Table 1.

Estimated regression coefficients describing the differences in the probability of an observation event in April being near wetland habitat among years. Coefficients are from the single logistic regression model fitted to data from each of the four political units separately. These models were parameterized so that the April 2020 proportion of observations near any wetlands is the intercept/reference value, and the coefficients for all earlier years represent deviations from the 2020 proportions. Thus, positive values for regression coefficients for the years prior to 2020 indicate that the proportion near wetlands were higher in these years than in 2020. Coefficients and standard errors in bold font indicate coefficients for which the 95% confidence intervals did not overlap with zero, indicating statistically reliable estimates. The final column, presenting the estimated proportions of observation events made near wetlands, were calculated based only on the fixed effect in the model (i.e. setting the random effect coefficient to zero).

Region	Predictor	Coefficient	SE	Proportion near wetlands
Spain	Intercept (2020)	−3.74	0.31	0.0232
	Year (2017)	1.29	0.06	0.0796
	Year (2018)	1.09	0.05	0.0660
	Year (2019)	1.04	0.05	0.0627
Portugal	Intercept (2020)	−3.57	0.43	0.0274
	Year (2016)	0.43	0.09	0.0414
	Year (2017)	0.62	0.09	0.0497
	Year (2018)	0.44	0.08	0.0418
	Year (2019)	0.83	0.08	0.0610
California	Intercept (2020)	−3.46	0.31	0.0305
	Year (2016)	0.38	0.03	0.0440
	Year (2017)	0.44	0.03	0.0468
	Year (2018)	0.27	0.03	0.0396
	Year (2019)	0.21	0.02	0.0374
New York	Intercept (2020)	−1.97	0.37	0.123
	Year (2016)	−0.005	0.02	0.122
	Year (2017)	0.07	0.02	0.131
	Year (2018)	0.04	0.02	0.127
	Year (2019)	0.07	0.02	0.130