More stories

  • in

    Modeling geographical invasions of Solenopsis invicta influenced by land-use patterns

    This study used comprehensive surveillance data to profile RIFA invasions in time and space on an isolated island. By using this surveillance data, which were collected regularly together with information on land-use in different years, distinctions of RIFA severity can be compared, and RIFA SIRH were therefore identified. Our statistical model decomposed the spatial invasion risk into four geographic and anthropogenic factors: land-use characteristics, distances from RIFA sampling location to the nearest road, and spatial factors. For land use from 2014 to 2017, agricultural land, transportation usage, and land-use change had significantly higher odds of RIFA SIRH than natural land cover. Regarding the distance from the nearest road, RIFA invasions were most likely ( > 60%) to occur within 350 m from the nearest road on the transportation usage land. Meanwhile, it was likely ( > 60%) to have RIFA invasions within 150 m from the nearest road in areas where land-use change had occurred between 2014 and 2016. Finally, the highest risks of RIFA SIRH were identified around the pier area and the area of the earliest RIFA invasions on Kinmen. Our study provided an example showing how RIFA gradually expanded to the entire isolated island.Highest risks for agricultural land, transportation usage, and land-use changeAgricultural landThe vulnerability of agricultural lands to RIFA invasions has been reported in many studies. For example, a review by Apperson and Adams showed that RIFA often infested soybean fields in the United States28. Way and Khoo reviewed the RIFA infestation of crop plants, including sugar cane and cotton29, and indicated that crop invasion by RIFAs was a common occurrence. The study conducted by Stuhler et al. demonstrated that in unthinned patches, RIFA mounds were likely to occur in agricultural lands compared to woodlands in South Carolina30. Thus, the results of our study align with the literature in finding that agricultural land tends to be highly assailable by RIFAs.The large majority of agricultural lands on Kinmen Island include sorghum farms, peanut farms, and other food crop farms31. These farms need to be plowed or cultivated at least twice per year. Therefore, soil disturbances by humans could be the reason for the defenselessness against RIFA invasions. The potential mechanism is that soil disturbances destroy habitats for all living organisms, including RIFA. However, RIFAs reestablished their colonies faster than others30,32. Thus, RIFAs became one of the dominant species in highly disturbed areas. Higher soil disturbances associated with higher RIFA abundances were evidenced by the study by Stuhler et al.30 in which the authors compared the thinned areas to unthinned areas, identifying more RIFA mounds in thinned plots. King and Tschinkel also conducted a field experiment on different levels of soil disturbances. They demonstrated that higher numbers of RIFAs persisted at higher levels of disturbance (i.e., plowing) than at lower levels (i.e., mowing)32.Land for transportation usageThe land-use type for transportation purposes, including roads and ports (i.e., seaports and airports), was also identified as a risk factor for RIFA SIRH in this study (Table 2). Among the 1814 sampling tubes in the transportation area, there were 1768 sampling tubes for roads and 46 for ports. As most of the sampling tubes were set along roads in the present study, it could be deduced that roadsides or road cuts were at risk of being infested by RIFA. This result was in compliance with previous studies in the U.S., showing that areas beside roads such as roadsides and road margins provided suitable habitats for RIFA development11,33,34,35,36,37.Roadsides or road cuts had significant risks of RIFA SIRH in Kinmen, which could be due to frequent disturbances from vehicles. In Kinmen, most roads have only one lane or two narrow lanes. When two vehicles traveling in opposite directions pass each other, they will sometimes take turns or pull over onto the side, resulting in frequent soil disturbance. Roadsides or areas near roads are generally considered highly disturbed10,11,34,38, and narrow and disturbed areas suitable for RIFA establishment were demonstrated by Stiles and Jones12.In addition to disturbances along roads, some vehicles may also transport RIFAs in potted plants and soil. Newly-mated queens may potentially attach to the surface of vehicles and fall during transportation, further facilitating invasions near roadsides. This traffic-related dispersal process has been documented in many plant species39,40,41.Road maintenance could also be a reason for the high risks near roadsides. Road maintenance involves moving soil from one place and adding soil to construction sites. If the transported soil is contaminated by RIFAs, the maintenance areas will likely be occupied by RIFA. A case report by King et al. revealed how RIFA spread to roadsides by road maintenance32.Ports, in addition to roads, are another land type for transportation usages. Our finding was in line with previous studies showing that airports or seaports were common areas of RIFA invasion in Taiwan and neighboring countries. For example, Taoyuan International Airport was considered one of the earliest RIFA infestation locations in Taiwan42,43. RIFAs were also detected in container yards in Taiwan’s Kaohsiung commercial port in 201844. In other Asia–Pacific countries, such as China, South Korea, Japan, and Australia, RIFAs have also been reported at ports in the last decade44,45.Ports in this study consist of one seaport and one airport (Fig. 1). Based on the predicted risk of RIFA SIRH (Fig. 8a), one of the highest risk areas was around Shuitou Pier in Jincheng township (Fig. 1). The Pier area had high risks could be because it is one of the cargo container entrances on Kinmen Island. Shipping cargo containers have been suggested to facilitate the movement of RIFAs from abroad or between domestic ports42,43,44. Container yards can become infested when RIFA-contaminated cargo containers are unloaded44,46. In addition to possible contributions from cargos, the pier area had high risks of invasions, which could be due to environmental conditions. This can be supported by the risk of spatial factors, showing that the Pier area had high risks (Fig. 8c). One of the possible environmental factors could be that floating rubbish tends to accumulate in the Pier area47. Studies have shown that nonnative species, including ants, can travel with marine litter to new locations32,48,49,50,51.The Kinmen Shangyi Airport is the other cargo entrance in Kinmen (Fig. 1). Intuitionally, because of cargo containers, the airport area was expected to have risks similar to those in the pier area; however, the risks of RIFA invasions in the airport area were considerably lower (Fig. 8a). The differences in risks could be due to their cargo carrying capacities. In 2018, the airport had 6778 tons of cargo, but the pier had one million tons of cargo52,53. Differences in the types of cargo between the two locations may also play a role in invasion risks. From 2001 to 2018, the majority of goods arriving at the Pier included building stones and block stones from China53. These products have higher risks of being contaminated by RIFAs than goods such as ferrous articles and eggs arriving from the airport of Taiwan53,54.Land-use changeThe land-use change category was identified as a risk factor for RIFA SIRH in the current study. Among land-use change areas, 61.6% were natural land cover in 2014 but were converted to agricultural land, transportation areas, and artificial structures in 2017, which we designated development-related areas (Fig. 6).As previously mentioned, the reasons why the land-use change category had a high risk of RIFA invasion could be due to anthropogenic disturbances. Taking development-related areas as an example, when natural land cover such as forests are changed to other land usages, the first step may be to remove vegetation by clearcutting or plowing. These activities involve soil or habitat disturbances and could aid in the establishment of RIFA populations55. Then, if lands are changed to build houses or schools (i.e., artificial structures), soil disturbances could also occur during construction activities56. For lands that are changed to transportation usages, moving and adding RIFA-contaminated soil could occur during road construction.Effects of roads on RIFA SIRHDistances to the nearest roads were important for understanding invasion where undergoing land-use change, as well in places used as transportation lands (Fig. 7). These land-use categories share a common feature: roads. Meanwhile, agriculture lands had the greatest level of RIFA SIRH, but did not show interaction with distance to roads (Table 2). This could be because agriculture lands were far from roads as compared to land-use change and transportation lands. The median distances to roads from these three land-use categories supported this speculation. Therefore, from this study, it can be deduced that the roads could play a role to transport RIFAs to areas closer to road (i.e., land-use change and transportation). However, the effects of roads on RIFA SIRH did not appear when the areas away from roads (i.e., agricultural lands).Lowest risk in natural land coverIn the present study, natural land cover were identified as the lowest risk category of RIFA SIRH among the five land-use categories (Fig. 8d). This finding was in line with the study conducted by Brown et al., showing that a high percentage of canopy cover was associated with a low mean number of RIFAs in Texas between 2008 and 201057. In addition, Tschinkel and King investigated longleaf pine forests in Florida in 2012 and found that RIFA had difficulty establishing long-term colonies in the forest35. However, in another longleaf pine forest in Georgia, the ant survey conducted by Stuble et al. revealed that RIFAs were the predominant species in the ant community from 2006 to 200758. Wetlands also had high numbers of RIFAs. In northern Florida, Tschinkel observed that RIFA mounds clustered near pond margins11.Natural land cover in Kinmen had the lowest risk of RIFA invasions, which could be because most areas ( > 75%, data not shown) are forests. The forests are preserved and protected by the Forestry Bureau of Taiwan. Because of protection, forests can avoid most anthropogenic disturbances, such as soil excavation, which are known as one of the factors facilitating RIFA relocation32,59,60. Additionally, the forest environment is cool, humid, and shaded, which are unfavorable environmental conditions for RIFAs1,12,30,34,61,62.Implications of study findings for RIFA management in KinmenPublic communicationsTo date, the Kinmen County Animal and Plant Disease Control Center (KAPCDC) has launched a program aimed at raising public awareness of RIFAs on the island through newspapers, social media, and posters. In addition, for RIFA control, the KAPCDC has listed certified pesticides such as pyriproxyfen and lambda-cyhalothrin for the use of controlling RIFAs on agricultural lands. Nevertheless, our study documented that a greater risk of RIFA invasions still occurred on agricultural lands and lands used for transportation, suggesting communications should target owners of agricultural lands as well as the general public in future campaigns. Many individuals of the general public may not be able to identify ant species, so communications should therefore emphasize the importance of reporting any ant mounds, especially along roads. As different sociodemographic groups react to source information differently, communications have to be tailored to ages and educational levels7. For example, for students in primary school, the study by Madeira et al. showed that by teaching activities including insect specimens and short-film presentations, students increased their awareness of the importance of pest control63. For owners of agricultural lands and workers at ports, educational activities on basic RIFA knowledge and pesticide treatments with suitable communication methods may be needed. Those methods included regular face-to-face discussions on RIFA elimination strategies in the meetings of farmers’ associations or a system sharing updated materials likely to be contaminated with RIFAs64,65.RIFA control personnelTo prioritize resources, according to the findings from this study, we suggest that government staff focus on the controls within 350 m from the nearest road on transportation usage land and within 150 m from the nearest road on the areas where land-use change occurred between 2014 and 2016. The authorities could consider integrated pest management approaches, which include chemical and biological controls, to preserve the local ecosystem66.For agricultural lands, RIFA management mainly relies on awareness and reports from owners, as control personnel cannot perform inspections and intervention on private agricultural lands without the owners’ permissions, Although control personnel cannot directly perform interventions on private land, plant quarantine officers in seaports, which were a high-risk area in this study, can prevent RIFA importation by checking cargos to ensure that RIFAs are not stowaways on materials such as plants, rocks, and soil. More

