium): Results from a large-scale field survey. Ann. Limnol. Int. J. Limnol. 49, 121–128 (2013).Article 

    Google Scholar 
    51.Cook, W. L. & Streams, F. A. Fish predation on Notonecta (Hemiptera): Relationship between prey risk and habitat utilization. Oecologia 64, 177–183 (1984).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    52.Swevers, L., Lambert, J. G. D. & De Loof, A. Synthesis and metabolism of vertebrate-type steroids by tissues of insects: A critical evaluation. Experientia 47, 687–698 (1991).CAS 
    PubMed 
    Article 

    Google Scholar 
    53.Bergsten, J. & Miller, K. B. Taxonomic revision of the Holarctic diving beetle genus Acilius Leach (Coleoptera: Dytiscidae): Acilius taxonomic revision. Syst. Entomol. 31, 145–197 (2005).Article 

    Google Scholar 
    54.Åbjörnsson, K., Wagner, B. M. A., Axelsson, A., Bjerselius, R. & Olsén, K. H. Responses of Acilius sulcatus (Coleoptera: Dytiscidae) to chemical cues from perch (Perca fluviatilis). Oecologia 111, 166–171 (1997).ADS 
    PubMed 
    Article 

    Google Scholar 
    55.Boukal, D. S. et al. Catalogue of water beetles of the Czech Republic. Klapalekiana 43(Suppl.), 1–289 (2007).
    Google Scholar 
    56.Gioria, M., Schaffers, A., Bacaro, G. & Feehan, J. The conservation value of farmland ponds: Predicting water beetle assemblages using vascular plants as a surrogate group. Biol. Conserv. 143, 1125–1133 (2010).Article 

    Google Scholar 
    57.Everard, M. Britain’s Freshwater Fishes. (Princeton University Press, 2013).58.Briers, R. A. & Warren, P. H. Competition between the nymphs of two regionally co-occurring species of Notonecta (Hemiptera: Notonectidae). Freshw. Biol. 42, 11–20 (1999).Article 

    Google Scholar 
    59.Wiggins, G. B., Mackay, R. J. & Smith, I. M. Evolutionary and ecological strategies of animals on annual temporary pools. Arch. Für Hydrobiol. Suppl. 58, 197–206 (1980).
    Google Scholar 
    60.Culler, L. E., Ohba, S. & Crumrine, P. Predator-Prey Interactions of Dytiscids. In Ecology, Systematics, and the Natural History of Predaceous Diving Beetles (Coleoptera: Dytiscidae) (ed. Yee, D. A.) 363–379 (Springer, 2014).61.Schuh, R. T. & Slater, J. A. True Bugs of the World (Hemiptera:Heteroptera): Classification and Natural History (Cornell University Press, Cornell, 1995).
    Google Scholar 
    62.Streams, F. A. Intrageneric predation by Notonecta (Hemiptera: Notonectidae) in the laboratory and in nature. Ann. Entomol. Soc. Am. 85, 265–273 (1992).Article 

    Google Scholar 
    63.Giacoma, C., Zugolaro, C. & Beani, L. The advertisement calls of the green toad (Bufo viridis): Variability and role in mate choice. Herpetologica 53, 454–464 (1997).
    Google Scholar 
    64.Pekár, S. & Brabec, M. Generalized estimating equations: A pragmatic and flexible approach to the marginal GLM modelling of correlated data in the behavioural sciences. Ethology 124, 86–93 (2018).Article 

    Google Scholar 
    65.Halekoh, U., Højsgaard, S. & Yan, J. The R Package geepack for generalized estimating equations. J. Stat. Softw. 15, 1–11 (2006).Article 

    Google Scholar 
    66.R Core Team. R: A Language and Environment for Statistical Computing (The R Foundation for Statistical Computing, Vienna, Austria). https://www.r-project.org/ (2020).67.Wells, K. D. The Ecology and Behavior of Amphibians. (University of Chicago Press, 2007).68.Purrenhage, J. L. & Boone, M. D. Amphibian community response to variation in habitat structure and competitor density. Herpetologica 65, 14–30 (2009).Article 

    Google Scholar 
    69.Formanowicz, D. R. & Bobka, M. S. Predation risk and microhabitat preference: An experimental study of the behavioral responses of prey and predator. Am. Midl. Nat. 121, 379–386 (1989).Article 

    Google Scholar 
    70.Egan, R. S. & Paton, P. W. C. Within-pond parameters affecting oviposition by wood frogs and spotted salamanders. Wetlands 24, 1–13 (2004).Article 

    Google Scholar 
    71.Ward, S. A. Optimal habitat selection in time-limited dispersers. Am. Nat. 129, 568–579 (1987).Article 

    Google Scholar 
    72.Fretwell, S. D. & Lucas, H. L. On territorial behavior and other factors influencing habitat distribution in birds. I. Theoretical development. Biotheoretica 19, 16–36 (1970).Article 

    Google Scholar 
    73.Austad, S. N. A classification of alternative reproductive behaviors and methods for field-testing ESS models. Am. Zool. 24, 309–319 (1984).Article 

    Google Scholar 
    74.Crespo, J. G. A review of chemosensation and related behavior in aquatic insects. J. Insect Sci. 11, 1–39 (2011).Article 

    Google Scholar 
    75.Wildermuth, H. Dragonflies recognize the water of rendezvous and oviposition sites by horizontally polarized light: A behavioural field test. Naturwissenschaften 85, 297–302 (1998).ADS 
    CAS 
    Article 

    Google Scholar 
    76.Chislock, M. F., Doster, E., Zitomer, R. A. & Wilson, A. E. Eutrophication: Causes, consequences, and controls in aquatic ecosystems. Nat. Educ. Knowl. 4, 10 (2013).
    Google Scholar 
    77.Dolný, A., Mižičová, H. & Harabiš, F. Natal philopatry in four European species of dragonflies (Odonata: Sympetrinae) and possible implications for conservation management. J. Insect Conserv. 17, 821–829 (2013).Article 

    Google Scholar 
    78.Refsnider, J. M. & Janzen, F. J. Putting eggs in one basket: Ecological and evolutionary hypotheses for variation in oviposition-site choice. Annu. Rev. Ecol. Evol. Syst. 41, 39–57 (2010).Article 

    Google Scholar 
    79.Brodin, T., Mikolajewski, D. J. & Johansson, F. Behavioural and life history effects of predator diet cues during ontogeny in damselfly larvae. Oecologia 148, 162–169 (2006).ADS 
    PubMed 
    Article 

    Google Scholar 
    80.Kershenbaum, A., Spencer, M., Blaustein, L. & Cohen, J. E. Modelling evolutionarily stable strategies in oviposition site selection, with varying risks of predation and intraspecific competition. Evol. Ecol. 26, 955–974 (2012).Article 

    Google Scholar 
    81.Hopper, K. R. Risk-spreading and bet-hedging in insect population biology. Annu. Rev. Entomol. 44, 535–560 (1999).CAS 
    PubMed 
    Article 

    Google Scholar 
    82.Gioria, M. Habitats. In Ecology, Systematics, and the Natural History of predaceous diving beetles (Coleoptera: Dytiscidae) (ed. Yee, D. A.) 307–362 (Springer, Netherlands, 2014).
    Google Scholar 
    83.Diehl, S. Fish predation and benthic community structure: The role of omnivory and habitat complexity. Ecology 73, 1646–1661 (1992).Article 

    Google Scholar 
    84.Giller, P. S. & McNeill, S. Predation strategies, resource partitioning and habitat selection in Notonecta (Hemiptera/Heteroptera). J. Anim. Ecol. 50, 789–808 (1981).Article 

    Google Scholar 
    85.Ribera, I. & Nilsson, A. N. Morphometric patterns among diving beetles (Coleoptera: Noteridae, Hygrobiidae, and Dytiscidae). Can. J. Zool. 73, 2343–2360 (2011).Article 

    Google Scholar 
    86.Roberts, G. Why individual vigilance declines as group size increases. Anim. Behav. 51, 1077–1086 (1996).Article 

    Google Scholar 
    87.Schoeppner, N. M. & Relyea, R. A. Damage, digestion, and defence: The roles of alarm cues and kairomones for inducing prey defences. Ecol. Lett. 8, 505–512 (2005).PubMed 
    Article 

    Google Scholar 
    88.Schoeppner, N. M. & Relyea, R. A. Interpreting the smells of predation: How alarm cues and kairomones induce different prey defences. Funct. Ecol. 23, 1114–1121 (2009).Article 

    Google Scholar 
    89.McCauley, S. J. & Rowe, L. Notonecta exhibit threat-sensitive, predator-induced dispersal. Biol. Lett. 6, 449–452 (2010).PubMed 
    PubMed Central 
    Article 

    Google Scholar  More

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    Persistence and accumulation of environmental DNA from an endangered dragonfly

