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1. Numerical Analysis of Resonant Axion-Photon Mixing: Part I

Author

Ginés, Estanis Utrilla, Noordhuis, Dion, Weniger, Christoph, and Witte, Samuel J.

Subjects
High Energy Physics - Phenomenology, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

Many present-day axion searches attempt to probe the mixing of axions and photons, which occurs in the presence of an external magnetic field. While this process is well-understood in a number of simple and idealized contexts, a strongly varying or highly inhomogeneous background can impact the efficiency and evolution of the mixing in a non-trivial manner. In an effort to develop a generalized framework for analyzing axion-photon mixing in arbitrary systems, we focus in this work on directly solving the axion-modified form of Maxwell's equations across a simulation domain with a spatially varying background. We concentrate specifically on understanding resonantly enhanced axion-photon mixing in a highly magnetized plasma, which is a key ingredient for developing precision predictions of radio signals emanating from the magnetospheres of neutron stars. After illustrating the success and accuracy of our approach for simplified limiting cases, we compare our results with a number of analytic solutions recently derived to describe mixing in these systems. We find that our numerical method demonstrates a high level of agreement with one, but only one, of the published results. Interestingly, our method also recovers the mixing between the axion and magnetosonic-t and Alfv\'{e}n modes; these modes cannot escape from the regions of dense plasma, but could non-trivially alter the dynamics in certain environments. Future work will focus on extending our calculations to study resonant mixing in strongly variable backgrounds, mixing in generalized media (beyond the strong magnetic field limit), and the mixing of photons with other light bosonic fields, such as dark photons., Comment: 15 pages, 7 figures + appendix

Published
2024

2. Axion Clouds around Neutron Stars

Author

Noordhuis, Dion, Prabhu, Anirudh, Weniger, Christoph, and Witte, Samuel J.

Subjects
High Energy Physics - Phenomenology, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Recent work has shown that axions can be efficiently produced via non-stationary pair plasma discharges in the polar cap region of pulsars. Here, we point out that for axion masses $10^{-9} \, {\rm eV} \lesssim m_a \lesssim 10^{-4} \, \rm eV$, a sizable fraction of the sourced axion population will be gravitationally confined to the neutron star. These axions accumulate over astrophysical timescales, thereby forming a dense `axion cloud' around the star. We argue that the existence of such a cloud, with densities reaching and potentially exceeding $\mathcal{O}(10^{22}) \, {\rm GeV \, cm^{-3}}$, is a generic expectation across a wide range of parameter space. For axion masses $m_a \gtrsim 10^{-7} \, \rm eV$, energy is primarily radiated from the axion cloud via resonant axion-photon mixing, generating a number of distinctive signatures that include: a sharp line in the radio spectrum of each pulsar (located at the axion mass, and with an order percent-level width), and transient events arising from the reconfiguration of charge densities in the magnetosphere. While a deeper understanding of the systematic uncertainties in these systems is required, our current estimates suggest that existing radio telescopes could improve sensitivity to the axion-photon coupling by more than an order of magnitude., Comment: v2: 21 pages, 14 figures. Updated to match published version. Added new subsection on uncertainties, updated plots, and corrected minor bugs and typos. v1: 17 pages, 14 figures

Published
2023

3. Novel Constraints on Axions Produced in Pulsar Polar-Cap Cascades

Author

Noordhuis, Dion, Prabhu, Anirudh, Witte, Samuel J., Chen, Alexander Y., Cruz, Fábio, and Weniger, Christoph

