Table 2.

Multiple regression models of species–energy relationships that take spatial autocorrelation into account.

number of species	response	temperature	temperature2	NDVI	NDVI2	model weight	r2 (%)
189	all species	F1,2257=137.9++++	F1,2257=111.9−−−−	F1,2257=19.7++++	F1,2257=17.9−−−−	0.987	30.4
107	non-passerines	F1,2257=57.1++++	F1,2257=45.2−−−−	F1,2257=18.1++++	F1,2257=19.2−−−−	0.946	16.0
82	passerines	F1,2257=205.8++++	F1,2257=170.3−−−−	F1,2257=13.4+++	F1,2257=9.7−−	0.562	43.1
82	passerines	F1,2258=219.2++++		F1,2258=20.9++++	F1,2258=14.0−−−	0.438	38.9
141	long distance resident	F1,2257=151.6++++	F1,2257=126.3−−−−	F1,2257=26.3++++	F1,2257=24.7−−−−	0.999	28.4
48	long distance migrant	F1,2258=60.8++++	F1,2258=45.1−−−−	F1,2258=9.6++		0.839	29.2
116	partial resident	F1,2257=144.9++++	F1,2257=110.5−−−−	F1,2257=24.8++++	F1,2257=21.9−−−−	0.998	45.6
73	partial migrant	F1,2259=98.3++++	F1,2259=91.1−−−−			0.846	3.2
35	red list	F1,2257=95.0++++	F1,2257=67.6−−−−	F1,2257=20.4++++	F1,2257=17.8−−−−	0.896	53.0
35	amber list	F1,2257=110.6++++	F1,2257=169.7−−−−	F1,2257=23.2++++	F1,2257=22.7−−−−	0.953	15.1
119	green list	F1,2257=115.3++++	F1,2257=89.6−−−−	F1,2257=14.9+++	F1,2257=13.3−−−	0.857	33.2
47	1st population quartile	F1,2257=336.0++++	F1,2257=262.4−−−−	F1,2257=16.8++++	F1,2257=12.6−−−	0.760	62.2
47	1st population quartile	F1,2258=340.7++++	F1,2258=265.7−−−−	F1,2258=26.1++++		0.241	58.2
47	2nd population quartile	F1,2258=132.9++++	F1,2258=118.8−−−−	F1,2258=5.6+		0.472	15.4
47	2nd population quartile	F1,2259=156.8++++	F1,2259=139.0−−−−			0.316	14.6
47	2nd population quartile	F1,2257=130.1++++	F1,2257=116.5−−−−	F1,2257=9.4+++	F1,2257=8.0−−	0.212	18.4
47	3rd population quartile	F1,2258=39.9++++		F1,2258=18.7+++	F1,2258=19.9−−−	0.782	8.3
48	4th population quartile	F1,2259=4.9+		F1,2259=37.0−−−−		0.391	7.4
48	4th population quartile	F1,2257=45.5++++				0.290	0.7
48	4th population quartile	F1,2258=6.2+	F1,2258=4.8−	F1,2258=39.2−−−−		0.237	7.6
47	1st mass quartile	F1,2258=127.2++++	F1,2258=98.5−−−−	F1,2258=24.4++++		0.599	39.3
47	1st mass quartile	F1,2257=123.2++++	F1,2257=95.1−−−−	F1,2257=12.3+++	F1,2257=9.0−−	0.401	40.6
47	2nd mass quartile	F1,2259=165.1++++	F1,2259=144.6−−−−			0.746	16.8
48	3rd mass quartile	F1,2259=63.6++++	F1,2259=42.72−−−−			0.660	35.2
48	3rd mass quartile	F1,2257=53.3++++	F1,2257=35.3−−−−	F1,2257=13.2+++	F1,2257=12.4−−−	0.231	42.5
47	4th mass quartile	F1,2259=86.6++++	F1,2259=82.0−−−−			0.508	9.6
47	4th mass quartile	F1,2257=84.1++++	F1,2257=80.7−−−−	F1,2257=12.6+++	F1,2257=13.8−−−	0.416	72.7
28	farmland	F1,2258=93.3++++	F1,2258=52.1−−−−	F1,2258=9.3++		0.841	69.3
49	woodland	F1,2258=175.8++++	F1,2258=145.7−−−−	F1,2258=33.9++++		0.525	39.0
49	woodland	F1,2257=168.3++++	F1,2257=139.0−−−−	F1,2257=13.7+++	F1,2257=9.4−−	0.475	40.8
112	other habitats	F1,2257=63.3++++	F1,2257=60.7−−−−	F1,2257=9.8++	F1,2257=11.5−−−	0.757	10.8
43	niche breadth (broad)	F1,2258=141.2++++	F1,2258=76.3−−−−	F1,2258=20.0++++		0.954	76.7
42	niche breadth (narrow)	F1,2257=245.5++++	F1,2257=244.9−−−−	F1,2257=15.9+++	F1,2257=14.5−−	0.743	27.2
43	niche position (low)	F1,2258=288.8++++	F1,2258=218.8−−−−	F1,2258=20.8++++		0.785	58.7
43	niche position (low)	F1,2257=284.8++++	F1,2257=215.9−−−−	F1,2257=10.7++++	F1,2257=7.7−−−−	0.214	62.3
42	niche position (high)	F1,2258=148.0++++	F1,2258=117.1−−−−	F1,2258=15.5++++		0.869	40.4
16	herbivores	F1,2257=64.7++++	F1,2257=40.8−−−−	F1,2257=27.5++++	F1,2257=26.7−−−−	0.958	52.1
64	Omnivores	F1,2257=102.7++++	F1,2257=73.3−−−−	F1,2257=27.4++++	F1,2257=24.2−−−−	0.998	49.7
81	Predators—inverts	F1,2259=148.4++++	F1,2259=126.4−−−−			0.770	13.9
28	Predators—verts	F1,2259=76.0++++	F1,2259=77.9−−−−			0.968	8.2

Model fit was assessed using the Akaike Information Criteria (AIC), smaller values indicate a better fit. The model weight is the probability that the model provides the best fit to the data; we present all models with weights greater than 0.2. Explanatory power is indicated by the r² values from general linear models. Models use either summer or annual measures of temperature and NDVI according to which measure provided the best fit to the data in tests that used a single energy metric as a predictor (see table 1). ++++p<0.0001, +++p<0.001, ++p<0.01, +p<0.05; Negative effects −−−−p<0.0001, −−−p<0.001, −−p< 0.01, − p<0.05.