    We developed environmental DNA (eDNA) detection protocols to assist in habitat identification for conservation for the US federally endangered Hine’s emerald dragonfly (Somatochlora hineana). Larval S. hineana have been observed in groundwater-fed calcareous fen habitats in Illinois, Wisconsin, Michigan, and Missouri in the USA, and Ontario, Canada. Habitat destruction and fragmentation have been the primary cause of S. hineana population decline1. Therefore, a key part of conservation efforts to benefit S. hineana is the identification and protection of any remaining habitat areas. Conventional sampling for the presence of S. hineana often includes both adult and larval sampling.Larval S. hineana surveys include benthic-sampling and the pumping of crayfish burrows. Larval S. hineana are most often found in the burrows of Cambarus (= Lacunicambarus) diogenes throughout the year and are almost exclusively found in C. diogenes burrows during their overwintering period2. Comprehensive larval surveys can take months to complete, require intensive training of field personnel, are reliant on favorable weather conditions, and are only effective if late instar larvae can be collected for identification. Adult S. hineana surveys are difficult due to short flight season, habitat segregation by sex, large potential flight range (adults can range for many kilometers from larval habitat), risk of harm when netting adult dragonflies, and difficulty observing genitalia characteristics necessary for accurate species identification when in flight1.Given the restrictions of conventional sampling techniques, there has been a great need to develop a method to expedite field site identification. Environmental DNA can be used to guide and prioritize locations for conventional surveying methods, increasing the speed at which habitats can be identified for protection and restoration.Environmental DNA (eDNA) is a relatively new surveillance method used to detect the presence of a species within a habitat by collecting environmental samples (e.g., soil and water) that contain cell fragments and exogenous DNA3. Mitochondrial genes, which are more plentiful and have a higher resistance to degradation than nuclear genes, are targeted and amplified to determine species presence or absence4,5,6,7.Currently, there is a taxonomic skew toward fish, amphibian, and mollusk eDNA studies7,8 suggesting the need to determine if eDNA methods can be useful for detecting aquatic insects. Environmental DNA analysis from 27 taxa of freshwater arthropods had been published as of 2019; some of these taxa include Procambarus clarkii, Pacifastacus leniusculus, and Gammarus pulex8. Additionally, the critically endangered plecopteran Isogenus nubecula was detected using eDNA methods9.The potential advantages of using eDNA rather than traditional surveying methods include the reduction of field labor hours10, reduced impact to sensitive habitats7, and a lower threshold of detection11,12. Additionally, eDNA has proven to be an effective tool when traditional methods require timely/costly surveying efforts6 and for detecting cryptic invasive species10.Although there is always some risk of damaging the habitat when studying a system, environmental DNA sampling (i.e., water, soil, ice) is much less invasive and has far less potential for harming native and endangered species than many traditional surveying methods7. For example, electrofishing can cause damage in the form of removing/killing fish from the sample site13. Traditional sampling methods for larval populations of S. hineana include benthic sampling (monitoring populations in stream beds) and burrow-pumping (a novel technique used to locate larvae within crayfish burrows)2. These techniques can disrupt flow patterns within shallow streams, collapse burrows, and harm/kill sampled individuals.While there has been some speculation that eDNA sampling may have high false-positive rates due to ancient DNA contamination from extirpated populations, studies show that eDNA typically becomes undetectable in water within 1–44 days after source removal10,14,15,16,17,18,19,20,21 and approximately 144 days in soil22. This suggests that eDNA surveys are contemporaneous and can be used to inform conservation efforts.Environmental DNA degradation is likely more complex in a field setting, and the persistence (defined here as the length of time eDNA remains detectable within a habitat or mesocosm) and net-accumulation (defined here as the difference between the amount of eDNA produced and the amount of eDNA degraded over time) are likely to vary depending on numerous factors that alter source/sink dynamics3. Spatiotemporal dynamics are especially important in affecting the persistence and accumulation of eDNA in the field and need to be accounted for when developing eDNA methodologies23. Concentrations of eDNA may fluctuate spatially and/or temporally as a result of fluctuations in biomass18,24,25, transport through a flowing system17,26,27,28, age structuring of target populations7,16, feeding activity29, life-history events5, seasonal habitat preference13,30, water temperature24,31,32,33, hydrology13,27, inhibition13,27, and microbial activity34. Some studies show that water pH affects eDNA degradation rates19, while others do not35. Similarly, some studies show that UV light exposure affects eDNA degradation rates17, while others show no such effect36.In this study, we focused on the effects that seasonal shifts in temperature have on the persistence and net-accumulation of larval S. hineana eDNA. Since temperature drives the production of eDNA through metabolic processes31 and directly alters the rate of microbial degradation of eDNA32, it may be the most important variable driving seasonal shifts in eDNA detection.Somatochlora hineana larval molting activity varies with seasonal changes, the net-accumulation of S. hineana eDNA within a habitat. Adult S. hineana females lay eggs within streams and streamlets during their flight period (July–early August). Eggs typically mature over winter. In the following year, hatching of pro-larva from eggs occurs between April and June. All S. hineana larvae go through approximately 12 larval instars (F-11 to F-0). The first 6 larval instars (F-11 through F-6) occur rapidly within the first year, and the final 6 (F-5 through F-0) occur more slowly over a period of 2–4 years1. Since S. hineana larvae take several years to fully mature, they survive overwintering in shallow, partially frozen streams within Cambarus (= Lacunicambarus) diogenes crayfish burrows. While S. hineana larvae overwinter within burrows, they rarely consume food or molt, thus reducing the amount of eDNA shed2.The net-accumulation of larval S. hineana eDNA was likely to increase with increasing temperatures2,31,37, while the persistence of larval S. hineana eDNA was likely to decrease with increasing temperatures32. Therefore, we assessed the seasonal shift in persistence and net-accumulation of larval S. hineana eDNA in temperature-controlled mesocosms that reflect the larval overwintering period (5.0 °C) and the larval active period (16.0 °C). This study provided preliminary information regarding the seasonal shift in eDNA production for larval S. hineana. Understanding the seasonal dynamics of larval S. hineana eDNA is vital for efficient detection of this rare aquatic species using eDNA protocols. Our mesocosm results have informed subsequent field sampling of S. hineana eDNA. More

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    First microsatellite markers for the European Robin (Erithacus rubecula) and their application in analysis of parentage and genetic diversity

    1.Cramp, S. & Perrins, C. M. in The Birds of the Western Palearctic, Vol. 7 (eds. Cramp, S. & Perrins, C. M.) (Oxford University Press, 1993).2.Lack, D. Clutch and brood size in the Robin. Br. Birds 39(98–109), 130–135 (1946).
    Google Scholar 
    3.Lack, D. Further notes on clutch and brood size in the Robin. Br. Birds 41(98–104), 130–137 (1948).
    Google Scholar 
    4.Lack, D. The Life of Robin (Witherby, 1965).
    Google Scholar 
    5.Harper, D. G. C. Pairing strategies and mate choice in female Robins (Erithacus rubecula). Anim. Behav. 33, 862–875 (1985).Article 

    Google Scholar 
    6.Lebedeva, N. V. & Lomadze, N. H. in The Robin Erithacus Rubecula in the North-Western Caucasus (eds. Matishov, G. G. & Lebedeva, N. V.) 252–277 (SSC RAS Publishing, 2007).7.Knysh, N. P. Materials on the biology of Robin in forest-steppe deciduous forests of Sumy region. Berkut 17, 41–60 (2008).
    Google Scholar 
    8.Zimin V. B. in The Robin in the North of the Area, Vol. 1. Distribution. Number. Reproduction (ed. Zimin, V. B.) 401–422 (Karel’skiy nauchnyy centr RAN, 2009).9.Baranovskiy, A. V. & Ivanov, E. S. Features of reproductive biology of robins (Erithacus rubecula) in anthropogenic habitats (for example, the city of Ryazan). Principy èkologii 6, 17–25 (2017).
    Google Scholar 
    10.Wesołowski, T. Primeval conditions—What can we learn from them?. Ibis 149, 64–77 (2007).Article 

    Google Scholar 
    11.Tobias, J. & Seddon, N. Territoriality as a paternity guard in the European robin Erithacus rubecula. Anim. Behav. 60, 165–173 (2000).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Tobias, J. & Seddon, N. Female begging in European robins: Do neighbors eavesdrop for extrapair copulations?. Behav. Ecol. 13, 637–642 (2002).Article 

    Google Scholar 
    13.Lubjuhn, T., Strohbach, S., Brün, J., Gerken, T. & Epplen, J. T. Extra-pair paternity in great tits (Parus major)—A long term study. Behaviour 136, 1157–1172 (1999).Article 

    Google Scholar 
    14.Griffith, S. C., Owens, I. P. F. & Thuman, K. A. Extra pair paternity in birds: A review of interspecific variation and adaptive function. Mol. Ecol. 11, 2195–2212 (2002).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.Cockburn, A. Prevalence of different modes of parental care in birds. Proc. Biol. Sci. 273, 1375–1383 (2006).PubMed 
    PubMed Central 

    Google Scholar 
    16.Zagalska-Neubauer, M. & Dubiec, A. Techniki i markery molekularne w badaniach zmienności genetycznej ptaków. Not. Ornit. 48, 193–206 (2007).
    Google Scholar 
    17.Brouwer, L. & Griffith, S. C. Extra-pair paternity in birds. Mol. Ecol. 28, 4864–4882 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    18.Petter, S. C., Miles, D. B. & White, M. M. Genetic evidence of mixed reproductive strategy in a monogamous bird. Condor 92, 702–708 (1990).Article 

    Google Scholar 
    19.Jennions, M. D. & Petrie, M. Why do females mate multiply? A review of the genetic benefits. Biol. Rev. 75, 21–64 (2000).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    20.Akçay, E. & Roughgarden, J. Extra-pair paternity in birds: Review of the genetic benefits. Evol. Ecol. Res. 9, 855–868 (2007).
    Google Scholar 
    21.Dietzen, C., Witt, H.-H. & Wink, M. The phylogeographic differentiation of the European robin Erithacus rubecula on the Canary Islands revealed by mitochondrial DNA sequence data and morphometrics: Evidence for a new robin on Gran Canaria?. Avian Sci. 3, 115–131 (2003).
    Google Scholar 
    22.Rodrigues, P. et al. Phylogeography and genetic diversity of the Robin (Erithacus rubecula) in the Azores Islands: Evidence of a recent colonisation. J. Ornithol. 154, 889–900 (2013).Article 

    Google Scholar 
    23.Fulgione, D., Rippa, D., Manganiello, E., Caliendo, M. F. & Rastogi, R. K. Seasonal genetic structure analysis of a resident population of European Robin. Open Zool. J. 1, 11–17 (2008).CAS 
    Article 

    Google Scholar 
    24.Morin, P. A., Messier, J. & Woodruff, D. S. DNA extraction, amplification, and direct sequencing from hornbill feathers. J. Sci. Soc. Thail. 20, 31–41 (1994).CAS 
    Article 

    Google Scholar 
    25.Wright, T. F. et al. Microsatellite variation among divergent populations of stalk-eyed flies, genus Cyrtodiopsis. Genet. Res. 84, 27–40 (2004).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Yue, G.-H., Kovacs, B. & Orban, L. A new problem with cross-species amplification of microsatellites: Generation of non-homologous products. Dongwuxue Yanjiu 2, 131–140 (2010).
    Google Scholar 
    27.Chapuis, M.-P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631 (2007).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Dąbrowski, M. J., Bornelöv, S., Kruczyk, M., Baltzer, N. & Komorowski, J. ‘True’ null allele detection in microsatellite loci: A comparison of methods, assessment of difficulties and survey of possible improvements. Mol. Ecol. Resour. 15, 477–488 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Primmer, C. R., Møller, A. P. & Ellegren, H. A wide-range survey of cross-species microsatellite amplification in birds. Mol. Ecol. 5, 365–378 (1996).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    30.Jaroszewicz, B. et al. Białowieża forest—A relic of the high naturalness of European forests. Forests 10, 849 (2019).Article 

    Google Scholar 
    31.Campos, A. R. et al. How do Robins Erithacus rubecula resident in Iberia respond to seasonal flooding by conspecific migrants?. Bird Study 58, 435–442 (2011).Article 

