Appendix S3 Detection probabilities
The matrix of presence / absence of the 71 species over the ten point counts of each
square was processed for 2003 and 2004 to estimate mean detection probabilities (1)
in each square for the global community and (2) across squares for each individual
species, using probabilistic capture-recapture models for closed animal populations
(Burnham & Overton 1979; Pollock 1982). The application of closed population
models is straightforward (Boulinier et al. 1998) because it is reasonable to think that
a sampled community is closed to local extinction and colonisation for the short
period over which the species presence-absence data are collected. Estimates of
detection probabilities were obtained by running the program COMDYN (Hines et al.
1999). The algorithm of COMDYN allows us to consider heterogeneous detection
probability among raw data (here either species within a square’s community, or
squares within individual species’ data), using the capture-recapture model M(h) and
the associated jackknife estimator (Burnham & Overton 1979). This model is the most
frequently selected model in the framework of species richness estimation when using
breeding bird survey data (Boulinier et al. 1998; Alpiza-Jara et al. 2004; Jiguet et al.
2005). Mean detection probabilities were estimated (1) for each square for the 71
species’ community in 2003 and 2004 (one mean value for the community per square
for each year), and (2) for each species across all squares in 2003 or 2004 (one mean
value per species for each year). We then compared detection probability between
years across the 653 sites for (1) and across the 71 species for (2) using paired t-tests
to evaluate whether it varied among years. We also tested the relationship between
thermal range and the difference in individual species’ detection probability between
2003 and 2004 using Pearson’s correlation coefficient. Finally, we estimated mean
detection probabilities of individual species in the hottest and coolest squares
surveyed in 2003 (using spring and summer temperature anomalies, respectively, to
identify hottest and coolest squares), and tested the relationship between thermal
range and the difference in individual species’ detection probability between hot and
cool sites, using Pearson’s correlation coefficient.
We found no variation in mean detection probabilities of the 71 species’
community for all monitored sites between 2003 and 2004 (paired t-test for sites, t652
= -0.43, P = 0.67). There was also no variation in mean detection probabilities for the
71 species between 2003 and 2004 (paired t-test for species, t70 = 0.47, P = 0.64), and
variation in mean detection probabilities in 2003 and in 2004 for the 71 species was
not correlated with the thermal range (n = 71, r = -0.02, P = 0.86). The further
comparison of 2003 mean detection probability between the hottest (with the largest
temperature anomalies in 2003) and the coldest (with the lowest temperature
anomalies in 2003) surveyed squares for species with enough available data again
revealed no significant trend between differences in detection probability (between
hottest and coolest squares in 2003) and thermal range (Pearson’s correlation
coefficients; spring temperature anomalies: n = 68, r = 0.06, P = 0.60; summer
temperature anomalies: n = 67, r = -0.10, P = 0.41).
So we found no variation in detection probabilities between 2003 and 2004, when
considering either the surveyed sites (mean detection probability of the 71 species
within the community) or the studied species (mean detection probability of
individual species across sites). Moreover, variation in detection probability of
individual species between 2003 and 2004 was not related to the thermal range of the
species concerned, and variation in detection probability of individual species
between the hottest and coolest (either in spring or summer) sites surveyed in 2003
was not related to the species’ thermal range. Therefore, we conclude that the
correlation between thermal range and response of growth rate to temperature
anomaly is not an artefact of variation in species’ detection under different climatic
conditions.
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