22 Works

2012 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2017 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2018 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Data from: Origins of global mountain plant biodiversity: testing the “mountain-geobiodiversity hypothesis”

Alexandra Muellner-Riehl, Jan Schnitzler, W. Daniel Kissling, Volker Mosbrugger, Kenneth Rijsdijk, Arie Seijmonsbergen, Hannes Versteegh & Adrien Favre
Aim Our objective is to analyse global-scale patterns of mountain biodiversity (vascular plants) and the driving forces leading to the observed patterns. More specifically, we test the “mountain geobiodiversity hypothesis” (MGH) which is based on the assumption that it is not mountain-uplift alone which drives the evolution of mountain biodiversity, but rather the combination of geodiversity evolution and Neogene and Pleistocene climate changes. Hence, we address the following questions: 1) Do areas of high geodiversity...

Data from: Combined transcriptome and metabolome analysis identifies defence responses in spider-mite infested pepper

Yuanyuan Zhang, Harro J. Bouwmeester & Iris F. Kappers
Plants regulate responses towards herbivory through fine-tuning of defence-related hormone production, expression of defence genes and production of secondary metabolites. Jasmonic acid (JA) plays a key role in plant-herbivorous arthropod interactions. To understand how pepper responds to herbivory, leaf transcriptomes and metabolomes of two genotypes different in their susceptibility to spider mites, were studied. Mites induced both JA and salicylic acid (SA) signalling. However, mite infestation and exogenous JA resulted in distinct transcriptome profiles. Compared...

2010 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2015 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

2016 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Data from: Which frugivory‐related traits facilitated historical long‐distance dispersal in the custard apple family (Annonaceae)?

Renske E. Onstein, W. Daniel Kissling, Lars W. Chatrou, Thomas L. P. Couvreur, Hélène Morlon & Hervé Sauquet
Aim Long-distance dispersal has contributed to the disjunct biogeographical distribution of rain forest plants – something that has fascinated biogeographers since Humboldt’s time. However, the dispersal ‘agent’ for these tropical plant lineages remains puzzling. Here, we investigate which frugivory-related traits may have facilitated past intercontinental long-distance dispersal in the custard apple family (Annonaceae), a major vertebrate-dispersed tropical plant family. We hypothesize that long-distance dispersal was associated with the evolution of traits related to dispersal by...

2014 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Data from: Canopy height explains species richness in the largest clade of Neotropical lianas

Leila Meyer, José Alexandre F. Diniz-Filho, Lúcia G. Lohmann, Joaquín Hortal, Elisa Barreto, Thiago Rangel & W. Daniel Kissling
Aim: Tall and structurally complex forests can provide ample habitat and niche space for climbing plants, supporting high liana species richness. We test to what extent canopy height (as proxy of 3D habitat structure), climate and soil interact to determine species richness in the largest clade of Neotropical lianas. We expect that the effect of canopy height on species richness is higher for lianas from closed tropical rainforests compared to riparian and savanna habitats. Location:...

Data from: PalmTraits 1.0, a species-level functional trait database for palms worldwide

W. Daniel Kissling, Henrik Balslev, William J. Baker, John Dransfield, Bastian Göldel, Jun Ying Lim, Renske E. Onstein & Jens-Christian Svenning
Plant traits are critical to plant form and function —including growth, survival and reproduction— and therefore shape fundamental aspects of population and ecosystem dynamics as well as ecosystem services. Here, we present a global species-level compilation of key functional traits for palms (Arecaceae), a plant family with keystone importance in tropical and subtropical ecosystems. We derived measurements of essential functional traits for all (>2500) palm species from key sources such as monographs, books, other scientific...

Climate drives community-wide divergence within species over a limited spatial scale: evidence from an oceanic island

Antonia Salces-Castellano, Jairo Patiño, Nadir Alvarez, Carmelo Andújar, Paula Arribas, Juan J. Braojos-Ruiz, Marcelino Del Arco-Aguilar, Víctor García-Olivares, Dirk Karger, Heriberto López, Ioanna Manolopoulou, Pedro Oromí, Antonio J. Pérez-Delgado, William W. Peterman, Kenneth F. Rijsdijk & Brent C. Emerson
Geographic isolation substantially contributes to species endemism on oceanic islands when speciation involves the colonisation of a new island. However, less is understood about the drivers of speciation within islands. What is lacking is a general understanding of the geographic scale of gene flow limitation within islands, and thus the geographic scale and drivers of geographical speciation within insular contexts. Using a community of beetle species, we show that when dispersal ability and climate tolerance...

Less is more: on-board lossy compression of accelerometer data increases biologging capacity

Rascha Nuijten, Theo Gerrits, Judy Shamoun-Baranes & Bart Nolet
GPS-tracking devices have been used in combination with a wide range of additional sensors to study animal behaviour, physiology and interaction with their environment. Tri-axial accelerometers allow researchers to remotely infer the behaviour of individuals, at all places and times. Collection of accelerometer data is relatively cheap in terms of energy usage, but the amount or raw data collected generally requires much storage space and is particularly demanding in terms of energy needed for data...