  • in

    Search performance and octopamine neuronal signaling mediate parasitoid induced changes in Drosophila oviposition behavior

    Diverse oviposition rates of Drosophila females after long exposure to waspsTo investigate whether D. melanogaster change oviposition behavior when they cohabit with Lb female wasps, we designed an experimental procedure and monitored egg laying for a much longer time than in previous experiments – approximately 20 days. Specifically, twenty 3-day-old female and five 3-day-old male D. melanogaster adults were placed in standard fly bottles containing fly food dishes. Flies were housed with twenty 2-day-old Lb female wasps (exposed) or without any female wasps (unexposed). The fly food dishes were replaced daily, and fly eggs were counted daily (Fig. 1a). Consistent with previous observations24, the exposed Drosophila females had significantly reduced oviposition numbers compared to the unexposed flies (Fig. 1b). This response lasted approximately 6 days in the presence of Lb females. After that, we surprisingly found that the number of eggs laid by the exposed flies did not differ from the numbers laid by the unexposed controls (Fig. 1b). This variation led us to speculate that this decreased oviposition may have been induced by the diverse life-threatening pressure when D. melanogaster females encounter different aged wasps, as old ones present less danger to their offspring28,29, or simply indicate that the flies become habituated to the constant presence of wasps.Fig. 1: D. melanogaster oviposition rates are altered in the presence of young Lb females.a Standard oviposition assay design. Each bottle contained twenty Canton-S (CS) female flies and five CS male flies, either with twenty female Lb wasps (exposed) or with no wasps (unexposed). Flies aged 3 days post-eclosion and wasps aged 2 days post-emergence were used. The food dishes were replaced daily, and the eggs laid each day were counted. b The daily number of eggs laid by the unexposed and exposed CS flies. Flies were exposed to wasps for 20 days. The experiment was performed eighteen times. Data represent the mean ± SEM. Significance was determined by two-way ANOVA with Sidak’s multiple comparisons test, p values are indicated in Source Data file (***p  More

  • in

    Warmth signals male growth

    Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Impacts on tourism demand

    Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Last glacial loess dynamics in the Southern Caucasus (NE-Armenia) and the phenomenon of missing loess deposition during MIS-2

    Lehmkuhl, F. et al. Loess landscapes of Europe-mapping, geomorphology, and zonal differentiation. Earth-Sci. Rev. 215, 103496 (2021).Article 

    Google Scholar 
    Li, Y., Shi, W., Aydin, A., Beroya-Eitner, M. A. & Gao, G. Loess genesis and worldwide distribution. Earth Sci. Rev. 201, 102947 (2020).Article 

    Google Scholar 
    Moine, O. et al. The impact of last Glacial climate variability in west-European loess revealed by radiocarbon dating of fossil earthworm granules. PNAS 114, 6209–6214 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Újvári, G. et al. Coupled European and Greenland last glacial dust activity driven by North Atlantic climate. PNAS 114, E10632–E10638 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Rousseau, D.-D. et al. Link between European and North Atlantic abrupt climate changes over the last glaciation. Geophys. Res. Lett. 34, L22713 (2007).ADS 
    Article 

    Google Scholar 
    Rousseau, D.-D. et al. Eurasian contribution to the last glacial dust cycle: how are loess sequences built?. Clim. Past. 13, 1181–1197 (2017).Article 

    Google Scholar 
    Fischer, P. et al. Millennial-scale terrestrial ecosystem responses to Upper Pleistocene climatic changes: 4D-reconstruction of the Schwalbenberg Loess-Palaeosol-Sequence (Middle Rhine Valley, Germany). CATENA 196, 104913 (2021).Article 

    Google Scholar 
    Wolf, D. et al. Evidence for strong relations between the Upper Tagus Loess Formation (Central Iberia) and the marine atmosphere off the Iberian Margin during the Last Glacial Period. Quat. Res. 101, 84–113 (2021).Article 

    Google Scholar 
    Porter, S. & An, Z. Correlation between climate events in the North Atlantic and China during the last glaciation. Nature 375, 305–308 (1995).ADS 
    CAS 
    Article 

    Google Scholar 
    Sun, Y. et al. Influence of Atlantic meridional overturning circulation on the East Asian winter monsoon. Nat. Geosci. 5, 46–49 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Zeeden, C. et al. Patterns and timing of loess-palaeosol transitions in Eurasia: Constraints for palaeoclimate studies. Glob. Planet. Change 162, 1–7 (2018).ADS 
    Article 

    Google Scholar 
    Cheng, H. et al. The climatic cyclicity in semiarid-arid central Asia over the past 500,000 years. Geophys. Res. Lett. 39, L01705 (2012).ADS 
    Article 

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

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

    Google Scholar 
    Youn, J. H., Seong, Y. B., Choi, J. H., Abdrakhmatov, K. & Ormukov, C. Loess deposits in the northern Kyrgyz Tien Shan: Implications for the paleoclimate reconstruction during the Late Quaternary. CATENA 117, 81–93 (2014).Article 

    Google Scholar 
    Li, Y. et al. Eolian dust dispersal patterns since the last glacial period in eastern Central Asia: Insights from a loess-paleosol sequence in the Ili Basin. Clim. Past 14, 271–286 (2018).Article 

    Google Scholar 
    Frechen, M., Oches, E. A. & Kohfeld, K. E. Loess in Europe—Mass accumulation rates during the Last Glacial Period. Quat. Sci. Rev. 22, 1835–1857 (2003).ADS 
    Article 

    Google Scholar 
    Antoine, P. et al. High resolution record of the last climatic cycle in the southern carpathian basin at Surduk (vojvodina, Serbia). Quat. Int. 198, 19–36 (2009).MathSciNet 
    Article 

    Google Scholar 
    Antoine, P. et al. Upper Pleistocene loess-palaeosols records from Northern France in the European context: Environmental background and dating of the Middle Palaeolithic. Quat. Int. 411, 4–24 (2016).Article 

    Google Scholar 
    Kang, S., Roberts, H. M., Wang, X., An, Z. S. & Wang, M. Mass accumulation rate changes in Chinese loess during MIS 2, and asynchrony with records from Greenland ice cores and North Pacific Ocean sediments during the last glacial maximum. Aeol. Res. 19, 251–258 (2015).Article 

