On the study area map we marked the major settlements connected by public roads open for cars.
All covariates were scaled and zero-centered prior to modelling. POIs – density of tourist infrastructure. When selecting covariates for the final models we ensured that the Pearson correlation …
(a, d) Estimated parameters for the wolf and lynx models, (b, e) maps of the predicted variation in their landscape use (relative density surfaces) and (c, f) fitted spatial random effects (SRE). …
(a) Estimated effects of covariates explaining the spatial variation in the parameter , which is the expected number of individuals using a given landscape grid cell (25 ha pixel) during the …
The maps show substantial variation in predicted landscape use for the five studied ungulate species (relative density surfaces). Specifically, this figure presents the spatial predictions for the …
The maps show the fitted spatial random effects (SRE) for the models of five studied ungulate species. The SRE are deviations from 0 at log-scale. The SRE captured all spatial variation not …
(a) Estimated effects of covariates explaining the variation in the parameter , which is the expected (daily) detection (trapping) rate at a single camera trap site (see the general and formal …
The pairwise spatial overlap between the studied ungulate species is presented as the Pearson correlation heatmap of their relative density surfaces predicted by the models (a) and fitted spatial …
Both variables, together with species-specific biomass raster layers, were used in the hierarchical clustering analysis. Interestingly, the lowest values of both parameters were largely associated …
(a) The spatial distribution of the five identified clusters (‘herbiscapes’) based on hierarchical clustering on the principal components analysis. (b) The distribution of identified clusters in the …
(a, b) The mean differences between the two tree height classes (saplings < 30 cm and ≥30 cm) in the proportional shares of Acer platanoides (Acer) and Carpinus betulus (Carpinus). The numbers on …
Image credit: Lisa Sánchez Aguilar
All plots follow a characteristic shape of a hollow or sigmoidal curve (Brown et al., 1995; Rocchini and Neteler, 2012) indicating a non-uniform, heterogenous distribution of all studied species.
The predicted biomass of red deer (both sexes, X axis) is shown as a share of the total biomass of the entire community of ungulates. Each dot on the plot is a 25 ha landscape pixel. In color, we …
When selecting covariates for the final models we ensured that the Pearson correlation value for all pairs of included covariates was lower than 0.7.
The five clusters were identified by assessing the inertia (i.e. change in within cluster homogeneity) gained by cutting the tree at different levels and the ecological interpretability of the …
The dark-red thick lines indicate high human activity and the light-blue thin lines indicate low human activity. For (A), (B) and (C) the color gradient from blue to red corresponds to the gradient …
In the background we plotted the raster map of wolf space use predicted by our model together with the raw camera trapping data (‘bubbles’ with trapping rates at each location). On top of it we …
Each bubble is a camera trap location and its size is proportional to the daily trapping rate (i.e. no. of individuals observed/no. of days).
Each bubble is a camera trap location and its size is proportional to the daily trapping rate (i.e. no. of individuals observed/no. of days).
Each bubble is a camera trap location and its size is proportional to the daily trapping rate (i.e. no. of individuals observed/no. of days).
Each bubble is a camera trap location and its size is proportional to the daily trapping rate (i.e. no. of individuals observed/no. of days).
Each bubble is a camera trap location and its size is proportional to the daily trapping rate (i.e. no. of individuals observed/no. of days).
Each bubble is a camera trap location and its size is proportional to the daily trapping rate (i.e. no. of individuals observed/no. of days).
Each bubble is a camera trap location and its size is proportional to the daily trapping rate (i.e. no. of individuals observed/no. of days).
Each camera location was manually tagged with a 4-level categorical label (‘Exclude’, ‘Acceptable’, ‘Good’, ‘Perfect’) describing the quality of view in front of the camera. Locations labeled with …
The covariates explain the spatial variation in the parameter , which is the expected number of individuals using a given landscape grid cell (25 ha pixel) during the sampling period (i.e. the …
The predictions are based on the model for all ungulate species using only a subset of the camera trap data covering a three month period (August - October) closely matching the period of the …
Days – the total number of trapping days (effort), Counts – the total number of individuals recorded during independent visits (events), Trate – trapping rate. Notice the dramatic differences in the …
Species | Days | Counts | Trate (daily) | Trate sd | Trate max |
---|---|---|---|---|---|
Ungulates survey (05.2012–05.2014) | |||||
Wild Boar | 9813 | 4818 | 0.49507 | 0.87881 | 10.16667 |
Red Deer | 9813 | 2025 | 0.20255 | 0.36340 | 3.90909 |
Red Deer Female | 9813 | 973 | 0.09648 | 0.20391 | 2.00000 |
Red Deer Male | 9813 | 547 | 0.05544 | 0.12867 | 1.25000 |
European Bison | 9813 | 440 | 0.04522 | 0.23212 | 4.50000 |
Roe Deer | 9813 | 194 | 0.02043 | 0.06611 | 0.54545 |
Eurasian Elk | 9813 | 82 | 0.00866 | 0.04714 | 0.66667 |
Wolf | 9813 | 51 | 0.00541 | 0.02960 | 0.36364 |
Eurasian Lynx | 9813 | 3 | 0.00027 | 0.00458 | 0.08333 |
Carnivores survey (09–10.2015) | |||||
Wolf | 3093 | 471 | 0.19129 | 0.49534 | 6.00000 |
Eurasian Lynx | 3093 | 35 | 0.01268 | 0.04997 | 0.33333 |
Roe deer | Wild boar | Red deer female | Red deer male | Moose | European bison | |
---|---|---|---|---|---|---|
Body mass | 20 | 80 | 90 | 150 | 200 | 400 |
Diet type | B | O | BG | BG | B | G |
Gut type | R | NR | R | R | R | R |
Source data tables and Python code of the analysis.
MCMC trace plots.