Why Some Birds Migrate (And Others Don’t)

A common swift (Apus apus) flying over Barcelona, Spain. This species is a long-distance migrant, flying annually from southern Africa to northern and central Europe to breed.
(Credit:
pau.artigas / CC-BY-SA 2.0)

Identifying global biodiversity patterns

Migration is mostly about energy optimisation

Fig. 1 | Model description. a, The model is built from the following three main components: species’ energetic costs (a function of the location of breeding and non breeding ranges, comprising thermoregulation, reproduction and migration costs); energy supply (derived from the NDVI, and variable across space and seasons); and 1,000 simulated range options (the same size as the average bird seasonal range size). Integrating these three components, the model is applied through a sequence of simulation steps whereby a virtual world with the same geography and seasonality as Earth is progressively filled with virtual species. b, At the start of the simulation (T0), the virtual world is empty of bird species (R = 0) and the energy available is equal to the energy supply (EA = ES). In each simulation step (Ti; sub-steps 1 to 4) a new virtual species is added to the virtual world, selected among 1,040,000 candidate species (each being a pair of a breeding and a non-breeding range options) by being the most energy-efficient distribution (lowest ratio between energetic costs and the energy available remaining given the n species already present EA = ES — nEC). As this new species is added (R = n + 1), the energy available. EA is further depleted in the corresponding breeding and non-breeding ranges. The simulation ends (Tend) when the virtual world is nearly saturated with simulated species (EA ≈ 0 in at least one season). The different size shading of the bird shadows indicate that the corresponding energetic costs (see top-left panel of the figure) have different values for different candidate distributions. The grey shading indicates that the two maps within it represent the state of the system at a given step. The purple shading highlights that the explanation on the right-hand side represents what happens during one simulation step.
(doi:
10.1038/s41559–018–0556–9)

Energy optimisation model accurately predicts five observed real-world patterns

Fig. 2 | contrast between empirical patterns in the global spatial distribution of terrestrial birds across seasons and the same patterns simulated through the overall best-fit model. a–d, Richness in breeding migrants. e–h, Richness in non-breeding migrants. i–l, Richness in residents. m–p, Seasonal difference in richness. q–t, Proportion of migrants. Latitudinal trends (c,g,k,o,s) were obtained using Nadaraya–Watson kernel regression estimates (using the ksmooth function from the stats package in R). In the scatterplots of the relationship between the empirical and simulated patterns (d,h,l,p,t), goodness-of-fit was computed using the sum of squared residuals from the 1:1 line (in red). In r, land hexagons with zero-simulated species (for which the proportion of migrants could not be calculated) are shaded in grey. A total of 7,783 virtual species were simulated.
(doi:
10.1038/s41559–018–0556–9)

Species are globally distributed in the most energy-efficient way

Canada geese (Branta canadensis) flying in a V-shaped formation. Although Canada geese are a migratory species, some populations do not migrate at all, instead remaining close to parks and golf courses year-round, where there is abundant food and water.
(Credit:
John Benson / Creative Commons Attribution 2.0 Generic license.)

Source:

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
𝐆𝐫𝐫𝐥𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭, scientist & writer

𝐆𝐫𝐫𝐥𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭, scientist & writer

PhD evolutionary ecology/ornithology. Psittacophile. scicomm Forbes, previously Guardian. always Ravenclaw. discarded scientist & writer, now an angry house elf