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Table 3 — Likelihood Ratio Test for the generalized linear model to explain the bat passes/hour/ species in an elevation gradient in a tropical forest in Costa Rica using as predictor period (months), elevation and temperature. The significance of the effects are represented with ** for pp <0.01 and *** for p<0.001.

Table 3 — Likelihood Ratio Test for the generalized linear model to explain the bat passes/hour/ species in an elevation gradient in a tropical forest in Costa Rica using as predictor period (months), elevation and temperature. The significance of the effects are represented with ** for pp <0.01 and *** for p<0.001.

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Activity patterns by species 960>1160>1360>760>1560m; q=1: 1360>1160>960>1560>760 m and q=2: 1160>1360>1560>960>760 m (Fig. S3). For coverage val- ues higher than 40% the nonoverlapping of the 95% confidence inter- vals for site 4 (960 m) and site 5 (760 m) imply that the diversities of order q=0 (species richness) and q=2 respectively, are significantly dif- ferent.
Activity patterns by species 960>1160>1360>760>1560m; q=1: 1360>1160>960>1560>760 m and q=2: 1160>1360>1560>960>760 m (Fig. S3). For coverage val- ues higher than 40% the nonoverlapping of the 95% confidence inter- vals for site 4 (960 m) and site 5 (760 m) imply that the diversities of order q=0 (species richness) and q=2 respectively, are significantly dif- ferent.
Figure 1— Bat passes / hour for each site (elevation) and month analysed. The dotted line represents the mean of bat passes / hour for each month
Figure 1— Bat passes / hour for each site (elevation) and month analysed. The dotted line represents the mean of bat passes / hour for each month
Table 4 — Likelihood ratio tests for the generalized linear models with negative binomial distribution to explain the bat passes/hour for each species with more than 500 records. The models were constructed using the effect of period (months), elevations and tem- perature. Models were tested using step AIC (Akaike Information Cirterion) and variables temoved when the model was improved. Variables removed are marked with NI (not in- cluded). The significance of the effects are represented with * for p<0.05, ** for p<0.01 and *** for p<0.001. along an elevational gradient in a Neotropical rainforest, using exclus- ively acoustic methods.
Table 4 — Likelihood ratio tests for the generalized linear models with negative binomial distribution to explain the bat passes/hour for each species with more than 500 records. The models were constructed using the effect of period (months), elevations and tem- perature. Models were tested using step AIC (Akaike Information Cirterion) and variables temoved when the model was improved. Variables removed are marked with NI (not in- cluded). The significance of the effects are represented with * for p<0.05, ** for p<0.01 and *** for p<0.001. along an elevational gradient in a Neotropical rainforest, using exclus- ively acoustic methods.
Figure 2 — Predicted values of bat passes / hour for each period (month) (A), elevation (B) and temperature (C) according to the generalized linear model. In A and B, dots represent the mean expected for each group and whiskers the standard error. Letters represent groups which are different between them (p<0.05). In C the line represents the fitted line and the gray shadow represents the standard error.
Figure 2 — Predicted values of bat passes / hour for each period (month) (A), elevation (B) and temperature (C) according to the generalized linear model. In A and B, dots represent the mean expected for each group and whiskers the standard error. Letters represent groups which are different between them (p<0.05). In C the line represents the fitted line and the gray shadow represents the standard error.
Figure 3 — Mean and standard error of the bat passes / hour for the six bat species in an elevation gradient of tropical forest in Costa Rica during four months.
Figure 3 — Mean and standard error of the bat passes / hour for the six bat species in an elevation gradient of tropical forest in Costa Rica during four months.
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