Subjects
High Energy Physics - Phenomenology, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Axions can be copiously produced in localized regions of neutron star magnetospheres where the ambient plasma is unable to efficiently screen the induced electric field. As these axions stream away from the neutron star they can resonantly transition into photons, generating a large broadband contribution to the neutron star's intrinsic radio flux. In this work, we develop a comprehensive end-to-end framework to model this process from the initial production of axions to the final detection of radio photons, and derive constraints on the axion-photon coupling, $g_{a\gamma\gamma}$, using observations of 27 nearby pulsars. We study the modeling uncertainty in the sourced axion spectrum by comparing predictions from 2.5 dimensional particle-in-cell simulations with those derived using a semi-analytic model; these results show remarkable agreement, leading to constraints on the axion-photon coupling that typically differ by a factor of no more than $\sim 2$. The limits presented here are the strongest to date for axion masses $10^{-8} \, {\rm eV} \lesssim m_a \lesssim 10^{-5} \, {\rm eV}$, and crucially do not rely on the assumption that axions are dark matter., Comment: v2: Updated to match published version. Added new SM sections on analysis and uncertainties, updated plots, and corrected minor bugs and typos. v1: 5 pages, 2 figures + Supplementary Material

Published
2022

4. Axion-Photon Conversion in Neutron Star Magnetospheres: The Role of the Plasma in the Goldreich-Julian Model

Author

Witte, Samuel J., Noordhuis, Dion, Edwards, Thomas D. P., and Weniger, Christoph

Subjects
High Energy Physics - Phenomenology, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

The most promising indirect search for the existence of axion dark matter uses radio telescopes to look for narrow spectral lines generated from the resonant conversion of axions in the magnetospheres of neutron stars. Unfortunately, a large list of theoretical uncertainties has prevented this search strategy from being fully accepted as robust. In this work we attempt to address major outstanding questions related to the role and impact of the plasma, including: $(i)$ does refraction and reflection of radio photons in the magnetosphere induce strong inhomogeneities in the flux, $(ii)$ can refraction induce premature axion-photon de-phasing, $(iii)$ to what extent do photon-plasma interactions induce a broadening of the spectral line, $(iv)$ does the flux have a strong time dependence, and $(v)$ can radio photons sourced by axions be absorbed by the plasma. We present an end-to-end analysis pipeline based on ray-tracing that exploits a state-of-the-art auto-differentiation algorithm to propagate photons from the conversion surface to asymptotically large distances. Adopting a charge symmetric Goldreich-Julian model for the magnetosphere, we show that for reasonable parameters one should expect a strong anisotropy of the signal, refraction induced axion-photon de-phasing, significant line-broadening, a variable time-dependence of the flux, and, for large enough magnetic fields, anisotropic absorption. Our simulation code is flexible enough to serve as the basis for follow-up studies with a large range of magnetosphere models., Comment: v3: Fix "?" citation. v2: Accepted for publication PRD. Convergence improved, plots updated, minor bugs and typos corrected. No major changes to results/conclusions. v1: 9 pages + Appendix

Published
2021
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5. PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Author

Li, Shen, Zhao, Yanli, Varma, Rohan, Salpekar, Omkar, Noordhuis, Pieter, Li, Teng, Paszke, Adam, Smith, Jeff, Vaughan, Brian, Damania, Pritam, and Chintala, Soumith

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning
Abstract

This paper presents the design, implementation, and evaluation of the PyTorch distributed data parallel module. PyTorch is a widely-adopted scientific computing package used in deep learning research and applications. Recent advances in deep learning argue for the value of large datasets and large models, which necessitates the ability to scale out model training to more computational resources. Data parallelism has emerged as a popular solution for distributed training thanks to its straightforward principle and broad applicability. In general, the technique of distributed data parallelism replicates the model on every computational resource to generate gradients independently and then communicates those gradients at each iteration to keep model replicas consistent. Despite the conceptual simplicity of the technique, the subtle dependencies between computation and communication make it non-trivial to optimize the distributed training efficiency. As of v1.5, PyTorch natively provides several techniques to accelerate distributed data parallel, including bucketing gradients, overlapping computation with communication, and skipping gradient synchronization. Evaluations show that, when configured appropriately, the PyTorch distributed data parallel module attains near-linear scalability using 256 GPUs., Comment: To appear in VLDB 2020

