| Literature DB >> 25567732 |
George W Gilchrist1, Lisa M Jeffers2, Brianna West3, Donna G Folk4, Jeremy Suess5, Raymond B Huey6.
Abstract
As invading species expand, they eventually encounter physical and biotic stressors that limit their spread. We examine latitudinal and climatic variation in physiological tolerance in one native and two invading populations of Drosophila subobscura. These flies are native to the Palearctic region, but invaded both South and North America around 1980 and spread rapidly across 15° of latitude on each continent. Invading flies rapidly evolved latitudinal clines in chromosome inversion frequencies and in wing size that parallel those of native populations in the Old World. Here we investigate whether flies on all three continents have evolved parallel clines in desiccation and starvation tolerance, such that flies in low-latitude regions (hot, dry) might have increased stress resistance. Starvation tolerance does not vary with latitude or climate on any continent. In contrast, desiccation tolerance varies clinally with latitude on all three continents, although not in parallel. In North American and Europe, desiccation tolerance is inversely related to latitude, as expected. But in South America, desiccation tolerance increases with latitude and is greatest in relatively cool and wet areas. Differences among continents in latitudinal patterns of interspecific-competition potentially influence clinal selection for physiological resistance, but no simple pattern is evident on these continents.Entities:
Keywords: cline; desiccation tolerance; invasive species; physiological tolerance; rapid evolution; starvation tolerance; stress resistance
Year: 2008 PMID: 25567732 PMCID: PMC3352378 DOI: 10.1111/j.1752-4571.2008.00040.x
Source DB: PubMed Journal: Evol Appl ISSN: 1752-4571 Impact factor: 5.183
Figure 1Maps of study populations aligned at 40° latitude, with South America inverted such that high-latitude populations are all at the top of the figure.
Regression slopes of ln time of death on ln wet mass for female and male Drosophila subosbscura from ancestral European and invasive South American populations.
| Sex | Continent | Location | Latitude | Slope | SE | |||
|---|---|---|---|---|---|---|---|---|
| Female | Europe | |||||||
| Dijon | 47.35 | 21 | 0.91 | 0.451 | 2.02 | 0.0447 | ||
| Arhus | 56.15 | 21 | 0.26 | 0.355 | 0.73 | 0.4648 | ||
| South America | ||||||||
| Chilan | 36.62 | 19 | 0.85 | 0.587 | 1.45 | 0.1486 | ||
| Coyhaique | 45.58 | 21 | 0.56 | 0.483 | 1.15 | 0.2501 | ||
| Male | Europe | |||||||
| Dijon | 47.35 | 19 | 0.41 | 0.878 | 0.46 | 0.6435 | ||
| South America | ||||||||
| Chilan | 36.62 | 21 | 0.61 | 0.511 | 1.19 | 0.2374 | ||
Significant results are indicated in bold.
Figure 2Geographic variation in (A) summer precipitation and (B) aridity index for sites in Europe (circles), South America (downward triangles) and North America (upward triangles).
Figure 3Clinal variation in the LT50 of desiccation time across latitudes for females (solid symbols) and males (open symbols) from Europe, South and North America. Regression lines are shown with ±1 SE curves.
Figure 4Variation in desiccation tolerance as a function of the aridity index for females and males from Europe, South and North America. Regression lines are shown with ±1 SE curves.
Figure 5Variation in mean desiccation tolerance as a function of mean mass for males and females from populations in Europe, South and North America. Regression lines are shown with ±1 SE curves.
Figure 6Geographic variation in starvation tolerance for females and males from Europe, South and North America. Regression lines are shown with ±1 SE curves.
| Population | Latitude | Longitude | Altitude |
|---|---|---|---|
| Århus, DK | 56.15 | 10.22 | 0 |
| Leiden, ND | 52.15 | 4.50 | −1 |
| Lille, FR | 50.63 | 3.07 | 24 |
| Gif-sur-Yvette, FR | 48.73 | 2.13 | 127 |
| Dijon, FR | 47.35 | 5.02 | 235 |
| Lyon, FR | 45.52 | 4.83 | 260 |
| Monpellier, FR | 43.63 | 3.88 | 18 |
| Barcelona, SP | 41.42 | 2.18 | 0 |
| Valencia, SP | 39.43 | −0.37 | 7 |
| Malaga, SP | 36.75 | −4.42 | 0 |
| Port Hardy, BC | 50.70 | −127.42 | 24 |
| Peachland, BC | 49.77 | −119.73 | 342 |
| Bellingham, WA | 48.74 | −122.47 | 30 |
| Centralia, WA | 46.66 | −122.97 | 58 |
| Salem, OR | 44.92 | −123.02 | 47 |
| Medford, OR | 42.34 | −122.85 | 117 |
| Eureka, CA | 40.80 | −124.16 | 13 |
| Redding, CA | 40.57 | −122.36 | 170 |
| Davis, CA | 38.55 | −121.74 | 15 |
| Gilroy, CA | 37.01 | −121.58 | 61 |
| Atascadero, CA | 35.49 | −120.69 | 268 |
| Coyhaique, CH | 45.58 | −72.07 | 302 |
| Castro, CH | 42.50 | −73.77 | 0 |
| Puerto_Montt, CH | 41.47 | −72.94 | 0 |
| Valdivia, CH | 39.77 | −73.23 | 4 |
| Laja, CH | 37.17 | −72.70 | 49 |
| Chillan, CH | 36.62 | −72.12 | 129 |
| Curico, CH | 34.92 | −71.23 | 214 |
| Santiago, CH | 33.50 | −70.67 | 521 |
| Illapel, CH | 32.00 | −71.17 | 388 |
| La Serena, CH | 29.92 | −71.25 | 28 |