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Salgesch, Switzerland

The Sempach Bird Observatory is a bird observatory and ornithological research centre, also known as the Swiss Ornithological Institute, which is based at the town of Sempach in the district of Sursee in the canton of Lucerne in Switzerland. It overlooks Lake Sempach. Founded in 1924, it is a non-profit organization and the largest private field research institute in Switzerland. It carries out a bird ringing program as well as other ornithological research, conservation biology and public education. Wikipedia.


Kery M.,Swiss Ornithological Institute | Royle J.A.,U.S. Geological Survey
Journal of Animal Ecology | Year: 2010

1. Population assessment in changing environments is challenging because factors governing abundance may also affect detectability and thus bias observed counts. We describe a hierarchical modelling framework for estimating abundance corrected for detectability in metapopulation designs, where observations of 'individuals' (e.g. territories) are replicated in space and time. We consider two classes of models; first, we regard the data as independent binomial counts and model abundance and detectability based on a product-binomial likelihood. Secondly, we use the more complex detection-non-detection data for each territory to form encounter history frequencies, and analyse the resulting multinomial/Poisson hierarchical model. Importantly, we extend both models to directly estimate population trends over multiple years. Our models correct for any time trends in detectability when assessing population trends in abundance. 2. We illustrate both models for a farmland and a woodland bird species, skylark Alauda arvensis and willow tit Parus montanus, by applying them to Swiss BBS data, where 268 1 km 2 quadrats were surveyed two to three times during 1999-2003. We fit binomial and multinomial mixture models where log (abundance) depended on year, elevation, forest cover and transect route length, and logit(detection) on year, season and search effort. 3. Parameter estimates were very similar between models with confidence intervals overlapping for most parameters. Trend estimates were similar for skylark (-0.074 ± 0.041 vs. -0.047 ± 0.019) and willow tit (0.044 ± 0.046 vs. 0.047 ± 0.018). As expected, the multinomial model gave more precise estimates, but also yielded lower abundance estimates for the skylark. This may be due to effects of territory misclassification (lumping error), which do not affect the binomial model. 4. Both models appear useful for estimating abundance and population trends free from distortions by detectability in metapopulation designs with temporally replicated observations. The ability to obtain estimates of abundance and population trends that are unbiased with respect to any time trends in detectability ought to be a strong motivation for the collection of replicate observation data. ©2009 The Authors. Journal compilation ©2009 British Ecological Society. Source


Kery M.,Swiss Ornithological Institute | Gardner B.,U.S. Geological Survey | Monnerat C.,Center Suisse Of Cartographie Of La Faune Cscf
Journal of Biogeography | Year: 2010

Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site-occupancy models applied to replicated detection/non-detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of 'cheap' checklist data greatly enhances the scope of applications of this useful class of models. © 2010 Blackwell Publishing Ltd. Source


Schmaljohann H.,Institute of Avian Research | Naef-Daenzer B.,Swiss Ornithological Institute
Journal of Animal Ecology | Year: 2011

1.An innate migration strategy guides birds through space and time. Environmental variation further modulates individual behaviour within a genetically determined frame. In particular, ecological barriers could influence departure direction and its timing. A shift in the migratory direction in response to an ecological barrier could reveal how birds adjust their individual trajectories to environmental cues and body condition. 2.Northern wheatears of the Greenland/Iceland subspecies Oenanthe oenanthe leucorhoa arrive in Western Europe en route from their West African winter range. They then undergo an endogenously controlled shift in migratory direction from north to north-west to cross a large ecological barrier, the North Atlantic. We radiotracked these songbirds departing from Helgoland, a small island in the North Sea, over an unprecedented range of their journey. 3.Here, we show that both birds' body condition and the wind conditions that they encountered influenced the departure direction significantly. Jointly high fuel loads and favourable wind conditions enabled migrants to cross large stretches of sea. Birds in good condition departed early in the night heading to the sea towards their breeding areas, while birds with low fuel loads and/or flying in poor weather conditions departed in directions leading towards nearby mainland areas during the entire night. These areas could be reached even after setting off late at night. 4.Behavioural adjustment of migratory patterns is a critical adaptation for crossing ecological barriers. The observed variation in departure direction and time in relation to fuel load and wind revealed that these birds have an innate ability to respond by jointly incorporating internal information (body condition) and external information (wind support). © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society. Source


Bauer S.,Swiss Ornithological Institute | Bauer S.,Netherlands Institute of Ecology | Hoye B.J.,University of Colorado at Boulder | Hoye B.J.,Deakin University
Science | Year: 2014

Animal migrations span the globe, involving immense numbers of individuals from a wide range of taxa. Migrants transport nutrients, energy, and other organisms as they forage and are preyed upon throughout their journeys. These highly predictable, pulsed movements across large spatial scales render migration a potentially powerful yet underappreciated dimension of biodiversity that is intimately embedded within resident communities. We review examples from across the animal kingdom to distill fundamental processes by which migratory animals influence communities and ecosystems, demonstrating that they can uniquely alter energy flow, food-web topology and stability, trophic cascades, and the structure of metacommunities. Given the potential for migration to alter ecological networks worldwide, we suggest an integrative framework through which community dynamics and ecosystem functioning may explicitly consider animal migrations. Source


Schaub M.,Swiss Ornithological Institute
Biological Conservation | Year: 2012

Energy production with wind turbines is increasing, because this form of energy production is CO 2 neutral and renewable, and because wind power is subsidised in many countries. However, wind turbines are not without impact on biodiversity, rather, they can affect bird and bat populations through collision-induced mortality. It is relatively well studied how wind turbine architecture or the surrounding habitat affect the collision risk of birds and bats. It is much less well understood how losses due to collisions affect bird and bat populations. Moreover, it is currently unknown how the spatial configuration of wind turbines in the landscape affects populations. I addressed these two questions using an individual-based simulation model inspired by the Swiss red kite Milvus milvus population. This species is a frequent collision victim at turbines and one of Europe's sole endemic species. I predicted the fate of populations in relation to the number and spatial configuration of wind turbines. I found that population growth rates declined progressively with an increasing number of wind turbines. These negative effects can be weakened if wind turbines are aggregated in power plants. Quantitatively the results strongly depended on the parametric form of the relationship between collision risk and the distance between wind turbines and kite nest location. Unfortunately, empirical knowledge about this relationship is scarce. As the effect of wind turbines depends on their total number and their spatial configuration within the area inhabited by a raptor population, I emphasise the importance of making environmental impact assessments not on a case-by-case basis but rather for an entire region with all its wind power plants, which collectively exert an impact on a raptor population. This must include the impact of extant as well as planned wind turbines in the same region in order to be biologically meaningful. © 2012 Elsevier Ltd. Source

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