    Google Scholar 
    Fitzsimmons, K. E. et al. Loess accumulation in the Tian Shan piedmont: Implications for palaeoenvironmental change in arid Central Asia. Quat. Int. 469, 30–43 (2018).Article 

    Google Scholar 
    Li, Y., Song, Y., Qiang, M., Miao, Y. & Zeng, M. Atmospheric dust variations in the Ili Basin, northwest China, during the last glacial period as revealed by a high mountain loess-paleosol sequence. J. Geophys. Res. Atmos. 124, 8449–8466 (2019).ADS 
    Article 

    Google Scholar 
    Pinto, J. G. & Ludwig, P. Extratropical cyclones over the North Atlantic and western Europe during the last glacial maximum and implications for proxy interpretation. Clim. Past 16, 611–626 (2020).Article 

    Google Scholar 
    Cheng, L. et al. Drivers for asynchronous patterns of dust accumulation in central and eastern Asia and in Greenland during the Last Glacial Maximum. Geophys. Res. Lett. 48, e2020GL01194 (2021).
    Google Scholar 
    Fenn, K. et al. A tale of two signals: Global and local influences on the Late Pleistocene loess sequences in Bulgarian Lower Danube. Quat. Sci. Rev. 274, 107264 (2021).Article 

    Google Scholar 
    Song, Y. et al. Spatio-temporal distribution of Quaternary loess across Central Asia. Palaeogeogr. Palaeoclim. Palaeoecol. 567, 110279 (2021).ADS 
    Article 

    Google Scholar 
    Hughes, P. D. & Gibbard, P. L. A stratigraphical basis for the Last Glacial Maximum (LGM). Quat. Int. 383, 174–185 (2015).Article 

    Google Scholar 
    Baykal, Y. et al. Detrital zircon U-Pb age analysis of last glacial loess sources and proglacial sediment dynamics in the Northern European Plain. Quat. Sci. Rev. 274, 107265 (2021).Article 

    Google Scholar 
    Pötter, S. et al. Disentangling sedimentary pathways for the Pleniglacial Lower Danube loess based on geochemical signatures. Front. Earth Sci. 9, 150 (2021).ADS 
    Article 

    Google Scholar 
    Prud’homme, C. et al. δ13C signal of earthworm calcite granules: A new proxy for palaeoprecipitation reconstructions during the Last Glacial in western Europe. Quat. Sci. Rev. 179, 158–166 (2018).ADS 
    Article 

    Google Scholar 
    Obreht, I. et al. A critical reevaluation of palaeoclimate proxy records from loess in the Carpathian Basin. Earth-Sci. Rev. 190, 498–520 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Joannin, S. et al. Vegetation, fire and climate history of the Lesser Caucasus: A new Holocene record from Zarishat fen (Armenia). J. Quat. Sci. 29, 70–82 (2014).Article 

    Google Scholar 
    Brittingham, A. et al. Influence of the north atlantic oscillation on δD and δ18O in meteoric water in the Armenian highland. J. Hydrol. 575, 513–522 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Bohn, U., Zazanashvili, N. & Nakhutsrishvili, G. The map of the natural vegetation of Europe and its application in the caucasus ecoregion. Bull. Georgian Natl. Acad. Sci. 175, 112–121 (2007).
    Google Scholar 
    Trigui, Y. et al. First calibration and application of leaf wax n-alkane biomarkers in Loess-Paleosol sequences and modern plants and soils in Armenia. Geosciences 9, 263 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Richter, C. et al. New insights into southern Caucasian glacial-interglacial climate conditions inferred from Quaternary Gastropod Fauna. J. Quat. Sci. 35, 634–649 (2020).Article 

    Google Scholar 
    Kharzyan, E. Geological Map of Republic of Armenia (Ministry of Nature Protection of Republic of Armenia, 2005).
    Google Scholar 
    Sosson, M. et al. Subductions, obduction and collision in the Lesser Caucasus (Armenia, Azerbaijan, Georgia), new insights. Geol. Soc. Spec. Publ. 340, 329–352 (2010).ADS 
    Article 

    Google Scholar 
    Lomax, J. et al. Testing post-IR-IRSL dating on Armenian loess palaeosol sections against independent age control. Quat. Geochron. 69, 101265 (2021).Article 

    Google Scholar 
    Újvári, G., Kovács, J., Varga, G., Raucsik, B. & Markovic, S. B. Dust flux estimates for the Last Glacial Period in East Central Europe based on terrestrial records of loess deposits: A review. Quat. Sci. Rev. 29, 3157–3166 (2010).ADS 
    Article 

    Google Scholar 
    Rudnick, R. L. & Gao, S. Composition of the continental crust. In The Crust (ed. Rudnick, R. L.) 1–64 (Elsevier-Pergamon, 2003).
    Google Scholar 
    Újvári, G., Varga, A. & Balogh-Brunstad, Z. Origin, weathering, and geochemical composition of loess in southwestern Hungary. Quat. Res. 69, 421–437 (2008).Article 
    CAS 

    Google Scholar 
    Galoyan, G. et al. Geology, geochemistry and 40Ar/39Ar dating of Sevan ophiolites (Lesser Caucasus, Armenia): Evidence for Jurassic Back-arc opening and hot spot event between the South Armenian Block and Eurasia. J. Asian Earth Sci. 34, 135–153 (2009).ADS 
    Article 

    Google Scholar 
    Hässig, M. et al. New structural and petrological data on the Amasia ophiolites (NW Sevan-Akera suture zone, Lesser Caucasus): Insights for a large-scale obduction in Armenia and NE Turkey. Tectonophysics 588, 135–153 (2013).ADS 
    Article 
    CAS 

    Google Scholar 
    Sahakyan, L. et al. Geochemistry of the Eocene magmatic rocks from the Lesser Caucasus area (Armenia): Evidence of a subduction geodynamic environment. in Tectonic Evolution of the Eastern Black Sea and Caucasus (eds. Sosson, M., Stephenson, R. A., Adamia, S. A.). Geological Society Special Publication. Vol. 428. (2016).Obreht, I. et al. Tracing the influence of Mediterranean climate on Southeastern Europe during the past 350,000 years. Sci. Rep. 6, 36334 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Profe, J., Wacha, L., Frechen, M., Ohlendorf, C. & Zolitschka, B. XRF scanning of discrete samples—A chemostratigraphic approach exemplified for loess-paleosol sequences from the Island of Susak, Croatia. Quat. Int. 494, 34–51 (2018).Article 

    Google Scholar 
    Profe, J., Zolitschka, B., Schirmer, W., Frechen, M. & Ohlendorf, C. Geochemistry unravels MIS3/2 paleoenvironmental dynamics at the loess-paleosol sequence Schwalbenberg II, Germany. Palaeogeogr. Palaeoclim. Palaeoecol. 459, 537–551 (2016).ADS 
    Article 

    Google Scholar 
    Zeeden, C. et al. Three climatic cycles recorded in a loess-palaeosol sequence at Semlac (Romania)—Implications for dust accumulation in south-eastern Europe. Quat. Sci. Rev. 154, 130–142 (2016).ADS 
    Article 

    Google Scholar 
    Song, Y. et al. Magnetic stratigraphy of the Danube loess: A composite Titel-Stari Slankamen loess section over the last one million years in Vojvodina, Serbia. J. Asian Earth Sci. 155, 68–80 (2018).ADS 
    Article 

    Google Scholar 
    Rouzaut, S. & Orgeira, M. J. Influence of volcanic glass on the magnetic signal of different paleosols in Córdoba, Argentina. Stud. Geophys. Geod. 61, 361–384 (2017).ADS 
    Article 

    Google Scholar 
    Campodonico, V. A., Rouzaut, S. & Pasquini, A. I. Geochemistry of a Late Quaternary loess-paleosol sequence in central Argentina: Implications for weathering, sedimentary recycling and provenance. Geoderma 351, 235–249 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Wolf, D. et al. Loess in Armenia—Stratigraphic findings and palaeoenvironmental indications. Proc. Geol. Assoc. 127, 29–39 (2016).Article 

    Google Scholar 
    Buggle, B. et al. Iron mineralogical proxies and Quaternary climate change in SE-European Loess–Paleosol sequences. CATENA 117, 4–22 (2014).CAS 
    Article 

    Google Scholar 
    Bradák, B. et al. Magnetic susceptibility in the European Loess Belt: New and existing models of magnetic enhancement in Loess. Palaeogeogr. Palaeoclim. Palaeoecol. 569, 110329 (2021).ADS 
    Article 

    Google Scholar 
    Laag, C. et al. A detailed paleoclimate proxy record for the Middle Danube Basin over the Last 430 kyr: A rock magnetic and colorimetric study of the Zemun loess-paleosol sequence. Front. Earth Sci. 9, 600086 (2021).ADS 
    Article 

