Evolutionary optimisation of neural network models for fish collective behaviours in mixed groups of robots and zebrafish

Animal and robot social interactions are interesting both for ethological studies and robotics. On the one hand, the robots can be tools and models to analyse animal collective behaviours, on the other hand, the robots and their artificial intelligence are directly confronted and compared to the natural animal collective intelligence. The first step is to design robots and their behavioural controllers that are capable of socially interact with animals. Designing such behavioural bio-mimetic controllers remains an important challenge as they have to reproduce the animal behaviours and have to be calibrated on experimental data. Most animal collective behavioural models are designed by modellers based on experimental data. This process is long and costly because it is difficult to identify the relevant behavioural features that are then used as a priori knowledge in model building. Here, we want to model the fish individual and collective behaviours in order to develop robot controllers. We explore the use of optimised black-box models based on artificial neural networks (ANN) to model fish behaviours. While the ANN may not be biomimetic but rather bio-inspired, they can be used to link perception to motor responses. These models are designed to be implementable as robot controllers to form mixed-groups of fish and robots, using few a priori knowledge of the fish behaviours. We present a methodology with multilayer perceptron or echo state networks that are optimised through evolutionary algorithms to model accurately the fish individual and collective behaviours in a bounded rectangular arena. We assess the biomimetism of the generated models and compare them to the fish experimental behaviours.Comment: 10 pages, 4 figure

Crop Updates 2011 - Nutrition, Precision Agriculture & Climate and Forecasting

This session covers sixteen papers from different authors: Nutrition 1. Balance® used in conventional cropping practice with half of the upfront fertiliser rate can sustain crop yield and build soil biological fertility, Deb Archdeacon1, Andrew Gulliver2 and David Cullen2, 1Agronomica, Wellington Mill, WA, 2Custom Composts, Nambeelup, WA 2. Effects of potassium (K) supply on plant growth, potassium uptake and grain Yield in wheat grown in grey sand, Qifu Ma1, Richard Bell1, Ross Brennan2 and Craig Scanlan2, 1School of Environmental Science, Murdoch University, 2Department of Agriculture and Food 3. Improving fertiliser management: redefining the relationship between soil tests and crop responses for wheat in WA, Wen Chen1, 2, Ross Brennan2, Geoff Anderson2, Richard Bell1 and Mike Bolland2, 1School of Environmental Science, Murdoch University, 2Department of Agriculture and Food 4. Improved phosphorus and potassium management: redefining the soil test and lupin response relationships in WA, Wen Chen1, 2, Ross Brennan2, Geoff Anderson2, Richard Bell1 and Mike Bolland2, 1School of Environmental Science, Murdoch University, Western Australia, 2Department of Agriculture and Food 5. Converting phosphorus retention index (PRI) to phosphorus buffering index (PBI) for Western Australian soils, Peter Rees and Sandy Alexander, Summit Fertilizers 6. Variability of radiometric potassium and Colwell potassium relationships across the Great Southern, Frank D’Emden, Precision Agronomics Australia 7. Rotary spading and mouldboard ploughing of water-repellent sandplain soils fulfils promise, Stephen Davies, Craig Scanlan and Breanne Best, Department of Agriculture and Food 8. Soil nitrous oxide (N2O) fluxes are low from a grain legume crop grown in a semi-arid climate Louise Barton1, Klaus Butterbach-Bahl2, Ralph Kiese2 and Daniel Murphy1, 1 School of Earth & Environment, University of Western Australia, 2 Karlsruhe Institute of Technology, Institute for Meteorology & Climate Research, Garmisch-Partenkirchen, Germany, 9. Mouldboard ploughing of sandplain soils – more grain, fewer weeds, Peter Newman Department of Agriculture and Food Precision Agriculture 10.What’s preventing growers from implementing precision agriculture (PA)? Roger Mandel1, Roger Lawes2 and Michael Robertson2, 1Curtin University, 2CSIRO 11. On how many paddocks does precision agriculture (PA) deliver a return? Roger Lawes1, Michael Robertson1 and Roger Mandel2, 1CSIRO Ecosystem Sciences, Floreat, WA, 2Curtin University 12. Demonstration pf precision agriculture (PA) principles in the Great Southern, Western Australia, Derk Bakker1, Jeremy Lemon1, Alison Lacey1, John Paul Collins1, Roger Mandel2, Frank D’Emden3, Glen Riethmuller1, 1Department of Agriculture and Food, 2Curtin University, 3Precision Agronomics Australia Climate and Forecasting 13. Statistical seasonal rainfall forecasts for south west Australia, Fiona H Evans Department of Agriculture of Food 14. How has changing climate recently affected Western Australia’s capacity to increase crop productivity and water use efficiency? David Stephens, Department of Agriculture and Food 15. Is Yield Prophet® a useful tool in Western Australia? — an agribusiness perspective, Caroline Peek, Department of Agriculture and Food 16. A season of Yield Prophet® — how it saw the dry, Tim Scanlon and Caroline Peek Department of Agriculture of Foo