Published
2020

6. Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Author

Goyal, Priya, Dollár, Piotr, Girshick, Ross, Noordhuis, Pieter, Wesolowski, Lukasz, Kyrola, Aapo, Tulloch, Andrew, Jia, Yangqing, and He, Kaiming

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Learning
Abstract

Deep learning thrives with large neural networks and large datasets. However, larger networks and larger datasets result in longer training times that impede research and development progress. Distributed synchronous SGD offers a potential solution to this problem by dividing SGD minibatches over a pool of parallel workers. Yet to make this scheme efficient, the per-worker workload must be large, which implies nontrivial growth in the SGD minibatch size. In this paper, we empirically show that on the ImageNet dataset large minibatches cause optimization difficulties, but when these are addressed the trained networks exhibit good generalization. Specifically, we show no loss of accuracy when training with large minibatch sizes up to 8192 images. To achieve this result, we adopt a hyper-parameter-free linear scaling rule for adjusting learning rates as a function of minibatch size and develop a new warmup scheme that overcomes optimization challenges early in training. With these simple techniques, our Caffe2-based system trains ResNet-50 with a minibatch size of 8192 on 256 GPUs in one hour, while matching small minibatch accuracy. Using commodity hardware, our implementation achieves ~90% scaling efficiency when moving from 8 to 256 GPUs. Our findings enable training visual recognition models on internet-scale data with high efficiency., Comment: Tech report (v2: correct typos)

Published
2017

27. Reproducible Gene Expression Measurement Among Multiple Laboratories Obtained in a Blinded Study Using Standardized RT (StaRT)-PCR

Author

Crawford, Erin L., Peters, Godfridus J., Noordhuis, Paul, Rots, Marianne G., Vondracek, Martin, Grafström, Roland C., Lieuallen, Kimberly, Lennon, Gregory, Zahorchak, Robert J., Georgeson, Melanie J., Wali, Anil, Lechner, John F., Fan, Pan Sheng, Kahaleh, M. Bashar, Khuder, Sadik A., Warner, Kristy A., Weaver, David A., and Willey, James C.

Published
2001
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35. Abstracts of poster presentations