    Google Scholar 
    32.Owen, J. C. Collecting, processing, and storing avian blood: A review. J. Field Ornithol. 82, 339–354 (2011).Article 

    Google Scholar 
    33.Horváth, M. B., Martínez-Cruz, B., Negro, J. J., Kalmár, L. & Godoy, J. A. An overlooked DNA source for non-invasive genetic analysis in birds. J. Avian Biol. 36, 84–88 (2005).Article 

    Google Scholar 
    34.Faircloth, B. C. MSATCOMMANDER: Detection of microsatellite repeat arrays and automated, locus-specific primer design. Mol. Ecol. Resour. 8, 92–94 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    35.Schuelke, M. An economic method for the fluorescent labeling of PCR fragments. Nat. Biotechnol. 18, 233–234 (2000).CAS 
    PubMed 
    Article 

    Google Scholar 
    36.Austin, J. D. et al. Permanent genetic resources added to Molecular Ecology Resources Database 1 February 2011–31 March 2011. Mol. Ecol. Resour. 11, 757–758 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    37.Peakall, R. & Smouse, P. E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update. Bioinformatics 28, 2537–2539 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    38.Raymond, M. & Rousset, F. GENEPOP (version 1.2): Population genetics software for exact tests and ecumenicism. Heredity 86, 248–249 (1995).Article 

    Google Scholar 
    39.Rousset, F. GENEPOP’007: A complete reimplementation of the GENEPOP software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).PubMed 
    Article 

    Google Scholar 
    40.Goudet, J. FSTAT, a program to estimate and test gene diversities and fixation indices, version 2.9.3. http://www.unil.ch/izea/softwares/fstat.htlm (2001).41.Kalinowski, S. T., Taper, M. L. & Marshall, T. C. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 16, 1099–1106 (2007).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    42.Grohme, M. A., Soler, R. F., Wink, M. & Frohme, M. Microsatellite marker discovery using single molecule real-time circular consensus sequencing on the Pacific Biosciences RS. Biotechniques 55, 253–256 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Liljegren, M. M., de Muinck, E. J. & Trosvik, P. Microsatellite length scoring by single molecule real time sequencing-effects of sequence structure and PCR regime. PLoS ONE 11, e0159232 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    44.Dutta, N. et al. Microsatellite marker set for genetic diversity assessment of primitive Chitala chitala (Hamilton, 1822) derived through SMRT sequencing technology. Mol. Biol. Rep. 46, 41–49 (2018).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    45.Selkoe, K. A. & Toonen, R. J. Microsatellites for ecologists: A practical guide to using and evaluating microsatellite markers. Ecol. Lett. 9, 615–629 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    46.Corner, S., Yuzbasiyan-Gurkan, V., Agnew, D. & Venta, P. J. Development of a 12-plex of new microsatellite markers using a novel universal primer method to evaluate the genetic diversity of jaguars (Panthera onca) from North American zoological institutions. Conserv. Genet. Resour. 11, 487–497 (2019).Article 

    Google Scholar 
    47.Graham, B. A., Carpenter, A. M., Friesen, V. L. & Burg, T. M. A comparison of neutral genetic differentiation and genetic diversity among migratory and resident populations of Golden-crowned-Kinglets (Regulus satrapa). J. Ornithol. 161, 509–519 (2020).Article 

    Google Scholar 
    48.Bensch, S., Grahn, M., Müller, N., Gay, L. & Akesson, S. A. Genetic, morphological, and feather isotope variation of migratory willow warblers show gradual divergence in a ring. Mol. Ecol. 18, 3087–3096 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    49.Kralj, J., Procházka, P., Fainová, D., Patzenhauerová, H. & Tutiš, V. Intraspecific variation in the wing shape and genetic differentiation of reed warblers Acrocephalus scirpaceus in Croatia. Acta Ornithol. 45, 51–58 (2010).Article 

    Google Scholar 
    50.Mettler, R. et al. Contrasting patterns of genetic differentiation among blackcaps (Sylvia atricapilla) with divergent migratory orientations in Europe. PLoS ONE 8, e81365 (2013).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    51.Gyllensten, U., Jakonsson, S. & Temrin, H. No evidence for illegitimate young in monogamous and polygynous warblers. Nature 343, 168–170 (1990).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    52.Gil, D., Slater, P. J. B. & Graves, J. A. Extrapair paternity and song characteristics in the willow warbler Phylloscopus trochilus. J. Avian Biol. 38, 291–297 (2007).Article 

    Google Scholar 
    53.Moskalenko, V. N., Belokon, M. M., Belokon, Y. S. & Goretskaia, M. I. Extrapair young in nests of the Wood Warbler (Phylloscopus sibilatrix) in the Middle Russia (poster). In 26th International Ornithological Congress (2014).54.Grendelmeier, A., Arlettaz, R., Olano-Marin, J. & Pasinelli, G. Experimentally provided conspecific cues boost bird territory density but not breeding performance. Behav. Ecol. 28, 174–185 (2017).Article 

    Google Scholar 
    55.Petrie, M. & Kempenaers, B. Extrapair paternity in birds: Explaining variation between species and populations. Trends Ecol. Evol. 13, 52–58 (1998).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    56.Wagner, R. H. Hidden leks: sexual selection and the clustering of avian territories. Ornithol. Monogr. 49, 123–145 (1998).Article 

    Google Scholar 
    57.Fletcher, R. J. & Miller, C. W. On the evolution of hidden leks and the implications for reproductive and habitat selection behaviours. Anim. Behav. 71, 1247–1251 (2006).Article 

    Google Scholar 
    58.Broughton, R. K., Bubnicki, J. W. & Maziarz, M. Multi-scale settlement patterns of a migratory songbird in a European primeval forest. Behav. Ecol. Sociobiol. 74, 1–12 (2020).Article 

    Google Scholar  More

  • in

    Dangerous demographics in post-bleach corals reveal boom-bust versus protracted declines

    1.Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543, 373–377 (2017).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Duarte, C. M. et al. Rebuilding marine life. Nature 580, 39–51 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    3.Darling, E. S. et al. Relationships between structural complexity, coral traits, and reef fish assemblages. Coral Reefs 36, 561–575 (2017).ADS 
    Article 

    Google Scholar 
    4.McWilliam, M., Chase, T. J. & Hoogenboom, M. O. Neighbor diversity regulates the productivity of coral assemblages. Curr. Biol. 28, 3634–3639 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    5.Graham, N. A. J., Jennings, S., MacNeil, M. A., Mouillot, D. & Wilson, S. K. Predicting climate-driven regime shifts versus rebound potential in coral reefs. Nature 518, 94–97 (2015).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.Hughes, T. P. et al. Global warming transforms coral reef assemblages. Nature 556, 492–496 (2018).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.Cornwall, C. E. et al. Global declines in coral reef calcium carbonate production under ocean acidification and warming. Proc. Natl. Acad. Sci. 118, e2015265118 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    8.Gardner, T. A. Long-term region-wide declines in caribbean corals. Science 301, 958–960 (2003).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.De’ath, G., Fabricius, K. E., Sweatman, H. & Puotinen, M. The 27—year decline of coral cover on the Great Barrier Reef and its causes. Proc. Natl. Acad. Sci. USA https://doi.org/10.1073/pnas.1208909109 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    10.Madin, J. S. et al. Cumulative effects of cyclones and bleaching on coral cover and species richness at Lizard Island. Mar. Ecol. Prog. Ser. 604, 263–268 (2018).ADS 
    Article 

    Google Scholar 
    11.Dietzel, A., Bode, M., Connolly, S. R. & Hughes, T. P. Long-term shifts in the colony size structure of coral populations along the Great Barrier Reef: Demographic change in Australia’s corals. Proc. R. Soc. B Biol. Sci. 287, 20201432 (2020).Article 

    Google Scholar 
    12.Claar, D. C. et al. Dynamic symbioses reveal pathways to coral survival through prolonged heatwaves. Nat. Commun. 11, 1–10 (2020).ADS 
    Article 
    CAS 

    Google Scholar 
    13.Claar, D. C. & Baum, J. K. Timing matters: Survey timing during extended heat stress can influence perceptions of coral susceptibility to bleaching. Coral Reefs 38, 559–565 (2019).ADS 
    Article 

    Google Scholar 
    14.Edmunds, P. J. Vital rates of small reef corals are associated with variation in climate. Limnol. Oceanogr. 66, 901–913 (2021).ADS 
    Article 

    Google Scholar 
    15.Hall, T. E. et al. Stony coral populations are more sensitive to changes in vital rates in disturbed environments. Ecol. Appl. 31, 1–11 (2021).Article 

    Google Scholar 
    16.Madin, J. S., Baird, A. H., Dornelas, M. & Connolly, S. R. Mechanical vulnerability explains size-dependent mortality of reef corals. Ecol. Lett. 17, 1008–1015 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    17.Edmunds, P. J. & Riegl, B. Urgent need for coral demography in a world where corals are disappearing. Mar. Ecol. Prog. Ser. 635, 233–242 (2020).ADS 
    Article 

    Google Scholar 
    18.Hughes, T. P. et al. Ecological memory modifies the cumulative impact of recurrent climate extremes. Nat. Clim. Chang. 9, 40–43 (2019).ADS 
    Article 

    Google Scholar 
    19.Pratchett, M. et al. Spatial, temporal and taxonomic variation in coral growth—Implications for the structure and function of coral reef ecosystems. Oceanogr. Mar. Biol. Ann. Rev. 53, 215–295 (2015).
    Google Scholar 
    20.Cantin, N. E. & Lough, J. M. Surviving coral bleaching events: Porites growth anomalies on the great barrier reef. PLoS ONE 9, e88720 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    21.Linares, C., Pratchett, M. S. & Coker, D. J. Recolonisation of Acropora hyacinthus following climate-induced coral bleaching on the Great Barrier Reef. Mar. Ecol. Prog. Ser. 438, 97–104 (2011).ADS 
    Article 

    Google Scholar 
    22.Victor, S., Golbuu, Y., Yukihira, H. & Van Woesik, R. Acropora size-frequency distributions reflect spatially variable conditions on coral reefs of Palau. Bull. Mar. Sci. 85, 149–157 (2009).
    Google Scholar 
    23.Wilson, S. K., Robinson, J. P. W., Chong-Seng, K., Robinson, J. & Graham, N. A. J. Boom and bust of keystone structure on coral reefs. Coral Reefs 38, 625–635 (2019).ADS 
    Article 

    Google Scholar 
    24.Pratchett, M. S., McWilliam, M. J. & Riegl, B. Contrasting shifts in coral assemblages with increasing disturbances. Coral Reefs 39, 783–793 (2020).Article 