    Google Scholar 
    Baumgart, P., Hambach, U., Meszner, S. & Faust, D. An environmental magnetic fingerprint of periglacial loess: Records of Late Pleistocene loess–palaeosol sequences from eastern Germany. Quat. Int. 296, 82–93 (2013).Article 

    Google Scholar 
    Boers, N., Ghil, M. & Rousseau, D.-D. Ocean circulation, ice shelf, and sea ice interactions explain Dansgaard-Oeschger cycles. PNAS 115, E11005–E11014 (2018).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Menviel, L. C., Skinner, L. C., Tarasov, L. & Tzedakis, P. C. An ice–climate oscillatory framework for Dansgaard-Oeschger cycles. Nat. Rev. Earth Environ. 1, 677–693 (2020).ADS 
    Article 

    Google Scholar 
    Rasmussen, S. O. et al. A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy. Quat. Sci. Rev. 106, 14–28 (2014).ADS 
    Article 

    Google Scholar 
    Martrat, B. et al. Four climate cycles ofrecurring deep and surface water destabilizations on the Iberian margin. Science 317, 502–507 (2007).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Broecker, W. S. Massive iceberg discharges as triggers for global climate change. Nature 372, 421–424 (1994).ADS 
    CAS 
    Article 

    Google Scholar 
    Jin, L., Chen, F., Ganopolski, A. & Claussen, M. Response of East Asian climate to Dansgaard/Oeschger and Heinrich events in a coupled model of intermediate complexity. J. Geophys. Res. 112, D06117 (2007).ADS 

    Google Scholar 
    Sun, Y., Wang, X., Liu, Q. & Clemens, S. C. Impacts of post-depositional processes on rapid monsoon signals recorded by the last glacial loess deposits of northern China. Earth Planet. Sci. Lett. 289, 171–179 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    Yang, S. & Ding, Z. A 249 kyr stack of eight loess grain size records from northern China documenting millennial-scale climate variability. Geochem. Geophys. Geosyst. 15, 798–814 (2014).ADS 
    Article 

    Google Scholar 
    Obreht, I. et al. Shift of large-scale atmospheric systems over Europe during late MIS 3 and implications for modern human dispersal. Sci. Rep. 7, 5848 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Antoine, P. et al. Evidence of rapid and cyclic eolian deposition during the Last Glacial in European loess series (Loess events): The high-resolution records from Nussloch (Germany). Quat. Sci. Rev. 28, 2955–2973 (2009).ADS 
    Article 

    Google Scholar 
    Rousseau, D. D. et al. North Atlantic abrupt climatic events of the last glacial period recorded in Ukrainian loess deposits. Clim. Past 7, 221–234 (2011).Article 

    Google Scholar 
    Machalett, B. et al. Aeolian dust dynamics in Central Asia during the Pleistocene: driven by the long-term migration, seasonality and permanency of the Asiatic polar front. Geophys. Geochem. Geosyst. 9, Q08Q09 (2008).Article 
    CAS 

    Google Scholar 
    Berger, A. & Loutre, M. F. Insolation values for the climate of the last 10 million years. Quat. Sci. Rev. 10, 297–317 (1991).ADS 
    Article 

    Google Scholar 
    Kutzbach, J., Chen, G., Cheng, H., Edwards, R. & Liu, Z. Potential role of winter rainfall in explaining increased moisture in the Mediterranean and Middle East during periods of maximum orbitally-forced insolation seasonality. Clim. Dynam. 42, 1079–1095 (2014).ADS 
    Article 

    Google Scholar 
    Marković, S. B. et al. Danube loess stratigraphy—Towards a pan-European loess stratigraphic model. Earth Sci. Rev. 148, 228–258 (2015).ADS 
    Article 

    Google Scholar 
    Li, G. et al. Paleoenvironmental changes recorded in a luminescence dated loess/paleosol sequence from the Tianshan Mountains, arid central Asia, since the penultimate glaciation. Earth Planet. Sci. Lett. 448, 1–12 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Lomax, J. et al. A luminescence-based chronology for the Harletz Loess sequence, Bulgaria. Boreas 48, 179–194 (2019).Article 

    Google Scholar 
    Kehl, M. et al. Pleistocene dynamics of dust accumulation and soil formation in the southern Caspian Lowlands—New insights from the loess-paleosol sequence at Neka-Abelou, northern Iran. Quat. Sci. Rev. 253, 106774 (2021).Article 

    Google Scholar 
    Ganopolski, A., Calov, R. & Claussen, M. Simulation of the last glacial cycle with a coupled climate ice-sheet model of intermediate complexity. Clim. Past 6, 229–244 (2010).Article 

    Google Scholar 
    Malinsky-Buller, A. et al. Evidence for Middle Palaeolithic occupation and landscape change in central Armenia at the open-air site of Alapars-1. Quat. Res. 99, 223–247 (2021).Article 

    Google Scholar 
    Rao, Z. et al. High-resolution summer precipitation variations in the western Chinese Loess Plateau during the last glacial. Sci. Rep. 3, 2785 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stevens, T., Marković, S. B., Zech, M., Hambach, U. & Sümegi, P. Dust deposition and climate in the Carpathian Basin over an independently dated last glacial-interglacial cycle. Quat. Sci. Rev. 30, 662–681 (2011).ADS 
    Article 

    Google Scholar 
    Torfstein, A., Goldstein, S. L., Stein, M. & Enzel, Y. Impacts of abrupt climate changes in the Levant from Last Glacial Dead Sea levels. Quat. Sci. Rev. 69, 1–7 (2013).ADS 
    Article 

    Google Scholar 
    Pickarski, N., Kwiecien, O., Langgut, D. & Litt, T. Abrupt climate and vegetation variability of eastern Anatolia during the last glacial. Clim. Past 11, 1491–1505 (2015).Article 

    Google Scholar 
    Wegwerth, A. et al. Northern hemisphere climate control on the environmental dynamics in the glacial Black Sea “Lake”. Quat. Sci. Rev. 135, 41–53 (2016).ADS 
    Article 

    Google Scholar 
    Ollivier, V., Fontugne, M. & Lyonnet, B. Geomorphic response and 14C chronology of base-level changes induced by Late Quaternary Caspian Sea mobility (middle Kura Valley, Azerbaijan). Geomorphology 230, 109–124 (2015).ADS 
    Article 

    Google Scholar 
    Egeland, C. P. et al. Bagratashen 1, a stratified open-air Middle Paleolithic site in the Debed river valley of northeastern Armenia: A preliminary report. Archaeol. Res. Asia 8, 1–20 (2016).Article 

    Google Scholar 
    von Suchodoletz, H., Gärtner, A., Zielhofer, C. & Faust, D. Eemian and post-Eemian fluvial dynamics in the Lesser Caucasus. Quat. Sci. Rev. 191, 189–203 (2018).ADS 
    Article 

    Google Scholar 
    Langbein, W. B. & Schumm, S. A. Yield of sediment in relation to mean annual precipitation. Trans. Am. Geophys. Union 39, 1076–1084 (1958).ADS 
    Article 

    Google Scholar 
    Wolman, M. G. & Miller, J. P. Magnitude and frequency of forces in geomorphic processes. J. Geol. 68, 54–74 (1960).ADS 
    Article 

    Google Scholar 
    Svirčev, Z. et al. Importance of biological loess crusts for loess formation in semi-arid environments. Quat. Int. 296, 206–215 (2013).Article 

    Google Scholar 
    Reber, R. et al. Glacier advances in northeastern Turkey before and during the global Last Glacial Maximum. Quat. Sci. Rev. 101, 177–192 (2014).ADS 
    Article 

    Google Scholar 
    Ammann, C., Jenny, B., Kammer, K. & Messerli, B. Late Quaternary glacier response to humidity changes in the arid Andes of Chile (18–29 °S). Palaeogeogr. Palaeoclim. Palaeoecol. 172, 313–326 (2001).ADS 
    Article 

    Google Scholar 
    Domínguez-Villar, D. et al. Early maximum extent of paleoglaciers from Mediterranean mountains during the last glaciation. Sci. Rep. 3, 2034 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Spötl, C. et al. Increased autumn and winter precipitation during the Last Glacial Maximum in the European Alps. Nat. Commun. 12, 1839 (2021).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Shumilovskikh, L. S. et al. Orbital and millennial-scale environmental changes between 64 and 20 ka BP recorded in Black Sea sediments. Clim. Past 10, 939–954 (2014).Article 

