@article{WichmannJohstSchwageretal.2005,
  author    = {Wichmann, Matthias and Johst, Karin and Schwager, Monika and Jeltsch, Florian and Blasius, Bernd},
  title     = {Extinction risk, coloured noise and the scaling of variance},
  year      = {2005},
  abstract  = {The impact of temporally correlated fluctuating environments (coloured noise) on the extinction risk of populations has become a main focus in theoretical population ecology. In this study we particularly focus on the extinction risk in strongly autocorrelated environments. Here, in contrast to moderate autocorrelation, we found the extinction risk to be highly dependent on the process of noise generation, in particular on the method of variance scaling. Such variance scaling is commonly applied to avoid variance-driven biases when comparing the extinction risk for white and coloured noise. In this study we found an often-used scaling technique to lead to high variability in the resulting variances of different time series for strong auto-correlation eventually leading to deviations in the projected extinction risk. Therefore, we present an alternative method that always delivers the target variance, even in the case of strong temporal correlation. Furthermore, in contrast to the earlier method, our very intuitive method is not bound to auto-regressive processes but can be applied to all types of coloured noises. We recommend the method introduced here to be used when the target of interest is the effect of noise colour on extinction risk not obscured by any variance effects.},
  language  = {en}
}
@article{WichmannDeanJeltsch2006,
  author    = {Wichmann, Matthias and Dean, W. R. J. and Jeltsch, Florian},
  title     = {Predicting the breeding success of large raptors in arid southern Africa : a first assessment},
  year      = {2006},
  abstract  = {Raptors are often priorities for conservation efforts and breeding success is a target measure for assessing their conservation status. The breeding success of large raptors in and southern Africa is thought to be higher in years of high rainfall. While this correlation has been found in several studies, it has not yet been shown for data from a wider geographical area. In conservation research, it is important to explore the differences between spatially- separated populations to estimate and to compare their conservation status, and to deduce specific management strategies. Using a theoretical approach, we develop a simplistic model to explain the breeding success-rainfall relationship in large African raptors at larger spatial scales. Secondly, we validate this model and we show that the inclusion of field data leads to consistent predictions. In particular, we recommend that the average size of the 'effective territory' should be included in the relationship between annual rainfall and breeding success of raptors in and southern Africa. Accordingly, we suggest that breeding success is a function of precipitation and inter- nest distance. We present a new measure of territory quality depending on rainfall and territory size. We suggest that our model provides a useful first approach to assess breeding success in large raptors of and southern Africa. However, we strongly emphasise the need to gather more data to further verify our model. A general problem in conservation research is to compare the status of populations assessed in different study areas under changing environmental conditions. Our simplistic approach indicates that this problem can be overcome by using a weighted evaluation of a target measure (i.e. breeding success), taking regional differences into account},
  language  = {en}
}
@article{JeltschWichmannDean2004,
  author    = {Jeltsch, Florian and Wichmann, Matthias and Dean, W. R. J.},
  title     = {Global change challenges the Tawny Eagle (Aquila rapax) : modelling extinction risk with respect to predicted climate and land use changes},
  year      = {2004},
  language  = {en}
}
@article{JeltschWichmannJohstetal.2003,
  author    = {Jeltsch, Florian and Wichmann, Matthias and Johst, J. and Moloney, Kirk A. and Wissel, Christian},
  title     = {Extinction risk in periodically fluctuating environments},
  year      = {2003},
  language  = {en}
}
@article{JeltschWichmannDeanetal.2003,
  author    = {Jeltsch, Florian and Wichmann, Matthias and Dean, W. R. J. and Moloney, Kirk A. and Wissel, Christian},
  title     = {Implications of climate change for the persistence of raptors in arid savannah},
  year      = {2003},
  language  = {en}
}
@article{WichmannJeltschDeanetal.2002,
  author    = {Wichmann, Matthias and Jeltsch, Florian and Dean, Richard and Moloney, Kirk A. and Wissel, Christian},