    Google Scholar 
    25.Loya, Y. et al. Coral bleaching: The winners and the losers. Ecol. Lett. 4, 122–131 (2001).Article 

    Google Scholar 
    26.Van Woesik, R., Sakai, K., Ganase, A. & Loya, Y. Revisiting the winners and the losers a decade after coral bleaching. Mar. Ecol. Prog. Ser. 434, 67–76 (2011).ADS 
    Article 

    Google Scholar 
    27.McWilliam, M., Pratchett, M. S., Hoogenboom, M. O. & Hughes, T. P. Deficits in functional trait diversity following recovery on coral reefs. Proc. R. Soc. B Biol. Sci. 287, 20192628 (2020).Article 

    Google Scholar 
    28.Marshall, P. A. & Baird, A. H. Bleaching of corals on the Great Barrier Reef: Differential susceptibilities among taxa. Coral Reefs 19, 155–163 (2000).Article 

    Google Scholar 
    29.Graham, N. A. J., Cinner, J. E., Norström, A. V. & Nyström, M. Coral reefs as novel ecosystems: Embracing new futures. Curr. Opin. Environ. Sustain. 7, 9–14 (2014).Article 

    Google Scholar 
    30.Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nat. Commun. 10, 1–5 (2019).CAS 
    Article 

    Google Scholar 
    31.Gilmour, J. P., Smith, L. D., Heyward, A. J., Baird, A. H. & Pratchett, M. S. Recovery of an isolated coral reef system following severe disturbance. Science 340, 69–71 (2013).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    32.Hughes, T. P. et al. Global warming impairs stock–recruitment dynamics of corals. Nature 568, 387–390 (2019).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Vercelloni, J. et al. Forecasting intensifying disturbance effects on coral reefs. Glob. Chang. Biol. 26, 2785–2797 (2020).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Team, R. C. R: A Language and Environment for Statistical Computing. (2020).35.Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378 (2017).Article 

    Google Scholar 
    36.Evans, R. D. et al. Early recovery dynamics of turbid coral reefs after recurring bleaching events. J. Environ. Manag. 268, 110666 (2020).Article 

    Google Scholar 
    37.Carlot, J. et al. Juvenile corals underpin coral reef carbonate production after disturbance. Glob. Chang. Biol. 27, 2623–2632 (2021).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    38.Bellwood, D. R. et al. Coral reef conservation in the Anthropocene: Confronting spatial mismatches and prioritizing functions. Biol. Conserv. 236, 604–615 (2019).Article 

    Google Scholar 
    39.Baird, A., Emslie, M. & Lewis, A. Extended periods of coral recruitment on the Great Barrier Reef. In Proc. 12th Int. Coral Reef Symp. (2012).40.Foster, N. L., Baums, I. B. & Mumby, P. J. Sexual vs. asexual reproduction in an ecosystem engineer: The massive coral Montastraea annularis. J. Anim. Ecol. 76, 384–391 (2007).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    41.Edmunds, P. J. Patterns in the distribution of juvenile corals and coral reef community structure in St. John, US Virgin Islands. Mar. Ecol. Prog. Ser. 202, 113–124 (2000).ADS 
    Article 

    Google Scholar 
    42.Hughes, T. P., Linares, C., Dakos, V., van de Leemput, I. A. & van Nes, E. H. Living dangerously on borrowed time during slow, unrecognized regime shifts. Trends Ecol. Evol. 28, 149–155 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83 (2018).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    44.Wismer, S., Tebbett, S. B., Streit, R. P. & Bellwood, D. R. Spatial mismatch in fish and coral loss following 2016 mass coral bleaching. Sci. Total Environ. 650, 1487–1498 (2019).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    45.Wismer, S., Tebbett, S. B., Streit, R. P. & Bellwood, D. R. Young fishes persist despite coral loss on the Great Barrier Reef. Commun. Biol. 2, 1–7 (2019).Article 

    Google Scholar 
    46.Abràmoff, M. D., Hospitals, I., Magalhães, P. J. & Abràmoff, M. Image processing with ImageJ. Biophotonics Int. 11, 36–42 (2004).
    Google Scholar  More

  • in

    Humpback whale song recordings suggest common feeding ground occupation by multiple populations

    1.Clapham, P. J. Humpback whale: Megaptera novaeangliae. In Encyclopedia of Marine Mammals 489–492 (Elsevier, 2018).Chapter 

    Google Scholar 
    2.Corkeron, P. J. & Connor, R. C. Why do baleen whales migrate?. Mar. Mamm. Sci. 15, 1228–1245 (1999).Article 

    Google Scholar 
    3.Geijer, C. K. A., Notarbartolo di Sciara, G. & Panigada, S. Mysticete migration revisited: Are Mediterranean fin whales an anomaly?. Mamm. Rev. 46, 284–296 (2016).Article 

    Google Scholar 
    4.Baker, C. S. & Herman, L. M. Aggressive behavior between humpback whales (Megaptera novaeangliae) wintering in Hawaiian waters. Can. J. Zool. 62, 1922–1937 (1984).Article 

    Google Scholar 
    5.Herman, L. M. The multiple functions of male song within the humpback whale (Megaptera novaeangliae) mating system: Review, evaluation, and synthesis. Biol. Rev. 92, 1795–1818 (2017).PubMed 
    Article 

    Google Scholar 
    6.Palsbøll, P. J., Clapham, P. J., Mattila, D. K. & Vasquez, O. Composition and dynamics of humpback whale competitive groups in the West Indies. Behaviour 122, 182–194 (1992).Article 

    Google Scholar 
    7.Payne, R. S. & Mcvay, S. Songs of Humpback Whales. Science 173, 585–597 (1971).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    8.Kroodsma, D. E. & Byers, B. E. The function (s) of bird song. Am. Zool. 31, 318–328 (1991).Article 

    Google Scholar 
    9.Garland, E. C. et al. Dynamic horizontal cultural transmission of humpback whale song at the Ocean Basin Scale. Curr. Biol. 21, 687–691 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    10.Noad, M. J. & Cato, D. H. Swimming speeds of singing and non-singing humpback whales during migration. Mar. Mamm. Sci. 23, 481–495 (2007).Article 

    Google Scholar 
    11.Smith, J. N., Goldizen, A. W., Dunlop, R. A. & Noad, M. J. Songs of male humpback whales, Megaptera novaeangliae, are involved in intersexual interactions. Anim. Behav. 76, 467–477 (2008).Article 

    Google Scholar 
    12.Ross-Marsh, E., Elwen, S., Prinsloo, A., James, B. & Gridley, T. Singing in South Africa: Monitoring the occurrence of humpback whale (Megaptera novaeangliae) song near the Western Cape. Bioacoustics 30, 163–179 (2020).Article 

    Google Scholar 
    13.Stimpert, A. K., Peavey, L. E., Friedlaender, A. S. & Nowacek, D. P. Humpback whale song and foraging behavior on an Antarctic feeding ground. PLoS ONE 7, e51214 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    14.Vu, E. T. et al. Humpback whale song occurs extensively on feeding grounds in the western North Atlantic Ocean. Aquat. Biol. 14, 175–183 (2012).Article 

    Google Scholar 
    15.McSweeney, D., Chu, K., Dolphin, W. & Guinee, L. North Pacific humpback whale songs: A comparison of southeast Alaskan feeding ground songs with Hawaiian wintering ground songs. Mar. Mamm. Sci. 5, 139–148 (1989).Article 

    Google Scholar 
    16.Kowarski, K., Evers, C., Moors-Murphy, H., Martin, B. & Denes, S. L. Singing through winter nights: Seasonal and diel occurrence of humpback whale (Megaptera novaeangliae) calls in and around the Gully MPA, offshore eastern Canada. Mar. Mamm. Sci. 34, 169–189 (2018).Article 

    Google Scholar 
    17.Clark, C. W. & Clapham, P. J. Acoustic monitoring on a humpback whale (Megaptera novaeangliae) feeding ground shows continual singing into late spring. Proc. R. Soc. B 271, 1051–1057 (2004).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    18.International Whaling Commission. Report on the workshop on the comprehensive assessment of Southern Hemisphere humpback whales. J. Cetac. Res. Manag. 3, 1–50 (2011).
    Google Scholar 
    19.International Whaling Commission. Annex H: Report of the Sub-Committee on Other Southern Hemisphere Whale Stocks. (2016).20.Garland, E. C. et al. Humpback whale song on the Southern Ocean feeding grounds: Implications for cultural transmission. PLoS ONE 8, e79422 (2013).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    21.Gabriele, C. & Frankel, A. The occurrence and significance of humpback whale songs in Glacier Bay, Southeastern Alaska. Arctic Res. USA 16, 42–47 (2002).
    Google Scholar 
    22.Payne, R. & Guinee, L. Humpback whales (Megaptera novaeangliae) songs as an indicator of stocks. In Communication and Behavior of Whales (ed. Payne, R.) 333–358 (Westview Press, 1983).
    Google Scholar 
    23.Payne, K. & Payne, R. Large scale changes over 19 years in songs of humpback whales in Bermuda. Z. Tierpsychol. 68, 89–114 (1985).Article 

    Google Scholar 
    24.Winn, H. et al. Song of the humpback whale—population comparisons. Behav. Ecol. Sociobiol. 8, 41–46 (1981).Article 

    Google Scholar 
    25.Winn, H. & Winn, L. The song of the humpback whale Megaptera novaeangliae in the West Indies. Mar. Biol. 47, 97–114 (1978).Article 

    Google Scholar 
    26.Cholewiak, D. M., Sousa-Lima, R. S. & Cerchio, S. Humpback whale song hierarchical structure: Historical context and discussion of current classification issues. Mar. Mamm. Sci. 29, E312–E332 (2013).Article 

    Google Scholar 
    27.Kowarski, K., Moors-Murphy, H., Maxner, E. & Cerchio, S. Western North Atlantic humpback whale fall and spring acoustic repertoire: Insight into onset and cessation of singing behavior. J. Acoust. Soc. Am. 145, 2305–2316 (2019).PubMed 
    Article 
    ADS 

    Google Scholar 
    28.Magnúsdóttir, E. E. & Lim, R. Subarctic singers: Humpback whale (Megaptera novaeangliae) song structure and progression from an Icelandic feeding ground during winter. PLoS ONE 14, e0210057 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    29.Magnúsdóttir, E. E. et al. Humpback whale (Megaptera novaeangliae) song unit and phrase repertoire progression on a subarctic feeding ground. J. Acoust. Soc. Am. 138, 3362–3374 (2015).PubMed 
    Article 
    ADS 