    Google Scholar 
    Wegwerth, A. et al. Black Sea temperature response to glacial millennial-scale climate variability. Geophys. Res. Lett. 42, 8147–8154 (2015).ADS 
    Article 

    Google Scholar 
    Sarıkaya, M. A., Zreda, M., Çiner, A. & Zweck, C. Cold and wet Last Glacial Maximum on Mount Sandıras, SW Turkey, inferred from cosmogenic dating and glacier modeling. Quat. Sci. Rev. 27, 769–780 (2008).ADS 
    Article 

    Google Scholar 
    Lézine, A.-M. et al. Lake Ohrid, Albania, provides an exceptional multi-proxy record of environmental changes during the last glacial–interglacial cycle. Palaeogeogr. Palaeoclim. Palaeoecol. 287, 116–127 (2010).ADS 
    Article 

    Google Scholar 
    Tecsa, V. et al. Revisiting the chronostratigraphy of late Pleistocene loess-paleosol sequences in southwestern Ukraine: OSL dating of Kurortne section. Quat. Int. 542, 65–79 (2020).Article 

    Google Scholar 
    Luetscher, M. et al. North Atlantic storm track changes during the Last Glacial Maximum recorded by Alpine speleothems. Nat. Commun. 6, 6344 (2015).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Ludwig, P., Schaffernicht, E. J., Shao, Y. & Pinto, J. G. Regional atmospheric circulation over Europe during the Last Glacial Maximum and its links to precipitation. J. Geophys. Res.-Atmos. 121, 2130–2145 (2016).ADS 
    Article 

    Google Scholar 
    Schaffernicht, E. J., Ludwig, P. & Shao, Y. Linkage between dust cycle and loess of the last glacial maximum in Europe. Atmos. Chem. Phys. 20, 4969–4986 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    Beghin, P. et al. What drives LGM precipitation over the western Mediterranean? A study focused on the Iberian Peninsula and northern Morocco. Clim. Dyn. 46, 2611–2631 (2016).Article 

    Google Scholar 
    Sümegi, P. et al. Vegetation and land snail-based reconstruction of the palaeocological changes in the forest steppe eco-region of the Carpathian Basin during last glacial warming. Glob. Ecol. Conserv. 33, e01976 (2022).Article 

    Google Scholar 
    Chen, J. et al. Revisiting Late Pleistocene Loess-Paleosol sequences in the Azov Sea Region of Russia: Chronostratigraphy and paleoenvironmental record. Front. Earth Sci. 9, 808157 (2022).Article 

    Google Scholar 
    Xepos, S. Analysis of trace elements in geological materials, soils and sludges. Spectro XRF Rep. 193, 1–5 (2007).
    Google Scholar 
    Buggle, B. et al. Geochemical characterization and origin of Southeastern and Eastern European loesses (Serbia, Romania, Ukraine). Quat. Sci. Rev. 27, 1058–1075 (2008).ADS 
    Article 

    Google Scholar 
    Weltje, G. J. & Tjallingii, R. Calibration of XRF core scanners for quantitative geochemical logging of sediment cores: Theory and application. Earth Planet. Sci. Lett. 274, 423–438 (2008).ADS 
    CAS 
    Article 

    Google Scholar 
    Dearing, J. Environmental Magnetic Susceptibility: Using the Bartington MS2 System (Chi Publishing, 1999).
    Google Scholar 
    Buylaert, J., Murray, A. S., Thomsen, K. J. & Jain, M. Testing the potential of an elevated temperature IRSL signal from K-feldspar. Radiat. Meas. 44, 560–565 (2009).CAS 
    Article 

    Google Scholar 
    Lomax, J. et al. Establishing a luminescence-based chronostratigraphy for the Last Glacial-interglacial cycle of the Loess-Palaeosol sequence Achajur (Armenia). Front. Earth Sci. 9, 755084 (2021).Article 

    Google Scholar 
    Lamothe, M., Auclair, M., Hamzaoui, C. & Huot, S. Towards a prediction of long-term anomalous fading of feldspar IRSL. Radiat. Meas. 37, 493–498 (2003).CAS 
    Article 

    Google Scholar 
    Tudyka, K. et al. Increased dose rate precision in combined α and β counting in the μDose system—A probabilistic approach to data analysis. Radiat. Meas. 134, 106310 (2020).CAS 
    Article 

    Google Scholar 
    Kolb, T. et al. The µDose-system: Determination of environmental dose rates by combined alpha and beta counting—Performance tests and practical experiences. GChron 4, 1–31 (2021).ADS 

    Google Scholar 
    Durcan, J. A., King, G. & Duller, G. DRAC: Dose rate and age calculator for trapped charge dating. Quat. Geochron. 28, 54–61 (2015).Article 

    Google Scholar 
    von Suchodoletz, H. & Faust, D. Late Quaternary fluvial dynamics and landscape evolution at the lower Shulaveris Ghele River (southern Caucasus). Quat. Res. 89, 254–269 (2018).Article 

    Google Scholar 
    von Suchodoletz, H. et al. Late Pleistocene river migrations in response to thrust belt advance and sediment-flux steering e the Kura River (southern Caucasus). Geomorphology 266, 53–65 (2016).ADS 
    Article 

    Google Scholar 
    Ryan, W. B. F. et al. Global multi-resolution topography (GMRT) synthesis data set. Geochem. Geophys. Geosyst. 10, Q03014 (2009).ADS 
    Article 

    Google Scholar 
    Nalivkin, D. V. et al. Geologicheskaya Karta Kavkaza, Mashtav 1:500.000 (Geological Map of the Caucasus, Scale 1:500,000). (Ministry of Geology of the USSR, 1976). More

  • in

    Vertically migrating phytoplankton fuel high oceanic primary production

    Westberry, T., Behrenfeld, M., Siegel, D. & Boss, E. Carbon-based primary productivity modeling with vertically resolved photoacclimation. Glob. Biogeochem. Cycles 22 (2008).Richardson, K. & Bendtsen, J. Vertical distribution of phytoplankton and primary production in relation to nutricline depth in the open ocean. Mar. Ecol. Prog. Ser. 620, 33–46 (2019).CAS 

    Google Scholar 
    Oschlies, A. in Ocean Modeling in an Eddying Regime (eds Hecht, M. W. & Hasumi, H.) 115–130 (AGU, 2008).Letscher, R. T., Primeau, F. & Moore, J. K. Nutrient budgets in the subtropical ocean gyres dominated by lateral transport. Nat. Geosci. 9, 815–819 (2016).CAS 

    Google Scholar 
    Johnson, K. S., Riser, S. C. & Karl, D. M. Nitrate supply from deep to near-surface waters of the North Pacific subtropical gyre. Nature 465, 1062–1065 (2010).CAS 

    Google Scholar 
    Fawcett, S. E., Lomas, M. W., Casey, J. R., Ward, B. B. & Sigman, D. M. Assimilation of upwelled nitrate by small eukaryotes in the Sargasso Sea. Nat. Geosci. 4, 717–722 (2011).CAS 

    Google Scholar 
    Knapp, A. N., Casciotti, K. L., Berelson, W. M., Prokopenko, M. G. & Capone, D. G. Low rates of nitrogen fixation in eastern tropical South Pacific surface waters. Proc. Natl Acad. Sci. USA 113, 4398–4403 (2016).CAS 

    Google Scholar 
    Böttjer, D. et al. Temporal variability of nitrogen fixation and particulate nitrogen export at station ALOHA. Limnol. Oceanogr. 62, 200–216 (2017).
    Google Scholar 
    Gruber, N., Keeling, C. D. & Stocker, T. F. Carbon-13 constraints on the seasonal inorganic carbon budget at the BATS site in the northwestern Sargasso Sea. Deep Sea Res. 1 45, 673–717 (1998).CAS 

    Google Scholar 
    Doney, S. C., Glover, D. M. & Najjar, R. G. A new coupled, one-dimensional biological–physical model for the upper ocean: applications to the JGOFS Bermuda Atlantic Time-series Study (BATS) site. Deep Sea Res. 2 43, 591–624 (1996).CAS 

    Google Scholar 
    Ascani, F. et al. Physical and biological controls of nitrate concentrations in the upper subtropical North Pacific Ocean. Deep Sea Res 2 93, 119–134 (2013).CAS 

    Google Scholar 
    Gran, H. H. in Rapport Vol. 56, 1–112 (Bureau du Conseil permanent international pour l’exploration de la mer, 1929).Hasle, G. R. Phototactic vertical migration in marine dinoflagellates. Oikos 2, 162–175 (1950).
    Google Scholar 
    Villareal, T. A. et al. Upward transport of oceanic nitrate by migrating diatom mats. Nature 397, 423–425 (1999).CAS 

