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Fig 1.

Examples of operating malaise traps in protected areas in western Germany, in habitat cluster 1 (A) and cluster 2 (B) (see Materials and methods).

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Table 1.

Overview of malaise-trap samples sizes.

For each year, the number of locations sampled, the number of location re-sampled, total number of samples, as well as mean and standard deviation of exposure time at the trap locations (in days) are presented.

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Table 2.

Overview of covariates included in each of the seven models.

The year covariate yields the annual trend coefficient.

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Table 2 Expand

Table 3.

Results for 7 models ranked by Deviance Information Criterion (DIC).

For each model, the number of parameters, the Deviance Information Criterion, the effective number of parameters (pD), calculated R2 and difference in DIC units between each model and the model with lowest ΔDIC. See Table 2 for covariates included in each model.

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Table 4.

Posterior parameter estimates of the final mixed effects model of daily insect biomass.

For each included variable, the corresponding coefficient mean, standard deviation and 95% credible intervals are given. P-values were calculated empirically based on posterior distributions of coefficients.

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Fig 2.

Temporal distribution of insect biomass.

(A) Boxplots depict the distribution of insect biomass (gram per day) pooled over all traps and catches in each year (n = 1503). Based on our final model, the grey line depicts the fitted mean (+95% posterior credible intervals) taking into account weather, landscape and habitat effects. The black line depicts the mean estimated trend as estimated with our basic model. (B) Seasonal distribution of insect biomass showing that highest insect biomass catches in mid summer show most severe declines. Color gradient in both panels range from 1989 (blue) to 2016 (orange).

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Fig 3.

Seasonal decline and phenology.

(A) Seasonal decline of mean daily insect biomass as estimated by independent month specific log-linear regressions (black bars), and our basic mixed effects model with interaction between annual rate of change and a quadratic trend for day number in season. (B), Seasonal phenology of insect biomass (seasonal quantiles of biomass at 5% intervals) across all locations revealing substantial annual variation in peak biomass (solid line) but no direction trend, suggesting no phenological changes have occurred with respect to temporal distribution of insect biomass.

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Fig 4.

Temporal distribution of insect biomass at selected locations.

(A) Daily biomass (mean ±1 se) across 26 locations sampled in multiple years (see S4 Fig for seasonal distributions). (B) Distribution of mean annual rate of decline as estimated based on plot specific log-linear models (annual trend coefficient = −0.053, sd = 0.002, i.e. 5.2% annual decline).

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Fig 5.

Marginal effects of temporal changes in considered covariates on insect biomass.

Each bar represents the rate of change in total insect biomass, as the combined effect of the relevant coefficient (Table 4) and the temporal development of each covariate independently (S2 and S3 Figs).

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