    Google Scholar 
    30.Mattila, D. K., Guinee, L. N. & Mayo, C. A. Humpback whale songs on a North Atlantic feeding ground. J. Mammal. 68, 880–883 (1987).Article 

    Google Scholar 
    31.Teschke, K., Pehlke, H., Deininger, M., Jerosch, K. & Brey, T. Scientific Background Document in Support of the Development of a CCAMLR MPA in the Weddell Sea (Antarctica)–Version 2016. (2016).32.Gridley, T., Silva, M., Wilkinson, C., Seakamela, S. & Elwen, S. H. Song recorded near a super-group of humpback whales on a mid-latitude feeding ground off South Africa. J. Acoust. Soc. Am. 143, 298–304 (2018).Article 
    ADS 

    Google Scholar 
    33.Spreen, G., Kaleschke, L. & Heygster, G. Sea ice remote sensing using AMSR-E 89-GHz channels. J. Geophys. Res.-Oceans 113, C02S03 (2008).Article 
    ADS 

    Google Scholar 
    34.Tynan, C. T. & Thiele, D. Report on Antarctic ice edge definition by the ad hoc working group on ice data collection in the Antarctic. Paper: SC/55/19, submitted to the Scientific Committee of the International Whaling Commission (2003).35.Dice, L. R. Measures of the amount of ecologic association between species. Ecology 26, 297–302 (1945).Article 

    Google Scholar 
    36.Kohonen, T. Median strings. Pattern Recogn. Lett. 3, 309–313 (1985).Article 
    ADS 

    Google Scholar 
    37.Schall, E. et al. Multi-year presence of humpback whales in the Atlantic sector of the Southern Ocean but not during El Niño. Commun. Biol. 4, 1–7 (2021).Article 

    Google Scholar 
    38.Ritschard, M. & Brumm, H. Zebra finch song reflects current food availability. Evol. Ecol. 26, 801–812 (2012).Article 

    Google Scholar 
    39.Darling, J. D., Acebes, J. M. V., Frey, O., Urbán, R. J. & Yamaguchi, M. Convergence and divergence of songs suggests ongoing, but annually variable, mixing of humpback whale populations throughout the North Pacific. Sci. Rep. 9, 1–14 (2019).ADS 

    Google Scholar 
    40.Schall, E. et al. Large-scale spatial variabilities in the humpback whale acoustic presence in the Atlantic sector of the Southern Ocean. R. Soc. Open Sci. 7, 201347 (2020).PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    41.Van Opzeeland, I., Van Parijs, S., Kindermann, L., Burkhardt, E. & Boebel, O. Calling in the cold: Pervasive acoustic presence of humpback whales (Megaptera novaeangliae) in Antarctic coastal waters. PLoS ONE 8, 1–7 (2013).
    Google Scholar 
    42.Craig, A. S., Herman, L. M., Gabriele, C. M. & Pack, A. A. Migratory timing of humpback whales (Megaptera novaeangliae) in the central north Pacific varies with age, sex and reproductive status. Behaviour 140, 981–1001 (2003).Article 

    Google Scholar 
    43.Dawbin, W. Temporal segregation of humpback whales during migration in southern hemisphere waters. Mem. Qld. Mus. 42, 105–138 (1997).
    Google Scholar 
    44.Magnúsdóttir, E., Rasmussen, M., Lammers, M. & Svavarsson, J. Humpback whale songs during winter in subarctic waters. Polar Biol. 37, 427–433 (2014).Article 

    Google Scholar 
    45.Bombosch, A. et al. Predictive habitat modelling of humpback (Megaptera novaeangliae) and Antarctic minke (Balaenoptera bonaerensis) whales in the Southern Ocean as a planning tool for seismic surveys. Deep Sea Res. Part 1 91, 101–114 (2014).Article 

    Google Scholar 
    46.Thiele, D. et al. Seasonal variability in whale encounters in the Western Antarctic Peninsula. Deep Sea Research (Part II, Topical Studies in Oceanography) 51, 2311–2325 (2004).Article 
    ADS 

    Google Scholar 
    47.Brown, M. R., Corkeron, P. J., Hale, P. T., Schultz, K. W. & Bryden, M. M. Evidence for a sex-segregated migration in the humpback whale (Megaptera novaeangliae). Proc. R. Soc. Lond. B 259, 229–234 (1995).CAS 
    Article 
    ADS 

    Google Scholar 
    48.McDonald, M. A., Mesnick, S. L. & Hildebrand, J. A. Biogeographic characterisation of blue whale song worldwide: Using song to identify populations. J. Cetac. Res. Manage. 8, 55–65 (2006).
    Google Scholar 
    49.Thomisch, K. et al. Spatio-temporal patterns in acoustic presence and distribution of Antarctic blue whales Balaenoptera musculus intermedia in the Weddell Sea. Endanger. Species Res. 30, 239–253 (2016).Article 

    Google Scholar 
    50.Oleson, E. M., Širović, A., Bayless, A. R. & Hildebr, J. A. Synchronous seasonal change in fin whale song in the North Pacific. PLoS ONE 9, e115678 (2014).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    51.Simon, M., Stafford, K. M., Beedholm, K., Lee, C. M. & Madsen, P. T. Singing behavior of fin whales in the Davis Strait with implications for mating, migration and foraging. J. Acoust. Soc. Am. 128, 3200–3210 (2010).PubMed 
    Article 
    ADS 

    Google Scholar 
    52.Stafford, K. M. et al. Spitsbergen’s endangered bowhead whales sing through the polar night. Endanger. Species Res. 18, 95–103 (2012).Article 

    Google Scholar 
    53.Risch, D. et al. Minke whale acoustic behavior and multi-year seasonal and diel vocalization patterns in Massachusetts Bay, USA. Mar. Ecol. Prog. Ser. 489, 279–295 (2013).Article 
    ADS 

    Google Scholar 
    54.Brenowitz, E. A., Margoliash, D. & Nordeen, K. W. An introduction to birdsong and the avian song system. J. Neurobiol. 33, 495–500 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    55.Tobias, J., Gamarra-Toledo, V., García-Olaechea, D., Pulgarin, P. & Seddon, N. Year-round resource defence and the evolution of male and female song in suboscine birds: Social armaments are mutual ornaments. J. Evol. Biol. 24, 2118–2138 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    56.Vu, E. T., Clark, C., Catelani, K., Kellar, N. M. & Calambokidis, J. Seasonal blubber testosterone concentrations of male humpback whales (Megaptera novaeangliae). Mar. Mam. Sci. 31, 1258–1264 (2015).Article 

    Google Scholar 
    57.Yamada, K. & Soma, M. Diet and birdsong: Short-term nutritional enrichment improves songs of adult Bengalese finch males. J. Avian Biol. 47, 865–870 (2016).Article 

    Google Scholar 
    58.Casagrande, S., Pinxten, R., Zaid, E. & Eens, M. Positive effect of dietary lutein and cholesterol on the undirected song activity of an opportunistic breeder. PeerJ 4, e2512 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    59.Weinrich, M. Humpback whale competitive groups observed on a high-latitude feeding ground. Mar. Mamm. Sci. 11, 251–254 (1995).Article 

    Google Scholar 
    60.Chittleborough, R. The breeding cycle of the female humpback whale, Megaptera nodosa (Bonnaterre). Mar. Freshw. Res. 9, 1–18 (1958).Article 

    Google Scholar 
    61.Chittleborough, R. Studies on the ovaries of the humback whale, Megaptera nodosa (bonnaterre), on the western Australian coast. Mar. Freshw. Res. 5, 35–63 (1954).Article 

    Google Scholar 
    62.Cerchio, S., Jacobsen, J. K. & Norris, T. F. Temporal and geographical variation in songs of humpback whales, Megaptera novaeangliae: Synchronous change in Hawaiian and Mexican breeding assemblages. Anim. Behav. 62, 313–329 (2001).Article 

    Google Scholar 
    63.Garland, E. C. et al. Quantifying humpback whale song sequences to understand the dynamics of song exchange at the ocean basin scale. J. Acoust. Soc. Am. 133, 560–569 (2013).PubMed 
    Article 
    ADS 

    Google Scholar 
    64.Allen, J. A., Garland, E. C., Dunlop, R. A. & Noad, M. J. Cultural revolutions reduce complexity in the songs of humpback whales. Proc. R. Soc. B 285, 20182088 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    65.Stevick, P. T. et al. Migrations of individually identified humpback whales between the Antarctic Peninsula and South America. J. Cetac. Res. Manag. 6, 109–113 (2004).
    Google Scholar 
    66.Engel, M. et al. Mitochondrial DNA diversity of the Southwestern Atlantic humpback whale (Megaptera novaeangliae) breeding area off Brazil, and the potential connections to Antarctic feeding areas. Conserv. Genet. 9, 1253–1262 (2008).CAS 
    Article 

    Google Scholar 
    67.Amaral, A. R. et al. Population genetic structure among feeding aggregations of humpback whales in the Southern Ocean. Mar. Biol. 163, 1–13 (2016).Article 

    Google Scholar 
    68.Rekdahl, M. L. et al. Culturally transmitted song exchange between humpback whales (Megaptera novaeangliae) in the southeast Atlantic and southwest Indian Ocean basins. R. Soc. Open Sci. 5, 172305 (2018).PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    69.Darling, J. D. & Sousa-Lima, R. S. Songs indicate interaction between humpback whale (Megaptera novaeangliae) populations in the western and eastern South Atlantic Ocean. Mar. Mamm. Sci. 21, 557–566 (2005).Article 

    Google Scholar 
    70.Razafindrakoto, Y., Cerchio, S., Collins, T., Rosenbaum, H. & Ngouessono, S. Similarity of humpback whale song from Madagascar and Gabon indicates significant contact between South Atlantic and southwest Indian Ocean populations. PLoS ONE 8, e79422 (2009).
    Google Scholar 
    71.Zerbini, A. et al. Migration and summer destinations of humpback whales (Megaptera novaeangliae) in the western South Atlantic Ocean. J. Cetac. Res. Manag. 3, 113–118 (2011).
    Google Scholar 
    72.Rosenbaum, H. C., Maxwell, S. M., Kershaw, F. & Mate, B. Long-range movement of humpback whales and their overlap with anthropogenic activity in the South Atlantic Ocean. Conserv. Biol. 28, 604–615 (2014).PubMed 
    Article 

