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- Broekman, Maarten J. E., et al.
(författare)
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Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data
- 2022
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Ingår i: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 31:8, s. 1526-1541
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert-based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert-based information with detailed empirical evidence. Here, we compared expert-based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individuals from 49 mammal species.Location: Worldwide.Time period: 1998-2021.Major taxa studied: Forty-nine terrestrial mammal species.Methods: Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types.Results: IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively.Main conclusions: We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data.
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- Hlozek, R., et al.
(författare)
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Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)
- 2023
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Ingår i: Astrophysical Journal Supplement Series. - 0067-0049 .- 1538-4365. ; 267:2
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Tidskriftsartikel (refereegranskat)abstract
- Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.
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- Williams, S. C., et al.
(författare)
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See Change : VLT spectroscopy of a sample of high-redshift Type Ia supernova host galaxies
- 2020
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Ingår i: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 495:4, s. 3859-3880
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Tidskriftsartikel (refereegranskat)abstract
- The Supernova Cosmology Project has conducted the 'See Change' programme, aimed at discovering and observing high-redshift (1.13 <= z <= 1.75) Type Ia supernovae (SNe Ia). We used multifilter Hubble Space Telescope (HST) observations of massive galaxy clusters with sufficient cadence to make the observed SN Ia light curves suitable for a cosmological probe of dark energy at z > 0.5. This See Change sample of SNe Ia with multi-colour light curves will be the largest to date at these redshifts. As part of the See Change programme, we obtained ground-based spectroscopy of each discovered transient and/or its host galaxy. Here, we present Very Large Telescope (VCT) spectra of See Change transient host galaxies, deriving their redshifts, and host parameters such as stellar mass and star formation rate. Of the 39 See Change transients/hosts that were observed with the VLT, we successfully determined the redshift for 26, including 15 SNe Ia at z > 0.97. We show that even in passive environments, it is possible to recover secure redshifts for the majority of SN hosts out to z = 1.5. We find that with typical exposure times of 3-4h on an 8-m-class telescope we can recover similar to 75 per cent of SN Ia redshifts in the range of 0.97 < z < 1.5. Furthermore, we show that the combination of HST photometry and VLT spectroscopy is able to provide estimates of host galaxy stellar mass that are sufficiently accurate for use in a mass-step correction in the cosmological analysis.
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