Abstract
Abstract. A model of avian goal-oriented navigation is described that is based on two empirical findings building a bridge from ornithology to atmospheric chemistry. (1) To orient their courses homeward from distant unfamiliar areas, homing pigeons require long-term exposure to undisturbed winds at the home site and olfactory access to the environmental air at home and abroad. (2) Above Germany, ratios among some atmospheric trace gases vary along differently oriented spatial gradients as well as depending on wind direction. The model emulates finding (1) by utilising the analysed air samples on which finding (2) is based. Starting with an available set of 46 omnipresent compounds, virtual pigeons determine the profile of relative weights among them at each of 96 sites regularly distributed around a central home site within a radius of 200 km and compare this profile with corresponding profiles determined at home under varying wind conditions. Referring to particular similarities and dissimilarities depending on home-wind direction, they try to estimate, at each site, the compass direction they should fly in order to approach home. To make the model work, an iterative algorithm imitates evolution by modifying sensitivity to the individual compounds stepwise at random. In the course of thousands of trial-and-error steps it gradually improves homeward orientation by selecting smaller sets of most useful and optimally weighted substances from whose proportional configurations at home and abroad it finally derives navigational performances similar to those accomplished by real pigeons. It is concluded that the dynamic chemical atmosphere most likely contains sufficient spatial information for home-finding over hundreds of kilometres of unfamiliar terrain. The underlying chemo-atmospheric processes remain to be clarified.
Highlights
This article deals with a problem that unexpectedly joins two disciplines which have never been considered to be in any way connected: avian behavioural biology and chemistry of the free atmosphere
Starting with an available set of 46 omnipresent compounds, virtual pigeons determine the profile of relative weights among them at each of 96 sites regularly distributed around a central home site within a radius of 200 km and compare this profile with corresponding profiles determined at home under varying wind conditions
Referring to particular similarities and dissimilarities depending on home-wind direction, they try to estimate, at each site, the compass direction they should fly in order to approach home
Summary
This article deals with a problem that unexpectedly joins two disciplines which have never been considered to be in any way connected: avian behavioural biology and chemistry of the free atmosphere. Forty years later we have a sizeable collection of coherent experimental results showing that experience of natural winds at the home site and smelling of airborne trace gases is a necessary precondition for homeward navigation of pigeons and other birds from unfamiliar areas over distances of some 50–300 km and more (for review and discussion of debated problems see Papi, 1986, 1989, 1991; Wallraff, 1990, 1996, 2001, 2004, 2005a, b, 2010; Gagliardo, 2013; see Able, 1996; Gagliardo et al, 2013). The present study aims to answer this question: to what extent can pigeons without knowledge of any conditions away from home, but experienced with winds and correlated specific olfactory sensations at home, potentially deduce information on the direction they should fly from trace gases perceived at various sites around their home loft at distances of up to 200 km? In the foreground, we have a biological problem: how do birds navigate? In the background, we have a problem of atmospheric chemistry, which appears not less intriguing: how is it possible that sufficiently stable and spatially far-reaching regularities in the proportional composition of a number of trace gases over the central European continent do exist? The model described below, using virtual birds as tools to analyse atmospheric data in an appropriate way, may help to approach this problem as well
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