  title     = {Does climate change in arid savanna affect the population persistence of raptors?},
  year      = {2002},
  language  = {en}
}
@article{WichmannJeltschDeanetal.2002,
  author    = {Wichmann, Matthias and Jeltsch, Florian and Dean, Richard and Moloney, Kirk A. and Wissel, Christian},
  title     = {Weather does matter : simulating population dynamics of tawny eagle (Aquila rapax) under various rainfall scenarios},
  year      = {2002},
  language  = {en}
}
@misc{GeirhosTemmeRauberetal.2018,
  author    = {Geirhos, Robert and Temme, Carlos R. Medina and Rauber, Jonas and Sch{\"u}tt, Heiko Herbert and Bethge, Matthias and Wichmann, Felix A.},
  title     = {Generalisation in humans and deep neural networks},
  series = {Proceedings of the 32nd International Conference on Neural Information Processing Systems},
  volume    = {31},
  journal   = {Proceedings of the 32nd International Conference on Neural Information Processing Systems},
  publisher = {Curran Associates Inc.},
  address   = {Red Hook},
  issn      = {1049-5258},
  pages     = {7549 -- 7561},
  year      = {2018},
  abstract  = {We compare the robustness of humans and current convolutional deep neural networks (DNNs) on object recognition under twelve different types of image degradations. First, using three well known DNNs (ResNet-152, VGG-19, GoogLeNet) we find the human visual system to be more robust to nearly all of the tested image manipulations, and we observe progressively diverging classification error-patterns between humans and DNNs when the signal gets weaker. Secondly, we show that DNNs trained directly on distorted images consistently surpass human performance on the exact distortion types they were trained on, yet they display extremely poor generalisation abilities when tested on other distortion types. For example, training on salt-and-pepper noise does not imply robustness on uniform white noise and vice versa. Thus, changes in the noise distribution between training and testing constitutes a crucial challenge to deep learning vision systems that can be systematically addressed in a lifelong machine learning approach. Our new dataset consisting of 83K carefully measured human psychophysical trials provide a useful reference for lifelong robustness against image degradations set by the human visual system.},
  language  = {en}
}
@article{vonderLippeBullockKowariketal.2013,
  author    = {von der Lippe, Moritz and Bullock, James M. and Kowarik, Ingo and Knopp, Tatjana and Wichmann, Matthias},
  title     = {Human-mediated dispersal of seeds by the airflow of vehicles},
  series = {PLoS one},
  volume    = {8},
  journal   = {PLoS one},
  number    = {1},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0052733},
  pages     = {10},
  year      = {2013},
  abstract  = {Human-mediated dispersal is known as an important driver of long-distance dispersal for plants but underlying mechanisms have rarely been assessed. Road corridors function as routes of secondary dispersal for many plant species but the extent to which vehicles support this process remains unclear. In this paper we quantify dispersal distances and seed deposition of plant species moved over the ground by the slipstream of passing cars. We exposed marked seeds of four species on a section of road and drove a car along the road at a speed of 48 km/h. By tracking seeds we quantified movement parallel as well as lateral to the road, resulting dispersal kernels, and the effect of repeated vehicle passes. Median distances travelled by seeds along the road were about eight meters for species with wind dispersal morphologies and one meter for species without such adaptations. Airflow created by the car lifted seeds and resulted in longitudinal dispersal. Single seeds reached our maximum measuring distance of 45 m and for some species exceeded distances under primary dispersal. Mathematical models were fit to dispersal kernels. The incremental effect of passing vehicles on longitudinal dispersal decreased with increasing number of passes as seeds accumulated at road verges. We conclude that dispersal by vehicle airflow facilitates seed movement along roads and accumulation of seeds in roadside habitats. Dispersal by vehicle airflow can aid the spread of plant species and thus has wide implications for roadside ecology, invasion biology and nature conservation.},
  language  = {en}
}
@article{Wichmann2002,
  author    = {Wichmann, Matthias},
  title     = {Survival in changing environments : modeling the impact of climate change and land use on raptors in arid savanna},
  pages     = {103 S.},
  year      = {2002},
  language  = {en}
}