Author

Agostinho, A. B., Rosi, F., Tabucchi, A., Carlucci, F., Pizzichini, M., Arnér, Elias S. J., Eriksson, Staffan, Barankiewicz, J., Trembacz, H., Zwierzchowski, L., Bergman, A. M., van Haperen, V. W. T. Ruiz, Veerman, G., Vermorken, J. B., Peters, G. J., Bory, C., Chantin, C., Rocca, J. L., Bzowska, A., Ananlev, A. V., Ramzaeva, N., Alksins, E., Maurins, J. A., Kulikowska, E., Shugar, D., Davies, P. M., Fairbanks, L. D., Simmonds, H. A., De Graaf, T. W., Van Dijk, W., de Jong D., Huysmans F., De Abreu R., Monnens L., Dijkman H., van Liebergen F., Assmann K., Duley, J. A., Hanefeld, F., Fabianowska-Majewska, K., Duley, A. J., Greger, J., Wasiak, T., Gathof, B. S., Ried, T., Zwieauer, K., Gresser, U., Griesmacher, A., Weigel, G., Müller, M. M., Gross, M., Empl, W., Guisan, B., Roch-Ramel, F., Harley, E. H., Baumgarten, I., Kaletha K., Nagel-Starczynowska G., Karlsson, Anna, Lambooy, L., Boerbooms, A., De Abreu, R., van de Putte, L., Stolk, J., vd Pulte, L., Komissarov, A. A., Romanova, D. V., Debabov, V. G., Kozlov, A. M., Sokolov, V. B., Aksinenko, A. Y., Fetisov, V. I., Komoriya, Keiji, Osada, Yoshio, Hasegawa, Masaichi, Kondo, Shiro, Couch, Ronald C., Griffin, Travis B., Lakaschus, G., Löffler, H. G., Löffler, M., Jiménez, M. López, Salinero, M. A., Guilarte, J. Sánchez, Matesanz, J. Perianes, Medina, L. Vigil, Galiana, J. Ruiz, Marlewski, M., Smolenski, R. T., Swierczynski, J., Rutkowski, B., Zydowo, M. M., Micheli, V., Pescaglini, M., Sestini, S., Jacomelli, G., Magagnoli, C., Pompucci, G., Hayek, G., Mimouni, M., Boptemps, F., Van den Berghe, G., Miranda, M. E., Mateos, F. A., Herrero, E., González, A., Puig, J. G., Miscetti, P., Minelli, A., Proietti, A., Moroni, M., Mezzasoma, I., Moro, J. F., Noam, I., Cameron, J. S., McBride, M. B., Mathew, C. G. P., Ogg, C. S., Puig, J. G., Miranda, M. E., Mateos, F. A., Luzi, L., Noordhuis, P., Kazemier, K., Kaspers, G. J. L., Overgaard-Hansen, K., Marcussen, M., Klenow, H., Pelatti, A., Quaratino, C. P., D'Amario, C., Tentarelli, R., Giacomello, A., Rocchigiani, M., Iacomelli, G., Pandolfi, M. L., Arezzini, L., Terzuoli, L., Pagani, R., Di Sciascio, N., Colosimo, A., Ranieri-Paggi, M., Ronca, F., Brown, P. E., Moir, A. J. G., Raggi, A., Schwendel A., Grune T., Siems W. G., Holzhuetter H. G., Sebesta, I., Krijt, J., Vondrak, K., Kmoch, S., Hrebicek, M., Senatore, G., Del Lucchese, G., Martini, C., Lucacchini, A., Siems, W. G., Mertsch, K., Blasig, I., Grune, T., Skladanowski, A. C., Hoffmann, C. S., Krass, J. D., Makarewicz, W., Jastorff, B., Slingerland, R. J., Bodlaender, J. M., Van Lenthe, H., Elzinga, L., Van Kuilenburg, A. B. P., Voûte, P. A., Van Gennip, A. H., Smid, K., van der Wilt, C. L., Aherne, G. W., Pinedo, H. M., Sorqi, M. L., Rucci, C., Zoppini, A., Staub M., Sasvári-Székely M., Spasokukockaja T., Hrabák A., Stolk, J. N., De Abreu, R. A., De Koning, D. G. M., Lambooy, L. H. M., Kerstens, P. J. S. M., Boerbooms, A. M. Th., van de Putte, L. B. A., Szüts, P., Szirovicza, éva, åbrahám, C. S., Havass, Z., Jezewska, M. M., Van Acker, K. J., Eyskens, F. J., Verkerk, R. H., Scharpé, S. S., van Kuppevelt, T. H., Veerkamp, J. H., Sabina, R. L., Van Laar J. A. M., Mayhew E., Durrani F. A., Peters G. J., Rustum Y. M., Wang, J. Z., Leoncini, R., Vannoni, D., and Marinello, E.

Published
1993
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36. Abstracts of oral presentations

