Typical temperatures and distributions

isotherms

There are very many examples of plant and animal distributions that are strikingly correlated with some aspect of environmental temperature even at gross taxonomic and systematic levels (Figure 2.13). At a finer scale, the distributions of many species closely match maps of some aspect of temperature. For example, the northern limit of the distribution of wild madder plants (Rubia peregrina) is closely correlated with the position of the January 4.5 °C

Figure 2.11 (a) The El Niño-Southern Oscillation (ENSO) from 1950 to 2000 as measured by sea surface temperature anomalies (differences from the mean) in the equatorial mid-Pacific. The El Niño events (> 0.4°C above the mean) are shown in dark color, and the La Niña events (> 0.4°C below the mean) are shown in pale color. (Image from http://www.cgd.ucar.edu/cas/catalog/ climind/Nino_3_3.4_indices.html.) (b) Maps of examples of El Niño (November 1997) and La Niña (February 1999) events in terms of sea height above average levels. Warmer seas are higher; for example, a sea height 15-20 cm below average equates to a temperature anomaly of approximately 2-3°C. (Image from http://topex-www.jpl.nasa.gov/science/images/el-nino-la-nina.jpg.) (For color, see Plate 2.1, between pp. 000 and 000.)

Figure 2.11 (a) The El Niño-Southern Oscillation (ENSO) from 1950 to 2000 as measured by sea surface temperature anomalies (differences from the mean) in the equatorial mid-Pacific. The El Niño events (> 0.4°C above the mean) are shown in dark color, and the La Niña events (> 0.4°C below the mean) are shown in pale color. (Image from http://www.cgd.ucar.edu/cas/catalog/ climind/Nino_3_3.4_indices.html.) (b) Maps of examples of El Niño (November 1997) and La Niña (February 1999) events in terms of sea height above average levels. Warmer seas are higher; for example, a sea height 15-20 cm below average equates to a temperature anomaly of approximately 2-3°C. (Image from http://topex-www.jpl.nasa.gov/science/images/el-nino-la-nina.jpg.) (For color, see Plate 2.1, between pp. 000 and 000.)

Figure 2.11 (continued) (c) The North Atlantic Oscillation (NAO) from 1864 to 2003 as measured by the normalized sea-level pressure difference (Ln — Sn) between Lisbon, Portugal and Reykjavik, Iceland. (Image from http://www.cgd.ucar.edu/~ihurrell/ nao.stat.winter.html#winter.) (d) Typical winter conditions when the NAO index is positive or negative. Conditions that are more than usually warm, cold, dry or wet are indicated. (Image from http://www.ldeo.columbia.edu/NAO/.) (For color, see Plate 2.2, between pp. 000 and 000.)

Figure 2.11 (continued) (c) The North Atlantic Oscillation (NAO) from 1864 to 2003 as measured by the normalized sea-level pressure difference (Ln — Sn) between Lisbon, Portugal and Reykjavik, Iceland. (Image from http://www.cgd.ucar.edu/~ihurrell/ nao.stat.winter.html#winter.) (d) Typical winter conditions when the NAO index is positive or negative. Conditions that are more than usually warm, cold, dry or wet are indicated. (Image from http://www.ldeo.columbia.edu/NAO/.) (For color, see Plate 2.2, between pp. 000 and 000.)

Figure 2.12 (a) The abundance of 3-year-old cod, Gadus morhua, in the Barents Sea is positively correlated with the value of the North Atlantic Oscillation (NAO) index for that year. The mechanism underlying this correlation is suggested in (b-d). (b) Annual mean temperature increases with the NAO index. (c) The length of 5-month-old cod increases with annual mean temperature. (d) The abundance of cod at age 3 increases with their length at 5 months. (After Ottersen et al., 2001.)

Figure 2.12 (a) The abundance of 3-year-old cod, Gadus morhua, in the Barents Sea is positively correlated with the value of the North Atlantic Oscillation (NAO) index for that year. The mechanism underlying this correlation is suggested in (b-d). (b) Annual mean temperature increases with the NAO index. (c) The length of 5-month-old cod increases with annual mean temperature. (d) The abundance of cod at age 3 increases with their length at 5 months. (After Ottersen et al., 2001.)

isotherm (Figure 2.14a; an isotherm is a line on a map joining places that experience the same temperature - in this case a January mean of 4.5°C). However, we need to be very careful how we interpret such relationships: they can be extremely valuable in predicting where we might and might not find a particular species; they may suggest that some feature related to temperature is important in the life of the organisms; but they do not prove that temperature causes the limits to a species' distribution. The literature relevant to this and many other correlations between temperature and distribution patterns is reviewed by Hengeveld (1990), who also describes a more subtle graphical procedure. The minimum temperature of the coldest month and the maximum temperature of the hottest month are estimated for many places within and outside the range of a species. Each location is then plotted on a graph of maximum against minimum temperature, and a line is drawn that optimally discriminates between the presence and absence records (Figure 2.14b). This line is then used to define the geographic margin of the species distributions (Figure 2.14c). This may have powerful predictive value, but it still tells us nothing about the underlying forces that cause the distribution patterns.

One reason why we need to be cautious about reading too much into correlations of species distributions with maps of temperature is that the temperatures measured for constructing isotherms for a map are only rarely those that the organisms experience. In nature an organism may choose to lie in the sun or hide

Figure 2.13 The relationship between absolute minimum temperature and the number of families of flowering plants in the northern and southern hemispheres. (After Woodward, 1987, who also discusses the limitations to this sort of analysis and how the history of continental isolation may account for the odd difference between northern and southern hemispheres.)

Figure 2.13 The relationship between absolute minimum temperature and the number of families of flowering plants in the northern and southern hemispheres. (After Woodward, 1987, who also discusses the limitations to this sort of analysis and how the history of continental isolation may account for the odd difference between northern and southern hemispheres.)

in the shade and, even in a single day, may experience a baking midday sun and a freezing night. Moreover, temperature varies from place to place on a far finer scale than will usually concern a geographer, but it is the conditions in these 'microclimates' that will be crucial in determining what is habitable for a particular species. For example, the prostrate shrub Dryas octopetala is restricted to altitudes exceeding 650 m in North Wales, UK, where it is close to its southern limit. But to the north, in Sutherland in Scotland, where it is generally colder, it is found right down to sea level.

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