@article{BersierFruchterStrolgeretal.2006,
  author    = {Bersier, David and Fruchter, Andrew S. and Strolger, Louis-Gregory and Gorosabel, Javier and Levan, Andrew and Burud, Ingunn and Rhoads, James E. and Becker, Andrew C. and Cassan, Andrew C. and Chornock, Ryan and Covino, Stefano and De Jong, Roelof S. and Dominis, Dijana and Filippenko, Alexei V. and Hjorth, Jens and Holmberg, Johan and Malesani, Daniele and Mobasher, Bahram and Olsen, Kurt A. G. and Stefanon, Mauro and Castro Cer{\´o}n, Jos{\´e} Mar{\´i}a C. and Fynbo, Johan P. U. and Holland, Stephen T. and Kouveliotou, Chryssa and Pedersen, Hans-Georg and Tanvir, Nieal R. and Woosley, S. E.},
  title     = {Evidence for a supernova associated with the X-ray flash 020903},
  issn      = {0004-637X},
  doi       = {10.1086/502640},
  year      = {2006},
  abstract  = {We present ground-based and Hubble Space Telescope optical observations of the X-ray flash ( XRF) 020903, covering 300 days. The afterglow showed a very rapid rise in the first day, followed by a relatively slow decay in the next few days. There was a clear bump in the light curve after similar to 25 days, accompanied by a drastic change in the spectral energy distribution. The light curve and the spectral energy distribution are naturally interpreted as describing the emergence and subsequent decay of a supernova ( SN), similar to SN 1998bw. At peak luminosity, the SN is estimated to be 0.8 +/- 0.1 mag fainter than SN 1998bw. This argues in favor of the existence of a SN associated with this XRF. A spectrum obtained 35 days after the burst shows emission lines from the host galaxy. We use this spectrum to put an upper limit on the oxygen abundance of the host at [O/H] <= 0.6 dex. We also discuss a possible trend between the softness of several bursts and the early behavior of the optical afterglow, in the sense that XRFs and X-ray-rich gamma- ray bursts ( GRBs) seem to have a plateau phase or even a rising light curve. This can be naturally explained in models in which XRFs are similar to GRBs but are seen off the jet axis.},
  language  = {en}
}
@article{HollandBurrowDythametal.2009,
  author    = {Holland, E. P. and Burrow, Jennifer F. and Dytham, Calvin and Aegerter, James N.},
  title     = {Modelling with uncertainty : introducing a probabilistic framework to predict animal population dynamics},
  issn      = {0304-3800},
  doi       = {10.1016/j.ecolmodel.2009.02.013},
  year      = {2009},
  abstract  = {Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback-Leibier distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios. We illustrate the framework's power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.},
  language  = {en}
}