Author

Boulieu, R., Lenoir, A., Mornex, J. F., Bohman, C., Balzarini, J., Wigerinck, P., Van Aerschot, A., Herdewijn, P., De Clercq, Erik, Brosh, S., Zoref-Shani, E., Sperling, O., Danziger, E., Sidi, Y., Bromberg, Y., Burgemeister, Renate, Rötzer, Elke, Gutensohn, Wolf, Connolly, G. P., Harrison, P. J., Diasio, R. B., Lu, Z., Zhang, R., Gresser, U., Gutensohn, W., Resta, R., Thompson, L. F., Javaux, F., Vincent, M. F., Van den Berghe, G., Kamilli, I., Rauch, R., Hahn, D., Keuzenkamp-Jansen, C. W., De Abreu, R. A., Bökkerink, J. P. M., vd Heijden, M. A. H., Löffler, M., Becker, C., Wegerie, E., Marcussen, M., Overgaard-Hansen, K., Klenow, H., Marinaki, A. M., Harley, E. H., McBride, M. B., Simmonds, H. A., Moro, F., Cameron, J. S., Ogg, C. S., Williams, D. G., Rigden, S., Haycock, G., Miranda, M. E., Puig, J. G., Mateos, F. A., Vázquez, J. O., van Haperen, V. W. T. Ruiz, Veerman, G., Vermorken, J. B., Peters, G. J., van der Wilt, C. L., Noordhuis, P., Smid, K., Pinedo, H. M., Salerno, C., Lomonte, A., Giardini, O., Crifo, C., Smolenski, R. T., Yacoub, M. H., Seymour, A. M. -L., Stegmann, A. P. A., Honders, M. W., Willemze, R., Landegent, J. E., Stet, E. H., Vogels-Mentink, G. M., Lambooy, L. H. J., Trijbels, J. M. F., Torres, R. J., Tozzi, M. G., Pesi, R., Turriani, M., Allegrini, S., Camici, M., Ipata, P. L., van den Berg, A. A., Meinsma, J. R., van Lenthe, H., van Gennip, A. H., van Kuilenburg, A. B. P., Abeling, N. G. G. M., Bakker, H. D., Slingerland, R. J., Van den Bergh, F., and Sabina, R. L.