    Google Scholar 
    Villareal, T. & Carpenter, E. Buoyancy regulation and the potential for vertical migration in the oceanic cyanobacterium Trichodesmium. Microb. Ecol. 45, 1–10 (2003).CAS 

    Google Scholar 
    Wirtz, K. & Smith, S. L. Vertical migration by bulk phytoplankton sustains biodiversity and nutrient input to the surface ocean. Sci. Rep. 10, 1142 (2020).CAS 

    Google Scholar 
    Silsbe, G. M., Behrenfeld, M. J., Halsey, K. H., Milligan, A. J. & Westberry, T. K. The CAFE model: a net production model for global ocean phytoplankton. Glob. Biogeochem. Cycles 30, 1756–1777 (2016).CAS 

    Google Scholar 
    Wang, W.-L., Moore, J. K., Martiny, A. C. & Primeau, F. W. Convergent estimates of marine nitrogen fixation. Nature 566, 205–211 (2019).CAS 

    Google Scholar 
    Karl, D. M., Letelier, R., Hebel, D. V., Bird, D. F. & Winn, C. D. in Marine Pelagic Cyanobacteria: Trichodesmium and Other Diazotrophs (eds Carpenter, E. J. et al.) 219–237 (Springer, 1992).Cullen, J. J. Subsurface chlorophyll maximum layers: enduring enigma or mystery solved? Ann. Rev. Mar. Sci. 7, 207–239 (2015).
    Google Scholar 
    Masuda, Y. et al. Photoacclimation by phytoplankton determines the distribution of global subsurface chlorophyll maxima in the ocean. Commun. Earth Environ. 2, 1–8 (2021).
    Google Scholar 
    Anugerahanti, P., Kerimoglu, O. & Smith, S. L. Enhancing ocean biogeochemical models with phytoplankton variable composition. Front. Mar. Sci. 8, 675428 (2021).
    Google Scholar 
    Pérez, V., Fernández, E., Marañón, E., Morán, X. A. G. & Zubkov, M. V. Vertical distribution of phytoplankton biomass, production and growth in the Atlantic subtropical gyres. Deep Sea Res. 1 53, 1616–1634 (2006).
    Google Scholar 
    Cornec, M. et al. Deep chlorophyll maxima in the global ocean: occurrences, drivers and characteristics. Glob. Biogeochem. Cycles 35, e2020GB006759 (2021).CAS 

    Google Scholar 
    Li, Q. P., Wang, Y., Dong, Y. & Gan, J. Modeling long-term change of planktonic ecosystems in the northern South China Sea and the upstream Kuroshio Current. J. Geophys. Res. 120, 3913–3936 (2015).
    Google Scholar 
    Latif, S., Ayub, Z. & Siddiqui, G. Seasonal variability of phytoplankton in a coastal lagoon and adjacent open sea in Pakistan. Turk. J. Botany 37, 398–410 (2013).CAS 

    Google Scholar 
    Liang, Y. et al. Nutrient-limitation induced diatom–dinoflagellate shift of spring phytoplankton community in an offshore shellfish farming area. Mar. Pollut. Bull. 141, 1–8 (2019).CAS 

    Google Scholar 
    Rahlff, J. et al. Short-term responses to ocean acidification: effects on relative abundance of eukaryotic plankton from the tropical Timor Sea. Mar. Ecol. Prog. Ser. 658, 59–74 (2021).CAS 

    Google Scholar 
    Kahru, M., Savchuk, O. & Elmgren, R. Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability. Mar. Ecol. Prog. Ser. 343, 15–23 (2007).
    Google Scholar 
    Klais, R., Tamminen, T., Kremp, A., Spilling, K. & Olli, K. Decadal-scale changes of dinoflagellates and diatoms in the anomalous Baltic Sea spring bloom. PLoS ONE 6, e21567 (2011).CAS 

    Google Scholar 
    Klais, R., Norros, V., Lehtinen, S., Tamminen, T. & Olli, K. Community assembly and drivers of phytoplankton functional structure. Funct. Ecol. 31, 760–767 (2017).
    Google Scholar 
    Villareal, T. A., Pilskaln, C. H., Montoya, J. P. & Dennett, M. Upward nitrate transport by phytoplankton in oceanic waters: balancing nutrient budgets in oligotrophic seas. PeerJ 2, e302 (2014).
    Google Scholar 
    Mignot, A. et al. Understanding the seasonal dynamics of phytoplankton biomass and the deep chlorophyll maximum in oligotrophic environments: a bio-argo float investigation. Glob. Biogeochem. Cycles 28, 856–876 (2014).CAS 

    Google Scholar 
    Chen, B., Smith, S. L. & Wirtz, K. W. Effect of phytoplankton size diversity on primary productivity in the North Pacific: trait distributions under environmental variability. Ecol. Lett. 22, 56–66 (2019).
    Google Scholar 
    Cabré, A., Marinov, I. & Leung, S. Consistent global responses of marine ecosystems to future climate change across the IPCC AR5 Earth system models. Clim. Dyn. 45, 1253–1280 (2015).
    Google Scholar 
    Giorgetta, M. A. et al. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Mod. Earth Sys. 5, 572–597 (2013).
    Google Scholar 
    Bopp, L. et al. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences 10, 6225–6245 (2013).
    Google Scholar 
    Fu, W., Randerson, J. T. & Moore, J. K. Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models. Biogeosciences 13, 5151–5170 (2016).
    Google Scholar 
    Gliwicz, M. Z. Predation and the evolution of vertical migration in zooplankton. Nature 320, 746–748 (1986).
    Google Scholar 
    Huettel, M., Forster, S., Kloser, S. & Fossing, H. Vertical migration in the sediment-dwelling sulfur bacteria Thioploca spp. in overcoming diffusion limitations. Appl. Environ. Microbiol. 62, 1863–1872 (1996).CAS 

    Google Scholar 
    Waterbury, J. B., Willey, J. M., Franks, D. G., Valois, F. W. & Watson, S. W. A cyanobacterium capable of swimming motility. Science 230, 74–76 (1985).CAS 

    Google Scholar 
    McCarren, J. et al. Inactivation of swmA results in the loss of an outer cell layer in a swimming Synechococcus strain. J. Bacteriol. 187, 224–230 (2005).CAS 

    Google Scholar 
    Eppley, R. W., Holm-Hansen, O. & Strickland, J. D. Some observations on the vertical migration of dinoflagellates. J. Phycol. 4, 333–340 (1968).CAS 

    Google Scholar 
    Sengupta, A., Carrara, F. & Stocker, R. Phytoplankton can actively diversify their migration strategy in response to turbulent cues. Nature 543, 555–558 (2017).CAS 

    Google Scholar 
    Waite, A., Fisher, A., Thompson, P. & Harrison, P. Sinking rate verses cell volume relationships illuminate sinking rate control mechanisms in marine diatoms. Mar. Ecol. Prog. Ser. 157, 97–108 (1997).
    Google Scholar 
    Throndsen, J. Motility in some marine nanoplankton flagellates. Nor. J. Zool. 21, 193–200 (1973).
    Google Scholar 
    Gittleson, S. M., Hotchkiss, S. K. & Valencia, F. G. Locomotion in the marine dinoflagellate Amphidinium carterae (Hulburt). Trans. Am. Microsc. Soc. 93, 101–105 (1974).Barsanti, L. et al. Swimming patterns of the quadriflagellate Tetraflagellochloris mauritanica (Chlamydomonadales, Chlorophyceae). J. Phycol. 52, 209–218 (2016).
    Google Scholar 
    Schuech, R. & Menden-Deuer, S. Going ballistic in the plankton: anisotropic swimming behavior of marine protists. Limnol. Oceanogr. Fluids Environ. 4, 1–16 (2014).
    Google Scholar 
    Eppley, R. W., Holmes, R. W. & Strickland, J. D. Sinking rates of marine phytoplankton measured with a fluorometer. J. Exp. Mar. Biol. Ecol. 1, 191–208 (1967).
    Google Scholar 
    Bienfang, P. Phytoplankton sinking rates in oligotrophic waters off Hawaii, USA. Mar. Biol. 61, 69–77 (1980).
    Google Scholar 
    Lisicki, M., Rodrigues, M. F. V., Goldstein, R. E. & Lauga, E. Swimming eukaryotic microorganisms exhibit a universal speed distribution. Elife 8, e44907 (2019).CAS 