    Google Scholar 
    73.Filun, D. et al. Frozen verses: Antarctic minke whales (Balaenoptera bonaerensis) call predominantly during austral winter. R. Soc. Open Sci. 7, 192112 (2020).PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    74.Rettig, S. et al. In International Confence and Exhibition on Underwater Acoustics. (eds Papadakis, J. & Bjorno, L.) 1669–1674.75.Baumgartner, M. F. & Mussoline, S. E. A generalized baleen whale call detection and classification system. J. Acoust. Soc. Am. 129, 2889–2902 (2011).PubMed 
    Article 
    ADS 

    Google Scholar 
    76.Klinck, H. et al. Long-range underwater vocalizations of the crabeater seal (Lobodon carcinophaga). J. Acoust. Soc. Am. 128, 474–479 (2010).PubMed 
    Article 
    ADS 

    Google Scholar 
    77.Risch, D. et al. Mysterious bio-duck sound attributed to the Antarctic minke whale (Balaenoptera bonaerensis). Biol. Lett. 10, 20140175 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    78.Schall, E. & Van Opzeeland, I. Calls produced by Ecotype C killer whales (Orcinus orca) off the Eckstrom iceshelf, Antarctica. Aquat. Mamm. 43, 117–126 (2017).Article 

    Google Scholar 
    79.Van Opzeeland, I. et al. Acoustic ecology of Antarctic pinnipeds. Mar. Ecol. Prog. Ser. 414, 267–291 (2010).Article 
    ADS 

    Google Scholar 
    80.Dunlop, R. A., Cato, D. H. & Noad, M. J. Non-song acoustic communication in migrating humpback whales (Megaptera novaeangliae). Mar. Mamm. Sci. 24, 613–629 (2008).Article 

    Google Scholar 
    81.Stimpert, A. K., Au, W. W., Parks, S. E., Hurst, T. & Wiley, D. N. Common humpback whale (Megaptera novaeangliae) sound types for passive acoustic monitoring. J. Acoust. Soc. Am. 129, 476–482 (2011).PubMed 
    Article 
    ADS 

    Google Scholar 
    82.Cavalieri, D., Parkinson, C., Gloersen, P. & Zwally, H. Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1 (NASA National Snow and Ice Data Center Distributed Active Archive Center, 1996).
    Google Scholar 
    83.Greene, C. A., Gwyther, D. E. & Blankenship, D. D. Antarctic mapping tools for MATLAB. Comput. Geosci. 104, 151–157 (2017).Article 
    ADS 

    Google Scholar 
    84.Greene, C. A. Daily Antarctic Sea Ice Concentration (2020).85.Schall, E., Roca, I. & Van Opzeeland, I. Acoustic metrics to assess humpback whale song unit structure from the Atlantic sector of the Southern ocean. J. Acoust. Soc. Am. 149, 4649–4658 (2021).PubMed 
    Article 
    ADS 

    Google Scholar 
    86.Dalla Rosa, L., Secchi, E., Maia, Y. G., Zerbini, A. & Heide-Jørgensen, M. Movements of satellite-monitored humpback whales on their feeding ground along the Antarctic Peninsula. Polar Biol. 31, 771–781 (2008).Article 

    Google Scholar 
    87.Zann, R. & Cash, E. Developmental stress impairs song complexity but not learning accuracy in non-domesticated zebra finches (Taeniopygia guttata). Behav. Ecol. Sociobiol. 62, 391–400 (2008).Article 

    Google Scholar 
    88.Woodgate, J. L., Mariette, M. M., Bennett, A. T., Griffith, S. C. & Buchanan, K. L. Male song structure predicts reproductive success in a wild zebra finch population. Anim. Behav. 83, 773–781 (2012).Article 

    Google Scholar 
    89.Boogert, N. J., Giraldeau, L.-A. & Lefebvre, L. Song complexity correlates with learning ability in zebra finch males. Anim. Behav. 76, 1735–1741 (2008).Article 

    Google Scholar 
    90.Templeton, C. N., Laland, K. N. & Boogert, N. J. Does song complexity correlate with problem-solving performance in flocks of zebra finches?. Anim. Behav. 92, 63–71 (2014).Article 

    Google Scholar 
    91.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018). https://www.R-project.org/.92.Suzuki, R., Terada, Y. & Shimodaira, H. pvclust: Hierarchical Clustering with P-values via Multiscale Bootstrap Resampling. R Package Version 2.2–0 (2019).93.Garland, E. C. et al. Improved versions of the Levenshtein distance method for comparing sequence information in animals’ vocalisations: Tests using humpback whale song. Behaviour 149, 1413–1441 (2012).Article 

    Google Scholar 
    94.Van der Loo, M. P. The stringdist package for approximate string matching. R J. 6, 111–122 (2014).Article 

    Google Scholar 
    95.Pawlowicz, R. M_Map: A Mapping Package for MATLAB v. Version 1.4m. www.eoas.ubc.ca/~rich/map.html (2020). More

  • in

    Multiyear trend in reproduction underpins interannual variation in gametogenic development of an Antarctic urchin

    1.Takemura, A., Rahman, M. S. & Park, Y. J. External and internal controls of lunar-related reproductive rhythms in fishes. J. Fish Biol. 76, 7–26 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    2.Brockington, S. & Clarke, A. The relative influence of temperature and food on the metabolism of a marine invertebrate. J. Exp. Mar. Bio. Ecol. 258, 87–99 (2001).CAS 
    Article 

    Google Scholar 
    3.Kelly, M. S. Environmental parameters controlling gametogenesis in the echinoid Psammechinus miliaris. J. Exp. Mar. Bio. Ecol. 266, 67–80 (2001).Article 

    Google Scholar 
    4.Muthiga, N. A. The reproductive biology of a new species of sea cucumber, Holothuria (Mertensiothuria) arenacava in a Kenyan marine protected area: The possible role of light and temperature on gametogenesis and spawning. Mar. Biol. 149, 585–593 (2006).Article 

    Google Scholar 
    5.Emilio, L. et al. Is the Orton’s rule still valid? Tropical sponge fecundity, rather than periodicity, is modulated by temperature and other proximal cues. Hydrobiologia 815, 187–205 (2018).Article 

    Google Scholar 
    6.St.Gelais, A. T., Chaves-Fonnegra, A., Moulding, A. L., Kosmynin, V. N. & Gilliam, D. S. Siderastrea siderea spawning and oocyte resorption at high latitude. Invertebr. Reprod. Dev. 60, 212–222 (2016).Article 

    Google Scholar 
    7.Zhadan, P. M., Vaschenko, M. A. & Ryazanov, S. D. Assessing the effect of environmental factors on the spawning activity of the sea urchin Strongylocentrotus intermedius through video recording observations. Mar. Ecol. Prog. Ser. 588, 101–119 (2018).CAS 
    Article 
    ADS 

    Google Scholar 
    8.Grange, L. J., Tyler, P. A., Peck, L. S. & Cornelius, N. Long-term interannual cycles of the gametogenic ecology of the Antarctic brittle star Ophionotus victoriae. Mar. Ecol. Prog. Ser. 278, 141–155 (2004).Article 
    ADS 

    Google Scholar 
    9.Balogh, R., Wolfe, K. & Byrne, M. Gonad development and spawning of the vulnerable commercial sea cucumber, Stichopus herrmanni, in the southern Great Barrier Reef. J. Mar. Biol. Assoc. United Kingdom 99, 487–495 (2019).Article 

    Google Scholar 
    10.Stenseth, N. C. et al. Studying climate effects on ecology through the use of climate indices: The North Atlantic Oscillation, El Niño Southern Oscillation and beyond. Proc. R. Soc. B Biol. Sci. 270, 2087–2096 (2003).Article 

    Google Scholar 
    11.Wood, S. et al. El Nino and coral larval dispersal across the eastern Pacific marine barrier. Nat. Commun. 7, 1 (2016).
    Google Scholar 
    12.Turner, J. The El Niño-Southern Oscillation and Antarctica. Int. J. Climatol. 24, 1–31 (2004).Article 

    Google Scholar 
    13.La, H. S. et al. Zooplankton and micronekton respond to climate fluctuations in the Amundsen Sea polynya, Antarctica.. Sci. Rep. 9, 1–7 (2019).CAS 
    Article 
    ADS 

    Google Scholar 
    14.Xuebin, Z. & Mcphaden, M. J. Eastern equatorial Pacific forcing of ENSO sea surface temperature anomalies. J. Clim. 21, 6070–6079 (2008).Article 
    ADS 

    Google Scholar 
    15.Oliver, E. C. J. et al. Longer and more frequent marine heatwaves over the past century. Nat. Commun. 9, 1–12 (2018).CAS 
    Article 

    Google Scholar 
    16.Ryan, J. P. et al. Causality of an extreme harmful algal bloom in Monterey Bay, California, during the 2014–2016 northeast Pacific warm anomaly. Geophys. Res. Lett. 44, 5571–5579 (2017).Article 
    ADS 

    Google Scholar 
    17.Conde, A. & Prado, M. Changes in phytoplankton vertical distribution during an El Niño event. Ecol. Indic. 90, 201–205 (2018).Article 

    Google Scholar 
    18.Santidrián Tomillo, P. et al. The impacts of extreme El Niño events on sea turtle nesting populations. Clim. Change https://doi.org/10.1007/s10584-020-02658-w (2020).Article 

    Google Scholar 
    19.Wilson, S. K. et al. Climatic forcing and larval dispersal capabilities shape the replenishment of fishes and their habitat-forming biota on a tropical coral reef. Ecol. Evol. 8, 1918–1928 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    20.Welhouse, L., Lazzara, M., Keller, L., Tripoli, G. & Hitchman, M. Composite analysis of the effects of ENSO events on Antarctica. J. Clim. 29, 1797–1808 (2016).Article 
    ADS 

    Google Scholar 
    21.Testa, J. W. et al. Temporal variability in Antarctic marine ecosystems: periodic fluctuations in the phocid seals. Can. J. Fish. Aquat. Sci. 48, 631–639 (1991).Article 

    Google Scholar 
    22.Román-González, A. et al. Analysis of ontogenetic growth trends in two marine Antarctic bivalves Yoldia eightsi and Laternula elliptica: Implications for sclerochronology. Palaeogeogr. Palaeoclimatol. Palaeoecol. 465, 300–306 (2017).Article 

    Google Scholar 
    23.Brown, M. et al. Long-term effect of photoperiod, temperature and feeding regimes on the respiration rates of Antarctic Krill (Euphausia superba). Open J. Mar. Sci. 3, 40–51 (2013).Article 

    Google Scholar 
    24.Ainley, D. G. et al. Decadal trends in abundance, size and condition of Antarctic toothfish in McMurdo Sound, Antarctica, 1972–2011. Fish Fish. 14, 343–363 (2013).Article 