Published
1993
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46. Preface

Author

Giacomello, Alessandro, Peters, G. J., Eriksson, Staffan, De Abreu, Ronney, Kristensen, T., Munch-Petersen, B., Vincenzetti, S., Cambi, A., Neuhard, J., Garattini, E., Vita, A., Oka, J., Matsumoto, A., Hosokawa, Y., Inoue, S., Allegrini, S., Johnson, R. B., Fiol, C. J., Eriksson, S., Fabianowska-Majewska, K., Wasiak, T., Duley, J., Simmonds, A., Bretner, M., Felczak, K., Poznański, J., Dzik, J. M., Golos, B., Jarmuła, A., Rode, W., Kulikowski, T., Codacci-Pisanelli, G., Pinedo, H. M., Noordhuis, P., van Groeningen, C. J., van der Wilt, C. L., Franchi, F., Hatse, S., Balzarini, J., De Clercq, E., Marinello, E., Rosi, F., Dispensa, E., Mangiavacchi, P., Riario-Sforza, G., Agostinho, A. B., Smolenski, R. T., Müller, Mathias M., Roch-Ramel, F., Guisan, B., Diezi, J., Tavenier, M., Skladanowski, A. C., de Abreu, R. A., de Jong, J. W., Åmellem, Øystein, Löffler, Monika, Pettersen, Erik O., Boulieu, R., Lenoir, A., Bertocchi, M., Mornex, J. F., Makarewicz, W., Spychala J., Mitchell B. S., Barankiewcz J., Góra-Tybor, Joanna, Robak, Tadeusz, Spasokukotskaja T., Sasvári-Székely M., Piróth Zs., Kazimierczuk Z., Staub M., Keuzenkamp-Jansen, C W, De Abreu, R A, Bökkerink, J P M, Trijbels, J M F, Eriksson S., Warzocha, K., Krykowski, E., Góra-Tybor, J., Fronczak, A., Robak, T., Minelli, A., Moroni, M., Monacelli, N., Mezzasoma, I., Amici, A., Emanuelli, M., Raffaelli, N., Ruggieri, S., Magni, G., Carta, M. C., Mattana, A., Poddie, F., Sgarrella, F., Tozzi, M. G., Veerman, G., Ruiz van Haperen, V. W. T., van Moorsel, C. J. A., Pesi, R., Baiocchi, C., Camici, M., Ipata, P. L., Kozłowska, M., Świerczyński, J., Smoleński, R. T., Jastorff, B., Messina, E., Savini, F., Procopio, A., Giacomello, A., Wielgus-Kutrowska, B., Kulikowska, E., Wierzchowski, J., Bzowska, A., Shugar, D., Fairbanks, Lynette D, Ruckemann, Katarzyna, Simmonds, H Anne, Kaletha, K., Szymańska, G., Thebault, M., Raffin, J. P., Le Gal, Y., Griesmacher, Andrea, De Abreu, Ronney A., Zych, M., Ruckemann, K., Jagodzinski, P., Kochan, Z., Stolk, J., Boerbooms, A., De Abreu, R., de Koning, D., van de Putte, L., Fiorini, M., Bazzichi, L., Bertolini, G., Martini, C., Ciompi, M. L., Lucacchini, A., Pizzichini, M., Terzuoli, L., Arezzini, L., Fe, L., Pagani, R., Miscetti, P., Allegrucci, C., Sebesta, I., Duley, J. A., Simmonds, H. A., Gross, M., Salerno, C., Stone, T. W., Van den Berghe, G., Valik, Dalibor, Jones, James D., Guerranti, R., Fè, L., Sforza, G. Riario, Knecht, Wolfgang, Grein, Klaus, Lodi, R., Iotti, S., Barbiroli, B., Bonin, B., Chantin, C., Bory, C., Micheli, V., Jacomelli, G., Morozzi, G., Fioravanti, A., Marcolongo, R., Pompucci, G., Peters G J, Noordhuis P, Komissarov A, Holwerda U, Kok R M, Van Laar J A M, Van der Wilt C L, Van Groeningen C J, Pinedo H M, Perrett, David, Jacobsson, Bengt, Sisto A., Iezzi A., Di Carlo M., Pizzigallo E., Akhondzadeh, S., MacGregor, D. G., Ogilvy, H. V., Zoref-Shani, E., Brosh, S., Sidi, Y., Bromberg, Y., Sperling, O., van Gennip, A. H., Abeling, N. G. G. M., Stroomer, A. E. M., van Lenthe, H., Bakker, H. D., van Kuilenburg, A. B. P., Connolly, G. P., Abbott, N. J., Lilling, G., Gozes, I., Vreken, P., Meinsma, R., de Ahreu, R. A., Diasio, R. B., Albin, N., Johnson, M. R., Shahinian, H., Wang, K., Gathof, B. S., Rocchigiani, M., Puig, J. G., Mateos, F., Sestini, S., Krijt, J., Shin, Y., Gresser, U., Costa, A., Maximova, N., Andolina, M., Paci, M., Carrozzi, M., Osbich, A., Durighello, M., Cavalli, F., Geatti, O., Zammarchi, E., Morgan, Gareth, Webster, A. D. B., Slavin, S., Naparstek, E., Nagler, A., Acker, M., Cividalli, G., Kapellushnik, Y., Varadi, G., Ben-Yoseph, R., Or, R., Parfenov, V. V., Ignatenko, M. A., Amchenkova, A. M., Narovlyansky, A. N., Spoto, G., Mastropasqua, L., Gizzi, F., Arduini, A., Del Gallo, P., Ciancaglini, M., Gallenga, P. E., Šebesta, I., Zeman, J., Crifò, C., Di Vito, M., Lomonte, A., Gerber, G., Carlucci, F., Tabucchi, A., Vannoni P., Di Pietro M. C., Vincent, M. F., Bontemps, F., Boer, P., Rötzer, E., Ehrmann, D., Empl, W., Bride, M. B. Mc, Ogg, C. S., Cameron, J. S., Moro, F., Rigden, S., Rees, L., Hoff, W. Van't, Raman, V., Palmieri, P., Mastropierro, G., Albertazzi, A., Rucci, C., Darlington, L. G., Cotton, S. R., de Gorter, J. J., Lawrence, E. S., Petrie, A., Sarsam, R. P., Semple, M. J., Warburton, E. A., Quaratino, C. P., Talone, L., Di Sciascio, N., Hrebíček, M. H., Poupětová, H., Ledvinová, J., Elleder, M., Vondrák, K., Rees, P. C., Wonke, B., Thein, S. L., Clegg, J. B., Marlewski, M., Pennelli, A., Di Marzio, M., Angelini, G., Sabatino, G., de Koning, P., Kerstens, P., de Graaf, R., Hayek, G., and Cardona, F.