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

How 'dynasty' became a modern global concept : intellectual histories of sovereignty and property

The modern concept of ‘dynasty’ is a politically-motivated modern intellectual invention. For many advocates of a strong sovereign nation-state across the nineteenth and early twentieth century, in France, Germany, and Japan, the concept helped in visualizing the nation-state as a primordial entity sealed by the continuity of birth and blood, indeed by the perpetuity of sovereignty. Hegel’s references to ‘dynasty’, read with Marx’s critique, further show how ‘dynasty’ encoded the intersection of sovereignty and big property, indeed the coming into self-consciousness of their mutual identification-in-difference in the age of capitalism. Imaginaries about ‘dynasty’ also connected national sovereignty with patriarchal authority. European colonialism helped globalize the concept in the non-European world; British India offers an exemplar of ensuing debates. The globalization of the abstraction of ‘dynasty’ was ultimately bound to the globalization of capitalist-colonial infrastructures of production, circulation, violence, and exploitation. Simultaneously, colonized actors, like Indian peasant/‘tribal’ populations, brought to play alternate precolonial Indian-origin concepts of collective regality, expressed through terms like ‘rajavamshi’ and ‘Kshatriya’. These concepts nourished new forms of democracy in modern India. Global intellectual histories can thus expand political thought today by provincializing and deconstructing Eurocentric political vocabularies and by recuperating subaltern models of collective and polyarchic power.PostprintPeer reviewe

Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats.

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., Andre, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbeoch, M., Ignaszewski, M., Baringer, M. O., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouet, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourles, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P., Rannou, J., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P., Velez-Belchi, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S., & Park, H. Argo data 1999-2019: two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats. Frontiers in Marine Science, 7, (2020): 700, doi:10.3389/fmars.2020.00700.In the past two decades, the Argo Program has collected, processed, and distributed over two million vertical profiles of temperature and salinity from the upper two kilometers of the global ocean. A similar number of subsurface velocity observations near 1,000 dbar have also been collected. This paper recounts the history of the global Argo Program, from its aspiration arising out of the World Ocean Circulation Experiment, to the development and implementation of its instrumentation and telecommunication systems, and the various technical problems encountered. We describe the Argo data system and its quality control procedures, and the gradual changes in the vertical resolution and spatial coverage of Argo data from 1999 to 2019. The accuracies of the float data have been assessed by comparison with high-quality shipboard measurements, and are concluded to be 0.002°C for temperature, 2.4 dbar for pressure, and 0.01 PSS-78 for salinity, after delayed-mode adjustments. Finally, the challenges faced by the vision of an expanding Argo Program beyond 2020 are discussed.AW, SR, and other scientists at the University of Washington (UW) were supported by the US Argo Program through the NOAA Grant NA15OAR4320063 to the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) at the UW. SW and other scientists at the Woods Hole Oceanographic Institution (WHOI) were supported by the US Argo Program through the NOAA Grant NA19OAR4320074 (CINAR/WHOI Argo). The Scripps Institution of Oceanography's role in Argo was supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). Euro-Argo scientists were supported by the Monitoring the Oceans and Climate Change with Argo (MOCCA) project, under the Grant Agreement EASME/EMFF/2015/1.2.1.1/SI2.709624 for the European Commission

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe