Table 5 Open in new tab Predictive...

Location	Season	Within location	Across location
Balandran.FR	1997	14	12	0.86	0.90	0.29	63	61	0.67	0.70	0.13
1999	10	0.88	0.91	0.32	50	0.76	0.79	0.14
Bourran.FR	2014	38	37	0.81	0.89	0.16	193	187	0.59	0.65	0.07
2015	38	0.84	0.90	0.16	192	0.64	0.68	0.07
Forli.IT	2014	11	10	0.81	0.88	0.32	56	50	0.84	0.91	0.14
2015	11	0.79	0.86	0.30	55	0.86	0.94	0.13
Prosser.US	2011	76	46	0.79	1.02	0.15	384	231	0.43	0.55	0.07
2012	71	0.73	0.95	0.12	360	0.44	0.57	0.05

Location	Season	Within location	Across location
Balandran.FR	1997	14	12	0.86	0.90	0.29	63	61	0.67	0.70	0.13
1999	10	0.88	0.91	0.32	50	0.76	0.79	0.14
Bourran.FR	2014	38	37	0.81	0.89	0.16	193	187	0.59	0.65	0.07
2015	38	0.84	0.90	0.16	192	0.64	0.68	0.07
Forli.IT	2014	11	10	0.81	0.88	0.32	56	50	0.84	0.91	0.14
2015	11	0.79	0.86	0.30	55	0.86	0.94	0.13
Prosser.US	2011	76	46	0.79	1.02	0.15	384	231	0.43	0.55	0.07
2012	71	0.73	0.95	0.12	360	0.44	0.57	0.05

Table 5

Predictive ability, prediction accuracy and standard error of prediction accuracy by location and season estimated from within-location and across-location validation

Location	Season	Within location					Across location
Location	Season	nG × L	nG × LS	PA	PACC	se.PACC	nG × L	nG × LS	PA	PACC	se.PACC
Balandran.FR	1997	14	12	0.86	0.90	0.29	63	61	0.67	0.70	0.13
Balandran.FR	1999	14	10	0.88	0.91	0.32	63	50	0.76	0.79	0.14
Bourran.FR	2014	38	37	0.81	0.89	0.16	193	187	0.59	0.65	0.07
Bourran.FR	2015	38	38	0.84	0.90	0.16	193	192	0.64	0.68	0.07
Forli.IT	2014	11	10	0.81	0.88	0.32	56	50	0.84	0.91	0.14
Forli.IT	2015	11	11	0.79	0.86	0.30	56	55	0.86	0.94	0.13
Prosser.US	2011	76	46	0.79	1.02	0.15	384	231	0.43	0.55	0.07
Prosser.US	2012	76	71	0.73	0.95	0.12	384	360	0.44	0.57	0.05

Location	Season	Within location					Across location
Location	Season	nG × L	nG × LS	PA	PACC	se.PACC	nG × L	nG × LS	PA	PACC	se.PACC
Balandran.FR	1997	14	12	0.86	0.90	0.29	63	61	0.67	0.70	0.13
Balandran.FR	1999	14	10	0.88	0.91	0.32	63	50	0.76	0.79	0.14
Bourran.FR	2014	38	37	0.81	0.89	0.16	193	187	0.59	0.65	0.07
Bourran.FR	2015	38	38	0.84	0.90	0.16	193	192	0.64	0.68	0.07
Forli.IT	2014	11	10	0.81	0.88	0.32	56	50	0.84	0.91	0.14
Forli.IT	2015	11	11	0.79	0.86	0.30	56	55	0.86	0.94	0.13
Prosser.US	2011	76	46	0.79	1.02	0.15	384	231	0.43	0.55	0.07
Prosser.US	2012	76	71	0.73	0.95	0.12	384	360	0.44	0.57	0.05

Also shown is the average number of individuals in each validation population per location (nG × L) and per location-by-season (nG × LS) for each validation approach

PA predictive ability, PACC prediction accuracy, se.PACC standard error of prediction accuracy

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