Figure SM-1.2. Duration of time-series (years) of observed changes in natural and managed systems used in statistical analysis of synthesis assessment in Section 1.4.

Table SM-1.6. Summary of observed impacts of temperature-related regional climate change in chapter synthesis assessment in Section 1.4.


Changes in glaciers, lake and river ice break-up, snow cover and permafrost active layer


Changes in spring peak discharge and lake levels

Coastal processes

Changes in storminess and coastal vegetation, shoreline retreat, coastal erosion

Marine, freshwater and terrestrial biological systems

Changes in phenology, community composition, productivity and synchrony; shifts in latitude/altitude ranges and breeding sites; genetic adaptation

Table SM-1.7. Comparison of significant observed changes in physical and biological systems with regional temperature changes at the global scale in chapter synthesis assessment in Section 1.4.

Temperature cells

Cells with significant observed change consistent with warming*

Cells with significant observed change not consistent with warming

Cells with significant observed change consistent with warming**

Significant warming

49% (2.5%)

9% (2.5%)

56% (5%)


31% (22.5%)

4% (22.5%)

36% (45%)


6% (22.5%)

0% (22.5%)

6% (45%)

Significant cooling

2% (2.5%)

0% (2.5%)

2% (5%)

Chi-squared value (significance level)

350 (<<1 %)

104 (<<1%)

* assuming three-fold null hypothesis; ** assuming two-fold null hypothesis; see text for full explanation

Note: Fraction of 5°x5° cells with significant observed changes in systems (from studies considered in this chapter) and temperature changes (over 1970-2004 from HadCRUT3 - Brohan et al., 2006) in different categories (significant warming, warming, cooling, significant cooling). Expected values shown in parentheses are for the null hypotheses:

(i) significant observed changes in systems are equally likely in each direction,

(ii) temperature trends are due to natural climate variations and are normally distributed,

(iii) there is no relationship between significant changes in systems and co-located warming.

The right-hand column repeats the analysis without assuming point (i) above and only considers significant observed changes in systems that are consistent with warming, in order to avoid the possible effects of publication or research biases.

The significance levels for the chi-squared values relative to the expected distribution are obtained by comparing the locations of the significant observed system changes with regional temperature trends over 35-year periods due to natural climate variability from long control simulations with 5 different coupled climate models; 192 independent 35-year periods were sampled from the control runs, allowing estimation of chi-squared values at about the 1% significance level due to natural variability.

The analysis was repeated using a second global gridded temperature dataset (GHCN-ERSST) and there were no significant differences in the results.

Footnote 1, continued from below Box SM.1 on next page. At each location, all of which are in the Northern Hemisphere, the changing trait is compared with modelled temperatures driven by: (a) Natural forcings (pink bars), (b) anthropogenic (i.e., human) forcings (orange bars), and (c) combined natural and anthropogenic forcings (yellow bars). In addition, on each panel the frequencies of the correlation coefficients between the actual temperatures recorded during each study and changes in the traits of 83 species, the only ones of the 145 with reported local-temperature trends, are shown (dark blue bars). On average the number of years species were examined is about 28 with average starting and ending years of 1960 to 1998. Note that the agreement: a) between the natural and actual plots is weaker (K=60.16, P>0.05) than b) between the anthropogenic and actual (K=35.15, P>0.05), which in turn is weaker than c) the agreement between combined and actual (K=3.65, P<0.01). Taken together, these plots show that a measurable portion of the warming regional temperatures to which species are reacting can be attributed to humans, therefore showing joint attribution (see Chapter 1).

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