Spatially varying selection shapes life history clines among populations of Drosophila melanogaster from sub-Saharan Africa

Abstract

Clines in life history traits, presumably driven by spatially varying selection, are widespread. Major latitudinal clines have been observed, for example, in Drosophila melanogaster, an ancestrally tropical insect from Africa that has colonized temperate habitats on multiple continents. Yet, how geographic factors other than latitude, such as altitude or longitude, affect life history in this species remains poorly understood. Moreover, most previous work has been performed on derived European, American and Australian populations, but whether life history also varies predictably with geography in the ancestral Afro-tropical range has not been investigated systematically. Here, we have examined life history variation among populations of D. melanogaster from sub-Saharan Africa. Viability and reproductive diapause did not vary with geography, but body size increased with altitude, latitude and longitude. Early fecundity covaried positively with altitude and latitude, whereas lifespan showed the opposite trend. Examination of genetic variance-covariance matrices revealed geographic differentiation also in trade-off structure, and QST -FST analysis showed that life history differentiation among populations is likely shaped by selection. Together, our results suggest that geographic and/or climatic factors drive adaptive phenotypic differentiation among ancestral African populations and confirm the widely held notion that latitude and altitude represent parallel gradients.

Keywords: adaptation; climate; clines; geography; life history; spatially varying selection.

Figure 1

Sampling locations of sub-Saharan African populations examined in this study. Open symbols: low-altitude populations (17–900 m AMSL); filled symbols: high-altitude populations (1661–3070 m AMSL). Dashed horizontal line: equator (0° latitude); vertical dashed line: meridian (0° longitude).

Figure 2

Clinal variation in female thorax length (mm), a major proxy of body size. The plots show regression of size against (A) altitude, (B) latitude, and (C) longitude. The grey line represents the regression line for each geographic factor, obtained from the multiple regression mixed model.

Figure 3

Clinal variation for two different estimators of early fecundity. Upper panel (A–C): early daily per capita fecundity between days 1–5. Lower panel (D–F): early daily per capita fecundity between days 1–10. The plots show regression of fecundity against (A, D) altitude, (B, E) latitude, and (C, F) longitude. The grey line represents the regression line for each geographic factor as obtained from the multiple regression mixed model.

Figure 4

Clinal variation in adult mortality. The figure shows the range risk ratio between the lowest and highest value of each of the geographic factors (altitude, latitude, longitude) as estimated from Cox regression. Risk ratios < 1 indicate a decrease in the hazard ratio with increasing values of the geographic factor (i.e., a negative slope), whereas risk ratios > 1 correspond to an increase in the hazard ratio (i.e., a positive slope). Error bars represent 95% confidence intervals.