    Google Scholar 
    Moore, J. & Villareal, T. Buoyancy and growth characteristics of three positively buoyant marine diatoms. Mar. Ecol. Prog. Ser. 132 (1996).Hawaii Ocean Time-series (HOT) (School of Ocean and Earth Science and Technology at the University of Hawai’i, 2020); http://hahana.soest.hawaii.edu/hot/hot-dogsBermuda Atlantic Time-Series (BATS) (Bermuda Institure of Ocean Sciences, 2020); http://bats.bios.eduThe Japanese 55-Year Reanalysis (JRA-55) (Japan Meteorological Agency, 2020); http://jra.kishou.go.jp/JRA-55Ridgway, K., Dunn, J. & Wilkin, J. Ocean interpolation by four-dimensional weighted least squares—application to the waters around Australasia. J. Atmos. Ocean. Technol. 19, 1357–1375 (2002).
    Google Scholar 
    CSIRO Atlas of Regional Seas (CARS) (CSIRO, 2009); http://www.marine.csiro.au/~dunn/cars2009Ocean Colour (ESA-CCI, 2020); http://www.esa-oceancolour-cci.orgCloud (ESA-CCI, 2020); http://www.esa-cloud-cci.orgSea Surface Temperature (ESA-CCI, 2020); http://www.esa-sst-cci.orgRosati, A. & Miyakoda, K. A general circulation model for upper ocean simulation. J. Phys. Oceanogr. 18, 1601–1626 (1988).
    Google Scholar 
    Ralston, D. K., McGillicuddy, D. J. & Townsend, D. W. Asynchronous vertical migration and bimodal distribution of motile phytoplankton. J. Plankton Res. 29, 803–821 (2007).
    Google Scholar 
    Kamykowski, D. & Yamazaki, H. A study of metabolism-influenced orientation in the diel vertical migration of marine dinoflagellates. Limnol. Oceanogr. 42, 1189–1202 (1997).
    Google Scholar 
    Richardson, T. L., Cullen, J. J., Kelley, D. E. & Lewis, M. R. Potential contributions of vertically migrating Rhizosolenia to nutrient cycling and new production in the open ocean. J. Plankton Res. 20, 219–241 (1998).
    Google Scholar 
    Ross, O. N. & Sharples, J. Phytoplankton motility and the competition for nutrients in the thermocline. Mar. Ecol. Prog. Ser. 347, 21–38 (2007).CAS 

    Google Scholar 
    Chavez, F. P., Messié, M. & Pennington, J. T. Marine primary production in relation to climate variability and change. Ann. Rev. Mar. Sci. 3, 227–260 (2011).
    Google Scholar 
    Saba, V. et al. An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe. Biogeosciences 8, 489–503 (2011).CAS 

    Google Scholar 
    Bhattathiri, P., Devassy, V. & Radhakrishna, K. Primary production in the Bay of Bengal during southwest monsoon of 1978. Mahasagar Bull. Natl Inst. Oceanogr. 13, 315–323 (1980).
    Google Scholar 
    Sarupria, J. & Bhargava, R. Seasonal primary production in different sectors of the EEZ of India. Mahasagar Bull. Natl Inst. Oceanogr. 26, 139–147 (1993).
    Google Scholar 
    Jyothibabu, R. et al. Differential response of winter cooling on biological production in the northeastern Arabian Sea and northwestern Bay of Bengal. Curr. Sci. 87, 783–791 (2004).
    Google Scholar 
    Kumar, S. P. et al. Is the biological productivity in the Bay of Bengal light limited? Curr. Sci. 98, 1331–1339 (2010).CAS 

    Google Scholar 
    Kumar, S. P. et al. Seasonal cycle of physical forcing and biological response in the Bay of Bengal. Ind. J. Mar. Sci. 39, 388–405 (2010).CAS 

    Google Scholar 
    Buitenhuis, E. T., Hashioka, T. & Quéré, C. L. Combined constraints on global ocean primary production using observations and models. Glob. Biogeochem. Cycles 27, 847–858 (2013).CAS 

    Google Scholar  More

  • in

    Fall and rise of the phytoplankton

    Wirtz, K., Smith, S. L., Mathis, M. & Taucher, J. Nat. Clim. Change https://doi.org/10.1038/s41558-022-01430-5 (2022).Article 

    Google Scholar 
    Watanabe, M., Kohata, K. & Kimura, T. Limnol. Oceanogr. 36, 593–602 (1991).Article 

    Google Scholar 
    Villareal, T. A. et al. Nature 397, 423–425 (1999).CAS 
    Article 

    Google Scholar 
    Krumhardt, K. M., Lovenduski, N. S., Iglesias-Rodriguez, M. D. & Kleypas, J. A. Prog. Oceanogr. 159, 276–295 (2017).Article 

    Google Scholar 
    Alldredge, A. L. & Silver, M. W. Prog. Oceanogr. 20, 41–82 (1988).Article 

    Google Scholar 
    White, A. E., Spitz, Y. H. & Letelier, R. M. Mar. Ecol. Prog. Ser. 323, 35–45 (2006).Article 

    Google Scholar 
    Kwiatkowski, L. et al. Biogeosciences 17, 3439–3470 (2020).CAS 
    Article 

    Google Scholar 
    Tittensor, D. P. et al. Nat. Clim. Change 11, 973–981 (2021).Article 

    Google Scholar 
    Giorgetta, M. A. et al. J. Adv. Model. Earth Syst. 5, 572–597 (2013).Article 

    Google Scholar 
    McGillicuddy, D. J. et al. Nature 394, 263–266 (1998).CAS 
    Article 

    Google Scholar 
    Lévy, M., Franks, P. J. & Smith, K. S. Nat. Commun. 9, 4758 (2018).Article 

    Google Scholar 
    Durham, W. M. & Stocker, R. Annu. Rev. Mar. Sci. 4, 177–207 (2012).Article 

    Google Scholar 
    Cullen, J. J. Annu. Rev. Mar. Sci. 7, 207–239 (2015).Article 

    Google Scholar 
    Moeller, H. V., Laufkötter, C., Sweeney, E. M. & Johnson, M. D. Nat. Commun. 10, 1978 (2019).Article 

    Google Scholar 
    Fawcett, S. E., Johnson, K. S., Riser, S. C., Van Oostende, N. & Sigman, D. M. Mar. Chem. 207, 108–123 (2018).CAS 
    Article 

    Google Scholar  More

  • in

    Selection on offspring size and contemporary evolution under ocean acidification

    Sunday, J. M., Crim, R. N., Harley, C. D. G. & Hart, M. W. Quantifying rates of evolutionary adaptation in response to ocean acidification. PLoS ONE 6, e22881 (2011).CAS 
    Article 

    Google Scholar 
    Kelly, M. W. & Hofmann, G. E. Adaptation and the physiology of ocean acidification. Funct. Ecol. 27, 980–990 (2013).Article 

    Google Scholar 
    Munday, P. L., Warner, R. R., Monro, K., Pandolfi, J. M. & Marshall, D. J. Predicting evolutionary responses to climate change in the sea. Ecol. Lett. 16, 1488–1500 (2013).Article 

    Google Scholar 
    Reusch, T. B. H. Climate change in the oceans: evolutionary versus phenotypically plastic responses of marine animals and plants. Evol. Appl. 7, 104–122 (2014).Article 

    Google Scholar 
    Sunday, J. M. et al. Evolution in an acidifying ocean. Trends Ecol. Evol. 29, 117–125 (2014).Article 

    Google Scholar 
    Kroeker, K. J., Kordas, R. L., Crim, R. N. & Singh, G. G. Meta-analysis reveals negative yet variable effects of ocean acidification on marine organisms. Ecol. Lett. 13, 1419–1434 (2010).Article 

    Google Scholar 
    Przeslawski, R., Byrne, M. & Mellin, C. A review and meta-analysis of the effects of multiple abiotic stressors on marine embryos and larvae. Glob. Change Biol. 21, 2122–2140 (2015).Article 

    Google Scholar 
    Cattano, C., Claudet, J., Domenici, P. & Milazzo, M. Living in a high CO2 world: a global meta-analysis shows multiple trait-mediated fish responses to ocean acidification. Ecol. Monogr. 88, 320–335 (2018).Article 

    Google Scholar 
    Lohbeck, K., Riebesell, U. & Reusch, T. Adaptive evolution of a key phytoplankton species to ocean acidification. Nat. Geosci. 5, 346–351 (2012).CAS 
    Article 

    Google Scholar 
    Dam, H. G. et al. Rapid, but limited, zooplankton adaptation to simultaneous warming and acidification. Nat. Clim. Change 11, 780–786 (2021).Article 