    Google Scholar 
    25.Doney, S. C. et al. Climate Change Impacts on Marine Ecosystems. Ann. Rev. Mar. Sci. 4, 11–37 (2012).PubMed 
    Article 

    Google Scholar 
    26.Peck, L. S. Antarctic Marine Biodiversity: Adaptations, Environments and Responses to Change. Oceanogr. Mar. Biol. An Annu. Rev. 56, 105–236 (2018).Article 

    Google Scholar 
    27.Peck, L. S. A Cold Limit to Adaptation in the Sea. Trends Ecol. Evol. 31, 13–26 (2016).PubMed 
    Article 

    Google Scholar 
    28.Brockington, S., Peck, L. S. & Tyler, P. A. Gametogenesis and gonad mass cycles in the common circumpolar Antarctic echinoid Sterechinus neumayeri. Mar. Ecol. Prog. Ser. 330, 139–147 (2007).Article 
    ADS 

    Google Scholar 
    29.Grange, L. J., Tyler, P. A. & Peck, L. S. Multi-year observations on the gametogenic ecology of the Antarctic seastar Odontaster validus. Mar. Biol. 153, 15–23 (2007).Article 

    Google Scholar 
    30.Brockington, S. The seasonal ecology and physiology of Sterechinus neumayeri (Echinodermata; Echinoidea) at Adelaide Island, Antarctica. PhD thesis The Open University. (2001).31.Bosch, I., Beauchamp, K. A., Steele, M. E. & Pearse, J. S. Development, metamorphosis, and seasonal abundance of embryos and larvae of the Antarctic sea urchin Sterechinus Neumayeri. Biol. Bull. 173, 126–135 (1987).PubMed 
    Article 

    Google Scholar 
    32.Stanwell-Smith, D. & Peck, L. S. Temperature and embryonic development in relation to spawning and field occurrence of larvae of three Antarctic echinoderms. Biol. Bull. 194, 44–52 (1998).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Fogt, R. L., Bromwich, D. H. & Hines, K. M. Understanding the SAM influence on the South Pacific ENSO teleconnection. Clim. Dyn. 36, 1555–1576 (2011).Article 

    Google Scholar 
    34.Kwok, R. & Comiso, J. C. Spatial patterns of variability in Antarctic surface temperature: Connections to the Southern Hemisphere Annular Mode and the Southern Oscillation. Geophys. Res. Lett. 29, 2–5 (2002).
    Google Scholar 
    35.Santamaría-Del-ángel, E. et al. Interannual climate variability in the west antarctic peninsula under austral summer conditions. Remote Sens. 13, 1 (2021).Article 

    Google Scholar 
    36.Montgomery, D. & Peck, E. Introduction to linear regression analysis. (Wiley, 1992).37.Halberg, F., Shankaraiah, K. & Giese, A. The chronobiology of marine invertebrates: methods of analysis. in Reproduction of marine invertebrates, Vol IX. General aspects: seeking unity in diversity 331–384 (The Boxwood Press, 1987).38.Loeb, V. J., Hofmann, E. E., Klinck, J. M., Holm-Hansen, O. & White, W. B. ENSO and variability of the antarctic peninsula pelagic marine ecosystem. Antarct. Sci. 21, 135–148 (2009).Article 
    ADS 

    Google Scholar 
    39.White, W. B., Chen, S. C., Allan, R. J. & Stone, R. C. Positive feedbacks between the Antarctic Circumpolar Wave and the global El Niño-Southern Oscillation wave. J. Geophys. Res. C Ocean. 107, 29–31 (2002).
    Google Scholar 
    40.Saba, G. K. et al. Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula. Nat. Commun. 5, 1–8 (2014).CAS 

    Google Scholar 
    41.Cavanagh, R. D. et al. A synergistic approach for evaluating climate model output for ecological applications. Front. Mar. Sci. 4, 1 (2017).Article 

    Google Scholar 
    42.Vergani, D. F., Labraga, J. C., Stanganelli, Z. B. & Dunn, M. The effects of El Niño-La Niña on reproductive parameters of elephant seals feeding in the Bellingshausen Sea. J. Biogeogr. 35, 248–256 (2008).Article 

    Google Scholar 
    43.Clark, G. F. et al. Light-driven tipping points in polar ecosystems. Glob. Chang. Biol. 19, 3749–3761 (2013).PubMed 
    Article 
    ADS 

    Google Scholar 
    44.Schneider, D. P., Okumura, Y. & Deser, C. Observed Antarctic interannual climate variability and tropical linkages. J. Clim. 25, 4048–4066 (2012).Article 
    ADS 

    Google Scholar 
    45.Yuan, X. ENSO-related impacts on Antarctic sea ice: A synthesis of phenomenon and mechanisms. Antarct. Sci. 16, 415–425 (2004).Article 
    ADS 

    Google Scholar 
    46.Loeb, V. J. & Santora, J. A. Population dynamics of Salpa thompsoni near the Antarctic Peninsula: Growth rates and interannual variations in reproductive activity (1993–2009). Prog. Oceanogr. 96, 93–107 (2012).Article 
    ADS 

    Google Scholar 
    47.Moran, A. L., McAlister, J. S. & Whitehill, E. A. G. Eggs as energy: Revisiting the scaling of egg size and energetic content among echinoderms. Biol. Bull. 224, 184–191 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    48.Gómez-Robles, E. & Saucedo, P. E. Evaluation of quality indices of the gonad and somatic tissues involved in reproduction of the pearl oyster Pinctada mazatlanica with histochemistry and digital image analysis. J. Shellfish Res. 28, 329–335 (2009).Article 

    Google Scholar 
    49.Gómez-Valdez, M., Ocampo, L., Carvalho-Saucedo, L. & Gutiérrez-González, J. Reproductive activity and seasonal variability in the biochemical composition of a pen shell, Atrina maura.. Mar. Ecol. Prog. Ser. 663, 99–113 (2021).Article 
    ADS 
    CAS 

    Google Scholar 
    50.Steinberg, D. K. et al. Long-term (1993–2013) changes in macrozooplankton off the Western Antarctic Peninsula. Deep. Res. Part I Oceanogr. Res. Pap. 101, 54–70 (2015).Article 
    ADS 

    Google Scholar 
    51.Rozema, P. D. et al. Interannual variability in phytoplankton biomass and species composition in northern Marguerite Bay (West Antarctic Peninsula) is governed by both winter sea ice cover and summer stratification. Limnol. Oceanogr. 62, 235–252 (2017).Article 
    ADS 

    Google Scholar 
    52.Starr, M., Himmelman, J. H. & Therriault, J. Direct coupling of marine invertebrate spawning with phytoplankton blooms. Science 247, 1071–1074 (1990).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    53.Harrington, L. H., Walker, C. W. & Lesser, M. P. Stereological analysis of nutritive phagocytes and gametogenic cells during the annual reproductive cycle of the green sea urchin, Strongylocentrotus droebachiensis.. Invertebr. Biol. 126, 202–209 (2007).Article 

    Google Scholar 
    54.Magniez, P. Reproductive cycle of the brooding echinoid Abatus cordatus (Echinodermata) in Kerguelen (Antarctic Ocean): changes in the organ indices, biochemical composition and caloric content of the gonads. Mar. Biol. 74, 55–64 (1983).CAS 
    Article 

    Google Scholar 
    55.Pérez, A. F., Morriconi, E., Boy, C. & Calvo, J. Seasonal changes in energy allocation to somatic and reproductive body components of the common cold temperature sea urchin Loxechinus albus in a Sub-Antarctic environment. Polar Biol. 31, 443–449 (2008).Article 

    Google Scholar 
    56.Hernandez, E., Vázquez, O. A., Torruco, A. & Rahman, M. S. Reproductive cycle and gonadal development of the Atlantic sea urchin Arbacia punctulata in the Gulf of Mexico: changes in nutritive phagocytes in relation to gametogenesis. Mar. Biol. Res. 16, 177–194 (2020).Article 

    Google Scholar 
    57.Bronstein, O., Kroh, A. & Loya, Y. Reproduction of the long-spined sea urchin Diadema setosum in the Gulf of Aqaba – Implications for the use of gonad-indexes. Sci. Rep. 6, 1–11 (2016).Article 
    CAS 

    Google Scholar 
    58.Alturkistani, H. A., Tashkandi, F. M. & Mohammedsaleh, Z. M. Histological Stains: A Literature Review and Case Study. Glob. J. Health Sci. 8, 72–79 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    59.Schindelin, J. et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    60.Rueden, C. T. et al. Image J2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18, 1–26 (2017).Article 
    ADS 

    Google Scholar 
    61.Lau, S. C. Y., Grange, L. J., Peck, L. S. & Reed, A. J. The reproductive ecology of the Antarctic bivalve Aequiyoldia eightsii (Protobranchia: Sareptidae) follows neither Antarctic nor taxonomic patterns. Polar Biol. 41, 1693–1706 (2018).Article 

    Google Scholar 
    62.Reed, A. J., Morris, J. P., Linse, K. & Thatje, S. Reproductive morphology of the deep-sea protobranch bivalves Yoldiella ecaudata, Yoldiella sabrina, and Yoldiella valettei (Yoldiidae) from the Southern Ocean. Polar Biol. 37, 1383–1392 (2014).Article 

    Google Scholar 
    63.Cleveland, W. S. Robust locally weighted regression and smoothing scatterplots. J. Am. Stat. Assoc. 74, 829–836 (1979).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    64.Venables, H. J., Clarke, A. & Meredith, M. P. Wintertime controls on summer stratification and productivity at the western Antarctic Peninsula. Limnol. Oceanogr. 58, 1035–1047 (2013).Article 
    ADS 

    Google Scholar 
    65.Clarke, A., Meredith, M. P., Wallace, M. I., Brandon, M. A. & Thomas, D. N. Seasonal and interannual variability in temperature, chlorophyll and macronutrients in northern Marguerite Bay, Antarctica.. Deep Res. Part II Top. Stud. Oceanogr. 55, 198–206 (2008).
    Google Scholar 
    66.Zuur, A., Ieno, E. N. & Smith, G. M. Analyzing Ecological Data. in Analyzing Ecological Data (ed. M. Gail, K. Krickeberg, J. Samet, A. Tsiatis, W. W.) 23–47 (Springer-Verlag New York, 2007).67.Burnham, K. P. & Anderson, D. R. Model selection and multimodel inference. A practical information-theoretical approach. Model Selection and Multimodel Inference (Springer, 2002). https://doi.org/10.1007/978-0-387-22456-5_768.Fisher, R., Wilson, S. K., Sin, T. M., Lee, A. C. & Langlois, T. J. A simple function for full-subsets multiple regression in ecology with R. Ecol. Evol. 8, 6104–6113 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    69.Wood, S. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. 73, 3–36 (2011).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    70.De Leij, R., Peck, L. S. & Grange, L. J. R code and csv. files. https://doi.org/10.5061/dryad.6q573n5z1 (2021).71.Grange, L. J., Peck, L. S. & Tyler, P. A. Reproductive ecology of the circumpolar Antarctic nemertean Parborlasia corrugatus: No evidence for inter-annual variation. J. Exp. Mar. Bio. Ecol. 404, 98–107 (2011).Article 