Published
1995
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47. Biometry, shell resistance and attachment of zebra and quagga mussels at the beginning of their co-existence in large European lakes.

Author

Balogh, Csilla, Serfőző, Zoltán, bij de Vaate, Abraham, Noordhuis, Ruurd, and Kobak, Jarosław

Abstract

In invasive dreissenid communities, the zebra mussel usually appears earlier and then is displaced by the quagga mussel. We analysed length-weight allometric relationships, attachment strength (2 days, 1 week and 1 month of exposure), shell crushing resistance and glycogen content across the entire size range of both species in large shallow European lakes where this displacement has recently occurred. In Lake Balaton (Hungary) and Ijsselmeer (The Netherlands), the soft tissue dry weight increment of zebra mussels per unit length decreased after the quagga mussel invasion and became lower than that of quagga mussels. In Lake Markermeer (the Netherlands), having relatively worse environmental conditions, dry weight increment per unit length was always higher in quagga mussels than in zebra mussels, but no negative change in dry weight increment occurred in zebra mussels during the quagga mussel invasion. Small zebra mussels had more resistant shells and stronger attachment than quagga mussels. These differences were reduced (shell hardness) or reversed (long-term attachment) in larger individuals. Zebra mussels had lower glycogen content than quagga mussels across the entire size range. Thus, the quagga mussel advantage over zebra mussel likely consists in the faster dry weight increment per unit length and higher storage product contents of the former, due to its lower investments in attachment strength and shell crushing resistance. [ABSTRACT FROM AUTHOR]

Published
2019
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48. Benthic hotspots in the pelagic zone: Light and phosphate availability alter aggregates of microalgae and suspended particles in a shallow turbid lake

Author

Brinkmann, Bregje W., Vonk, J. Arie, Beusekom, Sebastiaan A. M., Ibanez, Maria, Lucas Pardo, Miguel A., Noordhuis, Ruurd, Manders, Erik M. M., Verspagen, Jolanda M. H., and Geest, Harm G.

Abstract

Limnetic aggregates from a turbid delta lake with low dissolved nutrient availability were studied in relation to light and dissolved nutrient availability. Quick light‐attenuation restricts the euphotic zone to the top surface layer of the water column, whereas mineralization processes in the sediment specifically provide dissolved nutrients near the lakebed. This suggests neither the pelagic nor the benthic zone provides the combination of resources required for microalgal growth. Nutrient mineralization in aggregates could bridge this apparent spatial gap in light and nutrients by providing dissolved nutrients in the euphotic zone, promoting microalgal growth. To explore this, aggregates obtained from turbid and phosphate‐limited lake Markermeer (The Netherlands) were exposed in the laboratory to phosphate‐replete and phosphate depleted conditions, at high‐light and low‐light availability. Confocal microscopy revealed that aggregates exhibited alkaline phosphatase activity and contained microalgae, other microbes, and extracellular polymeric substances. The spatial distribution of the phosphatase activity in aggregates largely matched that of chlorophyll a(Chl a)‐lacking microbes, suggesting that these microbes were responsible for the activity. Colorimetric quantification revealed that aggregates exhibited over 1.9‐fold higher phosphatase activity than surrounding water. Two‐day exposure to different light and phosphate availabilities affected aggregate composition. Phosphate depleted conditions resulted in more Chl a‐lacking microbes and more phosphatase activity than phosphate‐replete conditions. Low‐light intensity resulted in higher abundance of extracellular polymeric substances than high‐light intensity. In contrast to aggregates from deep stratified systems, Markermeer aggregates were not enriched with dissolved phosphorus. These results suggest that P‐cycling in aggregates differs between shallow turbid and deep stratified ecosystems.

Published
2019
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