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Fig. 1 in Temperature-based activity estimation accurately predicts surface activity, but not microhabitat use, in the Endangered heliothermic lizard Gambelia sila

Fig. 1. Methodology used to predict morning emergence time of Gambelia sila. Emergence was predicted as the time of day immediately preceding a distinct upward slope in the lizard's T b (triangles and dotted line) based on the assumption that it would take several minutes for the radio transmitter to heat in the sun. The rising Tb was also typically associated with the departure from the burrow physical model temperatures (diamonds and long-dashed line) and the approach of the open (sun) physical model temperatures (squares and short-dashed line). In each case, the predicted time was then compared to the observed emergence time when the lizard's head first appeared outside its burrow. The average difference between observed and predicted emergence times was 11 minutes and 37 seconds.

Fig. 4 in Temperature-based activity estimation accurately predicts surface activity, but not microhabitat use, in the Endangered heliothermic lizard Gambelia sila

Fig. 4. Proportions of correctly predicted observations of microhabitat use of Gambelia sila using temperature-based activity estimation based on physical model temperatures. Lizard microhabitat use was predicted correctly most often when they were in the open, but overall microhabitat use was not accurately predicted with TBAE in this heliothermic lizard.

Fig. 3 in Temperature-based activity estimation accurately predicts surface activity, but not microhabitat use, in the Endangered heliothermic lizard Gambelia sila

Fig. 3. Temperature-based activity estimation resulted in accurate prediction of above-ground activity by Gambelia sila more often than accurate prediction of below-ground (burrow) occupation. Using air temperature (T air) was superior to using physical model temperatures when predicting below-ground occupation. For both methods, ~93% of observations predicted to be above ground were correct, whereas 62% (using T air) and 51% (using physical models) were correct for below-ground predictions.

Fig. 2 in Temperature-based activity estimation accurately predicts surface activity, but not microhabitat use, in the Endangered heliothermic lizard Gambelia sila

Fig. 2. Proportions of correct predictions using air temperature to predict surface activity versus below-ground refuge use of Gambelia sila. This method resulted in accurate predictions 64–76% of the time among the various temperature differentials shown on the x-axis. Predictions were maximized (76% correct) using the criterion that lizards are above ground when their body temperatures (T b) are at least 6 °C above the air temperature (T ).

Fig. 5 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru

Fig. 5. Comparisons of the sizes of Rhinella yanachaga individuals. (A) Differences in size of females in dry and wet seasons. (B) Differences in size of males in dry and wet seasons. (C) Differences in size between males and females. (D) Differences in the size of individuals with respect to microhabitats. The different letters indicate significant differences at p ≤ 0.05 according to the Tukey test after GLMM. Error bars represent standard errors.

Fig. 4 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru

Fig. 4. Correlations between the elevation and size of Rhinella yanachaga according to sex. The model presents correlation factors of r2 = 0.34; p = 0.01 for females and r2 = 0.003; p = 0.41 for males. The colors indicate sex (blue for males and red for females) and the shaded areas indicate the 95% confidence limits.

Fig. 2 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru

Fig. 2. Number of Rhinella yanachaga individuals per transect, T1 = 2,800–2,700 m, T2 = 2,700–2,600 m, T3 = 2,600–2,500 m, and T4 = 2,500–2,400 m, according to the elevation gradient for both sexes, in (A) dry season and (B) wet season. (C) Correlation between the abundance of Rhinella yanachaga and elevation for both sexes and seasons. The grey band indicates the 95% confidence limits.

Fig. 3 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru

Fig. 3. Numbers of individuals according to sex and length (SVL) ranges of Rhinella yanachaga in four transects, T1 = 2,800–2,700 m, T2 = 2,700–2,600 m, T3 = 2,600–2,500 m, and T4 = 2,500–2,400 m, according to the elevation gradient in the wet and dry seasons.

Fig. 1 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru

Fig. 1. (A) Map of the study area. The white circle indicates the location of the study site (San Alberto) within Yanachaga-Chemillén National Park, Oxapampa, Pasco; (B) lateral view, (C) ventral view, and (D) dorsal view of Rhinella yanachaga in life. Map by Vladimir Camel (A), photos by Shirley Huamán-Trucios (B–D).

Fig. 6 in Diversity and microhabitat use of benthic invertebrates in an urban forest stream (Southeastern Brazil)

Fig. 6. NMDS ordination (stress = 0.18) of each microhabitat type (litter, sand, and stone) sampled at the Tijuca River, located at the Tijuca Forest, Rio de Janeiro, Brazil.

Fig. 4. Rarefaction curves with extrapolations and 95 in Diversity and microhabitat use of benthic invertebrates in an urban forest stream (Southeastern Brazil)

Fig. 4. Rarefaction curves with extrapolations and 95% of confidence intervals for both the total sampling and each type of microhabitat of benthic invertebrates of Tijuca River, located at the Tijuca Forest, Rio de Janeiro, Brazil.

Fig. 5 in Diversity and microhabitat use of benthic invertebrates in an urban forest stream (Southeastern Brazil)

Fig. 5. Boxplot of the ecological descriptors calculated for each microhabitat type (litter, sand, and stone) with the one-way repeated measure ANOVA results and the Tukey pairwise post hoc test (letters). Different letters denote significant difference results (p <0.001).

Figs 1-3 in Diversity and microhabitat use of benthic invertebrates in an urban forest stream (Southeastern Brazil)

Figs 1-3. Sampled stretches of the Tijuca River, Tijuca Forest, Rio de Janeiro, Brazil: Figs 1, 2, first stretch located at 380 meters of altitude; and Fig. 3, second stretch located at 420 meters of altitude.

opencc-by-4.0Jun 2007View details →

Figure 1 in Microhabitat choice and differential use by anurans in forest streams in southeastern Brazil

Figure 1. Photograph taken at the first point (15 m) of stream 3, with the 15×21 line grid superimposed to quantify available microhabitats in three height classes at RPPN Santuário do Caraça, southeastern Brazil. Each height class encompasses five horizontal grid lines. The arrows point to the metric tape.

opencc-by-4.0Sep 2011View details →

Fig. 2 in Microhabitat use by Phalloceros harpagos Lucinda (Cyprinodontiformes: Poeciliidae) from a coastal stream from Southeast Brazil

Fig. 2. Microhabitat underwater observation. In detail substratum measurements (Photo: Rosana Mazzoni).

opencc-by-4.0Sep 2011View details →

Fig. 4 in Microhabitat use by Phalloceros harpagos Lucinda (Cyprinodontiformes: Poeciliidae) from a coastal stream from Southeast Brazil

Fig. 4. Availablity (light grey bars), use (dark grey bars) and Ivlev Index (black circles) for the six studied microhabitat descriptors affecting adult individuals of Phalloceros harpagos populations from Mato Grosso stream: (a) distance from the nearest bank; (b) total depth; (c) mesohabitat; (d) focal water velocity; (e) substratum, and (f) vegetal cover density.