    Google Scholar  More

  • in

    Food resources affect territoriality of invasive wild pig sounders with implications for control

    1.Lowe, S., Browne, M., Boudjelas, S. & De Poorter, M. 100 of the world’s worst invasive alien species: A selection from the global invasive species database. In Encyclopedia of Biological Invasions 12 (The Invasive Species Specialist Group (ISSG), Species Survival Commission (SSC), World Conservation Union (IUCN), 2000). https://doi.org/10.1525/9780520948433-159.2.North American Invasive Species Network. The ten most important invasive species or invasive species assemblages in North America in 2015. https://www.bugwoodcloud.org/mura/naisn/assets/File/NAISNPRJan2015.pdf (2015).3.Keuling, O. et al. Eurasian wild boar Sus scrofa (Linnaeus, 1758). in Ecology, Conservation and Management of Wild Pigs and Peccaries (eds. Melleti, M. & Meijaard, E.) 202–233 (Cambridge University Press, 2017).4.Strickland, B. K., Smith, M. D. & Smith, A. L. Wild pig damage to resources. In Invasive Wild Pigs in North America: Ecology, Impacts, and Management (eds VerCauteren, K. C. et al.) 143–174 (RC Press, London, 2020).
    Google Scholar 
    5.Pimental, D. Environmental and economic costs of vertebrate species invasions into the United States. In Managing Vertebrate Invasive Species: Proceedings of an International Symposium (eds. Witmer, G. W., Pitt, W. C. & Fagerstone, K. A.) 2–8 (USDA National Wildlife Research Center, Fort Collins, CO, USA, 2007).6.Ditchkoff, S. S. & Bodenchuk, M. J. Management of wild pigs. In Invasive Wild Pigs in North America: Ecology, Impacts, and Management (eds VerCauteren, K. C. et al.) 175–198 (CRC Press, London, 2020).
    Google Scholar 
    7.Maher, C. R. & Lott, D. F. Definitions of territoriality used in the study of variation in vertebrate spacing systems. Anim. Behav. 49, 1581–1597 (1995).Article 

    Google Scholar 
    8.Bastille-Rousseau, G. et al. Multi-level movement response of invasive wild pigs (Sus scrofa) to removal. Pest Manag. Sci. 77, 85–95 (2021).CAS 
    Article 

    Google Scholar 
    9.Boitani, L., Mattei, L., Nonis, D. & Corsi, F. Spatial and activity patterns of wild boars in Tuscany, Italy. J. Mammal. 75, 600–612 (1994).Article 

    Google Scholar 
    10.Ilse, L. M. & Hellgren, E. C. Resource partitioning in sympatric populations of collared peccaries and feral hogs in southern Texas. J. Mammal. 76, 784–799 (1995).Article 

    Google Scholar 
    11.Gabor, T. M., Hellgren, E. C., Bussche, R. A. V. D. & Silvy, N. J. Demography, sociospatial behaviour and genetics of feral pigs (Sus scrofa) in a semi-arid environment. J. Zool. 247, 311–322 (1999).Article 

    Google Scholar 
    12.Sparklin, B. D., Mitchell, M. S., Hanson, L. B., Jolley, D. B. & Ditchkoff, S. S. Territoriality of feral pigs in a highly persecuted population on Fort Benning, Georgia. J. Wildl. Manag. 73, 497–502 (2009).Article 

    Google Scholar 
    13.Beasley, J. C., Ditchkoff, S. S., Mayer, J. J., Smith, M. D. & VerCauteren, K. C. Research priorities for managing invasive wild pigs in North America. J. Wildl. Manag. 82, 674–681 (2018).Article 

    Google Scholar 
    14.Gray, S. M., Roloff, G. J., Montgomery, R. A., Beasley, J. C. & Pepin, K. M. Wild pig spatial ecology and behavior. In Invasive Wild Pigs in North America: Ecology, Impacts, and Management (eds VerCauteren, K. C. et al.) 33–56 (CRC Press, London, 2020).
    Google Scholar 
    15.Emlen, J. T. Defended area? A critique of the territory concept and of conventional thinking. Ibis 99, 352 (1957).
    Google Scholar 
    16.Kamath, A. & Wesner, A. B. Animal territoriality, property and access: A collaborative exchange between animal behaviour and the social sciences. Anim. Behav. 164, 233–239 (2020).Article 

    Google Scholar 
    17.ESRI. ArcGIS Pro. Environmental Systems Research Institute (2021).18.Mayer, J. J. Wild hog. In Ecology and Management of a Forested Landscape: Fifty Years on the Savannah River Site (eds Kilgo, J. C. & Blake, J. I.) 374–379 (Island Press, Washington, 2005).
    Google Scholar 
    19.Mayer, J. J., Edwards, T. B., Garabedian, J. E. & Kilgo, J. C. Sanitary waste landfill effects on an invasive wild pig population. J. Wildl. Manag. 85, 868–879 (2021).Article 

    Google Scholar 
    20.Royle, J. A., Chandler, R. B., Sollmann, R. & Gardner, B. Spatial Capture-Recapture (Academic Press, Cambridge, 2014).
    Google Scholar 
    21.Kranstauber, B., Kays, R., LaPoint, S. D., Wikelski, M. & Safi, K. A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement. J. Anim. Ecol. 81, 738–746 (2012).Article 

    Google Scholar 
    22.Byrne, M. E., Guthrie, J. D., Hardin, J., Collier, B. A. & Chamberlain, M. J. Evaluating wild Turkey movement ecology: An example using first-passage time analysis. Wildl. Soc. Bull. 38, 407–413 (2014).Article 

    Google Scholar 
    23.Clontz, L. M., Pepin, K. M., VerCauteren, K. C. & Beasley, J. C. Behavioral state resource selection in invasive wild pigs in the Southeastern United States. Sci. Rep. 11, 6924 (2021).CAS 
    Article 
    ADS 

    Google Scholar 
    24.White, G. C. & Garrott, R. A. Analysis of Wildlife Radio-Tracking Data (Academic Press, Cambridge, 1990).
    Google Scholar 
    25.Potts, J. R., Harris, Stephen & Giuggioli, L. Quantifying behavioral changes in territorial animals caused by sudden population declines. Am. Nat. 182, E73–E82 (2013).Article 

    Google Scholar 
    26.Fieberg, J. & Kochanny, C. O. Quantifying home-range overlap: The importance of the utilization distribution. J. Wildl. Manag. 69, 1346–1359 (2005).Article 

    Google Scholar 
    27.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing (2021).28.Schielzeth, H. & Forstmeier, W. Conclusions beyond support: Overconfident estimates in mixed models. Behav. Ecol. 20, 416–420 (2009).Article 

    Google Scholar 
    29.Kay, S. L. et al. Quantifying drivers of wild pig movement across multiple spatial and temporal scales. Mov. Ecol. 5, 14 (2017).Article 

    Google Scholar 
    30.Hurvich, C. M. & Tsai, C.-L. Regression and time series model selection in small samples. Biometrika 76, 297–307 (1989).MathSciNet 
    Article 

    Google Scholar 
    31.Long, J. A., Nelson, T. A., Webb, S. L. & Gee, K. L. A critical examination of indices of dynamic interaction for wildlife telemetry studies. J. Anim. Ecol. 83, 1216–1233 (2014).Article 

    Google Scholar 
    32.Benhamou, S., Valeix, M., Chamaillé-Jammes, S., Macdonald, D. W. & Loveridge, A. J. Movement-based analysis of interactions in African lions. Anim. Behav. 90, 171–180 (2014).Article 

    Google Scholar 
    33.Brotherton, P. N. M., Pemberton, J. M., Komers, P. E. & Malarky, G. Genetic and behavioural evidence of monogamy in a mammal, Kirk’s dik–dik (Madoqua kirkii). Proc. R. Soc. Lond. B Biol. Sci. 264, 675–681 (1997).CAS 
    Article 
    ADS 

    Google Scholar 
    34.Burt, W. H. Territoriality and home range concepts as applied to mammals. J. Mammal. 24, 346–352 (1943).Article 

    Google Scholar 
    35.Cooper, N. W., Sherry, T. W. & Marra, P. P. Modeling three-dimensional space use and overlap in birds. Auk 131, 681–693 (2014).Article 

    Google Scholar 
    36.Millspaugh, J. J., Gitzen, R. A., Kernohan, B. J., Larson, M. A. & Clay, C. L. Comparability of three analytical techniques to assess joint space use. Wildl. Soc. Bull. 32, 148–157 (2004).Article 

    Google Scholar 
    37.Pepin, K. M. et al. Contact heterogeneities in feral swine: Implications for disease management and future research. Ecosphere 7, e01230 (2016).Article 

    Google Scholar 
    38.Yang, A. et al. Effects of social structure and management on risk of disease establishment in wild pigs. J. Anim. Ecol. 90, 820–833 (2021).Article 

    Google Scholar 
    39.Carpenter, F. L. Food abundance and territoriality: To defend or not to defend?. Am. Zool. 27, 387–399 (1987).Article 

    Google Scholar 
    40.Both, C. & Visser, M. E. Density dependence, territoriality, and divisibility of resources: From optimality models to population processes. Am. Nat. 161, 326–336 (2003).Article 

    Google Scholar 
    41.Doncaster, C. P. & Macdonald, D. W. Optimum group size for defending heterogenous distributions of resources: A model applied to red foxes, Vulpes vulpes, Oxford city. J. Theor. Biol. 159, 189–198 (1992).Article 
    ADS 

    Google Scholar 
    42.Krause, J. & Ruxton, G. D. Living in Groups (University Press, Oxford, 2002).
    Google Scholar 
    43.Garabedian, J. E., Moorman, C. E., Peterson, M. N. & Kilgo, J. C. Effects of group size and group density on trade-offs in resource selection by a group-territorial central-place foraging woodpecker. Ibis 162, 477–491 (2020).Article 

    Google Scholar  More