    Google Scholar 
    Kelly, M. W., Padilla-Gamiño, J. L. & Hofmann, G. E. Natural variation and the capacity to adapt to ocean acidification in the keystone sea urchin Strongylocentrotus purpuratus. Glob. Change Biol. 19, 2536–2546 (2013).Article 

    Google Scholar 
    Pespeni, M. H. et al. Evolutionary change during experimental ocean acidification. Proc. Natl Acad. Sci. USA 110, 6937–6942 (2013).CAS 
    Article 

    Google Scholar 
    Foo, S. A., Dworjanyn, S. A., Poore, A. G. B., Harianto, J. & Byrne, M. Adaptive capacity of the sea urchin Heliocidaris erythrogramma to ocean change stressors: responses from gamete performance to the juvenile. Mar. Ecol. Prog. Ser. 556, 161–172 (2016).CAS 
    Article 

    Google Scholar 
    Malvezzi, A. J. et al. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification. Evol. Appl. 8, 352–362 (2015).CAS 
    Article 

    Google Scholar 
    Bitter, M. C., Kapsenberg, L., Gattuso, J.-P. & Pfister, C. A. Standing genetic variation fuels rapid adaptation to ocean acidification. Nat. Commun. 10, 5821 (2019).CAS 
    Article 

    Google Scholar 
    Falconer, D. S. & Mackay, T. F. C. Introduction to Quantitative Genetics 4th edn (Pearson Prentice Hall, 1996).Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits (Oxford Univ. Press, 1998).Ishimatsu, A., Hayashi, M. & Kikkawa, T. Fishes in high-CO2, acidified oceans. Mar. Ecol. Prog. Ser. 373, 295–302 (2008).CAS 
    Article 

    Google Scholar 
    Melzner, F. et al. Physiological basis for high CO2 tolerance in marine ectothermic animals: pre-adaptation through lifestyle and ontogeny? Biogeosciences 6, 2313–2331 (2009).CAS 
    Article 

    Google Scholar 
    Timothy A. Mousseau and Charles W. Fox. Maternal Effects as Adaptations 178–201 (Oxford Univ. Press, 1998).Marshall, D., Allen, R. & Crean, A. The ecological and evolutionary importance of maternal effects in the sea. Oceanogr. Mar. Biol. 46, 203–250 (2008).
    Google Scholar 
    Tasoff, A. J. & Johnson, D. W. Can larvae of a marine fish adapt to ocean acidification? Evaluating the evolutionary potential of California grunion (Leuresthes tenuis). Evol. Appl. 12, 560–571 (2019).CAS 
    Article 

    Google Scholar 
    Smith, C. C. & Fretwell, S. D. The optimal balance between size and number of offspring. Am. Nat. 108, 499–506 (1974).Article 

    Google Scholar 
    Shimada, Y., Shikano, T., Murakami, N., Tsuzaki, T. & Seikai, T. Maternal and genetic effects on individual variation during early development in Japanese flounder Paralichthys olivaceus. Fish. Sci. 73, 244–249 (2007).CAS 
    Article 

    Google Scholar 
    Johnson, D. W., Christie, M. R. & Moye, J. Quantifying evolutionary potential of marine fish larvae: heritability, selection, and evolutionary constraints. Evolution 64, 2614–2628 (2010).Article 

    Google Scholar 
    Miles, C. M., Hadfield, M. G. & Wayne, M. L. Heritability for egg size in the serpulid polychaete Hydroides elegans. Mar. Ecol. Prog. Ser. 340, 155–162 (2007).Article 

    Google Scholar 
    Iguchi, K. & Yamaguchi, M. Adaptive significance of inter- and intrapopulational egg size variation in ayu Plecoglossus altivelis (osmeridae). Copeia 1994, 184–190 (1994).Article 

    Google Scholar 
    Marshall, D. J. & Keough, M. J. Effects of settler size and density on early post-settlement survival of Ciona intestinalis in the field. Mar. Ecol. Prog. Ser. 259, 139–144 (2003).Article 

    Google Scholar 
    González-Ortegón, E. & Giménez, L. Environmentally mediated phenotypic links and performance in larvae of a marine invertebrate. Mar. Ecol. Prog. Ser. 502, 185–195 (2014).Article 

    Google Scholar 
    Pan, T.-C. F., Applebaum, S. L. & Manahan, D. T. Experimental ocean acidification alters the allocation of metabolic energy. Proc. Natl Acad. Sci. USA 112, 4696–4701 (2015).CAS 
    Article 

    Google Scholar 
    Rollinson, N. & Hutchings, J. A. Environmental quality predicts optimal egg size in the wild. Am. Nat. 181, 76–90 (2013).Article 

    Google Scholar 
    Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits (Oxford Univ. Press, 1998).Munday, P. L. Transgenerational acclimation of fishes to climate change and ocean acidification. F1000Prime Rep. 6, 99 (2014).Article 

    Google Scholar 
    Murray, C. S., Malvezzi, A., Gobler, C. J. & Baumann, H. Offspring sensitivity to ocean acidification changes seasonally in a coastal marine fish. Mar. Ecol. Prog. Ser. 504, 1–11 (2014).Article 

    Google Scholar 
    Baumann, H. Experimental assessments of marine species sensitivities to ocean acidification and co-stressors: how far have we come? Can. J. Zool. 97, 399–408 (2019).Article 

    Google Scholar 
    Chevin, L.-M., Lande, R. & Mace, G. M. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biol. 8, e1000357 (2010).Article 
    CAS 

    Google Scholar 
    Bell, G. Evolutionary rescue and the limits of adaptation. Phil. Trans. R. Soc. B 368, p20120080 (2013).Article 

    Google Scholar 
    Carlson, S. M., Cunningham, C. J. & Westley, P. A. H. Evolutionary rescue in a changing world. Trends Ecol. Evol. 29, 521–530 (2014).Article 

    Google Scholar 
    Smyder, E. A., Martin, K. L. M. & Gatten, R. E. Jr Temperature effects on egg survival and hatching during the extended incubation period of California grunion, Leuresthes tenuis. Copeia 2002, 313–320 (2002).Article 

    Google Scholar 
    Barneche, D. R., Robertson, D. R., White, C. R. & Marshall, D. J. Fish reproductive-energy output increases disproportionately with body size. Science 360, 642–645 (2018).CAS 
    Article 

    Google Scholar 
    Van Noordwijk, A. J. & de Jong, G. Acquisition and allocation of resources: their influence on variation in life history tactics. Am. Nat. 128, 137–142 (1986).Article 

    Google Scholar 
    Davidson, C. Spatial and Temporal Variability of Coastal Carbonate Chemistry in the Southern California Region. MSc thesis, Univ. California, San Diego (2015).Jones, J. M., Sweet, J., Brzezinski, M. A., McNair, H. M. & Passow, U. Evaluating carbonate system algorithms in a nearshore system: does total alkalinity matter? PLoS ONE 11, e0165191 (2016).Article 
    CAS 

    Google Scholar 
    Gruber, N. et al. Rapid progression of ocean acidification in the California current system. Science 337, 220–223 (2012).CAS 
    Article 

    Google Scholar 
    Turi, G., Lachkar, Z., Gruber, N. & Münnich, M. Climatic modulation of recent trends in ocean acidification in the California current system. Environ. Res. Lett. 11, 014007 (2016).Article 

    Google Scholar 
    Northcott, D. et al. Impacts of urban carbon dioxide emissions on sea-air flux and ocean acidification in nearshore waters. PLoS ONE 14, e0214403 (2019).CAS 
    Article 

    Google Scholar 
    Rausher, M. D. The measurement of selection on quantitative traits: biases due to environmental covariances between traits and fitness. Evolution 46, 616–626 (1992).Article 

    Google Scholar 
    Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S (Springer, 2002).R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).Kruuk, L. E. B. Estimating genetic parameters in natural populations using the animal model. Phil. Trans. R. Soc. B 359, 873–890 (2004).Article 

    Google Scholar 
    Wilson, A. J. et al. An ecologist’s guide to the animal model. J. Anim. Ecol. 79, 13–26 (2010).Article 

    Google Scholar 
    Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, (2010).Heidelberger, P. & Welch, P. D. Simulation run length control in the presence of an initial transient. Oper. Res. 31, 1109–1144 (1983).Article 

    Google Scholar 
    Clark, F. N. The Life History of Leuresthes Tenuis, an Atherine Fish with Tide Controlled Spawning Habits Fish Bulletin No. 10 (California Department of Fish and Game, 1925).Johnson, D.W. Data from: Selection on offspring size and contemporary evolution under ocean acidification. Dryad https://doi.org/10.5061/dryad.0gb5mkm3w (2022) More