Data from: Use and categorization of Light Detection and Ranging vegetation metrics in avian diversity and species distribution research

Tristan R. M. Bakx, Zsófia Koma, Arie C. Seijmonsbergen & W. Daniel Kissling
Aim: Vegetation structure is a key determinant of animal diversity and species distributions. The introduction of Light Detection and Ranging (LiDAR) has enabled the collection of massive amounts of point cloud data for quantifying habitat structure at fine resolution. Here, we review the current use of LiDAR-derived vegetation metrics in diversity and distribution research of birds, a key group for understanding animal-habitat relationships. Location: Global. Methods: We review 50 relevant papers and quantify where, in...

Data from: Breeding success but not mate choice is phenotype- and context-dependent in a color polymorphic raptor

Laura Gangoso & Jordi Figuerola
Morph-specific mate choice has been proposed as one of the evolutionary mechanisms that contribute to the maintenance of variation in color polymorphic systems. Coloration usually covaries with other phenotypic traits affecting life history and thus is often used as a criterion for mate choice. Here, we assess whether mating patterns, natal dispersal, and breeding output are phenotype-dependent in the color polymorphic Eleonora’s falcon. We used a long-term dataset of 946 individually ringed adult falcons that...

2013 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Beyond the group: how food, mates and group size influence inter-group encounters in wild bonobos

Stefano Lucchesi, Leveda Cheng, Karline Janmaat, Roger Mundry, Anne Pisor & Surbeck Martin
In social-living animals, interactions between groups are frequently agonistic, but they can also be tolerant and even cooperative. Inter-group tolerance and cooperation are regarded as a crucial step in the formation of highly-structured multilevel societies. Behavioral ecological theory suggests that inter-group tolerance and cooperation can emerge either when the costs of hostility outweigh the benefits of exclusive resource access, or when both groups gain fitness benefits through their interactions. However, the factors promoting inter-group tolerance...

Data from: Projecting consequences of global warming for the functional diversity of fleshy-fruited plants and frugivorous birds along a tropical elevational gradient

Larissa Nowak, W. Daniel Kissling, Irene M. A. Bender, D. Matthias Dehling, Till Töpfer, Katrin Böhning-Gaese & Matthias Schleuning
Aim: Species in ecological communities are linked by biotic interactions. It is therefore important to simultaneously study the impacts of global warming on interdependent taxa from different trophic levels. Here, we quantify current and potential future associations of functional diversity (based on multiple traits) and functional identity (based on individual traits) between interacting taxa using projection models under climate change. Location: A tropical elevational gradient (500–3500 m a.s.l.) in the Manú biosphere reserve, southeast Peru...

Shorebird feeding specialists differ in how environmental conditions alter their foraging time

Henk-Jan Van Der Kolk, Bruno J. Ens, Kees Oosterbeek, Willem Bouten, Andrew M. Allen, Magali Frauendorf, Thomas K. Lameris, Thijs Oosterbeek, Symen Deuzeman, Kelly De Vries, Eelke Jongejans & Martijn Van De Pol
Feeding specialisation is a common cause of individual variation. Fitness payoffs of specialisation vary with environmental conditions, but the underlying behavioural mechanisms are poorly understood. Such mechanistic knowledge, however, is crucial to reliably predict responses of heterogeneous populations to environmental change. We quantified spatiotemporal allocation of foraging behaviour in wintering Eurasian oystercatchers (Haematopus ostralegus), a species in which feeding specialisation can be inferred from bill shape. We combined GPS and accelerometer data to quantify foraging...

Data from: No signal of deleterious mutation accumulation in conserved gene sequences of extant asexual hexapods

Alexander Brandt, Jens Bast, Stefan Scheu, Karen Meusemann, Alexander Donath, Kai Schütte, Ryuichiro Machida & Ken Kraaijeveld
Loss of sex and recombination is generally assumed to impede the effectiveness of purifying selection and to result in the accumulation of slightly deleterious mutations. Empirical evidence for this has come from several studies investigating mutational load in a small number of individual genes. However, recent whole transcriptome based studies have yielded inconsistent results, hence questioning the validity of the assumption of mutational meltdown in asexual populations. Here, we study the effectiveness of purifying selection...

2011 Machine Learning Data Set for NASA's Solar Dynamics Observatory - Atmospheric Imaging Assembly

David Fouhey, Meng Jin, Mark Cheung, Abndres Munoz-Jaramillo, Richard Galvez, Rajat Thomas, Paul Wright, Alexander Szenicer, Monica G. Bobra, Yang Liu & James Mason
We present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a...

Registration Year

  • 2019
    22

Resource Types

  • Dataset
    22

Affiliations

  • University of Amsterdam
    13
  • Hansen Experimental Physics Laboratory, Stanford University
    9
  • Electrical Engineering and Computer Science Department, University of Michigan
    9
  • SUPA School of Physics and Astronomy, University of Glasgow
    9
  • NASA Goddard Space Flight Center
    9
  • Center for Data Science, New York University
    9
  • Lockheed Martin Solar & Astrophysics Laboratory
    9
  • SETI Institute
    9
  • Southwest Research Institute
    9
  • Department of Psychiatry, University of Amsterdam
    9